Cancer Associated Fibroblasts: The Architects of Stroma Remodeling

Abstract

Fibroblasts have exceptional phenotypic plasticity and capability to secrete vast amount of soluble factors, extracellular matrix components and extracellular vesicles. While in physiological conditions this makes fibroblasts master regulators of tissue homeostasis and healing of injured tissues, in solid tumors cancer associated fibroblasts (CAFs) co-evolve with the disease, and alter the biochemical and physical structure of the tumor microenvironment, as well as the behavior of the surrounding stromal and cancer cells. Thus CAFs are fundamental regulators of tumor progression and influence response to therapeutic treatments. Increasing efforts are devoted to better understand the biology of CAFs to bring insights to develop complementary strategies to target this cell type in cancer. Here we highlight components of the tumor microenvironment that play key roles in cancer progression and invasion, and provide an extensive overview of past and emerging understanding of CAF biology as well as the contribution that MS-based proteomics has made to this field.

Keywords: blood vessel; cancer; cancer associated fibroblasts; endothelial cell; extracellular matrix; immune system; invasion; proteome; secretome; tumor microenvironment.

Figure 1

Tumor progression. Schematic representation of tumor development with highlighted stromal components that contribute to progression and invasion.

Figure 2

CAF functions. Schematic representation of key CAF functions and CAF‐derived factors involved.

Figure 3

Consensus proteome. Proteins that were found consistently up‐ (red) and downregulated (blue) in the MS‐proteomic comparisons listed in Table 1 between matched CAFs and normal fibroblasts. Protein–protein interactions were define with STRING (version 10.5; all interaction sources were enabled and minimum interaction score of 0.4 was required) and visualized with Cytoscape.

Figure 4

Consensus secretome. Secreted proteins that were consistently identified in the MS‐proteomic analysis of CAF‐derived conditioned media listed in Table 2. Protein–protein interactions were define with STRING (version 10.5; the active interaction sources were “experiments”, “databases”, and “co‐expression”, and minimum interaction score of 0.7 was required) and visualized with Cytoscape.

Figure 5

MS‐proteomics and CAFs. Scheme showing how MS‐proteomics can contribute to understand CAF biology. TME, tumor microenvironment.