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dc.contributor.author Swanton C
dc.contributor.author Larkin JM
dc.contributor.author Gerlinger M
dc.contributor.author Eklund AC
dc.contributor.author Howell M
dc.contributor.author Stamp G
dc.contributor.author Downward J
dc.contributor.author Gore M
dc.contributor.author Futreal PA
dc.contributor.author Escudier B
dc.contributor.author Andre F
dc.contributor.author Albiges L
dc.contributor.author Beuselinck B
dc.contributor.author Oudard S
dc.contributor.author Hoffmann J
dc.contributor.author Győrffy, Balázs
dc.contributor.author Torrance CJ
dc.contributor.author Boehme KA
dc.contributor.author Volkmer H
dc.contributor.author Toschi L
dc.contributor.author Nicke B
dc.contributor.author Beck M
dc.contributor.author Szallasi Z
dc.date.accessioned 2018-10-04T09:08:52Z
dc.date.available 2018-10-04T09:08:52Z
dc.date.issued 2010
dc.identifier 78751693800
dc.identifier.citation pagination=53, pages: 10; journalVolume=2; journalIssueNumber=8; journalTitle=GENOME MEDICINE;
dc.identifier.uri http://repo.lib.semmelweis.hu//handle/123456789/6267
dc.identifier.uri doi:10.1186/gm174
dc.description.abstract ABSTRACT : The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and how the PREDICT consortium will endeavor to identify a new generation of predictive biomarkers.
dc.relation.ispartof urn:issn:1756-994X
dc.title Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets
dc.type Journal Article
dc.date.updated 2018-08-31T05:18:09Z
dc.language.rfc3066 en
dc.identifier.mtmt 1436957
dc.identifier.wos 000208627100053
dc.identifier.pubmed 20701793
dc.contributor.department SE/AOK/K/ISZGYK/MTA-SE Gyermekgyógyászati és Nephrológiai Kutatócsoport
dc.contributor.department SE/AOK/K/I. Sz. Gyermekgyógyászati Klinika
dc.contributor.institution Semmelweis Egyetem


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