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Computational models

An algorithm to predict drug combinations to treat genetically heterogeneous tumors

A computational model could help predict drug combinations for genetically heterogeneous tumors. Using published data on drug-genotype interactions, an algorithm predicted effective two-drug combinations. In a model of tumor genetic diversity consisting of mixed cultures of parental and shRNA-expressing subpopulations of lymphoma cells, combinations predicted by the algorithm decreased growth of subpopulations compared with three other drug combinations selected by alternative criteria. In a mouse model of genetically heterogeneous lymphoma, the algorithm-predicted drug combination minimized the emergence of any tumor subpopulation and increased tumor-free survival compared with another differently selected drug combination. Next steps could include testing the algorithm in additional tumor models.

SciBX 7(3); doi:10.1038/scibx.2014.100
Published online Jan. 23, 2014

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Zhao, B. et al. Cancer Discov.;
published online Dec. 6, 2013;
Contact: Michael T. Hemann, Massachusetts Institute of Technology, Cambridge, Mass.