Malignant rhabdoid tumors (MRT) are highly aggressive pediatric cancers that respond poorly to current therapies. In this study, we screened several MRT cell lines with large-scale RNAi, CRISPR-Cas9, and small-molecule libraries to identify potential drug targets specific for these cancers. We discovered MDM2 and MDM4, the canonical negative regulators of p53, as significant vulnerabilities. Using two compounds currently in clinical development, idasanutlin (MDM2-specific) and ATSP-7041 (MDM2/4-dual), we show that MRT cells were more sensitive than other p53 wild-type cancer cell lines to inhibition of MDM2 alone as well as dual inhibition of MDM2/4. These compounds caused significant upregulation of the p53 pathway in MRT cells, and sensitivity was ablated by CRISPR-Cas9-mediated inactivation of TP53. We show that loss of SMARCB1, a subunit of the SWI/SNF (BAF) complex mutated in nearly all MRTs, sensitized cells to MDM2 and MDM2/4 inhibition by enhancing p53-mediated apoptosis. Both MDM2 and MDM2/4 inhibition slowed MRT xenograft growth in vivo, with a 5-day idasanutlin pulse causing marked regression of all xenografts, including durable complete responses in 50% of mice. Together, these studies identify a genetic connection between mutations in the SWI/SNF chromatin-remodeling complex and the tumor suppressor gene TP53 and provide preclinical evidence to support the targeting of MDM2 and MDM4 in this often-fatal pediatric cancer.Significance: This study identifies two targets, MDM2 and MDM4, as vulnerabilities in a deadly pediatric cancer and provides preclinical evidence that compounds inhibiting these proteins have therapeutic potential. Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis):
The Michigan Portal for the Analysis of NGS data portal (http://mipanda.org) is an open-access online resource that provides the scientific community with access to the results of a large-scale computational analysis of thousands of high-throughput RNA sequencing (RNA-seq) samples. The portal provides access to gene expression profiles, enabling users to interrogate expression of genes across myriad normal and cancer tissues and cell lines. From these data, tissue- and cancer-specific expression patterns can be identified. Gene-gene coexpression profiles can also be interrogated. The current portal contains data for over 20,000 RNA-seq samples and will be continually updated.
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