Development of an Integrated Risk Prediction Model of Taxane-induced Peripheral Neuropathy

摘要 几种抗癌药物会引起一种称为周围神经病变的副作用，这种副作用可以永久性地减轻 患者的功能能力和生活质量。因为没有有效的策略来预防或治疗 周围神经病，临床实践指南建议停止或减少剂量化疗， 这会降低患者的存活率。临床和生活方式因素不能充分预测紫杉烷诱发的风险 周围神经病(TIPN)。因此，迫切需要验证其临床实用性和机械性。 信息性预测TIPN生物标记物，以开发有效的TIPN预防策略，以改善 紫杉烷治疗结果。营养失调，包括维生素D、组氨酸和鞘磷脂，以及 与遗传性神经病相关的基因变异已被确定为 TIPN。要确认这些候选生物标记物是TIPN风险的预测因素，需要大量的紫杉烷- 使用生物显微镜和详细的TIPN数据治疗的患者。这项建议的首要目标是 确定临床有用和机制信息丰富的TIPN生物标记物，开发综合TIPN风险 可以预测单个患者的TIPN风险的预测模型。我们将扩展SWOG 1714的价值 (S1714)，这是一项由NCI资助的大型(n=1,336)前瞻性临床研究，收集了生物有机磷和 创建临床TIPN预测模型所需的详细TIPN数据。我们的中心假设是我们的生理 (例如，维生素D、组氨酸、鞘磷脂)和遗传(例如，EPHA5)生物标记物候选是预测TIPN 生物标志物，并将丰富临床TIPN预测模型。我们将有针对性地全面开展 S1714生物样本的“组学”分析以验证临床应用和机制信息预测 TIPN生物标志物，并开发综合TIPN风险预测模型，以完成以下具体工作 目的：目的1：评估关键营养素和血脂对TIPN风险的预测价值。目标2：确定 导致TIPN风险的遗传特征。目的3：建立一个完整的TIPN预测模型。这个 这项研究的主要预期结果是：1)确认临床上有用的预测性TIPN 生物标志物，2)促进TIPN的机制过程的新知识，以及3) 创建一个综合的TIPN预测模型。这些结果将为开发小说提供关键的见解 研究小组可以在前瞻性临床试验中测试的药物和生物标记物信息治疗策略 防止TIPN。如果成功，这些策略可以转化为临床实践，以预防TIPN和 改善接受紫杉烷治疗的近100万癌症患者的长期临床结果 每年在美国接受治疗。

Abstract Several anticancer agents cause a side effect known as peripheral neuropathy that can permanently diminish patient’s functional ability and quality of life. Since there are no effective strategies to prevent or treat peripheral neuropathy, clinical practice guidelines recommend withholding or dose-reducing chemotherapy, which reduces patient survival. Clinical and lifestyle factors do not adequately predict risk of taxane-induced peripheral neuropathy (TIPN). Therefore, there is a critical need to validate clinically useful and mechanistically informative predictive TIPN biomarkers in order to develop effective TIPN prevention strategies that improve taxane treatment outcomes. Dysregulation of nutrients including vitamin D, histidine, and sphingomyelin, and variants in genes linked to hereditary neuropathy conditions, have been identified as candidate biomarkers of TIPN. Confirming these biomarker candidates as predictors of TIPN risk requires a large cohort of taxane- treated patients with biospecimens and detailed TIPN data. The overarching objective of this proposal is to identify clinically-useful and mechanistically-informative TIPN biomarkers and develop an Integrated TIPN Risk Prediction Model that can predict an individual patient’s TIPN risk. We will extend the value of SWOG 1714 (S1714), which is a large (n=1,336) NCI-funded prospective clinical study that collected biospecimens and detailed TIPN data to create a Clinical TIPN Prediction Model. Our central hypothesis is that our physiologic (e.g., vitamin D, histidine, sphingomyelin) and genetic (e.g., EPHA5) biomarker candidates are predictive TIPN biomarkers and will enrich the Clinical TIPN Prediction Model. We will conduct targeted and comprehensive “omics” analyses of S1714 biospecimens to validate clinically useful and mechanistically informative predictive TIPN biomarkers and develop an Integrated TIPN Risk Prediction Model to complete the following specific aims: Aim 1: Assess the predictive value of key nutrients and lipids on TIPN risk. Aim 2: Determine genetic features that contribute to TIPN risk. Aim 3: Develop an Integrated TIPN Prediction Model. The primary expected outcomes of this research are the: 1) confirmation of clinically useful predictive TIPN biomarkers, 2) generation of new knowledge of the mechanistic processes that contribute to TIPN, and 3) creation of an Integrated TIPN Prediction Model. These outcomes will provide critical insight to develop novel agents and biomarker-informed treatment strategies that the study team can test in prospective clinical trials to prevent TIPN. If successful, these strategies could be translated into clinical practice to prevent TIPN and improve long-term clinical outcomes in the nearly one million patients with cancer who receive taxane treatment each year in the United States.