ATRT-08. Exploiting lipid metabolism in atypical teratoid/rhabdoid tumors

Abstract Background Atypical teratoid/rhabdoid tumors (AT/RT) are extremely aggressive childhood central nervous system tumors that most often affect children age 3 and younger. While there have been some improvements in clinical outcomes with multimodal therapy, significant morbidity and severe toxicities are associated with such therapy. Metabolic pathways are often hijacked in cancer, thus providing tumor cells with the capacity to survive and invade. Importantly, these pathways can be targeted by pharmacologic inhibition, and their regulation is well understood through the basic helix-loop-helix transcription factor, sterol regulatory element binding protein (SREBP). SREBP acts as a master regulator of lipid metabolism. While lipid metabolic reprogramming has been recognized as a hallmark of cancer, it is unknown whether metabolic reprogramming is a characteristic of AT/RT cells, and whether this can be exploited as a therapeutic target. Methods Using in vitro patient-derived AT/RT models, RNA-sequencing, functional genomics, metabolic assays, mass spectrometry, and pharmacologic inhibitors of metabolism, we sought to test the hypothesis that lipid metabolic reprogramming represents a unique dependency in AT/RT. Results First, we utilized RNA-sequencing expression data from hundreds of pediatric brain tumor cell lines and performed enrichment analysis of lipid metabolism genes. AT/RT cells harbor significantly upregulated expression of genes involved in de novo lipogenesis, suggesting these pathways may represent unique vulnerabilities. Harnessing CRISPR/Cas9, we knocked out the most highly expressed metabolic genes in patient-derived AT/RT cells leading to significant attenuation of cell viability. Next, we tested inhibitors of these metabolic pathways in AT/RT cells. Lastly, we designed a custom pool of CRISPR/Cas9 sgRNAs targeting of approximately 3000 metabolism genes. This custom lentiviral library will enable high throughput assays to identify which metabolic genes represent cancer dependencies in AT/RT.