Exploring an RNA binding proteins-associated prognostic model for Gastric Cancer

Abstract

Background: Gastric cancer (GC) is one of the most prevalent malignant cancers around the world. Given that abnormal RNA binding proteins (RBPs) are involved in the tumorigenesis, we aimed to explore the potential value of RBPs-associated genes in gastric cancer.Methods: RNA-seq and clinical data were retrieved from The Cancer Genome Atlas (TCGA) database and differentially expressed RBPs genes were screened. GO and KEGG pathway enrichment analyses were implemented to elucidate the roles of RBPs in GC. The protein-protein interaction (PPI) networks of RBPs were carried out, and the hub genes were determined by MCODE built in Cytoscape. The TCGA-STAD dataset was randomly divided into training and testing groups. A prognostic signature including five RBPs was developed within the training cohort after Cox regression and Lasso regression analyses. We used Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves to evaluate the capacity of the model in both groups. Then, a nomogram based on hub RBPs expression was established. Gene Set Enrichment Analysis was performed between the high-risk and low-risk group.Results: A total of 166 up-regulated RBPs and 130 down-regulated RBPs were identified. Via Cox regression and Lasso regression analysis within the training group, five hub RBPs (RNASE1, SETD7, BOLL, PPARGC1B, MSI2) were screened and the prognostic model was constructed. The risk score was calculated and gastric cancer patients were divided into high-risk and low-risk groups. In multivariate analysis, risk score was still an independent prognostic indicator (HR = 1.80, 95% CI = 1.45-2.22, P < 0.01). Patients with low risk had favorable survival rate in both training and testing group compared to those at high risk (P < 0.001). The areas under the ROC curves (AUC) of the prognostic model are 0.718 in the training cohort and 0.651 in the testing cohort. The hub RBPs-based nomogram model exhibited excellent ability to predict the OS of GC. GSEA illustrated that several cancer-related signaling pathways were enriched in patients with a high-risk score.Conclusions: This study discovered a five RBPs signature which might provide a potential prognostic value to GC patients.