Growth Hormones and Breast Cancer Risk

描述（由申请人提供）：生长因子与乳腺癌病因之间的关系复杂，尚未完全了解；然而，强有力的实验证据支持它们在乳腺癌发生中的作用。因此，在本提案中，我们将对催乳素及其与乳腺癌风险的关系进行详细的评估。本研究将采用前瞻性巢式病例对照设计，在绝经前或围绝经期妇女中采血（截至2011年诊断的1542例）。1996- 1999年护士健康研究II （NHSII）从29,611名年龄在32至52岁的妇女中收集样本，1989- 1990年从32,826名年龄在43至62岁的NHS参与者中收集样本。除了评估催乳素与乳腺癌的整体相关性外，本研究还将研究催乳素是否与雌激素受体阳性肿瘤的风险相关性更强，以及催乳素、催乳素受体、细胞周期蛋白D1、磷酸化STAT3和STAT5的肿瘤染色阳性。观察到这种对催乳素受体及其下游靶点的特异性，将大大增加因果关系的案例。先前的研究使用免疫分析法评估催乳素水平，该方法测量具有不同生物活性的多种异构体。这项研究将首次通过催乳素生物活性测定对乳腺癌风险进行前瞻性评估，这可能更好地反映催乳素在生物学上的重要作用。此外，由于已知的生物活性催乳素相关因素很少，本提案将首次评估其与已知和假定的乳腺癌危险因素（例如，胎次，轮班工作）的关系。该队列现有激素数据的可用性将使泌乳素作为一个独立的乳腺癌危险因素及其与其他激素的相互关系的检查成为可能。重要的是，我们增加了一个目标，直接评估添加催乳素对乳腺癌的综合风险预测模型，这可能是有用的临床。催乳素的几个特征使其成为纳入此类模型的有吸引力的候选者，包括免疫测定是一种标准化和常见的临床测定，非常便宜且易于测量。此外，催乳素相关性的程度似乎与乳腺癌风险预测模型中包含的其他因素相似。我们还将评估生物测定的纳入情况；如果这种方法能比免疫测定法更好地提高预测能力，它将推动人们识别增加乳腺癌风险的泌乳素的特定亚型，并开发出廉价的检测方法。其他赠款将为后续和其他激素检测提供资金，以提高该项目的成本效益。最终，阐明催乳素在乳腺癌中的作用可以为治疗和预防开辟多个新的研究领域。

DESCRIPTION (provided by applicant): The relationship between growth factors and breast cancer etiology is complex and not completely understood; however, strong experimental evidence supports their role in breast carcinogenesis. Therefore, in this proposal, we will conduct a detailed evaluation of prolactin and its association with breast cancer risk. This study will use a prospective nested case-control design among pre- or perimenopausal women at blood collection (1,542 cases diagnosed through 2011). Samples were collected in the Nurses' Health Study II (NHSII) in 1996-99 from 29,611 women, ages 32 to 52 years, and in 1989-90 from 32,826 NHS participants, ages 43 to 62 years. In addition to assessing the overall prolactin-breast cancer association, this study will examine whether prolactin is more strongly associated with risk of estrogen receptor positive tumors, as well as tumors staining positive for prolactin, prolactin receptor, cyclin D1, and phosphorylated STAT3 and STAT5. Observing such specificity to the prolactin receptor and its downstream targets would add substantially to the case for causality. Prior studies have assessed prolactin levels using an immunoassay that measures multiple isoforms with differing biologic activities. This study will provide the first prospective assessment of breast cancer risk with a prolactin bioactivity assay, which may better reflect the portion of prolactin that is biologically important. Also, since few correlates of bioactive prolactin are known, this proposal will assess, for the first time, its relationship with known and putative breast cancer risk factors (e.g., parity, shift work). The availability of existing hormone data for this cohort will enable the examination of prolactin as an independent breast cancer risk factor and its interrelationships with other hormones. Importantly, we have added an aim to directly evaluate the addition of prolactin to a comprehensive risk prediction model for breast cancer, which could be useful clinically. Several features of prolactin make it an attractive candidate for inclusion into such models, including that the immunoassay is a standardized and common clinical assay that is very inexpensive and easy to measure. Further, the magnitude of the prolactin association appears to be similar to other factors included in breast cancer risk prediction models. We also will evaluate the inclusion of the bioassay; if this improves prediction better than the immunoassay, it would provide impetus to identify the specific isoforms of prolactin that increase risk of breast cancer and develop inexpensive assays for their measurement. Other grants will provide funding for follow-up and other hormone assays, increasing the cost-effectiveness of this project. Ultimately, elucidating the role of prolactin in breast cancer could open up multiple new areas of research for both treatment and prevention. PUBLIC HEALTH RELEVANCE: The relationship between growth factors and breast cancer etiology is complex and not completely understood; this proposal will extend knowledge about how prolactin, an important growth hormone, is associated with breast cancer risk among premenopausal and perimenopausal women. Characterizing this relationship will provide important knowledge that will translate to prevention and treatment applications. In particular, evaluation of whether prolactin improves risk prediction models could lead to better assessment of women at high risk of breast cancer and more accurate targeting of chemoprevention to these women, given that the Gail model already is utilized clinically and prolactin is an easily measured hormone that is stable across the menstrual cycle and the menopausal transition.