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

Abstract

Aging is an inevitable time-dependent process associated with a gradual decline in many physiological functions. Importantly, some studies have supported that aging may be involved in the development of lung adenocarcinoma (LUAD). However, no studies have described an aging-related gene (ARG)-based prognosis signature for LUAD. Accordingly, in this study, we analyzed ARG expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). After LASSO and Cox regression analyses, a six ARG-based signature (APOC3, EPOR, H2AFX, MXD1, PLCG2, and YWHAZ) was constructed using TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of overall survival (OS). Cox regression analysis indicated that the ARG signature was an independent prognostic factor in LUAD. A nomogram based on the ARG signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Moreover, to visualize the prediction results, we established a web-based calculator yurong.shinyapps.io/ARGs_LUAD/. Calibration plots showed good consistency between the prediction of the nomogram and actual observations. Receiver operating characteristic curve and decision curve analyses indicated that the ARG nomogram had better OS prediction and clinical net benefit than the staging system. Taken together, these results established a genetic signature for LUAD based on ARGs, which may promote individualized treatment and provide promising novel molecular markers for immunotherapy.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer

“…10,17 Aging can also promote carcinogenesis, tumor development and metastasis, 13,14,[17][18][19] and is a significant risk factor for colorectal tumor and lung carcinoma. 20,21 Therefore, novel aging-related markers can potentially be used to predict cancer prognosis, 33 so it is vital to understand the association between signature of aging and BC. In this study, our nomogram presented good calibration and discrimination in the TCGA set.…”

“…13,14,[17][18][19] Identifying key characteristics and induction of senescence in tumor cells has been a recent focus of cancer research, 13 as researchers have explored and confirmed their potential diagnostic or prognostic value as biomarkers in malignancy, including colorectal and lung cancer. 10,20,21 However, its prognostic value in BC remains unknown as no precise clinical signature has been established.…”

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

“…Regulation of tumor cellular senescence by ARGs can inhibit tumors, but ARGs can potentially promote tumor initiation, development, and metastasis ( Johnson et al, 2013 ; Mosteiro et al, 2016 ; Galluzzi et al, 2018 ; Calcinotto et al, 2019 ; Lee and Schmitt, 2019 ). Lately, the potential diagnostic or prognostic value of ARGs have been explored and confirmed in colorectal cancer and LUAD ( Xu and Chen, 2021 ; Yue et al, 2021 ). But its prognostic values and potential mechanisms in LUSC remain unknown, and no precise ARG-based risk signature has been developed for LUSC patients.…”

A Novel Inflammatory-Related Gene Signature Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma

“…With increasing convenience in data collection from open-access public databases, many studies concentrated on the relationship between RNA-seq data of specific gene sets and individual patient outcomes ( Wu et al, 2019 ; Qu et al, 2020 ; Zhu et al, 2020 ; Xu and Chen, 2021 ). These studies were limited to autophagy, aging, and immune infiltration, but most of them lack clinical applications.…”