Multiplexed Kinase Biosensor Technology to Detect Leukemia Signaling with Mass Sp

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DESCRIPTION (provided by applicant): Kinase inhibitor drugs have changed the face of chemotherapy and are projected to remain a major focus of leukemia treatment. However, their long-term efficacy is variable and can be attributed to differences in their activity on their targts from patient to patient that can be observed as early as one week after beginning treatment. We plan to validate a technology that enables quantification of efficacy at the very beginning of treatment, giving physicians and patients the opportunity to monitor an individual's response and likelihood of success immediately, rather than relying on the current watch-and-wait approach. We have established proof-of-concept for analyzing Bcr-Abl kinase activity and inhibition in chronic myelogenous leukemia (CML) with the support of an IMAT R21 award to the Parker laboratory. An IMAT award to the Turk laboratory at Yale University also supported work leading to a collaborative effort on proof-of-concept for developing substrates for other kinases, including the Src-family and JAK2 kinases. In this R33 advanced technology development and validation application, we will leverage both of these outcomes to further develop our approach to generate new reagents and protocols for detecting the activity and inhibition of specific kinases or kinase families in intact, live cells. We will also validate the quantitative and multiplexing capabilities of this technology in larger panels of patient samples, collected in collaboration with the Indiana University Simon Cancer Center Hematological Malignancies Tissue Bank. In Aim 1, we plan to address throughput and standardization by developing an isotope-coding strategy that will allow analyses of the same biosensor to be performed in different cells (controls, multiple patient samples) in parallel, followed by pooling and simultaneous analysis. In Aim 2, we will expand the biosensor and mass spectrometry analysis toolbox to include other kinases and kinase families that are important to CML drug resistance and/or other aspects of leukemia biology. In Aim 3, we will validate the application of this technology to patient cells, including optimization of biostability and delivery. This advanced development will establish the quantitative utility of the methodology, and expand the applicability of this technology to kinases and inhibitors relevant beyond CML alone. Ultimately, this work could transform cancer treatment by enabling physicians and patients to make informed decisions about inhibitor treatment choice, monitor efficacy in real time, and catch treatment failure in time to intervene before resistance and relapse become a problem.