The predictive value of RNA binding proteins in colon adenocarcinoma

Lipeng Luan; Feng Lu; Xiaochuan Wang; Yunliang Wang; Wei Wang; Yong Yang; Guoliang Chen; Huihui Yao; Xinyu Shi; Zihan Yuan; Guoqiang Zhou; Haitao Zhang; Songbing He

doi:10.21037/jgo-21-318

The predictive value of RNA binding proteins in colon adenocarcinoma

J Gastrointest Oncol. 2021 Aug;12(4):1543-1557. doi: 10.21037/jgo-21-318.

Authors

Affiliations

¹ Department of General Surgery, the First Affiliated Hospital of Soochow University, Suzhou, China.
² Center of Hepatobiliary Pancreatic Disease, Xu Zhou Central Hospital, Xuzhou, China.
³ Department of Oncology, Shengli Hospital of Shengli Oilfield, Dongying, China.
⁴ Department of Gastrointestinal Surgery, Changshu No. 2 Hospital, Suzhou, China.

Abstract

Background: RNA binding proteins (RBPs) play an important role in regulating post-transcriptional gene expression and have been reported to be closely associated with the occurrence and development of tumors. However, the effect of RBPs in colon cancer remains unclear.

Methods: We downloaded clinical information and transcriptome data of colon adenocarcinoma (COAD) from The Cancer Genome Atlas database (TCGA) database. After combining this data, we identified differentially expressed RBPs in normal and cancer tissues and subsequently performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Prognosis-related RBPs were identified via Cox regression analysis. The samples were randomly divided into two groups; an experimental group and a control group. A predictive model was constructed by dividing the experimental group into high- and low-risk subgroups based on the scores of the prognostic-related RBPs, and the prognosis of samples in these two subgroups was compared. Then, this model was applied to the control group. Finally, the model results were verified based on an online survival database and the Human Protein Atlas (HPA) database.

Results: A total of 469 differentially expressed RBPs were identified in normal and cancer tissues. Ten prognosis-related RBPs were determined by Cox regression analysis. In the prognostic prediction model, the prognosis of high-risk patients in the experimental group was worse than that in the low-risk group, and the same result was obtained in the control group. In addition, the risk score in the Cox regression analysis showed that the model could be used as an independent prognostic factor (P<0.001). The results of the online survival analysis tool, HPA database, and the model were consistent.

Conclusions: Some specific RBPs are significantly associated with the prognosis of patients with COAD, and this finding may provide important information for the future diagnosis and treatment of patients with COAD.

Keywords: Colon adenocarcinoma (COAD); RNA binding proteins (RBPs); bioinformatics; prognostic prediction model.