Back

High-resolution integrative analysis allows characterization and spatial annotation of normal and cancer-associated colon fibroblasts

Viitala, E. W.; Salminen, E.; Miihkinen, M.; Chalkidi, N.; Stavropoulou, A.; Lemmetyinen, T. T.; Päivinen, P.; Kaprio, T.; Hagström, J.; Haglund, C.; Mäkelä, T. P.; Aittokallio, T.; Katajisto, P.; Koliaraki, V.; Ollila, S.

2025-07-31 cancer biology
10.1101/2025.07.29.667377 bioRxiv
Show abstract

Fibroblasts represent key regulators of colon homeostasis, and cancer-associated fibroblasts (CAFs) play pivotal roles in colorectal cancer (CRC). Despite their critical influence, a consensus view of adult human colon fibroblast and CRC CAF heterogeneity, spatial organization, and developmental trajectories is currently lacking. Here, we address this gap by performing a comprehensive characterization of colonic fibroblasts and CRC CAFs. Using large-scale integration of single-cell RNA-sequencing datasets from normal colon and CRC we mapped the fibroblast subpopulations. Spatial transcriptomics, immunohistochemistry, and in situ hybridization were used for validation and computational analyses to predict developmental trajectories and transcription factors underlying CAF activation. Subepithelial myofibroblasts (SEMFs), mucosa-associated fibroblasts (MAFs), and submucosa-associated fibroblasts (SAFs) were identified as the main colon fibroblast subtypes, and in mice, further divided into location-based subclusters. We also identified a novel colon fibroblast subset: muscle-embedded interstitial fibroblasts (MIFs). CRCs contained normal fibroblasts as well as four cancer-specific CAF populations: inflammatory CAFs (iCAFs), matrix CAFs (mCAFs), and two precursor CAF (preCAF) subtypes. Our data suggested that iCAFs originate from SEMFs through a preCAF1 intermediate phenotype, while mCAFs derive from SAFs/MIFs via preCAF2s. Transcription factors PRRX1, MAFB, and TWIST1 were uncovered as potential regulators of CAF identity and CTHRC1 was identified as a specific and sensitive pan-CAF marker in CRC. Our study presents a detailed framework for understanding colon fibroblast and CRC CAF heterogeneity. This work lays the groundwork for future research into the roles and potential therapeutic relevance of different CRC CAF subsets.

Matching journals

The top 13 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.