Risk Factors for Breast Cancer in Younger Nurses

描述(由申请人提供)：随着对116,430名参加护士健康研究II的妇女的跟踪调查，现在由一项合作协议(UM1CA176726)支持，这项竞争性的更新继续对乳腺癌风险的可改变决定因素的科学追求，特别是那些在绝经前几年起作用的因素。在这个独特的队列中，暴露信息每隔两年收集一次，从1989年开始，当时女性年龄在25-42岁之间，93%的累积随访率。我们专注于年轻女性，并进行了28年的随访，从而可以检查早期成人接触情况以及绝经前后诊断的乳腺癌；到2017年，我们预计发生6,232例乳腺癌病例。我们广泛的生物库，包括血液和脸颊样本、肿瘤组织和乳房X光检查，使我们能够彻底检查生活方式因素、生物标记物、中间终点和肿瘤表达之间的关系。在这项建议中，我们的目标是确定与乳腺癌风险相关的饮食和代谢因素，并通过结合血浆代谢组谱和肿瘤亚型来研究潜在的机制。代谢组是一组小分子代谢物，是基因组的最终下游产物，但也受到饮食和其他可修饰因素的强烈影响，对细胞、组织和整个生物体的生长和维持至关重要。通过测量血浆中的特定代谢物，我们建议检测支链氨基酸(缬氨酸、亮氨酸、异亮氨酸)，并评估更广泛的代谢组学特征，这些特征可能在乳腺癌的发生中起重要作用。在之前确定与乳腺癌和糖尿病相关的饮食因素的基础上，我们将研究这些因素如何通过它们对代谢组的影响来影响乳腺癌，包括支链氨基酸的摄入量、饮食中的乳腺癌风险因素(酒精、红肉、水果、蔬菜)以及饮食中的糖尿病风险降低评分。我们将询问PI3K/Akt/mTOR信号通路，该信号通路调节细胞的生长、增殖、侵袭和生存，在乳腺癌中起重要作用。PIK3CA基因突变或PTEN缺失，出现在50%-75%的乳腺肿瘤中，导致结构性活跃的mTOR。影响这一途径的饮食和其他可改变的危险因素有望与由于这些基因变化而尚未激活PI3K途径的肿瘤特异性相关。为了评估这些机制的可能作用，我们将研究代谢、饮食和生活方式因素与乳腺癌风险的关系，包括肿瘤PIK3CA突变和PTEN缺失。对于我们观察到的任何重要关联，我们将检查乳房密度作为暴露与乳腺癌之间的中介。我们的目标将大大提高我们对饮食因素、代谢组和PI3K途径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战略，包括改变饮食，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.