Multiomic analysis reveals conservation of cancer associated fibroblast phenotypes across species and tissue of origin [multiome]

Cancer associated fibroblasts (CAFs) are integral to the solid tumor microenvironment. Once thought to be a relatively uniform population of matrix-producing cells, the arrival of single cell RNA sequencing has revealed diverse CAF phenotypes. Here, we further probe CAF heterogeneity with a comprehensive multiome approach. Using paired, same-cell chromatin accessibility and transcriptome analysis, we provide an integrated analysis of CAF subpopulations over a complex spatial transcriptomic and proteomic landscape to identify three superclusters – steady state-like (SSL), mechanoresponsive (MR) and immunomodulatory (IM) CAFs. These superclusters are recapitulated across multiple tissue types and species. Selective disruption of underlying mechanical force or immune checkpoint inhibition therapy results in shifts in CAF subpopulation distributions and impacts tumor growth. As such, the balance among CAF superclusters may have considerable translational implications. Collectively, this research expands our understanding of CAF biology, identifying regulatory pathways in CAF differentiation and elucidating novel therapeutic targets in a species- and tumor-agnostic manner. multiomic analysis (scRNA-seq + scATAC-seq of material from the same/paired cells) of unsorted cells from tumor samples from mouse and human breast cancer using the 10X Genomics Multiome platform The raw data for mouse samples have been split into separate samples. GSM6543819-GSM6543827 contains scRNA-seq raw data. GSM6774763-GSM6774771 contains scATAC-seq raw data. Human samples are associated with raw data for both scRNA-seq and scATAC-seq reads.