Musculoskeletal Pain Among Breast Cancer Survivors: Through Bio-behavioral and Imaging Lenses

乳腺癌幸存者的肌肉骨骼疼痛：通过生物行为和成像镜头

• 批准号: 10675521
• 负责人: Yehui Zhu
• 金额: $ 10.56万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10675521
• 关键词: Address; Age; Anabolism; Aromatase; Aromatase Inhibitors; Arthralgia; Behavioral; Biological; Brain; Breast Cancer survivor; Brief Pain Inventory; Central Nervous System; Characteristics; DNA; Data; Development; Disease; Distress; Education; Estrogens; Functional Magnetic Resonance Imaging; Future; Genes; Genetic; Genotype; Hormones; Image; Imaging Techniques; Immune checkpoint inhibitor; Immunotherapy; Individual; Inflammation; Intervention; Joints; Longitudinal Studies; Malignant Neoplasms; Measures; Metabolism; Modeling; Muscle; Musculoskeletal Diseases; Musculoskeletal Pain; Musculoskeletal System; Myalgia; Osteoblasts; Pathology; Pathway Analysis; Patient Self-Report; Pattern; Phenotype; Population; Postdoctoral Fellow; Postmenopause; Research; Review Literature; Role; Sampling; Symptoms; Time; Tissues; Training; Variant; Woman; anastrozole; biobehavior; bone; cancer therapy; chemotherapy; cohort; contextual factors; effective intervention; experience; high risk population; hormone therapy; inhibitor therapy; insight; inter-individual variation; lens; malignant breast neoplasm; muscle stiffness; physically handicapped; prevent; protective effect; taxane

Musculoskeletal Pain among Breast Cancer Survivors: Through Bio-behavioral and Imaging Lenses Musculoskeletal pain (MP) is a leading cause of physical disability and can be triggered or exacerbated by systemic cancer treatments, such as chemotherapy (e.g., taxane-based), endocrine therapy (aromatase inhibitors [AIs]), and immunotherapy (checkpoint inhibitors). MP is particularly common among women taking AI therapy, which is generally prescribed for 5-10 years for postmenopausal women with hormone-sensitive breast cancer. MP (including arthralgias, myalgia, and joint/muscle stiffness) is experienced by up to 85% of AI users, and is the number one contributor to the high treatment discontinuation rate (up to 73%). While strategies have been proposed to manage MP with AI therapy, there are still no consistently effective interventions to prevent or manage the problem, due in large part because the phenotype of MP has not been well-characterized and the mechanisms underlying MP have not been clearly explicated. Aiming to better characterize the phenotype of MP and gain a greater understanding of mechanism underlying MP, we propose a line of studies. The central hypothesis of these studies is that the influences of AI therapy on the phenotype of MP and MP-related alterations in deep tissues and the central nervous system are moderated by multiple genetic variabilities. The dissertation project (F99 study) will investigate the inter-individual variability of long- term trajectories (18 months) of MP with AI for breast cancer using a biobehavioral framework. The inter- individual variability of MP, and its related phenotypic and contextual factors will be examined. The association between inter-individual variability of MP and genotypic factors (DNA variation in genes related to estrogen biosynthesis, AI metabolism, inflammation, and musculoskeletal disorders) will be explored. In the postdoctoral project (K00 study), imaging techniques will be incorporated as a brand-new lens to describe the phenotype of MP and its related alterations in deep tissues (joints and muscles) and the central nervous system (the brain). The relationship among self-reported MP, structural joints/muscles pathology, and structural and functional alterations in the brain will be first described and explored among breast cancer survivors. The proposed F99/K00 training and studies are aimed at establishing a unique model integrating omics, imaging and behavioral data to provide greater insight into the phenotype and mechanisms of MP, and serve as the basis for predicting MP with AI therapy and development of individualized interventions.

乳腺癌幸存者的肌肉骨骼疼痛：通过生物行为和成像镜头 肌肉骨骼疼痛 (MP) 是导致身体残疾的主要原因，并且可能由以下因素引发或加剧： 全身癌症治疗，例如化疗（例如基于紫杉烷的化疗）、内分泌治疗（芳香酶 抑制剂[AI]）和免疫疗法（检查点抑制剂）。 MP 在服用药物的女性中尤其常见 AI 疗法，对于激素敏感的绝经后女性，通常需要 5-10 年 乳腺癌。高达 85% 的 AI 会经历 MP（包括关节痛、肌痛和关节/肌肉僵硬） 使用者，并且是高治疗中断率（高达 73%）的第一大原因。尽管 已经提出了用 AI 疗法来管理 MP 的策略，但仍然没有一致有效的方法 预防或管理该问题的干预措施，很大程度上是因为 MP 的表型尚未得到解决 MP 的特征和潜在机制尚未明确阐明。力求更好 描述 MP 表型的特征并更好地了解 MP 的潜在机制，我们建议 一系列的研究。这些研究的中心假设是人工智能治疗对表型的影响 深层组织和中枢神经系统中的 MP 和与 MP 相关的改变受到多种因素的调节 遗传变异。论文项目（F99 研究）将调查长期 使用生物行为框架，使用 AI 治疗乳腺癌的 MP 的长期轨迹（18 个月）。间 将检查 MP 的个体变异性及其相关表型和背景因素。协会 MP 的个体差异与基因型因素（雌激素相关基因的 DNA 变异）之间 生物合成、人工智能代谢、炎症和肌肉骨骼疾病）将得到探索。在博士后 项目（K00研究），成像技术将作为一种全新的镜头来描述 MP 及其在深层组织（关节和肌肉）和中枢神经系统（大脑）中的相关变化。 自我报告的 MP、结构关节/肌肉病理学以及结构和功能之间的关系 将首先在乳腺癌幸存者中描述和探索大脑的变化。拟议的 F99/K00培训和研究旨在建立一个集组学、成像和诊断于一体的独特模型 行为数据可以更深入地了解 MP 的表型和机制，并作为基础 用于通过人工智能治疗预测 MP 并开发个性化干预措施。