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Single nucleus transcriptomics of spinal ependymoma subtypes recognizes intratumoral heterogeneity [snRNA-seq]

GSE298501 Homo sapiens Expression profiling by high throughput sequencing 14 samples 2025/09/12 GPL24676GPL30173
Summary
The two most prevalent types of spinal ependymal tumors are myxopapillary ependymomas (MPE) and spinal ependymomas (SP-EPN). Based on molecular data from bulk tumor samples, we previously identified clinically relevant subtypes with poor (MPE-A; SP-EPN-A) and favorable progression-free survival (MPE-B; SP-EPN-B). However, detailed cellular compositions, molecular heterogeneity, and features of tumor progression are largely unknown. We performed single nucleus transcriptomic sequencing of 25 formalin-fixed and paraffin-embedded spinal ependymal tumors including all MPE and SP-EPN subtypes as well as six paired primary and relapsed MPE-A. Ependymoma subtypes presented with a broad, but comparable tumor microenvironment. Furthermore, neoplastic cells demonstrated inter- and intratumoral heterogeneity regarding cancer cell state composition. Overall, MPE tumors exhibited a significantly higher abundance of the astrocytic state, whereas a ciliated state was more prevalent in SP-EPN. Also, transcriptome-inferred copy number profiles revealed tumor cell clusters with distinct chromosomal alterations across tumors, suggesting subclonal neoplastic growth. Compared to normal human spinal cord cell populations, MPE tumor cells displayed similarities to astrocytes and ependymal cells, whereas SP-EPN exclusively matched ependymal cells. MPE-A demonstrated a distinct profile, being similar to the roof and floor plate of the developing spinal cord. Paired primary and relapsed MPE-A revealed mostly similar histology, epigenetics, copy number profiles, and cellular composition of neoplastic cells. Single nucleus transcriptomic sequencing provides valuable insights into the molecular composition of spinal ependymoma types and subtypes and may pave the way for a better understanding of tumor evolution and identification of therapeutic targets.
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