Abstract
Pancreatic adenocarcinoma (PAAD) is one of the deadliest malignancies. Aging is described as the degeneration of physiological function, which is complexly correlated with cancer. It is significant to explore the influences of aging-related genes (ARGs) on PAAD. Based on The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets, we used univariate Cox regression analysis and acquired eight differentially expressed ARGs with prognostic values. Two molecular subtypes were identified based on these ARGs to depict PAAD patients' overall survival (OS) and immune microenvironments preliminarily. Cluster 1 had a poor OS as well as a worse immune microenvironment. Through least absolute shrinkage and selection operator (LASSO) regression analysis, we constructed a seven-ARG risk signature based on the TCGA dataset and verified it in Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC) to predict the prognoses, immune microenvironments, signal pathways, tumor mutations, and drug sensitivity of PAAD patients. The high-risk group possessed an unfavorable OS compared with that of the low-risk group. We also verified the independence and clinical availability of the risk signature by Cox regression analyses and the establishment of a nomogram, respectively. The higher risk score was associated with several clinical factors such as higher grade and advanced tumor stage as well as lower immunoscore and cluster 1. The negative associations of risk scores with immune, stroma, and estimate scores proved the terrible immune microenvironment in the high-risk group. Relationships between risk score and immune checkpoint gene expression as well as signal pathways provided several therapeutic targets. PAAD patients in the low-risk group possessed lower tumor mutations as well as a higher susceptibility to axitinib and vorinostat. The high-risk group bore a higher TMB and cisplatin and dasatinib may be better options. We used immunohistochemistry and qPCR to confirm the expression of key ARGs with their influences on OS. In conclusion, we identified two ARG-mediated molecular subtypes and a novel seven-ARG risk signature to predict prognoses, immune microenvironments, signal pathways, tumor mutations, and drug sensitivity of PAAD patients.