Single-cell transcriptomics reveals immune suppression and cell states predictive of patient outcomes in rhabdomyosarcoma

The cellular differentiation states of paediatric rhabdomyosarcoma (RMS) remain to be explored. Here, single-cell RNA sequencing analysis of RMS tumours reveals an immunosuppressive microenvironment and distinct transcriptional programs predictive of patient outcomes. Paediatric rhabdomyosarcoma (RMS) is a soft tissue malignancy of mesenchymal origin that is thought to arise as a consequence of derailed myogenic differentiation. Despite intensive treatment regimens, the prognosis for high-risk patients remains dismal. The cellular differentiation states underlying RMS and how these relate to patient outcomes remain largely elusive. Here, we use single-cell mRNA sequencing to generate a transcriptomic atlas of RMS. Analysis of the RMS tumour niche reveals evidence of an immunosuppressive microenvironment. We also identify a putative interaction between NECTIN3 and TIGIT, specific to the more aggressive fusion-positive (FP) RMS subtype, as a potential cause of tumour-induced T-cell dysfunction. In malignant RMS cells, we define transcriptional programs reflective of normal myogenic differentiation and show that these cellular differentiation states are predictive of patient outcomes in both FP RMS and the less aggressive fusion-negative subtype. Our study reveals the potential of therapies targeting the immune microenvironment of RMS and suggests that assessing tumour differentiation states may enable a more refined risk stratification.

Automated summary

This study explores the cellular differentiation states of paediatric rhabdomyosarcoma (RMS) using single-cell RNA sequencing analysis and identifies an immunosuppressive microenvironment and transcriptional programs predictive of patient outcomes. The research generates a transcriptomic atlas of RMS and reveals evidence of an immunosuppressive microenvironment in the RMS tumour niche. The study also highlights the potential of therapies targeting the immune microenvironment and suggests that assessing tumour differentiation states may enable a more refined risk stratification.