Leveraging Single-Cell RNA Sequencing to Characterize Murine Ewing Sarcoma Xenografts

High-quality single-cell analyses critically depend on standardized tissue processing workflows that preserve cellular integrity and minimize dissociation-induced artifacts. Here, we describe a robust and reproducible protocol for the isolation, cryopreservation, and downstream processing of single-cell suspensions from Ewing sarcoma (EwS) tumors, including the bioinformatic analyses and tools to interrogate the resulting data. The workflow is optimized for strict cold-chain handling and employs a cold-active Bacillus licheniformis protease-based digestion strategy coupled with gentle mechanical dissociation to reduce cellular stress and transcriptional perturbations. Tumor tissue is processed under controlled low-temperature conditions, followed by filtration, cryopreservation, and storage compatible with single-cell RNA sequencing and multi-omics applications. This protocol supports high cell viability, preserves physiologically relevant transcriptional states, and provides a reproducible framework for downstream computational single-cell analyses of EwS tumor samples. The computational pipeline performs ambient RNA correction, barcode calling, doublet detection, SCTransform normalization, PCA/UMAP and clustering, and cell type annotation via the AUCell module scoring combined with multi-reference Azimuth label transfer. Cluster labels are validated by differential expression-based marker enrichment, and integrated embeddings are used for visualization. This end-to-end workflow ensures high cell viability, preserves physiologically relevant transcriptional states, and provides a reproducible framework for downstream computational single-cell analyses of EwS tumor samples.