Most of the 250,000 U.S. women diagnosed annually with in situ or invasive breast cancer (BC) were not recognized as being at increased risk for the disease. Both the NCI and Institute of Medicine have identified accurate individualized risk assessment as central to improving early detection and prevention. The most widely used risk prediction model for BC, the Gail model, generally performs well in predicting BC risk across groups of women, but is limited when predicting individualized risk. In general, the cancers for which we can predict susceptibility best are those where the at-risk tissue can be examined, e.g., cervix, colon, endometrium. In breast, benign tissue is available for risk assessment from women who have had a benign biopsy. Women with so-called benign breast disease (BBD), numbering 1-2 million/year In the US alone, are a common and clinically important group, with a known increased risk of BC. About 25% of women with BC report having had a prior benign biopsy. Our purpose with this project is to develop a risk prediction model for women with BBD. We hypothesize that features in benign breast tissue, in particular from subgroups known to be at increased risk for BC, can help to identify those women who are at highest likelihood of progression of BC. Two recognized higher-risk groups within BBD are women with atypia, and women in whom normal, age-related regression (or involution) of breast lobules has not occurred. Utilizing a cohort of over 11,000 women with BBD at the Mayo Clinic, we will identify novel BC-predictive biomarkers obtained from transcriptional profiling of women with atypia who either did or did not progress to BC and from dissection of the mechanisms underlying lobular involution, a physiological process which we recently found to be associated with decreased cancer risk. Using a newly-developed technique, we will also quantitate the specific extent of lobular involution that has occurred In these women to generate a continuous risk feature. Then in a nested case: control series within our BBD cohort, we will build a risk prediction model that incorporates the top predicting elements from histology, clinical-epidemiologic features, mammographic density, quantitation of involution and molecular biomarkers. Finally, building upon a strong collaboration fostered by Breast SPORE developmental funds, we will assess our BC risk model using the Nashville BBD cohort supported by the Vanderbilt Breast SPORE. Altogether these studies will test the ability to use tissue based features to enhance risk prediction of BC and potentially provide insights about important early events in breast carcinogenesis.

Public Health Relevance

With the proposed work, we are testing the principle that specific histopathologic and molecular features present in benign breast tissue can discriminate risk of a subsequent breast cancer more accurately than currently used clinical and epidemiologic features. Such a risk prediction approach would facilitate personalized clinical management strategies for the 1 -2 million US women/year who have a benign biopsy

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center (P50)
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Special Emphasis Panel (ZCA1-RPRB-7)
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Mayo Clinic, Rochester
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(2015) Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk. Hum Mol Genet 24:285-98
Yee, Douglas (2015) A tale of two receptors: insulin and insulin-like growth factor signaling in cancer. Clin Cancer Res 21:667-9
Ingle, James N; Kalari, Krishna R; Buzdar, Aman U et al. (2015) Estrogens and their precursors in postmenopausal women with early breast cancer receiving anastrozole. Steroids 99:32-8
Kiiski, Johanna I; Pelttari, Liisa M; Khan, Sofia et al. (2014) Exome sequencing identifies FANCM as a susceptibility gene for triple-negative breast cancer. Proc Natl Acad Sci U S A 111:15172-7
Whiley, Phillip J; Parsons, Michael T; Leary, Jennifer et al. (2014) Multifactorial likelihood assessment of BRCA1 and BRCA2 missense variants confirms that BRCA1:c.122A>G(p.His41Arg) is a pathogenic mutation. PLoS One 9:e86836
Osorio, Ana; Milne, Roger L; Kuchenbaecker, Karoline et al. (2014) DNA glycosylases involved in base excision repair may be associated with cancer risk in BRCA1 and BRCA2 mutation carriers. PLoS Genet 10:e1004256
D'Assoro, A B; Liu, T; Quatraro, C et al. (2014) The mitotic kinase Aurora--a promotes distant metastases by inducing epithelial-to-mesenchymal transition in ER*(+) breast cancer cells. Oncogene 33:599-610
Agarwal, D; Pineda, S; Michailidou, K et al. (2014) FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium. Br J Cancer 110:1088-100
Abdel-Aal, Abu-Baker M; Lakshminarayanan, Vani; Thompson, Pamela et al. (2014) Immune and anticancer responses elicited by fully synthetic aberrantly glycosylated MUC1 tripartite vaccines modified by a TLR2 or TLR9 agonist. Chembiochem 15:1508-13
Joshi, Poorval M; Sutor, Shari L; Huntoon, Catherine J et al. (2014) Ovarian cancer-associated mutations disable catalytic activity of CDK12, a kinase that promotes homologous recombination repair and resistance to cisplatin and poly(ADP-ribose) polymerase inhibitors. J Biol Chem 289:9247-53

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