Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing

TLDR

Cancer‑associated fibroblasts (CAFs) are a major component of the tumor microenvironment, yet their origins and roles in disease initiation, progression, and treatment response remain unclear due to heterogeneity. The study aims to define three distinct CAF subpopulations in a genetically engineered mouse model of breast cancer. Using negative selection and single‑cell RNA sequencing of 768 mesenchymal cell transcriptomes, the authors identified the CAF subpopulations. The CAF subclasses are spatially distinct, arise from peri‑vascular, mammary fat pad, and transformed epithelium niches, exhibit unique functional programs, and independently predict metastatic disease, highlighting opportunities for biomarker‑driven precision targeting.

Abstract

Abstract 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, we 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.