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This study identifies M2 macrophage-associated genes (M2RGs) using single-cell analyses to clarify their prognostic value and therapeutic relevance. Transcriptomic and scRNA-seq datasets from GEO and TCGA are analyzed, quantifying M2 infiltration via Cibersort and xCell, then linking these signals to PCa outcomes.",{"@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/m2-macrophage-related-genes-predict-prognosis-and-drug-response-in-prostate-cancer/352674/",{"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/m2-macrophage-related-genes-predict-prognosis-and-drug-response-in-prostate-cancer/352674.png","ImageObject",300,407,{"name":92,"@type":93},"WPS_1786070896","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main goal of this research in prostate cancer?","Question",{"text":112,"@type":113},"To pinpoint M2 macrophage-associated genes and evaluate how they relate to prognosis and drug response in prostate cancer.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which datasets and computational approaches were used to analyze M2 macrophages?",{"text":117,"@type":113},"Transcriptomic and scRNA-seq datasets from GEO and TCGA were used. M2 infiltration levels were quantified with Cibersort and xCell.",{"name":119,"@type":110,"acceptedAnswer":120},"How was the prognostic risk model (M2GS) built and validated?",{"text":121,"@type":113},"M2-related genes were selected using differential expression from scRNA-seq data, then a risk score model was developed with COX and LASSO regression. 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Discover Oncology (2026) 17:522 [https://doi.org/10.1007/s12672-026-04711-z](https://doi.org/10.1007/s12672-026-04711-z)  \nDiscover Oncology  \nANALYSIS Open Access  \nM2 macrophage related genes predict  \nprognosis and drug response in prostate cancer  \nZhikai Wu1,2†, Jianxin Li1,2†, Jintao Hu1,2†, Cong Lai1,2†, Zhuohang Li 1,3, Hao Yu1,3, Zhihan Yuan1,2, Mingzhou Dai 1,2, Juanyi Shi1,3, Cheng Liu 1,3* and Kewei Xu1,3,4*  \n†Zhikai Wu, Jianxin Li, Jintao Hu and Cong Lai have contributed equally to this work.  \n*Correspondence:  \nCheng Liu [liuch278@mail.sysu.edu.cn](liuch278@mail.sysu.edu.cn)[ ](liuch278@mail.sysu.edu.cn)Kewei Xu [xukewei@mail.sysu.edu.cn](xukewei@mail.sysu.edu.cn)[ ](xukewei@mail.sysu.edu.cn)1Department of Urology, SunYatsen Memorial Hospital, SunYat-sen University, Guangzhou 510000, Guangdong, China  \n2Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, SunYat-sen Memorial Hospital, Sun Yat-sen University,  \nGuangzhou 510000, Guangdong, China  \n3Guangdong Provincial Clinical Research Center for Urological Diseases, Guangzhou 510000, Guangdong, China  \n4South Medical University, Guangzhou 518000, Guangdong, China  \nAbstract  \nBackground M2 macrophages significantly contribute to the advancement of prostate cancer (PCa) . This research aims to pinpoint M2 macrophage-associated genes (M2RGs) by leveraging single-cell analyses, with a focus on evaluating their prognostic and therapeutic implications in PCa.  \nMethods We utilized transcriptomic and scRNA-seq datasets sourced from GEO and TCGA, analyzing both PCa and nearby non-cancerous tissues. M2 macrophage infiltration levels were quantified through“Cibersort” and “xCell” algorithms, followed by assessing their relationship with PCa outcomes. We identified M2RGs using differential expression analysis from scRNA-seq data. A risk score model (M2GS) was subsequently developed using COX and LASSO regression to predict biochemical recurrence-free survival (BRFS) and drug sensitivity. ROC curve analysis and subgroup assessments were conducted to evaluate model performance. Additionally, a nomogram integrating M2GS and clinical parameters was created to refine prediction accuracy.  \nResults Higher infiltration levels of M2 macrophages were linked to poorer outcomesin patients with prostate cancer (PCa) . Using COX regression and LASSO analyses, we identified seven M2 macrophage-related genes (M2RGs) with prognostic significance:  \nMTUS1, NFE2L2, CD9, NOP56, KIF22, RBM3, and RALGDS, which were incorporated into an M2-related gene signature (M2GS) . ROC analysis affirmed the model’s predictive capabilities, yielding AUC values of 0 . 702, 0 . 752, and 0.831 for predicting 1-, 3-, and 5-year survival, respectively. Subgroup analysis and violin plot comparisons highlighted distinct drug sensitivity patterns between high-and low-risk groups defined by M2GS. Both M2GS and T stage were independently validated as prognostic indicators. Thenomogram demonstrated consistent calibration and strong predictive performance. Conclusion Our prognostic risk scoring model effectively predicts BRFS and drug responsiveness in prostate cancer, providing clinicians with valuable guidance for tailoring individualized treatment strategies and follow-up protocols for patients. Keywords Prostate cancer, Single-cell sequencing analysis, M2 macrophages, Biochemical recurrence-free survival, Drug sensitivity, Risk score  \n© The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 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 ","cbCaiqfos1NudVIp","https://ap.wps.com/l/cbCaiqfos1NudVIp","pdf",4355320,15,"English","# Background\n## Tumor microenvironment and immunosuppression in PCa\n# Methods\n## Dataset sources and M2 infiltration quantification\n## Identification of M2RGs and construction of M2GS\n## Model evaluation and nomogram development\n# Results\n## Prognostic M2RGs and risk model performance\n## Drug sensitivity differences between risk groups\n# Conclusion","[{\"question\":\"What is the main goal of this research in prostate cancer?\",\"answer\":\"To pinpoint M2 macrophage-associated genes and evaluate how they relate to prognosis and drug response in prostate cancer.\"},{\"question\":\"Which datasets and computational approaches were used to analyze M2 macrophages?\",\"answer\":\"Transcriptomic and scRNA-seq datasets from GEO and TCGA were used. M2 infiltration levels were quantified with Cibersort and xCell.\"},{\"question\":\"How was the prognostic risk model (M2GS) built and validated?\",\"answer\":\"M2-related genes were selected using differential expression from scRNA-seq data, then a risk score model was developed with COX and LASSO regression. Performance was assessed using ROC analysis and a nomogram integrating M2GS and clinical parameters.\"}]","M2 macrophage related genes predict prognosis and drug response in prostate cancer | PDF",1790100776,38]