DNA Damage Response Gene-Based Subtypes Associated With Clinical Outcomes in Early-Stage Lung Adenocarcinoma.

Abstract

DNA damage response (DDR) pathways play a crucial role in lung cancer. In this retrospective analysis, we aimed to develop a prognostic model and molecular subtype based on the expression profiles of DDR-related genes in early-stage lung adenocarcinoma (LUAD). A total of 1,785 lung adenocarcinoma samples from one RNA-seq dataset of The Cancer Genome Atlas (TCGA) and six microarray datasets of Gene Expression Omnibus (GEO) were included in the analysis. In the TCGA dataset, a DNA damage response gene (DRG)-based signature consisting of 16 genes was constructed to predict the clinical outcomes of LUAD patients. Patients in the low-DRG score group had better outcomes and lower genomic instability. Then, the same 16 genes were used to develop DRG-based molecular subtypes in the TCGA dataset to stratify early-stage LUAD into two subtypes (DRG1 and DRG2) which had significant differences in clinical outcomes. The Kappa test showed good consistency between molecular subtype and DRG (K = 0.61, p < 0.001). The DRG subtypes were significantly associated with prognosis in the six GEO datasets (pooled estimates of hazard ratio, OS: 0.48 (0.41-0.57), p < 0.01; DFS: 0.50 (0.41-0.62), p < 0.01). Furthermore, patients in the DRG2 group benefited more from adjuvant therapy than standard-of-care, which was not observed in the DRG1 group. In summary, we constructed a DRG-based molecular subtype that had the potential to predict the prognosis of early-stage LUAD and guide the selection of adjuvant therapy for early-stage LUAD patients.

• Authors: Yang Zhao, Bei Qing, Chunwei Xu, Jing Zhao, Yuchen Liao, Peng Cui, Guoqiang Wang, Shangli Cai, Yong Song, Liming Cao, Jianchun Duan
• Journal: Frontiers in molecular biosciences (Front Mol Biosci) Vol. 9 Pg. 901829 ( 2022) ISSN: 2296-889X [Print] Switzerland
• PMID: 35813819 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Zhao, Qing, Xu, Zhao, Liao, Cui, Wang, Cai, Song, Cao and Duan.