Immune- and Stemness-Related Genes Revealed by Comprehensive Analysis and Validation for Cancer Immunity and Prognosis and Its Nomogram in Lung Adenocarcinoma - Chen, Mengqing; Wang, Xue; Wang, Wenjun; Gui, Xuemei; Li, Zhan (Frontiers in Immunology, 2022)
Abstract： Objective Lung adenocarcinoma (LUAD) is a familiar lung cancer with a very poor prognosis. This study investigated the immune and stemness related genes to develop model related with cancer immunity and prognosis in LUAD. Method The Cancer Genome Atlas(TCGA) was utilized for obtaining original transcriptome data and clinical information. Differential expression, prognostic value and correlation with clinic parameter of mRNA stemness index(mRNAsi) were conducted in LUAD. Significant mRNAsi related module and hub genes were screened using weighted gene coexpression network analysis(WGCNA). Meanwhile, immune related differential genes(IRGs) were screened in LUAD. Stem Cell index and immune-related differential genes(SC-IRGs) were screened and further developed to construct prognostic-related model and nomogram. Comprehensive analysis of hub genes and subgroups, involving enrichment in the subgroup(GSEA), gene mutation, genetic correlation, gene expression, immune, TMB, and drug sensitivity, were used bioinformatics and RT-PCR to demonstrate. Results Through difference analysis, mRNAsi of LUAD group was markedly higher than that of normal group. Clinical parameters(age, gender, T staging) were ascertained to be highly relevant to mRNAsi. MEturquoise and MEblue were found to be the most significant modules(including positive and negative correlations) related to mRNAsi via WGCNA. The functions and pathways of the two mRNAsi related modules were mainly enriched in tumorigenesis, development and metastasis. Combining Stem Cell index related differential genes and immune-related differential genes, 30 prognostic-related SC-IRGs were screened via COX regression analysis. Then 16 prognostic-related SC-IRGs were screened to construct a Lasso regression model at last. Additionally, model was successfully validated by using TCGA-LUAD and GSE68465, while c-index and the calibration curves were utilized to demonstrated the clinical value of our nomogram. Following validation of the model, GSEA, immune cell correlation, TMB, clinical relevance etc, have found significant difference in high and low risk groups, and 16 genes expression of the SC-IRGs model also were tested by RT-PCR. ADRB2, ANGPTL4, BDNF, CBLC, CX3CR1, IL3RA were found markedly different expression between tumor and normal group. Conclusion The SC-IRGs model and the prognostic nomogram could accurately predict LUAD survival. Our study used mRNAsi combined with immunity may lay a foundation for the future researches in LUAD.