Abstract
BACKGROUND: Aging, a multifaceted biological process, is thought to be associated with lung adenocarcinoma (LUAD) development and progression. However, it is unclear whether aging-related genes (ARGs) can predict tumor risk, chemotherapy and immunotherapy benefits, and prognosis in LUAD patients at different ages. METHODS: Gene expression datasets and clinical information of LUAD patients were downloaded from TCGA and GEO database. Univariate and multivariate Cox regression, and lasso algorithm were employed to identify the ARG signatures. Patients were stratified into high-risk and low-risk groups to evaluate the predictive accuracy using Kaplan-Meier curves, ROC curves, and time-dependent AUC. A nomogram was established to predict the survival probability. GSEA revealed potential pathways, and CIBERSORT indicated different immunologic status. TIDE score was used to predict the potential tumor response to immune checkpoint inhibitors, and GDSC was employed to evaluate the sensitivity of chemotherapeutic drugs. The correlation of TIDE score and patient age, as well as that of ARGs and patient age was investigated. And cell Culture and RT-qPCR for external validation for key gene. RESULTS: A novel gene signature based on seven ARGs was established, including BMP15, CD79A, CDKN3, CDX2, COL1A1, DKK1, and GRIK2. Our model demonstrated exceptional prediction accuracy for elderly LUAD patients of 71-90 years old. A nomogram model was constructed to predict the survival probability, and the C-index value was 0.737, indicating our prognostic nomogram model has high accuracy. Through external RT-qPCR validation, we found that CD79A expression in H1299 was higher than that of BEAS-2B. And novel immunotherapy and chemotherapy regimens were accordingly proposed for the elderly LUAD patients. CONCLUSION: We identified a novel gene signature based on seven ARGs for risk stratification, prognosis prediction and benefit evaluation of immunotherapy and chemotherapy in elderly LUAD patients.