Prognosis and immune correlation analysis of m1A/m5C/m6A/m7G regulated genes in gastric cancer

CHEN Xiaomei; WANG Anqi; YANG Jizhen; YU Miao

doi:10.3969/j.issn.1006-5725.2024.09.009

Abstract：Objective This study aims to develop a prognostic risk prediction model for gastric cancer based on m1A/m5C/m6A/m7G regulated genes and to investigate the relationship between this model and immunology.Methods The Cancer Genome Atlas(TCGA)gastric cancer dataset was utilized to identify m1A/m5C/m6A/m7G regulated genes with significant expression differences.A prognostic risk score(RS)model was constructed using univariate Cox regression analysis and the LASSO algorithm.The RS model was validated using the Kaplan-Meier(K-M)statistic and cell lines for RT-qPCR biological validation.A nomogram model was created using univariate and multivariate Cox regression analyses.The CIBERSORT algorithm and ESTIMATE package were employed to conduct immune correlation analysis.Results A prognostic RS model based on eight methylation regulated genes was developed to classify patients with gastric cancer as high-risk or low-risk.These eight genes showed significant expression in gastric cancer cell lines(P＜0.05).The TCGA-gastric cancer training set and GSE62254-validation set showed a substantial connection(P＜0.001)between overall survival rate(OS)and grouping status.The nomogram survival models accurately predicted 1-year(C-index = 0.703),3-year(C-index = 0.729),and 5-year(C-index = 0.734)survival rates.Immune correlation analysis showed that compared to the low-risk group,the high-risk group had higher immune scores and higher expression of immune checkpoint-related genes(P＜0.05).Conclusion We created a reliable prognostic RS model based on m1A/m5C/m6A/m7G regulated genes that can predict gastric cancer prognosis and guide individualized immunotherapy decisions.