Models for Predicting Response to Immunotherapy and Prognosis in Patients with Gastric Cancer: DNA Damage Response Genes

• Published in: BioMed research international Vol. 2022; pp. 4909544 - 21
• Main Authors: Dong, Rui, Chen, Shuran, Lu, Fei, Zheng, Ni, Peng, Guisen, Li, Yan, Yang, Pan, Wen, Hexin, Qiu, Quanwei, Wang, Yitong, Wu, Huazhang, Liu, Mulin
• Format: Journal Article
• Language: English
• Published: United States Hindawi 19.12.2022; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Algorithms; Cancer; Care and treatment; Cell cycle; Cell Line, Tumor; Chemotherapy; Complex systems; Damage; Deoxyribonucleic acid; DNA; DNA damage; DNA Damage - genetics; DNA methylation; DNA repair; DNA-Binding Proteins; Drug therapy; Gastric cancer; Gene expression; Gene set enrichment analysis; Genes; Genetic aspects; Genomes; Health aspects; Humans; Immune checkpoint; Immunotherapy; Medical prognosis; Microenvironments; Microsatellite instability; Mutation; N6-methyladenosine; Nomograms; Patients; Prognosis; Receptor activity modifying proteins; Risk; Risk groups; Stomach cancer; Stomach Neoplasms - genetics; Stomach Neoplasms - therapy; Survival analysis; Transcription Factors; Tumor cells; Tumor Microenvironment; Tumors; China
• ISSN: 2314-6133; 2314-6141; 2314-6141
• DOI: 10.1155/2022/4909544

Objective. DNA damage response (DDR) is a complex system that maintains genetic integrity and the stable replication and transmission of genetic material. m6A modifies DDR-related gene expression and affects the balance of DNA damage response in tumor cells. In this study, a risk model based on m6A-modified DDR-related gene was established to evaluate its role in patients with gastric cancer. Methods. We downloaded 639 DNA damage response genes from the Gene Set Enrichment Analysis (GSEA) database and constructed risk score models using typed differential genes. We used Kaplan-Meier curves and risk curves to verify the clinical relevance of the model, which was then validated with the univariate and multifactorial Cox analysis, ROC, C-index, and nomogram, and finally this model was used to evaluate the correlation of the risk score model with immune microenvironment, microsatellite instability (MSI), tumor mutational burden (TMB), and immune checkpoints. Results. In this study, 337 samples in The Cancer Genome Atlas (TCGA) database were used as training set to construct a DDR-related gene model, and GSE84437 was used as external data set for verification. We found that the prognosis and immunotherapy effect of gastric cancer patients in the low-risk group were significantly better than those in the high-risk group. Conclusion. We screened eight DDR-related genes (ZBTB7A, POLQ, CHEK1, NPDC1, RAMP1, AXIN2, SFRP2, and APOD) to establish a risk model, which can predict the prognosis of gastric cancer patients and guide the clinical implementation of immunotherapy.