Studies of cell and tissue mechanics have shown that significant changes in cell and tissue mechanics during lesions and cancers are observed, which provides new mechanical markers for disease diagnosis based on machine learning. However, due to the lack of effective mechanic markers, only elastic modulus and iconographic features are currently used as markers, which greatly limits the application of cell and tissue mechanics in disease diagnosis. Here, we develop a liver pathological state classifier through a support vector machine method, based on high dimensional viscoelastic mechanical data. Accurate diagnosis and grading of hepatic fibrosis facilitates early detection and treatment and may provide an assessment tool for drug development. To this end, we used the viscoelastic parameters obtained from the analysis of creep responses of liver tissues by a self-similar hierarchical model and built a liver state classifier based on machine learning. Using this classifier, we implemented a fast classification of healthy, diseased, and mesenchymal stem cells (MSCs)-treated fibrotic live tissues, and our results showed that the classification accuracy of healthy and diseased livers can reach 0.99, and the classification accuracy of the three liver tissues mixed also reached 0.82. Finally, we provide screening methods for markers in the context of massive data as well as high-dimensional viscoelastic variables based on feature ablation for drug development and accurate grading of liver fibrosis. We propose a novel classifier that uses the dynamical mechanical variables as input markers, which can identify healthy, diseased, and post-treatment liver tissues.

The volumes of living cells undergo dynamic changes to maintain the cells\' structural and functional integrity in many physiological processes. Minor fluctuations in cell volume can serve as intrinsic signals that play a crucial role in cell fate determination during mechanotransduction. In this review, we discuss the variability of cell volume and its role in vivo, along with an overview of the mechanisms governing cell volume regulation. Additionally, we provide insights into the current approaches used to control cell volume in vitro. Furthermore, we summarize the biological implications of cell volume regulation and discuss recent advances in understanding the fundamental relationship between cell volume and mechanotransduction. Finally, we delve into the potential underlying mechanisms, including intracellular macromolecular crowding and cellular mechanics, that govern the global regulation of cell fate in response to changes in cell volume. By exploring the intricate interplay between cell volume and mechanotransduction, we underscore the importance of considering cell volume as a fundamental signaling cue to unravel the basic principles of mechanotransduction. Additionally, we propose future research directions that can extend our current understanding of cell volume in mechanotransduction. Overall, this review highlights the significance of considering cell volume as a fundamental signal in understanding the basic principles in mechanotransduction and points out the possibility of controlling cell volume to control cell fate, mitigate disease-related damage, and facilitate the healing of damaged tissues.

Hepatocellular carcinoma (HCC) cells, especially those with metastatic competence, show reduced stiffness compared to the non-malignant counterparts. However, it is still unclear whether and how the mechanics of HCC cells influence their migration and invasion. This study reports that HCC cells with enhanced motility show reduced mechanical stiffness and cytoskeleton, suggesting the inverse correlation between cellular stiffness and motility. Through pharmacologic and genetic approaches, inhibiting actomyosin activity reduces HCC cellular stiffness but promotes their migration and invasion, while activating it increases cell stiffness but impairs cell motility. Actomyosin regulates cell motility through the influence on cellular stiffness. Mechanistically, weakening/strengthening cells inhibits/promotes c-Jun N terminal kinase (JNK) phosphorylation, activation/inhibition of which rescues the effects of cell mechanics on their migration and invasion. Further, HCC cancer stem cells (CSCs) exhibit higher motility but lower stiffness than control cells. Increasing CSC stiffness weakens migration and invasion through the activation of JNK signaling. In conclusion, our findings unveil a new regulatory role of actomyosin-mediated cellular mechanics in tumor cell motility and present new evidence to support that tumor cell softening may be one driving force for HCC metastasis. STATEMENT OF SIGNIFICANCE: Tumor cells progressively become softened during metastasis and low cell stiffness is associated with high metastatic potential. However, it remains unclear whether tumor cell softening is a by-product of or a driving force for tumor progression. This work reports that the stiffness of hepatocellular carcinoma cells is linked to their migration and invasion. Importantly, tumor cell softening promotes migration and invasion, while cell stiffening impairs the mobility. Weakening/strengthening cells inhibits/promotes JNK phosphorylation, activation/inhibition of which rescues the effects of cell mechanics on their migration and invasion ability. Further, stiffening liver cancer stem cells attenuates their motility through activating JNK signaling. In summary, our study uncovers a previously unappreciated role of tumor cell mechanics in migration and invasion and implicates the therapeutic potential of cell mechanics in the mechanotargeting of metastasis.

Using mechanical cues for cancer cells can realize precise control and efficient therapeutic effects. However, the cell cycle-specific response for dynamic mechanical manipulation is barely investigated. Here, RGD-modified iron oxide nanomanipulators were utilized as the intracellular magneto-mechanical transducers to investigate the mechanical impacts on the cell cycle under a dynamic magnetic field for cancer treatment. The G2/M phase was identified to be sensitive to the intracellular magneto-mechanical modulation with a synergistic treatment effect between the pretreatment of cell cycle-specific drugs and the magneto-mechanical destruction, and thus could be an important mechanical-targeted phase for regulation of cancer cell death. Finally, combining the cell cycle-specific drugs with magneto-mechanical manipulation could significantly inhibit glioma and breast cancer growth in vivo. This intracellular mechanical stimulus showed cell cycle-dependent cytotoxicity and could be developed as a spatiotemporal therapeutic modality in combination with chemotherapy drugs for treating deep-seated tumors.

OBJECTIVE: The mechanics of the nucleus depends on cellular structures and architecture, and impact a number of diseases. Nuclear mechanics is yet rather complex due to heterogeneous distribution of dense heterochromatin and loose euchromatin domains, giving rise to spatially variable stiffness properties.
METHODS: In this study, we propose to use the adjoint-based inverse solver to identify for the first time the nonhomogeneous elastic property distribution of the nucleus. Inputs of the inverse solver are deformation fields measured with microscopic imaging in contracting cardiomyocytes.
RESULTS: The feasibility of the proposed method is first demonstrated using simulated data. Results indicate accurate identification of the assumed heterochromatin region, with a maximum relative error of less than 5%. We also investigate the influence of unknown Poisson\'s ratio on the reconstruction and find that variations of the Poisson\'s ratio in the range [0.3-0.5] result in uncertainties of less than 15% in the identified stiffness. Finally, we apply the inverse solver on actual deformation fields acquired within the nuclei of two cardiomyocytes. The obtained results are in good agreement with the density maps obtained from microscopy images.
CONCLUSIONS: Overall, the proposed approach shows great potential for nuclear elastography, with promising value for emerging fields of mechanobiology and mechanogenetics.

Active deformation behavior reflects cell structural dynamics adapting to varying environmental constraints during malignancy progression. In most cases, cell mechanics is characterized by modeling using static equilibrium systems, which fails to comprehend cell deformation behavior leading to inaccuracies in distinguishing cancer cells from normal cells. Here, a method is introduced to measure the active deformation behavior of cancer cells using atomic force microscopy (AFM) and the newly developed deformation behavior cytometry (DBC). During the measurement, cells are deformed and allows a long timescale relaxation (≈5 s). Two parameters are derived to represent deformation behavior: apparent Poisson\'s ratio for adherent cells, which is measured with AFM and refers to the ratio of the lateral strain to the longitudinal strain of the cell, and shape recovery for suspended cells, which is measured with DBC. Active deformation behavior defines cancer cell mechanics better than traditional mechanical parameters (e.g., stiffness, diffusion, and viscosity). Additionally, aquaporins are essential for promoting the deformation behavior, while the actin cytoskeleton acts as a downstream effector. Therefore, the potential application of the cancer cell active deformation behavior as a biomechanical marker or therapeutic target in cancer treatment should be evaluated.

The tumor microenvironment (TME) is crucial in cancer progression, and the extracellular matrix (ECM) is an important TME component. Collagen is a major ECM component that contributes to tumor cell infiltration, expansion, and distant metastasis during cancer progression. Recent studies reported that collagen is deposited in the TME to form a collagen wall along which tumor cells can infiltrate and prevent drugs from working on the tumor cells. Collagen-tumor cell interaction is complex and requires the activation of multiple signaling pathways for biochemical and mechanical signaling interventions. In this review, we examine the effect of collagen deposition in the TME on tumor progression and discuss the interaction between collagen and tumor cells. This review aims to illustrate the functions and mechanisms of collagen in tumor progression in the TME and its role in tumor therapy. The findings indicated collagen in the TME appears to be a better target for cancer therapy.

The self-organization of embryonic stem cells (ESCs) into organized tissues with three distinct germ layers is critical to morphogenesis and early development. While the regulation of this self-organization by soluble signals is well established, the involvement of mechanical force gradients in this process remains unclear due to the lack of a suitable platform to study this process. In this study, we developed a 3D microenvironment to examine the influence of mechanical tension gradients on ESC-patterned differentiation during morphogenesis by controlling the geometrical signals (shape and size) of ESC colonies. We found that changes in colony geometry impacted the germ layer pattern, with Cdx2-positive cells being more abundant at edges and in areas with high curvatures. The differentiation patterns were determined by geometry-mediated cell tension gradients, with an extraembryonic mesoderm-like layer forming in high-tension regions and ectodermal-like lineages at low-tension regions in the center. Suppression of cytoskeletal tension hindered ESC self-organization. These results indicate that geometric confinement-mediated mechanical tension plays a crucial role in linking multicellular organization to cell differentiation and impacting tissue patterning.

Cell mechanics is an emerging field of research for translational medicine. Here, the cell is modeled as poroelastic cytoplasm wrapped by tensile membrane (poroelastic@membrane model) and is characterized by the atomic force microscopy (AFM). The parameters of cytoskeleton network modulus EC , cytoplasmic apparent viscosity ηC , and cytoplasmic diffusion coefficient DC are used to describe the mechanical behavior of cytoplasm, and membrane tension γ is used to evaluate the cell membrane. Poroelastic@membrane analysis of breast cells and urothelial cells show that non-cancer cells and cancer cells have different distribution regions and distribution trends in the four-dimensional space composed of EC , ηC . From non-cancer to cancer cells, there is often a trend of γ, EC , ηC decreases and DC increases. Patients with urothelial carcinoma at different malignant stages can be distinguished at high sensitivity and specificity by analyzing the urothelial cells from tissue or urine. However, sampling directly from tumor tissues is an invasive method, may lead to undesirable consequences. Thus, AFM-based poroelastic@membrane analysis of urothelial cells from urine may provide a non-invasive and no-bio-label method to detecting urothelial carcinoma.

Hyperthermia-induced overexpression of heat shock protein 70 (HSP70) leads to the thermoresistance of cancer cells and reduces the efficiency of photothermal therapy (PTT). In contrast, cancer cell-specific membrane-associated HSP70 has been proven to activate antitumor immune responses. The dual effect of HSP70 on cancer cells inspires us that in-depth research of membrane HSP70 (mHSP70) during PTT treatment is essential. In this work, a PTT treatment platform for human breast cancer cells (MCF-7 cells) based on a mPEG-NH2-modified polydopamine (PDA)-coated gold nanorod core-shell structure (GNR@PDA-PEG) is developed. Using the force-distance curve-based atomic force microscopy (FD-based AFM), we gain insight into the PTT-induced changes in the morphology, mechanical properties, and mHSP70 expression and distribution of individual MCF-7 cells with high-resolution at the single-cell level. PTT treatment causes pseudopod contraction of MCF-7 cells and generates a high level of intracellular reactive oxygen species, which severely disrupt the cytoskeleton, leading to a decrease in cellular mechanical properties. The adhesion maps, which are recorded by aptamer A8 functional probes using FD-based AFM, reveal that PTT treatment causes a significant upregulation of mHSP70 expression and it starts to exhibit a partial aggregation distribution on the MCF-7 cell surface. This work not only exemplifies that AFM can be a powerful tool for detecting changes in cancer cells during PTT treatment but also provides a better view for targeting mHSP70 for cancer therapy.