Joanna Rae Kovalski ,

My thesis work has focused on integrating proteomic and genomic datasets to elucidate novel protein, RNA and DNA targets in cancers driven by the Ras and Raf oncogenes. My first author work characterizes the functional protein interactome of mutant Ras and identifies mTOR complex 2 as a new, direct Ras effector. This manuscript was recently accepted at MOLECULAR CELL (Kovalski J et al. manuscript D-18-01856R3). Specifically, I implemented a new discovery pipeline to highlight top candidate interactors of common oncogenes, such as Ras, by integrating proximity proteomics and mass spectrometry with orthogonal multi cancer cell line CRISPR screens. Functional validation of the top mutant Ras candidate interactor, mTORC2, necessitated acquiring and employing a broad array of techniques, including biochemical assays, biophysical interaction measurements, transcriptomic profiling and in vivo mouse tumorigenesis studies. My drive to uncover new avenues to therapeutically target the Ras oncogene was spurred by my early thesis work examining the genomics of BRAFV600E-driven melanoma. In two co-authored studies, we identified a novel long non-coding RNA regulating cell migration (Flockhart R…Kovalski J et al. Genome Research 2010) and characterized a dynamic transcription factor-enhancer relationship that engages melanoma-specific innate resistance to BRAFV600E inhibition (Webster DE…Kovalski J et al. Genome Research 2014). Furthermore, in pioneering the use of proximity proteomics in the Khavari lab, I have helped adapt the technology to the study of RNA-protein interactions (Ramanathan M…Kovalski J et al. Nature Methods 2018) as well as to uncover an unexpected mechanism in which snoRNAs control Ras trafficking (Che Y, Siprashvili Z, Kovalski J et al. Nature Communications, manuscript NCOMMS-18-3100209). Throughout my multifaceted thesis work, I have built a strong and broad experimental toolkit. In my postdoctoral work, I look forward to extending my previous experience generating and integrating genomic data sets of cancer cell signaling towards uncovering new functions of the non-coding genome in development and cancer.