Zhandong Zhang, Shuaibing Lu, Liangqun Peng, Fusheng Ge, Bin Zhang, Yonglei Zhang, Fei Ma, Yawei Hua, Xiaobing Chen, Wei Yang
{"title":"Causal association between mitochondrial genes and colorectal cancer: a multi-omics Mendelian randomization study.","authors":"Zhandong Zhang, Shuaibing Lu, Liangqun Peng, Fusheng Ge, Bin Zhang, Yonglei Zhang, Fei Ma, Yawei Hua, Xiaobing Chen, Wei Yang","doi":"10.1007/s12672-025-03699-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Colorectal cancer (CRC) is the leading cause of cancer-related morbidity and mortality globally. Despite the established link between mitochondrial dysfunction and various cancers, including CRC, the precise role of mitochondrial genes remains unclear. This study aimed to elucidate the influence of mitochondrial-related genes on CRC through a multi-omics approach.</p><p><strong>Methods: </strong>The MitoCarta3.0 database, methylation quantitative trait loci (mQTL), expression QTL (eQTL), and protein QTL (pQTL) data from multiple sources were utilized. CRC-related genetic data were obtained from the IEU OpenGWAS project and FinnGen database. The MR analysis employed five regression models. Integration of the results from three levels of gene regulation revealed significant associations between mitochondrial-related gene regulation and CRC.</p><p><strong>Results: </strong>We identified 21 genes that exhibit multi-omics evidence associated with CRC. Tier 1 gene PNKD showed significant associations with CRC across multiple omics levels. Tier 2 genes, RBFA, COX15, TXN2, and ACSF3, were linked to CRC at the mQTL-eQTL level. Sixteen tier 3 genes were also identified. A total of eight genes, including COX15, had been identified as potential therapeutic and drug targets. A total of eight genes, including COX15, had been identified as potential drug targets. Additionally, the final structures of the corresponding eight proteins and their respective drugs had been successfully determined.</p><p><strong>Conclusions: </strong>The multi-omics approach identified several mitochondrial-related genes significantly associated with CRC risk, providing new insights into the role of mitochondrial dysfunction in CRC pathogenesis, and potentially providing further investigation and future therapeutic strategies targeting mitochondrial pathways in CRC management.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1864"},"PeriodicalIF":2.9000,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12521712/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discover. Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12672-025-03699-2","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Colorectal cancer (CRC) is the leading cause of cancer-related morbidity and mortality globally. Despite the established link between mitochondrial dysfunction and various cancers, including CRC, the precise role of mitochondrial genes remains unclear. This study aimed to elucidate the influence of mitochondrial-related genes on CRC through a multi-omics approach.
Methods: The MitoCarta3.0 database, methylation quantitative trait loci (mQTL), expression QTL (eQTL), and protein QTL (pQTL) data from multiple sources were utilized. CRC-related genetic data were obtained from the IEU OpenGWAS project and FinnGen database. The MR analysis employed five regression models. Integration of the results from three levels of gene regulation revealed significant associations between mitochondrial-related gene regulation and CRC.
Results: We identified 21 genes that exhibit multi-omics evidence associated with CRC. Tier 1 gene PNKD showed significant associations with CRC across multiple omics levels. Tier 2 genes, RBFA, COX15, TXN2, and ACSF3, were linked to CRC at the mQTL-eQTL level. Sixteen tier 3 genes were also identified. A total of eight genes, including COX15, had been identified as potential therapeutic and drug targets. A total of eight genes, including COX15, had been identified as potential drug targets. Additionally, the final structures of the corresponding eight proteins and their respective drugs had been successfully determined.
Conclusions: The multi-omics approach identified several mitochondrial-related genes significantly associated with CRC risk, providing new insights into the role of mitochondrial dysfunction in CRC pathogenesis, and potentially providing further investigation and future therapeutic strategies targeting mitochondrial pathways in CRC management.