Addressing Genetic Tumor Heterogeneity through Computationally Predictive Combination Therapy

Addressing Genetic Tumor Heterogeneity through Computationally Predictive Combination Therapy

Recent tumor sequencing data suggest an urgent need to develop a methodology to directly address intratumoral heterogeneity in the design of anticancer treatment regimens. We use RNA interference to model heterogeneous tumors, and demonstrate successful validation of computational predictions for ho...

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Bibliographic Details
Main Authors: Zhao, Boyang (Contributor), Pritchard, Justin R. (Contributor), Hemann, Michael (Contributor), Lauffenburger, Douglas A (Author)
Other Authors: Massachusetts Institute of Technology. Computational and Systems Biology Program (Contributor), Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Biology (Contributor), Koch Institute for Integrative Cancer Research at MIT (Contributor), Lauffenburger, Douglas A. (Contributor)
Format: Article
Language:English
Published: American Association for Cancer Research, 2014-09-04T19:37:06Z.
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