Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data
Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data
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DOI：
10.1182/blood-2007-11-126003
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发表时间：
2008-06-15
期刊：
影响因子：
20.3
通讯作者：
Jordan, Craig T.
中科院分区：
文献类型：
--
作者：
Hassane, Duane C.;Guzman, Monica L.;Jordan, Craig T.
越来越多的证据表明，恶性干细胞对于急性髓性白血病 (AML) 的发病机制很重要，并且是驱动 AML 发展和复发的细胞库。因此，需要新的治疗方案来预防复发并改善治疗结果。先前的研究表明，倍半萜内酯小白菊内酯 (PTL) 可以消除大量 AML 细胞、祖细胞和干 AML 细胞，同时不会对正常造血细胞造成明显的毒性。因此，PTL 必须激发能够介导 AML 选择性细胞死亡的细胞反应。鉴于化学基因组学的最新进展，例如基于基因表达离子的高通量筛选 (GE-HTS) 和连接图，我们假设用 PTL 治疗原发性 AML 所产生的基因表达特征可用于在存入基因表达综合库 (GEO) 的公开基因表达谱中搜索相似的特征。因此，我们使用 PTL 基因表达特征作为模板，对 GEO 数据库进行了广泛的计算机筛选，并发现了 2 种新药物：雷公藤红素和 4-羟基-2-壬烯醛，它们可以在体细胞、祖细胞和干细胞水平上有效根除 AML。这些发现表明使用多中心收集的高通量数据来促进白血病药物和药物靶点的发现。
Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene express ion-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets.