Research Article

Patient-derived models of acquired resistance can identify effective drug combinations for cancer

Science  13 Nov 2014:

DOI: 10.1126/science.1254721

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Abstract

Targeted cancer therapies have produced substantial clinical responses, but most tumors develop resistance to these drugs. Here, we describe a pharmacogenomic platform that facilitates rapid discovery of drug combinations that can overcome resistance. We established cell culture models derived from biopsy samples of lung cancer patients whose disease had progressed while on treatment with EGFR or ALK tyrosine kinase inhibitors and then subjected these cells to genetic analyses and a pharmacological screen. Multiple effective drug combinations were identified. For example, the combination of ALK and MEK inhibitors was active in an ALK-positive resistant tumor that had developed a MAP2K1 activating mutation, and the combination of EGFR and FGFR inhibitors was active in an EGFR mutant resistant cancer with a novel mutation in FGFR3. Combined ALK and SRC inhibition was effective in several ALK-driven patient-derived models, a result not predicted by genetic analysis alone. With further refinements, this strategy could help direct therapeutic choices for individual patients.

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