Oncotarget

Research Papers:

Application of pharmacologically induced transcriptomic profiles to interrogate PI3K-Akt-mTOR pathway activity associated with cancer patient prognosis

Matthew H. Ung, George L. Wang, Frederick S. Varn and Chao Cheng _

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Oncotarget. 2016; 7:84142-84154. https://doi.org/10.18632/oncotarget.11776

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Abstract

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

Correspondence to:

Chao Cheng, email: chao.cheng@dartmouth.edu

Keywords: pharmacogenomics, computational biology, PI3K, drug treatment

Received: May 16, 2016     Accepted: August 25, 2016     Published: August 31, 2016

ABSTRACT

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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