Proteomic analysis defines kinase taxonomies specific for subtypes of breast cancer

Multiplexed small molecule inhibitors covalently bound to Sepharose beads (MIBs) were used to capture functional kinases in luminal, HER2-enriched and triple negative (basal-like and claudin-low) breast cancer cell lines and tumors. Kinase MIB-binding profiles at baseline without perturbation proteomically distinguished the four breast cancer subtypes. Understudied kinases, whose disease associations and pharmacology are generally unexplored, were highly represented in MIB-binding taxonomies and are integrated into signaling subnetworks with kinases that have been previously well characterized in breast cancer. Computationally it was possible to define subtypes using profiles of less than 50 of the more than 300 kinases bound to MIBs that included understudied as well as metabolic and lipid kinases. Furthermore, analysis of MIB-binding profiles established potential functional annotations for these understudied kinases. Thus, comprehensive MIBs-based capture of kinases provides a unique proteomics-based method for integration of poorly characterized kinases of the understudied kinome into functional subnetworks in breast cancer cells and tumors that is not possible using genomic strategies. The MIB-binding profiles readily defined subtype-selective differential adaptive kinome reprogramming in response to targeted kinase inhibition, demonstrating how MIB profiles can be used in determining dynamic kinome changes that result in subtype selective phenotypic state changes.

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Publication Details

Journal
UNC Libraries
Published
2025-10-10
DOI
https://doi.org/10.17615/7afp-2m58
Primary Topic
Bioinformatics and Genomic Networks
Type
article
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article

Proteomic analysis defines kinase taxonomies specific for subtypes of breast cancer

Samantha M. Bevill, Sara H. Velarde, Noah Sciaky, Shawn M. Gomez et al.
UNC Libraries
Bioinformatics and Genomic Networks
article

Proteomic analysis defines kinase taxonomies specific for subtypes of breast cancer

Samantha M. Bevill, Sara H. Velarde, Noah Sciaky, Shawn M. Gomez, Timothy Joseph Stuhlmiller, Claire R. Hall, Gary L. Johnson, Trang T. Pham, Kyla Collins, Tudor Ionel Oprea, Steven P. Angus, Michael P. East, Daniel R. Goulet, Lee M. Graves, Jon S. Zawistowski
article en

Abstract

Multiplexed small molecule inhibitors covalently bound to Sepharose beads (MIBs) were used to capture functional kinases in luminal, HER2-enriched and triple negative (basal-like and claudin-low) breast cancer cell lines and tumors. Kinase MIB-binding profiles at baseline without perturbation proteomically distinguished the four breast cancer subtypes. Understudied kinases, whose disease associations and pharmacology are generally unexplored, were highly represented in MIB-binding taxonomies and are integrated into signaling subnetworks with kinases that have been previously well characterized in breast cancer. Computationally it was possible to define subtypes using profiles of less than 50 of the more than 300 kinases bound to MIBs that included understudied as well as metabolic and lipid kinases. Furthermore, analysis of MIB-binding profiles established potential functional annotations for these understudied kinases. Thus, comprehensive MIBs-based capture of kinases provides a unique proteomics-based method for integration of poorly characterized kinases of the understudied kinome into functional subnetworks in breast cancer cells and tumors that is not possible using genomic strategies. The MIB-binding profiles readily defined subtype-selective differential adaptive kinome reprogramming in response to targeted kinase inhibition, demonstrating how MIB profiles can be used in determining dynamic kinome changes that result in subtype selective phenotypic state changes.

UNC Libraries
University of North Carolina at Chapel Hill (US)
Openalex Percentile: Top 75%
Bioinformatics and Genomic Networks
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