Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer

Ti-Wei Miao; De-Qing Yang; Li-Juan Gao; Jie Yin; Qi Zhu; Jie Liu; Yan-Qiu He; Xin Chen

doi:10.3389/fmolb.2022.942402

Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer

Front Mol Biosci. 2022 Aug 16:9:942402. doi: 10.3389/fmolb.2022.942402. eCollection 2022.

Authors

Ti-Wei Miao^{1

2}, De-Qing Yang³, Li-Juan Gao⁴, Jie Yin⁵, Qi Zhu¹, Jie Liu¹, Yan-Qiu He², Xin Chen¹

Affiliations

¹ Department of Integrated Traditional Chinese and Western Medicine, Zigong First People's Hospital, Zigong, China.
² Department of Integrated Traditional Chinese and Western Medicine, West China Hospital of Sichuan University, Chengdu, China.
³ Department of Pharmacy, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
⁴ Division of Pulmonary Diseases, Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China.
⁵ School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, China.

Abstract

Background: An imbalance in the redox homeostasis has been reported in multiple cancers and is associated with a poor prognosis of disease. However, the prognostic value of redox-related genes in non-small-cell lung cancer (NSCLC) remains unclear. Methods: RNA sequencing data, DNA methylation data, mutation, and clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Redox-related differentially expressed genes (DEGs) were used to construct the prognostic signature using least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan-Meier survival curve and receiver operator characteristic (ROC) curve analyses were applied to validate the accuracy of the gene signature. Nomogram and calibration plots of the nomogram were constructed to predict prognosis. Pathway analysis was performed using gene set enrichment analysis. The correlations of risk score with tumor stage, immune infiltration, DNA methylation, tumor mutation burden (TMB), and chemotherapy sensitivity were evaluated. The prognostic signature was validated using GSE31210, GSE26939, and GSE68465 datasets. Real-time polymerase chain reaction (PCR) was used to validate dysregulated genes in NSCLC. Results: A prognostic signature was constructed using the LASSO regression analysis and was represented as a risk score. The high-risk group was significantly correlated with worse overall survival (OS) (p < 0.001). The area under the ROC curve (AUC) at the 5-year stage was 0.657. The risk score was precisely correlated with the tumor stage and was an independent prognostic factor for NSCLC. The constructed nomogram accurately predicted the OS of patients after 1-, 3-, and 5-year periods. DNA replication, cell cycle, and ECM receptor interaction were the main pathways enriched in the high-risk group. In addition, the high-risk score was correlated with higher TMB, lower methylation levels, increased infiltrating macrophages, activated memory CD4⁺ T cells, and a higher sensitivity to chemotherapy. The signature was validated in GSE31210, GSE26939, and GSE68465 datasets. Real-time PCR validated dysregulated mRNA expression levels in NSCLC. Conclusions: A prognostic redox-related gene signature was successfully established in NSCLC, with potential applications in the clinical setting.

Keywords: NSCLC; cancer prognosis; gene signature; immune infiltration; redox homeostasis.