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Intra-tumor microbial data of five cancer types were obtained from the Cancer Microbiome Atlas, and corresponding clinical data from the Cancer Genome Atlas. Statistical testing and feature-selection pipelines identified optimal markers, then a support vector machine classifier and nomogram, validated with Kaplan-Meier analyses. Overall, 463 tumor samples and 47 controls were analyzed.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/microbial-signatures-in-head-and-neck-versus-gastrointestinal-tumors-identification-and-prognostic-modeling/349502/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/microbial-signatures-in-head-and-neck-versus-gastrointestinal-tumors-identification-and-prognostic-modeling/349502.png","ImageObject",300,407,{"name":92,"@type":93},"awa","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-28","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main objective of this study?","Question",{"text":112,"@type":113},"To identify intra-tumor microbial signatures that distinguish head and neck tumors from gastrointestinal tumors and evaluate their diagnostic and prognostic value.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which datasets were used to derive microbial and clinical information?",{"text":117,"@type":113},"Intra-tumor microbial data came from the Cancer Microbiome Atlas, while corresponding clinical data were retrieved from the Cancer Genome Atlas.",{"name":119,"@type":110,"acceptedAnswer":120},"How were microbial markers selected and models validated?",{"text":121,"@type":113},"Wilcoxon testing compared microbial populations, and univariate logistic regression with LASSO and recursive feature elimination selected optimal markers. Predictive performance was validated using a nomogram and Kaplan-Meier survival analyses.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},349502,1790128254,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":36},3985747858093,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","ORIGINAL ARTICLE  \nPolish Journal of Microbiology 2026, Vol. 75, No 2, 123-138  \n[https://doi.org/10.33073/pjm-2026-012](https://doi.org/10.33073/pjm-2026-012)  \nMicrobial Signatures in Head and Neck versus Gastrointestinal Tumors: Identification and Prognostic Modeling  \nHUA GUO1*, JIHAN WANG2, YAQI NIU3 and FUQIANG LIU4  \n1The Nursing Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China  \n2Yan’an Medical College, Yan’an University, Yan’an, Shaanxi, China  \n3Rheumatology Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China  \n4 Cardiovascular Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China  \nSubmitted 22 November 2025, accepted 10 March 2026, published online 31 July 2026  \nAbs t rac t  \nThis study identified key intra-tumor microbial signatures distinguishing head and neck cancers from gastrointestinal cancers and explored their diagnostic and prognostic potential. Intra-tumor microbial data of five cancer types were obtained from the Cancer Microbiome Atlas, and corresponding clinical data were retrieved from the Cancer Genome Atlas. The Wilcoxon test was used to analyze differences in microbial populations. Univariate logistic regression, least absolute shrinkage and selection operator, and recursive feature elimination were sequentially applied to screen optimal microbial markers, and a support vector machine classification model was constructed. A nomogram model and Kaplan-Meier curves were used to validate the predictive and prognostic value of the optimal microbes, respectively. Overall, 463 tumor samples and 47 controls were included. Twenty-three microbes showed significant differences in distribution between head and neck and gastrointestinal tumors; among these, eight overlapping microbes were selected as optimal markers. The SVM model based on these eight microbes achieved AUCs of 0.937 and 0.856 in the training and validation datasets, respectively. The nomogram model constructed with these markers showed high predictive accuracy (C-index = 0.8944 in training, 0.8023 in validation) . Kaplan-Meier analysis revealed that high abundance of Capnocytophaga, Lachnospiraceae, and Bacteroidales was significantly associated with longer overall survival in both head and neck tumors and gastrointestinal tumors (all P \u003C 0.05) . The eight intra-tumor microbial communities serve as a robust signature for distinguishing head and neck tumors from gastrointestinal tumors. Among these, Capnocytophaga, Lachnospiraceae, and Bacteroidales have potential as prognostic biomarkers to improve survival prediction in cancers.  \nK e y w o r d s: microbiota, head and neck tumors, gastrointestinal tumors, prognostic value, diagnosis  \nIntroduction  \nTraditionally, the human body hosts an estimated 10–100 trillion microorganisms, contributing to its internal ecosystem. Microbes and their collective microbial genome reflect an individual’s health status. Notably, microbial dysbiosis can lead to a variety of diseases, including inflammatory bowel disease and  \ndiabetes (Elinav et al. 2019), and increasing evidence supports the contribution of the microbiota in cancer development, with 15–20% of cancers driven by specific microbes (Sears and Garrett 2014) . The microbiota influences cancer risk through multiple mechanisms, including regulation of cellular proliferation, immune function, and host metabolism (Sears and Garrett 2014) . Among these, chronic inflammation is recog-  \n* Corresponding author: H Guo, The Nursing Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China;  \n[e-mail: yuanweisxs@outlook.com](e-mail: yuanweisxs@outlook.com)  \n© 2026 Hua Guo et al.  \nThis work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License (https://creativecommons. org/licenses/by-nc-nd/4.0/) .  \n124 Guo H. et al. 2  \nnized as a critical factor in tumor invasion, promotion, and dissemination, which may further affect treatment efficacy (Arthur ","cbCaijMeaEPAEUad","https://ap.wps.com/l/cbCaijMeaEPAEUad","pdf",2561562,16,"English","# Abstract\n# Introduction\n## Microbiota and cancer development\n## Rationale for intra-tumor microbial signatures\n## Head and neck tumors and oral microbiota\n## Gastrointestinal tumors and gut microbiota","[{\"question\":\"What is the main objective of this study?\",\"answer\":\"To identify intra-tumor microbial signatures that distinguish head and neck tumors from gastrointestinal tumors and evaluate their diagnostic and prognostic value.\"},{\"question\":\"Which datasets were used to derive microbial and clinical information?\",\"answer\":\"Intra-tumor microbial data came from the Cancer Microbiome Atlas, while corresponding clinical data were retrieved from the Cancer Genome Atlas.\"},{\"question\":\"How were microbial markers selected and models validated?\",\"answer\":\"Wilcoxon testing compared microbial populations, and univariate logistic regression with LASSO and recursive feature elimination selected optimal markers. Predictive performance was validated using a nomogram and Kaplan-Meier survival analyses.\"}]","Microbial Signatures in Head and Neck versus Gastrointestinal Tumors - Identification and Prognostic Modeling | PDF",1790083906]