Genome-Wide Profiling of a Prognostic RNA-Binding Protein Signature in Esophageal Cancer

Abstract

Background the roles of RNA-binding proteins (RBPs) in esophageal cancer (EC) need elucidation. Materials and methods The gene expression profiles and clinical data of patients with EC were downloaded from the Xena database. Candidate genes were obtained by taking the union of RBP genes, KEGG pathway-related genes and differentially expressed RBP genes from cluster analysis. Hub genes were extracted by PPI network construction. Result We built a Cox proportional hazards regression model with 7 prognostic RBPs (TRMT2A, PDHA1, MPRIP, KRI1, IL17A, HSPA1A and HIST1H4J). The risk score of each patient in the internal and external dataset cohorts was calculated and then the patients were divided into two groups based on the median. There were significant differences between the RBP risk score and response to chemotherapy, with low-risk patients being more likely to achieve CR. Finally, the risk score was revealed to be significantly related to OS by univariate and multivariate analyses, and pathological stage could also be used independently to predict the prognosis of EC. Conclusion Our study indicated that the RBP signature could serve as a prognostic biomarker of EC and provide new insight into chemoresistance in EC patients.

Stemness-related gene signature for predicting therapeutic response in patients with esophageal cancer

“…A previous report showed that a de novo variant in the human HIST1H4J gene causes a syndrome analogous to HIST1H4C-associated neurodevelopmental disorder (66). Furthermore, HIST1H4J is the strongest negative predictor of ovarian cancer (67) and an important prognostic and chemoresistance predictor of ESCA (68). Herein, upregulation expression of HIST1H4J (log 2 FC =1.39; q value =1.87×10 −3 ) was observed in patients with ESCA.…”