ArticleCancer cell international2024
Decoding the immune microenvironment: unveiling CD8 + T cell-related biomarkers and developing a prognostic signature for personalized glioma treatment.
Article in Cancer cell international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Evaluating the role of astragalus polysaccharide in modulating immune infiltration and enhancing prognostic biomarkers in pediatric acute myeloid leukemia.Frontiers in pharmacology · 2025Article
- The Kinesin Eg5 Inhibitor K858 Enhances Radiosensitivity in Esophageal Squamous Cell Carcinoma and Affects the Expression of Epithelial-mesenchymal Transition Related Markers:Anti-cancer agents in medicinal chemistry · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundGliomas are aggressive brain tumors with poor prognosis. Understanding the tumor immune microenvironment (TIME) in gliomas is essential for developing effective immunotherapies. This study aimed to identify TIME-related biomarkers in glioma using bioinformatic analysis of RNA-seq data.
methodsIn this study, we employed weighted gene co-expression network analysis (WGCNA) on bulk RNA-seq data to identify TIME-related genes. To identify prognostic genes, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Based on these genes, we constructed a prognostic signature and delineated risk groups. To validate the prognostic signature, external validation was conducted.
resultsCD8 + T cell infiltration was strongly correlated with glioma patient prognosis. We identified 115 CD8 + T cell-related genes through integrative analysis of bulk-seq data. CDCA5, KIF11, and KIF4A were found to be significant immune-related genes (IRGs) associated with overall survival in glioma patients and served as independent prognostic factors. We developed a prognostic nomogram that incorporated these genes, age, gender, and grade, providing a reliable tool for clinicians to predict patient survival probabilities. The nomogram's predictions were supported by calibration plots, further validating its accuracy.
conclusionIn conclusion, our study identifies CD8 + T cell infiltration as a strong predictor of glioma patient outcomes and highlights the prognostic value of genes. The developed prognostic nomogram, incorporating these genes along with clinical factors, provides a reliable tool for predicting patient survival probabilities and has important implications for personalized treatment decisions in glioma.
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