Thursday, January 23, 2014
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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.
Published online Jan. 23, 2014
Patent and licensing status
Zhao, B. et al. Cancer
published online Dec. 6, 2013;
Contact: Michael T. Hemann, Massachusetts Institute of
Technology, Cambridge, Mass.
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