Carcinogenesis · 2018 · 166 citations · 43 references
Life SciencesOncologySystems BiologyGene ExpressionMolecular OncologyPathway AnalysisCancer BiomarkersCancer GenomicsCancer TranscriptomicsGene Co-expression AnalysisNetwork-based Biomarker DiscoveryPancreatic CancerDifferential Transcript ExpressionDisease Prognostic BiomarkersGene Co-expression Network AnalysisGene Expression Network AnalysisPrognostic BiomarkersPromoter MethylationWeighted Gene Coexpression Network AnalysisWeighted Network Analysis
High mortality and low survival rates for pancreatic ductal adenocarcinoma (PDAC) mainly result from the delay in diagnosis and treatment. Therefore, there is an urgent need to identify early PDAC biomarkers and new therapeutic targets. In this study, we applied a commonly used systems biology approach, the weighted gene co-expression network analysis (WGCNA), on lncRNA expression data. Eleven lncRNAs, namely A2M-AS1, DLEU2, LINC01133, LINC00675, MIR155HG, SLC25A25-AS1, LINC01857, LOC642852 (LINC00205), ITGB2-AS1, TSPOAP1-AS1 and PSMB8-AS1 have been identified and validated on an independent PDAC expression dataset. Furthermore, we characterized them by functional and pathway enrichment analysis and identified which lncRNAs showed differential expression, differential promoter methylation levels and copy number alterations between normal and PDAC samples. Finally, we also performed a survival analysis and identified A2M-AS1, LINC01133, LINC00205 and TSPOAP1-AS1 as prognostic biomarkers for PDAC. Interestingly, although only a few cancer-associated lncRNAs have been functionally characterized, LINC00675 and LINC01133 lncRNAs have already been demonstrated to be involved in PDAC development and progression. Therefore, our results provide new potential diagnostic/prognostic biomarkers and therapeutic targets for PDAC that deserve to be further investigated. Moreover, these lncRNAs may improve the understanding about molecular pathogenesis of PDAC.
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