This is a renewal application for our T32 Advanced Proteome Informatics of Cancer Training Program (PICTP) at the University of Michigan. The National Cancer Institute has made substantial investments in new technology platforms for cancer proteomics, most recently through the Clinical Proteomic Tumor Analysis Consortium (CPTAC). The proteome is critical to understanding functional genomics and systems biology of cancers and to discovery and validation of biomarker candidates and molecular targets for therapy and prevention. Sophisticated analysis of proteomes requires advanced informatics to deal with the complexity of specimens, the extreme dynamic range of protein concentrations, post--translational modifications, alternative splice isoforms, responses to all sorts of perturbations, and differences in databases and data formats. Furthermore, integrative analysis of data generated using multiple omics technologies (proteomics, genomics, metabolomics, etc.) has emerged as a powerful approach for reconstructing targetable pathways in cancer. The main goal of PICTP is to address the current scarcity of scientists able to effectively generate and bioinformaticly analyze their own proteomics data, to take advantage of CPTAC and other publicly available large-scale cancer proteomics datasets, and to perform multilevel data integration. PICTP a truly is a multi- disciplinary Training Program that is also very unique, with the U of M and nationally. Anchored in the university--wide Center for Computational Medicine and Bioinformatics (CCMB), it provides an opportunity to students from diverse backgrounds to become well skilled in all three PICTP focus areas - cancer biology, proteomics, and bioinformatics. We have a robust community of cancer researchers, bioinformaticians, statisticians, chemists, and software engineers. Our faculty and students are in the leadership of Human Proteome Organization (HUPO) initiatives, development and global deployment of data repositories and data analysis systems, and creation of new algorithms for proteome informatics and omics data integration. Our trainees come from larger Graduate Programs within the U of M (including Bioinformatics, Pathology, Chemistry, Biomedical Engineering, and Statistics) and receive training in cancer biology, bioinformatics, and proteomics through courses, seminars, and the journal club. PICTP strongly encourages dual mentorship of each trainee by a cancer researcher and a computational scientist. We will further strengthen our Training Program with an addition of a special Annual Workshop for our T32 trainees on the Analysis of Metrics for the HUPO Human Proteome Project. In summary, our ongoing NCI training program in Proteome Informatics of Cancer trains a new generation of scientists well prepared for an independent career in interdisciplinary biomedical research, enhances faculty research, and supports NCI goals.
Very large, complex datasets are being generated by cancer researchers using new proteomics technologies that allow them to study thousands of proteins simultaneously. This avalanche of data requires scientists well-trained in the specialized and multidisciplinary field of Proteome Informatics. Insufficient numbers of scientists are being trained in this rapidly growing field and this T32 proposes to address this issue.
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