Isela Sarahi Rivera, Juliet D French, Mainá Bitar, Haran Sivakumaran, Sneha Nair, Susanne Kaufmann, Kristine M Hillman, Mahdi Moradi Marjaneh, Jonathan Beesley, Stacey L Edwards
{"title":"全球基因组分析和三维染色质图谱确定了与激素依赖性癌症相关的多癌风险基因。","authors":"Isela Sarahi Rivera, Juliet D French, Mainá Bitar, Haran Sivakumaran, Sneha Nair, Susanne Kaufmann, Kristine M Hillman, Mahdi Moradi Marjaneh, Jonathan Beesley, Stacey L Edwards","doi":"10.1371/journal.pgen.1011490","DOIUrl":null,"url":null,"abstract":"<p><p>Hormone-dependent cancers (HDCs) share several risk factors, suggesting a common aetiology. Using data from genome-wide association studies, we showed spatial clustering of risk variants across four HDCs (breast, endometrial, ovarian and prostate cancers), contrasting with genetically uncorrelated traits. We identified 44 multi-HDC risk regions across the genome, defined as overlapping risk regions for at least two HDCs: two regions contained risk variants for all four HDCs, 13 for three HDCs and 28 for two HDCs. Integrating GWAS data, epigenomic profiling and promoter capture HiC maps from diverse cell line models, we annotated 53 candidate risk genes at 22 multi-HDC risk regions. These targets were enriched for established genes from the COSMIC Cancer Gene Census, but many had no previously reported pleiotropic roles. Additionally, we pinpointed lncRNAs as potential HDC targets and identified risk alleles in several regions that altered transcription factors motifs, suggesting regulatory mechanisms. Known drug targets were over-represented among the candidate multi-HDC risk genes, implying that some may serve as targets for therapeutic development or facilitate the repurposing of existing treatments for HDC. Our approach provides a framework for identifying common target genes driving complex traits and enhances understanding of HDC susceptibility.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"20 11","pages":"e1011490"},"PeriodicalIF":4.0000,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GWAS and 3D chromatin mapping identifies multicancer risk genes associated with hormone-dependent cancers.\",\"authors\":\"Isela Sarahi Rivera, Juliet D French, Mainá Bitar, Haran Sivakumaran, Sneha Nair, Susanne Kaufmann, Kristine M Hillman, Mahdi Moradi Marjaneh, Jonathan Beesley, Stacey L Edwards\",\"doi\":\"10.1371/journal.pgen.1011490\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Hormone-dependent cancers (HDCs) share several risk factors, suggesting a common aetiology. Using data from genome-wide association studies, we showed spatial clustering of risk variants across four HDCs (breast, endometrial, ovarian and prostate cancers), contrasting with genetically uncorrelated traits. We identified 44 multi-HDC risk regions across the genome, defined as overlapping risk regions for at least two HDCs: two regions contained risk variants for all four HDCs, 13 for three HDCs and 28 for two HDCs. Integrating GWAS data, epigenomic profiling and promoter capture HiC maps from diverse cell line models, we annotated 53 candidate risk genes at 22 multi-HDC risk regions. These targets were enriched for established genes from the COSMIC Cancer Gene Census, but many had no previously reported pleiotropic roles. Additionally, we pinpointed lncRNAs as potential HDC targets and identified risk alleles in several regions that altered transcription factors motifs, suggesting regulatory mechanisms. Known drug targets were over-represented among the candidate multi-HDC risk genes, implying that some may serve as targets for therapeutic development or facilitate the repurposing of existing treatments for HDC. Our approach provides a framework for identifying common target genes driving complex traits and enhances understanding of HDC susceptibility.</p>\",\"PeriodicalId\":49007,\"journal\":{\"name\":\"PLoS Genetics\",\"volume\":\"20 11\",\"pages\":\"e1011490\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PLoS Genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1371/journal.pgen.1011490\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PLoS Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1371/journal.pgen.1011490","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
GWAS and 3D chromatin mapping identifies multicancer risk genes associated with hormone-dependent cancers.
Hormone-dependent cancers (HDCs) share several risk factors, suggesting a common aetiology. Using data from genome-wide association studies, we showed spatial clustering of risk variants across four HDCs (breast, endometrial, ovarian and prostate cancers), contrasting with genetically uncorrelated traits. We identified 44 multi-HDC risk regions across the genome, defined as overlapping risk regions for at least two HDCs: two regions contained risk variants for all four HDCs, 13 for three HDCs and 28 for two HDCs. Integrating GWAS data, epigenomic profiling and promoter capture HiC maps from diverse cell line models, we annotated 53 candidate risk genes at 22 multi-HDC risk regions. These targets were enriched for established genes from the COSMIC Cancer Gene Census, but many had no previously reported pleiotropic roles. Additionally, we pinpointed lncRNAs as potential HDC targets and identified risk alleles in several regions that altered transcription factors motifs, suggesting regulatory mechanisms. Known drug targets were over-represented among the candidate multi-HDC risk genes, implying that some may serve as targets for therapeutic development or facilitate the repurposing of existing treatments for HDC. Our approach provides a framework for identifying common target genes driving complex traits and enhances understanding of HDC susceptibility.
期刊介绍:
PLOS Genetics is run by an international Editorial Board, headed by the Editors-in-Chief, Greg Barsh (HudsonAlpha Institute of Biotechnology, and Stanford University School of Medicine) and Greg Copenhaver (The University of North Carolina at Chapel Hill).
Articles published in PLOS Genetics are archived in PubMed Central and cited in PubMed.