Risk Factors for Breast Cancer in Younger Nurses

描述（由申请人提供）：通过对参加护士健康研究II的116，430名妇女进行随访，目前得到了合作协议（UM 1CA 176726）的支持，这种竞争性更新继续对乳腺癌风险的可改变决定因素进行科学追求，特别是那些在绝经前年龄起作用的因素。在这个独特的队列中，从1989年开始，每两年收集一次暴露信息，当时女性年龄为25-42岁，累积随访率为93%。我们对年轻女性进行了28年的随访，可以检查绝经前后诊断出的早期成人暴露和乳腺癌;到2017年，我们预计将有6，232例乳腺癌病例。我们广泛的生物储存库，包括血液和脸颊样本，肿瘤组织和乳房X线照片，使我们能够彻底检查生活方式因素，生物标志物，中间终点和肿瘤表达之间的关系。在这项提案中，我们的目标是确定与乳腺癌风险相关的饮食和代谢因素，并通过纳入血浆代谢组学特征和肿瘤亚型来研究潜在的机制途径。代谢组，定义为一组小分子代谢物，它们是基因组的最终下游产物，但也受到饮食和其他可改变因素的强烈影响，对于细胞，组织和整个生物体的生长和维持至关重要。测量血浆中的特定代谢物，我们建议检查支链氨基酸（缬氨酸，亮氨酸，异亮氨酸），以及更广泛地评估代谢组学的签名，可能是重要的乳腺癌发生。基于先前确定与乳腺癌和糖尿病相关的饮食因素的工作，我们将研究这些因素如何通过对代谢组的影响影响乳腺癌，包括支链氨基酸的摄入，饮食乳腺癌风险因素（酒精，红肉，水果，蔬菜）和饮食糖尿病风险降低评分。我们将询问PI 3 K/Akt/mTOR信号通路，其调节细胞生长、增殖、侵袭和存活，并且在乳腺癌中是重要的。PIK 3CA基因的突变或PTEN的缺失，存在于50-75%的乳腺肿瘤中的事件，导致组成型活性mTOR。影响这一通路的饮食和其他可改变的风险因素预计将与由于这些遗传变化而尚未激活PI 3 K通路的肿瘤特异性相关。为了评估这些机制的可能作用，我们将研究与乳腺癌风险相关的代谢组学，饮食和生活方式因素，包括肿瘤PIK 3CA突变和PTEN缺失。对于我们观察到的任何显着关联，我们将检查乳腺密度作为暴露和乳腺癌之间的中介。我们的目标将大大提高我们对饮食因素，代谢组学和PI 3 K通路在乳腺癌病因学中的作用的理解。这些目标将确定潜在的预防策略，包括饮食改变，以及用于风险预测和化学预防的新代谢目标。

DESCRIPTION (provided by applicant): With the follow-up of 116,430 women enrolled in the Nurses' Health Study II now supported by a cooperative agreement (UM1CA176726), this competing renewal continues the scientific pursuit of modifiable determinants of breast cancer risk, especially those acting during the premenopausal years. In this unique cohort, exposure information has been collected at two-year intervals, beginning in 1989 when women were 25-42 years of age, with 93% cumulative follow-up. Our focus on younger women with 28 years of follow-up allows examination of early adult exposures and breast cancers diagnosed before and after menopause; through 2017 we expect 6,232 incident breast cancer cases. Our extensive biorepository, with blood and cheek samples, tumor tissue, and mammograms, allows us to thoroughly examine relationships between lifestyle factors, biomarkers, intermediate endpoints, and tumor expression. In this proposal, we aim to identify dietary and metabolic factors associated with breast cancer risk, and to examine the underlying mechanistic pathways by incorporating plasma metabolomic profiles and tumor subtypes. The metabolome, defined as the set of small molecule metabolites that are the final downstream products of the genome, but which is also strongly influenced by diet and other modifiable factors, is critical for growth and maintenance of cells, tissues and entire organisms. Measuring specific metabolites in plasma, we propose to examine branched chain amino acids (valine, leucine, isoleucine) as well as evaluate more broadly metabolomic signatures that may be important in breast carcinogenesis. Building on previous work identifying dietary factors associated with breast cancer and diabetes, we will examine how these influence breast cancer through their effect on the metabolome, including intake of branched chain amino acids, dietary breast cancer risk factors (alcohol, red meat, fruits, vegetables), and a dietary diabetes risk reduction score. We will interrogate the PI3K/Akt/mTOR signaling pathway that regulates cell growth, proliferation, invasion, and survival and is important in breast cancer. Mutations in the PIK3CA gene or loss of PTEN, events present in 50-75% of breast tumors, lead to constitutively active mTOR. Dietary and other modifiable risk factors that influence this pathway would be expected to be associated specifically with tumors that do not already have an activated PI3K pathway due to these genetic changes. To evaluate the possible role of these mechanisms, we will examine metabolomic, dietary, and lifestyle factors in relation to breast cancer risk, incorporating tumor PIK3CA mutations and loss of PTEN. For any significant associations we observe, we will examine breast density as a mediator between exposures and breast cancer. Our aims will substantially enhance our understanding of the role of dietary factors, the metabolome, and the PI3K pathway in the etiology of breast cancer. These aims will identify potential preventive strategies, including dietary changes, and new metabolic targets for risk prediction and chemoprevention.