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，其中没有单一的治疗策略具有普遍的益处。FDA最近批准了几种药物用于MDS，但除了del（5 q）核型的患者亚组外，很难知道哪种治疗方案可能对个体患者最有益。所有药物都具有可能对患者有害的副作用;因此，非常需要知道哪种药物可能改善个体患者的血细胞减少症。基因表达谱已被用于将患者分成生物学相似的亚组。我们假设具有相似自然史和对特定药物治疗反应的患者可能共享区分反应者和非反应者的表达谱。使用这种技术，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。来那度胺的应答者与红细胞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评分量化），从而提供对该药物特别有益于MDS患者贫血的临床观察的分子验证。在目前的资助中，我们建议进一步研究使用红细胞表达特征预测患者反应的能力。我们将对接受来那度胺单药治疗的非del（5 q）输血依赖性低/Int-1 MDS患者进行前瞻性试验。将对治疗前骨髓进行微阵列和luminex测定的表达谱分析，并与临床应答相关。如有必要，可以使用所获得的数据来细化z分数的签名和边界。额外的患者数量将能够生成受试者工作特征曲线，该曲线测量签名将应答者与非应答者区分开的程度，并给出应答概率。本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，从而使其他患者免于不良毒性暴露。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。目前只有3种FDA批准的药物用于治疗这种疾病。一种药物，来那度胺，是非常有效的一个特定亚型的MDS中存在的染色体异常。此外，该药物可以在约25%的其他MDS患者中产生有益效果。面临的挑战是确定那些在接受来那度胺治疗之前有很高反应概率的患者，这些患者会引起严重的副作用。使用治疗前骨髓穿刺物的基因表达谱，我们已经确定了一个基因表达谱，该基因表达谱可以识别26例患者的应答者和非应答者。在这项提案中，我们将筛选不携带染色体异常的MDS患者（即对药物有1：4的反应机会），以了解我们已经确定的表达谱是否可以准确预测反应。此外，我们将测试一种成本效益更高、复杂性更低的检测方法的有效性，该方法可用于临床。

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.