{"title":"胶质母细胞瘤中与M2肿瘤相关巨噬细胞浸润相关的生物标志物鉴定。","authors":"Xue-Yuan Li, Zhi-Yun Yu, Hong-Jiang Li, Dong-Ming Yan, Chao Yang, Xian-Zhi Liu","doi":"10.3389/fneur.2025.1545608","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>M2 phenotype tumor-associated macrophages (TAMs) can promote tumor growth, invasion, chemotherapy resistance and so on, leading to malignant progression. The aim of this study was to identify novel prognostic profiles in glioblastoma (GBM) by integrating single-cell RNA sequencing (scRNA-seq) with bulk RNA-seq.</p><p><strong>Methods: </strong>We identified M2-associated genes by intersecting TAM marker genes derived from scRNA-seq with macrophage module genes from WGCNA RNA-seq data. Prognostic M2 TAM-related genes were determined using univariate Cox and LASSO regression analyses. In the following steps, prognostic characteristics, risk groups, and external validation were constructed and validated. The immune landscape of patients with GBM was examined by evaluating immune cells, functions, evasion scores, and checkpoint genes.</p><p><strong>Results: </strong>Analysis of scRNA-seq and bulk-seq data revealed 107 genes linked to M2 TAMs. Using univariate Cox and LASSO regression, 16 genes were identified as prognostic for GBM, leading to the creation and validation of a prognostic signature for GBM survival prediction.</p><p><strong>Conclusion: </strong>Our findings reveal the immune landscape of GBM and enhance understanding of the molecular mechanisms associated with M2 TAMs.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1545608"},"PeriodicalIF":2.7000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12117037/pdf/","citationCount":"0","resultStr":"{\"title\":\"Biomarker identification associated with M2 tumor-associated macrophage infiltration in glioblastoma.\",\"authors\":\"Xue-Yuan Li, Zhi-Yun Yu, Hong-Jiang Li, Dong-Ming Yan, Chao Yang, Xian-Zhi Liu\",\"doi\":\"10.3389/fneur.2025.1545608\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>M2 phenotype tumor-associated macrophages (TAMs) can promote tumor growth, invasion, chemotherapy resistance and so on, leading to malignant progression. The aim of this study was to identify novel prognostic profiles in glioblastoma (GBM) by integrating single-cell RNA sequencing (scRNA-seq) with bulk RNA-seq.</p><p><strong>Methods: </strong>We identified M2-associated genes by intersecting TAM marker genes derived from scRNA-seq with macrophage module genes from WGCNA RNA-seq data. Prognostic M2 TAM-related genes were determined using univariate Cox and LASSO regression analyses. In the following steps, prognostic characteristics, risk groups, and external validation were constructed and validated. The immune landscape of patients with GBM was examined by evaluating immune cells, functions, evasion scores, and checkpoint genes.</p><p><strong>Results: </strong>Analysis of scRNA-seq and bulk-seq data revealed 107 genes linked to M2 TAMs. Using univariate Cox and LASSO regression, 16 genes were identified as prognostic for GBM, leading to the creation and validation of a prognostic signature for GBM survival prediction.</p><p><strong>Conclusion: </strong>Our findings reveal the immune landscape of GBM and enhance understanding of the molecular mechanisms associated with M2 TAMs.</p>\",\"PeriodicalId\":12575,\"journal\":{\"name\":\"Frontiers in Neurology\",\"volume\":\"16 \",\"pages\":\"1545608\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12117037/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Neurology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fneur.2025.1545608\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Neurology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fneur.2025.1545608","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Biomarker identification associated with M2 tumor-associated macrophage infiltration in glioblastoma.
Purpose: M2 phenotype tumor-associated macrophages (TAMs) can promote tumor growth, invasion, chemotherapy resistance and so on, leading to malignant progression. The aim of this study was to identify novel prognostic profiles in glioblastoma (GBM) by integrating single-cell RNA sequencing (scRNA-seq) with bulk RNA-seq.
Methods: We identified M2-associated genes by intersecting TAM marker genes derived from scRNA-seq with macrophage module genes from WGCNA RNA-seq data. Prognostic M2 TAM-related genes were determined using univariate Cox and LASSO regression analyses. In the following steps, prognostic characteristics, risk groups, and external validation were constructed and validated. The immune landscape of patients with GBM was examined by evaluating immune cells, functions, evasion scores, and checkpoint genes.
Results: Analysis of scRNA-seq and bulk-seq data revealed 107 genes linked to M2 TAMs. Using univariate Cox and LASSO regression, 16 genes were identified as prognostic for GBM, leading to the creation and validation of a prognostic signature for GBM survival prediction.
Conclusion: Our findings reveal the immune landscape of GBM and enhance understanding of the molecular mechanisms associated with M2 TAMs.
期刊介绍:
The section Stroke aims to quickly and accurately publish important experimental, translational and clinical studies, and reviews that contribute to the knowledge of stroke, its causes, manifestations, diagnosis, and management.