Remodelling of the fibre-aggregate structure of collagen gels by cancer-associated fibroblasts: A time-resolved grey-tone image analysis based on stochastic modelling - Gommes, Cedric J.; Louis, Thomas; Bourgot, Isabelle; Noël, Agnès; Blacher, Silvia; Maquoi, Erik (Frontiers in Immunology, 2023)
Solid tumors consist of tumor cells associated with stromal and immune cells, secreted factors and extracellular matrix (ECM), that together constitute the tumor microenvironment. Among stromal cells, activated fibroblasts, known as cancer-associated fibroblasts (CAFs) are of particular interest. CAFs secrete a plethora of ECM components including collagen and modulate the architecture of the ECM, thereby influencing cancer cell migration. The characterization of the collagen fibre network and its space and time-dependent microstructural modifications is key to investigating the interactions between cells and the ECM. Developing image analysis tools for that purpose is still a challenge because the structural complexity of the collagen network calls for specific statistical descriptors. Moreover, the low signal-to-noise ratio of imaging techniques available for time-resolved studies rules out standard methods based on image segmentation. In this work, we develop a novel approach based on the stochastic modelling of the gel structure and on grey-tone image analysis. The method is then used to study the remodelling of a collagen matrix by migrating breast cancer-derived CAFs in a three-dimensional spheroid model of cellular invasion. Specifically, the structure of the collagen at the scale of a few microns is found to consist in regions with high fibre density separated by depleted regions, which can be thought of as aggregates and pores. The approach we develop captures this two-scale structure with a clipped Gaussian field model to describe the aggregates-and-pores large-scale structure, and a homogeneous Boolean model to describe the small-scale fibre network within the aggregates. The model parameters are identified by fitting the grey-tone histograms and correlation functions of confocal microscopy images. The method applies to unprocessed grey-tone images, and it can therefore be used with low magnification, noisy time-lapse reflectance images. When applied to the spheroid time-resolved images, the method reveals different matrix densification mechanisms for the matrix in direct contact or far from the cells.