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 肌肉骨骼疼痛（MP）是身体残疾的主要原因，可由以下因素引发或加剧： 全身性癌症治疗，如化疗（例如，紫杉烷为基础），内分泌治疗（芳香化酶 抑制剂[AI]）和免疫疗法（检查点抑制剂）。MP在女性中尤其常见， 人工智能疗法，通常为激素敏感的绝经后女性开5-10年的处方 乳腺癌高达85%的AI患者会出现MP（包括关节痛、肌痛和关节/肌肉僵硬） 使用者，并且是高治疗中止率（高达73%）的头号贡献者。而 虽然已经提出了用AI治疗来管理MP的策略，但仍然没有一致有效的方法。 预防或管理问题的干预措施，在很大程度上是因为MP的表型还没有得到解决。 MP的特点和机制尚未明确阐明。旨在更好 为了表征MP的表型并更好地理解MP的机制，我们提出 一系列的研究。这些研究的中心假设是AI治疗对表型的影响 深部组织和中枢神经系统中MP和MP相关改变的发生受到多种因素的调节， 遗传变异本论文项目（F99研究）将研究长- 使用生物行为框架的MP与AI治疗乳腺癌的长期轨迹（18个月）。间- 将检查MP的个体变异性及其相关的表型和环境因素。协会 MP的个体间变异性与基因型因素（雌激素相关基因的DNA变异）之间的关系 生物合成，AI代谢，炎症和肌肉骨骼疾病）将被探索。在博士后 项目（K 00研究），成像技术将被纳入作为一个全新的透镜，以描述表型 MP及其在深部组织（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、结构性关节/肌肉病理以及结构和功能之间的关系 大脑的改变将首先在乳腺癌幸存者中进行描述和探索。拟议 F99/K 00培训和研究旨在建立一个独特的模型，将组学，成像和 行为数据，以提供更深入的了解MP的表型和机制，并作为基础 用于AI治疗和个体化干预的发展预测MP。

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.