Mirna expression profiles identify drivers in colorectal and pancreatic cancers

Ada Piepoli, Francesca Tavano, Massimiliano Copetti, Tommaso Mazza, Orazio Palumbo, Anna Panza, Francesco Fabio Di Mola, Valerio Pazienza, Gianluigi Mazzoccoli, Giuseppe Biscaglia, Annamaria Gentile, Nicola Mastrodonato, Massimo Carella, Fabio Pellegrini, Pierluigi Di Sebastiano, Angelo Andriulli

Research output: Contribution to journalArticlepeer-review

Abstract

Background and Aim: Altered expression of microRNAs (miRNAs) hallmarks many cancer types. The study of the associations of miRNA expression profile and cancer phenotype could help identify the links between deregulation of miRNA expression and oncogenic pathways. Methods: Expression profiling of 866 human miRNAs in 19 colorectal and 17 pancreatic cancers and in matched adjacent normal tissues was investigated. Classical paired t-test and random forest analyses were applied to identify miRNAs associated with tissue-specific tumors. Network analysis based on a computational approach to mine associations between cancer types and miRNAs was performed. Results: The merge between the two statistical methods used to intersect the miRNAs differentially expressed in colon and pancreatic cancers allowed the identification of cancer-specific miRNA alterations. By miRNA-network analysis, tissue-specific patterns of miRNA deregulation were traced: the driving miRNAs were miR-195, miR-1280, miR-140-3p and miR-1246 in colorectal tumors, and miR-103, miR-23a and miR-15b in pancreatic cancers. Conclusion: MiRNA expression profiles may identify cancer-specific signatures and potentially useful biomarkers for the diagnosis of tissue specific cancers. miRNA-network analysis help identify altered miRNA regulatory networks that could play a role in tumor pathogenesis.

Original languageEnglish
Article numbere33663
JournalPLoS One
Volume7
Issue number3
DOIs
Publication statusPublished - Mar 30 2012

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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