Abstract
Abstract Pediatric solid and central nervous system tumors are the primary cause of cancer-related fatalities in children. Discovering novel targeted therapies requires utilizing pediatric cancer models that accurately mirror the patient's illness. However, the creation and evaluation of these models have significantly trailed adult cancer research, emphasizing the pressing demand for pediatric-centric cell line repositories. Here, we establish a centralized collection of over 450 childhood cancer cell lines. We subjected over 250 of these cell lines to comprehensive multi-omics analyses (including DNA sequencing, RNA sequencing, and DNA methylation analysis), while concurrently conducting pharmacological screenings and genetic CRISPR-Cas9 loss-of-function assays to unveil pediatric-specific treatment avenues and biomarkers. Machine learning approaches were then applied to uncover genotype-phenotype relationships and synthetic lethal interactions. Our endeavor sheds light on the specific vulnerabilities of pathways in molecularly characterized pediatric tumor subclasses and reveals clinically relevant therapeutic opportunities linked with biomarkers. We offer access to the cell line data and resources through an open-access portal. Citation Format: Ron Firestein. Generation and Mining of a Pediatric-focused Cancer Cell Line Atlas to Define Druggable Genetic Interactions in Childhood Malignancies [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA012.
Published Version
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