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Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays
Published on: October 23, 2019
Kinase inhibitor pulldown assay (KiP) for clinical proteomics
Alexander B Saltzman1, Doug W Chan2,3, Matthew V Holt2
1Mass Spectrometry Proteomics Core, Advanced Technology Cores, Baylor College of Medicine, Houston, TX, USA.
Abstract:
Protein kinases are frequently dysregulated and/or mutated in cancer and represent essential targets for therapy. Accurate quantification is essential. For breast cancer treatment, the identification and quantification of the protein kinase ERBB2 is critical for therapeutic decisions. While immunohistochemistry (IHC) is the current clinical diagnostic approach, it is only semiquantitative. Mass spectrometry-based proteomics offers quantitative assays that, unlike IHC, can be used to accurately evaluate hundreds of kinases simultaneously. The enrichment of less abundant kinase targets for quantification, along with depletion of interfering proteins, improves sensitivity and thus promotes more effective downstream analyses. Multiple kinase inhibitors were therefore deployed as a capture matrix for kinase inhibitor pulldown (KiP) assays designed to profile the human protein kinome as broadly as possible. Optimized assays were initially evaluated in 16 patient derived xenograft models (PDX) where KiP identified multiple differentially expressed and biologically relevant kinases. From these analyses, an optimized single-shot parallel reaction monitoring (PRM) method was developed to improve quantitative fidelity. The PRM KiP approach was then reapplied to low quantities of proteins typical of yields from core needle biopsies of human cancers. The initial prototype targeting 100 kinases recapitulated intrinsic subtyping of PDX models obtained from comprehensive proteomic and transcriptomic profiling. Luminal and HER2 enriched OCT-frozen patient biopsies subsequently analyzed through KiP-PRM also clustered by subtype. Finally, stable isotope labeled peptide standards were developed to define a prototype clinical method. Data are available via ProteomeXchange with identifiers PXD044655 and PXD046169.
Insights
This study introduces a novel mass spectrometry method, Kinase Inhibitor Pulldown coupled with Parallel Reaction Monitoring (KiP-PRM), for precise protein kinase quantification in cancer. This approach accurately profiles the kinome, aiding therapeutic decisions in breast cancer treatment.
Area of Science:
- Proteomics and Cancer Biology
- Mass Spectrometry-based Quantification
- Kinase Signaling in Oncology
Background:
- Protein kinases are crucial, often dysregulated, targets in cancer therapy.
- Current diagnostic methods like immunohistochemistry (IHC) for targets such as ERBB2 are semiquantitative.
- Accurate quantification of kinases is essential for effective cancer treatment decisions.
Purpose of the Study:
- To develop a highly sensitive and quantitative mass spectrometry assay for profiling the human kinome.
- To establish a method for accurate protein kinase quantification in limited clinical samples, such as biopsies.
- To enable simultaneous quantification of hundreds of kinases for comprehensive cancer profiling.
Main Methods:
- Kinase Inhibitor Pulldown (KiP) assays utilizing kinase inhibitors as a capture matrix.
- Optimization of KiP assays and development of a single-shot Parallel Reaction Monitoring (PRM) method for enhanced quantitative fidelity.
- Application of the KiP-PRM approach to patient-derived xenograft (PDX) models and human cancer biopsies, including the development of stable isotope labeled peptide standards.
Main Results:
- KiP assays successfully identified differentially expressed and biologically relevant kinases in PDX models.
- The optimized KiP-PRM method accurately quantified kinases in low-quantity human cancer biopsies.
- KiP-PRM profiling recapitulated intrinsic subtyping of PDX models and patient biopsies, correlating with transcriptomic data.
Conclusions:
- The KiP-PRM assay provides a sensitive and quantitative method for broad kinome profiling.
- This approach can accurately assess kinase expression in limited clinical samples, supporting precision medicine.
- The developed method offers a powerful tool for cancer diagnostics and therapeutic strategy development.

