Predictors of Ovarian Function in Women Treated With Aromatase Inhibitors

描述(申请人提供)：这份K07申请的目的是提供必要的培训和环境，使候选人能够成为一名独立的研究人员，能够设计、实施和获得资金，用于高质量的临床和转化性研究，重点是乳腺癌的内分泌治疗。在拟议的辅导期内，职业发展活动将包括(1)完成临床研究设计和统计分析(K30计划)硕士学位，以及在遗传学、药物基因组学和基因组研究伦理学方面的额外教学指导；(2)丹尼尔·海斯博士(国际公认的乳腺癌治疗和肿瘤标记物分析专家)在设计、实施和解释与乳腺癌辅助芳香酶抑制剂(AI)治疗中卵巢功能预测因素相关的研究方面的指导；(3)与乳腺癌药物基因组学联盟和密歇根大学的资深同事在药物基因组学、卵巢储备、以及更年期的转变。候选人提出了一项研究项目，该项目将专注于患有早期乳腺癌的绝经前女性，她们患有化疗导致的卵巢衰竭(CIOF)。这些妇女可能会从人工智能治疗中的雌激素剥夺中获得比从他莫昔芬中获得的更多的好处，正如已经在绝经后妇女中所证明的那样。然而，由于LHRH反馈环，很大一部分人可能在人工智能治疗期间恢复卵巢功能，这将使人工智能治疗无效。该提案的基石是对患有CIOF的女性进行人工智能治疗的前瞻性临床试验。总体目标是利用从研究参与者那里收集的研究样本和数据，确定人工智能治疗期间卵巢功能变化的临床适用的遗传、流行病学和生化预测因子。我们假设我们可以预测哪些妇女在人工智能治疗期间将保持绝经后状态，哪些妇女极有可能恢复卵巢功能。概述的职业发展计划，以及这项K07应用的指导研究建议，将增强候选人的知识和研究技能，使其能够成功过渡到临床和转化性乳腺肿瘤学的独立研究生涯。相关性：在美国，每年大约有2万名绝经前乳腺癌患者接受化疗和内分泌治疗。芳香酶抑制剂(AI)治疗可能比他莫昔芬更好，但由于卵巢功能可能恢复，并不是对所有患者都是安全的。在这项提案中，我们将确定哪些患者可以安全地接受人工智能治疗，这将使治疗决策更加个性化。

DESCRIPTION (provided by applicant): The purpose of this K07application is to provide the necessary training and environment to prepare the candidate to become an independent investigator, able to design, conduct, and acquire funding for high-quality clinical and translational studies that focus on endocrine therapy for breast cancer. During the proposed mentored period, career development activities will include (1) completion of a Masters Degree in Clinical Research Design and Statistical Analysis (K30 program), as well as additional didactic instruction in genetics, pharmacogenomics, and the ethics of genomic research, (2) mentorship by Dr. Daniel Hayes (an internationally recognized expert in breast cancer treatment and tumor marker analysis) in the design, execution, and interpretation of studies related to predictors of ovarian function during adjuvant aromatase inhibitor(AI) therapy for breast cancer, and (3) substantial collaboration with senior colleagues in the Consortium on Breast Cancer Pharmacogenomics and at the University of Michigan on pharmacogenomics, ovarian reserve, and the menopausal transition. The candidate proposes a research project that will focus on premenopausal women with early stage breast cancer who develop chemotherapy-induced ovarian failure (CIOF). These women likely would derive more benefit from estrogen deprivation with AI therapy than from tamoxifen, as has been demonstrated for postmenopausal women. However, a substantial percentage is likely to recover ovarian function during AI therapy due to LHRH feedback loops, which would render AI therapy ineffective. The cornerstone of this proposal is a prospective clinical trial of AI therapy in women with CIOF. The overall goal is to identify clinically applicable genetic, epidemiologic, and biochemical predictors of alterations of ovarian function during AI therapy using research samples and data collected from study participants. We hypothesize that we can predict which women will remain postmenopausal during AI therapy, and which are highly likely to recover ovarian function. The outlined career development program, along with the mentored research proposal for this K07 application, will augment the candidate's knowledge and research skills to enable the successful transition to an independent research career in clinical and translational breast oncology. RELEVANCE: Each year, approximately 20,000 premenopausal breast cancer patients in the U.S. receive chemotherapy and endocrine therapy. Aromatase inhibitor (AI) therapy may be preferable to tamoxifen, but may not be safe in all patients because of the potential for recovery of ovarian function. In this proposal we will identify those patients who can receive AI therapy safely, which will enable more personalized treatment decisions.