Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators
Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators
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DOI：
10.1016/j.ccr.2006.09.005
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发表时间：
2006-10-01
期刊：
影响因子：
50.3
通讯作者：
Golub, Todd R.
中科院分区：
文献类型：
--
作者：
Hieronymus, Haley;Lamb, Justin;Golub, Todd R.
虽然雄激素受体(AR)介导的信号转导是前列腺癌的核心，但调节AIR信号状态的能力是有限的。在这里，我们建立了一种化学基因组方法，用于发现和靶向预测癌症表型的调节因子，例如AIR信号。我们首先确定了空气活化抑制剂，包括一组结构上相关的化合物，包括雷公藤红素、吉都宁和衍生物。为了开发一种用于靶向途径识别的电子方法，我们应用了基于基因表达的分析，将HSP90抑制剂归类为具有与雷公藤红素和吉都宁相似的活性。验证这一预测，我们证明雷公藤红素和吉都宁抑制HSP90活性和HSP90客户，包括AR。广泛地说，这项工作通过基于基因表达的策略识别了HSP90的新调制模式。
Although androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AIR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AIR signaling. We first identify AIR activation inhibitors, including a group of structurally related compounds comprising celastrol, gedunin, and derivatives. To develop an in silico approach for target pathway identification, we apply a gene expression-based analysis that classifies HSP90 inhibitors as having similar activity to celastrol and gedunin. Validating this prediction, we demonstrate that celastrol and gedunin inhibit HSP90 activity and HSP90 clients, including AR. Broadly, this work identifies new modes of HSP90 modulation through a gene expression-based strategy.