Meningeal solitary fibrous tumor cell states phenocopy cerebral vascular development and homeostasis

Abstract Background Meningeal solitary fibrous tumors (SFTs) are rare mesenchymal neoplasms that are associated with local recurrence and hematogenous metastasis. The cell states and spatial transcriptomic architecture underlying the unique clinical behavior of meningeal SFTs are unknown. Methods Single-cell (n = 4), spatial (n = 8), and bulk RNA sequencing (n = 22) were used to define the cell states and spatial transcriptomic architecture of meningeal SFTs across histological grades and in patient-matched pairs of primary/recurrent or intracranial/metastatic samples. Immunofluorescence, immunohistochemistry, and comparison of single-cell types to meningiomas, or to cerebral vascular development or homeostasis, were used for validation. Results Here we show meningeal SFTs are comprised of regionally distinct gene expression programs that resemble cerebral vascular development or homeostasis. Single-cell trajectory analysis and pseudotemporal ordering of single cells suggest that meningeal SFT cell fate decisions are dynamic and interchangeable. Cell–cell communication analyses demonstrate receptor-ligand interactions throughout the meningeal SFT microenvironment, particularly between SFT cells, endothelia, and immature neurons. A direct comparison of single-cell transcriptomes from meningeal SFTs versus meningiomas shows that SFT cells are enriched in the expression of endothelial markers while meningioma cells are enriched in the expression of mural cell markers. Meningeal SFT spatial transcriptomes show regionally distinct intratumor heterogeneity in cell states, gene expression programs, and cell–cell interactions across World Health Organization histological grades and in patient-matched pairs of primary/recurrent or intracranial/metastatic samples. Conclusions These results shed light on pathways underlying meningeal SFT biology in comparison to other central nervous system tumors and provide a framework for integrating single-cell, spatial, and bulk RNA sequencing data across human cancers and normal tissues.