The goal of the postdoctoral Mayo Cancer Genetic Epidemiology Training Program (MCGETP) renewal is to produce investigators capable of developing an independent academic career in the evolving arena of cancer research that transects the disciplines of genomics, epidemiology, statistical genetics and bio- and clinical informatics. This training will converge and integrate multiple disciplines, which is critical to met the challenges of bridging the laboratory-translational interface, and to stimulate improvements in cancer detection, prevention, and treatment. Mayo Clinic is a highly respected center for medical training, research, and patient care, and has proven to be an outstanding environment for nurturing such integrated training over the past 10 years of this training program. The clinic environment and medical record infrastructure provide unique opportunities to couple existing information on a well-annotated practice with genomic, molecular and pathology data on tens of thousands of patients, and to perform research that will inform the practice of personalized medicine. Further, the resources of the Mayo Clinic Comprehensive Cancer Center and the Center for Translational Science Activities are available to this program. We seek continuing support for the MCGETP to provide three-year interdisciplinary training experiences for three types of postdoctoral trainees (doctoral level individuals prepared in a) laboratory-based research, b) medicine, or c) epidemiology, statistical genetics, informatics). Two Advisory Committees composed of senior faculty and external advisors will provide oversight. The MCGETP will ensure an integrated didactic education through a specialized core curriculum; opportunities through additional intramural and extramural courses and workshops in cancer biology, epigenetics, genetic epidemiology, bioinformatics, statistical genetics; and an individualized mentoring program that includes development of original research for grant applications. Each trainee is also integrated into highly interactive multidisciplinary tumor working groups at Mayo to enhance their research experience. The co- mentoring structure for each trainee ensures that they receive the benefit of multiple research perspectives and opportunities. The base of 38 faculty/mentors include nationally and internationally known investigators in their respective fields, who have a track record of funding and demonstrated excellence in mentoring junior investigators. Evaluation of trainees is performed on a regular basis, and they are expected to generate a research grant proposal that would be suitable for submission for competitive funding. Thus, through the MCGETP, trainees will be prepared to combine laboratory-based genomics research with clinical and population sciences studies. In turn, this will address a major need for cancer investigators with genetic and molecular epidemiology expertise who can best exploit and integrate rapidly developing genomic and analytic technology for improved detection, prevention, and treatment of cancer.

Public Health Relevance

The postdoctoral Mayo Cancer Genetic Epidemiology Training Program (MCGETP) seeks to produce investigators capable of developing an independent academic career in the rapidly evolving arena of cancer research that transects the disciplines of genomics, epidemiology, statistical genetics, bioinformatics, and clinical informatics. MCGETP will address a major need for cancer investigators with genetic and molecular epidemiology expertise who can best exploit rapidly developing 'omic', bioinformatics, and analytic technology and complex data to improve our approaches to cancer prevention and care.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Education Projects (R25)
Project #
5R25CA092049-12
Application #
8850818
Study Section
Subcommittee G - Education (NCI)
Program Officer
Perkins, Susan N
Project Start
2001-08-03
Project End
2019-07-31
Budget Start
2015-08-01
Budget End
2016-07-31
Support Year
12
Fiscal Year
2015
Total Cost
$469,757
Indirect Cost
$34,797
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
Zhu, Qianqian; Yan, Li; Liu, Qian et al. (2018) Exome chip analyses identify genes affecting mortality after HLA-matched unrelated-donor blood and marrow transplantation. Blood 131:2490-2499
Clay-Gilmour, Alyssa I; Kumar, Shaji; Rajkumar, S Vincent et al. (2018) Risk of MGUS in relatives of multiple myeloma cases by clinical and tumor characteristics. Leukemia :
McWilliams, Robert R; Wieben, Eric D; Chaffee, Kari G et al. (2018) CDKN2A Germline Rare Coding Variants and Risk of Pancreatic Cancer in Minority Populations. Cancer Epidemiol Biomarkers Prev 27:1364-1370
Wu, Dongyan; Yang, Haitao; Winham, Stacey J et al. (2018) Mediation analysis of alcohol consumption, DNA methylation, and epithelial ovarian cancer. J Hum Genet 63:339-348
Leon-Ferre, Roberto A; Polley, Mei-Yin; Liu, Heshan et al. (2018) Impact of histopathology, tumor-infiltrating lymphocytes, and adjuvant chemotherapy on prognosis of triple-negative breast cancer. Breast Cancer Res Treat 167:89-99
Orlenko, Alena; Moore, Jason H; Orzechowski, Patryk et al. (2018) Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure. Pac Symp Biocomput 23:460-471
Sucheston-Campbell, Lara E; Clay-Gilmour, Alyssa I; Barlow, William E et al. (2018) Genome-wide meta-analyses identifies novel taxane-induced peripheral neuropathy-associated loci. Pharmacogenet Genomics 28:49-55
Breitenstein, Matthew K; Liu, Hongfang; Maxwell, Kara N et al. (2018) Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution. Clin Transl Sci 11:85-92
Natanzon, Yanina; Earp, Madalene; Cunningham, Julie M et al. (2018) Genomic Analysis Using Regularized Regression in High-Grade Serous Ovarian Cancer. Cancer Inform 17:1176935118755341
Lilyquist, Jenna; Ruddy, Kathryn J; Vachon, Celine M et al. (2018) Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future. Cancer Epidemiol Biomarkers Prev 27:380-394

Showing the most recent 10 out of 124 publications