Inducing and measuring cell forces to improve disease models
Cell behavior is controlled not only by chemical signals but also by mechanical cues from their environment. Rather than being passive agents, cells sense these forces and in turn transmit forces back to remodel the environment. A number of disease processes, such as cancer and heart disease, arise in part due to an imbalance in force sensing and production. This dissertation aims to utilize materials to induce or measure cellular forces in healthy and disease conditions for improved disease modeling. Specifically, we utilized a methacrylated hyaluronic acid (MeHA) hydrogel that can dynamically stiffen in the presence of cells to recapitulate fibrotic remodeling associated with breast cancer progression and cardiac remodeling post infarction.
Mammary epithelial cells (MECs) form and remain as polarized acini but begin to decompose and resemble mesenchymal morphology upon matrix stiffening. The transcription factor Twist, transforming growth factor β (TGFβ), and YAP activation appeared to modulate stiffness-mediated signaling; when stiffness-mediated signals were blocked, collective MEC transformation was reduced in favor of single MECs transforming and migrating away from acini. These data indicates a more complex interplay of time-dependent stiffness signaling, acinar structure, and soluble cues that regulate MEC transformation than previous models suggest.
We next examined how the non-coding 9p21 gene locus regulates cardiac phenotypes associated with fibrotic remodeling. Induced pluripotent stem cell-derived cardiomyocytes (CMs) from patients homozygous for the risk (R/R) or non-risk (N/N) 9p21.3 locus were cultured on a methacrylated hyaluronic acid hydrogel capable of mimicking cardiac fibrotic stiffening. While CMs contracted synchronously in physiological niche independent of genotype, only R/R CMs exhibited asynchronous contractions due to a loss of connexin 43 expression after stiffening. Locus deletion was sufficient to prevent asynchronous contraction by maintaining gap junctions, demonstrating that stem cell technology can be extended beyond modeling of solely genetic disease to include modeling of acquired disease in response to changing environmental conditions.
In addition to the discoveries made with these studies, the methodology utilized here has broad applicability to a number of different diseases, highlighting the value of understanding the role of force induction and generation on cell behavior in the context of disease.