Saturday, September 7, 2024
9/7/2024
Project Abstract Protein kinases constitute one of the largest enzyme families in humans, and their aberrant and carcinogenic function in a vast array of cancers is well known. However, despite the now known inherent druggability of this enzyme class, only approximately two dozen kinases have been successfully exploited as drug targets, highlighting the need for major innovations for functional characterization and drug discovery. Moreover, nearly 200 kinases remain poorly/completely understudied at this time, and they can be considered as the ‘dark kinome,’ due to a lack of sensitive measurement platforms for their investigation. The goal of this proposal is to develop next-generation sample multiplexing-based proteomics technologies to transform kinome research. Accomplishing this goal will allow us to reliably measure relative and absolute kinase abundance across hundreds of cancer samples, shed light on their functions, elucidate mechanisms underlying kinase inhibitor resistance, and identify compounds as potential kinase degraders. Specifically, I propose to i) develop a targeted kinome assay to enable simultaneous absolute and relative quantification of the full human kinome (Aim 1), ii) develop a streamlined platform incorporating automated sample preparation to enable high-throughput kinome-focused compound library screening (Aim 2), and iii) perform compound library screening to identify new kinase degraders (Aim 3). The end result from the proposed studies will be an integrated paradigm-shifting platform to elevate human kinome research. I note that the platform can easily be adapted to characterize other entire protein categories (e.g., transcription factors) that are relevant to cancer pathology. Moreover, the data from this application will generate multiple first-of-their-kind resources, including a kinome expression map across different human cancer cell lines, a kinome response map of known kinase inhibitors, and a kinase degradation map with compound libraries. This proposal draws on my training in chemistry, proteomics, and bioinformatics. During my postdoctoral research, I have successfully applied my knowledge to understand a variety of biological and pathological processes, including platinum-resistant ovarian cancer, tissue-specific machinery in aging, impact of genetic variation on protein expression and lipid metabolism, and amyloid precursor protein processing in endo-lysosomal system. As cancer is one of the leading causes of death worldwide, my career goal is to develop a research program with the focus on mechanistic understanding of cancer, and therapeutic development for its treatment. I aim to become a leader in kinase biology using proteomics and chemical biology approaches, which will distinguish my independent work from that of my mentors.
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