title: Identification of candidate miRNA biomarkers for pancreatic ductal adenocarcinoma by weighted gene co-expression network analysis.
abstract: OBJECTIVE
  Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a dismal prognosis which is, among others, due to a lack of suitable biomarkers and therapeutic targets. Previously, basic gene expression analysis methods have been used for their identification, but recently new algorithms have been developed allowing more comprehensive data analyses. Among them, weighted gene co-expression network analysis (WGCNA) has already been applied to several cancer types with promising results.
  
  
  METHODS
  We applied WGCNA to miRNA expression data from PDAC patients. Specifically, we processed microarray-based expression data of 2555 miRNAs in serum from 100 PDAC patients and 150 healthy subjects. We identified network modules of co-expressed miRNAs in the healthy subject dataset and verified their preservation in the PDAC dataset. In the non-preserved modules, we selected key miRNAs and carried out functional enrichment analyses of their experimentally known target genes. Finally, we tested their prognostic significance using overall survival analyses.
  
  
  RESULTS
  Through WGCNA we identified several miRNAs that discriminate healthy subjects from PDAC patients and that, therefore, may play critical roles in PDAC development. At a functional level, we found that they regulate p53, FoxO and ErbB associated cellular signalling pathways, as well as cell cycle progression and various genes known to be involved in PDAC development. Some miRNAs were also found to serve as novel prognostic biomarkers, whereas others have previously already been proposed as such, thereby validating the WGCNA approach. In addition, we found that these novel data may explain at least some of our previous PDAC gene expression analysis results.
  
  
  CONCLUSIONS
  We identified several miRNAs critical for PDAC development using WGCNA. These miRNAs may serve as biomarkers for PDAC diagnosis/prognosis and patient stratification, and as putative novel therapeutic targets.
authors.affiliation: Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy. m.giulietti@univpm.it.
authors.forename: M
authors.identifier: http://orcid.org/0000-0002-9871-265X
authors.initials: M
authors.lastname: Giulietti
authors.affiliation: Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy.
authors.forename: G
authors.initials: G
authors.lastname: Occhipinti
authors.affiliation: Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy.
authors.forename: G
authors.initials: G
authors.lastname: Principato
authors.affiliation: Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy.
authors.forename: F
authors.initials: F
authors.lastname: Piva
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D021441:Carcinoma, Pancreatic Ductal / Q000235:genetics*; D016000:Cluster Analysis; D030541:Databases, Genetic; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism; D008875:Middle Aged; D058977:Molecular Sequence Annotation; D010190:Pancreatic Neoplasms / Q000235:genetics*; D012307:Risk Factors
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs
keywords: Biomarkers; PDAC; Pancreatic cancer; Systems biology; WGCNA; miRNA expression