Remodelling of the fibre-aggregate structure of collagen gels by cancer-associated fibroblasts: a time-resolved grey-tone image analysis based on stochastic modelling

TL;DR

This paper introduces a stochastic modelling approach to analyze the dynamic remodelling of collagen fibre networks by cancer-associated fibroblasts, revealing different densification mechanisms in tumor environments.

Contribution

It presents a novel mathematical modelling and image analysis method tailored for the complex, multiscale collagen network in tumor tissues, enabling detailed spatiotemporal characterization.

Findings

Identified two distinct densification mechanisms near and far from fibroblasts.

Revealed biochemical and mechanical influences on collagen remodelling.

Applied model successfully to time-resolved images of tumor-associated fibroblasts.

Abstract

In solid tumors, cells constantly interact with the surrounding extracellular matrix. In particular cancer-associated fibroblasts modulate the architecture of the matrix by exerting forces and contracting collagen fibres, creating paths that facilitate cancer cell migration. The characterization of the collagen fibre network and its space and time-dependent remodelling is therefore key to investigating the interactions between cells and the matrix, and to understanding tumor growth. The structural complexity and multiscale nature of the collagen network rule out classical image analysis algorithms, and call for specific methods. We propose an approach based on the mathematical modelling of the collagen network, and on the identification of the model parameters from the correlation functions and histograms of grey-tone images. The specific model considered accounts for both the small-scale fibrillar structure of the network and for the presence of large-scale aggregates. When applied to time-resolved images of cancer-associated fibroblasts actively invading a collagen matrix, the method reveals two different densification mechanisms for the matrix in direct contact or far from the cells. The very observation of two distinct phenomenologies hints at diverse mechanisms, which presumably involve both biochemical and mechanical effects.