Identification of significant prognostic risk markers for pancreatic ductal adenocarcinoma: a bioinformatic analysis

Abstract

Objective: This study aimed to identify novel prognostic biomarkers of pancreatic ductal adenocarcinoma (PDAC) using bioinformatics analyzes. Methods: Clinical information, microRNAs (miRNAs), and genes expression profile data from PDAC cases were downloaded from the Cancer Genome Atlas (TCGA) database. The potential prognostic risk miRNAs and genes were screened using the Elastic Net Cox proportional risk regression hazards (EN-COX) model. The receiver operating characteristic (ROC) curve and the Kaplan-Meier (KM) curve were used to identify miRNAs and genes of significant prognostic risk. Furthermore, significant prognostic risk miRNAs were functional enrichment analyses based on their target genes. Furthermore, the survival analyzes of the hub genes were validated through OncoLnc. Results: Complete clinical records and expression data of 797 miRNAs and 19969 genes from 137 PDAC cases were obtained, of which 59 potential prognostic risk factors, including 54 genes and 5 miRNAs, were selected by EN-COX analyzes. A total of 17 significant prognostic risk markers were identified (all P<0.05), including 16 genes and 1 miRNA (miRNA-125a). The miRNA-125a target genes were found in the MiRWalk database and the function enrichment analyzes were performed in the the DAVID website. Furthermore, according to data from the Oncomine and Human Protein Atlas (HPA) databases, the mRNA and protein level of frizzled class receptor 8 (FZD8) were overexpressed in pancreatic cancer tissues compared to the corresponding noncancer normal tissues (P<0.001). However, both glutathione S-transferase mu 4 (GSTM4) and inducible T cell costimulator ligand (ICOSLG) were negatively regulated in tissues of pancreatic cancer tissues (P<0.001). Finally, survival analysis was used to validate these factors by the OncoLnc database, and the results revealed that overexpression of ICOSLG was associated with a better prognosis (P=0.025). Conclusions: This study showed that the expression levels of FZD8, GSTM4 and ICOSLG were significantly different between PDAC and non-tumor tissues, especially ICOSLG, which could be a prognostic indicator and therapeutic target for PDAC.