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Computational response modeling reveals context dependent Akt activity in luminal breast cancer cells

View ORCID ProfileCemal Erdem, View ORCID ProfileAdrian V. Lee, View ORCID ProfileD. Lansing Taylor, View ORCID ProfileTimothy R. Lezon
doi: https://doi.org/10.1101/2020.10.22.349647
Cemal Erdem
1Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA
2University of Pittsburgh Drug Discovery Institute (UPDDI), University of Pittsburgh, Pittsburgh, PA
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Adrian V. Lee
3Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, PA
4Magee-Womens Research Institute, Pittsburgh, PA
5The Institute for Precision Medicine, Pittsburgh, PA
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D. Lansing Taylor
1Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA
2University of Pittsburgh Drug Discovery Institute (UPDDI), University of Pittsburgh, Pittsburgh, PA
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Timothy R. Lezon
1Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA
2University of Pittsburgh Drug Discovery Institute (UPDDI), University of Pittsburgh, Pittsburgh, PA
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  • For correspondence: lezon@pitt.edu
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ABSTRACT

Aberrant signaling through insulin (Ins) and insulin-like growth factor I (IGF1) receptors contributes to the risk and advancement of many cancer types by activating cell survival cascades. Mechanistic computational modeling of such pathways provides insights into each component’s role in the cell response. In previous computational models, the two receptors were treated as indistinguishable, missing the opportunity to delineate their distinct roles in cancer progression. Here, a dual receptor (IGF1R & InsR) computational model elucidated new experimental hypotheses on how differential early responses emerge. Complementary to our previous findings, the model suggested that the regulation of insulin receptor substrate (IRS) is critical in inducing differential MAPK and Akt activation. As predicted, perturbing ribosomal protein S6 kinase (RPS6K) kinase activity led to an increased Akt activation with insulin stimulation compared to IGF1 stimulation. Being able to discern differential downstream signaling, we can explore improved anti-IGF1R cancer therapies by eliminating emergence of compensation mechanisms, without disrupting InsR signaling.

Implications The study shows, both experimentally and through computational models, that IGF1 and insulin receptor signaling pathways respond differently to RPS6K inhibition.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted October 23, 2020.
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Computational response modeling reveals context dependent Akt activity in luminal breast cancer cells
Cemal Erdem, Adrian V. Lee, D. Lansing Taylor, Timothy R. Lezon
bioRxiv 2020.10.22.349647; doi: https://doi.org/10.1101/2020.10.22.349647
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Computational response modeling reveals context dependent Akt activity in luminal breast cancer cells
Cemal Erdem, Adrian V. Lee, D. Lansing Taylor, Timothy R. Lezon
bioRxiv 2020.10.22.349647; doi: https://doi.org/10.1101/2020.10.22.349647

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