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Zhang J, Wang Z, Zhu L, Wang C, Huang B, Zhong Y, Ying P, Wang H, Li Q, Feng L, Wang X, Jin H. Estrogen receptor α inhibits Caveolin 1 translation by promoting m6A-dependent miR199a-5p maturation to confer nab-paclitaxel resistance. Am J Cancer Res 2023; 13:6210-6225. [PMID: 38187046 PMCID: PMC10767350] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 11/15/2023] [Indexed: 01/09/2024] Open
Abstract
Estrogen receptor positive (ER+) breast cancer patients exhibit poorer responsiveness to nab-paclitaxel compared to ER negative (ER-) patients, with the underlying mechanisms remaining unknown. Caveolin 1 (CAV1) is a membrane invagination protein critical for the endocytosis of macromolecules including albumin-bound chemotherapeutic agents. Here, we demonstrate that ERα limits the efficacy of nab-paclitaxel in breast cancer cells while genetic or pharmacological inhibition of ERα increased the sensitivity of ER+ breast cancer cells to nab-paclitaxel. Notably, CAV1 expression inversely correlates with ERα and relates to improved clinical outcomes from nab-paclitaxel treatment. Importantly, ERα stimulates m6A dependent maturation of miR199a-5p, which is elevated in ER+ breast cancer, to inhibit CAV1 translation by antagonizing m6A modification of CAV1 mRNA. Together, our findings reveal a novel role of ERα in promoting m6A modification and subsequent maturation of miR199a-5p, which is upregulated in ER+ breast cancer, leading to the suppression of m6A modification of CAV1 and its mRNA translation, thereby contributing to nab-paclitaxel resistance. Thus, combining an ER antagonist with nab-paclitaxel could offer a promising strategy for treating ER+ breast cancer patients.
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Affiliation(s)
- Jianping Zhang
- Biomedical Research Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Zhuo Wang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Liyuan Zhu
- Biomedical Research Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Chaoqun Wang
- Department of Pathology, Affiliated Dongyang Hospital of Wenzhou Medical UniversityDongyang, Zhejiang, China
| | - Bifei Huang
- Department of Pathology, Affiliated Dongyang Hospital of Wenzhou Medical UniversityDongyang, Zhejiang, China
| | - Yiming Zhong
- Biomedical Research Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Pingting Ying
- Biomedical Research Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Hanying Wang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Qinglin Li
- The Cancer Hospital of The University of Chinese Academy of SciencesHangzhou, Zhejiang, China
| | - Lifeng Feng
- Biomedical Research Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Xian Wang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
| | - Hongchuan Jin
- Biomedical Research Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang UniversityHangzhou, Zhejiang, China
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Wang Y, Wang Y, Zhou J, Ying P, Wang Z, Wu Y, Hao M, Qiu S, Jin H, Wang X. A novel coiled-coil domain containing-related gene signature for predicting prognosis and treatment effect of breast cancer. J Cancer Res Clin Oncol 2023; 149:14205-14225. [PMID: 37558766 DOI: 10.1007/s00432-023-05222-y] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 07/28/2023] [Indexed: 08/11/2023]
Abstract
PURPOSE Breast cancer (BRCA) is a prevalent tumor worldwide. The association between the coiled-coil domain-containing (CCDC) protein family and different tumors has been established. However, the prognostic significance of this protein family in breast cancer remains uncertain. METHODS Gene expression and clinical data were obtained from the TCGA, METABRIC, and GEO databases. Prognosis genes were identified using univariate Cox and LASSO Cox regression, leading to the establishment of a prognostic signature. Subsequently, the risk model was conducted based on survival and clinical feature analyses, and a nomogram for prognosis prediction was developed. Furthermore, analyses of biological function, immune characteristics, and drug sensitivity were performed. Finally, single-cell sequencing data were utilized to uncover the expression patterns of genes in the risk model. RESULTS Five genes were identified and utilized for risk modeling. The model demonstrated excellent prognostic value as indicated by ROC and Kaplan-Meier analysis. The high-risk group exhibited shorter survival time and higher likelihood of recurrence. Functional annotation indicated a correlation between the risk score and immune pathways. Conversely, the low-risk group displayed a greater enrichment in immune pathways and exhibited more active immune microenvironment characteristics. Additionally, drug sensitivity analysis using both public and our sequencing data revealed that the risk model possessed a broad range of predictive values. CONCLUSIONS We have developed a gene signature and have verified that patients with low-risk are more likely to have better prognosis and respond positively to therapy. This finding offers a valuable point of reference for BRCA individualized treatment.
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Affiliation(s)
- Yufei Wang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yanmei Wang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jia Zhou
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Pingting Ying
- Laboratory of Cancer Biology, Key Lab of Biotherapy in Zhejiang Province, Cancer Center of Zhejiang University, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhuo Wang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yan Wu
- Laboratory of Cancer Biology, Key Lab of Biotherapy in Zhejiang Province, Cancer Center of Zhejiang University, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Minyan Hao
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shuying Qiu
- Laboratory of Cancer Biology, Key Lab of Biotherapy in Zhejiang Province, Cancer Center of Zhejiang University, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hongchuan Jin
- Laboratory of Cancer Biology, Key Lab of Biotherapy in Zhejiang Province, Cancer Center of Zhejiang University, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xian Wang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
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3
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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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4
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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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5
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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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6
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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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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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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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9
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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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10
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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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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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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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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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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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15
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Yang N, Ying P, Tian J, Wang X, Mei S, Zou D, Peng X, Gong Y, Yang Y, Zhu Y, Ke J, Zhong R, Chang J, Miao X. Genetic variants in m6A modification genes are associated with esophageal squamous-cell carcinoma in the Chinese population. Carcinogenesis 2020; 41:761-768. [PMID: 32047883 DOI: 10.1093/carcin/bgaa012] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 01/12/2020] [Accepted: 02/08/2020] [Indexed: 12/22/2022] Open
Abstract
N 6-methyladenosine (m6A) is an abundant modification in RNAs that affects RNA metabolism, and it is reported to be closely related to cancer occurrence and metastasis. In this study, we focused on evaluating the associations between genetic variants in m6A modification genes and the risk of esophageal squamous-cell carcinoma (ESCC). By integrating data of our previous genome-wide association studies and the predictions of several annotation tools, we identified a single nucleotide polymorphism, rs2416282 in the promoter of YTHDC2, that was significantly associated with the susceptibility of ESCC (odds ratio = 0.84, 95% CI: 0.77-0.92, P = 2.81 × 10-4). Through further functional experiments in vitro, we demonstrated that rs2416282 regulated YTHDC2 expression. Knockdown of YTHDC2 substantially promoted the proliferation rate of ESCC cells by affecting several cancer-related signaling pathways. Our results suggested that rs2416282 contributed to ESCC risk by regulating YTHDC2 expression. This study provided us a valuable insight into the roles of genetic variants in m6A modification genes for ESCC susceptibility and may contribute to the prevention of this disease in the future.
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Affiliation(s)
- Nan Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pingting Ying
- 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, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shufang Mei
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Danyi Zou
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiating Peng
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yajie Gong
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Yang
- Department of Epidemiology and Biostatistics, 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, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Juntao Ke
- Department of Epidemiology and Biostatistics, School of Public Health, 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
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Tian J, Ying P, Ke J, Zhu Y, Yang Y, Gong Y, Zou D, Peng X, Yang N, Wang X, Mei S, Zhang Y, Wang C, Zhong R, Chang J, Miao X. ANKLE1 N 6 -Methyladenosine-related variant is associated with colorectal cancer risk by maintaining the genomic stability. Int J Cancer 2020; 146:3281-3293. [PMID: 31509622 DOI: 10.1002/ijc.32677] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [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: 06/09/2019] [Accepted: 09/05/2019] [Indexed: 12/21/2022]
Abstract
The N6 -Methyladenosine (m6 A) modification plays an important role in many biological processes, especially tumor development. However, little is still known about how it affects colorectal cancer (CRC) carcinogenesis. Here, we first systematically investigate the association of variants related to m6 A modification with the CRC risk in 1,062 CRC cases and 2,184 controls by using our exome-wide association data and followed by two replication sets including 7,341 CRC cases and 7,902 controls. The variant rs8100241 located in ANKLE1 was significantly associated with CRC risk (odds ratio = 0.88, 95% confidence interval = 0.84-0.92, p = 4.85 × 10-8 ) in 8,403 cases and 10,086 controls. This variant was previously identified to be associated with the susceptibility of breast cancer with BRCA1 mutation triple negative breast cancer. Further functional analysis indicated that overexpression of the rs8100241[A] allele significantly increased the ANKLE1 m6 A level and facilitated the ANKLE1 protein expression compared to that of rs8100241[G] allele. We further found the ANKLE1 m6 A modification was catalyzed by the "writer" complex (METTL3, METTL14, or WTAP) and recognized by the "reader" YTHDF1. Mechanistically, we found that the ANKLE1 functions as a potential tumor suppressor that inhibits cell proliferation and facilitates the genomic stability. An elevated frequency of micronucleated cells, increased cell proliferation, and colony formation ability were observed when ANKLE1 knockdown. Our study illustrated that the germline missense variant can increase CRC risk by influencing ANKLE1 m6 A level, highlighting a clinical potential of variants-associated m6 A modification as a risk marker for CRC prevention.
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Affiliation(s)
- Jianbo Tian
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Pingting Ying
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Juntao Ke
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Ying Zhu
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Yang Yang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Yajie Gong
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Danyi Zou
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiating Peng
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Nan Yang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiaoyang Wang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Shufang Mei
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Yuxing Zhang
- Department of Colorectal Surgery, The Eighth Hospital of Wuhan City, Wuhan, China
| | - Changyi Wang
- Department of Non-Communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China
| | - Rong Zhong
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Jiang Chang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
| | - Xiaoping Miao
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, China
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17
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Yang Y, Peng X, Ying P, Tian J, Li J, Ke J, Zhu Y, Gong Y, Zou D, Yang N, Wang X, Mei S, Zhong R, Gong J, Chang J, Miao X. AWESOME: a database of SNPs that affect protein post-translational modifications. Nucleic Acids Res 2020; 47:D874-D880. [PMID: 30215764 PMCID: PMC6324025 DOI: 10.1093/nar/gky821] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 09/04/2018] [Indexed: 12/19/2022] Open
Abstract
Protein post-translational modifications (PTMs), including phosphorylation, ubiquitination, methylation, acetylation, glycosylation et al, are very important biological processes. PTM changes in some critical genes, which may be induced by base-pair substitution, are shown to affect the risk of diseases. Recently, large-scale exome-wide association studies found that missense single nucleotide polymorphisms (SNPs) play an important role in the susceptibility for complex diseases or traits. One of the functional mechanisms of missense SNPs is that they may affect PTMs and leads to a protein dysfunction and its downstream signaling pathway disorder. Here, we constructed a database named AWESOME (A Website Exhibits SNP On Modification Event, http://www.awesome-hust.com), which is an interactive web-based analysis tool that systematically evaluates the role of SNPs on nearly all kinds of PTMs based on 20 available tools. We also provided a well-designed scoring system to compare the performance of different PTM prediction tools and help users to get a better interpretation of results. Users can search SNPs, genes or position of interest, filter with specific modifications or prediction methods, to get a comprehensive PTM change induced by SNPs. In summary, our database provides a convenient way to detect PTM-related SNPs, which may potentially be pathogenic factors or therapeutic targets.
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Affiliation(s)
- Yang Yang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Xiating Peng
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Pingting Ying
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Jianbo Tian
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Jiaoyuan Li
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Juntao Ke
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Ying Zhu
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Yajie Gong
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Danyi Zou
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Nan Yang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Xiaoyang Wang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Shufang Mei
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Rong Zhong
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Jing Gong
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Jiang Chang
- Key Laboratory for Environment and Health (Ministry of Education), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, 430030, China
| | - Xiaoping Miao
- Key Laboratory for Environment and Health (Ministry of Education), 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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18
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Wang X, Tian J, Zhao Q, Yang N, Ying P, Peng X, Zou D, Zhu Y, Zhong R, Gao Y, Chang J, Miao X. Functional characterization of a low-frequency V1937I variant in FASN associated with susceptibility to esophageal squamous cell carcinoma. Arch Toxicol 2020; 94:2039-2046. [PMID: 32388819 DOI: 10.1007/s00204-020-02738-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [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: 01/10/2020] [Accepted: 04/06/2020] [Indexed: 12/31/2022]
Abstract
Metabolic reprogramming has been regarded as one of the core hallmarks of cancer and increased de novo fatty acid synthesis has been documented in multiple tumors including esophageal squamous cell carcinoma (ESCC). Our previous exome-wide analyses found a Val1937Ile variant (rs17848945) in the 34th exon of fatty acid synthase (FASN) that showed a strong association with the risk of ESCC. In this study, we performed a series of functional assays to investigate the biological functions underlying this variant in the development of ESCC. We demonstrated that FASN was upregulated in ESCC and both knockdown and knockout of FASN significantly inhibited ESCC cell proliferation, suggesting a tumor promoter role for this gene in ESCC. Furthermore, the results showed that overexpression of FASN[I] in the ESCC cells substantially enhanced cell proliferation, compared with overexpression of FASN[V], or the control vector. Intriguingly, we found that the FASN[I] variant can enhance the enzyme activity of FASN, and, thus, increase the amount of the FASN end-product, palmitate in the ESCC cells. We also observed elevated palmitate levels in the plasma of the FASN[I] genotype carriers among a total of 632 healthy Chinese adults. In conclusion, our results suggested that the FASN V1937I variant influenced ESCC cell proliferation and susceptibility by altering the catabolic activity of FASN on palmitate. These findings may highlight an important role of palmitate metabolism in the development of ESCC and may contribute to the personalized medicine of this disease.
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Affiliation(s)
- 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, 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, China
| | - Qianyu Zhao
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 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, China
| | - 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, 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, 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, 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, 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, China
| | - Ying Gao
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 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, 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, China.
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19
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Ke J, Tian J, Mei S, Ying P, Yang N, Wang X, Zou D, Peng X, Yang Y, Zhu Y, Gong Y, Wang Z, Gong J, Zhong R, Chang J, Miao X. Genetic Predisposition to Colon and Rectal Adenocarcinoma Is Mediated by a Super-enhancer Polymorphism Coactivating CD9 and PLEKHG6. Cancer Epidemiol Biomarkers Prev 2020; 29:850-859. [PMID: 31988071 DOI: 10.1158/1055-9965.epi-19-1116] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 11/22/2019] [Accepted: 01/21/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have identified dozens of loci associated with colon and rectal adenocarcinoma risk. As tissue-specific super-enhancers (SE) play important roles in tumorigenesis, we systematically investigate SEs and inner variants in established GWAS loci to decipher the underlying biological mechanisms. METHODS Through a comprehensive bioinformatics analysis on multi-omics data, we screen potential single-nucleotide polymorphisms (SNP) in cancer-specific SEs, and then subject them to a two-stage case-control study containing 4,929 cases and 7,083 controls from the Chinese population. A series of functional assays, including reporter gene assays, electrophoretic mobility shift assays (EMSA), CRISPR-Cas9 genome editing, chromosome conformation capture (3C) assays, and cell proliferation experiments, are performed to characterize the variant's molecular consequence and target genes. RESULTS The SNP rs11064124 in 12p13.31 is found significantly associated with the risk of colon and rectal adenocarcinoma with an odds ratio (OR) of 0.87 [95% confidence interval (CI), 0.82-0.92, P = 8.67E-06]. The protective rs11064124-G weakens the binding affinity with vitamin D receptor (VDR) and increases the enhancer's activity and interactions with two target genes' promoters, thus coactivating the transcription of CD9 and PLEKHG6, which are both putative tumor suppressor genes for colon and rectal adenocarcinoma. CONCLUSIONS Our integrative study highlights an SE polymorphism rs11064124 and two susceptibility genes CD9 and PLEKHG6 in 12p13.31 for colon and rectal adenocarcinoma. IMPACT These findings suggest a novel insight for genetic pathogenesis of colon and rectal adenocarcinoma, involving transcriptional coactivation of diverse susceptibility genes via the SE element as a gene regulation hub.
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Affiliation(s)
- Juntao Ke
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianbo Tian
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shufang Mei
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pingting Ying
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Nan Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyang Wang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Danyi Zou
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiating Peng
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yajie Gong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhihua Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Gong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Rong Zhong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiang Chang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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20
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Ke J, Peng X, Mei S, Tian J, Ying P, Yang N, Wang X, Zou D, Yang Y, Zhu Y, Gong Y, Gong J, Zhong R, Chang J, Fang Z, Miao X. Evaluation of polymorphisms in microRNA-binding sites and pancreatic cancer risk in Chinese population. J Cell Mol Med 2019; 24:2252-2259. [PMID: 31880394 PMCID: PMC7011162 DOI: 10.1111/jcmm.14906] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [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: 07/26/2019] [Revised: 11/12/2019] [Accepted: 12/03/2019] [Indexed: 12/20/2022] Open
Abstract
As promising biomarkers and therapy targets, microRNAs (miRNAs) are involved in various physiological and tumorigenic processes. Genetic variants in miRNA‐binding sites can lead to dysfunction of miRNAs and contribute to disease. However, systematic investigation of the miRNA‐related single nucleotide polymorphisms (SNPs) for pancreatic cancer (PC) risk remains elusive. We performed integrative bioinformatics analyses to select 31 SNPs located in miRNA‐target binding sites using the miRNASNP v2.0, a solid database providing miRNA‐related SNPs for genetic research, and investigated their associations with risk of PC in two large case‐control studies totally including 1847 cases and 5713 controls. We observed that the SNP rs3802266 is significantly associated with increased risk of PC (odds ratio (OR) = 1.21, 95% confidence intervals (CI) = 1.11‐1.31, P = 1.29E‐05). Following luciferase reporter gene assays show that rs3802266‐G creates a stronger binding site for miR‐181a‐2‐3p in 3′ untranslated region (3′UTR) of the gene ZHX2. Expression quantitative trait loci (eQTL) analysis suggests that ZHX2 expression is lower in individuals carrying rs3802266‐G with increased PC risk. In conclusion, our findings highlight the involvement of miRNA‐binding SNPs in PC susceptibility and provide new clues for PC carcinogenesis.
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Affiliation(s)
- Juntao Ke
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiating Peng
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shufang Mei
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianbo Tian
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pingting Ying
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Nan Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyang Wang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Danyi Zou
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yajie Gong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Gong
- College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Rong Zhong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiang Chang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zemin Fang
- Division of Cardiothoracic and Vascular Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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21
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Mei S, Ke J, Tian J, Ying P, Yang N, Wang X, Zou D, Peng X, Yang Y, Zhu Y, Gong Y, Zhong R, Chang J, Miao X. A functional variant in the boundary of a topological association domain is associated with pancreatic cancer risk. Mol Carcinog 2019; 58:1855-1862. [DOI: 10.1002/mc.23077] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 06/01/2019] [Accepted: 06/03/2019] [Indexed: 12/24/2022]
Affiliation(s)
- Shufang Mei
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Juntao Ke
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Jianbo Tian
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Pingting Ying
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Nan Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Xiaoyang Wang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Danyi Zou
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Xiating Peng
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Yang Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Ying Zhu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Yajie Gong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Rong Zhong
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Jiang Chang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Xiaoping Miao
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment & Health (Ministry of Education), Ministry of Environmental Protection Key Laboratory of Environment and Health (Wuhan), Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology Wuhan China
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22
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Zhu Y, Ke J, Gong Y, Yang Y, Peng X, Tian J, Zou D, Yang N, Wang X, Mei S, Rao M, Ying P, Deng Y, Wang H, Zhang H, Li B, Wan H, Li Y, Niu S, Cai Y, Zhang M, Lu Z, Zhong R, Miao X, Chang J. A genetic variant in PIK3R1 is associated with pancreatic cancer survival in the Chinese population. Cancer Med 2019; 8:3575-3582. [PMID: 31059194 PMCID: PMC6601582 DOI: 10.1002/cam4.2228] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [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: 02/03/2019] [Revised: 04/02/2019] [Accepted: 04/22/2019] [Indexed: 12/11/2022] Open
Abstract
Pancreatic cancer is one of the deadliest malignancies with few early detection tests or effective therapies. PI3K-AKT signaling is recognized to modulate cancer progression. We previously identified that a genetic variant in PKN1 increased pancreatic cancer risk through the PKN1/FAK/PI3K/AKT pathway. In order to investigate the associations between genetic variations in that pathway and pancreatic cancer prognosis, we conducted a two-stage survival analysis in a total of 547 Chinese pancreatic cancer patients. Consequently, a variant, rs13167294 A>C in PIK3R1, was significantly associated with poor survival in both stages and with hazard ratio being 1.32 (95% CI = 1.13-1.56, P = 0.0007) in the combined analysis. Function annotation and prediction suggested that genetic variants in this locus might affect overall survival of pancreatic cancer patients by regulating PIK3R1 expression.
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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
| | - Juntao Ke
- 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
| | - Yajie Gong
- 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
| | - Yang 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
| | - 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
| | - 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
| | - 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, 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
| | - 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
| | - Shufang Mei
- 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
| | - 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, 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
| | - Yao Deng
- 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
| | - Hongli 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
| | - 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
| | - Hao Wan
- 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
| | - 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
| | - 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
| | - 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
| | - 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
| | - 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
| | - 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
| | - 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
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23
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Ying P, Jin G, Tao Z. [Study on the adsorption of collagen onto surfaces with imaging ellipsometry]. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2001; 18:351-6. [PMID: 11605487] [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] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
Abstract
The adsorption of collagen onto hydrophilic and hydrophobic surfaces was studied with imaging ellipsometry in different pH, adsorption time, ion strength and BSA existence. The results showed that there was more collagen adsorbed onto hydrophobic surfaces than onto hydrophilic surfaces. The maximum collagen adsorption was observed at pH 7.2. The existence of BSA affected the adsorption of collagen onto hydrophobic surfaces more than that onto hydrophilic surfaces.
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Affiliation(s)
- P Ying
- National Microgravity Laboratory, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080
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24
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Jiang X, Ou Z, Ying P, Yediler A, Ketrrup A. [Transportation and transformation of 14C-phenanthrene in closed chamber (nutrient solution-lava-plant-air) system]. Ying Yong Sheng Tai Xue Bao 2001; 12:451-4. [PMID: 11758435] [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] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
The transportation and transformation of 14C-phenanthrene in a closed 'plant-lava-nutrient solution-air' chamber system was studied by using radioactivity technology. The results showed that in this closed chamber system, phenanthrene was degraded fast. The radioactivity of 14C left at 23d in the nutrient solution was only 25% of applied. At the end of experiment (46d), the distribution sequence of 14C activity in the components of closed chamber system was root (38.55%) > volatile organic compounds (VOCs, 17.68%) > lava (14.35%) > CO2 (11.42%) > stem (2%). 14C-activities in plant tissue were combined with the tissue, and existed in the forms of lava-bound(root 4.68%; stem and leaves 0.68%) and polar metabolites (root 23.14%; stem 0.78%).
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Affiliation(s)
- X Jiang
- Laboratory of Terrestrial Ecological Process, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016.
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25
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Liu W, Ou Z, Ying P. [Soil macropore and its studying methodology]. Ying Yong Sheng Tai Xue Bao 2001; 12:465-8. [PMID: 11758439] [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] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
This paper discusses the definition, size, types, formation of soil macropores. Soil macropore (> 0.03 mm) is the pore space that provides preferential paths of flow. The shape of macropore varies from crack or fissure, through to cylindrical pipe. Macropore is formed in main ways: by plant roots and soil fauna; wet-dry and freeze-thaw cycles; chemical weathering. The studying method of macropore divided into direct measurement and indirect description, which suitability and limitation are also reviewed.
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Affiliation(s)
- W Liu
- Laboratory of Terrestrial Ecological Process, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016.
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26
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Ying P, Wang Z, Jin G, Tao Z. [Using self-assembled monolayers to understand the interactions of surfaces with cells]. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2001; 18:276-9. [PMID: 11450553] [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] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
It is important to understand the interactions of surfaces with cells. Self-assembled monolayers formed on the adsorption of long-chain alkanethiols to the surface of gold or alkylsilanes to hydroxylated surfaces and their patterned surfaces permit of understanding and controlling over the surface-cell interactions at the molecular scale. The present paper reviewed the latest research in using patterned self-assembled monolayers to understand surface-cell interactions.
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Affiliation(s)
- P Ying
- Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080
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27
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Li Y, Liang C, Slemenda CW, Ji R, Sun S, Cao J, Emsley CL, Ma F, Wu Y, Ying P, Zhang Y, Gao S, Zhang W, Katz BP, Niu S, Cao S, Johnston CC. Effect of long-term exposure to fluoride in drinking water on risks of bone fractures. J Bone Miner Res 2001; 16:932-9. [PMID: 11341339 DOI: 10.1359/jbmr.2001.16.5.932] [Citation(s) in RCA: 63] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Findings on the risk of bone fractures associated with long-term fluoride exposure from drinking water have been contradictory. The purpose of this study was to determine the prevalence of bone fracture, including hip fracture, in six Chinese populations with water fluoride concentrations ranging from 0.25 to 7.97 parts per million (ppm). A total of 8266 male and female subjects > or =50 years of age were enrolled. Parameters evaluated included fluoride exposure, prevalence of bone fractures, demographics, medical history, physical activity, cigarette smoking, and alcohol consumption. The results confirmed that drinking water was the only major source of fluoride exposure in the study populations. A U-shaped pattern was detected for the relationship between the prevalence of bone fracture and water fluoride level. The prevalence of overall bone fracture was lowest in the population of 1.00-1.06 ppm fluoride in drinking water, which was significantly lower (p < 0.05) than that of the groups exposed to water fluoride levels > or =4.32 and < or =0.34 ppm. The prevalence of hip fractures was highest in the group with the highest water fluoride (4.32-7.97 ppm). The value is significantly higher than the population with 1.00-1.06 ppm water fluoride, which had the lowest prevalence rate. It is concluded that long-term fluoride exposure from drinking water containing > or =4.32 ppm increases the risk of overall fractures as well as hip fractures. Water fluoride levels at 1.00-1.06 ppm decrease the risk of overall fractures relative to negligible fluoride in water; however, there does not appear to be similar protective benefits for the risk of hip fractures.
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Affiliation(s)
- Y Li
- Center for Dental Research, Loma Linda University School of Dentistry, California 92350, USA
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28
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Ni Y, Ou Z, Ying P. [Preferential flow and its effect on solute migration in soil]. Ying Yong Sheng Tai Xue Bao 2001; 12:103-7. [PMID: 11813410] [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] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
The characteristics of soil preferential flow and the preferential migrate in soil for non-absorptive bromide and nitrate ions were studied. With undisturbed and packed soil columns, the results showed that soil preferential flow was characterized with preferential breakthrough, non-symmetric breakthrough curve, lateral infiltration, tailing and so on. The preferential breakthrough for Br- was 24 hours after it was applied, and the leachate volume was only 0.04 times as-much as the pore volumes. The preferential flow for Br- accounted for 26% of total flux in the undisturbed soil columns. But the accumulative leachate mass for Br- resulted from the preferential flow were 86.7% of total accumulative leachate mass, showing that the soil preferential flow accounted for relative small ratio of the flux, but caused relative much more solute transference. NO3- was moved down rapidly by preferential flow at only one time as large as pore volumes, and got 11% of the applied amount, respectively. As a result of the preferential flow, the lateral infiltration flow enabled Br- and NO3- rapidly distribute and diffuse into the deeper soil.
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Affiliation(s)
- Y Ni
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016.
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29
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Emsley CL, Gao S, Li Y, Liang C, Ji R, Hall KS, Cao J, Ma F, Wu Y, Ying P, Zhang Y, Sun S, Unverzagt FW, Slemenda CW, Hendrie HC. Trace element levels in drinking water and cognitive function among elderly Chinese. Am J Epidemiol 2000; 151:913-20. [PMID: 10791564 DOI: 10.1093/oxfordjournals.aje.a010295] [Citation(s) in RCA: 34] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The relation between trace element levels in drinking water and cognitive function was investigated in a population-based study of elderly residents (n = 1,016) in rural China in 1996-1997. Cognitive function was measured using a Chinese translation of the Community Screening Interview for Dementia. A mixed effects model was used to evaluate the effect of each of the elements on cognitive function while adjusting for age, sex, and educational level. Several of the elements examined had a significant effect on cognitive function when they were assessed in a univariate context. However, after adjustment for other elements, many of these results were not significant. There was a significant quadratic effect for calcium and a significant zinc-cadmium interaction. Cognitive function increased with calcium level up to a certain point and then decreased as calcium continued to increase. Zinc showed a positive relation with cognitive function at low cadmium levels but a negative relation at high levels.
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Affiliation(s)
- C L Emsley
- Department of Medicine, Indiana University School of Medicine, Indianapolis 46202, USA
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30
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Ying P, Shakibaei M, Patankar MS, Clavijo P, Beavis RC, Clark GF, Frevert U. The malaria circumsporozoite protein: interaction of the conserved regions I and II-plus with heparin-like oligosaccharides in heparan sulfate. Exp Parasitol 1997; 85:168-82. [PMID: 9030667 DOI: 10.1006/expr.1996.4134] [Citation(s) in RCA: 55] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The malaria circumsporozoite (CS) protein binds to glycosaminoglycans from heparan sulfate proteoglycans on the cell surface of hepatocytes and is specifically cleared from the bloodstream by the liver. We show here that the two conserved regions, I and II-plus, of the CS protein, in a concerted action, preferentially bind to highly sulfated heparin-like oligosaccharides in heparan sulfate. In a concentration-dependent manner, peptides representing region I and region II-plus inhibited the binding of recombinant CS protein to HepG2 cells by 62 and 84%, respectively. Furthermore, the action of endoproteinase Arg-C, which cleaves the recombinant CS constructs CS27IVC and CSFZ(Cys) predominantly at the conserved region I, was inhibited by heparin in a concentration-dependent fashion. CSFZ(Cys), which has a higher affinity to HSPGs than CS27IVC, was stabilized by heparin at a w/w ratio (CS protein:glycosaminoglycan) of 20/1, whereas full protection of CS27IVC required more heparin (5/1). Heparan sulfate provided full protection of CSFZ(Cys) only at a ratio of 1/10. Native fucoidan as well as normally sulfated fuco-oligosaccharides (0.76 mol sulfate/mol fucose) inhibited Plasmodium berghei development in HepG2 cells by 84 and 66%, respectively, in a concentration-dependent manner and sporozoite invasion into CHO cells by 80%. Desulfated fucoidan oligosaccharides were inactive. These results may explain the selective interaction between the CS protein and the unique heparan sulfate from liver, which is noted for its unusually high degree of sulfation, and may provide a plausible explanation for the selective targeting of the malaria CS protein to the liver.
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Affiliation(s)
- P Ying
- Department of Medical and Molecular Parasitology, NYU Medical Center, New York, New York 10010, USA
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Abstract
We recently identified a locus on the Staphylococcus aureus chromosome, designated sar, for staphylococcal accessory regulator, that is involved in the global regulation of extracellular and cell wall-associated proteins. Previous phenotypic and Southern blot analyses with Tn917 and agr probes indicated that this locus is distinct from agr, a previously described global regulator of exoproteins in S. aureus. To understand the mode of regulatory control of exoprotein synthesis by the sar locus, the sar genotype was transduced from the original sar mutant 11D2 into two prototypic S. aureus strains, RN6390 and RN450, with well-defined genetic backgrounds. An analysis of extracellular protein profiles by use of silver-stained sodium dodecyl sulfate gels revealed alterations in the pattern of exoprotein production in the late log-early stationary phase in the sar mutants in comparison with the corresponding parents. In addition, most of the phenotypic changes that occurred in the conversion from the sar+ genotype to the sar genotype in mutant 11D2 were also found in these mutants. Northern (RNA) blot analyses of two exoprotein transcripts (alpha- and beta-hemolysins) from strain RN6390 and its corresponding sar mutant revealed downregulation of these transcripts in the mutant. Serial studies of these hemolysin transcripts at various growth intervals demonstrated that the transcriptional regulation of the hemolysin genes by the sar locus began during the log phase and continued into the postexponential phase. These data suggested that the sar locus probably regulates exoprotein genes at the transcriptional level. This mode of regulation is similar to that of exoprotein target gene transcription by agr.
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Affiliation(s)
- A L Cheung
- Laboratory of Bacterial Pathogenesis and Immunology, Rockefeller University, New York, New York 10021
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32
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Shen SL, Zhang ZY, Sun Z, Wang QM, Ying P. [The appliance of image analysis in the diagnosis of oral Lichen Planus and it's malignant change]. Shanghai Kou Qiang Yi Xue 1993; 2:32-4. [PMID: 15159879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
After the Feulgen dying,if the normal oral mucous,oral Lichen planus as well as the pathological cut sheets with atypical dysplasia and malignant change in defferent degrees,use the image analysis technique to measure the morphologic parameters of the nucleus(including nuclear surface area,perimeter maximum nuclear diameter,minimum nulear diameter,equivalent circle diameter,morphological factor) and the amount of DNA,5CER acts as an indes of distinguishing malignancy or benignancy,the value of 5CER in malignant is more than 10% and in benignant is less than 10%.The result of the analysis from the optical microscope differs from the optical microscope differs form the image analysis.There are so many personal factors in the qualitative analysis by optical microscope that it because quite imperative to research for a new diagnosing way.The synchronization of quantitative analysis and qualitative analysis can correct the personal errors in qualitative analysis.It will be very useful for directing the clinical practice and the judgment of prognosis.
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Affiliation(s)
- S L Shen
- Affiliated Hospital of Stomaotlogy,Capital Medical College. Beijing 100050, China
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33
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Geng SF, Xu L, Ying P, Cao CF. [Clinical evaluation of manual and ultrasonic subgingival scaling using image analysis]. Shanghai Kou Qiang Yi Xue 1992; 1:73-6. [PMID: 15159894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
The objective of this study was to compare the effect of hand and ultrasonic instrumentation in removing subgingival plaque and calculus.In experiment one,forty-eight teeth from patients were randomly assigned to be scaled with curettes or ultrasonic scaler.Probing depth,clinical attachment level and bleeding index were reexamined 2 months latter.The results demonstrated that no significant differences between the two mehtods.In experiment two,seventeen teeth from six patient were also randomly scaled manualty ultrasonic or uninstrumented as a control.All these teeth were extracted immediately after subgingival scaling.The proportion of tooth surfaces covered by residual plaque and calculus(relative to the total surface area of the side of the tooth)was analysed on each tooth using computerized graphic processing.The findings showed the proportional areas of residual plaque and calculus in teeth.But the hand scaled root surface were much smoother than those treated with ultrasonic scaler.
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Affiliation(s)
- S F Geng
- Department of Prothodontics, School of Stomatology, Shanghai Second Medical University. Shanghai 200011, China
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34
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Abstract
Routine assays to detect proteinases in biological samples are generally tedious and time-consuming. To expedite the recognition of proteinases, we have developed an assay utilizing the gelatin on the surface of an unprocessed Kodak X-Omat AR film as the proteolytic substrate. A positive reaction is indicated by a clear zone on the film after it has been rinsed with running water. This proteinase assay has been found to be inexpensive, rapid, and simple. Besides its ease of use, this assay has been found to be quantitatively reproducible with a well-defined endpoint. More importantly, this assay method is applicable to a variety of proteolytic enzymes under diverse pH (5-8.5) and salt conditions (up to 5 M NaCl) and has a sensitivity similar to that of azocoll. Since the assay does not require sophisticated equipment, it is useful as a general laboratory procedure.
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Affiliation(s)
- A L Cheung
- Laboratory of Bacteriology and Immunology, Rockefeller University, New York, New York 10021
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