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Review
. 2011 Mar;8(3):161-70.
doi: 10.1038/nrclinonc.2011.3.

Targeted therapy in GIST: in silico modeling for prediction of resistance

Affiliations
Review

Targeted therapy in GIST: in silico modeling for prediction of resistance

Marco A Pierotti et al. Nat Rev Clin Oncol. 2011 Mar.

Abstract

Elucidation of the genetic processes leading to neoplastic transformation has identified cancer-promoting molecular alterations that can be selectively targeted by rationally designed therapeutic agents. Protein kinases are druggable targets and have been studied intensively. New methodologies--including crystallography and three-dimensional modeling--have allowed the rational design of potent and selective kinase inhibitors that have already reached the clinical stage. However, despite the clinical success of kinase-targeted therapies, most patients that respond eventually relapse as a result of acquired resistance. Darwinian-type selection of secondary mutations seems to have a major role in this resistance. The emergence and/or expansion of tumor clones containing new mutations in the target kinase and that are drug-insensitive have been observed after chronic treatment. The resistance mechanisms to tyrosine kinase inhibitors, in particular secondary resistant mutations as a consequence of treatment, will be discussed in detail. In particular, this Review will focus on KIT and PDGFRA mutations, which are involved in the pathogenesis of gastrointestinal stromal tumors. Harnessing the selection of mutated variants developed to overcome these resistance mechanisms is an ongoing goal of current research and new strategies to overcome drug resistance is being envisaged.

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