Rapid Plastic Deformation of Cancer Cells Correlates with High Metastatic Potential

Viscoelastic Mechanics: From Pathology and Cell Fate to Tissue Regeneration Biomaterial Development

Viscoelasticity is the mechanical feature of living tissues and the cellular extracellular matrix (ECM) and has been recognized as an essential biophysical cue in cell function and fate regulation, tissue development and homeostasis maintenance, and disease progression. These findings provide new insights for the development of biomaterials with comparable viscoelastic properties as native ECMs and the tissue matrix, displaying promising applications in regeneration medicine. In this review, the relationship between matrix viscoelasticity and tissue functions (e.g., development and regeneration) in physiological conditions and disease progression (e.g., aging, degenerative, fibrosis, and tumor) in pathological conditions will be especially highlighted to figure out the potential therapeutic target for disease treatment and inspiration for tissue regeneration related biomaterial development. Furthermore, findings and an understanding of the cell response to ECM viscoelasticity and the mechanism behind it are comprehensively summarized to provide a pathophysiological basis for viscoelastic biomaterials design. The advances of viscoelastic biomaterials on defect tissue repair are also reviewed, suggesting the significance of the native matrix matchable microenvironment on tissue regeneration. Although challenging, tunable viscoelastic biomaterials that match the mechanical properties of native tissues and ECMs show great promise. They could promote tissue regeneration, treat degenerative diseases, and support the development of organoids and artificial organs.

Deformation under flow and morphological recovery of cancer cells

The metastatic cascade includes a blood circulation step for cells detached from the primary tumor. This stage involves significant shear stress as well as large and fast deformation as the cells circulate through the microvasculature. These mechanical stimuli are well reproduced in microfluidic devices. However, the recovery dynamics after deformation is also pivotal to understand how a cell can pass through the multiple capillary constrictions encountered during a single hemodynamic cycle. The microfluidic system developed in this work allows single cell recovery to be studied under flow-free conditions following pressure-actuated cell deformation inside constricted microchannels. We used three breast cancer cell lines - namely MCF-7, SK-BR3 and MDA-MB231 - as cellular models representative of different cancer phenotypes. Changing the size of the constriction allows exploration of moderate to strong deformation regimes, the latter being associated with the formation of plasma membrane blebs. In the regime of moderate deformation, all cell types display a fast elastic recovery behavior followed by a slower viscoelastic regime, well described by a double exponential decay. Among the three cell types, cells of the mesenchymal phenotype, i.e. the MDA-MB231 cells, are softer and the most fluid-like, in agreement with previous studies. Our main finding here is that the fast elastic recovery regime revealed by our novel microfluidic system is under the control of cell contractility ensured by the integrity of the cell cortex. Our results suggest that the cell cortex plays a major role in the transit of circulating tumor cells by allowing their fast morphological recovery after deformation in blood capillaries.

Beyond stiffness: Multiscale viscoelastic features as biomechanical markers for assessing cell types and states

Cell mechanics are pivotal in regulating cellular activities, diseases progression, and cancer development. However, the understanding of how cellular viscoelastic properties vary in physiological and pathological stimuli remains scarce. Here, we develop a hybrid self-similar hierarchical theory-microrheology approach to accurately and efficiently characterize cellular viscoelasticity. Focusing on two key cell types associated with livers fibrosis-the capillarized liver sinusoidal endothelial cells and activated hepatic stellate cells-we uncover a universal two-stage power-law rheology characterized by two distinct exponents, αshort and αlong. The mechanical profiles derived from both exponents exhibit significant potential for discriminating among diverse cells. This finding suggests a potential common dynamic creep characteristic across biological systems, extending our earlier observations in soft tissues. Using a tailored hierarchical model for cellular mechanical structures, we discern significant variations in the viscoelastic properties and their distribution profiles across different cell types and states from the cytoplasm (elastic stiffness E1 and viscosity η), to a single cytoskeleton fiber (elastic stiffness E2), and then to the cell level (transverse expansion stiffness E3). Importantly, we construct a logistic-regression-based machine-learning model using the dynamic parameters that outperforms conventional cell-stiffness-based classifiers in assessing cell states, achieving an area under the curve of 97% vs. 78%. Our findings not only advance a robust framework for monitoring intricate cell dynamics but also highlight the crucial role of cellular viscoelasticity in discerning cell states across a spectrum of liver diseases and prognosis, offering new avenues for developing diagnostic and therapeutic strategies based on cellular viscoelasticity.

A nano-platform combats the "attack" and "defense" of cytoskeleton to block cascading tumor metastasis

The cytoskeleton facilitates tumor cells invasion into the bloodstream via vasculogenic mimicry (VM) for "attack", and protects cells against external threats through cytoskeletal remodeling and tunneling nanotubes (TNTs) for "defense". However, the existing strategies involving cytoskeleton are not sufficient to eliminate tumor metastasis due to mitochondrial energy supply, both within tumor cells and from outside microenvironment. Here, considering the close relationship between cytoskeleton and mitochondria both in location and function, we construct a nano-platform that combats the "attack" and "defense" of cytoskeleton in the cascading metastasis. The nano-platform is composed of KFCsk@LIP and KTMito@LIP for the cytoskeletal collapse and mitochondrial dysfunction. KFCsk@LIP prevents the initiation and circulation of cascading tumor metastasis, but arouses limited suppression in tumor cell proliferation. KTMito@LIP impairs mitochondria to trigger apoptosis and impede energy supply both from inside and outside, leading to an amplified effect for metastasis suppression. Further mechanisms studies reveal that the formation of VM and TNTs are seriously obstructed. Both in situ and circulating tumor cells are disabled. Subsequently, the broken metastasis cascade results in a remarkable anti-metastasis effect. Collectively, based on the nano-platform, the cytoskeletal collapse with synchronous mitochondrial dysfunction provides a potential therapeutic strategy for cascading tumor metastasis suppression.

Inertial Multi-Force Deformability Cytometry for High-Throughput, High-Accuracy, and High-Applicability Tumor Cell Mechanotyping

Previous on-chip technologies for characterizing the cellular mechanical properties often suffer from a low throughput and limited sensitivity. Herein, an inertial multi-force deformability cytometry (IMFDC) is developed for high-throughput, high-accuracy, and high-applicability tumor cell mechanotyping. Three different deformations, including shear deformations and stretch deformations under different forces, are integrated with the IMFDC. The 3D inertial focusing of cells enables the cells to deform by an identical fluid flow, and 10 parameters, such as cell area, perimeter, deformability, roundness, and rectangle deformability, are obtained in three deformations. The IMFDC is able to evaluate the deformability of different cells that are sensitive to different forces on a single chip, demonstrating the high applicability of the IMFDC in analyzing different cell lines. In identifying cell types, the three deformations exhibit different mechanical responses to cells with different sizes and deformability. A discrimination accuracy of ≈93% for both MDA-MB-231 and MCF-10A cells and a throughput of ≈500 cells s-1 can be achieved using the multiple-parameters-based machine learning model. Finally, the mechanical properties of metastatic tumor cells in pleural and peritoneal effusions are characterized, enabling the practical application of the IMFDC in clinical cancer diagnosis.

Dexamethasone Selectively Inhibits Detachment of Metastatic Thyroid Cancer Cells during Random Positioning

We recently reported that synthetic glucocorticoid dexamethasone (DEX) is able to suppress metastasis-like spheroid formation in a culture of follicular thyroid cancer (FTC)-133 cells cultured under random positioning. We now show that this inhibition was selective for two metastatic thyroid carcinoma cells, FTC-133 and WRO, whereas benign Nthy-ori 3-1 thyrocytes and recurrent ML-1 follicular thyroid cancer cells were not affected by DEX. We then compare Nthy-ori 3-1 and FTC-133 cells concerning their adhesion and mechanosignaling. We demonstrate that DEX disrupts random positioning-triggered p38 stress signaling in FTC-133 cells, thereby antagonizing a variety of biological functions. Thus, DEX treatment of FTC-133 cells is associated with increased adhesiveness, which is mainly caused by the restored, pronounced formation of a normal number of tight junctions. Moreover, we show that Nthy-ori 3-1 and ML-1 cells upregulate the anti-adhesion protein mucin-1 during random positioning, presumably as a protection against mechanical stress. In summary, mechanical stress seems to be an important component in this metastasis model system that is processed differently by metastatic and healthy cells. The balance between adhesion, anti-adhesion and cell–cell connections enables detachment of adherent human cells on the random positioning machine—or not, allowing selective inhibition of thyroid in vitro metastasis by DEX.