Embr-27. Neoplastic and Immune Single Cell Transcriptomics Define Subgroup-specific Intra-tumoral Heterogeneity of Childhood Medulloblastoma
Year: 2021
Type: article
Abstract: Medulloblastoma (MB) is a heterogeneous disease in which neoplastic cells and associated immune cells contribute to disease progression. To better understand cellular heterogeneity in MB we used single-cell RNA sequencing, immunohistochemistry and deconvolution of transcriptomic data to profile neoplastic and immune populations in childhood MB samples and MB genetically engineered mouse models (GEMM). Neoplastic cells clustered primarily according to individual sample of origin which is in part due to the effect of chromosomal copy number gains and losses. Harmony alignment of single cell transcriptomic data revealed novel MB subgroup/subtype-associated subpopulations that recapitulate neurodevelopmental processes and are associated with clinical outcomes. This includes photoreceptor-like cells and glutamatergic lineage unipolar brush cells in both GP3 and GP4 subgroups of MB, and a SHH subgroup nodule-associated neuronally-differentiated cell subpopulation. We definitively chart the spectrum of MB immune cell infiltrates, which reveals unexpected degree of myeloid cell diversity. Myeloid subpopulations include subgroup/subtype-associated developmentally-related neuron-pruning as well as antigen presenting myeloid cells. Human MB cellular diversity is recapitulated in subgroup-specific MB GEMM, supporting the fidelity of these models. These findings provide a clearer understanding of both the neoplastic and immune cell heterogeneity in MB and how these impact subgroup/subtype classification and clinical outcome.
Source: Neuro-Oncology
Authors: Andrew Donson, Kent Riemondy, Sujatha Venkataraman, Nicholas Willard, Anandani Nellan, Bridget Sanford, Andrea Griesinger, Vladimir Amani, Siddhartha Mitra, Todd Hankinson, Michael Handler, Martin Sill, Jennifer Ocasio, Seth Weir, Daniel Malawsky, Timothy Gershon, Alexandra Garancher, Robert Wechsler-Reya, Jay Hesselberg, Nicholas Foreman, Rajeev Vibhakar
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,326
OpenAlex ID: W4232367545
