Mammographic Density and Metabolic Genotyping for Predicting Cancer Prognosis

摘要 标题：乳腺X线密度和代谢基因分型预测癌症预后 本项目将研究定量乳腺摄影密度(MD)和细胞色素P450的作用 CYP2D6代谢基因分型在乳腺癌患者预后中的作用 使用它们作为预测预后的指标，以改善可以提供给每个人的治疗 有耐心的。乳房X光照相密度是患乳腺癌的既定危险因素，还有 有证据表明，致密组织区域产生的癌症更具侵袭性；因此 他们认为MD可以作为预后的预测指标。在这个项目中，我们将利用一个单一的机构，所有- 在一家医院使用类似策略治疗的中国患者队列(台中老兵总医院) 台湾的医院)。他们的乳房护理中心已经建立了详细的登记，每个患者的 个人因素、TNM分期、分子生物标志物、影像表现和治疗方案(手术、 放射治疗、化疗和荷尔蒙治疗)都在数据库中有很好的记录。患有疾病的患者 新诊断的I期、II期和III期浸润性乳腺癌将从登记中确定为纳入 标准。大多数患者在同一家医院继续接受随访，因此很容易 发现他们的预后信息，包括复发、继发性BC、远处转移 和公元前特有的死亡。这一登记处为调查MD与 患者预后(AIM-1)。对于激素受体阳性的BC患者，它是 注意给予他们激素治疗，例如对绝经前和围绝经期妇女使用他莫昔芬。尽管 治疗已被证明在提高无病生存率和总生存率方面非常有效。 统计基础上，许多患者仍发展为进展性疾病，提出了个体化的问题 响应性。激素治疗药物与各种副作用有关；因此有很强的 有兴趣寻找可以预测每个患者反应的生物标记物，以确保 有利的收益风险比。MD约简已被显示为预测的有效替代标记 他莫昔芬的反应，理解为什么一些女性会有反应和 显示MD减少，但其他人没有。AIM-2用于预测他莫昔芬的疗效 MD减少和已知的影响他莫昔芬代谢为活性的CYP2D6基因分型 对雌激素受体有很高亲和力的化合物。病人返回医院接受面谈 将邀请后续人员使用一种新的方法为CYP2D6基因分型提供血液样本 基于高分辨率熔化曲线分析(HRM)，已在中国妇女中得到验证 并被证明是高效和低成本的。根据基因等位基因，患者将被确定为广泛性 代谢物或中间代谢物。CYP2D6代谢状态将与MD相关 减少，然后两者都与预后相关。此外，他们将被联合起来调查是否 这两个因素可以结合起来提高预后的预测。

ABSTRACT Title: Mammographic Density and Metabolic Genotyping for Predicting Cancer Prognosis This project will investigate the role of quantitative mammographic density (MD) and cytochrome P450 CYP2D6 metabolic genotyping in the prognosis of breast cancer (BC) patients, with the ultimate goal of using them as prognostic predictors for improving the treatment that can be provided to each individual patient. Mammographic density is an established risk factor for developing breast cancer, and there is also evidence suggesting that cancers arising from dense tissue area are more aggressive; therefore collectively they suggest MD may serve as a prognostic predictor. In this project we will utilize a single-institution, all- Chinese, patient cohort that is treated in one hospital using similar strategies (Taichung Veteran's General Hospital in Taiwan). Their Breast Care Center has established a detailed registry, and each patient's personal factors, TNM staging, molecular biomarkers, imaging findings, and treatment protocols (surgery, radiation, chemotherapy and hormonal therapy) are all well documented in the database. Patients with newly diagnosed Stage I, II, and III invasive breast cancer will be identified from the registry as the inclusion criteria. The majority of patients are continuingly being followed in the same hospital, so it is very easy to find their prognostic information, including development of recurrence, secondary BC, distant metastasis and BC-specific death. This registry provides a great resource for investigating the association of MD with patients' prognosis (Aim-1). For patients diagnosed with hormonal receptor positive BC, it is the standard of care to give them hormonal therapy, e.g. tamoxifen for pre- and peri-menopausal women. Although the treatment has been shown very effective in improving disease-free survival and overall survival on a statistical basis, many patients still develop progressive disease, raising the question of individual responsiveness. The hormonal therapy drugs are associated with various side effects; thus there is a strong interest to find biomarkers that can predict the responsiveness of each individual patient to ensure a favorable benefit-to-risk ratio. MD reduction has been shown as a valid surrogate marker for predicating tamoxifen response, and it would be very interesting to understand why some women would respond and show MD reduction but others not. Aim-2 was designed to predict tamoxifen treatment efficacy based on MD reduction and the CYP2D6 genotyping that are known to affect the metabolism of tamoxifen to active compounds that have a high affinity for estrogen receptors. Patients returning to hospital for in-person follow-up will be invited to provide blood samples for the CYP2D6 genotyping, by using a new method based on the high-resolution melting curve analysis (HRM), which has been validated in Chinese women and proven to be efficient and low-cost. Based on the gene alleles patients will be determined as extensive metabolizers or intermediate metabolizers. The CYP2D6 metabolic status will be correlated with MD reduction, and then both correlated with prognosis. Further, they will be combined to investigate whether these two factors can be added to improve the prediction of prognosis.