TY - JOUR
T1 - Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets
AU - Swanton, Charles
AU - Larkin, James M.
AU - Gerlinger, Marco
AU - Eklund, Aron C.
AU - Howell, Michael
AU - Stamp, Gordon
AU - Downward, Julian
AU - Gore, Martin
AU - Futreal, P. Andrew
AU - Escudier, Bernard
AU - Andre, Fabrice
AU - Albiges, Laurence
AU - Beuselinck, Benoit
AU - Oudard, Stephane
AU - Hoffmann, Jens
AU - Gyorffy, Balázs
AU - Torrance, Chris J.
AU - Boehme, Karen A.
AU - Volkmer, Hansjuergen
AU - Toschi, Luisella
AU - Nicke, Barbara
AU - Beck, Marlene
AU - Szallasi, Zoltan
N1 - Funding Information:
JML has accepted honoraria and grants from both Novartis and Pfizer, SO and BE have accepted honoraria from both Novartis and Pfizer. CS receives clinical translational trial grant funding from Novartis. Pfizer and Novartis are providing trials funding for S-PREDICT/PREINSUT and E-PREDICT, respectively. The other authors declare that they have no competing interests.
Funding Information:
CS is funded by the UK Medical Research Council and Cancer Research UK. BG is sponsored by a Bolyai fellowship and by ETT. ZS is funded by the National Institute of Health (grants NCI SPORE P50 CA 89393, R21LM008823-01A1) by the Breast Cancer Research Foundation and the Danish Council for Independent Research-Medical Sciences (FSS). MG was supported by an academic clinical fellowship from the National Institute for Health Research.
PY - 2010/8/11
Y1 - 2010/8/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=78751693800&partnerID=8YFLogxK
U2 - 10.1186/gm174
DO - 10.1186/gm174
M3 - Article
AN - SCOPUS:78751693800
SN - 1756-994X
VL - 2
JO - Genome Medicine
JF - Genome Medicine
IS - 8
M1 - 53
ER -