Mammographic Density and Metabolic Genotyping for Predicting Cancer Prognosis

用于预测癌症预后的乳房 X 线摄影密度和代谢基因分型

• 批准号: 9376399
• 负责人: Jeon-Hor Chen
• 金额: $ 20.16万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9376399
• 关键词: Adjuvant; Adverse effects; Affect; Affinity; Alleles; Antineoplastic Protocols; Archives; Area; Aromatase Inhibitors; Biological Markers; Blood; Blood specimen; Breast; Breast Cancer Patient; CYP2D6 gene; Cancer Prognosis; Caring; Cessation of life; Chemoprevention; Chinese People; Confounding Factors (Epidemiology); Consent; Contralateral; Cytochrome P450; Data; Databases; Development; Diagnosis; Diagnostic; Disease; Disease-Free Survival; Distant Metastasis; Ensure; Enzymes; Estrogen Antagonists; Estrogen Receptors; Failure; Formalin; General Hospitals; Genes; Genetic Status; Genotype; Goals; High Risk Woman; Hormonal; Hospitals; Image; Individual; Institution; Koreans; Magnetic Resonance Imaging; Malignant Neoplasms; Mammographic Density; Mammography; Measures; Mediating; Metabolic; Metabolism; Methods; Monitor; Newly Diagnosed; Odds Ratio; Operative Surgical Procedures; Paraffin Embedding; Patient Care; Patients; Perimenopause; Persons; Pharmaceutical Preparations; Postmenopause; Premenopause; Prognostic Factor; Progressive Disease; Prospective Studies; Radiation; Recording of previous events; Recurrence; Registries; Research; Resolution; Resources; Risk; Risk Factors; Role; Staging; Subgroup; Surrogate Markers; Sweden; TNM; Taiwan; Tamoxifen; Tissues; Treatment Efficacy; Treatment Protocols; Treatment outcome; Veterans; Visit; Woman; XCL1 gene; base; breast density; cancer recurrence; cancer risk; chemotherapy; cohort; cost; density; design; follow-up; genetic analysis; genetic variant; hormone therapy; improved; inclusion criteria; individual patient; interest; malignant breast neoplasm; melting; molecular marker; outcome forecast; prognostic; prognostic value; randomized placebo controlled trial; receptor; response; standard of care; success

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.

抽象的 标题：用于预测癌症预后的乳房X光密度和代谢基因分型 该项目将研究定量乳腺 X 光密度 (MD) 和细胞色素 P450 的作用 CYP2D6 代谢基因分型在乳腺癌 (BC) 患者预后中的应用，最终目标 使用它们作为预后预测因子，以改善可以为每个人提供的治疗 病人。乳房 X 光密度是发生乳腺癌的既定危险因素，而且还有 有证据表明，致密组织区域产生的癌症更具侵袭性；因此集体地 他们认为 MD 可以作为预后预测因子。在这个项目中，我们将利用一个单一机构，全 使用类似策略在一家医院接受治疗的中国患者队列（台中退伍军人总医院） 台湾医院）。他们的乳房护理中心建立了详细的登记册，每个患者的 个人因素、TNM 分期、分子生物标志物、影像学结果和治疗方案（手术、 放射、化疗和激素疗法）都在数据库中有详细记录。患者患有 新诊断的 I、II 和 III 期浸润性乳腺癌将从登记中确定为纳入对象 标准。大多数患者在同一家医院继续接受随访，因此很容易 查找他们的预后信息，包括复发情况、继发性 BC、远处转移 和 BC 特有的死亡。该注册表为调查 MD 与 患者的预后（Aim-1）。对于诊断为激素受体阳性 BC 的患者，其标准是 照顾他们进行荷尔蒙治疗，例如他莫昔芬适用于绝经前和围绝经期妇女。虽然 治疗已被证明对于提高无病生存率和总生存率非常有效 根据统计，许多患者仍然出现进展性疾病，这就提出了个体化问题 反应能力。激素治疗药物会产生各种副作用；因此有很强的 有兴趣寻找可以预测每个患者反应性的生物标志物，以确保 有利的收益风险比。 MD 减少已被证明是预测的有效替代标记 他莫昔芬的反应，了解为什么有些女性会做出反应，这将是非常有趣的 显示 MD 减少，但其他人则没有。 Aim-2 旨在根据以下因素预测他莫昔芬治疗效果： MD 减少和 CYP2D6 基因分型已知会影响他莫昔芬代谢为活性药物 对雌激素受体具有高亲和力的化合物。患者亲自返回医院 后续将受邀提供血样进行CYP2D6基因分型，采用新方法 基于高分辨率熔解曲线分析 (HRM)，该分析已在中国女性中得到验证 并被证明是高效且低成本的。根据基因等位基因，患者将被确定为广泛性 代谢者或中间代谢者。 CYP2D6代谢状态将与MD相关 减少，然后两者都与预后相关。此外，他们将联合起来调查是否 可以添加这两个因素来改善预后的预测。