[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-360811-105":59,"doc-detail-360811-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","pathology-derived-clinical-micro-architectural-diagnostics-of-tumour-microbiome-interactions-in-colorectal-cancer","Pathology-derived clinical micro-architectural diagnostics of tumour-microbiome interactions in colorectal cancer","","Classical colorectal tumour pathology staging overlooks microbiome-associated micro-architectural signatures that can inform intratumoral microbial ecology, prognosis, and treatment-relevant microbial risk. Using scanned USA pathology reports, the study quantifies microbiome-linked micro-architectural features via rule-based NLP, identifies barrier-disruption and invasion-access signatures, and builds a z-scored RMELS composite index. Results show high prevalence of these signatures, stage-dependent, heterogeneous patterns, and improved discrimination of early versus advanced disease beyond single-feature groups.",{"@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":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/pathology-derived-clinical-micro-architectural-diagnostics-of-tumour-microbiome-interactions-in-colorectal-cancer/360811/",{"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/pathology-derived-clinical-micro-architectural-diagnostics-of-tumour-microbiome-interactions-in-colorectal-cancer/360811.png","ImageObject",300,407,{"name":92,"@type":93},"Blitz","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-27","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is classical colorectal cancer pathology staging insufficient for tumour-microbiome insights?","Question",{"text":112,"@type":113},"Routine staging does not consider microbiome-associated tumour micro-architecture signatures, limiting understanding of intratumoral microbial ecology, prognostic stratification, and treatment-relevant microbial information.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were micro-architectural signatures extracted from pathology reports?",{"text":117,"@type":113},"The study used rule-based natural language processing on scanned TCGA pathology reports to extract microbiome-linked micro-architectural features.",{"name":119,"@type":110,"acceptedAnswer":120},"What is RMELS and how does it relate to clinical discrimination?",{"text":121,"@type":113},"RMELS is a z-scored composite index derived from the extracted signatures, discriminating early (T1) from advanced (T4) disease more effectively than barrier or invasion features alone.","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},360811,1790473950,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"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":145},24464137899374,"https://us-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Steele et al. Journal of Translational Medicine (2026) 24:856  \n[https://doi.org/10.1186/s12967-026-08426-1](https://doi.org/10.1186/s12967-026-08426-1)  \nJournal of Translational Medicine  \nRESEARCH Open Access  \nPathology-derived clinical micro-architectural  diagnostics of tumour-microbiome  \ninteractions in colorectal cancer  \nSinclair Steele1*, Pedzisai Mazengenya3 and Ramadhani Chambuso1,2*  \nAbstract  \nBackground Classical tumour pathology reports contain a largely untapped layer of information that may indicate tumour-microbial interactions. However, routine colorectal cancer pathology staging does not take into account microbiome-associated tumour micro-architecture signatures, thus limiting insights into intratumoral microbial ecology, prognostic stratification and treatment-relevant microbial information. In this study, we analysed scanned USA pathology reports to quantify likely intratumoral microbiome-associated micro-architectural signatures.  \nMethods We studied 1,978 TCGA colorectal cancer pathology reports from 1,249 colon adenocarcinomas, 559 rectal adenocarcinomas and 170 reports without a definitive anatomic site using rule-based natural language processing to extract microbiome-linked micro-architectural features. Barrier-disruption and invasion-access signatures were identified from the reports as microbiome-associated pathology micro-architecture signatures that occur with microbial-related necrosis, hypoxia, toxins, colonisation, persistence, metabolic activity and/or tumour interaction. We developed a z-scored composite index called Report-based Microbial Ecology Likelihood Score (RMELS) and used Kaplan-Meier log-rank analyses, multivariable Cox regression, Kruskal-Wallis tests and receiver operation characteristic curves with bootstrap confidence intervals. Proportional hazards assumptions were tested for statistical significance at two-sided p \u003C 0.05.  \nResults Microbiome-associated pathology micro-architectural signatures were highly prevalent in the pathology reports. Barrier-disruption features, including ulceration (41 . 1%) and mucin alteration (16 . 7%), were common and increased with tumour stage (Kruskal-Wallis p \u003C 0. 0001) . Prominent invasion-access features included infiltrative growth (59 .4%, 95% CI 57.2–61. 5), lymphovascular invasion (18 . 6%, 95% CI 17.0–20.4) and perineural invasion (22 . 9%, 95% CI 21.1–24. 8) . All showed heterogeneous, non-monotonic distributions across pathologic stages, indicating activation of microbial injury and invasion programmes. Integration of these features into our signature score, ordered tumours along a continuous microbiome-permissiveness gradient independent of pathological stage. With limited information, our signature score discriminated early (T1) from advanced (T4) disease more effectively than barrier or invasion features alone (AUC = 0 . 66, 95% CI 0 .58–0. 74, p \u003C 0. 0001) . Right-sided colonic tumours exhibited significantly  \n*Correspondence:  \nSinclair Steele[s.steele@ajman.ac.ae](s.steele@ajman.ac.ae)[ ](s.steele@ajman.ac.ae)Ramadhani Chambuso[r.chambuso@ajman.ac.ae](r.chambuso@ajman.ac.ae)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2026, modified publication 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercialNoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the articl","cbCaikyjfVdO74d6","https://ap.wps.com/l/cbCaikyjfVdO74d6","pdf",9854037,31,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions\n# Introduction","[{\"question\":\"Why is classical colorectal cancer pathology staging insufficient for tumour-microbiome insights?\",\"answer\":\"Routine staging does not consider microbiome-associated tumour micro-architecture signatures, limiting understanding of intratumoral microbial ecology, prognostic stratification, and treatment-relevant microbial information.\"},{\"question\":\"How were micro-architectural signatures extracted from pathology reports?\",\"answer\":\"The study used rule-based natural language processing on scanned TCGA pathology reports to extract microbiome-linked micro-architectural features.\"},{\"question\":\"What is RMELS and how does it relate to clinical discrimination?\",\"answer\":\"RMELS is a z-scored composite index derived from the extracted signatures, discriminating early (T1) from advanced (T4) disease more effectively than barrier or invasion features alone.\"}]","Pathology-derived clinical micro-architectural diagnostics of tumour-microbiome interactions in colorectal cancer | PDF",1790141666,78]