Electrodeformation-Based Biomechanical Chip for Quantifying Global Viscoelasticity of Cancer Cells Regulated by Cell Cycle

Biophysical phenotyping of single-cell based on impedance and application for individualized precision medicine

Single-cell biophysical characterization based on impedance measurement is an advantageous approach due to its label-free, high-efficiency, cost-effective and real-time capability. Biophysical phenotyping can yield timely and rich information on physiological and pathological state of cells for disease diagnosis, drug screening, precision medicine, etc. However, precise measurement on single-cell impedance is challenging, particularly hard to figure out the detailed biophysical parameters of single cell due to coupling and complexity of impedance model. Here, we propose an analytic determination method to decode single-cell electrophysiological parameters (including cell-substrate interface capacitance, cell membrane capacitance, cell membrane conductivity, and cytoplasm conductivity) from the impedances measured at optimized frequencies by using analytic solution rather than spectrum fitting. With this simple and fast analytic solution method, the physiological parameters of single cell in natural adhesion state can be accurately determined in real time. We validate this cell parameter determination method in monitoring the change of cell adhesion under hydraulic effects and exploring electrophysiological differences among MCF-7, HeLa, Huh7, and MDA-MB-231 cell lines. Particularly, we apply the approach to optimize tumor treating fields (TTFields) therapy, realizing individualized precision medicine. Our work provides an accurate and efficient approach for characterizing single-cell biophysical properties with real-time, in-situ, label-free, and less invasive advantages.

Microfluidic characterization of single-cell biophysical properties and the applications in cancer diagnosis

Single-cell biophysical properties play a crucial role in regulating cellular physiological states and functions, demonstrating significant potential in the fields of life sciences and clinical diagnostics. Therefore, over the last few decades, researchers have developed various detection tools to explore the relationship between the biophysical changes of biological cells and human diseases. With the rapid advancement of modern microfabrication technology, microfluidic devices have quickly emerged as a promising platform for single-cell analysis offering advantages including high-throughput, exceptional precision, and ease of manipulation. Consequently, this paper provides an overview of the recent advances in microfluidic analysis and detection systems for single-cell biophysical properties and their applications in the field of cancer. The working principles and latest research progress of single-cell biophysical property detection are first analyzed, highlighting the significance of electrical and mechanical properties. The development of data acquisition and processing methods for real-time, high-throughput, and practical applications are then discussed. Furthermore, the differences in biophysical properties between tumor and normal cells are outlined, illustrating the potential for utilizing single-cell biophysical properties for tumor cell identification, classification, and drug response assessment. Lastly, we summarize the limitations of existing microfluidic analysis and detection systems in single-cell biophysical properties, while also pointing out the prospects and future directions of their applications in cancer diagnosis and treatment.

High throughput cell mechanotyping of cell response to cytoskeletal modulations using a microfluidic cell deformation system

Cellular mechanical properties influence cellular functions across pathological and physiological systems. The observation of these mechanical properties is limited in part by methods with a low throughput of acquisition or with low accessibility. To overcome these limitations, we have designed, developed, validated, and optimized a microfluidic cellular deformation system (MCDS) capable of mechanotyping suspended cells on a population level at a high throughput rate of ∼300 cells pers second. The MCDS provides researchers with a viable method for efficiently quantifying cellular mechanical properties towards defining prognostic implications of mechanical changes in pathology or screening drugs to modulate cytoskeletal integrity.

Critical review of single-cell mechanotyping approaches for biomedical applications

Accurate mechanical measurements of cells has the potential to improve diagnostics, therapeutics and advance understanding of disease mechanisms, where high-resolution mechanical information can be measured by deforming individual cells. Here we evaluate recently developed techniques for measuring cell-scale stiffness properties; while many such techniques have been developed, much of the work examining single-cell stiffness is impacted by difficulties in standardization and comparability, giving rise to large variations in reported mechanical moduli. We highlight the role of underlying mechanical theories driving this variability, and note opportunities to develop novel mechanotyping devices and theoretical models that facilitate convenient and accurate mechanical characterisation. Moreover, many high-throughput approaches are confounded by factors including cell size, surface friction, natural population heterogeneity and convolution of elastic and viscous contributions to cell deformability. We nevertheless identify key approaches based on deformability cytometry as a promising direction for further development, where both high-throughput and accurate single-cell resolutions can be realized.

Molecular Rotors: Fluorescent Sensors for Microviscosity and Conformation of Biomolecules

The viscosity and crowding of biological environment are considered vital for the correct cellular function, and alterations in these parameters are known to underly a number of pathologies including diabetes, malaria, cancer and neurodegenerative diseases, to name a few. Over the last decades, fluorescent molecular probes termed molecular rotors proved extremely useful for exploring viscosity, crowding, and underlying molecular interactions in biologically relevant settings. In this review, we will discuss the basic principles underpinning the functionality of these probes and will review advances in their use as sensors for lipid order, protein crowding and conformation, temperature and non-canonical nucleic acid structures in live cells and other relevant biological settings.

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.

Arresting the G2/M phase empowers synergy in magnetic nanomanipulator-based cancer mechanotherapy and chemotherapy

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.

Viscoelastic-Sorting Integrated Deformability Cytometer for High-Throughput Sorting and High-Precision Mechanical Phenotyping of Tumor Cells

The counts and phenotypes of circulating tumor cells (CTCs) in whole blood are useful for disease monitoring and prognostic assessment of cancer. However, phenotyping CTCs in the blood is difficult due to the presence of a large number of background blood cells, especially some blood cells with features similar to those of tumor cells. Herein, we presented a viscoelastic-sorting integrated deformability cytometer (VSDC) for high-throughput label-free sorting and high-precision mechanical phenotyping of tumor cells. A sorting chip for removing large background blood cells and a detection chip for detecting multiple cellular mechanical properties were integrated into our VSDC. Our VSDC has a sorting efficiency and a purity of over 95% and over 81% for tumor cells, respectively. Furthermore, multiple mechanical parameters were used to distinguish tumor cells from white blood cells using machine learning. An accuracy of over 97% for identifying tumor cells was successfully achieved with the highest identification accuracy of 99.4% for MCF-7 cells. It is envisioned that our VSDC will open up new avenues for high-throughput and label-free single-cell analysis in various biomedical applications.

Measuring cell deformation by microfluidics

Microfluidics is an increasingly popular method for studying cell deformation, with various applications in fields such as cell biology, biophysics, and medical research. Characterizing cell deformation offers insights into fundamental cell processes, such as migration, division, and signaling. This review summarizes recent advances in microfluidic techniques for measuring cellular deformation, including the different types of microfluidic devices and methods used to induce cell deformation. Recent applications of microfluidics-based approaches for studying cell deformation are highlighted. Compared to traditional methods, microfluidic chips can control the direction and velocity of cell flow by establishing microfluidic channels and microcolumn arrays, enabling the measurement of cell shape changes. Overall, microfluidics-based approaches provide a powerful platform for studying cell deformation. It is expected that future developments will lead to more intelligent and diverse microfluidic chips, further promoting the application of microfluidics-based methods in biomedical research, providing more effective tools for disease diagnosis, drug screening, and treatment.

High-Throughput Electromechanical Coupling Chip Systems for Real-Time 3D Invasion/Migration Assay of Cells

Cell invasion/migration through three-dimensional (3D) tissues is not only essential for physiological/pathological processes, but a hallmark of cancer malignancy. However, how to quantify spatiotemporal dynamics of 3D cell migration/invasion is challenging. Here, this work reports a 3D cell invasion/migration assay (3D-CIMA) based on electromechanical coupling chip systems, which can monitor spatiotemporal dynamics of 3D cell invasion/migration in a real-time, label-free, nondestructive, and high-throughput way. In combination with 3D topological networks and complex impedance detection technology, this work shows that 3D-CIMA can quantitively characterize collective invasion/migration dynamics of cancer cells in 3D extracellular matrix (ECM) with controllable biophysical/biomechanical properties. More importantly, this work further reveals that it has the capability to not only carry out quantitative evaluation of anti-tumor drugs in 3D microenvironments that minimize the impact of cell culture dimensions, but also grade clinical cancer specimens. The proposed 3D-CIMA offers a new quantitative methodology for investigating cell interactions with 3D extracellular microenvironments, which has potential applications in various fields like mechanobiology, drug screening, and even precision medicine.

Computer-Vision-Based Dielectrophoresis Mobility Tracking for Characterization of Single-Cell Biophysical Properties

Fast and precise measurements of live single-cell biophysical properties is significant in disease diagnosis, cytopathologic analysis, etc. Existing methods still suffer from unsatisfied measurement accuracy and low efficiency. We propose a computer vision method to track cell dielectrophoretic movements on a microchip, enabling efficient and accurate measurement of biophysical parameters of live single cells, including cell radius, cytoplasm conductivity, and cell-specific membrane capacitance, and in situ extraction of cell texture features. We propose a prediction-iteration method to optimize the cell parameter measurement, achieving high accuracy (less than 0.79% error) and high efficiency (less than 30 s). We further propose a hierarchical classifier based on a support vector machine and implement cell classification using acquired cell physical parameters and texture features, achieving high classification accuracies for identifying cell lines from different tissues, tumor and normal cells, different tumor cells, different leukemia cells, and tumor cells with different malignancies. The method is label-free and biocompatible, allowing further live cell studies on a chip, e.g., cell therapy, cell differentiation, etc.

Controlled Intracellular Polymerization for Cancer Treatment

Numerous prodrugs have been developed and used for cancer treatments to reduce side effects and promote efficacy. In this work, we have developed a new photoactivatable prodrug system based on intracellular photoinduced electron transfer-reversible addition-fragmentation chain-transfer (PET-RAFT) polymerization. This unique polymerization process provided a platform for the synthesis of structure-predictable polymers with well-defined structures in living cells. The intracellularly generated poly(N,N-dimethylacrylamide)s were found to induce cell cycle arrest, apoptosis, and necroptosis, inhibit cell proliferation, and reduce cancer cell motilities. This polymerization-based "prodrug" system efficiently inhibits tumor growth and metastasis both in vitro and in vivo and will promote the development of targeted and directed cancer chemotherapy.

Integration of electrotaxis and durotaxis in cancer cells: Subtle nonlinear responses to electromechanical coupling cues

Cells in living organisms live in multiphysics-coupled environments. There is growing evidence indicating that both exogenous electric field (EEF) and extracellular stiffness gradient (ESG) can regulate directional movement of cells, which are known as electrotaxis and durotaxis, respectively. How single cells respond to the ubiquitous electromechanical coupling cues, however, remains mysterious. Using microfluidic chip-based methodology and finite element-based electromechanical coupling design strategies, we develope an electromechanical coupling microchip system, enabling us to quantitatively investigate polarization and directional migration governed by EEF and ESG at the single cell level. It is revealed that both of electrotaxis and durotaxis nonlinearly depend on the physiological EEF and ESG, respectively. Specific combinations of EEF and ESG can subtly modify the polarization states of single cells and thus induce hyperpolarization and depolarization. Cells can integrate electrotaxis and durotaxis in response to multi-cue microenvironments via subtle mechanisms involving cooperation and competition during cellular electrosensing and mechanosensing. The work offers a platform for quantifying migration and polarization of cells driven by electromechanical cues, which is essential not only for elucidating physiological and pathological processes like embryo development, and invasion and metastasis of cancer cells, but for manipulating cell behaviors in a controllable and programmable fashion.

Single-cell mechanical analysis and tension quantification via electrodeformation relaxation

The mechanical behavior and cortical tension of single cells are analyzed using electrodeformation relaxation. Four types of cells, namely, MCF-10A, MCF-7, MDA-MB-231, and GBM, are studied, with pulse durations ranging from 0.01 to 10 s. Mechanical response in the long-pulse regime is characterized by a power-law behavior, consistent with soft glassy rheology resulting from unbinding events within the cortex network. In the subsecond short-pulse regime, a single timescale well describes the process and indicates the naive tensioned (prestressed) state of the cortex with minimal force-induced alteration. A mathematical model is employed and the simple ellipsoidal geometry allows for use of an analytical solution to extract the cortical tension. At the shortest pulse of 0.01 s, tensions for all four cell types are on the order of 10^{-2} N/m.

Characterization of Single-Cell Osmotic Swelling Dynamics for New Physical Biomarkers

Characterization of cell physical biomarkers is vital to understand cell properties and applicable for disease diagnostics. Current methods used to analyze physical phenotypes involve external forces to deform the cells. Alternatively, internal tension forces via osmotic swelling can also deform the cells. However, an established assumption contends that the forces generated during hypotonic swelling concentrated on the plasma membrane are incapable of assessing the physical properties of nucleated cells. Here, we utilized an osmotic swelling approach to characterize different types of nucleated cells. Using a microfluidic device for cell trapping arrays with truncated hanging micropillars (CellHangars), we isolated single cells and evaluated the swelling dynamics during the hypotonic challenge at 1 s time resolution. We demonstrated that cells with different mechanical phenotypes showed unique swelling dynamics signature. Different types of cells can be classified with an accuracy of up to ∼99%. We also showed that swelling dynamics can detect cellular mechanical property changes due to cytoskeleton disruption. Considering its simplicity, swelling dynamics offers an invaluable label-free physical biomarker for cells with potential applications in both biological studies and clinical practice.

Determination of Dielectric Properties of Cells using AC Electrokinetic-based Microfluidic Platform: A Review of Recent Advances

Cell dielectric properties, a type of intrinsic property of cells, can be used as electrophysiological biomarkers that offer a label-free way to characterize cell phenotypes and states, purify clinical samples, and identify target cancer cells. Here, we present a review of the determination of cell dielectric properties using alternating current (AC) electrokinetic-based microfluidic mechanisms, including electro-rotation (ROT) and dielectrophoresis (DEP). The review covers theoretically how ROT and DEP work to extract cell dielectric properties. We also dive into the details of differently structured ROT chips, followed by a discussion on the determination of cell dielectric properties and the use of these properties in bio-related applications. Additionally, the review offers a look at the future challenges facing the AC electrokinetic-based microfluidic platform in terms of acquiring cell dielectric parameters. Our conclusion is that this platform will bring biomedical and bioengineering sciences to the next level and ultimately achieve the shift from lab-oriented research to real-world applications.

Responses of Cellular Adhesion Strength and Stiffness to Fluid Shear Stress during Tumor Cell Rolling Motion

Biochemical and physical factors affect the rolling of tumor cells across the blood vessel. The biochemical factors have been well studied, while the influence of physical factors such as fluid shear stress (FSS) remains poorly understood. Here, human glioma cells (U87 cells) in a straight microfluidic channel were exposed to FSS (0.12, 1.2, and 1.8 dyn/cm²); and their locomotion behaviors from crawling-to-rolling and changes in cellular morphology (concave, elongated, less elongated, and round) were observed. The adhesion strength and stiffness of the cells of different morphologies were analyzed using a live single-cell extractor and atomic force microscopy, respectively. In general, the FSS stimulated cells showed stronger adhesion strength than the cells not exposed to FSS. The cell not exposed to FSS always exhibited greater nuclear stiffness than cortex stiffness, while after FSS treatment the cortex hardened and nucleus softened, where the round-shaped cell had a cortex that was more rigid than its nucleus. These results indicated that FSS influenced the biomechanics of circulating tumor cells, and elucidation of the mechanical responses to FSS might provide a deeper insight for cancer metastasis.

Biophysical phenotyping of single cells using a differential multiconstriction microfluidic device with self-aligned 3D electrodes

Precise measurement of mechanical and electrical properties of single cells can yield useful information on the physiological and pathological state of cells. In this work, we develop a differential multiconstriction microfluidic device with self-aligned 3D electrodes to simultaneously characterize the deformability, electrical impedance and relaxation index of single cells at a high throughput manner (>430 cell/min). Cells are pressure-driven to flow through a series of sequential microfluidic constrictions, during which deformability, electrical impedance and relaxation index of single cells are extracted simultaneously from impedance spectroscopy measurements. Mechanical and electrical phenotyping of untreated, Cytochalasin B treated and N-Ethylmaleimide treated MCF-7 breast cancer cells demonstrate the ability of our system to distinguish different cell populations purely based on these biophysical properties. In addition, we quantify the classification of different cell types using a back propagation neural network. The trained neural network yields the classification accuracy of 87.8% (electrical impedance), 70.1% (deformability), 42.7% (relaxation index) and 93.3% (combination of electrical impedance, deformability and relaxation index) with high sensitivity (93.3%) and specificity (93.3%) for the test group. Furthermore, we have demonstrated the cell classification of a cell mixture using the presented biophysical phenotyping technique with the trained neural network, which is in quantitative agreement with the flow cytometric analysis using fluorescent labels. The developed concurrent electrical and mechanical phenotyping provide great potential for high-throughput and label-free single cell analysis.