| Literature DB >> 25814194 |
Darragh G McArt1, Jaine K Blayney1, David P Boyle1, Gareth W Irwin1, Michael Moran1, Ryan A Hutchinson1, Peter Bankhead1, Declan Kieran1, Yinhai Wang1, Philip D Dunne1, Richard D Kennedy1, Paul B Mullan1, D Paul Harkin1, Mark A Catherwood1, Jacqueline A James1, Manuel Salto-Tellez2, Peter W Hamilton3.
Abstract
Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.Entities:
Keywords: Biomarker discovery; Digital pathology; Pathology integromics
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Year: 2015 PMID： 25814194 PMCID： PMC5528750 DOI： 10.1016/j.molonc.2015.02.002
Source DB: PubMed Journal: Mol Oncol ISSN： 1574-7891 Impact factor: 6.603