Single-cell sequencing

Bone marrow and peripheral blood were collected from mice carrying orthotopic PyMT-N tumors (C57BL/6, Envigo), using previously described methods (29). RNA isolated from Hematopoietic cells using 10X Genomics Chromium protocol was subjected to single-cell RNA sequencing. The 10X Genomics Chromium system was used for library preparation and libraries were prepared per 10x Genomics guidelines. Sequencing adapters are provided by 10x Genomics. All sequencing results were pooled from three mice (three technical replicates). Raw sequencing files were imported into the 10x Genomics Cell Ranger toolkit (v3.1.0) for alignment, filtering, barcode counting, and UMI counting with default parameters. The mm10 (v3.0.0) genome was used for reads mapping. The Seurat (v3.2.3) package on R (v4.0.2) was used for downstream analysis. For quality control, we kept cells with less than 20,000 read counts and have less than 10% mitochondria genes. These parameters aimed to filter doublets and dead cells. We then filtered mitochondrial genes (genes start with mt), ribosomal protein genes (genes start with Rpl and Rps), and unspecified genes (genes start with Gm). Next, we used the SCTransform function in the Seurat package, which implemented regularized negative binomial regression to normalize raw Unique Molecular Identifier (UMI) counts. Variable genes identified by this method were used as inputs for principal component analysis (PCA). We applied Uniform Manifold Approximation and Projection analysis for visualization using the first 50 principal components identified by PCA. Cells were clustered by the shared nearest neighbor with the FindNeighbors and FindClusters functions in the Seurat package. Matured neutrophils are identified by expression of Ly6g, Camp, Ltf, and S100a9. Various clusters were ordered in pseudo-time using the Monocle 3 package (v1.0.0). In blood, two neutrophil clusters were identified, one before infiltration of tumors and the other after tumor infiltration according to pseudo-time, and were defined as “pre-” and “posttumor” clusters. The difference in Malat1 RNA expression of neutrophils before entering the tumor and neutrophils after exiting the tumor was visualized by a violin plot generated by Vlnplot function in Seurat package. The P value was calculated by FindAllMarkers function in Seurat package using a Wilcoxon Rank-Sum test. Single-cell sequencing data generated in this study are publicly available in Gene Expression Omnibus (GEO) using the accession number {"type":"entrez-geo","attrs":{"text":"GSE222854","term_id":"222854"}}GSE222854.