Editors' ChoiceCancer

Drug Resistance, Up Close and Personal

See allHide authors and affiliations

Science Signaling  23 Dec 2014:
Vol. 7, Issue 357, pp. ec357
DOI: 10.1126/scisignal.aaa5282

Cancer therapies that target specific genetic mutations driving tumor growth have shown promising results in patients; however, the response is often short-lived because the tumors acquire new mutations that render them resistant to these therapies. Complicating matters, the mechanism of resistance can vary from patient to patient. To identify drugs most likely to be effective against resistant tumors, Crystal et al. established cell lines from the tumors of individual patients after resistance occurred and performed a drug screen and genetic analysis on the cultured cells. This strategy successfully identified drug combinations that halted the growth of resistant tumor cells both in culture and in mice. In the future, pharmacological profiling of patient-derived cells could be an efficient way to direct therapeutic choices for individual cancer patients.

A. S. Crystal, A. T. Shaw, L. V. Sequist, L. Friboulet, M. J. Niederst, E. L. Lockerman, R. L. Frias, J. F. Gainor, A. Amzallag, P. Greninger, D. Lee, A. Kalsy, M. Gomez-Caraballo, L. Elamine, E. Howe, W. Hur, E. Lifshits, H. E. Robinson, R. Katayama, A. C. Faber, M. M. Awad, S. Ramaswamy, M. Mino-Kenudson, A. J. Iafrate, C. H. Benes, J. A. Engelman, Patient-derived models of acquired resistance can identify effective drug combinations for cancer. Science 346, 1480–1486 (2014). [Abstract] [Full Text]

Stay Connected to Science Signaling