Illuminating understudied druggable proteins using pan-cancer proteogenomics data

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Project Summary Proteins in the families of kinases, G protein coupled receptors, and ion channels frequently contribute to disease pathogenesis and are good candidates for the development of therapeutics. In fact, 41% of the FDA- approved drugs target proteins in these families. However, each of these protein families has a number of members about which very little is known. Better understanding of these ‘dark’ members may pave the way to new methods for treating diseases. Utilizing existing large omics datasets can be a great starting point to generate new hypotheses on the function and phenotype association of the understudied proteins. Recently, the NCI’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) program has characterized over 1,000 primary tumors covering 10 cancer types using multiple omics platforms. While previous large-scale omics datasets have focused on genomic and transcriptomic data, the CPTAC data also integrate mass spectrometry (MS)-based proteomics and phosphoproteomics. Published studies by our colleagues and us in the CPTAC consortium have demonstrated the value of these proteogenomics datasets as a comprehensive resource for reinforcing existing knowledge, identifying new biological insights, and generating therapeutic hypotheses. The goal of this application is to illuminate understudied druggable proteins using CPTAC pan-cancer proteogenomics data. We will achieve this goal by addressing two specific Aims. Aim 1 is built upon our established multi-omics data analysis portal LinkedOmics. We will extend LinkedOmics into a knowledgebase, LinkedOmicsKB, in which information derived from harmonized CPTAC pan-cancer proteogenomics data will be organized into gene- centric web pages with easily browsable sections and effective visualizations. Aim 2 is based on our previous report that protein profiling data is much more closely aligned with gene function than mRNA profiling data. We will use CPTAC pan-cancer proteomics data to make function predictions for the understudied druggable proteins, followed by experimental validation of selected predictions. Data, visualization, and prediction results from both Aims will be integrated into Pharos, the knowledge portal of the Illuminating the Druggable Genome (IDG) program, to accelerate our understanding of IDG-eligible understudied proteins.