An Investigation of the Molecular Mechanisms for and Prediction of the Severity of Cancer Chemotherapy-Related Fatigue Using a Multi-staged Integrated Omics Approach

癌症相关性疲劳(CRF)是癌症及其治疗中最常见的症状。 中到重度慢性肾功能衰竭对患者耐受治疗的能力以及他们的 生活质量。在一些患者中，CRF非常严重，以至于他们停止了癌症治疗。考虑到它的高 发生和严重的负面影响，必须开发有效的治疗方法 毁灭性的症状。CRF的两个主要知识缺口是缺乏风险预测模型和 对其潜在机制缺乏了解。一个敏感而具体的风险预测模型将有助于 临床医生确定哪些患者最有可能经历高水平的CRF并提供 关于修改活动干预措施(例如，锻炼)的建议。增加了对 慢性肾功能衰竭的机制可以确定治疗干预的潜在靶点。这两方面的知识 这项申请将填补差距。这项研究将使用多种来源的“组学”数据来调查 与慢性肾功能衰竭严重程度相关的分子机制在一份描述良好的肿瘤学样本中的研究 早晚CRF水平低与高的患者(n=1343)。因为这些 患者正在接受化疗(CTX)，我们的研究将调查CTX相关疲劳(CTXRF)。我们会 使用多阶段分析来整合基因表达、遗传和表观遗传学数据。我们会带上 基因表达谱分析中确定的功能候选基因提供基因座的优势 以便在随后的遗传和表观遗传学分析中进行分析。本研究中确定的候选基因和途径 研究将提供有关CTXRF机制的新的和必要的信息，以及潜在的治疗方法 目标。先前的研究表明，患者将在本周经历CTXRF严重程度的增加 在CTX之后。然而，目前还没有预测这一增长幅度的模型。这种无法预测的能力 在随后的CTX周期中CTXRF的严重程度限制了临床医生识别高危患者的能力 并为他们提供管理CTXRF的建议。为了解决这一知识鸿沟，我们建议 使用人口学、临床和组学数据开发预测早晚严重程度的模型 根据患者在CTX治疗前一周的CTXRF资料，患者在CTX治疗一周后所经历的CTXRF 收到这一周期的CTX。这项研究将为能够识别高危患者提供新的见解 以及确定潜在的治疗靶点。该项目将指导开发和临床研究，以 研究CTXRF和其他类型疲劳的其他机制和治疗干预 与癌症及其治疗(如放射治疗、手术)有关。

Cancer-related fatigue (CRF) is the most common symptom associated with cancer and its treatments. Moderate to severe CRF has a negative impact on patients’ ability to tolerate treatments as well as on their quality of life. In some patients, CRF is so severe, that they discontinue cancer treatment. Given its high occurrence and significant negative impact, it is imperative that effective treatments be developed for this devastating symptom. Two of the major knowledge gaps for CRF are a lack of a risk prediction model and a lack of knowledge of its underlying mechanisms. A sensitive and specific risk prediction model would assist clinicians to determine which patients are most likely to experience high levels of CRF and provide recommendations regarding activity modifying interventions (e.g., exercise). Increased knowledge of the mechanisms for CRF could identify potential targets for therapeutic interventions. Both of these knowledge gaps will be addressed in this application. This study will use multiple sources of “omics” data to investigate the molecular mechanisms associated with the severity of CRF in a well characterized sample of oncology patients (n=1343) who are experiencing low versus high levels of morning and evening CRF. Because these patients are undergoing chemotherapy (CTX), our study will investigate CTX-related fatigue (CTXRF). We will use a multi-staged analysis to integrate the gene expression, genetic, and epigenetic data. We will take advantage of the functional candidate genes identified in a gene expression profiling analyses to provide loci for analysis in subsequent genetic and epigenetic analyses. Candidate genes and pathways identified in this study will provide new and needed information on CTXRF mechanisms, as well as potential therapeutic targets. Prior studies suggest that patients will experience an increase in the severity of CTXRF in the week following CTX. However, no models exist to predict the magnitude of this increase. This inability to predict the severity of CTXRF during subsequent cycles of CTX limits the ability of clinicians to identify high-risk patients and provide them with recommendations to manage CTXRF. To address this knowledge gap, we propose to use demographic, clinical, and omics data to develop a model to predict the severity of morning and evening CTXRF experienced by a patient one week following CTX based on their profile for CTXRF in the week prior to the receipt of this cycle of CTX. This study will provide new insights to be able to identify high-risk patients as well as identify potential therapeutic targets. This project will guide the development and clinical studies to investigate additional mechanisms and therapeutic interventions for CTXRF and other types of fatigue associated with cancer and its treatment (e.g., radiation therapy, surgery).