Single-cell RNA-seq
v.4.1.1, Tumor, necrotic
-11, METASTASIS, TUMOR, NECROTIC
Endometrial metastasis biopsies were dissociated for single-cell RNA-seq using the Tumor Dissociation kit by Miltenyi Biotec (no. 130–095-929). Briefly, the biopsy was placed in RPMI medium in a Petri dish on ice and cut into small pieces (2–4 mm) after removal of necrotic tissue. Pieces were then infused with the RPMI/enzyme mix (Miltenyi Biotec), transferred to a gentleMACS C tube containing RPMI/enzyme mix, attached to the sleeve of the gentleMACS Octo Dissociator and run using the programme 37_h-TDK1. After completion of the programme the cells were spun down at 300Except when specifically mentioned, all analyses were performed with R/Bioconductor packages, R v.4.2.2 (2022-11-10 r83330) (Filtered barcoded matrices from single-cell RNA-seq data were imported into R using the Seurat package (v.4.1.1). Doublets were detected with DoubletFinder (v.2.0.3) and filtered out, together with cells showing a low number of features (nFeature_RNA < 500) or a high percentage of mitochondrial genes (above 25%). Seurat functions were used for normalization (SCTransform), merging, dimensional reduction and clustering. Initial cell type identification was based on consensus from several automated cell annotation packages (SciBet’ v.1.0, SingleR v.1.10.0 and scType (Spatial RNA-seq matrices and images were imported into R using the Load10X_Spatial function of the Seurat package. For each sample, only those spots with more than 1,000 features were kept for downstream preprocessing, including SCTransform normalization, dimensional reduction and clustering. Most analyses were performed independently for each sample (without merging or integration). Two strategies were used for cell type annotation: label transfer following integration of the single-cell RNA-seq data described above, and manual annotation using known markers for major cell types.Inference of cell–cell communication was done with CellChat (v.1.6.0), for both single-cell and spatial RNA-seq data.