Prediction of Response to Revlimid

描述(由申请人提供)：骨髓增生异常综合征(MDS)构成了一组不同类型的骨髓干细胞疾病，没有单一的治疗策略具有普遍的益处。FDA最近批准了几种治疗MDS的药物，但除了del(5q)核型的患者亚组外，很难知道哪些治疗方案可能对个体患者最有利。所有这些药物都有可能对患者有害的副作用；因此，知道哪种药物可能改善患者的细胞减少症(S)将是非常可取的。基因表达谱已被用来将患者分成生物相似的亚组。我们假设，对特定药物治疗有相似自然病史和反应的患者可能具有区分有效和无反应的表达特征。使用这项技术，我们比较了对来那度胺有反应的患者和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。来那度胺的反应者与红系分化相关的基因表达不足，表明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一表情签名。有缺陷的红系信号可以用来预测对来那度胺的敏感性(通过计算的z分数来量化)，为临床观察提供了分子验证，即该药物特别有利于MDS患者的贫血。在目前的授权中，我们建议进一步研究使用红系表达特征预测患者反应的能力。我们将对单用来那度胺治疗的非del(5q)输血依赖的Low/Int-1 MDS患者进行前瞻性试验。将对治疗前的骨髓进行微阵列和Luminex分析的表达谱分析，并与临床反应相关。如有必要，可以使用所获得的数据来改进z分数的签名和边界。额外的患者编号将能够生成接收器操作特征曲线，该曲线测量签名将应答者和非应答者区分得有多好，并给出应答者的概率。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该药物有反应的患者，从而避免其他人受到不必要的毒性暴露。公共卫生相关性：骨髓增生异常综合征(MDS)的治疗仍然是临床医生面临的一个挑战。MDS是一种主要发生在老年人的克隆性骨髓衰竭疾病。现在只有3种FDA批准的药物治疗这种疾病。一种名为来那度胺的药物对存在染色体异常的特定亚型MDS非常有效。此外，该药物可对约25%的其他MDS患者产生有益效果。挑战是在接受来那度胺治疗之前识别那些有很高反应概率的患者，这些患者会导致严重的副作用。使用治疗前骨髓抽吸物的基因表达谱，我们已经确定了26名患者中识别应答者和无应答者的基因表达谱。在这项建议中，我们将对没有携带染色体异常的MDS患者进行筛查(即对药物有1：4的反应机会)，看看我们识别的表达谱是否可以准确预测反应。此外，我们还将测试一种更具成本效益和更简单的检测方法的有效性，该方法可以用于临床。

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.