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DESCRIPTION (provided by applicant): To understand the multi-factorial nature of breast carcinogenesis, we must determine what factors play a role at each stage. By studying benign breast disease we can examine an earlier period in the disease process. This proposal aims to examine a full spectrum of stages on the pathway to breast cancer in Nurses' Health Study I and II: 1) early stages by focusing on the relationship between adolescent diet and incidence of proliferative breast disease; 2) intermediate and cumulative lifetime exposures by concentrating on genetic and molecular predictors of proliferative breast disease; and 3) later stages by examining protein expression in benign breast tissue and subsequent breast cancer risk. Specifically, we hypothesize that adolescent intake of total and specific subtypes of fat are associated with proliferative breast disease; polymorphisms and haplotypes in the insulin-like growth factor (IGF)-I pathway and the progesterone receptor, as well as circulating levels of IGF-1 and IGFBP-3, are related to incidence of proliferative benign breast disease; expression of molecular markers (ER-a, PR, IGF-1 R, Ki67 and cytokeratin 5/6) in benign breast disease tissue is associated with subsequent risk of breast cancer. This study offers a unique opportunity to prospectively examine adolescent diet and molecular markers in relation to proliferative breast disease. Additional follow-up of the breast cancer nested case-control data set will allow us to examine in more detail the relationship between proliferative breast disease and subsequent breast cancer. The creation of tissue microarrays using benign breast tissue will lay the foundation for this and future studies to efficiently examine the role of molecular markers in the development of breast cancer.
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Stromal contributions to breast carcinogenesis
  • 批准号:
    10748124
  • 项目类别:
  • 资助金额:
    $75.85万
  • 财政年份:
    2023
  • 负责人:
    Rulla M Tamimi
  • 依托单位:
Administrative Core
Prediagnostic exposures, germline genetics, and triple negative breast cancer mutational and immune profiles
Computational pathology to predict breast cancer risk in benign breast disease
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