Identification of a Ubiquitination-Related Gene Risk Model for Predicting Survival in Patients With Pancreatic Cancer.

Hao Zuo,Qibin Song,Na Li,Luojun Chen

doi:10.3389/fgene.2020.612196

Abstract

Pancreatic cancer is known as “the king of cancer,” and ubiquitination/deubiquitination-related genes are key contributors to its development. Our study aimed to identify ubiquitination/deubiquitination-related genes associated with the prognosis of pancreatic cancer patients by the bioinformatics method and then construct a risk model. In this study, the gene expression profiles and clinical data of pancreatic cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database and the Genotype-tissue Expression (GTEx) database. Ubiquitination/deubiquitination-related genes were obtained from the gene set enrichment analysis (GSEA). Univariate Cox regression analysis was used to identify differentially expressed ubiquitination-related genes selected from GSEA which were associated with the prognosis of pancreatic cancer patients. Using multivariate Cox regression analysis, we detected eight optimal ubiquitination-related genes (RNF7, NPEPPS, NCCRP1, BRCA1, TRIM37, RNF25, CDC27, and UBE2H) and then used them to construct a risk model to predict the prognosis of pancreatic cancer patients. Finally, the eight risk genes were validated by the Human Protein Atlas (HPA) database, the results showed that the protein expression level of the eight genes was generally consistent with those at the transcriptional level. Our findings suggest the risk model constructed from these eight ubiquitination-related genes can accurately and reliably predict the prognosis of pancreatic cancer patients. These eight genes have the potential to be further studied as new biomarkers or therapeutic targets for pancreatic cancer.

Highlights

Pancreatic cancer is a highly fatal disease, with 43,090 deaths every 5 years (Siegel et al, 2017), the 5-year overall survival rate is only 6% (Miller et al, 2019)
MRNA expression data from 178 patients with pancreatic cancer and 36 normal pancreatic tissues were used for gene set enrichment analysis (GSEA) analysis, and significant differences were found in two functions
Combined with Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, the results suggest that these genes are closely related to the ubiquitination process of pancreatic cancer

Summary

Introduction

Pancreatic cancer is a highly fatal disease, with 43,090 deaths every 5 years (Siegel et al, 2017), the 5-year overall survival rate is only 6% (Miller et al, 2019). Many factors contribute to low survival rates for pancreatic cancer. Pancreatic cancer is characterized by early recurrence and invasion and by chemical and radiation resistance (Adamska et al, 2018). In recent years, targeted therapy and emerging immunotherapy have opened up new prospects for the treatment of pancreatic cancer. The exploration of new therapeutic targets and prognostic biomarkers for pancreatic cancer still needs to be further carried out. Numerous studies have identified some sensitive and effective biomarkers for pancreatic cancer

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