Metabolite Profiles and Mammographic Density in Premenopausal Women

摘要 2019年，美国约有268，600名女性将被诊断患有乳腺癌，使其成为全球最大的乳腺癌患者。 女性癌症的原因。这些病例中约25%发生在绝经前妇女中。年度 自20世纪90年代中期以来，50岁以下妇女的乳腺癌发病率一直在缓慢上升， 与50岁以上女性中观察到的情况形成鲜明对比，50岁以上女性的发病率在50年内保持稳定 时间年轻妇女发病率的持续上升表明， 需要对绝经前妇女进行一级预防。乳房X线摄影乳腺密度是 乳腺癌的最强风险因素，特别是在绝经前妇女中，估计39%的 乳腺癌病例可归因于乳房致密。乳腺密度的降低会导致 乳腺癌的发病率。尽管如此，乳房X线摄影乳腺密度的分子基础和 致密乳腺增加乳腺癌风险的机制知之甚少。更大 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志物。代谢组学是一种很有前途的工具， 为疾病病因学、生物学机制和途径提供新的见解。代谢组学， 然而，尚未应用于研究乳腺X线摄影乳腺密度。我们的试点分析显示， 脂肪性乳房的女性与致密性乳房的女性之间的代谢物水平。根据这些 新的发现，我们将应用最先进的代谢组学平台，1）研究代谢组学的 绝经前妇女的乳房X线摄影乳腺密度; 2）量化乳房X线摄影乳腺密度的变化 密度的代谢组解释; 3）确定乳腺钼靶摄影密度的代谢组是否 预测绝经前妇女乳腺癌的发展。我们的首要假设是， 利用代谢组学来揭示分子机制，生物途径，以及新的可操作的 与绝经前妇女乳房X线摄影乳腺密度相关的生物标志物。我们的研究 人群将包括在Joanne的年度筛查乳房X光检查中招募的绝经前妇女。 密苏里州圣路易斯市华盛顿大学医学院的奈特乳房健康中心。乳房摄影 使用Volpara定量评估乳腺密度。在同一天采集空腹血样 妇女们都做了乳房X光检查这些妇女还填写了一份问卷，其中详细介绍了 乳腺癌的危险因素和乳腺摄影密度的决定因素。最后，我们将在我们的 令人兴奋的初步数据揭示了与乳腺X线摄影相关的新型可操作生物标志物 密度，以及绝经前妇女乳腺癌的发展。这些生物标志物可以作为 乳腺癌的预防在未来的研究。

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.