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.