Comprehensive bioinformatics analysis of prognosis and immunotherapy in lung adenocarcinoma.

Abstract

Background: Research has shown that genetic mutations play an important role in the prognosis of lung adenocarcinoma (LUAD). However, the genes that influence the prognosis and immunotherapy of lung cancer patients have not yet been thoroughly studied. In this study, data from The Cancer Genome Atlas (TCGA) Program and other databases were used to identify the survival-related genes in LUAD.

Methods: First, the TCGA database was used to screen key LUAD genes. Second, the Gene Expression Profiling Interactive Analysis 2 (GEPIA2), University of ALabama at Birmingham CANcer (UALCAN), Tumor IMmune Estimation Resource (TIMER), Kaplan-Meier plotter, and cBioPortal databases, and a univariate Cox analysis combined with a random forest (RF) model were used to estimate gene expression, patient prognosis, and gene mutations, respectively. TIMER was also used to predict the immune function of the genes.

Results: A total of 2,138 up-regulated and 2,559 down-regulated differentially expressed genes (DEGs) were identified from TCGA-LUAD dataset. Next, four prognostic genes (i.e., CENPH, SLC35F4, TESMIN, and TERT) were identified as the key genes. The expression levels of all four genes were higher in LUAD tissues than those in the normal lung tissues, but only CENPH and TESMIN were correlated with poor overall survival (OS). The four genes were also found to be associated with immunoinfiltration.

Conclusions: Of the four key genes identified, CENPH and TESMIN would not only contribute to the diagnosis and prognosis of LUAD but could also serve as potential immunotherapy targets for LUAD.