PICan: An integromics framework for dynamic cancer biomarker discovery

Darragh G. McArt, Jaine K. Blayney, David P. Boyle, Gareth W. Irwin, Michael Moran, Ryan A. Hutchinson, Peter Bankhead, Declan Kieran, Yinhai Wang, Philip D. Dunne, Richard D. Kennedy, Paul B. Mullan, D. Paul Harkin, Mark A. Catherwood, Jacqueline A. James, Manuel Salto-Tellez*, Peter W. Hamilton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1234-1240
Number of pages7
JournalMolecular oncology
Issue number6
Early online date04 Mar 2015
Publication statusPublished - 01 Jun 2015


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