The prognostic value of bioinformatics analysis of ECM receptor signaling pathways and LAMB1 identification as a promising prognostic biomarker of lung adenocarcinoma

Abstract

Abstract Background Our study attempts to investigate the impact of genes related to the extracellular matrix (ECM) receptor interaction pathway on immune-targeted therapy and lung adenocarcinoma (LUAD) prognosis. Methods This study obtained LUAD chip data (GSE68465, GSE31210, GSE116959) from NCBI GEO. Moreover, we downloaded the gene data associated with the ECM receptor interaction pathway from the MsigDB database. Differentially expressed genes (DEGs) were identified using GEO2R, followed by analyzing their correlation with immune cell infiltration. Univariate Cox regression analysis screened out ECM-related genes significantly related to the survival prognosis of LUAD patients. Additionally, Lasso regression and multivariate Cox regression analysis helped construct a prognostic model. Patients were stratified by risk score and survival analyses. The prognostic models were evaluated using receiver operating characteristic curves, and risk scores and prognosis associations were analyzed using univariate and multivariate Cox regression analyses. We selected a core gene for GSEA and CIBERSORT analysis to determine its function and tumor-infiltrating immune cell proportion, respectively. Results The most abundant pathways among DEGs in LUAD primarily involved the cell cycle, ECM receptor interaction, protein digestion and absorption, p53 signaling pathway, complement and coagulation cascade, and tyrosine metabolism. Two ECM-associated subtypes were identified by consensus clustering. Besides, we validated an ECM-related prognostic model to predict LUAD survival, and it was associated with the tumor immune microenvironment (TME). Additional cross-analysis screened LAMB1 for further research. The results indicated that the survival time of LUAD patients with elevated LAMB1 expression was longer than those with low LAMB1 expression. GSEA and CIBERSORT analyses revealed that LAMB1 expression correlated with TME. Conclusions According to the GEO and TCGA databases, a prognostic model of LUAD patients depending on the ECM receptor interaction pathway was constructed. Screening out LAMB1 can become a prognostic risk factor for LUAD patients or a potential target during LUAD treatment.