An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Squamous Carcinoma.

ABSTRACT: Aging is an inevitable process characterized by a decline in many physiological activities, and has been known as a significant risk factor for many kinds of malignancies, but there are few studies about aging-related genes (ARGs) in lung squamous carcinoma (LUSC). We designed this study to explore the prognostic value of ARGs and establish an ARG-based prognosis signature for LUSC patients. RNA-sequencing and corresponding clinicopathological data of patients with LUSC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The ARG risk signature was developed on the basis of results of LASSO and multivariate Cox analysis in the TCGA training dataset (n = 492). Furthermore, the GSE73403 dataset (n = 69) validated the prognostic performance of t

SUBMITTER: Zhai WY 

PROVIDER: S-EPMC8921527 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature