Identification of prognostic gene signature associated with microenvironment of lung adenocarcinoma

Abstract

BackgroundLung cancer has the highest morbidity and mortality worldwide, and lung adenocarcinoma (LADC) is the most common pathological subtype. Accumulating evidence suggests the tumor microenvironment (TME) is correlated with the tumor progress and the patient’s outcome. As the major components of TME, the tumor-infiltrated immune cells and stromal cells have attracted more and more attention. In this study, differentially expressed immune and stromal signature genes were used to construct a TME-related prognostic model for predicting the outcomes of LADC patients.MethodsThe expression profiles of LADC samples with clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) related to the TME of LADC were identified using TCGA dataset by Wilcoxon rank sum test. The prognostic effects of TME-related DEGs were analyzed using univariate Cox regression. Then, the least absolute shrinkage and selection operator (LASSO) regression was performed to reduce the overfit and the number of genes for further analysis. Next, the prognostic model was constructed by step multivariate Cox regression and risk score of each sample was calculated. Then, survival and Receiver Operating Characteristic (ROC) analyses were conducted to validate the model using TCGA and GEO datasets, respectively. The Kyoto Encyclopedia of Genes and Genomes analysis of gene signature was performed using Gene Set Enrichment Analysis (GSEA). Finally, the overall immune status, tumor purity and the expression profiles of HLA genes of high- and low-risk samples was further analyzed to reveal the potential mechanisms of prognostic effects of the model.ResultsA total of 93 TME-related DEGs were identified, of which 23 DEGs were up-regulated and 70 DEGs were down-regulated. The univariate cox analysis indicated that 23 DEGs has the prognostic effects, the hazard ratio ranged from 0.65 to 1.25 (p < 0.05). Then, seven genes were screened out from the 23 DEGs by LASSO regression method and were further analyzed by step multivariate Cox regression. Finally, a three-gene (ADAM12, Bruton Tyrosine Kinase (BTK), ERG) signature was constructed, and ADAM12, BTK can be used as independent prognostic factors. The three-gene signature well stratified the LADC patients in both training (TCGA) and testing (GEO) datasets as high-risk and low-risk groups, the 3-year area under curve (AUC) of ROC curves of three GEO sets were 0.718 (), 0.646 () and 0.643 (). The GSEA analysis indicated that highly expressed ADAM12, BTK, ERG mainly correlated with the activation of pathways involving in focal adhesion, immune regulation. The immune analysis indicated that the low-risk group has more immune activities and higher expression of HLA genes than that of the high-risk group. In sum, we identified and constructed a three TME-related DEGs signature, which could be used to predict the prognosis of LADC patients.

BTK Has Potential to Be a Prognostic Factor for Lung Adenocarcinoma and an Indicator for Tumor Microenvironment Remodeling: A Study Based on TCGA Data Mining

“…BTK was overexpressed in some solid tumors and their periphery cells in TME such as dendritic cells, macrophages, myeloid derived suppressor cells, and endothelial cells (15,16), suggesting that BTK might play a role in TME. Here we embarked from differentially expressed genes (DEGs) generated by comparison between immune components and stromal components in LUAD samples and revealed that the BTK might be a potential indicator for the alteration of TME status in LUAD.…”

Integrative modeling of multi-omics data for predicting tumor mutation burden in lung cancer patients

“…High TMB indicates the presence of more neoantigens in the tumor microenvironment, which promote the in ammatory response and result in the alteration of transcriptomic and epigenetic signature [47]. It has been proved that gene expression signatures in the tumor microenvironment were associated with the prognosis in NSCLC [48][49][50][51]. In agreement with previous studies, the differentially expressed genes between TMB-H and TMB-L patients identi ed in this study were found to enrich in the immune-related damaged DNA binding, nuclear division, nuclear chromosome segregation, organelle ssion, single-stranded DNA binding, ribonucleoprotein complex binding and pyrimidine metabolism (Additional le 2: Figure S2) [52][53][54][55][56].…”

GNG5 is a Novel Oncogene Associated with Poor Prognosis in Glioma Patients

“…Previous studies have reported a correlation between programmed death-1/ligand-1 (PD-1/PD-L1) and immune activity in tumors in triple-negative breast cancer [20]; Moreover, a large number of studies have shown that ssGSEA and ESTIMATE are highly reliable in the evaluation of tumor immune strati cation and immune invasion analysis [22,[49][50][51][52]. Furthermore, we analyzed the correlation between the expression of GNG5 and in ltration level of tumor-in ltrating immune cells using TIMER.…”