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Sci Rep. 2016 Feb 26;6:22120. doi: 10.1038/srep22120.

An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine.

Liu Y1,2,3, Fei T4,5, Zheng X6, Brown M4,5, Zhang P7, Liu XS3,5, Wang H1,3.

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School of Life Science and Technology, Tongji University, Shanghai 200092, China.
Shanghai Key laboratory of tuberculosis, Shanghai Pulmonary Hospital, Shanghai 200433, China.
Department of Biostatistics and Computational Biology, Dana-Faber Cancer Institute and Harvard School of Public Health, Boston, MA 02215, USA.
Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115, USA.
Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, MA 02115, USA.
Department of Mathematics, Shanghai Normal University, Shanghai 200234, China.
Department of Thoracic Surgery, Shanghai Pulmonary Hospital of Tongji University School of Medicine, Shanghai 200433, China.


An individual tumor harbors multiple molecular alterations that promote cell proliferation and prevent apoptosis and differentiation. Drugs that target specific molecular alterations have been introduced into personalized cancer medicine, but their effects can be modulated by the activities of other genes or molecules. Previous studies aiming to identify multiple molecular alterations for combination therapies are limited by available data. Given the recent large scale of available pharmacogenomic data, it is possible to systematically identify multiple biomarkers that contribute jointly to drug sensitivity, and to identify combination therapies for personalized cancer medicine. In this study, we used pharmacogenomic profiling data provided from two independent cohorts in a systematic in silico investigation of perturbed genes cooperatively associated with drug sensitivity. Our study predicted many pairs of molecular biomarkers that may benefit from the use of combination therapies. One of our predicted biomarker pairs, a mutation in the BRAF gene and upregulated expression of the PIM1 gene, was experimentally validated to benefit from a therapy combining BRAF inhibitor and PIM1 inhibitor in lung cancer. This study demonstrates how pharmacogenomic data can be used to systematically identify potentially cooperative genes and provide novel insights to combination therapies in personalized cancer medicine.

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