Spatially resolved transcriptomics of benign and malignant peripheral nerve sheath tumors

Background:

Peripheral nerve sheath tumors (PNSTs) encompass entities with different cellular differentiation and degrees of malignancy. Spatial heterogeneity complicates diagnosis and grading of PNSTs in some cases. In malignant PNST (MPNST) for example, single cell sequencing data has shown dissimilar differentiation states of tumor cells. Here, we aimed at determining the spatial and biological heterogeneity of PNSTs.

Methods:

We performed spatial transcriptomics on formalin-fixed paraffin-embedded diseased peripheral nerve tissue. We used spatial clustering and weighted correlation network analysis to construct niche-similarity networks and gene expression modules. We determined differential expression in primary pathologies, analysed pathways to investigate the biological significance of identified meta-signatures, integrated the transcriptional data with histological features and existing single cell data, and validated expression data by immunohistochemistry.

Results:

We identified distinct transcriptional signatures differentiating PNSTs. We observed spatial transcriptional heterogeneity within hybrid PNSTs (HPNSTs) and immune cells preferentially infiltrating the neurofibroma component. S100b and Vimentin were validated as markers for schwannomas and schwannoma components of HPNSTs, while APOD highlights neurofibroma components of HPNSTs. Furthermore, we mapped cells with different differentiation states, including Schwann cell precursors, neural crest-like cells and those with mesenchymal transition in MPNST in space.

Conclusions:

This pilot study shows that spatial transcriptomics can be applied to PNSTs to gain insight into their biology. It helps establishing new markers, provides spatial information about cellular composition and distribution of cellular differentiation states. Hence, it is a powerful tool for integrating morphological and high-dimensional molecular data with the potential to facilitate PNSTs classification in the future.