Identification of an Immune Classification and Prognostic Genes for Lung Adenocarcinoma Based on Immune Cell Signatures - Deng, Lili; Long, Fei; Wang, Ting; Dai, Ling; Chen, Huajian; Yang, Yujun; Xie, Guoming (Frontiers in Medicine, 2022)
Objective: Current advances in immunotherapy requires accurate tumor sub-classification due to the heterogeneity of lung adenocarcinoma (LUAD). This study aimed to develop a LUAD sub-classification system based on immune cell signatures and identified prognostic gene markers. Methods: Signatures related to the prognosis of TCGA-LUAD and 4 GSE cohorts were screened and intersected from 184 previously published immune cell signatures. The LUAD samples in the TCGA were clustered by ConsensusClusterPlus. Molecular characteristics, immune characteristics and sensitivity to immunotherapies/chemotherapies were compared. LDA score was established through Linear Discriminant Analysis (LDA). Co-expression module was constructed by Weighted Gene Co-Expression Network Analysis (WGCNA). Results: Four LUAD subtypes with different molecular and immune characteristics were identified. Significant differences in prognosis among the four subtypes were observed. The IS1 subtype with the worst prognosis showed the highest number of TMB, mutant genes, IFN γ score, angiogenesis score and immune score. 20 co-expression modules were generated by WGCNA. Blue module, sky blue module and light yellow module were significantly correlated with LUAD prognosis. The hub genes (CCDC90B, ARNTL2, RIPK2, SMCO2 and ADA and NBN) showing great prognostic significance were identified from the blue module. A total of 8 hub genes (NLRC3, CLEC2D, GIMAP5, CXorf65, PARP15, AKNA, ZC3H12D and ARRDC5) were found in the light yellow module. Except for CXorf65, the expression of the other 7 genes were significantly correlated with LUAD prognosis. Conclusion: This study determined four LUAD subtypes with different molecular and immune characteristics and 13 genes closely related to the prognosis of LUAD. The current findings could help understand the heterogeneity of LUAD immune classes.