An official website of the United States government
Abstract Cell shape is linked to cell function. The significance of cell morphodynamics, namely the temporal fluctuation of cell shape, is much less understood. Here we study the morphodynamics of MDA-MB-231 cells in type I collagen extracellular matrix (ECM). We systematically vary ECM physical properties by tuning collagen concentrations, alignment, and gelation temperatures. We find that morphodynamics of 3D migrating cells are externally controlled by ECM mechanics and internally modulated by Rho/ROCK-signaling. We employ machine learning to classify cell shape into four different morphological phenotypes, each corresponding to a distinct migration mode. As a result, we map cell morphodynamics at mesoscale into the temporal evolution of morphological phenotypes. We characterize the mesoscale dynamics including occurrence probability, dwell time and transition matrix at varying ECM conditions, which demonstrate the complex phenotype landscape and optimal pathways for phenotype transitions. In light of the mesoscale dynamics, we show that 3D cancer cell motility is a hidden Markov process whereby the step size distributions of cell migration are coupled with simultaneous cell morphodynamics. Morphological phenotype transitions also facilitate cancer cells to navigate non-uniform ECM such as traversing the interface between matrices of two distinct microstructures. In conclusion, we demonstrate that 3D migrating cancer cells exhibit rich morphodynamics that is controlled by ECM mechanics, Rho/ROCK-signaling, and regulate cell motility. Our results pave the way to the functional understanding and mechanical programming of cell morphodynamics as a route to predict and control 3D cell motility.
more »
« less
This content will become publicly available on April 24, 2026
Representation of high-dimensional cell morphology and morphodynamics in 2D latent space
Abstract The morphology and morphodynamics of cells as important biomarkers of the cellular state are widely appreciated in both fundamental research and clinical applications. Quantification of cell morphology often requires a large number of geometric measures that form a high-dimensional feature vector. This mathematical representation creates barriers to communicating, interpreting, and visualizing data. Here, we develop a deep learning-based algorithm to project 13-dimensional (13D) morphological feature vectors into 2-dimensional (2D) morphological latent space (MLS). We show that the projection has less than 5% information loss and separates the different migration phenotypes of metastatic breast cancer cells. Using the projection, we demonstrate the phenotype-dependent motility of breast cancer cells in the 3D extracellular matrix, and the continuous cell state change upon drug treatment. We also find that dynamics in the 2D MLS quantitatively agrees with the morphodynamics of cells in the 13D feature space, preserving the diffusive power and the Lyapunov exponent of cell shape fluctuations even though the dimensional reduction projection is highly nonlinear. Our results suggest that MLS is a powerful tool to represent and understand the cell morphology and morphodynamics.
more »
« less
- Award ID(s):
- 1844627
- PAR ID:
- 10615446
- Publisher / Repository:
- IOP Publishing Ltd
- Date Published:
- Journal Name:
- Physical Biology
- Volume:
- 22
- Issue:
- 3
- ISSN:
- 1478-3967
- Page Range / eLocation ID:
- 036001
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Contact guidance is a major physical cue that modulates cancer cell morphology and motility, and is directly linked to the prognosis of cancer patients. Under physiological conditions, particularly in the three-dimensional (3D) extracellular matrix (ECM), the disordered assembly of fibers presents a complex directional bias to the cells. It is unclear how cancer cells respond to these noncoherent contact guidance cues. Here we combine quantitative experiments, theoretical analysis, and computational modeling to study the morphological and migrational responses of breast cancer cells to 3D collagen ECM with varying degrees of fiber alignment. We quantify the strength of contact guidance using directional coherence of ECM fibers, and find that stronger contact guidance causes cells to polarize more strongly along the principal direction of the fibers. Interestingly, sensitivity to contact guidance is positively correlated with cell aspect ratio, with elongated cells responding more strongly to ECM alignment than rounded cells. Both experiments and simulations show that cell–ECM adhesions and actomyosin contractility modulate cell responses to contact guidance by inducing a population shift between rounded and elongated cells. We also find that cells rapidly change their morphology when navigating the ECM, and that ECM fiber coherence modulates cell transition rates between different morphological phenotypes. Taken together, we find that subcellular processes that integrate conflicting mechanical cues determine cell morphology, which predicts the polarization and migration dynamics of cancer cells in 3D ECM.more » « less
-
Collagen I is the primary extracellular matrix component of most solid tumors and influences metastatic progression. Collagen matrix engineering techniques are useful for understanding how this complex biomaterial regulates cancer cell behavior and for improving in vitro cancer models. Here, we establish an approach to tune collagen fibril architecture using PEG as an inert molecular crowding agent during gelation and cell embedding. We find that crowding produces matrices with tighter fibril networks that are less susceptible to proteinase mediated degradation, but does not significantly alter matrix stiffness. The resulting matrices have the effect of preventing cell spreading, confining cells, and reducing cell contractility. Matrix degradability and fibril length are identified as strong predictors of cell confinement. Further, the degree of confinement predicts whether breast cancer cells will ultimately undergo individual or collective behaviors. Highly confined breast cancer cells undergo morphogenesis to form either invasive networks reminiscent of aggressive tumors or gland and lobule structures reminiscent of normal breast epithelia. This morphological transition is accompanied by expression of cell–cell adhesion genes, including PECAM1 and ICAM1. Our study suggests that cell confinement, mediated by matrix architecture, is a design feature that tunes the transcriptional and morphogenic state of breast cancer cells.more » « less
-
Engineered three-dimensional (3D) cell culture models can accelerate drug discovery, and lead to new fundamental insights in cell–cell, cell–extracellular matrix (ECM), and cell–biomolecule interactions. Existing hydrogel or scaffold-based approaches for generating 3D tumor models do not possess significant tunability and possess limited scalability for high throughput drug screening. We have developed a new library of hydrogels, called Amikagels, which are derived from the crosslinking of amikacin hydrate (AH) and poly(ethylene glycol) diglycidyl ether (PEGDE). Here we describe the use of Amikagels for generating 3D tumor microenvironments (3DTMs) of breast cancer cells. Biological characteristics of these breast cancer 3DTMs, such as drug resistance and hypoxia were evaluated and compared to those of two-dimensional (2D) monolayer cultures. Estrogen receptor (ER) positive breast cancer 3DTMs formed on Amikagels were more dormant compared to their respective 2D monolayer cultures. Relative to their respective 2D cultures, breast cancer 3DTMs were resistant to cell death induced by mitoxantrone and doxorubicin, which are commonly used chemotherapeutic drugs in cancer, including breast cancer. The drug resistance seen in 3DTMs was correlated with hypoxia seen in these cultures but not in 2D monolayer cultures. Inhibition of Mucin 1 (MUC1), which is overexpressed in response to hypoxia, resulted in nearly complete cell death of 2D monolayer and 3DTMs of breast cancer. Combination of an ER stress inducer and MUC1 inhibition further enhanced cell death in 2D monolayer and 3DTMs. Taken together, this study shows that the Amikagel platform represents a novel technology for the generation of physiologically relevant 3DTMs in vitro and can serve as a platform to discover novel treatments for drug-resistant breast cancer.more » « less
-
Abstract Fibroblasts are an abundant cell type in tumor microenvironments. Activated fibroblasts, known as carcinoma‐associated fibroblasts (CAFs), interact with cancer cells through biochemical signaling and render cancer cells proliferative, invasive, and resistant to therapeutics. Targeting CAFs–cancer cells interactions offers a strategy to block cancer progression. 2D and 3D co‐cultures of human mammary fibroblasts and triple negative breast cancer (TNBC) cells are used to investigate the impact of heterotypic cellular interactions on the proliferation of matrix invasion of TNBC cells. The results show that fibroblasts secreting a chemokine, CXCL12, significantly enhance proliferation of TNBC cells expressing the chemokine receptor, CXCR4. Disrupting this interaction with a receptor antagonist normalizes cancer cell proliferation to that of a co‐culture model lacking this signaling. When co‐culture spheroids are embedded in collagen, fibroblasts producing CXCL12 promote collagen invasion of TNBC cells. Although co‐cultures containing normal fibroblasts also lead to TNBC cell spreading into the matrix, a morphological analysis of cells and inhibition of chemokine‐receptor signaling shows that this spreading is due to the incompatibility of fibroblasts and cancer cells leading to the segregation of the two cell types from the spheroid.more » « less
