Cancer-associated fibroblasts (CAFs) are a major constituent of the tumor microenvironment, although their origin and roles in shaping disease initiation, progression and treatment response remain unclear due to significant heterogeneity. Here, following a negative selection strategy combined with single-cell RNA sequencing of 768 transcriptomes of mesenchymal cells from a genetically engineered mouse model of breast cancer, Lund University researchers define three distinct subpopulations of CAFs. Validation at the transcriptional and protein level in several experimental models of cancer and human tumors reveal spatial separation of the CAF subclasses attributable to different origins, including the peri-vascular niche, the mammary fat pad and the transformed epithelium. Gene profiles for each CAF subtype correlate to distinctive functional programs and hold independent prognostic capability in clinical cohorts by association to metastatic disease. In conclusion, the improved resolution of the widely defined CAF population opens the possibility for biomarker-driven development of drugs for precision targeting of CAFs.
Unbiased clustering of fibroblast single cell transcriptomic data reveals four populations
a Schematic representation of negative selection strategy removing CD31+, CD45+, NG2+, and EPCAM+ cells. b Gating strategy and quantification of flow cytometry for single cell sequencing. After gating out doublets and DAPI+ dead cells, EpCAM−CD31−CD45−NG2− CAFs made up 2.5% of the cells. FSC forward scatter, SSC side scatter. For single marker staining see also Supplementary Figure 1. c Violin plot of detected genes in 784 sorted fibroblasts. d t-SNE layout of CAFs (n = 716) by RPKM-normalized transcriptomic data. Colors represent clusters assigned by DBSCAN. e Expression plots on t-SNE layout. log2(RPKM + 1) levels of CAF marker genes in individual cells. f Cell size and granularity as determined by forward-scattered light (FSC) and side-scattered light (SSC) of different CAF populations