Medulloblastoma is one of the most common pediatric malignant brain tumors, currently comprising four distinct molecular subgroups: wingless [WNT], sonic hedgehog [SHH], and groups 3-4. Efforts to identify the mechanisms of medulloblastoma development have focused on mapping the extent of the tumor cell heterogeneity within each subgroup. Nevertheless, little is known about the role of the tumor microenvironment (TME) in medulloblastoma progression, particularly in subgroups 3-4, which have the worst prognosis due to metastatic disease. In this study, we performed single-cell transcriptomics on 14 human medulloblastoma samples spanning all molecular subgroups, to uncover novel TME-tumor interactions modulating medulloblastoma progression and metastasis. Unsupervised clustering of all medulloblastoma samples revealed 18 subclusters, including tumor granule neuron progenitors (GNPs) in different stages of differentiation, stromal cells (including oligodendrocyte precursors, mature oligodendrocytes, astrocytes, fibroblasts, endothelial cells and pericytes), myeloid cells (including microglia, monocytes and macrophages) as well as lymphoid cells. To investigate subgroup-specific signatures as well as TME-tumor pathways, we analyzed each subgroup separately. Analysis of supporting stroma cells in groups 3-4 demonstrated the presence of 8 different stroma populations, including a population of tumor-associated endothelial cells. Tumor-associated endothelial and fibroblast populations of groups 3-4 showed the highest expression of genes for vascular remodeling and extracellular matrix degradation, suggesting an active reprogramming of the stroma by tumor GNP cells to support medulloblastoma progression. Epithelial-to-mesenchymal transition-like processes that regulate stem cell, invasion and metastatic properties were upregulated in the tumor GNP populations of groups 3-4 compared to SHH and WNT subgroups. Finally, we highlight the presence of the CXCL1-CXCL5/CXCR2 metastasis-associated axis in groups 3-4 medulloblastomas as a potential therapeutic target. Our findings provide biological insights into TME processes for the different subgroups of medulloblastoma and possible new potential therapeutic avenues. Citation Format: Ioanna Tsea, Yana Ruchiy, Manouk Verhoeven, Indranil Sinha, Klas Blomgren, Lena Maria Carlson, John Inge Johnsen, Cecilia Dyberg, Ninib Baryawno. Transcriptomic landscape of medulloblastoma reveals pathways of tumor-stroma remodelling [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 1677.
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.
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