PICan: An integromics framework for dynamic cancer biomarker discovery. Issue 6 (4th March 2015) - McArt, Darragh G.; Blayney, Jaine K.; Boyle, David P.; Irwin, Gareth W.; Moran, Michael; Hutchinson, Ryan A.; Bankhead, Peter; Kieran, Declan; Wang, Yinhai; Dunne, Philip D.; Kennedy, Richard D.; Mullan, Paul B.; et al.
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. Highlights: Novel methodology for integrating and interrogating phenomic, genomic and clinical data. Facilitates cancer biomarker discovery, patient stratification and digital pathology. Flexible and dynamic to accommodate large data cohorts and high‐throughput data. Applied to demonstrate utility on the biological and clinical relevance of TP53. PICan could recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.