Modern biomedical research relies on both multidisciplinary and interdisciplinary approaches to advance our understanding of complex and multifaceted illnesses of growing public health significance such as cancer. Emerging technologies enable population scientists to generate data on a scale never before imaginable (i.e., through whole genome array scans). Thus, there is a critical need to not only train the next generation of scientists in the classic disciplines involved in studies of human malignancies, but to cross-train them in complementary disciplines to allow them to bring their scientific discoveries to light. Therefore, we propose to continue a highly successful postdoctoral program that combines specialized research knowledge and methodologies in the fields of bioinformatics, biostatistics and epidemiology. This novel program, entitled Training Program for Quantitative Population Sciences in Cancer, will be structured to complement the existing resources for cancer research and education at the Geisel School of Medicine and will be aligned with the mission of the Norris Cotton Cancer Center (NCCC), an NCI designated Comprehensive Cancer Center affiliated with the Geisel School of Medicine at Dartmouth and Dartmouth Hitchcock Medical Center (DHMC). The training efforts will continue to be led by established investigators with complementary expertise in the fields of bioinformatics, biostatistics and epidemiology within the Departments of Genetics and Community and Family Medicine, Section of Biostatistics and Epidemiology. We will capitalize on Dartmouth's expanded faculty in these disciplines who can offer expert mentorship, and an enlarging portfolio of research and center grants that can supply access to a wealth of population science data, biologic samples and core research facilities. To accomplish our objectives, we propose to cross-train six postdoctoral trainees in epidemiology, bioinformatics or biostatistics for a period of 2 to 3 years. Trainees will be paired with a primary and secondary mentor from two of the focus disciplines and complete cross-disciplinary coursework in the first year of the program. In years two and three of the program, trainees will concentrate on the conduct of mentored research activities, prepare a mock NIH grant application, and participate in the preparation of professional manuscripts and presentations at symposia and scientific conferences. Program leaders, with consultation of an Advisory Committee, will select trainees, monitor their progress and provide recommendations to ensure that the necessary didactic and research experiences are provided to produce highly knowledgeable investigators for the future of interdisciplinary cancer research in the population sciences. The ultimate goal of the training program is to accelerate cancer research by enhancing the existing pool of cancer researchers with the skills needed to meet the present and future needs in translational cancer research in the population sciences.

Public Health Relevance

We will continue our goal of improving the resources available for future cancer research by providing innovative interdisciplinary training for postdoctoral fellows. This program is designed to provide early career researchers with opportunities to integrate specialized research knowledge and methodologies within the fields of bioinformatics, biostatistics and epidemiology. Trainees will be positioned to expedite the translation of cancer science into public health practice as leaders on multidisciplinary research teams.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Education Projects (R25)
Project #
5R25CA134286-07
Application #
8882287
Study Section
Subcommittee G - Education (NCI)
Program Officer
Perkins, Susan N
Project Start
2008-07-01
Project End
2019-07-31
Budget Start
2015-08-01
Budget End
2016-07-31
Support Year
7
Fiscal Year
2015
Total Cost
$489,546
Indirect Cost
$36,263
Name
Dartmouth College
Department
Family Medicine
Type
Schools of Medicine
DUNS #
041027822
City
Hanover
State
NH
Country
United States
Zip Code
03755
Batsis, J A; Mackenzie, T A; Vasquez, E et al. (2018) Association of adiposity, telomere length and mortality: data from the NHANES 1999-2002. Int J Obes (Lond) 42:198-204
Brickley, Elizabeth B; Strauch, Carolyn B; Wieland-Alter, Wendy F et al. (2018) Intestinal Immune Responses to Type 2 Oral Polio Vaccine (OPV) Challenge in Infants Previously Immunized With Bivalent OPV and Either High-Dose or Standard Inactivated Polio Vaccine. J Infect Dis 217:371-380
Moen, Erika L; Bynum, Julie P; Austin, Andrea M et al. (2018) Assessing Variation in Implantable Cardioverter Defibrillator Therapy Guideline Adherence With Physician and Hospital Patient-sharing Networks. Med Care 56:350-357
Rippberger, Peter L; Emeny, Rebecca T; Mackenzie, Todd A et al. (2018) The association of sarcopenia, telomere length, and mortality: data from the NHANES 1999-2002. Eur J Clin Nutr 72:255-263
He, Xiaofei; Schifferdecker, Karen E; Ozanne, Elissa M et al. (2018) How Do Women View Risk-Based Mammography Screening? A Qualitative Study. J Gen Intern Med 33:1905-1912
Emeny, Rebecca T; Baumert, Jens; Zannas, Anthony S et al. (2018) Anxiety Associated Increased CpG Methylation in the Promoter of Asb1: A Translational Approach Evidenced by Epidemiological and Clinical Studies and a Murine Model. Neuropsychopharmacology 43:342-353
Felix, Janine F; Joubert, Bonnie R; Baccarelli, Andrea A et al. (2018) Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium. Int J Epidemiol 47:22-23u
Fricano-Kugler, Catherine J; Getz, Stephanie A; Williams, Michael R et al. (2018) Nuclear Excluded Autism-Associated Phosphatase and Tensin Homolog Mutations Dysregulate Neuronal Growth. Biol Psychiatry 84:265-277
Salas, Lucas A; Johnson, Kevin C; Koestler, Devin C et al. (2017) Integrative epigenetic and genetic pan-cancer somatic alteration portraits. Epigenetics 12:561-574
Lee, Jai Woo; Punshon, Tracy; Moen, Erika L et al. (2017) Penalized estimation of sparse concentration matrices based on prior knowledge with applications to placenta elemental data. Comput Biol Chem 71:219-223

Showing the most recent 10 out of 99 publications