MEDB-82. Exploring cell-cell communication networks in medulloblastoma using single-cell genomics. (3rd June 2022)

• Record Type: Journal Article
• Authors: Gabler, Lisa; Gojo, Johannes; Smith, Kyle S; Bihannic, Laure; Filbin, Mariella G; Northcott, Paul A; Berger, Walter; Hovestadt, Volker
• Is Part Of: Neuro-oncology. Volume 24(2022)Supplement 1
• Page Start: i125
• Page End: i126
• Publication Date: 2022-06-03
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noac079.456
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Medulloblastoma is a high-risk embryonal brain tumor arising in the cerebellum. Genomic profiling has revealed a striking molecular heterogeneity between medulloblastoma patients, yet treatment regimens are mostly uniform. Many children with medulloblastoma die from their disease and surviving patients often face severe long-term side effects, highlighting an urgent need for more effective treatment options. We and others have recently identified pronounced intra-tumoral heterogeneity and defined cellular hierarchies within medulloblastoma tumors. The functional role of these cellular hierarchies remains unknown. We now hypothesize the existence of an inter-cellular communication network that is maintained by receptor/ligand interactions. To test our hypothesis, we use our medulloblastoma single-cell RNA sequencing dataset of 25 patients, as well as bulk RNA sequencing, DNA methylation array, and genome sequencing data across molecular subtypes. Single-cell RNA sequencing data are analyzed to dissect cell compartments characterized by high expression of potentially oncogenic receptors and their respective ligands. Consequently, cell type-specific roles in auto- or paracrine signal transduction within the cellular community are explored. We further investigate downstream oncogenic signaling pathways by approximating transcription factor activity and explore genetic and epigenetic activation mechanisms by matched genome sequencing and DNA methylation profiling, respectively. Our findings will be applied to deconvolute bulk RNA sequencing data, thus identifying therapeutically relevant signaling networks in larger cohorts of medulloblastoma patients. Eventually, candidate targets will be validated on patient-derived cell models and xenografts by overexpression and inhibition studies. Together, here we aim at identifying tumor-driving receptor/ligand interactions in medulloblastoma, with the goal to define targets susceptible to precision oncology approaches.