Metabolite Profiles and Mammographic Density in Premenopausal Women

摘要 2019年，美国约有268,600名女性将被诊断出患有乳腺癌，使其成为全球 女性罹患癌症的原因。其中约25%的病例发生在绝经前的妇女中。一年一度的 自20世纪90年代中期以来，50岁以下女性的乳腺癌发病率一直在缓慢增长， 与50岁以上女性的观察结果形成鲜明对比的是，50岁以上女性的发病率在 时间到了。年轻女性发病率的持续上升表明，新的治疗方法 需要对绝经前妇女进行初级预防。乳房X光检查的乳房密度是 乳腺癌的最大危险因素，特别是在绝经前的妇女中，估计有39% 乳腺癌病例可归因于乳房致密。乳房密度的降低会导致乳房密度的减少 乳腺癌发病率的上升。然而，乳房X光检查乳房密度的分子基础和 致密乳房增加乳腺癌风险的机制还知之甚少。一个更伟大的 了解这些机制是至关重要的，并将发现新的生物途径和可操作的 可以靶向预防乳腺癌发展的生物标记物。代谢组学是一种很有前途的工具 为疾病病因、生物机制和途径提供新的见解。代谢组学已经， 然而，目前尚未将其应用于乳房X光摄影密度的研究。我们的试点分析显示， 乳房肥大的女性与乳房致密的女性之间的代谢物水平。建立在这些基础上 新发现，我们将应用最先进的代谢组学平台1)研究 绝经前妇女乳腺钼靶摄影密度；2)乳腺钼靶摄影变异的量化 密度用代谢组来解释；3)决定代谢组乳腺X线摄影的密度是否 预测绝经前妇女患乳腺癌的情况。我们最重要的假设是我们会 利用代谢组学揭示分子机制、生物途径以及新的可操作的 与绝经前妇女乳房X光检查乳房密度相关的生物标记物。我们的研究 人口将由乔安妮每年筛查乳房X光检查时招募的绝经前妇女组成 密苏里州圣路易斯市华盛顿大学医学院的骑士乳房健康中心。乳房X光摄影 乳房密度使用Volpara进行定量评估。在同一天采集禁食血样 这些妇女做了乳房X光检查。这些妇女还完成了一份调查问卷，上面有关于 乳腺癌的危险因素和乳房X线摄影密度的决定因素。总而言之，我们将在我们的 令人兴奋的初步数据揭示与乳房X光检查相关的新的、可操作的生物标记物 密度，以及绝经前妇女中乳腺癌的发展。这些生物标志物可能成为目标 在未来的研究中对乳腺癌的预防。

ABSTRACT In 2019, approximately 268,600 women in the US will be diagnosed with breast cancer, making it the leading cause of cancer in women. About 25% of these cases occurred in premenopausal women. The annual incidence of breast cancer among women under age 50 has been increasing slowly since the mid-1990s, in contrast to what is observed in women aged over 50 years, where the incidence has remained stable over time. This persistent increase in the incidence among younger women indicates that new approaches to primary prevention in premenopausal women are needed. Mammographic breast density is one of the strongest risk factors for breast cancer, especially in premenopausal women, where an estimated 39% of breast cancer cases is attributable to having dense breasts. A decrease in breast density leads to a reduction in breast cancer incidence. Nevertheless, the molecular basis of mammographic breast density and the mechanisms through which dense breast increases breast cancer risk are poorly understood. A greater understanding of these mechanisms is crucial, and will uncover new biological pathways and actionable biomarkers that can be targeted to prevent breast cancer development. Metabolomics is a promising tool to provide novel insights into disease etiology, biological mechanisms, and pathways. Metabolomics has, however, not been applied to study mammographic breast density. Our pilot analyses show differences in metabolite levels between women with fatty breasts compared to women with dense breasts. Building on these novel findings, we will apply state-of-the art metabolomics platforms to 1) investigate the metabolome of mammographic breast density in premenopausal women; 2) quantify the variation in mammographic breast density explained by the metabolome; 3) determine whether the metabolome of mammographic breast density predicts breast cancer development in premenopausal women. Our overarching hypothesis is that we will leverage metabolomics to uncover the molecular mechanisms, biological pathways, as well as novel actionable biomarkers that are associated with mammographic breast density in premenopausal women. Our study population will consist of premenopausal women recruited during annual screening mammogram at the Joanne Knight Breast Health Center at the Washington University School of Medicine, St. Louis, MO. Mammographic breast density is quantitatively assessed using Volpara. Fasting blood samples are collected on the same day the women have their mammograms. The women also complete a questionnaire with detailed information on breast cancer risk factors and determinants of mammographic density. In conclusion, we will build on our exciting preliminary data to uncover novel, actionable biomarkers associated with mammographic breast density, and also breast cancer development in premenopausal women. These biomarkers could be targeted in breast cancer prevention in future studies.