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Mol Cell Proteomics. 2016 Sep;15(9):3045-57. doi: 10.1074/mcp.M115.057729. Epub 2016 Jun 30.

Proteomic Screening and Lasso Regression Reveal Differential Signaling in Insulin and Insulin-like Growth Factor I (IGF1) Pathways.

Author information

1
From the ‡Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania; §University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania;
2
¶Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania; ‖Women's Cancer Research Center, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania;
3
**Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas;
4
¶Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania; ‖Women's Cancer Research Center, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania; ‡‡Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania.
5
From the ‡Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania; §University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania; lezon@pitt.edu.

Abstract

Insulin and insulin-like growth factor I (IGF1) influence cancer risk and progression through poorly understood mechanisms. To better understand the roles of insulin and IGF1 signaling in breast cancer, we combined proteomic screening with computational network inference to uncover differences in IGF1 and insulin induced signaling. Using reverse phase protein array, we measured the levels of 134 proteins in 21 breast cancer cell lines stimulated with IGF1 or insulin for up to 48 h. We then constructed directed protein expression networks using three separate methods: (i) lasso regression, (ii) conventional matrix inversion, and (iii) entropy maximization. These networks, named here as the time translation models, were analyzed and the inferred interactions were ranked by differential magnitude to identify pathway differences. The two top candidates, chosen for experimental validation, were shown to regulate IGF1/insulin induced phosphorylation events. First, acetyl-CoA carboxylase (ACC) knock-down was shown to increase the level of mitogen-activated protein kinase (MAPK) phosphorylation. Second, stable knock-down of E-Cadherin increased the phospho-Akt protein levels. Both of the knock-down perturbations incurred phosphorylation responses stronger in IGF1 stimulated cells compared with insulin. Overall, the time-translation modeling coupled to wet-lab experiments has proven to be powerful in inferring differential interactions downstream of IGF1 and insulin signaling, in vitro.

PMID:
27364358
PMCID:
PMC5013316
DOI:
10.1074/mcp.M115.057729
[Indexed for MEDLINE]
Free PMC Article

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