AUTHOR=Zhai Wen-Yu , Duan Fang-Fang , Chen Si , Wang Jun-Ye , Zhao Ze-Rui , Wang Yi-Zhi , Rao Bing-Yu , Lin Yao-Bin , Long Hao 

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

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.770550

DOI=10.3389/fcell.2022.770550

ISSN=2296-634X

ABSTRACT=Aging is an inevitable process characterized by declining in many physiological activities, and has been known as a significant risk factor for kinds of malignancies, but there is a few of study 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 basis of results of LASSO and multivariate Cox analysis in the TCGA training dataset (n=492). Furtherly, the GSE73403 dataset (n=69) validated the prognostic performance of this ARG signature. Immunohistochemistry (IHC) stain was used to verify the expression of ARGs in the signature. A five ARG-based signature, including A2M, CHEK2, ELN, FOS and PLAU, was constructed in the TCGA dataset, and stratified patients into low- and high-risk group with significantly different overall survival (OS). The ARGs risk score remained to be considered as an independent indicator of OS in the multivariate Cox regression model for LUSC patients. Then, a prognostic nomogram incorporating the ARGs risk score with T-, N- and M-classification was established, it achieved a good discriminative ability with a C-index of 0.628 (95% confidence interval [CI]: 0.586-0.671) in the TCGA cohort and 0.648 (95% CI: 0.535-0.762) in the GSE73403 dataset. Calibration curves displayed excellent agreement between the actual observations and the nomogram-predicted survival. The IHC stain discovered these 5 ARGs were overexpression in LUSC tissues. Besides, the immune infiltration analysis in the TCGA cohort represented a distinctly differentiated infiltration of anti-tumor immune cells between the low- and high-risk groups. We identified a novel-ARG related prognostic signature, which may be served as a potential biomarker for individualized survival predictions and personalized therapeutic recommendation of anti-tumor immunity for patients with LUSC.