Prediction of Response to Revlimid

描述（由申请人提供）：骨髓增生异常综合征（MDS）是一组异质性骨髓干细胞疾病，没有单一的治疗策略具有普遍的益处。最近FDA已经批准了几种治疗MDS的药物，但除了del（5q）核型患者亚组外，很难知道哪种治疗方案可能对个体患者有最大的益处。所有的药物都有可能对病人有害的副作用；因此，了解哪种药物可能改善单个患者的细胞减少症是非常可取的。基因表达谱已被用于将患者分为生物学上相似的亚组。我们假设具有相似的自然病史和对特定药物治疗的反应的患者可能共享区分反应者和无反应者的表达谱。使用这项技术，我们比较了对来那度胺有反应的患者和对来那度胺没有反应的患者的基因表达谱，并确定了与反应相关的独特特征。对来那度胺的应答者与红细胞分化相关的基因表达不足，提示产生成熟红细胞的能力存在缺陷。然后，我们在一组独立的患者中验证了这种表达特征。有缺陷的红细胞特征可用于预测对来那度胺的敏感性（通过计算的z分数量化），为临床观察提供了分子验证，即该药物特异性地改善MDS患者的贫血。在目前的拨款中，我们建议进一步研究利用红细胞表达特征预测患者反应的能力。我们将对非del（5q）输血依赖的低/Int-1 MDS患者进行单药来那度胺治疗的前瞻性试验。微阵列和luminex检测的表达谱分析将在治疗前的骨髓中进行，并与临床反应相关。如果有必要，将有可能用获得的数据来完善签名和z分数的边界。额外的患者数量将能够生成接受者操作特征曲线，该曲线测量信号如何区分应答者和非应答者，并给出应答的概率。这项研究的结果可能提供一种临床工具，可用于预先选择可能对药物有反应的患者，从而使其他人免于不良的毒性暴露。公共卫生相关性：骨髓增生异常综合征（MDS）是一种主要发生于老年人的克隆性骨髓衰竭疾病，其治疗仍然是临床医生面临的一个挑战。目前FDA批准的治疗这种疾病的药物只有3种。来那度胺（lenalidomide）对存在染色体异常的MDS的特定亚型非常有效。此外，该药物对其他约25%的MDS患者有有益作用。挑战在于在接受来那度胺治疗之前确定那些有很大可能产生反应的患者，来那度胺治疗会产生严重的副作用。使用治疗前骨髓抽吸的基因表达谱，我们已经确定了一个基因表达谱，可以识别26名患者的应答者和无应答者。在本提案中，我们将筛选不携带染色体异常的MDS患者（即有1:4的药物反应机会），看看我们已经确定的表达谱是否可以准确预测反应。此外，我们将测试一种更具成本效益和更简单的可用于临床的检测方法的功效。

DESCRIPTION (provided by applicant): Myelodysplastic syndromes (MDS) constitute a group of heterogeneous bone marrow stem cell disorders where no single treatment strategy has been of universal benefit. Several drugs have recently been approved by the FDA for MDS, but except for the subgroup of patients with a del(5q) karyotype, it is difficult to know which of the therapeutic options are likely to be of greatest benefit to the individual patient. All of the drugs have side effects that can be deleterious to the patient; knowing which drug is likely to improve the cytopenia(s) of the individual patient would thus be highly desirable. Gene expression profiling has been used to stratify patients into biologically similar subgroups. We hypothesized that patients with a similar natural history and response to a specific drug therapy may share an expression profile that distinguishes between responders and non- responders. Using this technology, we compared gene expression profiles of patients who responded to lenalidomide to those who did not, and identified a unique signature associated with response. Responders to lenalidomide under-expressed genes associated with erythroid differentiation, suggesting a defect in the ability to produce mature erythrocytes. We then validated this expression signature in an independent group of patients. The defective erythroid signature could be used to predict sensitivity to lenalidomide (quantified by a calculated z-score), providing a molecular validation of the clinical observation that this drug specifically benefits anemia in MDS patients. In the current grant, we propose to further investigate the ability to predict patient response using the erythroid expression signature. We will conduct a prospective trial of non-del(5q) transfusion dependant low/Int-1 MDS patient treated with single agent lenalidomide. Expression profiling by both microarray and luminex assay will be performed on the pre-treatment marrow and correlated with clinical response. If necessary, it will be possible to refine both the signature and the boundaries of the z-score with the data obtained. The additional patient numbers will enable the generation of a receiver operating characteristic curve that measures how well the signature separates responder from non-responder and gives a probability of response. The results of this study are likely to provide a clinical tool that could be used to pre-select patients likely to respond to the drug thus sparing the others from undesirable toxic exposure. PUBLIC HEALTH RELEVANCE: Treatment of myelodysplastic syndromes (MDS), a clonal bone marrow failure disease primarily of the elderly, remains a challenge to the clinician. There are now only 3 FDA approved drugs for this disease. One drug, lenalidomide, is highly effective for a specific subtype of MDS in which a chromosomal abnormality is present. In addition, the drug can have a beneficial effect in about 25% of other MDS patients. The challenge is to identify those patients who have a high probability of response before they receive lenalidomide therapy, which have cause serious side effects. Using gene expression profiling of pre-treatment bone marrow aspirates, we have identified a gene expression profile that identifies responders from non-responders in 26 patients. In this proposal we will screen MDS patients who do not carry the chromosomal abnormality (i.e. have a 1:4 chance of responding to the drug) to see whether the expression profile that we have identified can accurately predict response. In addition we will test the efficacy of a more cost-effect and less complex assay the can be used in the clinic.