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Updated: May 27, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Integrated analysis of M2 macrophage-related gene prognostic model and single-cell sequence to predict immunotherapy
Meifang Li1, Zhiping Wang2, Bin Huang2
1Department of Medical Oncology, Fujian Cancer Hospital, Clinical Oncology School of Fujian Medical University, Fuzhou, China.
Background:
Lung adenocarcinoma (LUAD) patients have high heterogeneity. The significance and clinical value of M2 macrophage-related genes in LUAD require further exploration. We aimed to construct a prognostic signature to predict the immunotherapy efficacy and prognosis in LUAD.
Methods:
GSE26939 and GSE19188 chips were downloaded from the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analysis were used to screen M2 macrophage-related prognostic genes. A signature based on M2 macrophage-related prognostic genes was established and used to predict the prognosis and immunotherapy efficacy in LUAD.
Results:
Twenty-two M2 macrophage-related genes associated with the prognosis of LUAD were confirmed using WGCNA, and then two molecular subtypes were identified with significantly different survival, gene expressions, and clinic characteristics were classified. LASSO analysis identified nine M2 macrophage-related prognostic genes to establish a risk signature, classifying patients into low- and high-risk groups. Data indicated that low-risk patients had better survival. Moreover, the signature was an independent prognostic factor for LUAD and a potential biomarker for patients receiving immunotherapy. Single-cell transcriptome analysis may provide important information on molecular subtypes and heterogeneity.
Conclusion:
Risk signature based on M2 macrophage-related genes is a valuable tool for predicting prognosis and immunotherapy response in patients with LUAD.
