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Zou D, Cai Y, Jin M, Zhang M, Liu Y, Chen S, Yang S, Zhang H, Zhu X, Huang C, Zhu Y, Miao X, Wei Y, Yang X, Tian J. A genetic variant in the immune-related gene ERAP1 affects colorectal cancer prognosis. Chin Med J (Engl) 2024; 137:431-440. [PMID: 37690994 PMCID: PMC10876254 DOI: 10.1097/cm9.0000000000002845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Indexed: 09/12/2023] Open
Abstract
BACKGROUND Findings on the association of genetic factors and colorectal cancer (CRC) survival are limited and inconsistent, and revealing the mechanism underlying their prognostic roles is of great importance. This study aimed to explore the relationship between functional genetic variations and the prognosis of CRC and further reveal the possible mechanism. METHODS We first systematically performed expression quantitative trait locus (eQTL) analysis using The Cancer Genome Atlas (TCGA) dataset. Then, the Kaplan-Meier analysis was used to filter out the survival-related eQTL target genes of CRC patients in two public datasets (TCGA and GSE39582 dataset from the Gene Expression Omnibus database). The seven most potentially functional eQTL single nucleotide polymorphisms (SNPs) associated with six survival-related eQTL target genes were genotyped in 907 Chinese CRC patients with clinical prognosis data. The regulatory mechanism of the survival-related SNP was further confirmed by functional experiments. RESULTS The rs71630754 regulating the expression of endoplasmic reticulum aminopeptidase 1 ( ERAP1 ) was significantly associated with the prognosis of CRC (additive model, hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.08-1.88, P = 0.012). The results of dual-luciferase reporter assay and electrophoretic mobility shift assay showed that the A allele of the rs71630754 could increase the binding of transcription factor 3 (TCF3) and subsequently reduce the expression of ERAP1 . The results of bioinformatic analysis showed that lower expression of ERAP1 could affect the tumor immune microenvironment and was significantly associated with severe survival outcomes. CONCLUSION The rs71630754 could influence the prognosis of CRC patients by regulating the expression of the immune-related gene ERAP1 . TRIAL REGISTRATION No. NCT00454519 ( https://clinicaltrials.gov/ ).
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Affiliation(s)
- Danyi Zou
- Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Meng Jin
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Shuhui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Heng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Chaoqun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei 430071, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei 430071, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China
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Cai Y, Hong C, Han J, Fan L, Xiao X, Xiao J, Wei Y, Zhu Y, Tian J, Zhu X, Jin M, Miao X. Healthy dietary patterns, genetic risk, and gastrointestinal cancer incident risk: a large-scale prospective cohort study. Am J Clin Nutr 2024; 119:406-416. [PMID: 38042409 DOI: 10.1016/j.ajcnut.2023.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 11/19/2023] [Accepted: 11/28/2023] [Indexed: 12/04/2023] Open
Abstract
BACKGROUND Dietary patterns have been associated with several cancers, especially gastrointestinal cancer (GIC). However, whether a healthy dietary pattern could modify the risk of GIC among people with different genetic backgrounds is not clear. OBJECTIVE The objective of the study was to investigate how dietary patterns and genetic susceptibility contribute to the risk of GIC independently and jointly. METHODS This large-scale prospective cohort study included 105,463 participants in UK Biobank who were aged 40-72 y and cancer-free at baseline. Dietary intake (Oxford WebQ) was used to calculate dietary pattern scores including dietary approach to stop hypertension (DASH) score and healthful plant-based diet index (hPDI). Genetic risk was quantified by a polygenic risk score (PRS) comprising 129 known GIC-associated loci. Cox proportional hazards regression was performed to estimate the associations of dietary patterns and PRS with GIC incidence after adjusting for potential confounders. RESULTS Over a median follow-up of 11.70 y, 1,661 participants were diagnosed with GIC. DASH and hPDI were associated with 20% and 36% reductions, respectively, in GIC risk. Low PRS was associated with a 30 % decrease in GIC risk (HR: 0.70; 95% CI: 0.62, 0.79). Participants with healthy dietary scores at high-genetic risk had a lower GIC risk with HR of 0.77 (95% CI: 0.60, 0.98) for DASH and 0.66 (95% CI: 0.52, 0.84) for hPDI than those with unhealthy dietary score. Participants with both high-dietary score and low-genetic risk showed the lowest risk of GIC, with HR of 0.58 (95% CI: 0.45, 0.75) for DASH and 0.45 (95% CI: 0.34, 0.58) for hPDI. CONCLUSIONS Adherence to DASH and hPDI were associated with a lower risk of some gastrointestinal cancers, and these 2 dietary patterns may partly compensate for genetic predispositions to cancer. Our results advance the development of precision medicine strategies that consider both dietary patterns and genetics to improve gastrointestinal health.
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Affiliation(s)
- Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Canlin Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei, China
| | - Jinxin Han
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei, China
| | - Xinyu Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei, China
| | - Jun Xiao
- Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei, China.
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital, Wuhan University, Wuhan, Hubei, China.
| | - Meng Jin
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei, China.
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Zhang M, Wang X, Yang N, Zhu X, Lu Z, Cai Y, Li B, Zhu Y, Li X, Wei Y, Zhang S, Tian J, Miao X. Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks. Sci China Life Sci 2024; 67:132-148. [PMID: 37747674 DOI: 10.1007/s11427-023-2439-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/26/2023] [Indexed: 09/26/2023]
Abstract
Genome-wide association studies (GWASs) have identified over 140 colorectal cancer (CRC)-associated loci; however, target genes at the majority of loci and underlying molecular mechanisms are poorly understood. Here, we utilized a Bayesian approach, integrative risk gene selector (iRIGS), to prioritize risk genes at CRC GWAS loci by integrating multi-omics data. As a result, a total of 105 high-confidence risk genes (HRGs) were identified, which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC. Among the 105 HRGs, CEBPB, located at the 20q13.13 locus, acted as a transcription factor playing critical roles in cancer. Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK, PI3K-Akt, and Ras signaling. Next, by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls, we elucidated that rs1810503, a putative functional variant regulating CEBPB, was associated with CRC risk (OR=0.90, 95%CI=0.86-0.93, P=1.07×10-7). The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls. Mechanistically, the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via long-range promoter-enhancer interactions, mediated by the transcription factor, REST, and thus decreased CRC risk. In summary, our study provides a genetic resource and a generalizable strategy for CRC etiology investigation, and highlights the biological implications of CEBPB in CRC tumorigenesis, shedding new light on the etiology of CRC.
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Affiliation(s)
- Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, 450008, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Xiangpan Li
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, 430062, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, 450008, China.
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430073, China.
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, 211166, China.
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Long L, He H, Shen Q, Peng H, Zhou X, Wang H, Zhang S, Qin S, Lu Z, Zhu Y, Tian J, Chang J, Miao X, Shen N, Zhong R. Birthweight, genetic risk, and gastrointestinal cancer incidence: a prospective cohort study. Ann Med 2023; 55:62-71. [PMID: 36503347 PMCID: PMC9754019 DOI: 10.1080/07853890.2022.2146743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The epidemiologic studies investigating the association of birthweight and genetic factors with gastrointestinal cancer remain scarce. The study aimed to prospectively assess the interactions and joint effects of birthweight and genetic risk levels on gastrointestinal cancer incidence in adulthood. METHODS A total of 254,997 participants were included in the UK Biobank study. We used multivariate restricted cubic splines and Cox regression models to estimate the hazard ratios (HRs) and 95% confidential intervals (CI) for the association between birthweight and gastrointestinal cancer risk, then constructed a polygenic risk score (PRS) to assess its interaction and joint effect with birthweight on the development of gastrointestinal cancer. RESULTS We documented 2512 incident cases during a median follow-up of 8.88 years. Compare with participants reporting a normal birthweight (2.5-4.5 kg), multivariable-adjusted HR of gastrointestinal cancer incidence for participants with high birthweight (≥4.5 kg) was 1.17 (95%CI: 1.01-1.36). Such association was remarkably observed in pancreatic cancer, with an HR of 1.82 (95%CI: 1.26-2.64). No statistically significant association was observed between low birth weight and gastrointestinal cancers. Participants with high birthweight and high PRS had the highest risk of gastrointestinal cancer (HR: 2.95, 95%CI: 2.19-3.96). CONCLUSION Our findings highlight that high birthweight is associated with a higher incidence of gastrointestinal cancer, especially for pancreatic cancer. Benefits would be obtained from birthweight control, particularly for individuals with a high genetic risk.KEY MESSAGESThe epidemiologic studies investigating the association of birthweight and genetic factors with gastrointestinal cancer remain scarce.This cohort study of 254,997 adults in the United Kingdom found an association of high birthweight with the incidence of gastrointestinal cancer, especially for pancreatic cancer, and also found that participants with high birthweight and high polygenic risk score had the highest risk of gastrointestinal cancer.Our data suggests a possible effect of in utero or early life exposures on adulthood gastrointestinal cancer, especially for those with a high genetic risk.
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Affiliation(s)
- Lu Long
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Heng He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qian Shen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongxia Peng
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiaorui Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shifan Qin
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- School of Public Health, Wuhan University, Wuhan, China
| | - Jianbo Tian
- School of Public Health, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- School of Public Health, Wuhan University, Wuhan, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, HUST, Wuhan, China
- Na Shen Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- CONTACT Rong Zhong Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
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5
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Ning C, Fan L, Jin M, Wang W, Hu Z, Cai Y, Chen L, Lu Z, Zhang M, Chen C, Li Y, Zhang F, Wang W, Liu Y, Chen S, Jiang Y, He C, Wang Z, Chen X, Li H, Li G, Ma Q, Geng H, Tian W, Zhang H, Liu B, Xia Q, Yang X, Liu Z, Li B, Zhu Y, Li X, Zhang S, Tian J, Miao X. Genome-wide association analysis of left ventricular imaging-derived phenotypes identifies 72 risk loci and yields genetic insights into hypertrophic cardiomyopathy. Nat Commun 2023; 14:7900. [PMID: 38036550 PMCID: PMC10689443 DOI: 10.1038/s41467-023-43771-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 11/18/2023] [Indexed: 12/02/2023] Open
Abstract
Left ventricular regional wall thickness (LVRWT) is an independent predictor of morbidity and mortality in cardiovascular diseases (CVDs). To identify specific genetic influences on individual LVRWT, we established a novel deep learning algorithm to calculate 12 LVRWTs accurately in 42,194 individuals from the UK Biobank with cardiac magnetic resonance (CMR) imaging. Genome-wide association studies of CMR-derived 12 LVRWTs identified 72 significant genetic loci associated with at least one LVRWT phenotype (P < 5 × 10-8), which were revealed to actively participate in heart development and contraction pathways. Significant causal relationships were observed between the LVRWT traits and hypertrophic cardiomyopathy (HCM) using genetic correlation and Mendelian randomization analyses (P < 0.01). The polygenic risk score of inferoseptal LVRWT at end systole exhibited a notable association with incident HCM, facilitating the identification of high-risk individuals. The findings yield insights into the genetic determinants of LVRWT phenotypes and shed light on the biological basis for HCM etiology.
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Grants
- Z201100006820064 Beijing Nova Program
- Z211100002121165 Beijing Nova Program
- National Science Fund for Distinguished Young Scholars of China (NSFC-81925032), Key Program of National Natural Science Foundation of China (NSFC-82130098), the Leading Talent Program of the Health Commission of Hubei Province, Knowledge Innovation Program of Wuhan (2023020201010060) and Fundamental Research Funds for the Central Universities (2042022rc0026, 2042023kf1005) for Xiaoping Miao
- National Science Fund for Excellent Young Scholars (NSFC-82322058), Program of National Natural Science Foundation of China (NSFC-82103929, NSFC-82273713), Young Elite Scientists Sponsorship Program by cst(2022QNRC001), National Science Fund for Distinguished Young Scholars of Hubei Province of China (2023AFA046), Fundamental Research Funds for the Central Universities (WHU:2042022kf1205) and Knowledge Innovation Program of Wuhan (whkxjsj011, 2023020201010073) for Jianbo Tian
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Affiliation(s)
- Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Meng Jin
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Wenji Wang
- SenseTime Research, Shanghai, 201103, China
| | | | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Liangkai Chen
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yuan Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Chunyi He
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Zhuo Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Xu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Hanting Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Gaoyuan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Qianying Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Hui Geng
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Wen Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Heng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Bo Liu
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Qing Xia
- SenseTime Research, Shanghai, 201103, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Xiangpan Li
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Shaoting Zhang
- SenseTime Research, Shanghai, 201103, China.
- Shanghai Artificial Intelligence Laboratory, Shanghai, 200232, China.
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
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6
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Li B, Cai Y, Chen C, Li G, Zhang M, Lu Z, Zhang F, Huang J, Fan L, Ning C, Li Y, Wang W, Geng H, Liu Y, Chen S, Li H, Yang S, Zhang H, Tian W, Zhu Z, Xu B, Li H, Li H, Jin M, Wang X, Zhang S, Liu J, Huang C, Yang X, Wei Y, Zhu Y, Tian J, Miao X. Genetic Variants That Impact Alternative Polyadenylation in Cancer Represent Candidate Causal Risk Loci. Cancer Res 2023; 83:3650-3666. [PMID: 37669142 DOI: 10.1158/0008-5472.can-23-0251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 05/17/2023] [Accepted: 08/29/2023] [Indexed: 09/07/2023]
Abstract
Alternative polyadenylation (APA) is emerging as a major mechanism of posttranscriptional regulation. APA can impact the development and progression of cancer, suggesting that the genetic determinants of APA might play an important role in regulating cancer risk. Here, we depicted a pan-cancer atlas of human APA quantitative trait loci (apaQTL), containing approximately 0.7 million apaQTLs across 32 cancer types. Systematic multiomics analyses indicated that cancer apaQTLs could contribute to APA regulation by altering poly(A) motifs, RNA-binding proteins (RBP), and chromatin regulatory elements and were preferentially enriched in genome-wide association studies (GWAS)-identified cancer susceptibility loci. Moreover, apaQTL-related genes (aGene) were broadly related to cancer signaling pathways, high mutational burden, immune infiltration, and drug response, implicating their potential as therapeutic targets. Furthermore, apaQTLs were mapped in Chinese colorectal cancer tumor tissues and then screened for functional apaQTLs associated with colorectal cancer risk in 17,789 cases and 19,951 controls using GWAS-ChIP data, with independent validation in a large-scale population consisting of 6,024 cases and 10,022 controls. A multi-ancestry-associated apaQTL variant rs1020670 with a C>G change in DNM1L was identified, and the G allele contributed to an increased risk of colorectal cancer. Mechanistically, the risk variant promoted aberrant APA and facilitated higher usage of DNM1L proximal poly(A) sites mediated by the RBP CSTF2T, which led to higher expression of DNM1L with a short 3'UTR. This stabilized DNM1L to upregulate its expression, provoking colorectal cancer cell proliferation. Collectively, these findings generate a resource for understanding APA regulation and the genetic basis of human cancers, providing insights into cancer etiology. SIGNIFICANCE Cancer risk is mediated by alternative polyadenylation quantitative trait loci, including the rs1020670-G variant that promotes alternative polyadenylation of DNM1L and increases colorectal cancer risk.
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Affiliation(s)
- Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Gaoyuan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Jinyu Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Hui Geng
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Hanting Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Shuhui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Heng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Wen Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Zhongchao Zhu
- Department of Pancreatic Surgery Department, Renmin Hospital of Wuhan University, Wuhan, China
| | - Bin Xu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Haijie Li
- Department of Gastrointestinal Cancer Research Institute, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Meng Jin
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyang Wang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China
| | - Jiuyang Liu
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Chaoqun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Department of Pancreatic Surgery Department, Renmin Hospital of Wuhan University, Wuhan, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
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Zhang M, Chen C, Lu Z, Cai Y, Li Y, Zhang F, Liu Y, Chen S, Zhang H, Yang S, Gen H, Jiang Y, Ning C, Huang J, Wang W, Fan L, Zhang Y, Jin M, Han J, Xiong Z, Cai M, Liu J, Huang C, Yang X, Xu B, Li H, Li B, Zhu X, Wei Y, Zhu Y, Tian J, Miao X. Genetic Control of Alternative Splicing and its Distinct Role in Colorectal Cancer Mechanisms. Gastroenterology 2023; 165:1151-1167. [PMID: 37541527 DOI: 10.1053/j.gastro.2023.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 07/20/2023] [Accepted: 07/23/2023] [Indexed: 08/06/2023]
Abstract
BACKGROUND & AIMS Dysregulation of alternative splicing is implicated in many human diseases, and understanding the genetic variation underlying transcript splicing is essential to dissect the molecular mechanisms of cancers. We aimed to provide a comprehensive functional dissection of splicing quantitative trait loci (sQTLs) in cancer and focus on elucidating its distinct role in colorectal cancer (CRC) mechanisms. METHODS We performed a comprehensive sQTL analysis to identify genetic variants that control messenger RNA splicing across 33 cancer types from The Cancer Genome Atlas and independently validated in our 154 CRC tissues. Then, large-scale, multicenter, multi-ethnic case-control studies (34,585 cases and 76,023 controls) were conducted to examine the association of these sQTLs with CRC risk. A series of biological experiments in vitro and in vivo were performed to investigate the potential mechanisms of the candidate sQTLs and target genes. RESULTS The molecular characterization of sQTL revealed its distinct role in cancer susceptibility. Tumor-specific sQTL further showed better response to cancer development. In addition, functionally informed polygenic risk score highlighted the potentiality of sQTLs in the CRC prediction. Complemented by large-scale population studies, we identified that the risk allele (T) of a multi-ancestry-associated sQTL rs61746794 significantly increased the risk of CRC in Chinese (odds ratio, 1.20; 95% CI, 1.12-1.29; P = 8.82 × 10-7) and European (odds ratio, 1.11; 95% CI, 1.07-1.16; P = 1.13 × 10-7) populations. rs61746794-T facilitated PRMT7 exon 16 splicing mediated by the RNA-binding protein PRPF8, thus increasing the level of canonical PRMT7 isoform (PRMT7-V2). Overexpression of PRMT7-V2 significantly enhanced the growth of CRC cells and xenograft tumors compared with PRMT7-V1. Mechanistically, PRMT7-V2 functions as an epigenetic writer that catalyzes the arginine methylation of H4R3 and H3R2, subsequently regulating diverse biological processes, including YAP, AKT, and KRAS pathway. A selective PRMT7 inhibitor, SGC3027, exhibited antitumor effects on human CRC cells. CONCLUSIONS Our study provides an informative sQTLs resource and insights into the regulatory mechanisms linking splicing variants to cancer risk and serving as biomarkers and therapeutic targets.
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Affiliation(s)
- Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China; Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China; Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China; Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Heng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Shuhui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Hui Gen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Yuan Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jinyu Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Yi Zhang
- Department of Hygiene Toxicology, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China
| | - Meng Jin
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jinxin Han
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Xiong
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming Cai
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiuyang Liu
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Chaoqun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Bin Xu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China; Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China; Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, China; Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China.
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Zhang M, Li Y, Zhang F, Geng H, Cai Y, Lu Z, Li B, Ning C, Wang W, Li H, Tian J, Zhu Y, Miao X. Risk SNP in a transcript of RP11-638I2.4 increases lncRNA-YY1 interaction and pancreatic cancer susceptibility. Arch Toxicol 2023; 97:2799-2812. [PMID: 37587385 DOI: 10.1007/s00204-023-03564-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 07/24/2023] [Indexed: 08/18/2023]
Abstract
Tens of thousands of long non-coding RNAs (lncRNAs) have been identified through RNA-seq analysis, but the biological and pathological significance remains unclear. By integrating the genome-wide lncRNA data with a cross-ancestry meta-analysis of PDAC GWASs, we depicted a comprehensive atlas of pancreatic ductal adenocarcinoma (PDAC)-associated lncRNAs, containing 1,204 lncRNA (445 novel lncRNAs and 759 GENCODE annotated lncRNAs) and 4,368 variants. Furthermore, we found that PDAC-associated lncRNAs could function by altering chromatin activity, transcription factors, and RNA-binding proteins binding affinity. Importantly, genetic variants linked to PDAC are preferentially found at PDAC-associated lncRNA regions, supporting the biological and clinical relevance of PDAC-associated lncRNAs. Finally, we prioritized a novel transcript (MICT00000110172.1) of RP11-638I2.4 as a potential tumor promoter. MICT00000110172.1 is able to reinforce the interaction with YY1, which could reverse the effect of YY1 on pancreatic cancer cell cycle arrest to promote the pancreatic cancer growth. G > A change at rs2757535 in the second exon of MICT00000110172.1 induces a spatial structural change and creates a target region for YY1 binding, which enforces the effect of MICT00000110172.1 in an allele-specific manner, and thus confers susceptibility to tumorigenesis. In summary, our results extend the repertoire of PDAC-associated lncRNAs that could act as a starting point for future functional explorations, and the identification of lncRNA-based target therapy.
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Affiliation(s)
- Ming Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Hui Geng
- Department of Epidemiology and Biostatistics, School of Public Health, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Haijie Li
- Department of Gastrointestinal Cancer Research Institute, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China.
- Department of Gastrointestinal OncologyTaiKang Center for Life and Medical Sciences, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
- Department of Gastrointestinal OncologyTaiKang Center for Life and Medical Sciences, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health (Ministry of Education), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China.
- Department of Gastrointestinal OncologyTaiKang Center for Life and Medical Sciences, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
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Bennett S, Verry C, Kaza E, Miao X, Berbeco RI, Sudhyadhom A. Theranostic Nanoparticle Uptake in Patient Brain Tumors as Quantified by MP2RAGE T1 Mapping. Int J Radiat Oncol Biol Phys 2023; 117:S32. [PMID: 37784476 DOI: 10.1016/j.ijrobp.2023.06.296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Modern radiation therapy techniques provide effective treatments for solid tumors, but there remain challenges with delivering high doses to elusive tumors without causing toxicity to surrounding normal tissue. Pre-clinical trials have demonstrated the theranostic properties of a recently developed gadolinium-based nanoparticle (Gd-NP). The first in-human clinical trial was conducted to assess the safety and dose tolerance of intravenous Gd-NPs in combination with whole brain radiotherapy and showed favorable results, including a significant correlation between tumor uptake and therapeutic response. The second, double-blinded, in-human clinical trial is underway in the US and aims to evaluate if brain-directed stereotactic radiation in conjunction with NPs will improve local tumor control compared to radiation alone. The current work investigates uptake patterns in brain tumors of 23 patients as quantified by magnetization prepared 2 rapid gradient echo (MP2RAGE) T1 mapping. MATERIALS/METHODS A phantom containing eight vials of NP-saline solutions at varying concentrations was created to examine the relationship between NP concentration and longitudinal relaxation (T1, in seconds). This relationship is known as relaxivity and is dependent on the contrast agent, field strength and T1 mapping sequence. A 3T MAGNETOM Vida scanner and MP2RAGE sequence were used to image the phantom and MP2RAGE T1 maps were calculated using Bloch equations (QMRLab software). Relaxivity was determined and applied to 23 patient T1 maps (pre- and post- Gd-NP administration) to calculate uptake on an individual tumor basis. Theranostic NP uptake was calculated for every voxel in each of 129 brain metastases and examined for patterns in quantity and distribution. RESULTS Average individual tumor uptake ranged from 0.02-0.12 mg/ml, where average overall uptake was equal to 0.05 mg/ml. A relationship between tumor diameter and mean NP concentration was observed and best represented by a power-based curve (R2 = 0.92). In contrast, patients with suspected placebo administration appeared to have no uptake and therefore no relationship with tumor diameter. The distribution of NP concentration within the tumor was also examined; on average, linear uptake profiles through tumor centroids (ant-post, left-right) demonstrated roughly gaussian patterns of uptake with lower concentrations at the tumor edges and higher concentrations at the tumor center. This pattern indicates robust tumor penetration and may have implications for amplifying radiation dose to hypoxic tumors. CONCLUSION Gd-NP uptake in brain metastases can be quantified using MP2RAGE T1 mapping. Uptake was determined for each voxel in each tumor volume, where a gaussian pattern of spatial concentrations was observed. This analysis procedure will be applied to the full data set, when available, to evaluate the impact of NP uptake (in conjunction with radiation therapy) within individual patients and individual tumors.
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Affiliation(s)
- S Bennett
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - C Verry
- Centre Hospitalier Universitaire Grenoble-Alpes, Maquis du Grésivaudan, 38700 La Tronche, France
| | - E Kaza
- Department of Radiation Oncology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Boston, MA
| | - X Miao
- Siemens Medical Solutions USA Inc, Malvern, PA
| | - R I Berbeco
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - A Sudhyadhom
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA
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10
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Ying P, Chen C, Lu Z, Chen S, Zhang M, Cai Y, Zhang F, Huang J, Fan L, Ning C, Li Y, Wang W, Geng H, Liu Y, Tian W, Yang Z, Liu J, Huang C, Yang X, Xu B, Li H, Zhu X, Li N, Li B, Wei Y, Zhu Y, Tian J, Miao X. Genome-wide enhancer-gene regulatory maps link causal variants to target genes underlying human cancer risk. Nat Commun 2023; 14:5958. [PMID: 37749132 PMCID: PMC10520073 DOI: 10.1038/s41467-023-41690-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 09/14/2023] [Indexed: 09/27/2023] Open
Abstract
Genome-wide association studies have identified numerous variants associated with human complex traits, most of which reside in the non-coding regions, but biological mechanisms remain unclear. However, assigning function to the non-coding elements is still challenging. Here we apply Activity-by-Contact (ABC) model to evaluate enhancer-gene regulation effect by integrating multi-omics data and identified 544,849 connections across 20 cancer types. ABC model outperforms previous approaches in linking regulatory variants to target genes. Furthermore, we identify over 30,000 enhancer-gene connections in colorectal cancer (CRC) tissues. By integrating large-scale population cohorts (23,813 cases and 29,973 controls) and multipronged functional assays, we demonstrate an ABC regulatory variant rs4810856 associated with CRC risk (Odds Ratio = 1.11, 95%CI = 1.05-1.16, P = 4.02 × 10-5) by acting as an allele-specific enhancer to distally facilitate PREX1, CSE1L and STAU1 expression, which synergistically activate p-AKT signaling. Our study provides comprehensive regulation maps and illuminates a single variant regulating multiple genes, providing insights into cancer etiology.
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Grants
- Distinguished Young Scholars of China (NSFC-81925032), Key Program of National Natural Science Foundation of China (NSFC-82130098), the Fundamental Research Funds for the Central Universities (2042022rc0026, 2042023kf1005),Knowledge Innovation Program of Wuhan (2023020201010060).
- Youth Program of National Natural Science Foundation of China (NSFC-82003547), Program of Health Commission of Hubei Province (WJ2023M045) and Fundamental Research Funds for the Central Universities (WHU: 2042022kf1031).
- The National Science Fund for Excellent Young Scholars (NSFC-82322058), Program of National Natural Science Foundation of China (NSFC-82103929, NSFC-82273713), Young Elite Scientists Sponsorship Program by cst(2022QNRC001), National Science Fund for Distinguished Young Scholars of Hubei Province of China (2023AFA046), Fundamental Research Funds for the Central Universities (WHU:2042022kf1205) and Knowledge Innovation Program of Wuhan (whkxjsj011, 2023020201010073).
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Affiliation(s)
- Pingting Ying
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Jinyu Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Hui Geng
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Wen Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Zhiyong Yang
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Jiuyang Liu
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Chaoqun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Bin Xu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Heng Li
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China.
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11
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He H, Shen Q, He MM, Qiu W, Wang H, Zhang S, Qin S, Lu Z, Zhu Y, Tian J, Chang J, Wang K, Zhang X, Miao X, Song M, Zhong R. In Utero and Childhood/Adolescence Exposure to Tobacco Smoke, Genetic Risk, and Cancer Incidence in Adulthood: A Prospective Cohort Study. Mayo Clin Proc 2023; 98:1164-1176. [PMID: 37422733 DOI: 10.1016/j.mayocp.2023.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 03/11/2023] [Accepted: 03/28/2023] [Indexed: 07/10/2023]
Abstract
OBJECTIVE To evaluate the association of early-life tobacco smoke exposure, especially interacting with cancer genetic variants, with adult cancer. PARTICIPANTS AND METHODS We examined the associations of in utero tobacco smoke exposure, age of smoking initiation, and their interaction with genetic risk levels with cancer incidence in 393,081 participants from the UK Biobank. Information on tobacco exposure was obtained by self-reported questionnaires. A cancer polygenic risk score was constructed by weighting and integrating 702 genome-wide association studies-identified risk variants. Cox proportional hazards regression models were used to calculate hazard ratios (HRs) for overall cancer and organ-specific cancer incidence. RESULTS During 11.8 years of follow-up, 23,450 (5.97%) and 23,413 (6.03%) incident cancers were included in the analyses of in utero exposure and age of smoking initiation, respectively. The HR (95% CI) for incident cancer in participants with in utero exposure to tobacco smoke was 1.04 (1.01-1.07) for overall cancer, 1.59 (1.44-1.75) for respiratory cancer, and 1.09 (1.03-1.17) for gastrointestinal cancer. The relative risk of incident cancer increased with earlier smoking initiation (Ptrend<.001), with the HR (95% CI) of 1.44 (1.36-1.51) for overall cancer, 13.28 (11.39-15.48) for respiratory cancer, and 1.72 (1.54-1.91) for gastrointestinal cancer in smokers with initiation in childhood compared with never smokers. Importantly, a positive additive interaction between age of smoking initiation and genetic risk was observed for overall cancer (Padditive=.04) and respiratory cancer (Padditive=.003) incidence. CONCLUSION In utero exposure and earlier smoking initiation are associated with overall and organ-specific cancer, and age of smoking initiation interaction with genetic risk is associated with respiratory cancer.
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Affiliation(s)
- Heng He
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qian Shen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming-Ming He
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Weihong Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shifan Qin
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Mingyang Song
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA; Clinical and Translational Epidemiology Unit, Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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12
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Lu Z, Fan L, Zhang F, Huang C, Cai Y, Chen C, Li G, Zhang M, Huang J, Ning C, Li Y, Wang W, Geng H, Liu Y, Chen S, Li H, Yang S, Zhang H, Tian W, Ye T, Liu J, Yang X, Xu B, Zhu Y, Zhong R, Li H, Tian J, Li B, Miao X. HSPA12A was identified as a key driver in colorectal cancer GWAS loci 10q26.12 and modulated by an enhancer-promoter interaction. Arch Toxicol 2023; 97:2015-2028. [PMID: 37245169 DOI: 10.1007/s00204-023-03494-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 04/04/2023] [Indexed: 05/29/2023]
Abstract
Although genome-wide association studies (GWASs) have identified over 100 colorectal cancer (CRC) risk loci, an understanding of causal genes or risk variants and their biological functions in these loci remain unclear. Recently, genomic loci 10q26.12 with lead SNP rs1665650 was identified as an essential CRC risk loci of Asian populations. However, the functional mechanism of this region has not been fully clarified. Here, we applied an RNA interfering-based on-chip approach to screen for the genes essential for cell proliferation in the CRC risk loci 10q26.12. Notably, HSPA12A had the most significant effect among the identified genes and functioned as a crucial oncogene facilitating cell proliferation. Moreover, we conducted an integrative fine-mapping analysis to identify putative casual variants and further explored their association with CRC risk in a large-scale Chinese population consisting of 4054 cases and 4054 controls and also independently validated in 5208 cases and 20,832 controls from the UK biobank cohort. We identified a risk SNP rs7093835 in the intron of HSPA12A that was significantly associated with an increased risk of CRC (OR 1.23, 95% CI 1.08-1.41, P = 1.92 × 10-3). Mechanistically, the risk variant could facilitate an enhancer-promoter interaction mediated by the transcriptional factor (TF) GRHL1 and ultimately upregulate HSPA12A expression, which provides functional evidence to support our population findings. Collectively, our study reveals the important role of HSPA12A in CRC development and illustrates a novel enhancer-promoter interaction module between HSPA12A and its regulatory elements rs7093835, providing new insights into the etiology of CRC.
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Affiliation(s)
- Zequn Lu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Chaoqun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Gaoyuan Li
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Jinyu Huang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Hui Geng
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Hanting Li
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Shuhui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Heng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Wen Tian
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Tianrun Ye
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiuyang Liu
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Bin Xu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Heng Li
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China.
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.
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13
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He H, Zhang F, Zhou S, Zhang S, Wang L, Li J, Zeng Q, Zhu Y, Tian J, Chang J, Cheng L, Lu Q, Miao X, Shen N, Zhong R. Interaction of metabolism-related pathway gene variants with bisphenol A exposure on serum lipid profiles. Environ Toxicol Pharmacol 2023:104173. [PMID: 37302441 DOI: 10.1016/j.etap.2023.104173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 06/02/2023] [Accepted: 06/06/2023] [Indexed: 06/13/2023]
Abstract
Bisphenol A (BPA) can be metabolized by metabolic enzymes and may induce abnormal lipid metabolism. We hypothesized that BPA exposure and its interaction with metabolism-related genes might be associated with serum lipid profiles. We performed a two-stage study among 955 middle-aged and elderly participants in Wuhan, China. Urinary BPA level was estimated without (BPA, μg/L) or with (BPA/Cr, μg/g) adjustments for urinary creatinine and ln-transformed values (ln-BPA or ln-BPA/Cr) were used to normalize the asymmetrical distributions. A total of 412 metabolism-related gene variants were selected and used for gene-BPA interaction analysis. Multiple linear regression was used to analyze the interactions between BPA exposure and metabolism-related genes on serum lipid profiles. In the discovery stage, both ln-BPA and ln-BPA/Cr was associated with decreased high-density lipoprotein cholesterol (HDL-C). Gene-urinary BPA interaction for IGFBP7 rs9992658 was observed to associate with HDL-C levels in both discovery and validation stages, with Pinteraction equal to 9.87×10-4 (ln-BPA) and 1.22×10-3 (ln-BPA/Cr) in combined analyses. In addition, the inverse association of urinary BPA with HDL-C levels was only observed among individuals carrying rs9992658 AA genotype, but not in individuals carrying rs9992658 AC or CC genotypes. The interaction between BPA exposure and metabolism-related gene IGFBP7 (rs9992658) was associated with HDL-C levels. AVAILABILITY OF DATA AND MATERIAL: Not applicable.
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Affiliation(s)
- Heng He
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shuang Zhou
- Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan 430015, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lu Wang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiang Zeng
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- School of Public Health, Wuhan University, Wuhan, China
| | - Jianbo Tian
- School of Public Health, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qing Lu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- School of Public Health, Wuhan University, Wuhan, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Rong Zhong
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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14
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Fan L, Cai Y, Wang H, Zhang H, Chen C, Zhang M, Lu Z, Li Y, Zhang F, Ning C, Wang W, Liu Y, Li H, Li G, Peng J, Hu K, Li B, Huang C, Yang X, Wei Y, Zhu Y, Jin M, Miao X, Tian J. Saturated fatty acid intake, genetic risk and colorectal cancer incidence: A large-scale prospective cohort study. Int J Cancer 2023. [PMID: 37087737 DOI: 10.1002/ijc.34544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/23/2023] [Accepted: 04/05/2023] [Indexed: 04/24/2023]
Abstract
Previous investigations mainly focused on the associations of dietary fatty acids with colorectal cancer (CRC) risk, which ignored gene-environment interaction and mechanisms interpretation. We conducted a case-control study (751 cases and 3058 controls) and a prospective cohort study (125 021 participants) to explore the associations between dietary fatty acids, genetic risks, and CRC. Results showed that high intake of saturated fatty acid (SFA) was associated with a higher risk of CRC than low SFA intake (HR =1.22, 95% CI:1.02-1.46). Participants at high genetic risk had a greater risk of CRC with the HR of 2.48 (2.11-2.91) than those at low genetic risk. A multiplicative interaction of genetic risk and SFA intake with incident CRC risk was found (PInteraction = 7.59 × 10-20 ), demonstrating that participants with high genetic risk and high SFA intake had a 3.75-fold greater risk of CRC than those with low genetic risk and low SFA intake. Furthermore, incorporating PRS and SFA into traditional clinical risk factors improved the discriminatory accuracy for CRC risk stratification (AUC from 0.706 to 0.731). Multi-omics data showed that exposure to SFA-rich high-fat dietary (HFD) can responsively induce epigenome reprogramming of some oncogenes and pathological activation of fatty acid metabolism pathway, which may contribute to CRC development through changes in gut microbiomes, metabolites, and tumor-infiltrating immune cells. These findings suggest that individuals with high genetic risk of CRC may benefit from reducing SFA intake. The incorporation of SFA intake and PRS into traditional clinical risk factors will help improve high-risk sub-populations in individualized CRC prevention.
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Affiliation(s)
- Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Heng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Hanting Li
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Gaoyuan Li
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jingyi Peng
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Kexin Hu
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Chaoqun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Meng Jin
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health; Department of Gastrointestinal Oncology, Zhongnan Hospital, Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, China
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15
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Niu S, Shi K, Yue X, Pan M, Song L, Gu L, Tan Y, Miao X, Tian J, Chang J. A variant in CYP26B1 associated with esophageal squamous cell carcinoma risk by affecting retinoic acid metabolism. Mol Carcinog 2023. [PMID: 37042568 DOI: 10.1002/mc.23540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 03/04/2023] [Accepted: 03/27/2023] [Indexed: 04/13/2023]
Abstract
All-trans retinoic acid (ATRA) is the natural and synthetic analogue of vitamin A, playing an essential tumor suppressive role in multiple cancers including the esophageal squamous cell carcinoma (ESCC). Cytochrome P450 family 26 subfamily B member 1 (CYP26B1) exerts a critical regulator of ATRA levels through specific inactivation of ATRA to hydroxylated forms. Our previous exome-wide analyses revealed a rare missense variant in CYP26B1 significantly associated with ESCC risk in the Chinese population. However, it is still unclear whether there are common variants in CYP26B1 affect the susceptibility of ESCC and the tumor promotion role of CYP26B1 in vivo. In this research, we conducted a two-stage case-control study comprised of 5057 ESCC cases and 5397 controls, followed by a series of biochemical experiments to explore the function of CYP26B1 and its common variants in the tumorigenesis of ESCC. Intriguingly, we identified a missense variant rs2241057[A>G] in the fourth exon of CYP26B1 significantly associated with the ESCC risk (combined odds ratio = 1.28; 95% confidence interval = 1.15-1.42; p = 2.96 × 10-6 ). Through further functional analysis, we demonstrated that ESCC cells with the overexpression of rs2241057[G] had a significant lower level of retinoic acid, compared with the overexpression of rs2241057[A] or the control vector. In addition, the CYP26B1 overexpression and knock-out ESCC cells affected cell proliferation rate both in vitro and in vivo. These results highlighted the carcinogenicity of CYP26B1 related to the ATRA metabolism in ESCC risk.
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Affiliation(s)
- Siyuan Niu
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ke Shi
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xinying Yue
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Miaoxin Pan
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lina Song
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Linglong Gu
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yuqian Tan
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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16
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Wang H, Cai Y, Jin M, Huang CQ, Ning C, Niu S, Fan L, Li B, Zhang M, Lu Z, Dong X, Luo Z, Zhong R, Li H, Zhu Y, Miao X, Yang X, Chang J, Li N, Tian J. Identification of specific susceptibility loci for the early-onset colorectal cancer. Genome Med 2023; 15:13. [PMID: 36869385 PMCID: PMC9983269 DOI: 10.1186/s13073-023-01163-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 02/15/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND The incidence of early-onset colorectal cancer (EOCRC; patients < 50 years old) has been rising rapidly, whereas the EOCRC genetic susceptibility remains incompletely investigated. Here, we aimed to systematically identify specific susceptible genetic variants for EOCRC. METHODS Two parallel GWASs were conducted in 17,789 CRC cases (including 1490 EOCRC cases) and 19,951 healthy controls. A polygenic risk score (PRS) model was built based on identified EOCRC-specific susceptibility variants by using the UK Biobank cohort. We also interpreted the potential biological mechanisms of the prioritized risk variant. RESULTS We identified 49 independent susceptibility loci that were significantly associated with the susceptibility to EOCRC and the diagnosed age of CRC (both P < 5.0×10-4), replicating 3 previous CRC GWAS loci. There are 88 assigned susceptibility genes involved in chromatin assembly and DNA replication pathways, mainly associating with precancerous polyps. Additionally, we assessed the genetic effect of the identified variants by developing a PRS model. Compared to the individuals in the low genetic risk group, the individuals in the high genetic risk group have increased EOCRC risk, and these results were replicated in the UKB cohort with a 1.63-fold risk (95% CI: 1.32-2.02, P = 7.67×10-6). The addition of the identified EOCRC risk loci significantly increased the prediction accuracy of the PRS model, compared to the PRS model derived from the previous GWAS-identified loci. Mechanistically, we also elucidated that rs12794623 may contribute to the early stage of CRC carcinogenesis via allele-specific regulating the expression of POLA2. CONCLUSIONS These findings will broaden the understanding of the etiology of EOCRC and may facilitate the early screening and individualized prevention.
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Affiliation(s)
- Haoxue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Meng Jin
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Chao Qun Huang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Siyuan Niu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuesi Dong
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zilin Luo
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China.,Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Xiaojun Yang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. .,Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, 430071, China.
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17
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Chen H, Shi J, Lu M, Li Y, Du L, Liao X, Wei D, Dong D, Gao Y, Zhu C, Ying R, Zheng W, Yan S, Xiao H, Zhang J, Kong Y, Li F, Zou S, Liu C, Wang H, Zhang Y, Lu B, Luo C, Cai J, Tian J, Miao X, Ding K, Brenner H, Dai M. Comparison of Colonoscopy, Fecal Immunochemical Test, and Risk-Adapted Approach in a Colorectal Cancer Screening Trial (TARGET-C). Clin Gastroenterol Hepatol 2023; 21:808-818. [PMID: 35964896 DOI: 10.1016/j.cgh.2022.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/30/2022] [Accepted: 08/02/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS The screening yield and related cost of a risk-adapted screening approach compared with established screening strategies in population-based colorectal cancer (CRC) screening are not clear. METHODS We randomly allocated 19,373 participants into 1 of the 3 screening arms in a 1:2:2 ratio: (1) one-time colonoscopy (n = 3883); (2) annual fecal immunochemical test (FIT) (n = 7793); (3) annual risk-adapted screening (n = 7697), in which, based on the risk-stratification score, high-risk participants were referred for colonoscopy and low-risk ones were referred for FIT. Three consecutive screening rounds were conducted for both the FIT and the risk-adapted screening arms. Follow-up to trace the health outcome for all the participants was conducted over the 3-year study period. The detection rate of advanced colorectal neoplasia (CRC and advanced precancerous lesions) was the main outcome. The trial was registered in the Chinese Clinical Trial Registry (number: ChiCTR1800015506). RESULTS In the colonoscopy, FIT, and risk-adapted screening arms over 3 screening rounds, the participation rates were 42.4%, 99.3%, and 89.2%, respectively; the detection rates for advanced neoplasm (intention-to-treat analysis) were 2.76%, 2.17%, and 2.35%, respectively, with an odds ratio (OR)colonoscopy vs FIT of 1.27 (95% confidence interval [CI]: 0.99-1.63; P = .056), an ORcolonoscopy vsrisk-adapted screening of 1.17 (95% CI, 0.91-1.49; P = .218), and an ORrisk-adapted screeningvs FIT of 1.09 (95% CI, 0.88-1.35; P = .438); the numbers of colonoscopies needed to detect 1 advanced neoplasm were 15.4, 7.8, and 10.2, respectively; the costs for detecting 1 advanced neoplasm from a government perspective using package payment format were 6928 Chinese Yuan (CNY) ($1004), 5821 CNY ($844), and 6694 CNY ($970), respectively. CONCLUSIONS The risk-adapted approach is a feasible and cost-favorable strategy for population-based CRC screening and therefore could complement the well-established one-time colonoscopy and annual repeated FIT screening strategies. (Chinese Clinical Trial Registry; ChiCTR1800015506).
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Affiliation(s)
- Hongda Chen
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jufang Shi
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ming Lu
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yanjie Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lingbin Du
- Department of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Xianzhen Liao
- Department of Cancer Prevention, Hunan Cancer Hospital, Changsha, China
| | - Donghua Wei
- Department of Cancer Prevention, Anhui Provincial Cancer Hospital, Hefei, China
| | - Dong Dong
- Office of Cancer Prevention and Treatment, Xuzhou Cancer Hospital, Xuzhou, China
| | - Yi Gao
- Department of Colorectum Surgery, Tumor Hospital of Yunnan Province/Third Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Chen Zhu
- Department of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Rongbiao Ying
- Department of Surgical Oncology, Taizhou Cancer Hospital, Taizhou, China
| | - Weifang Zheng
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Department of Proctology, Lanxi Red Cross Hospital, Jinhua, China
| | - Shipeng Yan
- Department of Cancer Prevention, Hunan Cancer Hospital, Changsha, China
| | - Haifan Xiao
- Department of Cancer Prevention, Hunan Cancer Hospital, Changsha, China
| | - Juan Zhang
- Department of Cancer Prevention, Anhui Provincial Cancer Hospital, Hefei, China
| | - Yunxin Kong
- Office of Cancer Prevention and Treatment, Xuzhou Cancer Hospital, Xuzhou, China
| | - Furong Li
- Department of Colorectum Surgery, Tumor Hospital of Yunnan Province/Third Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuangmei Zou
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chengcheng Liu
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hong Wang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Yuhan Zhang
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bin Lu
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chenyu Luo
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Cai
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianbo Tian
- School of Public Health, Taikang Center for Life and Medical Sciences, Wuhan University; Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xiaoping Miao
- School of Public Health, Taikang Center for Life and Medical Sciences, Wuhan University; Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, China
| | - Kefeng Ding
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Cancer Center, Zhejiang University, Hangzhou, China
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg, Germany; German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - Min Dai
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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18
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He H, He MM, Wang H, Qiu W, Liu L, Long L, Shen Q, Zhang S, Qin S, Lu Z, Cai Y, Zhang M, Niu S, Li J, Shen N, Zhu Y, Tian J, Chang J, Miao X, Zhong R. In Utero and Childhood/Adolescence Exposure to Tobacco Smoke, Genetic Risk, and Lung Cancer Incidence and Mortality in Adulthood. Am J Respir Crit Care Med 2023; 207:173-182. [PMID: 35943859 DOI: 10.1164/rccm.202112-2758oc] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Rationale: The individual effects of early-life tobacco smoke exposure and its interactions with genetic factors on lung cancer in adulthood remain unclear. Objectives: To investigate the associations of early-life tobacco exposures as well as their interactions with polygenic risk scores (PRSs) with lung cancer incidence and mortality. Methods: A total of 432,831 participants from the UK Biobank study were included. We estimated the associations of in utero exposure to tobacco smoke, the age of smoking initiation and their interactions with PRSs with lung cancer incidence and mortality in adulthood using Cox proportional hazard models. Measurements and Main Results: Lung cancer incidence (hazard ratio [HR]: 1.59, 95% confidence interval [CI], 1.44-1.76) increased among participants with in utero tobacco exposure. Multivariable-adjusted HRs (with 95% CIs) of lung cancer incidence for smoking initiation in adulthood, adolescence, and childhood (versus never-smokers) were 6.10 (5.25-7.09), 9.56 (8.31-11.00), and 15.15 (12.90-17.79) (Ptrend < 0.001). Similar findings were observed in lung cancer mortality. Participants with high PRSs and in utero tobacco exposure (versus low PRSs participants without in utero exposure) had an HR of 2.35 for lung cancer incidence (95% CI, 1.97-2.80, Pinteraction = 0.089) and 2.43 for mortality (95% CI, 2.05-2.88, Pinteraction = 0.032). High PRSs with smoking initiation in childhood (versus never-smokers with low PRSs) had HRs of 18.71 for incidence (95% CI, 14.21-24.63, Pinteraction = 0.004) and 19.74 for mortality (95% CI, 14.98-26.01, Pinteraction = 0.033). Conclusions: In utero and childhood/adolescence exposure to tobacco smoke and its interaction with genetic factors may substantially increase the risks of lung cancer incidence and mortality in adulthood.
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Affiliation(s)
- Heng He
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Ming-Ming He
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Weihong Qiu
- Department of Occupational & Environmental Health, and
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Liu
- Division of Cardiology, Department of Internal Medicine and
| | - Lu Long
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; and
| | - Qian Shen
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Shifan Qin
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Zequn Lu
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Yimin Cai
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Ming Zhang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Siyuan Niu
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Jiaoyuan Li
- Department of Laboratory Medicine Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Na Shen
- Department of Laboratory Medicine Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- School of Health Sciences, Wuhan University, Wuhan, China
| | - Jianbo Tian
- School of Health Sciences, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
| | - Xiaoping Miao
- School of Health Sciences, Wuhan University, Wuhan, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health
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Cai X, Ning C, Fan L, Li Y, Wang L, He H, Dong T, Cai Y, Zhang M, Lu Z, Chen C, Shi K, Ye T, Zhong R, Tian J, Li H, Li H, Zhu Y, Miao X. Triclosan is associated with breast cancer via oxidative stress and relative telomere length. Front Public Health 2023; 11:1163965. [PMID: 37213605 PMCID: PMC10197149 DOI: 10.3389/fpubh.2023.1163965] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 04/10/2023] [Indexed: 05/23/2023] Open
Abstract
Introduction Triclosan (TCS), a widely prescribed broad-spectrum antibacterial agent, is an endocrine-disrupting chemical. The relationship and biological mechanisms between TCS exposure and breast cancer (BC) are disputed. We aimed to examine the correlation between urinary TCS exposure and BC risk and estimated the mediating effects of oxidative stress and relative telomere length (RTL) in the above association. Methods This case-control study included 302 BC patients and 302 healthy individuals in Wuhan, China. We detected urinary TCS, three common oxidative stress biomarkers [8-hydroxy-2-deoxyguanosine (8-OHdG), 8-iso-prostaglandin F2α (8-isoPGF2α), 4-hydroxy-2-nonenal-mercapturic acid (HNE-MA)], and RTL in peripheral blood mononuclear cells. Results Significant associations were observed between log-transformed urinary concentrations of TCS, 8-OHdG, HNE-MA, 8-isoPGF2α, RTL, and BC risk, with the odds ratios (95% confidence intervals) being 1.58 (1.32-1.91), 3.08 (1.55-6.23), 3.39 (2.45-4.77), 3.99 (2.48-6.54), and 1.67 (1.35-2.09), respectively. Continuous TCS exposure was significantly positively correlated with RTL, HNE-MA, and 8-isoPGF2α (all p<0.05) but not with 8-OHdG (p = 0.060) after adjusting for covariates. The mediated proportions of 8-isoPGF22α and RTL in the relationship between TCS and BC risk were 12.84% and 8.95%, respectively (all p<0.001). Discussion In conclusion, our study provides epidemiological evidence to confirmed the deleterious effects of TCS on BC and indicated the mediating effect of oxidative stress and RTL on the correlation between TCS and BC risk. Moreover, exploring the contribution of TCS to BC can clarify the biological mechanisms of TCS exposure, provide new clues for the pathogenesis of BC, which is of great significance to improving public health systems.
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Affiliation(s)
- Xiaomin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linyun Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lu Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Tianyi Dong
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tianrun Ye
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Heng Li, ; Haijie Li, ; Ying Zhu, ; Xiaoping Miao,
| | - Haijie Li
- Department of Gastrointestinal Cancer Research Institute, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Heng Li, ; Haijie Li, ; Ying Zhu, ; Xiaoping Miao,
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University; Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, China
- *Correspondence: Heng Li, ; Haijie Li, ; Ying Zhu, ; Xiaoping Miao,
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Heng Li, ; Haijie Li, ; Ying Zhu, ; Xiaoping Miao,
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Lin L, Li S, Hu S, Yu W, Jiang B, Mao C, Li G, Yang R, Miao X, Jin M, Gu Y, Lu E. UCHL1 Impairs Periodontal Ligament Stem Cell Osteogenesis in Periodontitis. J Dent Res 2023; 102:61-71. [PMID: 36112902 DOI: 10.1177/00220345221116031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Periodontitis comprises a series of inflammatory responses resulting in alveolar bone loss. The suppression of osteogenesis of periodontal ligament stem cells (PDLSCs) by inflammation is responsible for impaired alveolar bone regeneration, which remains an ongoing challenge for periodontitis therapy. Ubiquitin C-terminal hydrolase L1 (UCHL1) belongs to the family of deubiquitinating enzymes, which was found to play roles in inflammation previously. In this study, the upregulation of UCHL1 was identified in inflamed PDLSCs isolated from periodontitis patients and in healthy PDLSCs treated with tumor necrosis factor-α or interleukin-1β, and the higher expression level of UCHL1 was accompanied with the impaired osteogenesis of PDLSCs. Then UCHL1 was inhibited in PDLSCs using the lentivirus or inhibitor, and the osteogenesis of PDLSCs suppressed by inflammation was rescued by UCHL1 inhibition. Mechanistically, the negative effect of UCHL1 on the osteogenesis of PDLSCs was attributable to its negative regulation of mitophagy-dependent bone morphogenetic protein 2/Smad signaling pathway in periodontitis-associated inflammation. Furthermore, a ligature-induced murine periodontitis model was established, and the specific inhibitor of UCHL1 was administrated to periodontitis mice. The histological results showed increased active osteoblasts on alveolar bone surface and enhanced alveolar bone regeneration when UCHL1 was inhibited in periodontitis mice. Besides, the therapeutic effects of UCHL1 inhibition on ameliorating periodontitis were verified, as indicated by less bone loss and reduced inflammation. Altogether, our study proved UCHL1 to be a key negative regulator of the osteogenesis of PDLSCs in periodontitis and suggested that UCHL1 inhibition holds promise for alveolar bone regeneration in periodontitis treatment.
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Affiliation(s)
- L Lin
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - S Li
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - S Hu
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - W Yu
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - B Jiang
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - C Mao
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - G Li
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - R Yang
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - X Miao
- Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - M Jin
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Y Gu
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - E Lu
- Department of Stomatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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21
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Thomas H, Miao X, Ferguson D, Krishnamurthy U, Feng M, Scholey J. Contrast-Enhanced 4D MRI for Internal Target Volume Generation in Treatment Planning for Liver Tumors. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.2192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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22
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Chen C, Cai Y, Liu Y, Chen S, Li Y, Zhang F, Zhang M, Lu Z, Ying P, Huang J, Fan L, Cai X, Ning C, Wang W, Jiang Y, Zhang H, Yang S, Wang Z, Wang X, Zhang SK, Huang C, Xu B, Fu Z, Song Q, Jin M, Chen K, Chen H, Dai M, Miao X, Yang X, Zhu Y, Tian J. Pan-cancer analysis of microbiome quantitative trait loci. Cancer Res 2022; 82:3449-3456. [PMID: 35972351 DOI: 10.1158/0008-5472.can-22-1854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/09/2022] [Accepted: 08/08/2022] [Indexed: 11/16/2022]
Abstract
Microorganisms are commonly detected in tumor tissues, and the species and abundance have been reported to affect cancer initiation, progression, and therapy. Host genetics have been associated with gut microbial abundances, while the relationships between genetic variants and the cancer microbiome still require systematic interrogation. Therefore, identification of cancer microbiome quantitative trait loci (mbQTL) across cancer types might elucidate the contributions of genetic variants to tumor development. Using genotype data from The Cancer Genome Atlas and microbial abundance levels from Kraken-derived data, we developed a computational pipeline to identify mbQTLs in 32 cancer types. This systematically identified 38,660 mbQTLs across cancers, ranging 50 in endometrial carcinoma to 3,133 in thyroid carcinoma. Furthermore, a strong enrichment of mbQTLs was observed among transcription factor binding sites and chromatin regulatory elements, such as H3K27ac. Notably, mbQTLs were significantly enriched in cancer GWAS loci and explained an average of 2% of cancer heritability, indicating that mbQTLs could provide additional insights into cancer etiology. Correspondingly, 24,443 mbQTLs overlapping with GWAS linkage disequilibrium regions were identified. Survival analyses identified 318 mbQTLs associated with patient overall survival. Moreover, we uncovered 135,248 microbiome-immune infiltration associations and 166,603 microbiome-drug response associations that might provide clues for microbiome-based biomarkers. Finally, a user-friendly database, Cancer-mbQTL (http://canmbqtl.whu.edu.cn/#/), was constructed for users to browse, search, and download data of interest. This study provides a valuable resource for investigating the roles of genetics and microorganisms in human cancer.
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Affiliation(s)
| | - Yimin Cai
- Wuhan University, Wuhan, Hubei, China
| | | | | | - Yanmin Li
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fuwei Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ming Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zequn Lu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Pingting Ying
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinyu Huang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Linyun Fan
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaomin Cai
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Caibo Ning
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wenzhuo Wang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | | | | | | | | | - Xiaoyang Wang
- Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, China
| | - Shao-Kai Zhang
- The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | | | - Bin Xu
- Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhenming Fu
- Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Qibin Song
- Renmin Hospital of Wuhan University, Wuhan, China
| | - Mingjuan Jin
- Zhejiang University, School of Medicine, Hangzhou, Zhejiang, China
| | - Kun Chen
- Zhejiang University, School of Medicine, Hangzhou, Zhejiang, China
| | - Hongda Chen
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Min Dai
- Peking Union Medical College Hospital, Beijing, China
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Miao X, Zhou S, Wang C. A DFT Study on the Adsorption of Carboxyl-Containing Monomers on CH (001) Surface. Russ J Phys Chem B 2022. [DOI: 10.1134/s199079312204011x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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24
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Zhu Y, Peng X, Wang X, Ying P, Wang H, Li B, Li Y, Zhang M, Cai Y, Lu Z, Niu S, Yang N, Zhong R, Tian J, Chang J, Miao X. Systematic analysis on expression quantitative trait loci identifies a novel regulatory variant in ring finger and WD repeat domain 3 associated with prognosis of pancreatic cancer. Chin Med J (Engl) 2022; 135:1348-1357. [PMID: 35830250 PMCID: PMC9433068 DOI: 10.1097/cm9.0000000000002180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Pancreatic adenocarcinoma (PAAD) is an extremely lethal malignancy. Identification of the functional genes and genetic variants related to PAAD prognosis is important and challenging. Previously identified prognostic genes from several expression profile analyses were inconsistent. The regulatory genetic variants that affect PAAD prognosis were largely unknown. METHODS Firstly, a meta-analysis was performed with seven published datasets to systematically explore the candidate prognostic genes for PAAD. Next, to identify the regulatory variants for those candidate genes, expression quantitative trait loci analysis was implemented with PAAD data resources from The Cancer Genome Atlas. Then, a two-stage association study in a total of 893 PAAD patients was conducted to interrogate the regulatory variants and find the prognostic locus. Finally, a series of biochemical experiments and phenotype assays were carried out to demonstrate the biological function of variation and genes in PAAD progression process. RESULTS A total of 128 genes were identified associated with the PAAD prognosis in the meta-analysis. Fourteen regulatory loci in 12 of the 128 genes were discovered, among which, only rs4887783, the functional variant in the promoter of Ring Finger and WD Repeat Domain 3 ( RFWD3 ), presented significant association with PAAD prognosis in both stages of the population study. Dual-luciferase reporter and electrophoretic mobility shift assays demonstrated that rs4887783-G allele, which predicts the worse prognosis, enhanced the binding of transcript factor REST, thus elevating RFWD3 expression. Further phenotypic assays revealed that excess expression of RFWD3 promoted tumor cell migration without affecting their proliferation rate. RFWD3 was highly expressed in PAAD and might orchestrate the genes in the DNA repair process. CONCLUSIONS RFWD3 and its regulatory variant are novel genetic factors for PAAD prognosis.
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Affiliation(s)
- Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei 430072, China
| | - Xiating Peng
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Pingting Ying
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Siyuan Niu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei 430072, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei 430030, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, Hubei 430072, China
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25
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Tian J, Chen C, Rao M, Zhang M, Lu Z, Cai Y, Ying P, Li B, Wang H, Wang L, Li Y, Huang J, Fan L, Cai X, Ning C, Li Y, Zhang F, Wang W, Jiang Y, Liu Y, Wang M, Li H, Huang C, Yang Z, Chang J, Zhu Y, Yang X, Miao X. Aberrant RNA splicing is a primary link between genetic variation and pancreatic cancer risk. Cancer Res 2022; 82:2084-2096. [PMID: 35363263 DOI: 10.1158/0008-5472.can-21-4367] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 02/15/2022] [Accepted: 03/30/2022] [Indexed: 11/16/2022]
Abstract
Understanding the genetic variation underlying transcript splicing is essential for fully dissecting the molecular mechanisms of common diseases. The available evidence from splicing quantitative trait locus (sQTL) studies using pancreatic ductal adenocarcinoma (PDAC) tissues have been limited to small sample sizes. Here we present a genome-wide sQTL analysis to identify single nucleotide polymorphisms (SNPs) that control mRNA splicing in 176 PDAC samples from TCGA. From this analysis, 16,175 sQTLs were found to be significantly enriched in RNA binding protein (RBP) binding sites and chromatin regulatory elements and overlapped with known loci from PDAC genome-wide association studies (GWAS). sQTLs and expression QTLs (eQTL) showed mostly non-overlapping patterns, suggesting sQTLs provide additional insights into the etiology of disease. Target genes affected by sQTLs were closely related to cancer signaling pathways, high mutational burden, immune infiltration, and pharmaceutical targets, which will be helpful for clinical applications. Integration of a large-scale population consisting of 2,782 PDAC patients and 7,983 healthy controls identified an sQTL variant rs1785932-T allele that promotes alternative splicing of ELP2 exon 6 and leads to a lower level of the ELP2 full-length isoform (ELP2_V1) and a higher level of a truncated ELP2 isoform (ELP2_V2), resulting in decreased risk of PDAC (OR=0.83, 95%CI=0.77-0.89, P=1.16×10-6). The ELP2_V2 isoform functioned as a potential tumor suppressor gene, inhibiting PDAC cell proliferation by exhibiting stronger binding affinity to JAK1/STAT3 than ELP2_V1 and subsequently blocking the pathological activation of the p-STAT3 pathway. Collectively, these findings provide an informative sQTL resource and insights into the regulatory mechanisms linking splicing variants to PDAC risk.
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Affiliation(s)
| | | | | | - Ming Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zequn Lu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yimin Cai
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Pingting Ying
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Li
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Haoxue Wang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lu Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei, China
| | - Yao Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, China
| | - Jinyu Huang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Linyun Fan
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaomin Cai
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Caibo Ning
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yanmin Li
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fuwei Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wenzhuo Wang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | | | | | - Min Wang
- Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Heng Li
- Tongji Hospital, Wuhan, Hubei, China
| | | | | | - Jiang Chang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China
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26
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Zhong R, He H, Jin M, Lu Z, Deng Y, Liu C, Shen N, Li J, Wang H, Ying P, Li B, Zeng Q, Lu Q, Cheng L, Zhu Y, Miao X, Tian J. Genome-wide gene-bisphenol A, F and triclosan interaction analyses on urinary oxidative stress markers. Sci Total Environ 2022; 807:150753. [PMID: 34619205 DOI: 10.1016/j.scitotenv.2021.150753] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 09/28/2021] [Accepted: 09/29/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Bisphenols and triclosan (TCS) are common endocrine disrupters (EDCs) that may induce oxidative stress. However, there is limited information as to whether these EDCs interact with genetic variants to modify the levels of oxidative stress on a genome-wide scale. METHODS We first performed a genome-wide scan among a Chinese population and also measured three urinary EDCs, including bisphenol A (BPA), bisphenol F (BPF) and TCS, and three urinary oxidative stress markers [4-hydroxy-2-nonenal-mercapturic acid (HNE-MA), 8-iso-prostaglandin-F2α (8-isoPGF2α) and 8-hydroxy-deoxyguanosine (8-OHdG)]. Subsequently, we examined interactions between three urinary EDCs and nearly 4.6 million genetic variants for three urinary oxidative stress markers by the general linear model. RESULTS Urinary BPA, BPF and TCS were positively associated with HNE-MA, 8-isoPGF2α and 8-OHdG. Significant rs6855040 (4p15.32/between SNORA75B and QDPR)-BPA, rs1112943 (4q35.1/SNX25)-TCS interactions were associated with the 8-isoPGF2α levels (all P < 5 × 10-8). In addition, rs4656116 (1p22.3/CACL1), rs16958760 (17p11.2/between USP43 and DHRS7C) and rs11651078 (17p11.2/LOC339260) showed significant gene-TCS interactions with 8-OHdG (all P < 5 × 10-8). The gene-level analysis found significant interaction between SNX25 and TCS for 8-isoPGF2α levels (P < 2.12 × 10-6). CONCLUSION Our results identify several gene-EDCs interactions for oxidative stress, highlighting that EDCs may modify the effect of genetic variants on oxidative stress.
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Affiliation(s)
- Rong Zhong
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng He
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Meng Jin
- Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yao Deng
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Zhuhai Precision Medical Center, Zhuhai People's Hospital (Zhuhai hospital affiliated with Jinan University), Zhuhai, China
| | - Chong Liu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pingting Ying
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Li
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiang Zeng
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qing Lu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Xiaoping Miao
- School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Jianbo Tian
- School of Health Sciences, Wuhan University, Wuhan 430071, China.
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He H, Deng Y, Wan H, Shen N, Li J, Zeng Q, Chang J, Lu Q, Miao X, Tian J, Zhong R. Urinary bisphenol A and its interaction with CYP17A1 rs743572 are associated with breast cancer risk. Chemosphere 2022; 286:131880. [PMID: 34426286 DOI: 10.1016/j.chemosphere.2021.131880] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 07/26/2021] [Accepted: 08/11/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVE Bisphenol A (BPA), a common endocrine disrupter, can be activated by cytochrome P450 (CYP) metabolizing enzymes and might influence the development of breast cancer (BC). We hypothesized that BPA could interact with CYP genes, synergistically contributing to the BC risk. METHODS Urinary BPA was measured in a total of 302 newly diagnosed BC patients and 302 healthy controls by ultra-high performance liquid chromatography-high resolution mass spectrometry. A set of seven CYP gene polymorphisms was genotyped by using the Sequenom MassARRAY system. A multivariate logistic regression model was used to assess the associations of BPA and BPA-SNP interaction with BC risk. RESULTS BC patients had a higher urinary BPA concentration than healthy individuals (P < 0.001). Each 1-unit increase in log-transformed urinary BPA was associated with a 54 % increased BC risk [95 % confidence interval (CI), 1.34-1.77, P < 0.001]. Individuals with the CYP19A1 rs1902580 GA + AA genotype showed a significantly higher BC risk than those with the GG genotype (OR = 1.45, 95 % CI, 1.01-2.09, P < 0.05). A significant BPA-CYP17A1 rs743572 interaction was found to be associated with a higher risk of BC (Pinteraction = 0.020). Compared with low-BPA individuals carrying CYP17A1 rs743572 GG genotypes, high-BPA individuals with the GA + AA genotype had a higher BC risk, with an odds ratio of 2.49 (95 % CI, 1.52-4.13, P < 0.05). CONCLUSIONS The positive association of BPA exposure with BC risk might be modified by CYP17A1 rs743572, providing evidence for the interaction effect of environment-genes on the etiology of BC.
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Affiliation(s)
- Heng He
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yao Deng
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Zhuhai Precision Medical Center, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Zhuhai, China
| | - Hao Wan
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiang Zeng
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qing Lu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Rong Zhong
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Zhou S, Zhu Q, Liu H, Jiang S, Zhang X, Peng C, Yang G, Li J, Cheng L, Zhong R, Zeng Q, Miao X, Lu Q. Associations of polycyclic aromatic hydrocarbons exposure and its interaction with XRCC1 genetic polymorphism with lung cancer: A case-control study. Environ Pollut 2021; 290:118077. [PMID: 34523522 DOI: 10.1016/j.envpol.2021.118077] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 08/27/2021] [Accepted: 08/29/2021] [Indexed: 06/13/2023]
Abstract
Humans are extensively exposed to polycyclic aromatic hydrocarbons (PAHs) daily via multiple pathways. Epidemiological studies have demonstrated that occupational exposure to PAHs increases the risk of lung cancer, but related studies in the general population are limited. Hence, we conducted a case-control study among the Chinese general population to investigate the associations between PAHs exposure and lung cancer risk and analyze the modifications of genetic polymorphisms in DNA repair genes. In this study, we enrolled 122 lung cancer cases and 244 healthy controls in Wuhan, China. Urinary PAHs metabolites were determined by gas chromatography-mass spectrometry, and rs25487 in X-ray repair cross-complementation 1 (XRCC1) gene was genotyped by the Agena Bioscience MassARRAY System. Then, multivariable logistic regression models were performed to estimate the potential associations. We found that urinary hydroxynaphthalene (OH-Nap), hydroxyphenanthrene (OH-Phe) and the sum of hydroxy PAHs (∑OH-PAHs) levels were significantly higher in lung cancer cases than those in controls. After adjusting for gender, age, BMI, smoking status, smoking pack-years, drinking status and family history, urinary ∑OH-Nap and ∑OH-Phe levels were positively associated with lung cancer risk, with dose-response relationships. Compared with those in the lowest tertiles, individuals in the highest tertiles of ∑OH-Nap and ∑OH-Phe had a 2.13-fold (95% CI: 1.10, 4.09) and 2.45-fold (95% CI: 1.23, 4.87) increased risk of lung cancer, respectively. Effects of gender, age, smoking status and smoking pack-years on the associations of PAHs exposure with lung cancer risk were shown in the subgroup analysis. Furthermore, associations of urinary ∑OH-Nap and ∑OH-PAHs levels with lung cancer risk were modified by XRCC1 rs25487 (Pinteraction ≤ 0.025), and were more pronounced in wild-types of rs25487. These findings suggest that environmental exposure to naphthalene and phenanthrene is associated with increased lung cancer risk, and polymorphism of XRCC1 rs25487 might modify the naphthalene exposure-related lung cancer effect.
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Affiliation(s)
- Shuang Zhou
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Qiuqi Zhu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Huimin Liu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Shunli Jiang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China; Key Laboratory of Occupational Health and Environmental Medicine, Department of Public Health, Jining Medical University, 133 Hehua Road, Jining, Shandong, 272067, China
| | - Xu Zhang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Cheng Peng
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Guanlin Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Road, Wuhan, Hubei, 430030, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Road, Wuhan, Hubei, 430030, China
| | - Rong Zhong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Qiang Zeng
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Xiaoping Miao
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Qing Lu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, China.
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He J, Li Z, Wang R, Nie H, Wang F, Yuan J, Miao X, Yao P, Wei S, Zhang X, Guo H, Yang H, Wu T, He M. Association of blood pressure and long-term change with chronic kidney disease risk among Chinese adults with different glucose metabolism according to the 2017 ACC/AHA guidelines. J Clin Hypertens (Greenwich) 2021; 23:2080-2088. [PMID: 34773360 PMCID: PMC8696214 DOI: 10.1111/jch.14371] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/03/2021] [Accepted: 09/19/2021] [Indexed: 12/15/2022]
Abstract
Whether the definition of hypertension according to 2017 AHA/ACC guidelines and blood pressure (BP) changes was related to the increased risk of chronic kidney disease (CKD) remained debated. This prospective cohort study aimed to investigate the association of BP and long‐term BP change with CKD risk with different glucose metabolism according to the new hypertension guidelines. This study examined 12 951 participants and 11 183 participants derived from the older people cohort study, respectively. Participants were divided into three groups based on blood glucose and the risks were assessmented by the logistic regression model. During a 10 years of follow‐up period, 2727 individuals developed CKD (21.1%). Compared with those with BP < 130/80 mmHg, individuals with increased BP levels had significantly increased risk of incident CKD. Participants with BP of 130–139/80–89 or ≥140/90 mmHg had 1.51‐ and 1.89‐fold incident risk of CKD in patients with diabetes mellitus (DM). Compared with individuals with stable BP (−5 to 5 mmHg), the risk of CKD was reduced when BP decreased by 5 mmHg or more and increased when BP increased ≥5 mmHg among normoglycemia and prediabetes participants. Similar results were observed for rapid estimated glomerular filtration rate (eGFR) decline. In conclusion, the BP of 130–139/80–89 mmHg combined with prediabetes or DM had an increased risk of incident CKD and rapid eGFR decline in older people. Long‐term changes of BP by more than 5 mmHg among normoglycemia or prediabetes were associated with the risk of incident CKD and rapid eGFR decline.
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Affiliation(s)
- Jia He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhaoyang Li
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ruixin Wang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hongli Nie
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fei Wang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jing Yuan
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoping Miao
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ping Yao
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Sheng Wei
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huan Guo
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Handong Yang
- Dongfeng Central Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan, Hubei, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Wang H, Yang B, Cai X, Cheng X, Shen N, Liu L, Li J, Wang Y, He H, Ying P, Li B, Lu Z, Yang N, Wang X, Zhang F, Li Y, Wang W, Ning C, Zhu Y, Chang J, Miao X, Tian J, Zhong R. Hepatocellular carcinoma risk variant modulates lncRNA HLA-DQB1-AS1 expression via a long-range enhancer-promoter interaction. Carcinogenesis 2021; 42:1347-1356. [PMID: 34665859 DOI: 10.1093/carcin/bgab095] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/15/2021] [Accepted: 10/18/2021] [Indexed: 01/01/2023] Open
Abstract
Substantial evidence highlighted the critical role of long non-coding RNAs (lncRNA) in driving hepatocarcinogenesis. We hypothesized that functional variants in genome-wide association studies (GWASs) associated loci might alter the expression levels of lncRNAs and contribute to the development of hepatocellular carcinoma (HCC). Here, we prioritized potentially cis-expression quantitative trait loci-based single nucleotide polymorphism (SNP)-lncRNA association together with the physical interaction by the analyses from Hi-C data in GWAS loci of chronic hepatitis B and HCC. Subsequently, by leveraging two-stage case-control study (1738 hepatitis B [HBV]) related HCC cases and 1988 HBV persistent carriers) and biological assays, we identified that rs2647046 was significantly associated with HCC risk (odds ratio = 1.26, 95% CI = 1.11 to 1.43, P = 4.14 × 10-4). Luciferase reporter assays and electrophoretic mobility shift assays showed that rs2647046 A allele significantly increased transcriptional activity via influencing transcript factor binding affinity. Allele-specific chromosome conformation capture assays revealed that enhancer with rs2647046 interacted with the HLA-DQB1-AS1 promoter to allele-specifically influence its expression by CTCF-mediated long-range loop. Cell proliferation assays indicated that HLA-DQB1-AS1 is a potential oncogene in HCC. Our study showed HLA-DQB1-AS1 regulated by a causal SNP in a long-range interaction manner conferred the susceptibility to HCC, suggesting an important mechanism of modulating lncRNA expression for risk-associated SNPs in the etiology of HCC.
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Affiliation(s)
- Haoxue Wang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Beifang Yang
- Hubei Institute for Infectious Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Xiaomin Cai
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Xiang Cheng
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Li Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ying Wang
- Department of Virology, Wuhan Centers for Disease Prevention and Control, Wuhan, Hubei, China
| | - Heng He
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Pingting Ying
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Bin Li
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Wenzhuo Wang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Ying Zhu
- School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Xiaoping Miao
- School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Jianbo Tian
- School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
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Deng Y, He H, Wan H, Shen N, Li J, Zhang S, Zeng Q, Chang J, Lu Q, Zhong R, Miao X. Bisphenol A exposure, interaction with genetic variants and colorectal cancer via mediating oxidative stress biomarkers. Environ Pollut 2021; 287:117630. [PMID: 34182385 DOI: 10.1016/j.envpol.2021.117630] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 05/31/2021] [Accepted: 06/19/2021] [Indexed: 06/13/2023]
Abstract
Bisphenol A (BPA) may induce oxidative stress as well as the toxicity of colon cancer cells. We hypothesized that BPA exposure and interactions with genetic variants might be associated with colorectal cancer (CRC) risk, and the association might be partly mediated by oxidative stress. We measured urinary BPA and three oxidative stress markers [8-iso-prostaglandinF2α (8-isoPGF2α), 8-hydroxydeoxyguanosine (8-OHdG) and 4-hydroxy-2-nonenal-mercapturic acid (HNE-MA)] in 275 new CRC cases and 538 healthy controls. A set of 25 genetic variations in 12 candidate DNA repair genes and 5 metabolic enzyme genes were genotyped by Sequenom MassARRAY approach. In multivariable logistic regression, significant positive associations of CRC risk with BPA, 8-OHdG and HNE-MA were observed. Additionally, 8-OHdG, HNE-MA and 8-isoPGF2α were significantly positively associated with BPA (P < 0.05). The mediation analysis showed BPA-associated HNE-MA significantly mediated 11.81% of the effect of BPA on CRC risk. Moreover, BPA was found to interact with ERCC5 rs17655 and rs2296147 (both Pmultiplicative < 0.05) to increase CRC risk. In brief, our results suggested BPA was associated with CRC risk and the positive association of BPA with CRC risk might be partly mediated by the oxidative stress HNE-MA. BPA might interact with ERCC5 rs17655 and rs2296147 to increase CRC risk.
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Affiliation(s)
- Yao Deng
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Zhuhai Precision Medical Center, Zhuhai People's Hospital (Zhuhai Hospital affiliated with Jinan University), Zhuhai, China
| | - Heng He
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Wan
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiang Zeng
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qing Lu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Zhang Y, Lu M, Lu B, Liu C, Ma Y, Liu L, Miao X, Qin J, Chen H, Dai M. Leveraging Fecal Microbial Markers to Improve the Diagnostic Accuracy of the Fecal Immunochemical Test for Advanced Colorectal Adenoma. Clin Transl Gastroenterol 2021; 12:e00389. [PMID: 34408121 PMCID: PMC8373536 DOI: 10.14309/ctg.0000000000000389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 07/08/2021] [Indexed: 02/06/2023] Open
Abstract
INTRODUCTION Fecal immunochemical tests (FITs) detect colorectal adenoma inefficiently. The gut microbiota participates in colorectal cancer development. We aimed to explore fecal microbial signatures for advanced adenomas and evaluate their diagnostic value and complementary capacity to FIT. METHODS Using 16S rRNA sequencing, we studied gut microbiota in feces from 1,546 subjects in a screening setting, including 268 patients with advanced adenomas, 490 patients with nonadvanced adenomas, and 788 healthy subjects. Feature selections were performed using linear discriminant analysis effect size, multivariate association with linear models, and least absolute shrinkage and selection operator. The diagnostic performance of microbial signatures and their auxiliary role to FITs and the added value of the Asia-Pacific Colorectal Screening score were evaluated. We applied 0.632+ bootstrapping to adjust the potential overfitting. RESULTS We identified 13 microbial signatures to show the joint diagnostic value for advanced adenoma, with genus Tyzzerella 4 demonstrating the highest adjusted area under the curve (AUC) of 0.545 (95% confidence interval [CI], 0.520-0.610). The 13-bacteria increased the adjusted AUC to 0.607 (95% CI, 0.548-0.660). Compared with individual FIT (adjusted AUC = 0.527; 95% CI, 0.519-0.571), 13-bacteria and FITs collectively reached an adjusted AUC of 0.641 (95% CI, 0.579-0.691). At cutoff values yielding specificities of 90% and 80%, the adjusted sensitivities were 28.4% (95% CI, 19.3-36.8) and 41.1% (95% CI, 29.9-49.4), respectively. The Asia-Pacific Colorectal Screening score further boosted the adjusted AUC to 0.706 (95% CI, 0.648-0.750). DISCUSSION In this study using fecal samples from a screening setting, the identified microbial signatures could complement FITs for detecting advanced adenomas. Gut microbiota can act as a promising tool to optimize the current colorectal cancer screening modalities.
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Affiliation(s)
- Yuhan Zhang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ming Lu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bin Lu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chengcheng Liu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yiming Ma
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Li Liu
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | | | - Hongda Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Min Dai
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Chen H, Liu L, Lu M, Zhang Y, Lu B, Zhu Y, Tian J, Li X, Nie S, Miao X, Dai M. Implications of Lifestyle Factors and Polygenic Risk Score for Absolute Risk Prediction of Colorectal Neoplasm and Risk-Adapted Screening. Front Mol Biosci 2021; 8:685410. [PMID: 34336927 PMCID: PMC8324207 DOI: 10.3389/fmolb.2021.685410] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/15/2021] [Indexed: 12/24/2022] Open
Abstract
Background: Estimation of absolute risk of developing colorectal neoplasm is essential for personalized colorectal cancer (CRC) screening. We developed models to determine relative and absolute risks of colorectal neoplasm based on lifestyle and genetic variants and to validate their application in risk-adapted screening. Methods: We prospectively collected data from 203 advanced neoplasms, 464 non-advanced adenomas, and 1,213 healthy controls from a CRC screening trial in China in 2018–2019. The risk prediction model based on four lifestyle factors and a polygenic risk score (PRS) consisted of 19 CRC-associated single-nucleotide polymorphisms. We assessed the relative and 10-year absolute risks of developing colorectal neoplasm and the yield of a risk-adapted screening approach incorporating risk models, fecal immunochemical test, and colonoscopy. Results: Compared to the participants with favorable lifestyle and lower PRS, those with unfavorable lifestyle and higher PRS had 2.87- and 3.79-fold higher risk of colorectal neoplasm in males and females, respectively. For a 50-year-old man or a 50-year-old woman with the highest risk profile, the estimated 10-year absolute risk of developing colorectal neoplasm was 6.59% (95% CI: 6.53–6.65%) and 4.19% (95% CI: 4.11–4.28%), respectively, compared to 2.80% (95% CI: 2.78–2.81%) for men and 2.24% (95% CI: 2.21–2.27%) for women with the lowest risk profile. The positive predictive value for advanced neoplasm was 31.7%, and the number of colonoscopies needed to detect one advanced neoplasm was 3.2. Conclusion: The risk models, absolute risk estimates, and risk-adapted screening presented in our study would contribute to developing effective personalized CRC prevention and screening strategies.
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Affiliation(s)
- Hongda Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Li Liu
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming Lu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuhan Zhang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bin Lu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xinying Li
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaofa Nie
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Dai
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Wang H, Zhu Y, Chen H, Yang N, Wang X, Li B, Ying P, He H, Cai Y, Zhang M, Niu S, Li Y, Lu Z, Peng X, Zou D, Zhong R, Chang J, Dai M, Tian J, Miao X. Colorectal cancer risk variant rs7017386 modulates two oncogenic lncRNAs expression via ATF1-mediated long-range chromatin loop. Cancer Lett 2021; 518:140-151. [PMID: 34274452 DOI: 10.1016/j.canlet.2021.07.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/26/2021] [Accepted: 07/12/2021] [Indexed: 01/02/2023]
Abstract
The activating transcription factor 1 (ATF1) has been identified as a vital pathogenic factor in the progression of colorectal cancer (CRC), whiles, the precise regulatory mechanisms remain elusive. Here, we comprehensively characterized the ATF1 cistrome by RNA-seq and ChIP-seq assays in CRC cell lines. As the results, we identified 358 genes differentially regulated and 15,029 ATF1 binding sites and demonstrated that ATF1 was widely involved in major signaling pathways in CRC, such as Wnt, TNF, Jak-STAT. Subsequently, by the expression quantitative trait loci (eQTL) analyses, we found that rs7017386 was associated with the expression of CCAT1 and PVT1 in the Wnt pathway. By a two-stage population study with 6,131 CRC cases and 10,022 healthy controls, we identified the variant was associated with CRC risk. Mechanistically, we found rs7017386 allele-specifically enhanced the binding affinity of ATF1 and promoted the expressions of PVT1 and CCAT1, via forming a long-range chromatin loop. Moreover, those two lncRNAs could synergistically facilitate c-Myc expression to activate the Wnt pathway in CRC progression. Our findings not only demonstrated the transcriptomic profiling of ATF1 in CRC, but also provided important clues for the etiology of CRC.
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Affiliation(s)
- Haoxue Wang
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongda Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pingting Ying
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng He
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Siyuan Niu
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiating Peng
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Danyi Zou
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Dai
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, And the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Liu L, Chen HG, Li Y, Li H, Li J, Wang Y, Yao S, Qin C, Tong S, Yuan X, Luo X, Miao X, Pan A, Liu Z, Cheng L. Temporal Profiles of Antibody Responses, Cytokines, and Survival of COVID-19 Patients: A Retrospective Cohort. Engineering (Beijing) 2021; 7:958-965. [PMID: 34026297 PMCID: PMC8129785 DOI: 10.1016/j.eng.2021.04.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 04/15/2021] [Accepted: 04/21/2021] [Indexed: 05/08/2023]
Abstract
The longitudinal immunologic status of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients and its association with the clinical outcome are barely known. Thus, we sought to analyze the temporal profiles of specific antibodies, as well as the associations between the antibodies, proinflammatory cytokines, and survival of patients with coronavirus disease 2019 (COVID-19). A total of 1830 laboratory-confirmed COVID-19 cases were recruited. The temporal profiles of the virus, antibodies, and cytokines of the patients until 12 weeks since illness onset were fitted by the locally weighted scatter plot smoothing method. The mediation effect of cytokines on the associations between antibody responses and survival were explored by mediation analysis. Of the 1830 patients, 1435 were detectable for SARS-CoV-2, while 395 were positive in specific antibodies only. Of the 1435 patients, 2.4% presented seroconversion for neither immunoglobulin G (IgG) nor immunoglobulin M (IgM) during hospitalization. The seropositive rates of IgG and IgM were 29.6% and 48.1%, respectively, in the first week, and plateaued within five weeks. For the patients discharged from the hospital, the IgM decreased slowly, while high levels of IgG were maintained at around 188 AU·mL-1 for the 12 weeks since illness onset. In contrast, in the patients who subsequently died, IgM declined rapidly and IgG dropped to 87 AU·mL-1 at the twelfth week. Elevated interleukin-6, interleukin-8, interleukin-10, interleukin-1β, interleukin-2R, and tumor necrosis factor-α levels were observed in the deceased patients in comparison with the discharged patients, and 12.5% of the association between IgG level and mortality risk was mediated by these cytokines. Our study deciphers the temporal profiles of SARS-CoV-2-specific antibodies within the 12 weeks since illness onset and indicates the protective effect of antibody response on survival, which may help to guide prognosis estimation.
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Affiliation(s)
- Li Liu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Heng-Gui Chen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ying Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Huijun Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shuang Yao
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Chuan Qin
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shutao Tong
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xu Yuan
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xia Luo
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zheng Liu
- Department of Otolaryngology-Head and Neck Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Zhu Y, Tian J, Peng X, Wang X, Yang N, Ying P, Wang H, Li B, Li Y, Zhang M, Cai Y, Lu Z, Niu S, Li Y, Zhong R, Chang J, Miao X. A genetic variant conferred high expression of CAV2 promotes pancreatic cancer progression and associates with poor prognosis. Eur J Cancer 2021; 151:94-105. [PMID: 33975060 DOI: 10.1016/j.ejca.2021.04.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/16/2021] [Accepted: 04/06/2021] [Indexed: 12/12/2022]
Abstract
AIM This study aimed to identify the functional genes and genetic variants associated with the prognosis of pancreatic ductal adenocarcinoma (PDAC) and reveal the mechanism underlying their prognostic roles. METHODS First, we implement a two-stage exome-wide association study in a total of 1070 patients to identify the genetic variant correlated with PDAC prognosis. Then we performed fine mapping through bioinformatics analysis and dual-luciferase reporter assays to reveal the causal functional variant and prognostic gene. Next, we established the gene knockdown, knockout, and overexpression cell lines with small interfering RNA, CRISPR/Cas9, and lentivirus, respectively, and investigated the gene function on cell proliferation and migration in vivo and in vitro. Finally, we performed the RNA-seq to elucidate downstream genes and mechanisms altering PDAC prognosis. RESULTS We identified the CAV1-CAV2 locus tagged by rs8940 was significantly associated with PDAC prognosis, and rs10249656 in the 3'untranslated region of CAV2 was the real functional variant, which upregulated CAV2 expression through abolishing miR-548s binding. We observed upregulated CAV2 in PDAC and the higher expression correlated with worse prognosis. Transient knockdown of CAV2 inhibited PDAC migration without affecting proliferation rate. Knockout of CAV2 suppressed PDAC progression and metastasis, whereas stable overexpression of CAV2 promoted. Overexpressed CAV2 promoted the PDAC progression and metastasis via perturbing genes in the focal adhesion (CCND1, IGTA1, and ZYX) and extracellular matrix organisation (PLOD2, CAST, and ITGA1) pathways mechanically. CONCLUSION These findings shed light on an important role of CAV2 on PDAC progression and the prognostic impact of its genetic variation.
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Affiliation(s)
- Ying Zhu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiating Peng
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Pingting Ying
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Siyuan Niu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Yao Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China.
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Liu S, Li XM, Yuan JB, Li LL, Wang C, Lin XM, Miao X, Shi ZC. MiR-665 inhibits inflammatory response in microglia following spinal cord injury by targeting TREM2. Eur Rev Med Pharmacol Sci 2021; 25:65-70. [PMID: 33506893 DOI: 10.26355/eurrev_202101_24349] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The purpose of this study was to uncover the role of microRNA-665 (miR-665) in protecting inflammatory response in microglia following spinal cord injury (SCI) and the underlying mechanism. PATIENTS AND METHODS The serum levels of miR-665 and TREM2 (triggering receptor expressed on myeloid 2) in SCI patients (n=24) and healthy subjects (n=24) were detected by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Then, the serum levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) were detected by enzyme-linked immunosorbent assay (ELISA). After lipopolysaccharide (LPS) induction in BV2 cells, the relative levels of miR-665 and TREM2 were detected by qRT-PCR, and relative levels of IL-6 and TNF-α in the culture medium were examined by ELISA. Next, TREM2, the target gene of miR-665, was determined by Dual-Luciferase reporter assay, and the relationship between the expression levels of TREM2 and miR-665 in SCI patients and BV2 cells was analyzed. Finally, the regulatory effects of miR-665 and TREM2 on IL-6 and TNF-α levels in the culture medium of LPS-induced BV2 cells were assessed. RESULTS It was found that miR-665 was downregulated in serum of SCI patients and LPS-induced BV2 cells, while TREM2 was upregulated. Silenced miR-665 or overexpressed TREM2 was involved in protecting inflammatory response following SCI. Besides, rescue experiments showed that miR-665 participated in the regulation of inflammatory response following SCI by targeting TREM2. CONCLUSIONS MiR-665 inhibits inflammatory response following SCI by targeting TREM2.
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Affiliation(s)
- S Liu
- Department of Orthopaedics, Changhai Hospital, Second Military Medical University, Shanghai, China.
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Tian J, Lu Z, Niu S, Zhang S, Ying P, Wang L, Zhang M, Cai Y, Dong T, Zhu Y, Zhong R, Wang Z, Chang J, Miao X. Aberrant MCM10 SUMOylation induces genomic instability mediated by a genetic variant associated with survival of esophageal squamous cell carcinoma. Clin Transl Med 2021; 11:e485. [PMID: 34185429 PMCID: PMC8236122 DOI: 10.1002/ctm2.485] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/13/2021] [Accepted: 06/16/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Esophageal squamous cell carcinoma (ESCC) is one of the common gastrointestinal malignancy with an inferior prognosis outcome. DNA replication licensing aberration induced by dysregulation of minichromosome maintenance proteins (MCMs) causes genomic instability and cancer metastasis. SUMOylation modification plays a pivotal role in regulation of genomic integrity, while its dysregulation fueled by preexisting germline variants in cancers remains poorly understood. METHODS Firstly, we conducted two-stage survival analysis consisting of an exome-wide association study in 904 ESCC samples and another independent 503 ESCC samples. Then, multipronged functional experiments were performed to illuminate the potential biological mechanisms underlying the promising variants, and MCM10 influences the ESCC progression. Finally, we tested the effects of MCM10 inhibitors on ESCC cells. RESULTS A germline variant rs2274110 located at the exon 15 of MCM10 was identified to be significantly associated with the prognosis of ESCC patients. Individuals carrying rs2274110-AA genotypes confer a poor survival (hazard ratio = 1.61, 95% confidence interval = 1.35-1.93, p = 1.35 × 10-7 ), compared with subjects carrying rs2274110-AG/GG genotypes. Furthermore, we interestingly found that the variant can increase SUMOylation levels at K669 site (Lys[K]699Arg[R]) of MCM10 protein mediated by SUMO2/3 enzymes, which resulted in an aberrant overexpression of MCM10. Mechanistically, aberrant overexpression of MCM10 facilitated the proliferation and metastasis abilities of ESCC cells in vitro and in vivo by inducing DNA over-replication and genomic instability, providing functional evidence to support our population finding that high expression of MCM10 is extensively presented in tumor tissues of ESCC and correlated with inferior survival outcomes of multiple cancer types, including ESCC. Finally, MCM10 inhibitors Suramin and its analogues were revealed to effectively block the metastasis of ESCC cells. CONCLUSIONS These findings not only demonstrate a potential biological mechanism between aberrant SUMOylation, genomic instability and cancer metastasis, but also provide a promising biomarker aiding in stratifying ESCC individuals with different prognosis, as well as a potential therapeutic target MCM10.
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Affiliation(s)
- Jianbo Tian
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Zequn Lu
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Siyuan Niu
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Shanshan Zhang
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Pingting Ying
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Lu Wang
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Ming Zhang
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Yimin Cai
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Tianyi Dong
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Ying Zhu
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Rong Zhong
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Zhihua Wang
- Department of UrologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Jiang Chang
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
| | - Xiaoping Miao
- Department of Epidemiology and BiostatisticsKey Laboratory for Environment and HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Sciences and TechnologyWuhanChina
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Yang J, Yang FJ, Wang YG, Su GF, Miao X. LncRNA MIR497HG inhibits proliferation and migration of retinal endothelial cells under high-level glucose treatment via miRNA-128-3p/SIRT1 axis. Eur Rev Med Pharmacol Sci 2021; 24:5871-5877. [PMID: 32572899 DOI: 10.26355/eurrev_202006_21479] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The aim of this study was to elucidate the potential influence of MIR497HG on regulating proliferative capacity of human retinal endothelial cells (HRECs). MATERIALS AND METHODS Relative expression levels of MIR497HG, microRNA-128-3p (miRNA-128-3p) and SIRT1 in HRECs treated with different doses of glucose and mannitol were detected by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Dual-Luciferase reporter gene assay was conducted to assess the interaction among MIR497HG, miRNA-128-3p, and SIRT1. In addition, the potential effects of MIR497HG/miRNA-128-3p/SIRT1 axis on proliferative and migratory capacities in HRECs were evaluated by Cell Counting Kit-8 (CCK-8), 5-Ethynyl-2'- deoxyuridine (EdU) and transwell assay, respectively. RESULTS High-level glucose (HG) treatment significantly downregulated MIR497HG and SIRT1 expression, whereas upregulated miRNA-128-3p expression in HRECs (p<0.05). MiRNA-128-3p was the target gene binding MIR497HG, and SIRT1 was the downstream gene of miRNA-128-3p. Overexpression of MIR497HG significantly attenuated proliferative and migratory abilities of HG-induced HRECs (p<0.05). Furthermore, decreased trends were partially reversed by overexpression of miRNA-128-3p or knockdown of SIRT1. CONCLUSIONS MIR497HG is downregulated after HG treatment. In addition, it suppresses the proliferation and migration of HRECs by targeting miRNA-128-3p/SIRT1 axis, thus influencing the progression of diabetic retinopathy.
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Affiliation(s)
- J Yang
- Department of Ophthalmology, The Second Hospital of Jilin University, Changchun, China.
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Zheng YQ, Miao X, Li J, Hu MF, Zhu YS, Li XR, Zhang YJ. Trichostatin A alleviates the process of breast carcinoma by downregulating LPAR5. Eur Rev Med Pharmacol Sci 2021; 24:6417-6425. [PMID: 32572939 DOI: 10.26355/eurrev_202006_21540] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To elucidate the role of histone deacetylase inhibitor Trichostatin A (TSA) in affecting metastasis of breast carcinoma, and its molecular mechanism. PATIENTS AND METHODS LPAR5 levels in breast carcinoma tissues and paracancerous tissues were detected by quantitative real-time polymerase chain reaction (qRT-PCR), and its expression pattern was further verified in breast carcinoma cell lines. The relationship between LPAR5 and prognosis of breast carcinoma patients was analyzed. After TSA induction (100-400 nmol/L) for 6-48 h, the proliferative and migratory abilities of SKBR3 and MDA-MB-231 cells in overexpressing LPAR5 were examined by cell counting kit-8 (CCK-8), transwell and wound healing assay. By constructing a xenograft model in nude mice, the influences of TSA and LPAR5 on in vivo growth of breast carcinoma were examined. RESULTS LPAR5 was upregulated in breast carcinoma samples. High level of LPAR5 predicted higher rates of lymphatic metastasis and distant metastasis, as well as lower overall survival and progression-free survival in breast carcinoma patients. LPAR5 level was dose-dependently downregulated in TSA-induced SKBR3 and MDA-MB-231 cells. In addition, TSA induction dose-dependently declined proliferative ability, and time-dependently attenuated migratory ability in breast carcinoma cells. In vivo overexpression of LPAR5 in nude mice reversed the inhibitory effect of TSA on breast carcinoma growth. CONCLUSIONS TSA induction can suppress proliferative and migratory abilities in breast carcinoma by downregulating LPAR5.
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Affiliation(s)
- Y-Q Zheng
- Department of General Surgery, First Medical Center, PLA General Hospital, Beijing, China.
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Ding T, Wang T, Zhang J, Cui P, Chen Z, Zhou S, Yuan S, Ma W, Zhang M, Rong Y, Chang J, Miao X, Ma X, Wang S. Analysis of Ovarian Injury Associated With COVID-19 Disease in Reproductive-Aged Women in Wuhan, China: An Observational Study. Front Med (Lausanne) 2021; 8:635255. [PMID: 33816526 PMCID: PMC8017139 DOI: 10.3389/fmed.2021.635255] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 02/23/2021] [Indexed: 12/19/2022] Open
Abstract
Objective: This study was intended to investigate the relationship between COVID-19 disease and ovarian function in reproductive-aged women. Methods: Female COVID-19 patients of reproductive age were recruited between January 28 and March 8, 2020 from Tongji Hospital in Wuhan. Their baseline and clinical characteristics, as well as menstrual conditions, were recorded. Differentials in ovarian reserve markers and sex hormones (including anti-Müllerian hormone [AMH], follicle-stimulating hormone [FSH], the ratio of FSH to luteinizing hormone [LH], estradiol [E2], progesterone [P], testosterone [T], and prolactin [PRL] were compared to those of healthy women who were randomly selected and individually matched for age, region, and menstrual status. Uni- and multi-variable hierarchical linear regression analyses were performed to identify risk factors associated with ovarian function in COVID-19 women. Results: Seventy eight patients agreed to be tested for serum hormone, of whom 17 (21.79%) were diagnosed as the severe group and 39 (50%) were in the basal level group. Menstrual status (P = 0.55), menstrual volumes (P = 0.066), phase of menstrual cycle (P = 0.58), and dysmenorrhea history (P = 0.12) were similar without significant differences between non-severe and severe COVID-19 women. Significant lower serum AMH level/proportion (0.19/0.28 vs. 1.12 ng/ml, P = 0.003/0.027; AMH ≤
1.1 ng/ml: 75/70.4 vs. 49.7%, P = 0.009/0.004), higher serum T (0.38/0.39 vs. 0.22 ng/ml, P < 0.001/0.001) and PRL (25.43/24.10 vs. 12.12 ng/ml, P < 0.001/0.001) levels were observed in basal level and the all-COVID-19 group compared with healthy age-matched control. When adjusted for age, menstrual status and parity variations in multivariate hierarchical linear regression analysis, COVID-19 disease was significantly associated with serum AMH (β = −0.191; 95% CI: −1.177–0.327; P = 0.001), T (β = 0.411; 95% CI: 11.154–22.709; P < 0.001), and PRL (β = 0.497; 95% CI: 10.787–20.266; P < 0.001), suggesting an independent risk factor for ovarian function, which accounted for 3.2% of the decline in AMH, 14.3% of the increase in T, and 20.7% of the increase in PRL. Conclusion: Ovarian injury, including declined ovarian reserve and reproductive endocrine disorder, can be observed in women with COVID-19. More attention should be paid to their ovarian function under this pandemic, especially regarding reproductive-aged women. Clinical Trial Number: ChiCTR2000030015.
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Affiliation(s)
- Ting Ding
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Tian Wang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Jinjin Zhang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Pengfei Cui
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Zhe Chen
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Su Zhou
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Suzhen Yuan
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Wenqing Ma
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Minli Zhang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Yueguang Rong
- Department of Pathogen Biology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiangyi Ma
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Shixuan Wang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrical and Gynecological Diseases, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
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Ji P, Chang J, Wei X, Song X, Yuan H, Gong L, Li Y, Ding D, Zhang E, Yan C, Zhu M, Miao X, Wu C, Jin G, Hu Z, Shen H, Ma H. Genetic variants associated with expression of TCF19 contribute to the risk of head and neck cancer in Chinese population. J Med Genet 2021; 59:335-345. [PMID: 34085947 DOI: 10.1136/jmedgenet-2020-107410] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 01/08/2021] [Accepted: 02/02/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Squamous cell carcinoma of the head and neck (SCCHN) is one of the most common cancers worldwide and includes cancers arising from the oral cavity, pharynx and larynx. Genome-wide association studies have found several genetic variants related to the risk of SCCHN; however, they could only explain a small fraction of the heritability. Thus, more susceptibility loci associated with SCCHN need to be identified. METHODS An association study was conducted by genotyping 555 patients with SCCHN and 1367 controls in a Chinese population. Single-variant association analysis was conducted on 63 373 SNPs, and the promising variants were then confirmed by a two-stage validation with 1875 SCCHN cases and 4637 controls. Bioinformatics analysis and functional assays were applied to uncover the potential pathogenic mechanism of the promising variants and genes associated with SCCHN. RESULTS We first identified three novel genetic variants significantly associated with the risk of SCCHN (p=7.45×10-7 for rs2517611 at 6p22.1, p=1.76×10-9 for rs2524182 at 6p21.33 and p=2.17×10-10 for rs3131018 at 6p21.33). Further analysis and biochemical assays showed that rs3094187, which was in a region in high linkage disequilibrium with rs3131018, could modify TCF19 expression by regulating the binding affinity of the transcription factor SREBF1 to the promoter of TCF19. In addition, experiments revealed that the inhibition of TCF19 may affect several important pathways involved in tumourigenesis and attenuate the cell proliferation and migration of SCCHN. CONCLUSION These findings offer important evidence that functional genetic variants could contribute to development of SCCHN and that TCF19 may function as a putative susceptibility gene for SCCHN.
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Affiliation(s)
- Pei Ji
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiaoyu Wei
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Xueyao Song
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Hua Yuan
- Jiangsu Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China
| | - Linnan Gong
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Yuancheng Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Dongsheng Ding
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Erbao Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Chen Wu
- Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China .,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, China
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Chen L, Zhang W, Huang R, Miao X, Li J, Yu D, Li Y, Hsu W, Qiu M, Zhang Z, Li F. The function of Wls in ovarian development. Mol Cell Endocrinol 2021; 522:111142. [PMID: 33359762 DOI: 10.1016/j.mce.2020.111142] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/17/2020] [Accepted: 12/20/2020] [Indexed: 11/26/2022]
Abstract
WNT ligand transporter Wls is essential for the WNT dependent developmental and pathogenic processes. The spatiotemporal expression pattern of Wls was investigated in this study. Immature female mice (21-22 days old) were treated with 5 IU, pregnant mare's serum gonadotrophin (PMSG) to stimulate follicular development, followed 48 h later by injection with 5 IU, human chorionic gonadotrophin (hCG) to induce ovulation. The expression of Wls was stimulated in granulosa cells and the forming corpus luteum after hCG administration. To study the function of Wls, the Amhr2tm3(cre)Bhr strain was used to target deletion of Wls in granulosa cells. The deletion of Wls caused a significant decrease in the fertility of WlsAmhr2-Cre female mice. In female WlsAmhr2-Cre mice, decreased ovarian size and number of antral follicles were found. The number of corpus luteum in immature PMSG/hCG primed WlsAmhr2-Cre mice was much less than that in the control group. Compared with control animals, WlsAmhr2-Cre mice have lower serum progesterone levels. RNA sequencing was used to identify genes regulated by Wls after hCG treatment. Several genes known to be critical for follicle development and steroidogenesis were significantly down-regulated, such as Fshr, Lhcgr, Sfrp4, Inhba, Cyp17a1, Hsd3b1, and Hsd17b7. The expression of WNT signaling downstream target genes, Bmp2 and Cyp19a1, also decreased significantly in WlsAmhr2-Cre ovary. In summary, the findings of this study suggest that Wls is critical for female fertility and luteinization.
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Affiliation(s)
- Luyi Chen
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Wei Zhang
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Ruiqi Huang
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Xiaoping Miao
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Jianying Li
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Dongliang Yu
- Plant Genomics & Molecular Improvement of Colored Fiber Lab, College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, 310018, People's Republic of China
| | - Yan Li
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Wei Hsu
- Department of Biomedical Genetics, Center for Oral Biology, James P Wilmot Cancer Center, University of Rochester Medical Center, Rochester, NY, USA
| | - Mengsheng Qiu
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Zunyi Zhang
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China
| | - Feixue Li
- Zhejiang Key Laboratory of Organ Development and Regeneration, Institute of Developmental and Regenerative Biology, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China.
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Tian J, Zhang M, Jin M, Zhang F, Chu Q, Wang X, Chen C, Yue H, Zhang L, Du R, Zhao D, Zeng Z, Zhao Y, Liu K, Wang M, Hu K, Miao X, Zhang H. Repurposed Tocilizumab in Patients with Severe COVID-19. J Immunol 2021; 206:599-606. [PMID: 33298617 PMCID: PMC7812057 DOI: 10.4049/jimmunol.2000981] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 11/20/2020] [Indexed: 01/08/2023]
Abstract
The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable morbidity and mortality. Tocilizumab, an inhibitor of IL-6, has been widely repurposed as a treatment of severely ill patients without robust evidence supporting its use. In this study, we aimed to systematically describe the effectiveness of treatment and prevention of the cytokine storms in COVID-19 patients with tocilizumab. In this multicentered retrospective and observational cohort study, 65 patients with COVID-19 receiving tocilizumab and 130 not receiving tocilizumab were propensity score matched at a ratio of 2:1 based on age, sex, and comorbidities from January 20, 2020 to March 18, 2020 in Wuhan, China. After adjusting for confounding, the detected risk for in-hospital death was lower in the tocilizumab group versus nontocilizumab group (hazard ratio = 0.47; 95% confidence interval = 0.25-0.90; p = 0.023). Moreover, use of tocilizumab was associated with a lower risk of acute respiratory distress syndrome (odds ratio = 0.23; 95% confidence interval = 0.11-0.45; p < 0.0001). Furthermore, patients had heightened inflammation and more dysregulated immune cells before treatment, which might aggravate disease progression. After tocilizumab administration, abnormally elevated IL-6, C-reactive protein, fibrinogen, and activated partial thromboplastin time decreased. Tocilizumab may be of value in prolonging survival in patients with severe COVID-19, which provided a novel strategy for COVID-19-induced cytokine release syndrome. Our findings could inform bedside decisions until data from randomized, controlled clinical trials become available.
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Affiliation(s)
- Jianbo Tian
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China
| | - Meng Jin
- Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Fengqin Zhang
- Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Qian Chu
- Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China
| | - Huihui Yue
- Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Li Zhang
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; and
| | - Ronghui Du
- Department of Respiratory and Critical Care Medicine, Wuhan Pulmonary Hospital, Wuhan 430030, China
| | - Dong Zhao
- Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Zhaofu Zeng
- Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yang Zhao
- Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Kui Liu
- Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Mengmei Wang
- Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Ke Hu
- Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan 430060, China;
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China;
| | - Huilan Zhang
- Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China;
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Tian J, Cai Y, Li Y, Lu Z, Huang J, Deng Y, Yang N, Wang X, Ying P, Zhang S, Zhu Y, Zhang H, Zhong R, Chang J, Miao X. CancerImmunityQTL: a database to systematically evaluate the impact of genetic variants on immune infiltration in human cancer. Nucleic Acids Res 2021; 49:D1065-D1073. [PMID: 33010176 PMCID: PMC7778991 DOI: 10.1093/nar/gkaa805] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 09/10/2020] [Accepted: 09/17/2020] [Indexed: 12/15/2022] Open
Abstract
Tumor-infiltrating immune cells as integral component of the tumor microenvironment are associated with tumor progress, prognosis and responses to immunotherapy. Genetic variants have been demonstrated to impact tumor-infiltrating, underscoring the heritable character of immune landscape. Therefore, identification of immunity quantitative trait loci (immunQTLs), which evaluate the effect of genetic variants on immune cells infiltration, might present a critical step toward fully understanding the contribution of genetic variants in tumor development. Although emerging studies have demonstrated the determinants of germline variants on immune infiltration, no database has yet been developed to systematically analyze immunQTLs across multiple cancer types. Using genotype data from TCGA database and immune cell fractions estimated by CIBERSORT, we developed a computational pipeline to identify immunQTLs in 33 cancer types. A total of 913 immunQTLs across different cancer types were identified. Among them, 5 immunQTLs are associated with patient overall survival. Furthermore, by integrating immunQTLs with GWAS data, we identified 527 immunQTLs overlapping with known GWAS linkage disequilibrium regions. Finally, we constructed a user-friendly database, CancerImmunityQTL (http://www.cancerimmunityqtl-hust.com/) for users to browse, search and download data of interest. This database provides an informative resource to understand the germline determinants of immune infiltration in human cancer and benefit from personalized cancer immunotherapy.
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Affiliation(s)
- Jianbo Tian
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jinyu Huang
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yao Deng
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Pingting Ying
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Huilan Zhang
- Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory of Environmental Health of Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Affiliation(s)
- Jianbo Tian
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China
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Ying P, Li Y, Yang N, Wang X, Wang H, He H, Li B, Peng X, Zou D, Zhu Y, Zhong R, Miao X, Tian J, Chang J. Identification of genetic variants in m 6A modification genes associated with pancreatic cancer risk in the Chinese population. Arch Toxicol 2021; 95:1117-1128. [PMID: 33474615 DOI: 10.1007/s00204-021-02978-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/04/2021] [Indexed: 12/24/2022]
Abstract
N6-Methyladenosine (m6A) is the most prevalent modification of RNA in eukaryotes, and is associated with many cellular processes and even the development of cancers. We hypothesized that single-nucleotide polymorphisms (SNPs) in m6A modification genes, including its "writers", "erasers" and "readers", might affect the m6A functions and associate with the susceptibility to pancreatic ductal adenocarcinoma (PDAC). We first conducted a two-stage case-control study in Chinese population to interrogate all SNPs in 22 m6A modification genes. In the discovery stage, a total of 2735 SNPs were genotyped in 980 patients and 1991 controls. Then, the promising SNP was replicated in another independent population consisting of 858 cases and 2084 controls. As a result, we found the rs7495 in 3'UTR of hnRNPC was significantly associated with increased risk of PDAC in both stages (combined odds ratio = 1.22, 95% confidence interval = 1.12-1.32, P = 2.39 × 10-6). To further reveal the biological function of rs7495 and hnRNPC, we performed a series of biochemical experiments. Luciferase reporter assays indicated that rs7495G allele promoted hnRNPC expression through disrupting a putative binding site for has-miR-183-3p. Cell viability assay demonstrated that knockdown of hnRNPC suppressed the proliferation of PDAC cells. RNA-seq analysis suggested that as an m6A "reader", hnRNPC played an important role in RNA biological processes. In conclusion, our findings elucidated that rs7495G could confer higher risk of PDAC via promoting the expression of hnRNPC through a miRNA-mediated manner. These results provided a novel insight into the critical role of m6A modification in tumorigenesis.
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Affiliation(s)
- Pingting Ying
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yao Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Heng He
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xiating Peng
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Danyi Zou
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Ding L, Miao X, Lu J, Hu J, Xu X, Zhu H, Xu Q, Zhu S. Comparing the Performance of Different Instruments for Diagnosing Frailty and Predicting Adverse Outcomes among Elderly Patients with Gastric Cancer. J Nutr Health Aging 2021; 25:1241-1247. [PMID: 34866152 DOI: 10.1007/s12603-021-1701-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVES To examine the diagnostic performance of the Tilburg Frailty Indicator (TFI), 11-factor modified frailty index (mFI-11), and 5-factor modified frailty index (mFI-5) for frailty defined by Frailty Phenotype (FP), as well as to compare the predictive ability of TFI, mFI-11, and mFI-5 for adverse outcomes in hospital among elderly patients undergoing gastric cancer surgery. DESIGN A prospective cohort study. SETTING Hospitalization setting, Nanjing, China. PARTICIPANTS We recruited 259 elderly patients undergoing gastric cancer surgery from a tertiary hospital. MEASUREMENTS Frailty was assessed by the FP, TFI, mFI-11, and mFI-5 before surgery, respectively. The receiver operating characteristic (ROC) curves were plotted to compared the diagnostic performance of TFI, mFI-11, and mFI-5 using FP as the reference. ROC curves were used to examine the performance of TFI, mFI-11, and mFI-5 in predicting adverse outcomes. The area under the curve (AUC)>0.70 was regarded as an indicator of good performance. RESULTS The prevalence of frailty ranged from 8.5% (mFI-11) to 45.9% (TFI). The AUCs of TFI (AUC: 0.764, p<0.001) was significantly greater than that of mFI-11 (AUC: 0.600, p=0.033) and mFI-5 (AUC: 0.600, p=0.0311) in the detection of frailty defined by FP, with quite different sensitivity and specificity at their original cutoffs. TFI and mFI-11 both had statistically significant but similarly inadequate predictive accuracy for adverse outcomes in hospital, including total complications (AUCs: 0.618; 0.621), PLOS (AUCs: 0.593; 0.639), increased hospital costs (AUCs: 0.594; 0.624), and hypoproteinemia (AUCs: 0.573; 0.600). For the mFI-5, only the predictive ability for hypoproteinemia was statistically significant, with poor accuracy (AUC: 0.592, p<0.0055). CONCLUSION The TFI performed slightly better than mFI-11 and mFI-5 in our study. Moreover, future studies are needed to further determine an optimal frailty instrument with great diagnostic and predictive accuracy.
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Affiliation(s)
- L Ding
- Qin Xu, Professor, School of Nursing, Nanjing Medical University, 101Longmian Avenue, Jiangning District, Nanjing, China, ; Shuqin Zhu, Associate Professor, School of Nursing, Nanjing Medical University, 101Longmian Avenue, Jiangning District, Nanjing, China,
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Tian J, Zhu Y, Rao M, Cai Y, Lu Z, Zou D, Peng X, Ying P, Zhang M, Niu S, Li Y, Zhong R, Chang J, Miao X. N 6-methyladenosine mRNA methylation of PIK3CB regulates AKT signalling to promote PTEN-deficient pancreatic cancer progression. Gut 2020; 69:2180-2192. [PMID: 32312789 DOI: 10.1136/gutjnl-2019-320179] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 03/09/2020] [Accepted: 03/11/2020] [Indexed: 12/08/2022]
Abstract
OBJECTIVE Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide. Thus far, most drugs have failed to significantly improve patient survival. N6-methyladenosine (m6A) plays an important role in the progression of PDAC, but its aberrant regulation driven by germline variants in human diseases remains unclear. DESIGN We first performed an exome-wide association analysis in 518 PDAC patients with overall survival and replicated in an independent population containing 552 PDAC patients. Then, a series of biochemical experiments in vitro and in vivo were conducted to investigate potential mechanisms of the candidate variant and its target gene PIK3CB underlying the PDAC progression. Moreover, the PIK3CB-selective inhibitor KIN-193 was used to block PDAC tumour growth. RESULTS We identified a missense variant rs142933486 in PIK3CB that is significantly associated with the overall survival of PDAC by reducing the PIK3CB m6A level, which facilitated its mRNA and protein expression levels mediated by the m6A 'writer' complex (METTL13/METTL14/WTAP) and the m6A 'reader' YTHDF2. The upregulation of PIK3CB is widely found in PDAC tumour tissues and significantly correlated with the poor prognosis of PDAC, especially in PTEN-deficient patients. We further demonstrated that PIK3CB overexpression substantially enhanced the proliferation and migration abilities of PTEN-deficient PDAC cells and activated AKT signalling pathway. Remarkably, KIN-193, a PIK3CB-selective inhibitor, is shown to serve as an effective anticancer agent for blocking PTEN-deficient PDAC. CONCLUSIONS These findings demonstrate aberrant m6A homoeostasis as an oncogenic mechanism in PDAC and highlight the potential of PIK3CB as a therapeutic target for this disease.
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Affiliation(s)
- Jianbo Tian
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Meilin Rao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Danyi Zou
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Xiating Peng
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Pingting Ying
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Siyuan Niu
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan 430030, China, Huazhong University of Science and Technology Tongji Medical College, Wuhan, China
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He Y, Bai Y, Wei S, Yuan J, Wang Y, Chen W, Yao P, Miao X, Liang Y, Zhang X, He M, Nie S, Yang H, Wu T, Guo H, Liu L. Healthy lifestyle and cancer risk among Chinese population in the Dongfeng-Tongji cohort. Ann Med 2020; 52:393-402. [PMID: 32683897 PMCID: PMC7877923 DOI: 10.1080/07853890.2020.1798017] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Studies on the association between healthy lifestyle and cancer risk are limited among the old Chinese population. METHODS The healthy lifestyle score was derived from smoking, drinking, diet, body mass index and physical activity among 23734 retired employees from the Dongfeng-Tongji Cohort. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). The rate advancement periods (RAPs) and the population attributable risk percentage (PAR%) were estimated to indicate the benefits of removing risk lifestyle factors. RESULTS During a median follow-up of 8.16 years, 2023 cancer cases were identified. Compared with 0-2 points of the healthy lifestyle score, the HRs were 0.87 (95% CI: 0.76, 0.99), 0.83 (95% CI: 0.73, 0.94), and 0.74 (95% CI: 0.64, 0.86) for 3, 4, and 5 points, respectively, with the corresponding RAPs of -4.40 (95% CI: -8.39, -0.41), -5.84 (95% CI: -9.77, -1.90), and -9.14 (95% CI: -14.03, -4.25), respectively. Approximately 15% of incident cancer cases among total population and 22% among men would be prevented by following all 5 healthy lifestyle factors. CONCLUSIONS The current study suggests that healthy lifestyle could reduce cancer risk in the retired Chinese population, especially in males. Key messages Healthy lifestyle derived by smoking, drinking, diet, body mass index and physical activity presented a strong protective effect on cancer risk among the retired Chinese population, especially in males. We employed the rate advancement periods and the population attributable risk percentage to indicate the benefits of adopting healthy lifestyle and we found that following all 5 healthy lifestyle factors could delay the risk of developing cancer by 9.14 years and prevent 15% of incident cancer cases.
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Affiliation(s)
- Yangting He
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health,Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yansen Bai
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sheng Wei
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health,Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Yuan
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Youjie Wang
- Department of Maternal and Child Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Weihong Chen
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Yao
- Department of Nutrition and Food Hygiene, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health,Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuan Liang
- Department of Social Medicine and Health Management, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Meian He
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaofa Nie
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health,Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Handong Yang
- Dongfeng General Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huan Guo
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Li Liu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health,Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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