Hao Lin, Zhen Zeng, Hong Zhang, Yongbin Jia, Jiangmei Pang, Jingjing Chen, Hu Zhang
{"title":"卵巢癌的肠道-阴道微生物群串扰:对早期诊断的意义。","authors":"Hao Lin, Zhen Zeng, Hong Zhang, Yongbin Jia, Jiangmei Pang, Jingjing Chen, Hu Zhang","doi":"10.3390/pathogens14070635","DOIUrl":null,"url":null,"abstract":"<p><p>Ovarian cancer remains a formidable global health burden, characterized by frequent late-stage diagnosis and elevated mortality rates attributable to its elusive pathogenesis and the critical lack of reliable early-detection biomarkers. Emerging investigations into the gut-vaginal microbiome axis have unveiled novel pathogenic mechanisms and potential diagnostic targets in ovarian carcinogenesis. This comprehensive review systematically examines the compositional alterations in and functional interplay between vaginal and intestinal microbial communities in ovarian cancer patients. We elucidate three principal mechanistic pathways through which microbial dysbiosis may drive oncogenesis: (1) estrogen-mediated metabolic reprogramming via β-glucuronidase activity; (2) chronic activation of pro-inflammatory cascades (particularly NF-κB and STAT3 signaling); (3) epigenetic silencing of tumor suppressor genes through DNA methyltransferase modulation. We propose an integrative diagnostic framework synthesizing multi-omics data-incorporating microbial profiles, metabolic signatures, pathway-specific molecular alterations, established clinical biomarkers, and imaging findings-within a multifactorial etiological paradigm. This innovative approach aims to enhance early-detection accuracy through machine learning-enabled multidimensional pattern recognition. By bridging microbial ecology with tumor biology, this review provides novel perspectives for understanding ovarian cancer etiology and advancing precision oncology strategies through microbiome-targeted diagnostic innovations.</p>","PeriodicalId":19758,"journal":{"name":"Pathogens","volume":"14 7","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12298164/pdf/","citationCount":"0","resultStr":"{\"title\":\"Gut-Vaginal Microbiome Crosstalk in Ovarian Cancer: Implications for Early Diagnosis.\",\"authors\":\"Hao Lin, Zhen Zeng, Hong Zhang, Yongbin Jia, Jiangmei Pang, Jingjing Chen, Hu Zhang\",\"doi\":\"10.3390/pathogens14070635\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Ovarian cancer remains a formidable global health burden, characterized by frequent late-stage diagnosis and elevated mortality rates attributable to its elusive pathogenesis and the critical lack of reliable early-detection biomarkers. Emerging investigations into the gut-vaginal microbiome axis have unveiled novel pathogenic mechanisms and potential diagnostic targets in ovarian carcinogenesis. This comprehensive review systematically examines the compositional alterations in and functional interplay between vaginal and intestinal microbial communities in ovarian cancer patients. We elucidate three principal mechanistic pathways through which microbial dysbiosis may drive oncogenesis: (1) estrogen-mediated metabolic reprogramming via β-glucuronidase activity; (2) chronic activation of pro-inflammatory cascades (particularly NF-κB and STAT3 signaling); (3) epigenetic silencing of tumor suppressor genes through DNA methyltransferase modulation. We propose an integrative diagnostic framework synthesizing multi-omics data-incorporating microbial profiles, metabolic signatures, pathway-specific molecular alterations, established clinical biomarkers, and imaging findings-within a multifactorial etiological paradigm. This innovative approach aims to enhance early-detection accuracy through machine learning-enabled multidimensional pattern recognition. By bridging microbial ecology with tumor biology, this review provides novel perspectives for understanding ovarian cancer etiology and advancing precision oncology strategies through microbiome-targeted diagnostic innovations.</p>\",\"PeriodicalId\":19758,\"journal\":{\"name\":\"Pathogens\",\"volume\":\"14 7\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12298164/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pathogens\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3390/pathogens14070635\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pathogens","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/pathogens14070635","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
Gut-Vaginal Microbiome Crosstalk in Ovarian Cancer: Implications for Early Diagnosis.
Ovarian cancer remains a formidable global health burden, characterized by frequent late-stage diagnosis and elevated mortality rates attributable to its elusive pathogenesis and the critical lack of reliable early-detection biomarkers. Emerging investigations into the gut-vaginal microbiome axis have unveiled novel pathogenic mechanisms and potential diagnostic targets in ovarian carcinogenesis. This comprehensive review systematically examines the compositional alterations in and functional interplay between vaginal and intestinal microbial communities in ovarian cancer patients. We elucidate three principal mechanistic pathways through which microbial dysbiosis may drive oncogenesis: (1) estrogen-mediated metabolic reprogramming via β-glucuronidase activity; (2) chronic activation of pro-inflammatory cascades (particularly NF-κB and STAT3 signaling); (3) epigenetic silencing of tumor suppressor genes through DNA methyltransferase modulation. We propose an integrative diagnostic framework synthesizing multi-omics data-incorporating microbial profiles, metabolic signatures, pathway-specific molecular alterations, established clinical biomarkers, and imaging findings-within a multifactorial etiological paradigm. This innovative approach aims to enhance early-detection accuracy through machine learning-enabled multidimensional pattern recognition. By bridging microbial ecology with tumor biology, this review provides novel perspectives for understanding ovarian cancer etiology and advancing precision oncology strategies through microbiome-targeted diagnostic innovations.
期刊介绍:
Pathogens (ISSN 2076-0817) publishes reviews, regular research papers and short notes on all aspects of pathogens and pathogen-host interactions. There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles.