This is a renewal application for our T32 Proteogenomics of Cancer Training Program (PCTP) 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 proteogenomics analysis of data generated using multiple omics technologies (proteomics, genomics, transcriptomics, metabolomics, etc.) has emerged as a powerful approach for reconstructing targetable pathways in cancer. The main goal of PCTP 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 proteomics datasets, and to perform multi-level proteogenomics data integration. PCTP is a truly 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, it provides an opportunity to students from diverse backgrounds to become well skilled in all PCTP focus areas - cancer biology, proteomics, bioinformatics, and proteogenomics. PCTP is requesting 7 slots/year to supports pre-doctoral trainees for 1-2 years. We have a robust community of cancer researchers, bioinformaticians, data scientists, statisticians, and chemists. Our faculty and students are in the leadership of Human Proteome Organization initiatives, development and global deployment of data repositories and data analysis systems, and creation of new algorithms for proteome bioinformatics and multi-omics data integration. Our trainees come from larger Graduate Programs within the U of M (including Bioinformatics, Pathology, Cancer Biology, Chemistry, and Biomedical Engineering) and receive training in cancer biology, bioinformatics, and proteomics through courses, seminars, and special workshops. PCTP 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 Proteogenomics Data Analysis, taking advantage of our Faculty?s engagement in the efforts of the CPTAC consortium. In summary, our ongoing NCI training program in Proteogenomics 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.

Public Health Relevance

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 proteomics. Insufficient numbers of scientists are being trained in this rapidly growing field and this T32 proposes to address this issue. !

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Institutional National Research Service Award (T32)
Project #
2T32CA140044-11
Application #
10024747
Study Section
Subcommittee I - Transistion to Independence (NCI)
Program Officer
Schmidt, Michael K
Project Start
2010-05-01
Project End
2025-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
11
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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