The longterm objective of this work is to advance breast cancer prevention and risk prediction by identifying molecular events underlying early initiation/predisposition to breast cancer. Current prevention therapies for breast cancer are proven to be effective at reducing estrogen receptor positive (ER+) cancers but have no impact on preventing ER negative (ER-) cancers. This differential effect on breast cancer prevention provides strong evidence that ER+ and ER- cancers have different pathways to carcinogenesis, but the earliest steps in tumorigenesis remain poorly understood. Furthermore, there are no existing methods to accurately predict an individual woman's risk for either ER+ or ER- breast cancer. Investigation into early drivers of breast cancer through study of premalignant breast tissues will yield information on biomarkers for risk prediction and relevant pathways that may inform new prevention strategies. In this research proposal, high throughput molecular studies of benign breast biopsy tissues will be performed in a large cohort of women who underwent benign breast biopsy, with information available on later breast cancers and ER status of the tumors. A case control subset will be developed from the cohort, with equal numbers of ER+, ER-, and control subjects.
In Aim 1 we will perform gene expression profiling and create gene signatures associated with risk of ER+ and ER- breast cancer.
In Aim 2, benign breast biopsy tissues will be evaluated for select candidate driver mutations (the most common based on published findings) and their associations with risk of ER+ and ER- breast cancer. A subset of samples with paired breast tissue and germline DNA will undergo whole exome sequencing to investigate somatic mutations associated with cancer. Gene pathways identified in profiling studies will be correlated with driver mutations.
In Aim 3, information on gene expression profiles and somatic mutations in benign breast disease tissues will be used to improve risk stratification for ER+ and ER- breast cancers. This work will result in the creation of gene signatures predictive of ER+ and ER- BC, which will likely improve risk prediction for ER+ BC and increase uptake of ER+ prevention therapies. Genomic signatures of ER- BC risk will help to identify key oncogenic pathways and new prevention treatments for ER- BC.
In this research, breast tissue samples without cancer are studied for changes in tissue molecules and genes that help to identify women at increased risk for developing future breast cancer. These tissue molecules will also be studied for associations with the two main types of breast cancers - those that grow in response to estrogen and those that grow without estrogen. The research findings will help to improve the ability to predict which women get breast cancer and what type of cancer it may be, and it will lead to new ideas for preventing breast cancer.
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|Degnim, Amy C; Winham, Stacey J; Frank, Ryan D et al. (2018) Model for Predicting Breast Cancer Risk in Women With Atypical Hyperplasia. J Clin Oncol 36:1840-1846|
|Visscher, Daniel W; Frank, Ryan D; Carter, Jodi M et al. (2017) Breast Cancer Risk and Progressive Histology in Serial Benign Biopsies. J Natl Cancer Inst 109:|
|Stallings-Mann, Melody L; Heinzen, Ethan P; Vierkant, Robert A et al. (2017) Postlactational involution biomarkers plasminogen and phospho-STAT3 are linked with active age-related lobular involution. Breast Cancer Res Treat 166:133-143|
|Vierkant, Robert A; Degnim, Amy C; Radisky, Derek C et al. (2017) Mammographic breast density and risk of breast cancer in women with atypical hyperplasia: an observational cohort study from the Mayo Clinic Benign Breast Disease (BBD) cohort. BMC Cancer 17:84|
|Ghosh, Karthik; Vierkant, Robert A; Frank, Ryan D et al. (2017) Association between mammographic breast density and histologic features of benign breast disease. Breast Cancer Res 19:134|
|Winham, Stacey J; Mehner, Christine; Heinzen, Ethan P et al. (2017) NanoString-based breast cancer risk prediction for women with sclerosing adenosis. Breast Cancer Res Treat 166:641-650|
|Radisky, Derek C; Visscher, Daniel W; Frank, Ryan D et al. (2016) Natural history of age-related lobular involution and impact on breast cancer risk. Breast Cancer Res Treat 155:423-30|
|Visscher, Daniel W; Frost, Marlene H; Hartmann, Lynn C et al. (2016) Clinicopathologic features of breast cancers that develop in women with previous benign breast disease. Cancer 122:378-85|
|Degnim, Amy C; Visscher, Daniel W; Radisky, Derek C et al. (2016) Breast cancer risk by the extent and type of atypical hyperplasia. Cancer 122:3087-8|
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