Altered mechanical properties of actin fibers due to breast cancer invasion: parameter identification based on micropipette aspiration and multiscale tensegrity modeling

Navigating the Collective: Nanoparticle-Assisted Identification of Leader Cancer Cells During Migration

Cancer-related deaths primarily occur due to metastasis, a process involving the migration and invasion of cancer cells. In most solid tumors, metastasis occurs through collective cell migration (CCM), guided by "cellular leaders". These leader cells generate forces through actomyosin-mediated protrusion and contractility. The cytoskeletal mechanisms employed by metastatic cells during the migration process closely resemble the use of the actin cytoskeleton in endocytosis. In our previous work, we revealed that tumor cells exhibiting high metastatic potential (MP) are more adept at encapsulating 100-200 nm nanoparticles than those with lower MP. The objective of this study was to investigate whether nanoparticle encapsulation could effectively differentiate leader tumor cells during their CCM. To achieve our objectives, we employed a two-dimensional CCM model grounded in the wound-healing ("scratch") assay, utilizing two breast cancer cell lines, MCF7 and MDA-MB-231, which display low and high migratory potential, respectively. We conducted calibration experiments to identify the "optimal time" at which cells exhibit peak speed during wound closure. Furthermore, we carried out experiments to assess nanoparticle uptake, calculating the colocalization coefficient, and employed phalloidin staining to analyze the anisotropy and orientation of actin filaments. The highest activity for low-MP cells was achieved at 2.6 h during the calibration experiments, whereas high-MP cells were maximally active at 3.9 h, resulting in 8% and 11% reductions in wound area, respectively. We observed a significant difference in encapsulation efficiency between leader and peripheral cells for both high-MP (p < 0.013) and low-MP (p < 0.02) cells. Moreover, leader cells demonstrated a considerably higher anisotropy coefficient (p < 0.029), indicating a more organized, directional structure of actin filaments compared to peripheral cells. Thus, nanoparticle encapsulation offers a groundbreaking approach to identifying the most aggressive and invasive leader cells during the CCM process in breast cancer. Detecting these cells is crucial for developing targeted therapies that can effectively curb metastasis and improve patient outcomes.

Viscoelasticity in 3D Cell Culture and Regenerative Medicine: Measurement Techniques and Biological Relevance

The field of mechanobiology is gaining prominence due to recent findings that show cells sense and respond to the mechanical properties of their environment through a process called mechanotransduction. The mechanical properties of cells, cell organelles, and the extracellular matrix are understood to be viscoelastic. Various technologies have been researched and developed for measuring the viscoelasticity of biological materials, which may provide insight into both the cellular mechanisms and the biological functions of mechanotransduction. Here, we explain the concept of viscoelasticity and introduce the major techniques that have been used to measure the viscoelasticity of various soft materials in different length- and timescale frames. The topology of the material undergoing testing, the geometry of the probe, the magnitude of the exerted stress, and the resulting deformation should be carefully considered to choose a proper technique for each application. Lastly, we discuss several applications of viscoelasticity in 3D cell culture and tissue models for regenerative medicine, including organoids, organ-on-a-chip systems, engineered tissue constructs, and tunable viscoelastic hydrogels for 3D bioprinting and cell-based therapies.

Advantages of integrating Brillouin microscopy in multimodal mechanical mapping of cells and tissues

Recent research has highlighted the growing significance of the mechanical properties of cells and tissues in the proper execution of physiological functions within an organism; alterations to these properties can potentially result in various diseases. These mechanical properties can be assessed using various techniques that vary in spatial and temporal resolutions as well as applications. Due to the wide range of mechanical behaviors exhibited by cells and tissues, a singular mapping technique may be insufficient in capturing their complexity and nuance. Consequently, by utilizing a combination of methods-multimodal mechanical mapping-researchers can achieve a more comprehensive characterization of mechanical properties, encompassing factors such as stiffness, modulus, viscoelasticity, and forces. Furthermore, different mapping techniques can provide complementary information and enable the exploration of spatial and temporal variations to enhance our understanding of cellular dynamics and tissue mechanics. By capitalizing on the unique strengths of each method while mitigating their respective limitations, a more precise and holistic understanding of cellular and tissue mechanics can be obtained. Here, we spotlight Brillouin microscopy (BM) as a noncontact, noninvasive, and label-free mechanical mapping modality to be coutilized alongside established mechanical probing methods. This review summarizes some of the most widely adopted individual mechanical mapping techniques and highlights several recent multimodal approaches demonstrating their utility. We envision that future studies aim to adopt multimodal techniques to drive advancements in the broader realm of mechanobiology.

Microfluidic device featuring micro-constrained channels for multi-parametric assessment of cellular biomechanics and high-precision mechanical phenotyping of gastric cells

BACKGROUND

Cellular biomechanics plays a significant role in the regulation of cellular physiological and pathological processes. In recent years, multiple methods have been developed to evaluate cellular biomechanics, such as atomic force microscopy (AFM), micropipette aspiration, and magnetic tweezers. However, most of these methods only focus on a single parameter and cannot automate the process at a high-efficiency level. A novel microfluidic method is necessary to achieve the simultaneous multi-parametric measurement of cellular biomechanics and high-precision cellular mechanical phenotyping at high throughput.

RESULTS

To tackle the issue concerning the low-throughput and cellular single-parameter evaluation, we designed and fabricated a microfluidic chip featuring multiple micro-constrained channels structure, providing a simultaneous multi-parametric assessment of cellular biomechanics, including elastic modulus, recovery capability, and deformability. We compared the biomechanical properties of normal human gastric mucosal epithelial cells (GES-1) and human gastric cancer cells (AGS and MKN-45) by the chip. Results demonstrated that the elastic modulus of GES-1, AGS, and MKN-45 cells decreased sequentially, which was the opposite of their invasiveness and metastasis potential, suggesting the inverse correlation between cellular elastic modulus and malignancy. Meanwhile, the recovery capability and deformability of GES-1, AGS, and MKN-45 cells increased sequentially, demonstrating the positive correlation between cellular deformability and malignancy. Furthermore, multiple parameters were used to distinguish gastric cancer cells from normal gastric cells via machine learning. An accuracy of over 94.8% for identifying gastric cancer cells was achieved.

SIGNIFICANCE

This study provides a deep insight into the biophysical mechanism of gastric cancer metastasis at the single-cell level and possesses great potential to function as a valuable tool for single-cell analysis, thereby facilitating high-precision and high-throughput discrimination of cellular phenotypes that are not easily discernible through single-marker analysis.

Cell deformability heterogeneity recognition by unsupervised machine learning from in-flow motion parameters

Cell deformability is a well-established marker of cell states for diagnostic purposes. However, the measurement of a wide range of different deformability levels is still challenging, especially in cancer, where a large heterogeneity of rheological/mechanical properties is present. Therefore, a simple, versatile and cost-effective recognition method for variable rheological/mechanical properties of cells is needed. Here, we introduce a new set of in-flow motion parameters capable of identifying heterogeneity among cell deformability, properly modified by the administration of drugs for cytoskeleton destabilization. Firstly, we measured cell deformability by identification of in-flow motions, rolling (R), tumbling (T), swinging (S) and tank-treading (TT), distinctively associated with cell rheological/mechanical properties. Secondly, from a pool of motion and structural cell parameters, an unsupervised machine learning approach based on principal component analysis (PCA) revealed dominant features: the local cell velocity (V_Cell/V_Avg), the equilibrium position (Y_Eq) and the orientation angle variation (Δφ). These motion parameters clearly defined cell clusters in terms of motion regimes corresponding to specific deformability. Such correlation is verified in a wide range of rheological/mechanical properties from the elastic cells moving like R until the almost viscous cells moving as TT. Thus, our approach shows how simple motion parameters allow cell deformability heterogeneity recognition, directly measuring rheological/mechanical properties.

Effects of chemically EGFR targeting on non-targeted physical cell behaviors in 2D and 3D microfluidic cultures of invasive and non-invasive breast cancer cell lines

Cancer development comprehends changes in cell structural and physical states. Cancer cells are softer than normal cells, produce higher contractile forces, and migrate more easily. While chemotherapy, targets proteins involved in biological behaviors, it may affect cell physicomechanical state due to the interconnections among signaling pathways. Here we treated non-invasive and invasive breast cancer cell lines by targeting EGRF which modulates major biological behaviors. We quantified migration potential of cancer cells in a microfluidic device, and evaluated expression of proteins associated with physical behaviors. Results indicated significant alterations in physical behaviors, with a higher impact on invasive cells. The anti-cancer synergy between biological and physical behaviors was shown by decreasing actin, vinculin, and myosin II content and altered distribution, limiting cell invasion in 3D collagen structure, accompanied by decreasing cell viability and vimentin expression as the EMT biomarker. The center point of changes in physical behaviors was in cytoskeletal remodeling by chemical treatment, potentially through lower contractile force generation and less development of focal adhesions and stress fibers. The synergy between physical and chemical pathways can be used in enhancing anti-cancer drug efficacy.

Methods for assessment of membrane protrusion dynamics

Membrane protrusions are a critical facet of cell function. Mediating fundamental processes such as cell migration, cell-cell interactions, phagocytosis, as well as assessment and remodeling of the cell environment. Different protrusion types and morphologies can promote different cellular functions and occur downstream of distinct signaling pathways. As such, techniques to quantify and understand the inner workings of protrusion dynamics are critical for a comprehensive understanding of cell biology. In this chapter, we describe approaches to analyze cellular protrusions and correlate physical changes in cell morphology with biochemical signaling processes. We address methods to quantify and characterize protrusion types and velocity, mathematical approaches to predictive models of cytoskeletal changes, and implementation of protein engineering and biosensor design to dissect cell signaling driving protrusive activity. Combining these approaches allows cell biologists to develop a comprehensive understanding of the dynamics of membrane protrusions.