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Multi-Omic Biomarkers for Neuropathic Pain Secondary to Chemotherapy

化疗继发神经病理性疼痛的多组学生物标志物

基本信息

批准号：
10709410
负责人：
JOSEPH F FOSS
金额：
$ 163.6万
依托单位：
CLEVELAND CLINIC LERNER COM-CWRU
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-30 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10709410
关键词：
Multi Omic Biomarkers Neuropathic Pain

项目摘要

PROJECT SUMMARY Taxanes are among the most efficacious chemotherapeutic agents and are frequently used in the treatment of early stage and metastatic breast cancer, but are known to produce a pain condition known as chemotherapy- induced peripheral neuropathic pain (CIPNP). CIPNP is one of the primary dose-limiting toxicities of taxane administration. No diagnostic tool exists to identify patients that will develop CIPNP in response to taxane therapy. To address this unmet clinical need, this proposal seeks to develop biomarker signatures associated with taxane-induced neuropathic pain to 1) identify patients at risk for developing debilitating taxane neuropathic pain before chemotherapy is initiated and 2) to identify patients on treatment that are at risk of developing neuropathic pain and need dose adjustments to prevent the onset of symptoms. Our long-term goal is to identify biomarker signatures that can identify patients at high risk of developing taxane-induced CIPNP to enable personalized dose adjustments to minimize CIPNP and optimize therapeutic outcomes. During the R61 phase, we will perform genome-wide, epigenome-wide, miRNome-wide, and untargeted metabolome-wide associations of the 11-point pain-intensity Numerical Rating Scale (NRS), Chemotherapy-induced peripheral neuropathy 20- item (CIPN20), the Pain Catastrophizing Scale (PCS), and Patient Reported Outcome Measurement System (PROMIS) scores for physical function, anxiety, depression, and pain interference to identify novel biomarkers associated with identifiable phenotypes (Aim 1A). Next, we will test panels of candidate mRNA and cytokine biomarkers for their association with NRS, CIPN20, PCS, and PROMIS scores (Aim 1B). An added strength of this study is that by collecting samples before, during, and after taxane treatment we will be able to compare those patients who develop CIPNP to those that remain pain free, providing a better understanding of the molecular mechanism predisposing a patient to developing neuropathic pain. R61 milestones include developing biomarker signatures that identify patients at risk of developing neuropathic pain that compromise quality of life (i) before taxane therapy is started and (ii) over the time course of taxane therapy. One rationale is that some patients will have a detectable biomarker profile suggesting a high likelihood of long term (i.e., greater than 1 year) neuropathic pain and a need to either avoid or reduce taxane doses. A second rationale is that some patients may not have a biomarker signature indicating an adverse response to taxane therapy at baseline, but develop one through the course of taxane therapy. This biomarker signature will be used to detect these susceptible patients early and personalize their taxane therapy to minimize CIPNP. In the R33 phase (Aim 2), we will use machine learning to develop and validate algorithms using biomarker signatures from associations with phenotypic changes from Aim 1 (A and B) to predict individuals at risk of developing CIPNP and to identify patients who are at risk of developing an adverse profile as taxane therapy is administered.

项目总结紫杉烷是最有效的化疗药物之一，经常用于治疗早期和转移性乳腺癌，但已知会产生一种称为化疗的疼痛状况- 诱导周围神经病理性疼痛(CIPNP)。CIPNP是紫杉烷的主要剂量限制毒性之一。行政管理。目前还没有诊断工具来识别紫杉烷引起CIPNP的患者心理治疗。为了解决这一未得到满足的临床需求，这项提议寻求开发与通过紫杉烷诱导的神经病理性疼痛1)确定有可能发展为衰弱的紫杉烷神经病理性疼痛的患者化疗开始前的疼痛和2)识别治疗中有发展风险的患者神经病理性疼痛，需要调整剂量以防止症状的出现。我们的长期目标是确定生物标志物签名，可以识别发生紫杉烷诱导CIPNP的高危患者，以使个性化的剂量调整，以最大限度地减少CIPNP，优化治疗结果。在R61阶段期间，我们将执行基因组范围、表观基因组范围、miRNome范围和非靶向代谢组范围的关联在11点疼痛强度数字评定量表(NRS)中，化疗引起的周围神经病变20- 项目(CIPN20)、疼痛灾变量表(PCS)和患者报告结果测量系统 (PROMIS)身体功能、焦虑、抑郁和疼痛干扰的评分，以确定新的生物标记物与可识别的表型相关(目标1A)。接下来，我们将测试候选信使核糖核酸和细胞因子的面板生物标记物与NRS、CIPN20、PCS和PROMIS分数的关联(目标1B)。一个额外的力量这项研究是通过在紫杉烷治疗之前、期间和之后收集样本，我们将能够比较那些发展成CIPNP的患者到那些保持无痛状态的患者，提供了更好的理解导致患者发生神经病理性疼痛的分子机制。R61的里程碑包括开发识别有患神经病理性疼痛风险的患者的生物标记物特征 (I)在紫杉烷治疗开始之前，以及(Ii)在紫杉烷治疗的整个过程中。其中一个理由是，有些人患者将有一个可检测的生物标志物档案，表明长期(即大于1)的可能性很高年)神经性疼痛，以及需要避免或减少紫杉烷剂量。第二个理由是，有些人患者可能没有生物标记物标记，表明基线时对紫杉烷治疗的不良反应，但在紫杉烷治疗过程中发展出一种。这个生物标志物签名将被用来检测这些易感患者及早进行个体化紫杉烷治疗，将CIPNP降至最低。在R33阶段(目标2)，我们将使用机器学习来开发和验证使用来自关联的生物标记物签名的算法根据目标1(A和B)的表型变化来预测患CIPNP的风险个体并识别接受紫杉烷治疗时有出现不良症状的风险的患者。