Abstract

Solid tumor progression is significantly influenced by interactions between cancer cells and the surrounding extracellular matrix (ECM). Specifically, the cancer cell-driven changes to ECM fiber alignment and collagen deposition impact tumor growth and metastasis. Current methods of quantifying these processes are incomplete, require simple or artificial matrixes, rely on uncommon imaging techniques, preclude the use of biological and technical replicates, require destruction of the tissue, or are prone to segmentation errors. We present a set of methodological solutions to these shortcomings that were developed to quantify these processes in cultured, ex vivo human breast tissue under the influence of breast cancer cells and allow for the study of ECM in primary breast tumors. Herein, we describe a method of quantifying fiber alignment that can analyze complex native ECM from scanning electron micrographs that does not preclude the use of replicates and a high-throughput mechanism of quantifying collagen content that is non-destructive. The use of these methods accurately recapitulated cancer cell-driven changes in fiber alignment and collagen deposition observed by visual inspection. Additionally, these methods successfully identified increased fiber alignment in primary human breast tumors when compared to human breast tissue and increased collagen deposition in lobular breast cancer when compared to ductal breast cancer. The successful quantification of fiber alignment and collagen deposition using these methods encourages their use for future studies of ECM dysregulation in human solid tumors.

Highlights

  • The extracellular matrix (ECM) is a complex network of macromolecules which provides biochemical and biomechanical signals that govern cell behavior (Walker et al, 2018)

  • MDA-MB-231 breast cancer cells were seeded into the minced breast tissue. 300 μL of the BC cell-breast tissue mixture was aliquoted onto bottom layer cell sheets

  • Segmentation of fibers can be done via the Waikato Environment for Knowledge Analysis (WEKA)-DJ method in which the WEKA Trainable Segmentation (WTS) Tool is used prior to analysis by DiameterJ

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Summary

Introduction

The extracellular matrix (ECM) is a complex network of macromolecules which provides biochemical and biomechanical signals that govern cell behavior (Walker et al, 2018). The three primary gaps are: (1) a lack of methods to visualize and quantify fiber alignment changes in common ECM images such as those captured by scanning electron microscopy (SEM); (2) the absence of generalized statistical methods to combine and analyze fiber alignment frequency distributions across multiple samples; and (3) a lack of methods to reliably and accurately quantify changes in the collagen content of light microscopy images. Together, these gaps inhibit the study of ECM in human solid tumors

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