Construction and validation of a prognostic risk model for lung adenocarcinoma based on pyroptosis and necroptosis-related genes.

Abstract

e20034 Background: Lung cancer is a leading cause of cancer-related deaths worldwide, and lung adenocarcinoma (LUAD) is the most common subtype. Despite some progress in early detection and treatment, the prognosis remains poor, and the disease burden is substantial. Therefore, identifying new potential therapeutic targets is of great significance. This study aimed to screen pyroptosis and necroptosis-related genes associated with LUAD prognosis, construct a prognostic risk model for LUAD, and identify potential target genes associated with LUAD prognosis. Methods: LUAD data containing survival information were collected from the UCSC Xena and cBioPortal databases. The TCGA cohort, GSE68465, and GSE31210 cohorts were used as the training and validation sets, respectively. Bioinformatic analysis of pyroptosis and necroptosis characteristic genes was performed. Kaplan-Meier curves and log-rank tests were used to calculate the significance of differentially expressed genes. A prognostic risk score model was constructed and validated using LASSO regression. The expression levels and prognostic value of prognostic genes were analyzed based on the TCGA and GTEx databases. Results: Eight pyroptosis and necroptosis characteristic genes (GJB3, PLK1, GAPDH, LDHA, GNG7, PKP2, LYPD3, KRT6A) were used to construct a prognostic risk model for LUAD. Patients in the low-risk group in both the training and validation sets showed significant survival benefits, demonstrating good independent prognostic predictive ability. Analysis of the TCGA and GTEx databases showed that GJB3 among the eight risk genes had a high hazard ratio and significantly impacted the overall survival (OS) and disease-free survival (DFS) of LUAD. Conclusions: A prognostic risk model for lung adenocarcinoma based on pyroptosis and necroptosis-related genes was successfully constructed using data mining techniques. This model serves as an independent prognostic factor for lung adenocarcinoma with good predictive performance. GJB3 is highly and specifically expressed in lung adenocarcinoma and is a potential oncogene affecting prognosis.