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MDB-04. SINGLE-CELL TRANSCRIPTOMIC ANALYSIS REVEALS DISTINCT GENOMIC LANDSCAPES, CELL TRAJECTORIES, AND TUMOUR-MICROENVIRONMENT INTERACTIONS IN FOUR SUBTYPES OF MEDULLOBLASTOMA

Medulloblastoma is the most common paediatric high-grade brain tumour, which comprises four different molecular subtypes (SHH, Wnt, Group 3, and Group 4), each defined by different molecular characteristics, genomic aberrations, and prognosis. High levels of inter- and intra-tumoural heterogeneity,...

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Detalles Bibliográficos
Autores principales: Ruchiy, Yana, Tsea, Ioanna, Verhoeven, Bronte Manouk, Sinha, Indranil, Preka, Efthalia, Olsen, Thale Kristin, Mei, Shenglin, Blomgren, Klas, Johnsen, John Inge, Carlson, Lena-Maria, Dyberg, Cecilia, Baryawno, Ninib
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10259932/
http://dx.doi.org/10.1093/neuonc/noad073.237
Descripción
Sumario:Medulloblastoma is the most common paediatric high-grade brain tumour, which comprises four different molecular subtypes (SHH, Wnt, Group 3, and Group 4), each defined by different molecular characteristics, genomic aberrations, and prognosis. High levels of inter- and intra-tumoural heterogeneity, together with the detrimental side effects caused by the current medulloblastoma treatments, need to be addressed in order to develop more personalised treatments and improve the quality of life of these patients. In this study, we analysed single-cell RNA sequencing data from 14 medulloblastoma patients, comprising all four molecular subtypes. We found that these tumours exhibit great levels of heterogeneity with regard to their copy number variation (CNV) profiles analysed using Numbat, as well as immune cell infiltration and composition within these tumours. Tumour-infiltrating immune cells represented a heterogeneous population comprised of monocytes, M1- and M2-like macrophages, dendritic cells, and microglia. Our ligand-receptor analysis also identified a subset of immune cells that send EGF signals to the tumour clusters, potentially contributing to the tumour growth. In addition, we showed that the tissue of origin of the immune cells found within the tumour microenvironment and their medulloblastoma subgroup specificity greatly influence their clustering when projected onto a UMAP. We also found that the clustering of tumour cells is influenced by their CNV levels. Finally, we performed RNA velocity analysis and identified subgroup-specific cell trajectories for each medulloblastoma subtype. As predicted, identified cell trajectories demonstrated that cells move in a direction of increasing CNV levels, making it possible to visualise and track the tumour progression and identify genetic markers specific to either earlier or later tumour stages. Overall, our study underlines high levels of inter-tumoural heterogeneity in medulloblastoma. It also provides opportunities for the identification of subgroup-specific biomarkers for the early stages of medulloblastoma, potentially contributing to the discovery of novel drug targets.