Study and comparison of prognostic characteristics of lung adenocarcinoma based on tumor microenvironment gene set

Abstract

Abstract Background: TME (Tumor microenvironment) plays a key role in the occurrence and development of lung cancer. Further research on TME will provide more comprehensive insights into relevant prognostic biomarkers and potential therapeutic targets. The purpose of this study is to develop a better prognosis model to predict the OS (overall survival) time of LUAD patients by identifying the TME component in lung cancer (especially lung adenocarcinoma) and comparing it with previous similar research results. Methods: The original LUAD related data was from TCGA (the Cancer Genome Atlas). The DEGs (differentially expressed genes) related to TME in tumor tissues and normal tissues were calculated respectively. Then, NMF (nonnegative matrix factorization) clustering was applied to identify different subtypes. Univariate Cox regression analysis and lasso regression analysis were performed to screen genes with prognostic significance to construct the prognostic characteristics. Finally, ROC (receiver operating characteristic) curve and DCA (decision curve analysis) were used to verify the model both internally and externally. Results: Finally, we constructed a LUAD prognosis model containing five TME related genes (including C1QTNF6, PLEK2, FURIN, TM6SF1 and IGF2BP1). In our model, the survival time of high-risk group was indeed shorter. The prediction accuracy of the model was further verified by an independent cohort (GSE13213) in GEO (the Gene Expression Omnibus). In addition, we also integrated relevant clinical factors and drew a prognosis nomograph. The results showed that the patients in the high-risk group had less immune cell infiltration, more fibroblasts in the tissues, and poorer prognosis.