Single cell analysis of patient-derived MSCs.

A) CD90+ cells were isolated from normal donors or patients with invasive breast cancer and subjected to single cell analysis. Gene expression profiles from single cells were clustered using tSNE, and 7 distinct cell clusters were observed. B) Candidate gene expression profiles were used to functionally characterize MSCs into 3 main subclasses (osteogenic, chondrogenic or adipogenic). C) Comparison of cells derived from healthy donors or breast cancer patients demonstrated proportional changes in number of cells contributing to specific clusters. D) Ontology categories associated with single cell populations.</p

MSC-related gene expression can be observed in whole tumor single cell RNAseq.

UMAP visualization of 130,246 cells analyzed by scRNA-seq and integrated across 26 primary breast tumors (from Wu et al [34]). Clusters were annotated for their cell types as predicted using canonical markers for epithelial cells (EPCAM), proliferating cells (MKI67), T cells (CD3D), myeloid cells (CD68), B cells (MS4A1), plasmablasts (JCHAIN), endothelial cells (PECAM1) and mesenchymal cells (fibroblasts/perivascular-like cells; PDGFRB) and gene signature-based annotation. A) Non-tumor MSC, perivascular and endothelial cells cluster on left side of plot demonstrated the majority of THY1 (CD90), CXCL12 and ACTA2 expression in the whole tumor. B) UMAP visualization of reclustered mesenchymal cells, including CAFs (6,573 cells), PVL cells (5,423 cells), endothelial cells (7,899 cells), lymphatic endothelial cells (203 cells) and cycling PVL cells, demonstrating that the majority of CD90 (THY1) positive cells residing in the assigned MSC cluster. C) Feature plots of gene expression of COL1A1, COL8A1 in whole tumor UMAP demonstrating gene expression restricted to MSC-associated clusters, and D) MSC UMAP demonstrating COL10A1 gene expression restricted to MSC/CAFS.</p

S3 Data -

The tumor microenvironment is a complex mixture of cell types that bi-directionally interact and influence tumor initiation, progression, recurrence, and patient survival. Mesenchymal stromal cells (MSCs) of the tumor microenvironment engage in crosstalk with cancer cells to mediate epigenetic control of gene expression. We identified CD90+ MSCs residing in the tumor microenvironment of patients with invasive breast cancer that exhibit a unique gene expression signature. Single-cell transcriptional analysis of these MSCs in tumor-associated stroma identified a distinct subpopulation characterized by increased expression of genes functionally related to extracellular matrix signaling. Blocking the TGFβ pathway reveals that these cells directly contribute to cancer cell proliferation. Our findings provide novel insight into communication between breast cancer cells and MSCs that are consistent with an epithelial to mesenchymal transition and acquisition of competency for compromised control of proliferation, mobility, motility, and phenotype.</div

Schematic of sample acquisition for analysis.

A) CD90 positive mesenchymal stromal cells isolated from breast cancer patients express a unique gene expression profile indicative of increased cell to cell signaling. MSCs were isolated from fresh stromal tissue adjacent to an invasive lesion (tumor-associated) or distal to the tumor site (patient-normal). B) Microscopy images demonstrating phenotypic characteristics of CD45+ or CD45-/CD90+ cells isolated by magnetic-activated cell sorting (MACS). C) CD90+ cells were subjected to FACS for phenotypic mesenchymal associated cell surface markers. D) Microscopy images demonstrating tumor tissues used for FFPE gene expression analysis. Hematoxylin and Eosin staining of tissue sections used for analysis (left panel) and images of tumor sections before and after Laser Capture microdissection (LCM) (right panels).</p

S1 Data -

The tumor microenvironment is a complex mixture of cell types that bi-directionally interact and influence tumor initiation, progression, recurrence, and patient survival. Mesenchymal stromal cells (MSCs) of the tumor microenvironment engage in crosstalk with cancer cells to mediate epigenetic control of gene expression. We identified CD90+ MSCs residing in the tumor microenvironment of patients with invasive breast cancer that exhibit a unique gene expression signature. Single-cell transcriptional analysis of these MSCs in tumor-associated stroma identified a distinct subpopulation characterized by increased expression of genes functionally related to extracellular matrix signaling. Blocking the TGFβ pathway reveals that these cells directly contribute to cancer cell proliferation. Our findings provide novel insight into communication between breast cancer cells and MSCs that are consistent with an epithelial to mesenchymal transition and acquisition of competency for compromised control of proliferation, mobility, motility, and phenotype.</div

Ontology analysis of gene expression data.

Gene expression profiles from heatmap clusters highlighting expression groups with similar expression patterns were merged and Gene Ontology (GO) annotation analyses of gene sets were performed using GSEA/MSIgDB (Broad). GO Term enrichment was considered significant for all terms with P (ZIP)</p

S2 Data -

The tumor microenvironment is a complex mixture of cell types that bi-directionally interact and influence tumor initiation, progression, recurrence, and patient survival. Mesenchymal stromal cells (MSCs) of the tumor microenvironment engage in crosstalk with cancer cells to mediate epigenetic control of gene expression. We identified CD90+ MSCs residing in the tumor microenvironment of patients with invasive breast cancer that exhibit a unique gene expression signature. Single-cell transcriptional analysis of these MSCs in tumor-associated stroma identified a distinct subpopulation characterized by increased expression of genes functionally related to extracellular matrix signaling. Blocking the TGFβ pathway reveals that these cells directly contribute to cancer cell proliferation. Our findings provide novel insight into communication between breast cancer cells and MSCs that are consistent with an epithelial to mesenchymal transition and acquisition of competency for compromised control of proliferation, mobility, motility, and phenotype.</div

Gene expression analysis of patient-derived stromal and tumor samples.

A) Principal component analysis (PCA) of gene expression profiles from MSCs isolated from patients. PCA of 35,264 transcripts expressed in MSCs isolated from unaffected young individuals (normal), unaffected tissue from breast cancer patients (PNS), or patient tumor stroma associated sites (PTS). Gene signatures in CD90+ MSCs from breast cancer (BC) patients are sufficient to distinguish between breast cancer patients and healthy individuals as well as tumor associated site and unaffected site. B) Scatterplot of gene expression demonstrating that tumor-associated MSCs (PTS) demonstrate gene expression changes compared to a distal site (PNS). C) Heatmap demonstrating trends in expression of 133 genes that showed significant variation between CD45-/CD90+ cells isolated from normal, patient normal stroma and patient tumor stroma. Gene signatures from MSCs were subjected to hierarchal clustering analysis but could not define cancer subtypes, but could define MSCs from normal or adjacent to tumor tissue. D) Heatmap demonstrating trends in expression of genes in Laser Capture Microdissection (LCM) of stromal and tumor samples derived from FFPE tissue and processed by SMART 3SEQ. Gene signatures from samples subjected to hierarchal clustering analysis and distinct gene expression signatures relating to MSC genes could differentiate stroma versus tumor tissues.</p

Pathway and ontology analyses reveal that patient-derived MSCs demonstrate unique properties.

A) Dot plot of proportion of cells in the respective cell clusters (Other, Chondrogenic, Patient-specific) expressing each gene (dot size), and average expression (color scale). B) Ontology and GSEA enrichment plots demonstrating category association of gene signatures expressed by patient-specific MSCs. C) Gene expression pattern in enriched pathways. Squares show enriched DEGs in the corresponding terms (rows). Color indicates the expression value of the DEGs (average logFC).</p

Raw gene counts, gene expression values and single cell matrix files used in the study.

Quality control analysis of fastq raw data was performed using FastQC [93]. Reads were aligned to reference genome (hg38) using STAR, and reads were quantified using HTSeq-counts with Gencode annotation v38 and raw counts provided in Table 2a. Differential expression analysis was performed with DESeq. For differential gene expression analyses, the cutoff for significant fold change was >1.5, adjusted p-value Table 2b. Single cell data: After samples were demultiplexed, individual fastq files were subjected to barcode processing and UMI counting using Cell Ranger v2.1.0 (https://support.10xgenomics.com). Each individual library was processed using cellranger count function to generate a gene-barcode matrix for each library and reads aligned to the human reference genome (hg38). Cell barcodes and UMIs associated with the aligned reads were subjected to correction and filtering using an estimation of 3000 recovered cells (—expect-cells 3000). The resulting gene-cell UMI count matrices for each sample were then concatenated into one matrix using the “cellranger aggr” pipeline and files are provided as compressed files in Table 2c. (ZIP)</p