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

AbstractCellular 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.