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Connecting clusters of patient to drug responses of cell lines to suggest personalized therapeutics for breast cancer

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2 Author(s)
Gordonov, S. ; Dept. of Pharmacology & Syst. Therapeutics, Mount Sinai Sch. of Med., New York, NY, USA ; Ma'ayan, A.

Recent surge in genome-wide expression data from patient tumors and cell-lines in breast cancer, as well as response data of breast cancer cell-lines to many drugs, opens the opportunity for data integration approaches that can lead to better personalized therapeutics. Here we integrated such data to generate a tripartite network that connects clusters of patients to cell-lines, and cell-lines to drugs to suggest which drugs may work best for each cluster of patients. We combined gene expression profiles from 400 patient tumor samples from two independent publicly-available studies, with gene expression and drug growth-inhibition-response profiles of 31 breast cancer cell-lines to build this tripartite network.

Published in:

Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on

Date of Conference:

4-7 Oct. 2012

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