SINGLE-CELL TRANSCRIPTIONAL PROFILING OF ATRTS REVEALS HETEROGENEOUS SIGNATURES OF TUMOR AND NONMALIGNANT CELL POPULATIONS

Abstract Atypical Teratoid/Rhabdoid Tumors (ATRTs) are known for exhibiting high inter-tumor heterogeneity, even though they are almost all characterized by a common loss of SMARCB1 (or rarely SMARCA4). Three subgroups have been identified at bulk methylome and transcriptome level: ATRT-TYR, ATRT-SHH, and ATRT-MYC. To better understand the biology underlying each subgroup and potentially unveil their (different) cell(s) of origin, we performed single-cell transcriptomic analyses in 22 ATRTs using fresh frozen samples and both 10X and Smartseq technology. All data, grouped by technology, underwent quality control and normalization, regressing out the biases introduced by each sample. Tumor microenvironment (TME) and tumor bulk (TB) clusters were characterized by a combination of copy number variant analyses, enrichment in literature lists of marker genes for specific cell populations, and in-depth analysis of differentially enriched (DE) genes. Non-negative Matrix Factorization (NMF) was applied to TB to reveal major transcriptional profiles, which were grouped into meta-signatures. A total of 71 gene lists were retrieved from NMF (TB) and DE analyses (TME + TB), that gathered into 11 signature groups by Jaccard similarity, with one extra group accounting for unique signatures. Three groups targeted TME, accounting for either microglia, fibroblasts and endothelial cells, or OPCs, oligodendrocytes, astrocytes and neurons. These signatures are enriched in specific clusters across technologies. The remaining eight groups divide into two types, either enriched in clusters predominantly formed by cells of one or two ATRT subgroups or signatures enriched for a particular phenotype, such as cilial, cycling, axonogenesis or EM transition. While the first type is enriched across clusters in a gradient fashion, the second shows enrichment for selected clusters across technologies. Further analyses on the integrated dataset and additional samples are ongoing to validate and refine these 11 signature groups in ATRTs to see how this may lead to new treatment approaches.