Screening and Validation of Independent Predictors of Poor Survival in Pancreatic Cancer.

Shui Liu,Jiyao Sheng,Yan Cai,E Changyong,Xuewen Zhang

doi:10.3389/pore.2021.1609868

Abstract

Pancreatic cancer is a digestive system malignant tumor with high mortality and poor prognosis, but the mechanisms of progression remain unclear in pancreatic cancer. It’s necessary to identify the hub genes in pancreatic cancer and explore the novel potential predictors in the prognosis of pancreatic cancer. We downloaded two mRNA expression profiles from Gene Expression Omnibus and The Cancer Genome Atlas Pancreatic Cancer (TCGA-PAAD) datasets to screen the commonly differentially expressed genes in pancreatic cancer by limma package in R. Subsequently, measurement of the functional similarity among the 38 DEGs in common was performed to identify the hub genes using GOSemSim package. Then, survival analysis and Cox regression were applied to explore prognosis-related hub genes using the survival package. Statistics analysis by two-tailed Student’s t-test or one-way based on TCGA-PAAD datasets and qPCR detection in clinical samples were performed to explore the correlations between expression of hub genes in pancreatic cancer tissues and clinical parameters. Based on integrated analysis of TCGA and GEO datasets, we screened 38 DEGs in common, which were all up-regulated. The functional similarity results showed that 10 DEGs including TSPAN1, MSLN, C1orf116, PKP3, CEACAM6, BAIAP2L1, PPL, RAB25, ERBB3, and AP1M2 in the DEGs in common, which had the higher average functional similarity, were considered as the hub genes. Survival analysis results and Cox regression analysis showed that TSPAN1, CEACAM6, as well as ERBB3 were all associated with poor overall survival of PC. qPCR results showed that the expression levels of TSPAN1 and ERBB3 were significantly upregulated in the PC tissues. The statistical analysis results revealed that TSPAN1 expression correlated significantly with histologic grade, T stage, clinical stage, and vital status by two-tailed Student’s t-test or one-way ANOVA; ERBB3 expression correlated significantly with T stage, clinical stage, and vital status by two-tailed Student’s t-test or one-way ANOVA. We found that TSPAN1 and ERBB3 could be independent predictors of poor survival in pancreatic cancer.

Highlights

Pancreatic cancer (PC) is a common digestive system malignant tumor that is characterized by high mortality and poor prognosis
We identified differentially expressed genes (DEGs) in PC based on a comprehensive analysis of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas Pancreatic Cancer (TCGA-PAAD), and obtained the hub genes through measurement of functional similarity
A total of 38 upregulated DEGs was identified from the two GEO profile datasets and TCGA-PAAD RNA-Seq expression datasets (Table 1; Figure 2)

Summary

Introduction

Pancreatic cancer (PC) is a common digestive system malignant tumor that is characterized by high mortality and poor prognosis. There are more than 458,918 estimated new cases and 432,242 estimated death cases every year around the world in 2018 [1]. Due to its high malignancy, the 5-years survival rate of PC patients is only 10% [2]. Identification of new independent prognostic biomarkers is still of great significance for patients with PC for improving treatment and prognosis of PC patients. Public databases, including the well-known The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, etc., have been widely applied in screening of the molecular mechanisms of PC, which could provide powerful support for identification of effective and accurate prognosis predictors of PC patients [3, 4]

Methods

Results

Conclusion