) Epidemiologic studies have highlighted the relationship between hormones and carcinogenesis in the breast by identifying endocrine risk factors for breast cancer that are related to the timing of reproductive endocrine events. This relationship is illustrate by the observation that women who undergo an early first full-term pregnancy have a significantly reduced lifetime risk of breast cancer. The recognition that specific reproductive endocrine events alter breast cancer risk in a predictable fashion raises the possibility that events associated with a decrease in breast cancer risk, such as early first full-term pregnancy, might be mimicked pharmacologically. As such, understanding the mechanisms by which these events influence breast cancer risk would facilitate the design of safe and effective hormonal chemoprevention regimens. In addition, the testing of such regimens would be facilitated by the identification of biomarkers that accurately reflect early biological changes in the breast associated with reproductive endocrine events that alter breast cancer susceptibility. We hypothesize that understanding the biological mechanisms by which endogenous hormones exposures influence breast cancer susceptibility will require a thorough understanding of the cell types present in the breast and the manner in which hormones affect their normal programs of differentiation and development.
The specific aims of this proposal are designed to develop molecular biomarkers for parity-induced changes in the breast using an established rodent model for parity-induced protection against breast cancer, to evaluate the utility of these biomarkers in human breast tissue, and to use these biomarkers to explore the molecular and cellular changes that occur in the breast a result of parity. Ultimately, these studies are intended as a step towards determining the mechanisms by which breast cancer susceptibility is modulated by reproductive history.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
1P01CA077596-01
Application #
6103462
Study Section
Project Start
1998-07-15
Project End
1999-06-30
Budget Start
Budget End
Support Year
1
Fiscal Year
1998
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Type
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Jordan, Susan J; Na, Renhua; Johnatty, Sharon E et al. (2017) Breastfeeding and Endometrial Cancer Risk: An Analysis From the Epidemiology of Endometrial Cancer Consortium. Obstet Gynecol 129:1059-1067
Cote, Michele L; Alhajj, Tala; Ruterbusch, Julie J et al. (2015) Risk factors for endometrial cancer in black and white women: a pooled analysis from the Epidemiology of Endometrial Cancer Consortium (E2C2). Cancer Causes Control 26:287-296
Gabriel, Courtney A; Mitra, Nandita; Demichele, Angela et al. (2013) Association of progesterone receptor gene (PGR) variants and breast cancer risk in African American women. Breast Cancer Res Treat 139:833-43
Chen, Fang; Chen, Gary K; Stram, Daniel O et al. (2013) A genome-wide association study of breast cancer in women of African ancestry. Hum Genet 132:39-48
Setiawan, Veronica Wendy; Yang, Hannah P; Pike, Malcolm C et al. (2013) Type I and II endometrial cancers: have they different risk factors? J Clin Oncol 31:2607-18
O'Mara, Tracy A; Fahey, Paul; Ferguson, Kaltin et al. (2011) Progesterone receptor gene variants and risk of endometrial cancer. Carcinogenesis 32:331-5
Healey, Catherine S; Ahmed, Shahana; ANECS et al. (2011) Breast cancer susceptibility polymorphisms and endometrial cancer risk: a Collaborative Endometrial Cancer Study. Carcinogenesis 32:1862-6
Rebbeck, Timothy R; Su, H Irene; Sammel, Mary D et al. (2010) Effect of hormone metabolism genotypes on steroid hormone levels and menopausal symptoms in a prospective population-based cohort of women experiencing the menopausal transition. Menopause 17:1026-34
Rebbeck, Timothy R; DeMichele, Angela; Tran, Teo V et al. (2009) Hormone-dependent effects of FGFR2 and MAP3K1 in breast cancer susceptibility in a population-based sample of post-menopausal African-American and European-American women. Carcinogenesis 30:269-74
Mushlin, Richard A; Gallagher, Stephen; Kershenbaum, Aaron et al. (2009) Clique-finding for heterogeneity and multidimensionality in biomarker epidemiology research: the CHAMBER algorithm. PLoS One 4:e4862

Showing the most recent 10 out of 25 publications