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Circulating microbial DNA can reflect the host microbiome overview, yet its relationship with non-small cell lung cancer (NSCLC) prognosis and underlying mechanisms in the tumor immune microenvironment remains unclear. Blood microbiome and matched tumor RNA-seq data from TCGA NSCLC patients were integrated to build a MAPS prognostic scoring model and evaluate associations with survival, immune microenvironment features, and treatment efficacy.",{"@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/leveraging-circulating-microbiome-signatures-to-predict-tumor-immune-microenvironment-and-prognosis-of-patients-with-non-small-cell-lung-cancer/406292/",{"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/leveraging-circulating-microbiome-signatures-to-predict-tumor-immune-microenvironment-and-prognosis-of-patients-with-non-small-cell-lung-cancer/406292.png","ImageObject",300,407,{"name":92,"@type":93},"Elsa","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-05","2026-09-28",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 MAPS in this study and how was it constructed?","Question",{"text":112,"@type":113},"MAPS (circulating microbial abundance prognostic scoring) is a model built from circulating microbiome signatures identified using univariate and multivariate Cox regression. It was constructed to predict overall survival in NSCLC patients.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does circulating MAPS relate to the tumor immune microenvironment?",{"text":117,"@type":113},"Joint analysis of blood microbiome and matched tumor RNA-seq data shows interactions between circulating prognostic microbiome signatures and immune features. MAPS-low and MAPS-high groups show different enrichment patterns in immune cell populations and immune-related pathways.",{"name":119,"@type":110,"acceptedAnswer":120},"What does the study suggest about MAPS for treatment response?",{"text":121,"@type":113},"Drug sensitivity analysis indicates that circulating MAPS may help predict chemotherapy efficacy. 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Journal of Translational Medicine (2023) 21:800  \n[https://doi.org/10.1186/s12967-023-04582-w](https://doi.org/10.1186/s12967-023-04582-w)  \nJournal of Translational Medicine  \n RESEARCH Open Access  \nLeveraging circulating microbiome signatures to predict tumor immune microenvironment and prognosis of patients with non-small cell lung cancer  \nXiaohan Zhou1†, Liting You1,2†, Zhaodan Xin1, Huiting Su3, Juan Zhou1* andYing Ma 1*  \nAbstract  \nBackground Accumulating evidence supports the significant role of human microbiome in development and therapeutic response of tumors. Circulating microbial DNA is non-invasive and could show a general view of the microbiome of host, making it a promising biomarker for cancers. However, whether circulating microbiome is associated with prognosis of non-small cell lung cancer (NSCLC) and its potential mechanisms on tumor immune microenvironment still remains unknown.  \nMethods The blood microbiome data and matching tumor RNA-seq data of TCGA NSCLC patients were obtained from Poore’s study and UCSC Xena. Univariate and multivariate Cox regression analysis were used to identify circulating microbiome signatures associated with overall survival (OS) and construct the circulating microbial abundance prognostic scoring (MAPS) model. Nomograms integrating clinical characteristics and circulating MAPS scores were established to predict OS rate of NSCLC patients. Joint analysis of blood microbiome data and matching tumor RNA-seq data was used to deciphered the tumor microenvironment landscape of patients in circulating MAPS-high and MAPS-low groups. Finally, the predictive value of circulating MAPS on the efficacy of immunotherapy and chemotherapy were assessed.  \nResults A circulating MAPS prediction model consisting of 14 circulating microbes was constructed and had an independent prognostic value for NSCLC. The integration of circulating MAPS into nomograms may improve the prognosis predictive power. Joint analysis revealed potential interactions between prognostic circulating microbiome and tumor immune microenvironment. Especially, intratumor plasma cells and humoral immune response were enriched in circulating MAPS-low group, while intratumor CD4 + Th2 cells and proliferative related pathways were enriched in MAPS-high group. Finally, drug sensitivity analysis indicated the potential of circulating MAPS as a predictor of chemotherapy efficacy.  \n†Xiaohan Zhou and Liting You contributed equally to this work.  \n*Correspondence:  \nJuan Zhou [zhoujuan39@wchscu.cn](zhoujuan39@wchscu.cn)[ ](zhoujuan39@wchscu.cn)Ying Ma[maying@scu.edu.cn](maying@scu.edu.cn)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 changes were made. 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 article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ()[. The Creative Commons Public Domain Dedication waiver (](http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ()[http://creativeco](http://creativeco)[mmons.org/publicdomain/zero/1.0/](mmons.org/publicdomain/zero/1.0/)) applies to the data made available in this","cbCaihCPTy910drk","https://ap.wps.com/l/cbCaihCPTy910drk","pdf",2454471,15,"English","# Abstract\n# Introduction\n## Rationale for NSCLC prognosis biomarkers\n## Role of microbiome in tumorigenesis and immune shaping\n# Methods\n## Data sources and cohort integration\n## Cox regression and MAPS model construction\n## Nomograms and microenvironment analysis\n## Assessment of immunotherapy and chemotherapy relevance\n# Results\n## MAPS prediction model performance\n## Associations with immune microenvironment features\n## Drug sensitivity implications","[{\"question\":\"What is MAPS in this study and how was it constructed?\",\"answer\":\"MAPS (circulating microbial abundance prognostic scoring) is a model built from circulating microbiome signatures identified using univariate and multivariate Cox regression. It was constructed to predict overall survival in NSCLC patients.\"},{\"question\":\"How does circulating MAPS relate to the tumor immune microenvironment?\",\"answer\":\"Joint analysis of blood microbiome and matched tumor RNA-seq data shows interactions between circulating prognostic microbiome signatures and immune features. MAPS-low and MAPS-high groups show different enrichment patterns in immune cell populations and immune-related pathways.\"},{\"question\":\"What does the study suggest about MAPS for treatment response?\",\"answer\":\"Drug sensitivity analysis indicates that circulating MAPS may help predict chemotherapy efficacy. The study also evaluates the predictive value of MAPS for immunotherapy and chemotherapy outcomes.\"}]","Leveraging circulating microbiome signatures to predict tumor immune microenvironment and prognosis of patients with non-small cell lung cancer | PDF",1790564669,38]