LGG-45. Genetic dependencies inMYB/MYBL1-driven pediatric low-grade glioma models

Neuro-oncology(2022)

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摘要
Abstract AIM: Pediatric low-grade gliomas (pLGGs) are a heterogenous group of tumors, diverse in their localization, histology, mutational landscape, clinical behavior, and treatment response. Genomic alterations impacting the MYB family of transcription factors were identified in two distinct pLGG subtypes: Angiocentric Gliomas (AG) and Diffuse Astrocytomas (DA). The molecular profiles and therapeutic vulnerabilities associated with these genomic alterations remain unexplored. In this study we highlight the use of genome-wide CRISPR/Cas9 knock-out screens for an unbiased identification of translatable therapeutic targets. METHODOLOGY: Given the lack of patient-derived pLGG cell lines, we engineered in vitro pLGG mouse and human neural stem cell (NSC) models to harbor pLGG-relevant genomic alterations. We performed single cell RNA sequencing to investigate the transcriptional profiles driven by these mutations and to dissect the central regulatory networks enabling tumorigenesis. Specific genetic dependencies associated with MYB/MYBL1 mutations were screened using the Brie genome-wide mouse CRISPR lentiviral knock-out pooled library, consisting of 78,637 single guide RNAs (sgRNAs) targeting 19,674 mouse genes. RESULTS: We have successfully generated in vitro NSC-based pLGG models crucial to deepening our knowledge on pLGG biology and the identification of translatable therapeutic targets. Genome-scale CRISPR/Cas9 knock-out screens in isogenic NSCs models, expressing distinct MYB/MYBL1 alterations or a control transgene, revealed several differential genetic dependencies. Among the top identified dependencies are regulators of cell-stress response, cell-cycle progression, and modulators of the ubiquitin-proteasome degradation pathway. CONCLUSION: Genome-wide CRISPR knock-out screens are a powerful tool for the unbiased identification of mutation-specific genetic dependencies that can be explored as candidates for precision medicine approaches.
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