Guorui Zhang, Su Mao, Guangwei Yuan, Yang Wang, Jingyun Yang, Yuxin Dai
{"title":"探索子宫内膜癌的潜在因果遗传变异和基因:开放目标遗传学,孟德尔随机化和多组织转录组全关联分析。","authors":"Guorui Zhang, Su Mao, Guangwei Yuan, Yang Wang, Jingyun Yang, Yuxin Dai","doi":"10.21037/tcr-24-887","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with incidence rates continuing to rise globally. However, the precise mechanisms underlying EC pathogenesis remain largely unexplored. This study aims to prioritize genes associated with EC by leveraging multi-omics data through various bioinformatic methods.</p><p><strong>Methods: </strong>We utilized the Open Targets Genetics (OTG) database to pinpoint potential causal variants and target genes for EC. To explore the pleiotropic effects of gene expression on EC, we applied the Summary-based Mendelian Randomization (SMR) using summary data from a genome-wide association study (GWAS) on EC and expression quantitative trait loci (eQTL) data from the Consortium for the Architecture of Gene Expression (CAGE). We also conducted a cross-tissue transcriptome-wide association study (TWAS) employing sparse canonical correlation analysis (sCCA). Results from the sCCA TWAS and single-tissue TWAS for 22 tissues were combined using the aggregated Cauchy association test (sCCA + ACAT) to identify genes with cis-regulated expression levels linked to EC.</p><p><strong>Results: </strong>The OTG database recognized 15 genomic loci showing independent association with EC. Gene prioritization highlighted nine genes with relatively high locus-to-gene (L2G) scores (≥0.5), the majority of which aligned with those identified using the closest gene. Colocalization analysis identified 11 additional genes at these loci. Our SMR analysis revealed two genes, <i>EVI2A</i> and <i>SRP14</i>, exhibiting a significant pleiotropic association with EC. Cross-tissue TWAS identified 31 genes whose expression was significantly associated with EC after correction for multiple testing, with four genes (<i>EIF2AK4</i>, <i>EVI2A</i>, <i>EVI2B</i>, and <i>NF1</i>) also confirmed by gene colocalization in the OTG analysis.</p><p><strong>Conclusions: </strong>We confirmed the involvement of <i>EVI2A</i> in the pathogenesis of EC and identified several other genes that may contribute to EC development. These findings offer new insights into the genetic mechanisms underlying EC and may inform future research and therapeutic strategies.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"5971-5982"},"PeriodicalIF":1.5000,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651742/pdf/","citationCount":"0","resultStr":"{\"title\":\"Exploring potential causal genetic variants and genes for endometrial cancer: Open Targets Genetics, Mendelian randomization, and multi-tissue transcriptome-wide association analysis.\",\"authors\":\"Guorui Zhang, Su Mao, Guangwei Yuan, Yang Wang, Jingyun Yang, Yuxin Dai\",\"doi\":\"10.21037/tcr-24-887\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with incidence rates continuing to rise globally. However, the precise mechanisms underlying EC pathogenesis remain largely unexplored. This study aims to prioritize genes associated with EC by leveraging multi-omics data through various bioinformatic methods.</p><p><strong>Methods: </strong>We utilized the Open Targets Genetics (OTG) database to pinpoint potential causal variants and target genes for EC. To explore the pleiotropic effects of gene expression on EC, we applied the Summary-based Mendelian Randomization (SMR) using summary data from a genome-wide association study (GWAS) on EC and expression quantitative trait loci (eQTL) data from the Consortium for the Architecture of Gene Expression (CAGE). We also conducted a cross-tissue transcriptome-wide association study (TWAS) employing sparse canonical correlation analysis (sCCA). Results from the sCCA TWAS and single-tissue TWAS for 22 tissues were combined using the aggregated Cauchy association test (sCCA + ACAT) to identify genes with cis-regulated expression levels linked to EC.</p><p><strong>Results: </strong>The OTG database recognized 15 genomic loci showing independent association with EC. Gene prioritization highlighted nine genes with relatively high locus-to-gene (L2G) scores (≥0.5), the majority of which aligned with those identified using the closest gene. Colocalization analysis identified 11 additional genes at these loci. Our SMR analysis revealed two genes, <i>EVI2A</i> and <i>SRP14</i>, exhibiting a significant pleiotropic association with EC. Cross-tissue TWAS identified 31 genes whose expression was significantly associated with EC after correction for multiple testing, with four genes (<i>EIF2AK4</i>, <i>EVI2A</i>, <i>EVI2B</i>, and <i>NF1</i>) also confirmed by gene colocalization in the OTG analysis.</p><p><strong>Conclusions: </strong>We confirmed the involvement of <i>EVI2A</i> in the pathogenesis of EC and identified several other genes that may contribute to EC development. These findings offer new insights into the genetic mechanisms underlying EC and may inform future research and therapeutic strategies.</p>\",\"PeriodicalId\":23216,\"journal\":{\"name\":\"Translational cancer research\",\"volume\":\"13 11\",\"pages\":\"5971-5982\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651742/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational cancer research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21037/tcr-24-887\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/21 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tcr-24-887","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/21 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
Exploring potential causal genetic variants and genes for endometrial cancer: Open Targets Genetics, Mendelian randomization, and multi-tissue transcriptome-wide association analysis.
Background: Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with incidence rates continuing to rise globally. However, the precise mechanisms underlying EC pathogenesis remain largely unexplored. This study aims to prioritize genes associated with EC by leveraging multi-omics data through various bioinformatic methods.
Methods: We utilized the Open Targets Genetics (OTG) database to pinpoint potential causal variants and target genes for EC. To explore the pleiotropic effects of gene expression on EC, we applied the Summary-based Mendelian Randomization (SMR) using summary data from a genome-wide association study (GWAS) on EC and expression quantitative trait loci (eQTL) data from the Consortium for the Architecture of Gene Expression (CAGE). We also conducted a cross-tissue transcriptome-wide association study (TWAS) employing sparse canonical correlation analysis (sCCA). Results from the sCCA TWAS and single-tissue TWAS for 22 tissues were combined using the aggregated Cauchy association test (sCCA + ACAT) to identify genes with cis-regulated expression levels linked to EC.
Results: The OTG database recognized 15 genomic loci showing independent association with EC. Gene prioritization highlighted nine genes with relatively high locus-to-gene (L2G) scores (≥0.5), the majority of which aligned with those identified using the closest gene. Colocalization analysis identified 11 additional genes at these loci. Our SMR analysis revealed two genes, EVI2A and SRP14, exhibiting a significant pleiotropic association with EC. Cross-tissue TWAS identified 31 genes whose expression was significantly associated with EC after correction for multiple testing, with four genes (EIF2AK4, EVI2A, EVI2B, and NF1) also confirmed by gene colocalization in the OTG analysis.
Conclusions: We confirmed the involvement of EVI2A in the pathogenesis of EC and identified several other genes that may contribute to EC development. These findings offer new insights into the genetic mechanisms underlying EC and may inform future research and therapeutic strategies.
期刊介绍:
Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.