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Description

Despite numerous methods available to identify potential mRNA targets for miRNAs, prognostic relationship of these molecules in diseases like cancers where deregulation of gene expression is a major pathogenic factor, has not yet been emphasized. We performed in-silico identification of prognostically inversely correlated miRNA - mRNA pairs (PIC’s) in multiple cancers using expression data from The Cancer Genome Atlas. Partners in a PIC show inverse correlation of expression and opposite hazard implication. Using a three step approach, we identified a total of 1,253,443 PIC’s from 23 cancer types, several of which have previously been shown to have a predicted or experimentally validated relationship. A maximum 375,621 PICs were identified in Lower Grade Gliomas, while a minimum 300 PICs were identified in Prostate adenocarcinoma. Four miRNA-mRNA pairs were identified as PICs in 7 different cancer types. Two miRNA-mRNA pairs were identified as PICs in 5 different cancer types where the mRNA is also a validated target of miRNA. Organ specific analysis was performed to identify PICs common to cancers from same or related tissue of origin. We have also developed a database PROGTar for hosting our analysis results. PROGTar is available freely for non-commercial use at www.xvm145.jefferson.edu/progtar. We believe our method and analysis results will provide a novel prognostically relevant, pan-cancer perspective to study of miRNA-mRNA interactions and miRNA target validation.

Publication Date

1-7-2016

Keywords

In-silico identification of Prognostically Inversely Correlated miRNAs and mRNAs (PIC’s) in multiple cancers, Thomas Jefferson University, Department of Pathology, Anatomy and Cell Biology

Disciplines

Medical Anatomy | Medical Cell Biology | Medical Pathology

In-silico identification of Prognostically Inversely Correlated miRNAs and mRNAs (PIC’s) in multiple cancers

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