Resolving the heterogeneous tumour microenvironment in cardiac myxoma through single-cell and spatial transcriptomics

Cardiac myxoma (CM) is the most common (58%-80%) type of primary cardiac tumours. Currently, there is a need to develop medical therapies, especially for patients not physically suitable for surgeries. However, the mechanisms that shape the tumour microenvironment (TME) in CM remain largely unknown, which impedes the development of targeted therapies. Here, we aimed to dissect the TME in CM at single-cell and spatial resolution.

We performed single-cell transcriptomic sequencing and Visium CytAssist spatial transcriptomic (ST) assays on tumour samples from patients with CM. A comprehensive analysis was performed, including unsupervised clustering, RNA velocity, clonal substructure inference of tumour cells and cell-cell communication.

Unsupervised clustering of 34 759 cells identified 12 clusters, which were assigned to endothelial cells (ECs), mesenchymal stroma cells (MSCs), and tumour-infiltrating immune cells. Myxoma tumour cells were found to encompass two closely related phenotypic states, namely, EC-like tumour cells (ETCs) and MSC-like tumour cells (MTCs). According to RNA velocity, our findings suggest that ETCs may be directly differentiated from MTCs. The immune microenvironment of CM was found to contain multiple factors that promote immune suppression and evasion, underscoring the potential of using immunotherapies as a treatment option. Hyperactive signals sent primarily by tumour cells were identified, such as MDK, HGF, chemerin, and GDF15 signalling. Finally, the ST assay uncovered spatial features of the subclusters, proximal cell-cell communication, and clonal evolution of myxoma tumour cells.

Our study presents the first comprehensive characterisation of the TME in CM at both single-cell and spatial resolution. Our study provides novel insight into the differentiation of myxoma tumour cells and advance our understanding of the TME in CM. Given the rarity of cardiac tumours, our study provides invaluable datasets and promotes the development of medical therapies for CM.