Fiber density and matrix stiffness modulate distinct cell migration modes in a 3D stroma mimetic composite hydrogel
The peritumoral stroma is a complex 3D tissue that provides cells with myriad biophysical and biochemical cues. Histologic observations suggest that during metastatic spread of carcinomas, these cues influence transformed epithelial cells, prompting a diversity of migration modes spanning single cell and multicellular phenotypes. Purported consequences of these variations in tumor escape strategies include differential metastatic capability and therapy resistance. Therefore, understanding how cues from the peritumoral stromal microenvironment regulate migration mode phenotypes has prognostic and therapeutic value. Here, we utilize a synthetic stromal mimetic in which matrix fiber density and bulk hydrogel stiffness can be orthogonally tuned to investigate the contribution of these two key matrix attributes on MCF10A migration mode phenotypes, epithelial-mesenchymal transition (EMT), and invasive potential. We developed an automated computational image analysis framework to extract migratory phenotypes from fluorescent images and determine 3D migration metrics relevant to metastatic spread. Using this analysis, we find that matrix fiber density and bulk hydrogel stiffness distinctly contribute to a variety of MCF10A migration modes including amoeboid, single mesenchymal, multicellular clusters, and collective strands. Taking advantage of the tunability of this material platform, we identify a combination of physical and soluble cues that induces distinct heterogeneous migration modes originating from the same MCF10A spheroid and use this setting to examine a functional consequence of migration mode - apoptotic resistance. We find that cells migrating as part of collective strands are more resistant to staurosporine-induced apoptosis than either disconnected multicellular clusters or individual invading cells. Improved models of the peritumoral stromal microenvironment that help elucidate relationships between matrix attributes and cell migration mode can contribute to ongoing efforts to identify efficacious cancer therapeutics that address migration plasticity-based therapy resistances.