Integrated image-processing and transcriptomic analysis of cancer-associated fibroblasts (CAFs) in breast cancer subtypes

The tumor microenvironment (TME) plays an important role in driving cancer progression and affecting treatment efficacy. Cellular components of the TME include various immune subsets (tumor infiltrating lymphocytes (TILs) and macrophages), cancer-associated fibroblasts (CAFs) and vascular cells. While immune lineage has been a main focus of intensive research on the TME, CAFs have also been shown to be highly heterogeneous in their molecular phenotype and function. Using a protein marker immunofluorescence multiplexing system (Cell DIVE, Leica Microsystems) and quantitative imaging tools, we investigated the identity of various CAF clusters based on the expression of alpha-Smooth Muscle Actin (alpha SMA) and Fibroblast Activation Protein (FAP), and compared their distributions across breast cancer subtypes. We determined the cell counts of various CAF subsets using binary counting and identified the heterogeneous presentations of clusters using K-means clustering and Uniform Manifold Approximation and Projection (UMAP). We found that the abundance of CAF clusters varied among breast cancer subtypes. An integrated analysis of CAF cluster composition in each cancer and the transcriptomic data of CAF-associated genes such as CD29, IL6 and PDGFR beta was performed. We observed increased densities of proliferative, alpha SMA-positive CAFs in basal-like breast cancers that exhibited a co-expression signature of CAF-associated genes. Finally, an association analysis of CAF cluster composition and gene expression with previously identified radiomic phenotype was performed, but significant correlation was not detected.