Dr. Keshishian has extensive training in Mass Spectrometry, and over the last 20 years has applied her knowledge and skills in the development of novel proteomics methods and its application to address compelling questions in biology, chemistry, and clinical medicine.

Over the last five to ten years, proteomics has emerged as another dimension with genomics, transcriptomics, epigenomics, etc. for helping understand various biological and clinical problems. Particularly important are proteomics technologies for quantification of various post-translational modifications such as phosphorylation, acetylation, and ubiquitination. With the latest developments of instrumentation, proteomics data generation has become relatively high-throughput making production of large datasets routine, but the analysis of resulting data still a major bottleneck.

We have applied a deep proteomics profiling workflow to study cell lines representing a number of cancers and genetic contexts with and without treatment with kinase inhibitors and generated proteome and phosphoproteome datasets across number of different cancer cell lines and at different treatment time points. This effort resulted in generation of quantitative information across the cell lines and conditions for more than 14,000 proteins and 100,000 phosphorylation sites. This dataset has been used to study changes in key signaling pathways in response to the kinase inhibitors, explore common changes among the different cancer types as well as specific changes for any given genetic alteration. We have developed computational tools to help us easily navigate through the data, apply appropriate statistical tests as well as visualize the results.