Comprehensive Analysis of eRNAs and Genes Involved in Gastric Cancer and Constructing a Prognostic Model Predicting the Overall Survival of Patients

Abstract

Background: Gastric cancer (GC) is one of the most prevalent cancers and the first cause of cancer-related deaths in Iran. These patients are diagnosed at advanced stages, which leads to poor prognosis because there is inadequate knowledge of molecular factors to provide diagnostic/prognostic biomarkers. The aim of the current study was the comprehensive analysis of enhancer RNAs (eRNAs) to determine their molecular interactions with other genes and propose a survival-related model for patients. Methods: RNA-sequencing raw data of GC patients were downloaded from The Cancer Genome Atlas (TCGA), and differentially-expressed eRNAs and genes in tumor compared to non-tumor samples were extracted. The target genes of each eRNA were then identified based on physical distance and correlation and a regulatory network was constructed with these elements. A prognostic model for predicting the overall survival of patients was eventually established by performing univariate and multivariate Cox regression analyses, and the performance of the model was surveyed. Findings: By performing differential expression analysis, 69 and 2606 differentially-expressed eRNAs and genes were extracted, respectively and by identifying the relationships between these elements, a regulatory network consisting of 84 nodes and 119 edges was constructed. A three-components' survival-related model subsequently was established which had the ability to predict patients' outcomes. Conclusion: Based on the results, the 3-component constructed model, including an eRNA and two other genes, can be considered as a possible prognostic tool; however, further research is needed to clinically implement it. © 2023 Isfahan University of Medical Sciences(IUMS). All rights reserved.