Development and validation of a novel M1 macrophage-related gene prognostic signature for lung cancer

Abstract

Background: Lung cancer (LC) is the most common cancer. Using data from The Cancer Genome Atlas (TCGA), we analyzed the functional roles of M1 macrophage status in LC patients.Methods: Clinical and transcriptome data of LC patients were obtained from the TCGA dataset.We identified M1 macrophage-related genes in LC patients and investigated the underlying molecular mechanisms of these genes in LC patients. After performing a least absolute shrinkage and selection operator (LASSO) Cox regression analysis, the LC patients were divided into two subtypes, and the underlying mechanism of the association between them was further explored. A comparison of immune infiltration was conducted between the two subtypes. Based on gene set enrichment analysis (GSEA), the key regulators associated with subtypes were further explored.Results: M1 macrophage-related genes were identified using TCGA data, and these genes might be related to the activation of the immune response and cytokine-mediated signaling pathways in LC. A seven M1 macrophage-related gene signature (including STAT1, TAP1, UBE2L6, TAP2, CXCR6, PSMB8 and CD2) was identified in LC using LASSO Cox regression analysis. Two subtypes (low risk and high risk) of LC patients were created based on the seven M1 macrophage-related gene signature. Univariate and multivariate survival analyses further confirmed that the subtype classification was an effective independent prognostic factor.Moreover, the two subtypes were correlated with immune infiltration, and GSEA revealed that the pathways of tumor cell proliferation and immune-related biological processes (BPs) might play an important role in LC in the high-risk group and low-risk group, respectively.Conclusions: M1 macrophage-related subtypes of LC were identified and were closely associated with immune infiltration. The gene signature involved in M1 macrophage-related genes could help make a distinction and predict prognosis for LC patients.

Correlation between chromatin epigenetic-related lncRNA signature (CELncSig) and prognosis, immune microenvironment, and immunotherapy in non-small cell lung cancer

“…We downloaded RNA sequence transcription data (FPKM), RNA transcription data (n = 19508), and lncRNA transcription data (n = 13481) from the TCGA website ( https://portal.gdc.cancer.gov /). The Cancer Genome Atlas (TCGA) database is a comprehensive collection of genomic, epigenomic, and clinical data from cancer patients [ 12 , 13 ]. In addition, we also obtained relevant clinical samples of lung cancer, including the following information: age, sex, tumor grade, TNM, stage, survival time, and survival status.…”