Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis.

Jun Zhou,Xiaoliang Hui,Ying Mao,Liya Fan

doi:10.1042/bsr20190625

Jun Zhou, Xiaoliang Hui + Show 2 more

Open Access

https://doi.org/10.1042/bsr20190625

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Journal: Bioscience reports	Publication Date: Aug 2, 2019
Citations: 37	License type: CC BY 4.0

Affiliation: Zhejiang Hospital

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a class of the commonest malignant carcinomas. The present study aimed to elucidate the potential biomarker and prognostic targets in PDAC. The array data of GSE41368, GSE43795, GSE55643, and GSE41369 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed microRNAs (DEmiRNAs) in PDAC were obtained by using GEO2R, and overlapped DEGs were acquired with Venn Diagrams. Functional enrichment analysis of overlapped DEGs and DEmiRNAs was conducted with Metascape and FunRich, respectively. The protein–protein interaction (PPI) network of overlapped DEGs was constructed by STRING and visualized with Cytoscape. Overall survival (OS) of DEmiRNAs and hub genes were investigated by Kaplan–Meier (KM) plotter (KM plotter). Transcriptional data and correlation analyses among hub genes were verified through GEPIA and Human Protein Atlas (HPA). Additionally, miRNA targets were searched using miRTarBase, then miRNA–DEG regulatory network was visualized with Cytoscape. A total of 32 DEmiRNAs and 150 overlapped DEGs were identified, and Metascape showed that DEGs were significantly enriched in cellular chemical homeostasis and pathways in cancer, while DEmiRNAs were mainly enriched in signal transduction and Glypican pathway. Moreover, seven hub genes with a high degree, namely, V-myc avian myelocytomatosis viral oncogene homolog (MYC), solute carrier family 2 member 1 (SLC2A1), PKM, plasminogen activator, urokinase (PLAU), peroxisome proliferator activated receptor γ (PPARG), MET proto-oncogene, receptor tyrosine kinase (MET), and integrin subunit α 3 (ITGA3), were identified and found to be up-regulated between PDAC and normal tissues. miR-135b, miR-221, miR-21, miR-27a, miR-199b-5p, miR-143, miR-196a, miR-655, miR-455-3p, miR-744 and hub genes predicted poor OS of PDAC. An integrative bioinformatics analysis identified several hub genes that may serve as potential biomarkers or targets for early diagnosis and precision target treatment of PDAC.

Highlights

Pancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic neoplasm, accounting for approximately 90% of all pancreatic cancers (PCs), with a poor overall survival (OS) rate of 5–8% [1,2]
For the GSE41369 dataset, a total of 32 differentially expressed microRNA (DEmiRNA) (24 up-regulated and 8 down-regulated miRNAs, Figure 1A and Table 2) were extracted, and a total of 1828, 3233, and 1144 genes were extracted from the GSE41368, GSE43795, and GSE55643 datasets, respectively (Figure 1B–D); these miRNAs and genes were recognized as differentially expressed in PDAC samples compared with normal samples
The messenger RNA (mRNA) and miRNA expression data obtained from the Gene Expression Omnibus (GEO) database yielded an overall total of 150 genes (76 up-regulated and 74 down-regulated genes) and 32 miRNAs (24 up-regulated and 8 down-regulated miRNAs) that were differentially expressed in PDAC samples and normal tissues

Summary

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic neoplasm, accounting for approximately 90% of all pancreatic cancers (PCs), with a poor overall survival (OS) rate of 5–8% [1,2]. The preferred and most promising strategy for PC treatment is surgical resection, and the detection of PC during the surgically resectable stages has vast importance for ameliorating the survival benefit of patients with PC [4]. A wealth of previous studies have reported that microRNAs (miRNAs), a class of noncoding RNAs characterized by approximately 22 nucleotides in length, can inhibit the stability and translation of messenger RNAs (mRNAs) through binding to the specific sequence of genes, which are used as potential biomarkers for different kinds of cancer. No breakthrough in the conventional treatment strategy has been investigated because of the difficulty in the early diagnosis and ominous prognosis of PDAC, and there is urgent need to identify more genetic information about pivotal genes in the progression of this disease

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