Pharmacogenomics of the chemotherapeutic agent paclitaxel

描述（由申请人提供）：化疗药物基因组学研究的长期目标是使用遗传信息来识别具有特定药物诱导毒性风险的癌症患者，并相应地调整或改变其治疗。该建议的目标是发现和功能验证预测化疗剂紫杉醇的治疗结果的遗传标记。紫杉醇是一种微管稳定化疗药物，常用于治疗乳腺癌、卵巢癌和非小细胞肺癌，但个体间的耐药性和毒性限制了成功的结果。常见的紫杉醇诱导的毒性包括外周感觉神经病变和肾毒性，导致约20%的患者停止治疗。药物反应的变化可能取决于多种基因产物和环境因素变化的综合效应。通过使用经典的基于SNP的全基因组关联（GWA）方法，在受控环境下在淋巴母细胞系（LCL）中研究了紫杉醇诱导细胞毒性的遗传学。初步分析表明，来自紫杉醇诱导的周围神经病变临床试验的最高SNP富集了与LCL中紫杉醇诱导的细胞毒性相关的SNP，从而证实了LCL模型在分析患者紫杉醇反应相关基因中的作用。来自初步分析的重叠SNP位于RFX 2的内含子中。通过siRNA降低该基因的表达导致NS-1细胞对紫杉醇的敏感性增加，通过减少的神经突生长和增加的细胞毒性来测量，在功能上验证RFX 2参与紫杉醇敏感性。虽然这种方法成功地识别了一个重要的基因，但我们的计划是进行基于基因的GWA研究，因为我们意识到，使用传统的基于SNP的GWA方法可能无法检测到一些相关的遗传变异。一种新的基于基因的方法来检测小效应的变异，结合表达数量性状基因座（eQTL），罕见和常见的编码变异，和其他功能信息，将增加功率在基因水平的测试与紫杉醇敏感性。该研究员和研究团队还计划将基于基因的LCL结果与临床研究的结果进行比较。重叠的基因将成为功能测试的优秀候选人 在周围神经病变的细胞模型中。将在NS-1模型中测试在计算分析中鉴定的其他基因。因此，除了鉴定有助于紫杉醇诱导表型变化的新标记物外，这些实验将增强对紫杉醇反应机制的理解。这项工作将提供一个框架，选择SNP和基因，来自LCL GWA研究，在未来的临床研究中询问。通过完成本提案的目标，该研究员将获得人类遗传学和分子生物学方面的经验，同时为转化癌症研究领域做出贡献。 公共卫生相关性：紫杉醇是一种常用于治疗乳腺癌、卵巢癌和肺癌的化疗药物，但个体间的毒性差异限制了成功的结果。如果医生能够预测哪些患者更有可能出现这些严重的副作用，那么就可以规定更低的剂量或替代治疗。这项研究的目的是发现和验证预测紫杉醇反应的遗传标记，以改善癌症患者的预后。

DESCRIPTION (provided by applicant): The long-term goal of chemotherapeutic pharmacogenomics research is to use genetic information to identify cancer patients at risk of particular drug-induced toxicities and adjust or alter their treatment accordingly. The goal of thi proposal is to discover and functionally validate genetic markers that predict treatment outcomes of the chemotherapeutic agent paclitaxel. Paclitaxel is a microtubule-stabilizing chemotherapy drug often used in the treatment of breast, ovarian and non-small-cell lung cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Common paclitaxel-induced toxicities include peripheral sensory neuropathy and nephrotoxicity, which lead to discontinuation of therapy in approximately 20% of patients. Variation in drug response is likely to be dependent on the combined effects of variation in multiple gene products and environmental factors. By using a classic SNP-based genome-wide association (GWA) approach, the genetics of paclitaxel-induced cytotoxicity has been investigated in lymphoblastoid cell lines (LCLs) under a controlled environment. A preliminary analysis has shown that the top SNPs from a clinical trial of paclitaxel-induced peripheral neuropathy are enriched for SNPs associated with paclitaxel-induced cytotoxicity in LCLs, thus confirming a role for the LCL model in the analysis of genes involved in patient paclitaxel response. An overlap SNP from the preliminary analysis is located in an intron of RFX2. Decreased expression of this gene by siRNA resulted in increased sensitivity of NS-1 cells to paclitaxel measured by reduced neurite outgrowth and increased cytotoxicity, functionally validating the involvement of RFX2 in paclitaxel sensitivity. Although this approach was successful in identifying an important gene, our plan is to perform gene-based GWA studies because we realize that some of the associated genetic variants may not be detectable using a traditional SNP-based GWA approach. A novel gene-based approach to detect variants of small effect working together that incorporates expression quantitative trait loci (eQTLs), rare and common coding variants, and other functional information will increase power in a gene-level test for association with paclitaxel sensitivity. The fellow and research team also plan to compare the gene-based LCL results to those from clinical studies. Genes that overlap will make excellent candidates to test functionally in cell models of peripheral neuropathy. Additional genes identified in the computational analyses will be tested in the NS-1 model. Thus, in addition to identifying novel markers that contribute to variation in paclitaxel-induced phenotypes, these experiments will enhance understanding of the mechanisms involved in paclitaxel response. This work will provide a framework for choosing SNPs and genes that come from LCL GWA studies to interrogate in future clinical studies. By completing the aims of this proposal, the fellow will gain experience i human genetics and molecular biology while contributing to the field of translational cancer research. PUBLIC HEALTH RELEVANCE: Paclitaxel is a chemotherapy drug often used in the treatment of breast, ovarian and lung cancers, yet variable toxicities among individuals limit successful outcomes. If physicians could predict which patients are more likely to experience these severe side effects, lower doses or alternative treatments could be prescribed. The goal of this research is to discover and validate genetic markers that predict response to paclitaxel in order to improve outcomes for cancer patients.