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Kinome state is predictive of cell viability in pancreatic cancer tumor and stroma cell lines

View ORCID ProfileMatthew E. Berginski, Madison R. Jenner, Chinmaya U. Joisa, Silvia G. Herrera Loeza, Brian T. Golitz, Matthew B. Lipner, John R. Leary, Naim U. Rashid, Gary L. Johnson, Jen Jen Yeh, Shawn M. Gomez
doi: https://doi.org/10.1101/2021.07.21.451515
Matthew E. Berginski
1Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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  • ORCID record for Matthew E. Berginski
Madison R. Jenner
1Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Chinmaya U. Joisa
5Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA
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Silvia G. Herrera Loeza
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Brian T. Golitz
1Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Matthew B. Lipner
1Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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John R. Leary
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
6Department of Biostatistics, The University of Florida, Gainesville, FL, USA
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Naim U. Rashid
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
3Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Gary L. Johnson
1Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Jen Jen Yeh
1Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
4Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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  • For correspondence: jjyeh@med.unc.edu smgomez@unc.edu
Shawn M. Gomez
1Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
5Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA
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  • For correspondence: jjyeh@med.unc.edu smgomez@unc.edu
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ABSTRACT

Numerous aspects of cellular signaling are regulated by the kinome – the network of over 500 protein kinases that guides and modulates information transfer throughout the cell. The key role played by both individual kinases and assemblies of kinases organized into functional subnetworks leads to kinome dysregulation being a key driver of many diseases, particularly cancer. In the case of pancreatic ductal adenocarcinoma (PDAC), a variety of kinases and associated signaling pathways have been identified for their key role in the establishment of disease as well as its progression. However, the identification of additional relevant therapeutic targets has been slow and is further confounded by interactions between the tumor and the surrounding tumor microenvironment. Fundamentally, it is an open question as to the degree to which knowledge of the state of the kinome at the protein level is able to provide insight into the downstream phenotype of the cell.

In this work, we attempt to link the state of the kinome, or kinotype, with cell viability in representative PDAC tumor and stroma cell lines. Through the application of both regression and classification models to independent kinome perturbation and kinase inhibitor cell screen data, we find that the inferred kinotype of a cell has a significant and predictive relationship with cell viability. While regression models perform poorly, we find that classification approaches are able to predict drug viability effects. We further find that models are able to identify a set of kinases whose behavior in response to perturbation drive the majority of viability responses in these cell lines. Using the models to predict new compounds with cell viability effects and not in the initial data set, we conducted a validation screen that confirmed the accuracy of the models. These results suggest that characterizing the state of the protein kinome provides significant opportunity for better understanding signaling behavior and downstream cell phenotypes, as well as providing insight into the broader design of potential therapy design for PDAC.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Kinome state is predictive of cell viability in pancreatic cancer tumor and stroma cell lines

  • https://github.com/gomezlab/PDACperturbations

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted October 19, 2021.
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Kinome state is predictive of cell viability in pancreatic cancer tumor and stroma cell lines
Matthew E. Berginski, Madison R. Jenner, Chinmaya U. Joisa, Silvia G. Herrera Loeza, Brian T. Golitz, Matthew B. Lipner, John R. Leary, Naim U. Rashid, Gary L. Johnson, Jen Jen Yeh, Shawn M. Gomez
bioRxiv 2021.07.21.451515; doi: https://doi.org/10.1101/2021.07.21.451515
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Kinome state is predictive of cell viability in pancreatic cancer tumor and stroma cell lines
Matthew E. Berginski, Madison R. Jenner, Chinmaya U. Joisa, Silvia G. Herrera Loeza, Brian T. Golitz, Matthew B. Lipner, John R. Leary, Naim U. Rashid, Gary L. Johnson, Jen Jen Yeh, Shawn M. Gomez
bioRxiv 2021.07.21.451515; doi: https://doi.org/10.1101/2021.07.21.451515

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