论文标题
通过癌症相关的成纤维细胞重塑胶原蛋白凝胶的纤维凝集结构:基于随机建模的时间分辨灰色图像分析
Remodelling of the fibre-aggregate structure of collagen gels by cancer-associated fibroblasts: a time-resolved grey-tone image analysis based on stochastic modelling
论文作者
论文摘要
在实体瘤中,细胞不断与周围的细胞外基质相互作用。特别是与癌症相关的成纤维细胞通过施加力和收缩胶原蛋白纤维来调节基质的结构,从而产生促进癌细胞迁移的途径。因此,胶原纤维网络及其空间和时间依赖性重塑的表征是研究细胞与基质之间的相互作用以及理解肿瘤生长的关键。胶原蛋白网络的结构复杂性和多规律性质排除了经典的图像分析算法,并呼吁采用特定方法。我们提出了一种基于胶原蛋白网络的数学建模以及从灰色图像的相关函数和直方图的模型参数识别的方法。该特定模型考虑了网络的小规模纤维结构和大规模聚集体的存在。当应用于积极入侵胶原基质的癌症相关成纤维细胞的时间分辨图像时,该方法揭示了直接接触或远离细胞的基质的两种不同的致密机制。对两种不同现象的观察到了不同的机制,可能涉及生化和机械效应。
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.