Some cancer centers already take biopsies of tumors and run them through genetic tests, to get a better sense of what’s driving the cancer. That information can be helpful in deciding which of the growing number of targeted anti-cancer drugs will work best to stop those growths.
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.
Sources and more information
- Patient-derived models of acquired resistance can identify effective drug combinations for cancer, sciencemag,
DOI: 10.1126/science.1254721, November 13 2014.
- The Cancer Breakthrough With Big Implications,
Time, Nov. 13, 2014.
- Direct drug screening of patient biopsies could overcome resistance to targeted therapy, massgeneral, November 13, 2014.