Abstract LB059: Subtype classification of pediatric high-grade glioma tumors by comparative transcriptomics

Abstract Pediatric high-grade glioma (pHGG) is a highly malignant and poorly understood cancer driven by diverse genetic and epigenetic mechanisms. Here, we use comparative RNA sequencing, outlier analysis, and spectral clustering approaches to analyze transcriptomic data of 1,543 pediatric brain tumor specimens from the UCSC Treehouse Childhood Cancer Initiative (Treehouse) and Open Pediatric Brain Tumor Atlas (OpenPBTA) to identify subpopulations of pHGG patients with characteristic gene expression profiles. We find that approximately half (45%) of pHGG tumors from OpenPBTA exist in three subgroups defined by high outlier-level expression either of: mitochondrially-encoded 12S and 16S rRNAs; genes enriched in the HSF1-mediated heat shock response and activation pathways; or six C/D box snoRNA (SNORD) genes originating from the paternally-expressed SNORD116 locus involved in Prader-Willi syndrome, a complex neurodevelopmental disorder. Interestingly, the same set of HSF1-dependent pathway genes is also significantly upregulated in a subset (~11%) of pHGG tumors from Treehouse, validating this finding in two independent compendia with different transcript isolation strategies (Treehouse, polyA selection; OpenPBTA, ribodepletion). Our work identifies distinct classes of tumors with outlier-level expression of genes with previously unknown roles in pHGG and provides a framework for subtyping tumors by comparative transcriptomics that is adaptable to any cancer type. We are currently investigating the molecular roles of HSF1-response genes and the imprinted SNORD116 gene cluster in pHGG. Our ongoing research into the biomolecular signatures and mechanisms of the three major tumor classes of pHGG as defined in our study will contribute to a greater understanding of pHGG disease manifestation and progression, and will inform strategies of tailored therapeutic interventions for children with this devastating disease. Citation Format: Gina D. Mawla, A. Geoffrey Lyle, Ellen T. Kephart, Katrina Learned, Holly C. Beale, Joshua E. Goldford, Olena M. Vaske. Subtype classification of pediatric high-grade glioma tumors by comparative transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB059.