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Genomics of drug sensitivity in cancer | 575
Translational Medicine

Translational Medicine
Open Access

ISSN: 2161-1025

+44 1223 790975

Genomics of drug sensitivity in cancer


International Conference on Translational Medicine

September 17-19, 2012 Holiday Inn San Antonio, Texas, USA

Sonja Heidorn

AcceptedAbstracts: Transl Med

Abstract :

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. To uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines�which represent much of the tissue-type and genetic diversity of human cancers�with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing�s sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

Biography :

Sonja Heidorn completed her PhD at the Institute of Cancer Research in London under the supervision of Professor Richard Marais. During this time she elucidated how BRAF-targeted drugs paradoxically activate ERK signaling in RAS mutant melanoma cells. She is now a postdoctoral research fellow at the Wellcome Trust Sanger Institute where she is part of a multidisciplinary team searching for therapeutic biomarkers that can be used to identify patients most likely to respond to anticancer drugs.

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