Application of pharmacologically induced transcriptomic profiles to interrogate PI3K-Akt-mTOR pathway activity associated with cancer patient prognosis
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Matthew H. Ung1, George L. Wang1, Frederick S. Varn1, Chao Cheng1,2,3
1Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, 03755 USA
2Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, 03755 USA
3Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, 03766 USA
Chao Cheng, email: [email protected]
Keywords: pharmacogenomics, computational biology, PI3K, drug treatment
Received: May 16, 2016 Accepted: August 25, 2016 Published: August 31, 2016
The PI3K-Akt-mTOR signaling pathway has been identified as a key driver of carcinogenesis in several cancer types. As such, a major area of focus in cancer biology is the development of genomic biomarkers that can measure the activity level of the PI3K-Akt-mTOR pathway. In this study, we systematically estimate PI3K-Akt-mTOR pathway activity in breast primary tumor samples using transcriptomic profiles derived from drug treatment in MCF7 cell lines. We demonstrate that gene expression profiles derived from chemically-induced protein inhibition allows us to measure PI3K-Akt-mTOR pathway activity in patient tumor samples. With this approach, we predict prognosis and response to chemotherapy in cancer patients, and screen for potential pharmacological modulators of PI3K-Akt-mTOR pathway inhibitors.
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