Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators

Abstract

Although androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AR signaling. We first identify AR 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.