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Published in: Cellular Oncology 4/2016

01-08-2016 | Original Paper

Weighted gene co-expression network analysis reveals key genes involved in pancreatic ductal adenocarcinoma development

Authors: Matteo Giulietti, Giulia Occhipinti, Giovanni Principato, Francesco Piva

Published in: Cellular Oncology | Issue 4/2016

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Abstract

Purpose

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Up till now, the patient’s prognosis remains poor which, among others, is due to the paucity of reliable early diagnostic biomarkers. In the past, candidate diagnostic biomarkers and therapeutic targets have been delineated from genes that were found to be differentially expressed in normal versus tumour samples. Recently, new systems biology approaches have been developed to analyse gene expression data, which may yield new biomarkers. As of yet, the weighted gene co-expression network analysis (WGCNA) tool has not been applied to PDAC microarray-based gene expression data.

Methods

PDAC microarray-based gene expression datasets, listed in the Gene Expression Omnibus (GEO) database, were analysed. After pre-processing of the data, we built two final datasets, Normal and PDAC, encompassing 104 and 129 patient samples, respectively. Next, we constructed a weighted gene co-expression network and identified modules of co-expressed genes distinguishing normal from disease conditions. Functional annotations of the genes in these modules were carried out to highlight PDAC-associated molecular pathways and common regulatory mechanisms. Finally, overall survival analyses were carried out to assess the suitability of the genes identified as prognostic biomarkers.

Results

Using WGCNA, we identified several key genes that may play important roles in PDAC. These genes are mainly related to either endoplasmic reticulum, mitochondrion or membrane functions, exhibit transferase or hydrolase activities and are involved in biological processes such as lipid metabolism or transmembrane transport. As a validation of the applied method, we found that some of the identified key genes (CEACAM1, MCU, VDAC1, CYCS, C15ORF52, TMEM51, LARP1 and ERLIN2) have previously been reported by others as potential PDAC biomarkers. Using overall survival analyses, we found that several of the newly identified genes may serve as biomarkers to stratify PDAC patients into low- and high-risk groups.

Conclusions

Using this new systems biology approach, we identified several genes that appear to be critical to PDAC development. As such, they may represent potential diagnostic biomarkers as well as therapeutic targets with clinical utility.
Appendix
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Metadata
Title
Weighted gene co-expression network analysis reveals key genes involved in pancreatic ductal adenocarcinoma development
Authors
Matteo Giulietti
Giulia Occhipinti
Giovanni Principato
Francesco Piva
Publication date
01-08-2016
Publisher
Springer Netherlands
Published in
Cellular Oncology / Issue 4/2016
Print ISSN: 2211-3428
Electronic ISSN: 2211-3436
DOI
https://doi.org/10.1007/s13402-016-0283-7

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