Identification of Prognosis-Related RNA-Binding Proteins to Reveal the Role of RNA-Binding Proteins in the Progression and Prognosis of Colon Cancer

Abstract

Yue Ding,1,* Lei Fang,2,* Xiao-Ping Yang,3 Qi Zou1 1Department of General Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, People’s Republic of China; 2Department of Radiology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, People’s Republic of China; 3Department of Hepatobiliary Pancreatic Surgery, First Hospital of Ningbo City, Ningbo, 315010, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qi ZouDepartment of General Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, People’s Republic of ChinaTel [phone]Fax [phone]Email [email protected] YangDepartment of Hepatobiliary Pancreatic Surgery, First Hospital of Ningbo City, No. 59 of Liuting Street, Haishu District, Ningbo, 315010, People’s Republic of ChinaTel [phone]Fax [phone]Email [email protected]: RNA binding proteins (RBPs) are now under discussion as novel promising bio-markers for patients with colon cancer. The purpose of our study is to identify several RBPs related to the progression and prognosis of colon cancer and to further investigate the mechanism of their influence on tumor progression.Methods: The transcriptome data of colon cancer and clinical characteristics were downloaded from The Cancer Genome Atlas (TCGA) database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA) were performed to elucidate the gene functions and relative pathways. Cox and Lasso regression analyses were used to analyze the effect of immune genes on the prognosis of colon cancer. An immune risk scoring model was constructed based on the statistical correlation between hub immune genes and survival. Meanwhile, multivariate Cox regression analysis was utilized to investigate whether the immune gene risk score model was an independent factor for predicting the prognosis of colon cancer. A nomogram was constructed to comprehensively predict the survival rate of colon cancer. P < 0.05 was considered statistically significant.Results: The results showed that 473 RBPs exhibited differential expression between normal and colon cancer tissues (P < 0.05). Univariate Cox regression analysis revealed 25 RBPs statistically correlated with colon cancer-related survival risk (P < 0.05). In addition, a 10-RBPs based risk scoring model was constructed through multivariate Cox regression analysis. A K–M curve indicated that high-risk patients were associated with poor outcomes (P < 0.001). A ROC curve indicated that the immune risk score model was reliable in predicting survival risk (5-year overall survival (OS), area under curve (AUC) = 0.782). Our model showed satisfying AUC and survival correlation in the validation dataset (5-year OS, AUC = 0.744). Furthermore, multivariate Cox regression analysis confirmed that the immune risk score model was an independent factor for predicting the prognosis of colon cancer. Finally, we found that 10-RBPs and risk scores were significantly associated with clinical factors and prognosis and were involved in multiple oncogenic pathways.Conclusion: Collectively, RBPs play an essential role in the progression and prognosis of colon cancer by regulating multiple biological pathways. Furthermore, the RBP risk score was an independent predictive factor of colon cancer, indicating poor survival.Keywords: RNA binding proteins, RBPs, colon cancer, prognosis, risk model

Keywords

• rna binding proteins (rbps)
• colon cancer
• prognosis
• risk model.