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Xing T, Zhao Y, Wang L, Geng W, Liu W, Zhou J, Huang C, Wang W, Chu X, Liu B, Chen K, Zheng H, Li L. Fine-scale mapping of chromosome 9q22.33 identifies candidate causal variant in ovarian cancer. PeerJ 2024; 12:e16918. [PMID: 38371376 PMCID: PMC10874173 DOI: 10.7717/peerj.16918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 01/18/2024] [Indexed: 02/20/2024] Open
Abstract
Ovarian cancer is a complex polygenic disease in which genetic factors play a significant role in disease etiology. A genome-wide association study (GWAS) identified a novel variant on chromosome 9q22.33 as a susceptibility locus for epithelial ovarian cancer (EOC) in the Han Chinese population. However, the underlying mechanism of this genomic region remained unknown. In this study, we conducted a fine-mapping analysis of 130 kb regions, including 1,039 variants in 200 healthy women. Ten variants were selected to evaluate the association with EOC risk in 1,099 EOC cases and 1,591 controls. We identified two variants that were significantly associated with ovarian cancer risk (rs7027650, P = 1.91 × 10-7; rs1889268, P = 3.71 × 10-2). Expression quantitative trait locus (eQTL) analysis found that rs7027650 was significantly correlated with COL15A1 gene expression (P = 0.009). The Luciferase reporter gene assay confirmed that rs7027650 could interact with the promoter region of COL15A1, reducing its activity. An electrophoretic mobility shift assay (EMSA) showed the allele-specific binding capacity of rs7027650. These findings revealed that rs7027650 could be a potential causal variant at 9q22.33 region and may regulate the expression level of COL15A1. This study offered insight into the molecular mechanism behind a potential causal variant that affects the risk of ovarian cancer.
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Affiliation(s)
- Tongyu Xing
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Yanrui Zhao
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Lili Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Wei Geng
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Wei Liu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Jingjing Zhou
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Caiyun Huang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Wei Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Xinlei Chu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ben Liu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Hong Zheng
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Lian Li
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
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Subramanian A, Su S, Moding EJ, Binkley MS. Investigating the tissue specificity and prognostic impact of cis-regulatory cancer risk variants. Hum Genet 2023; 142:1395-1405. [PMID: 37474751 DOI: 10.1007/s00439-023-02586-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 07/07/2023] [Indexed: 07/22/2023]
Abstract
The tissue-specific incidence of cancers and their genetic basis are poorly understood. Although prior studies have shown global correlation across tissues for cancer risk single-nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS), any shared functional regulation of gene expression on a per SNP basis has not been well characterized. We set to quantify cis-mediated gene regulation and tissue sharing for SNPs associated with eight common cancers. We identify significant tissue sharing for individual SNPs and global enrichment for breast, colorectal, and Hodgkin lymphoma cancer risk SNPs in multiple tissues. In addition, we observe increasing tissue sharing for cancer risk SNPs overlapping with super-enhancers for breast cancer and Hodgkin lymphoma providing further evidence of tissue specificity. Finally, for genes under cis-regulation by breast cancer SNPs, we identify a phenotype characterized by low expression of tumor suppressors and negative regulators of the WNT pathway associated with worse freedom from progression and overall survival in patients who eventually develop breast cancer. Our results introduce a paradigm for functionally annotating individual cancer risk SNPs and will inform the design of future translational studies aimed to personalize assessment of inherited cancer risk across tissues.
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Affiliation(s)
- Ajay Subramanian
- Department of Radiation Oncology, Stanford Cancer Institute and Stanford University School of Medicine, Stanford, CA, USA
| | - Shengqin Su
- Department of Radiation Oncology, Stanford Cancer Institute and Stanford University School of Medicine, Stanford, CA, USA
| | - Everett J Moding
- Department of Radiation Oncology, Stanford Cancer Institute and Stanford University School of Medicine, Stanford, CA, USA
| | - Michael Sargent Binkley
- Department of Radiation Oncology, Stanford Cancer Institute and Stanford University School of Medicine, Stanford, CA, USA.
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Zheng J, Wang X, Li J, Wu Y, Chang J, Xin J, Wang M, Wang T, Wei Q, Wang M, Zhang R. Rare variants confer shared susceptibility to gastrointestinal tract cancer risk. Front Oncol 2023; 13:1161639. [PMID: 37483484 PMCID: PMC10358854 DOI: 10.3389/fonc.2023.1161639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 06/12/2023] [Indexed: 07/25/2023] Open
Abstract
Background Cancers arising within the gastrointestinal tract are complex disorders involving genetic events that cause the conversion of normal tissue to premalignant lesions and malignancy. Shared genetic features are reported in epithelial-based gastrointestinal cancers which indicate common susceptibility among this group of malignancies. In addition, the contribution of rare variants may constitute parts of genetic susceptibility. Methods A cross-cancer analysis of 38,171 shared rare genetic variants from genome-wide association assays was conducted, which included data from 3,194 cases and 1,455 controls across three cancer sites (esophageal, gastric and colorectal). The SNP-level association was performed by multivariate logistic regression analyses for single cancer, followed by association analysis for SubSETs (ASSET) to adjust the bias of overlapping controls. Gene-level analyses were conducted by SKAT-O, with multiple comparison adjustments by false discovery rate (FDR). Based on the significant genes indicated by SKATO analysis, pathways analysis was conducted using Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases. Results Meta-analysis in three gastrointestinal (GI) cancers identified 13 novel susceptibility loci that reached genome-wide significance (P ASSET< 5×10-8). SKAT-O analysis revealed EXOC6, LRP5L and MIR1263/LINC01324 to be significant genes shared by GI cancers (P adj<0.05, P FDR<0.05). Furthermore, GO pathway analysis identified significant enrichment of synaptic transmission and neuron development pathways shared by all three cancer types. Conclusion Rare variants and the corresponding genes potentially contribute to shared susceptibility in different GI cancer types. The discovery of these novel variants and genes offers new insights for the carcinogenic mechanisms and missing heritability of GI cancers.
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Affiliation(s)
- Ji Zheng
- Department of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Xin Wang
- Department of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
- 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
| | - Jingrao Li
- Department of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Yuanna Wu
- Department of Biological Sciences, Dedman College of Humanities and Sciences, Southern Methodist University, Dallas, TX, United States
| | - Jiang Chang
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Junyi Xin
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meilin Wang
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Tianpei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qingyi Wei
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Mengyun Wang
- Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai Medical College, Shanghai, China
| | - Ruoxin Zhang
- Department of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
- Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai Medical College, Shanghai, China
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Wang X, Glubb DM, O'Mara TA. 10 Years of GWAS discovery in endometrial cancer: Aetiology, function and translation. EBioMedicine 2022; 77:103895. [PMID: 35219087 PMCID: PMC8881374 DOI: 10.1016/j.ebiom.2022.103895] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 02/07/2022] [Accepted: 02/08/2022] [Indexed: 12/24/2022] Open
Abstract
Endometrial cancer is a common gynaecological cancer with increasing incidence and mortality. In the last decade, endometrial cancer genome-wide association studies (GWAS) have provided a resource to explore aetiology and for functional interpretation of heritable risk variation, informing endometrial cancer biology. Indeed, GWAS data have been used to assess relationships with other traits through correlation and Mendelian randomisation analyses, establishing genetic relationships and potential risk factors. Cross-trait GWAS analyses have increased statistical power and identified novel endometrial cancer risk variation related to other traits. Functional analysis of risk loci has helped prioritise candidate susceptibility genes, revealing molecular mechanisms and networks. Lastly, risk scores generated using endometrial cancer GWAS data may allow for clinical translation through identification of patients at high risk of disease. In the next decade, this knowledge base should enable substantial progress in our understanding of endometrial cancer and, potentially, new approaches for its screening and treatment.
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Wang Y, Chen P, Chen X, Gong D, Wu Y, Huang L, Chen Y. ROS-Induced DCTPP1 Upregulation Contributes to Cisplatin Resistance in Ovarian Cancer. Front Mol Biosci 2022; 9:838006. [PMID: 35223993 PMCID: PMC8865183 DOI: 10.3389/fmolb.2022.838006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 01/20/2022] [Indexed: 12/20/2022] Open
Abstract
Cisplatin resistance hinders the improvement of the prognosis of patients with ovarian cancer. Cisplatin induces cancer cell apoptosis by inducing reactive oxygen species (ROS). dCTP pyrophosphatase 1 (DCTPP1) is a newly discovered dNTP pyrophosphatase. This study aimed to identify the role of DCTPP1 in oxidative stress and cisplatin response of ovarian cancer. Our results indicates cisplatin-induced ROS generation was responsible for the upregulation of DCTPP1 in ovarian cancer cells, whereas DCTPP1 knockdown significantly enhanced the sensitivity of ovarian cancer cells to cisplatin, reflect in reactive oxygen species (ROS) generation, double-strand DNA breaks, and cell apoptosis. The expression of redox-related genes and the activation of the PI3/Akt signaling pathway were also inhibited by DCTPP1 knockdown. Our data proposes that the development of therapeutic approaches targeting DCTPP1 may be useful in the treatment of ovarian cancer.
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Affiliation(s)
- Yu Wang
- Obstetrics and Gynecology Center, Nanfang Hospital, Guangzhou, China
| | - Peishi Chen
- School of Medical Laboratory and Biotechnology, Southern Medical University, Guangzhou, China
| | - Xueping Chen
- Obstetrics and Gynecology Center, Nanfang Hospital, Guangzhou, China
| | - Daoyuan Gong
- Guangzhou Customs District technology center, Foshan, China
| | - Yingsong Wu
- School of Medical Laboratory and Biotechnology, Southern Medical University, Guangzhou, China
| | - Liping Huang
- Obstetrics and Gynecology Center, Nanfang Hospital, Guangzhou, China
- *Correspondence: Liping Huang, ; Yao Chen,
| | - Yao Chen
- School of Medical Laboratory and Biotechnology, Southern Medical University, Guangzhou, China
- *Correspondence: Liping Huang, ; Yao Chen,
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Wu Q, Li D. CRIA: An Interactive Gene Selection Algorithm for Cancers Prediction Based on Copy Number Variations. FRONTIERS IN PLANT SCIENCE 2022; 13:839044. [PMID: 35386679 PMCID: PMC8978562 DOI: 10.3389/fpls.2022.839044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 01/19/2022] [Indexed: 05/05/2023]
Abstract
Genomic copy number variations (CNVs) are among the most important structural variations of genes found to be related to the risk of individual cancer and therefore they can be utilized to provide a clue to the research on the formation and progression of cancer. In this paper, an improved computational gene selection algorithm called CRIA (correlation-redundancy and interaction analysis based on gene selection algorithm) is introduced to screen genes that are closely related to cancer from the whole genome based on the value of gene CNVs. The CRIA algorithm mainly consists of two parts. Firstly, the main effect feature is selected out from the original feature set that has the largest correlation with the class label. Secondly, after the analysis involving correlation, redundancy and interaction for each feature in the candidate feature set, we choose the feature that maximizes the value of the custom selection criterion and add it into the selected feature set and then remove it from the candidate feature set in each selection round. Based on the real datasets, CRIA selects the top 200 genes to predict the type of cancer. The experiments' results of our research show that, compared with the state-of-the-art related methods, the CRIA algorithm can extract the key features of CNVs and a better classification performance can be achieved based on them. In addition, the interpretable genes highly related to cancer can be known, which may provide new clues at the genetic level for the treatment of the cancer.
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Kho PF, Mortlock S, Rogers PAW, Nyholt DR, Montgomery GW, Spurdle AB, Glubb DM, O'Mara TA. Genetic analyses of gynecological disease identify genetic relationships between uterine fibroids and endometrial cancer, and a novel endometrial cancer genetic risk region at the WNT4 1p36.12 locus. Hum Genet 2021; 140:1353-1365. [PMID: 34268601 DOI: 10.1007/s00439-021-02312-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 07/05/2021] [Indexed: 12/27/2022]
Abstract
Endometriosis, polycystic ovary syndrome (PCOS) and uterine fibroids have been proposed as endometrial cancer risk factors; however, disentangling their relationships with endometrial cancer is complicated due to shared risk factors and comorbidities. Using genome-wide association study (GWAS) data, we explored the relationships between these non-cancerous gynecological diseases and endometrial cancer risk by assessing genetic correlation, causal relationships and shared risk loci. We found significant genetic correlation between endometrial cancer and PCOS, and uterine fibroids. Adjustment for genetically predicted body mass index (a risk factor for PCOS, uterine fibroids and endometrial cancer) substantially attenuated the genetic correlation between endometrial cancer and PCOS but did not affect the correlation with uterine fibroids. Mendelian randomization analyses suggested a causal relationship between only uterine fibroids and endometrial cancer. Gene-based analyses revealed risk regions shared between endometrial cancer and endometriosis, and uterine fibroids. Multi-trait GWAS analysis of endometrial cancer and the genetically correlated gynecological diseases identified a novel genome-wide significant endometrial cancer risk locus at 1p36.12, which replicated in an independent endometrial cancer dataset. Interrogation of functional genomic data at 1p36.12 revealed biologically relevant genes, including WNT4 which is necessary for the development of the female reproductive system. In summary, our study provides genetic evidence for a causal relationship between uterine fibroids and endometrial cancer. It further provides evidence that the comorbidity of endometrial cancer, PCOS and uterine fibroids may partly be due to shared genetic architecture. Notably, this shared architecture has revealed a novel genome-wide risk locus for endometrial cancer.
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Affiliation(s)
- Pik Fang Kho
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Science, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Sally Mortlock
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | | | | | - Peter A W Rogers
- Department of Obstetrics and Gynaecology, Gynaecology Research Centre, Royal Women's Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Dale R Nyholt
- School of Biomedical Science, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Grant W Montgomery
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Amanda B Spurdle
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Dylan M Glubb
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Tracy A O'Mara
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. .,Molecular Cancer Epidemiology Group, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD, 4006, Australia.
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Wang W, Song F, Feng X, Chu X, Dai H, Tian J, Fang X, Song F, Liu B, Li L, Li X, Zhao Y, Zheng H, Chen K. Functional Interrogation of Enhancer Connectome Prioritizes Candidate Target Genes at Ovarian Cancer Susceptibility Loci. Front Genet 2021; 12:646179. [PMID: 33815481 PMCID: PMC8017555 DOI: 10.3389/fgene.2021.646179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Accepted: 02/08/2021] [Indexed: 12/11/2022] Open
Abstract
Identifying causal regulatory variants and their target genes from the majority of non-coding disease-associated genetic loci is the main challenge in post-Genome-Wide Association Studies (GWAS) functional studies. Although chromosome conformation capture (3C) and its derivative technologies have been successfully applied to nominate putative causal genes for non-coding variants, many GWAS target genes have not been identified yet. This study generated a high-resolution contact map from epithelial ovarian cancer (EOC) cells with two H3K27ac-HiChIP libraries and analyzed the underlying gene networks for 15 risk loci identified from the largest EOC GWAS. By combinatory analysis of 4,021 fine-mapped credible variants of EOC GWAS and high-resolution contact map, we obtained 162 target genes that mainly enriched in cancer related pathways. Compared with GTEx eQTL genes in ovarian tissue and annotated proximal genes, 132 HiChIP targets were first identified for EOC causal variants. More than half of the credible variants (CVs) involved interactions that were over 185 kb in distance, indicating that long-range transcriptional regulation is an important mechanism for the function of GWAS variants in EOC. We also found that many HiChIP gene targets showed significantly differential expressions between normal ovarian and EOC tumor samples. We validated one of these targets by manipulating the rs9303542 located region with CRISPR-Cas9 deletion and dCas9-VP64 activation experiments and found altered expression of HOXB7 and HOXB8 at 17q21.32. This study presents a systematic analysis to identify putative target genes for causal variants of EOC, providing an in-depth investigation of the mechanisms of non-coding regulatory variants in the etiology and pathogenesis of ovarian cancer.
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Affiliation(s)
- Wei Wang
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Xiangling Feng
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xinlei Chu
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Jing Tian
- Department of Gynecological Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Xuan Fang
- The Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Fangfang Song
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ben Liu
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Lian Li
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Xiangchun Li
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Yanrui Zhao
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Hong Zheng
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
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