Construction and Validation of a Prognostic Model Based on Novel Senescence-Related Genes in Non-Small Cell Lung Cancer Patients with Drug Sensitivity and Tumor Microenvironment

Abstract

Cellular senescence contributes to cancer pathogenesis and immune regulation. Using the LASSO Cox regression, we developed a 12-gene prognostic signature for lung adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) and a Gene Expression Omnibus (GEO) dataset. We assessed gene expression, drug sensitivity, immune infiltration, and conducted cell line experiments. High-risk LUAD patients showed increased mortality risk and shorter survival (P < 0.001). Senescence-related gene analysis indicated differences in protein phosphorylation and DNA methylation between normal individuals and LUAD patients. The high-risk group showed a positive association with PD-L1 expression (P = 0.003). Single-cell sequencing data suggested PEBP1 might significantly impact T cell infiltration. We predicted potential sensitive compounds for 12 senescence genes and found GAPDH promoted cell line proliferation. We established a novel prognostic system based on a newly identified senescence gene. High-risk patients had elevated immunosuppressive markers, and PEBP1 might influence T cell infiltration significantly. GAPDH, expressed at higher levels in tumors, could affect cancer progression. Our drug prediction model may guide treatment selection.