Metabolomics: Novel Strategies to Improve Breast Cancer Radiotherapy Responses

代谢组学：改善乳腺癌放射治疗反应的新策略

基本信息

批准号：
9810248
负责人：
Jennifer J Hu
金额：
$ 23.37万
依托单位：
UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2021-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9810248
关键词：
Acute Address Adjuvant Radiotherapy Adverse reactions African American Alanine American Area Aspartate Benefits and Risks Bioinformatics Biological Markers Breast Breast Cancer Patient Breast Cancer survivor Cancer Etiology Cancer Survivor Cessation of life Characteristics Clinic Clinical Clinical Data Computational Biology Cosmetics DNA Repair Data Development Discipline Edema Epidemiologist Funding Genomics Glutamate Metabolism Pathway Glutaminase Goals Health Services Research Hispanics Individual Industry Inflammatory Interdisciplinary Study Intervention Knowledge Late Effects Logistic Regressions Metabolic Metabolic Pathway Minority Modeling Molecular Genetics Normal tissue morphology Not Hispanic or Latino Outcome Pain Parents Pathway interactions Patients Performance Population Positioning Attribute Postoperative Period Precision therapeutics Process Progression-Free Survivals Proteomics Quality of life Radiation Radiation Oncologist Radiation Tolerance Radiation therapy Reaction Receiver Operating Characteristics Recurrence Research Research Project Grants Resources Risk Sampling Skin Technology Testing Toxic effect Underserved Population United States National Institutes of Health Urine Validation Woman base biomarker-driven breast cancer survival breast lumpectomy cancer biomarkers cancer diagnosis cancer health disparity cancer radiation therapy clinical application clinical practice drug metabolism effective intervention evidence base experience high risk high risk population improved indexing inhibitor/antagonist innovation inter-individual variation malignant breast neoplasm metabolomics multidisciplinary novel novel strategies personalized intervention predictive modeling prevent racial and ethnic response side effect study population tool transcriptomics treatment strategy tumor tumor metabolism underserved minority

项目摘要

PROJECT SUMMARY/ABSTRACT Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death in American women. Lumpectomy followed by radiotherapy (RT) has significantly improved survival. However, about 42%-47% of patients develop worse early adverse skin reactions (EASRs), pain, breast edema and poor cosmetic results that impact quality of life. Inter-individual variability in the development of RT-induced adverse reactions in normal tissue is well-documented for both acute and late effects. African-American (AA) and underserved populations are less likely than Whites to receive the recommended adjuvant RT, if treated, have a higher risk for developing RT-related side effects and worse clinical outcome. To achieve our long-term goals in improving quality of life, clinical outcome, and overcoming breast cancer disparities, we will use a metabolomics approach to test prediction models for RT-induced EASRs/pain in three racial/ethnic populations. We will test a new paradigm that multiple metabolites/pathways contribute to radiation sensitivity that may predict RT-induced EASRs/pain. Investigating this new paradigm will develop powerful tools in identifying high- risk populations and targets for precision intervention and treatment. Aim 1 will evaluate global metabolomics - driven prediction models of RT-induced EASRs/pain. Aim 2 will quantitate and validate significant metabolites and pathways from Aim 1 in predicting RT-induced EASRs/pain. Aim 3 will develop and assess the performance of comprehensive model (i.e., metabolomics/pathways from Aim 2, patient characteristics, and clinical variables) in predicting RT-induced EASRs/pain. Our preliminary data showed that the alanine, aspartate and glutamate metabolism pathway may contribute to RT-induced EASRs/pain. Thus, targeting tumor metabolism by glutaminase inhibitors may prevent RT-induced EASRs/pain in addition to their anti-tumor activities. Capitalizing on existing urine samples and clinical data from a large tri-racial/ethnic breast cancer population to target 480 patients (67% minorities), promising pilot data, state-of-the-art metabolomics technologies, innovative bioinformatics approach, and skilled multidisciplinary team, we are in an exceptional position to carry out the proposed research. To the best of our knowledge, this is the first metabolomics study of RT-induced EASRs/pain in breast cancer. Using a hypothesis-driven approach, the outcomes will significantly improve the accuracy of urgently needed prediction models of RT-induced EASRs/pain in breast cancer. The outcomes of the proposed research will advance our scientific knowledge in the accurate assessment of RT outcomes and targeted intervention. They also may enable the development of benefit-risk indices that will aid in the decision and planning of RT. The outcome will target effective intervention and treatment strategies, and ultimately improve the quality of life and progression-free survival in breast cancer patients, particularly in underserved minorities with worse RT-induced EASRs/pain and clinical outcome.

项目摘要/摘要乳腺癌是最常见的癌症，也是癌症死亡的第二大原因美国妇女。乳房切除术后进行放疗（RT）的生存率显着提高。然而，大约42％-47％的患者出现较差的早期不良皮肤反应（EASR），疼痛，乳腺水肿和差影响生活质量的美容结果。 RT引起的不良发展的个体间变异性正常组织中的反应均有充分记录在急性和晚期作用方面。非裔美国人（AA）和服务不足的人群比白人接受建议的辅助RT（如果接受治疗）的可能性较小发展与RT相关的副作用和临床结果较差的风险更高。实现我们的长期目标在改善生活质量，临床结局和克服乳腺癌差异方面，我们将使用在三个种族/族裔人群中，用于测试RT诱导的EASRS/疼痛的预测模型的代谢组学方法。我们将测试一个新的范式，即多种代谢物/途径有助于辐射灵敏度预测RT诱导的EASRS/疼痛。调查这一新范式将开发出强大的工具，以确定高级风险人群和目标进行精确干预和治疗。 AIM 1将评估全球代谢组学 - RT引起的EASRS/疼痛的驱动预测模型。 AIM 2将定量并验证大量代谢物和AIM 1的途径预测RT诱导的EASRS/疼痛。 AIM 3将发展和评估性能综合模型（即AIM 2的代谢组学/途径，患者特征和临床变量）在预测RT诱导的EASRS/疼痛时。我们的初步数据表明丙氨酸，天冬氨酸和谷氨酸代谢途径可能有助于RT诱导的EASRS/疼痛。因此，通过谷氨酰胺酶抑制剂除了抗肿瘤活性外，还可以防止RT诱导的EASRS/疼痛。大写关于现有的尿液样本和来自大型三种族/种族乳腺癌人群的临床数据，以480 患者（67％的少数民族），有希望的试验数据，最先进的代谢组学技术，创新生物信息学方法和熟练的多学科团队，我们处于非凡的位置拟议的研究。据我们所知，这是RT引起的EASRS/疼痛的首次代谢组学研究在乳腺癌中。使用假设驱动的方法，结果将显着提高急需RT诱导的EASR/乳腺癌疼痛的预测模型。提议的结果研究将在对RT结果的准确评估中提高我们的科学知识并针对性干涉。它们还可以实现福利风险指数的发展，这将有助于决策和 RT计划。结果将针对有效的干预和治疗策略，并最终提高乳腺癌患者的生活质量和无进展生存的质量，尤其是服务不足的少数民族较差，RT引起的EASRS/疼痛和临床结果。