FUNCTIONAL ANALYSIS OF TYROSINE KINASE MUTANTS IN CANCER
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Date
2016-08-15
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Johns Hopkins University
Abstract
Cancer or uncontrolled cell division which can invade into other tissues is today among the leading causes of morbidity and mortality worldwide. Genomic alterations in protein coding genes are a major feature of cancerous cells. But in general, any tumor has many mutations that arise spontaneously during cell division, of which very few have a causal impact on oncogenesis (1). More than 100-fold variation of such background mutation rate between different individuals, different regions of the genome and different cancers accentuated by mutated DNA repair pathways, exposure to mutagens, chromosomal abnormalities, all of which affect cancer cells make it very difficult to statistically tease apart causative driver mutations from inert passenger mutations even with the most recent advances in sequencing to identify somatic mutations in tumor cells (2). Hence there is a need to incorporate experimental data involving functional implications of mutations to pin point the driver mutations and characterize the causal mechanism (3).
The goal of this project is to develop an experimental workflow to interrogate biochemical functional implications of mutations in coding regions in order to characterize their driver potential. We have chosen to work with protein tyrosine kinases, owing to their importance in cell signaling, acute involvement in many cancers, and the promise of existing therapeutic successes targeting these pathways. We test for protein activity in high throughput on Human Proteome (HuProt) arrays, covering 19,000 human proteins and splice variants. This approach is helpful to know the catalytic activity and substrate preference of different mutant kinases, giving valuable insights into driver like potential depending on the pathways it acts on and the variation between the wild type enzyme and the mutant. Success with this platform will enable deployment of the same pipeline to other protein families with known biochemical functions and potentially to clinical applications in personalized medicine.
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Keywords
Protein microarray, Cancer, High-Throughput, Proteomics, Tyrosine Kinase, RTK, Targated therapy, Personalized medicine