Identification of an RNA binding protein-related gene signature in hepatocellular carcinoma patients

Abstract

Background Hepatocellular carcinoma (HCC) is a common malignant primary cancer with high mortality. Previous studies have demonstrated that RNA binding proteins (RBPs) are involved in the biological processes of cancers, including hepatocellular cancer. Methods In this study, we aimed to identify the clinical value of RNA-binding proteins for hepatocellular carcinoma. We obtained gene expression and clinical data of hepatocellular carcinoma patients from the TCGA and ICGC databases. The prognostic value of RBP-related genes in patients with hepatocellular carcinoma and their function were studied by comprehensive bioinformatics analyses. The gene signature of SMG5, EZH2, FBLL1, ZNF239, and IGF2BP3 was generated by univariate and multivariate Cox regression and LASSO regression analyses. We built and verified a prognostic nomogram based on RBP-related genes. The gene signature was validated by the ICGC database. The expression of RBP-related genes was validated by the Oncomine database, the Human Protein Atlas and Kaplan–Meier plotter. Result Most RBP-related genes were significantly different in cancer and normal tissues. The survival of patients in the different groups was significantly different. The gene signature showed good performance for predicting the survival of HCC patients by having a better area under the receiver operating characteristic curve than other clinicopathological parameters. Conclusion Gene signatures based on RNA-binding proteins can be independent risk factors for hepatocellular carcinoma patients.

A Novel Ferroptosis-Related Gene Signature For Clinically Predicting Recurrence After Hepatectomy of Hepatocellular Carcinoma Patients.

“…Massive studies focus on establishing prognosticrelated gene signature models to improve diagnostic e ciency and overall survival prognosis [33]. Wang et al established an RNA-binding proteins-related gene signature to predict the overall survival and found that this gene signature can be an independent risk factor for HCC patients [34]. Yang and colleagues constructed a two-gene signature (HNRNPA2B1 and RBM15) to identify and treat HBV-related HCC patients and has the predictive value for OS [35].…”

Development and Validation of a Gene Mutation-Associated Nomogram for Hepatocellular Carcinoma Patients From Four Countries

“…The connections of mutations to cancer development and progression have led to advances in treatment, as various targeted therapies have focused on specific gene mutations ( Maemondo et al, 2010 ; Zhao et al, 2017 ; Christensen et al, 2020 ). However, few studies have taken advantage of these connections in a predictive way by aiming to develop nomograms based on specific genes to guide the prognosis of HCC ( Hsu et al, 2016 ; Wang et al, 2020 ). Our development of a strongly correlative predictive tool, then, fills an important gap in management of a common and deadly cancer.…”

Ferroptosis-Related Gene Signature Accurately Predicts Survival Outcomes in Patients With Clear-Cell Renal Cell Carcinoma

“…Subsequently, multivariate Cox regression analysis was performed on the candidate ferroptosis-related genes, and the prognostic model was determined based on the lowest AIC value. The risk score was calculated according to the expression level of each gene and its corresponding regression coefficient (18). The formula is established as follows: Risk Scor e = S n i=1 Coef (i) Â x(i), where Coef (i) and x(i) r e p r e s e n t t h e regression coefficient and the expression value of each prognosis related ferroptosis gene, respectively.…”