Analysis of the tumor immune environment identifies an immune gene set–based prognostic signature in non-small cell lung cancer
Guangran Guo, Longjun Yang, Yingsheng Wen, Gongming Wang, Rusi Zhang, Dechang Zhao, Zirui Huang, Xuewen Zhang, Yongbin Lin, Lanjun Zhang
Abstract
BACKGROUND: The tumor immune environment plays a critical role in lung cancer initiation and prognosis. Therefore, understanding how the tumor immune environment impacts the overall survival (OS) of patients with advanced lung cancer post immunotherapy is of great importance. In this article, we aimed to identify the immune components of lung cancer and develop an immune prognostic signature to predict OS. METHODS: Differentially expressed immune-related genes were calculated between tumor and normal tissues using expression data from The Cancer Genome Atlas (TCGA) database. Then univariate Cox regression analysis was conducted to select prognosis-related genes and the prognostic risk model was constructed by multivariate Cox regression analysis. Patient risk scores were calculated, and a clinical correlation analysis was performed within the risk model. In addition, immune cell infiltration patterns were identified to find the immune cell subtypes related to prognosis. RESULTS: ), were associated with more malignant clinical manifestations. Further, we discovered that extensive infiltration of B cells, dendritic cells, and mast cells indicated a favorable prognosis. CONCLUSIONS: The signature developed in this paper could be an effective model for estimating OS in lung cancer patients, and the immune cell infiltration analysis of the tumor immune microenvironment could shed light on more effective treatment in clinical practice.