The impact of sphingosine kinase inhibitor-loaded nanoparticles on bioelectrical and biomechanical properties of cancer cells

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.

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.

Cancer-Nano-Interaction: From Cellular Uptake to Mechanobiological Responses

With the advancement of nanotechnology, the nano-bio-interaction field has emerged. It is essential to enhance our understanding of nano-bio-interaction in different aspects to design nanomedicines and improve their efficacy for therapeutic and diagnostic applications. Many researchers have extensively studied the toxicological responses of cancer cells to nano-bio-interaction, while their mechanobiological responses have been less investigated. The mechanobiological properties of cells such as elasticity and adhesion play vital roles in cellular functions and cancer progression. Many studies have noticed the impacts of cellular uptake on the structural organization of cells and, in return, the mechanobiology of human cells. Mechanobiological changes induced by the interactions of nanomaterials and cells could alter cellular functions and influence cancer progression. Hence, in addition to biological responses, the possible mechanobiological responses of treated cells should be monitored as a standard methodology to evaluate the efficiency of nanomedicines. Studying the cancer-nano-interaction in the context of cell mechanics takes our knowledge one step closer to designing safe and intelligent nanomedicines. In this review, we briefly discuss how the characteristic properties of nanoparticles influence cellular uptake. Then, we provide insight into the mechanobiological responses that may occur during the nano-bio-interactions, and finally, the important measurement techniques for the mechanobiological characterizations of cells are summarized and compared. Understanding the unknown mechanobiological responses to nano-bio-interaction will help with developing the application of nanoparticles to modulate cell mechanics for controlling cancer progression.

Real-time monitoring of liver fibrosis through embedded sensors in a microphysiological system

Hepatic fibrosis is a foreshadowing of future adverse events like liver cirrhosis, liver failure, and cancer. Hepatic stellate cell activation is the main event of liver fibrosis, which results in excessive extracellular matrix deposition and hepatic parenchyma's disintegration. Several biochemical and molecular assays have been introduced for in vitro study of the hepatic fibrosis progression. However, they do not forecast real-time events happening to the in vitro models. Trans-epithelial electrical resistance (TEER) is used in cell culture science to measure cell monolayer barrier integrity. Herein, we explored TEER measurement's utility for monitoring fibrosis development in a dynamic cell culture microphysiological system. Immortal HepG2 cells and fibroblasts were co-cultured, and transforming growth factor β1 (TGF-β1) was used as a fibrosis stimulus to create a liver fibrosis-on-chip model. A glass chip-based embedded TEER and reactive oxygen species (ROS) sensors were employed to gauge the effect of TGF-β1 within the microphysiological system, which promotes a positive feedback response in fibrosis development. Furthermore, albumin, Urea, CYP450 measurements, and immunofluorescent microscopy were performed to correlate the following data with embedded sensors responses. We found that chip embedded electrochemical sensors could be used as a potential substitute for conventional end-point assays for studying fibrosis in microphysiological systems.

Comparative Study of Prostate Cancer Biophysical and Migratory Characteristics via Iterative Mechanoelectrical Properties (iMEP) and Standard Migration Assays

This study reveals a new microfluidic biosensor consisting of a multi-constriction microfluidic device with embedded electrodes for measuring the biophysical attributes of single cells. The biosensing platform called the iterative mechano-electrical properties (iMEP) analyzer captures electronic records of biomechanical and bioelectrical properties of cells. The iMEP assay is used in conjunction with standard migration assays, such as chemotaxis-based Boyden chamber and scratch wound healing assays, to evaluate the migratory behavior and biophysical properties of prostate cancer cells. The three cell lines evaluated in the study each represent a stage in the standard progression of prostate cancer, while the fourth cell line serves as a normal/healthy counterpart. Neither the scratch assay nor the chemotaxis assay could fully differentiate the four cell lines. Furthermore, there was not a direct correlation between wound healing rate or the migratory rate with the cells' metastatic potential. However, the iMEP assay, through its multiparametric dataset, could distinguish between all four cell line populations with p-value < 0.05. Further studies are needed to determine if iMEP signatures can be used for a wider range of human cells to assess the tumorigenicity of a cell population or the metastatic potential of cancer cells.

Cancer cells optimize elasticity for efficient migration

Cancer progression is associated with alternations in the cytoskeletal architecture of cells and, consequently, their mechanical properties such as stiffness. Changing the mechanics of cells enables cancer cells to migrate and invade to distant organ sites. This process, metastasis, is the main reason for cancer-related mortality. Cell migration is an essential step towards increasing the invasive potential of cells. Although many studies have shown that the migratory speed and the invasion of cells can be inversely correlated to the stiffness of cells, some other investigations indicate opposing results. In the current work, based on the strain energy stored in cells due to the contractile forces, we defined an energy-dependent term, migratory index, to approximate how changes in the mechanical properties of cells influence cell migration required for cancer progression. Cell migration involves both cell deformation and force transmission within cells. The effects of these two parameters can be represented equally by the migratory index. Our mechanical modelling and computational study show that cells depending on their shape, size and other physical parameters have a maximum migratory index taking place at a specific range of cell bulk elasticity, indicating the most favourable conditions for invasive mobility. This approximate model could be used to explain why the stiffness of cells varies during cancer progression. We believe that the stiffness of cancer or malignant cells depending on the stiffness of their normal or non-malignant counterparts is either decreased or increased to reach the critical condition in which the mobility potential of cells is approximated to be maximum.

In-air EIS sensor for in situ and real-time monitoring of in vitro epithelial cells under air-exposure

This paper reports in-air monitoring of in vitro monolayer cells under air-exposure utilizing electrochemical impedance spectroscopy (EIS). In-air impedance measurement was performed by placing integrated electrodes laterally, instead of vertically, to a cell membrane, avoiding electrical disconnection, unlike conventional transepithelial-electrical-resistance (TEER). The in-air EIS sensor platform mainly consisted of two chambers, separated by a porous membrane where cells were cultured, that enabled cell exposure to both air (apical side) and liquid (basal side) for long-term measurement. On top of the membrane, EIS interdigitated electrodes were patterned and lung epithelial cells (A549 type II) were cultured with air exposure on one side. The fabricated in-air EIS sensor successfully demonstrated in situ real-time measurement of cell populations in confluency in the range of 7.8 × 104 and 9.6 × 105 cells per cm2 at a sensitivity of 3.0 × 10-2 Ω per cell in impedance and in the range of 1.0 × 104 and 9.6 × 105 cells per cm2 at a sensitivity of 0.17 × 10-15 F per cell in capacitance under AC frequencies of 100 kHz and 1 MHz, respectively. It also successfully monitored transient modulation of tight-junctions that collectively began to open in 30 minutes after the injection of 100 ng ml-1 TNF-α (a relaxation agent), reached maximum relaxation with a 12.6% increase in impedance value and a 12% decrease in capacitance in 60 minutes, and recovered back to its original junction status after 720 minutes, which confirmed the observation in animal models in the literature. Note that the opposite trends in impedance and capacitance allowed the in-air EIS sensor to distinguish cell population changes from tight junction modulation. It was concluded that the developed in-air EIS sensor in an in vitro platform can enable in situ and real-time monitoring of the population of the 'air-exposed' cells as well as the modulation of tight-junctions, which has not been demonstrated yet.

Post-enrichment circulating tumor cell detection and enumeration via deformability impedance cytometry

Circulating tumor cells (CTCs) in blood can provide valuable information when detecting, diagnosing, and monitoring cancer. This paper describes a system that consists of a constriction-based microfluidic sensor with embedded electrodes that can detect and enumerate cancer cells in blood. The biosensor measures impedance in terms of magnitude and phase at multiple frequencies as cells transit through the constriction channel. Cancer cells deform as they move through while blood cells remain intact, thus generating differential impedance profiles that can be used for detecting and counting CTCs. Two versions of this device are reported, one where the electrodes are embedded into the disposable microfluidic channel, and the other in which the disposable chip is externally fixed to a reusable substrate housing the electrodes. Both configurations were tested by spiking breast or prostate cancer cells into murine blood, and both detected all tumor cells passing through the narrow channels while being able to differentiate between the two cell lines. The chip in its current format has a throughput of 1 μL/min. While the throughput is scalable by integrating more constriction channels in parallel, the presented assay is intended for post-enrichment label-free enumeration and characterization of CTCs.

Biophysical phenotyping of cells via impedance spectroscopy in parallel cyclic deformability channels

This paper describes a new microfluidic biosensor with capabilities of studying single cell biophysical properties. The chip contains four parallel sensing channels, where each channel includes two constriction regions separated by a relaxation region. All channels share a pair of electrodes to record the electrical impedance. Single cell impedance magnitudes and phases at different frequencies were obtained. The deformation and transition time information of cells passing through two sequential constriction regions were gained from the time points on impedance magnitude variations. Constriction channels separated by relaxation regions have been proven to improve the sensitivity of distinguishing single cells. The relaxation region between two sequential constriction channels provides extra time stamps that can be identified in the impedance plots. The new chip allows simultaneous measurement of the biophysical attributes of multiple cells in different channels, thereby increasing the overall throughput of the chip. Using the biomechanical parameters represented by the time stamps in the impedance results, breast cancer cells (MDA-MB-231) and the normal epithelial cells (MCF-10A) could be distinguished by 85%. The prediction accuracy at the single-cell level reached 97% when both biomechanical and bioelectrical parameters were utilized. While the new label-free assay has been tested to distinguish between normal and cancer cells, its application can be extended to include cell-drug interactions and circulating tumor cell detection in blood.

Kernel-Based Microfluidic Constriction Assay for Tumor Sample Identification

A high-throughput multiconstriction microfluidic channels device can distinguish human breast cancer cell lines (MDA-MB-231, HCC-1806, MCF-7) from immortalized breast cells (MCF-10A) with a confidence level of ∼81-85% at a rate of 50-70 cells/min based on velocity increment differences through multiconstriction channels aligned in series. The results are likely related to the deformability differences between nonmalignant and malignant breast cells. The data were analyzed by the methods/algorithms of Ridge, nonnegative garrote on kernel machine (NGK), and Lasso using high-dimensional variables, including the cell sizes, velocities, and velocity increments. In kernel learning based methods, the prediction values of 10-fold cross-validations are used to represent the difference between two groups of data, where a value of 100% indicates the two groups are completely distinct and identifiable. The prediction value is used to represent the difference between two groups using the established algorithm classifier from high-dimensional variables. These methods were applied to heterogeneous cell populations prepared using primary tumor and adjacent normal tissue obtained from two patients. Primary breast cancer cells were distinguished from patient-matched adjacent normal cells with a prediction ratio of 70.07%-75.96% by the NGK method. Thus, this high-throughput multiconstriction microfluidic device together with the kernel learning method can be used to perturb and analyze the biomechanical status of cells obtained from small primary tumor biopsy samples. The resultant biomechanical velocity signatures identify malignancy and provide a new marker for evaluation in risk assessment.

Entrapment of Prostate Cancer Circulating Tumor Cells with a Sequential Size-Based Microfluidic Chip

Circulating tumor cells (CTCs) are broadly accepted as an indicator for early cancer diagnosis and disease severity. However, there is currently no reliable method available to capture and enumerate all CTCs as most systems require either an initial CTC isolation or antibody-based capture for CTC enumeration. Many size-based CTC detection and isolation microfluidic platforms have been presented in the past few years. Here we describe a new size-based, multiple-row cancer cell entrapment device that captured LNCaP-C4-2 prostate cancer cells with >95% efficiency when in spiked mouse whole blood at ∼50 cells/mL. The capture ratio and capture limit on each row was optimized and it was determined that trapping chambers with five or six rows of micro constriction channels were needed to attain a capture ratio >95%. The device was operated under a constant pressure mode at the inlet for blood samples which created a uniform pressure differential across all the microchannels in this array. When the cancer cells deformed in the constriction channel, the blood flow temporarily slowed down. Once inside the trapping chamber, the cancer cells recovered their original shape after the deformation created by their passage through the constriction channel. The CTCs reached the cavity region of the trapping chamber, such that the blood flow in the constriction channel resumed. On the basis of this principle, the CTCs will be captured by this high-throughput entrapment chip (CTC-HTECH), thus confirming the potential for our CTC-HTECH to be used for early stage CTC enrichment and entrapment for clinical diagnosis using liquid biopsies.

High-precision modular microfluidics by micromilling of interlocking injection-molded blocks

Wider use and adaptation of microfluidics is hindered by the infrastructure, knowledge, and time required to build prototype systems, especially when multiple fluid operations and measurements are required. As a result, 3D printing of microfluidics is attracting interest, yet cannot readily achieve the feature size, smoothness, and optical transparency needed for many standard microfluidic systems. Herein we present a new approach to the design and construction of high-precision modular microfluidics, using standard injection-molded blocks that are modified using micromilling and assembled via elastically averaged contacts. Desktop micromilling achieves channel dimensions as small as 50 μm depth and 150 μm width and adhesive films seal channels to allow internal fluid pressure of >400 kPa. Elastically averaged connections between bricks result in a mechanical locating repeatability of ∼1 μm, enabling fluid to pass between bricks via an O-ring seal with >99.9% reliability. We demonstrated and tested block-based systems for generating droplets at rates above 9000 min^-1 and COV <3%, and integrated optical sensors. We also show how blocks can be used to build easily reconfigurable interfaces with glass microfluidic devices and imaging hardware. Microfluidic bricks fabricated by FDM and SLA 3D printing cannot achieve the dimensional quality of molded bricks, yet 3D printing allows customized bricks to be integrated with standard LEGOs. Our approach enables a wide variety of modular microfluidic units to be built using a widely available, cost-effective platform, encouraging use in both research and education.

Rationalization of a nanoparticle-based nicotine nanovaccine as an effective next-generation nicotine vaccine: A focus on hapten localization

A lipid-polymeric hybrid nanoparticle-based next-generation nicotine nanovaccine was rationalized in this study to combat nicotine addiction. A series of nanovaccines, which had nicotine-haptens localized on carrier protein (LPKN), nanoparticle surface (LPNK), or both (LPNKN), were designed to study the impact of hapten localization on their immunological efficacy. All three nanovaccines were efficiently taken up and processed by dendritic cells. LPNKN induced a significantly higher immunogenicity against nicotine and a significantly lower anti-carrier protein antibody level compared to LPKN and LPNK. Meanwhile, it was found that the anti-nicotine antibodies elicited by LPKN and LPNKN bind nicotine stronger than those elicited by LPKN, and LPNK and LPNKN resulted in a more balanced Th1-Th2 immunity than LPKN. Moreover, LPNKN exhibited the best ability to block nicotine from entering the brain of mice. Collectively, the results demonstrated that the immunological efficacy of the hybrid nanoparticle-based nicotine vaccine could be enhanced by modulating hapten localization, providing a promising strategy to combatting nicotine addiction.

Mammalian sphingosine kinase (SphK) isoenzymes and isoform expression: challenges for SphK as an oncotarget

The various sphingosine kinase (SphK) isoenzymes (isozymes) and isoforms, key players in normal cellular physiology, are strongly implicated in cancer and other diseases. Mutations in SphKs, that may justify abnormal physiological function, have not been recorded. Nonetheless, there is a large and growing body of evidence demonstrating the contribution of gain or loss of function and the imbalance in the SphK/S1P rheostat to a plethora of pathological conditions including cancer, diabetes and inflammatory diseases. SphK is expressed as two isozymes SphK1 and SphK2, transcribed from genes located on different chromosomes and both isozymes catalyze the phosphorylation of sphingosine to S1P. Expression of each SphK isozyme produces alternately spliced isoforms. In recent years the importance of the contribution of SpK1 expression to treatment resistance in cancer has been highlighted and, additionally, differences in treatment outcome appear to also be dependent upon SphK isoform expression. This review focuses on an exciting emerging area of research involving SphKs functions, expression and subcellular localization, highlighting the complexity of targeting SphK in cancer and also comorbid diseases. This review also covers the SphK isoenzymes and isoforms from a historical perspective, from their first discovery in murine species and then in humans, their role(s) in normal cellular function and in disease processes, to advancement of SphK as an oncotarget.

Microfluidic Iterative Mechanical Characteristics (iMECH) Analyzer for Single-Cell Metastatic Identification

This study describes the development of a microfluidic biosensor called the iterative mechanical characteristics (iMECH) analyzer which enables label-free biomechanical profiling of individual cells for distinction between metastatic and non-metastatic human mammary cell lines. Previous results have demonstrated that pulsed mechanical nanoindentation can modulate the biomechanics of cells resulting in distinctly different biomechanical responses in metastatic and non-metastatic cell lines. The iMECH analyzer aims to move this concept into a microfluidic, clinically more relevant platform. The iMECH analyzer directs a cyclic deformation regimen by pulling cells through a test channel comprised of narrow deformation channels and interspersed with wider relaxation regions which together simulate a dynamic microenvironment. The results of the iMECH analysis of human breast cell lines revealed that cyclic deformations produce a resistance in non-metastatic 184A1 and MCF10A cells as determined by a drop in their average velocity in the iterative deformation channels after each relaxation. In contrast, metastatic MDA-MB-231 and MDA-MB-468 cells exhibit a loss of resistance as measured by a velocity raise after each relaxation. These distinctive modulatory mechanical responses of normal-like non-metastatic and metastatic cancer breast cells to the pulsed indentations paradigm provide a unique bio-signature. The iMECH analyzer represents a diagnostic microchip advance for discriminating metastatic cancer at the single-cell level.

Improvement of Depth Profiling into Biotissues Using Micro Electrical Impedance Spectroscopy on a Needle with Selective Passivation

A micro electrical impedance spectroscopy (EIS)-on-a-needle for depth profiling (μEoN-DP) with a selective passivation layer (SPL) on a hypodermic needle was recently fabricated to measure the electrical impedance of biotissues along with the penetration depths. The SPL of the μEoN-DP enabled the sensing interdigitated electrodes (IDEs) to contribute predominantly to the measurement by reducing the relative influence of the connection lines on the sensor output. The discrimination capability of the μEoN-DP was verified using phosphate-buffered saline (PBS) at various concentration levels. The resistance and capacitance extracted through curve fitting were similar to those theoretically estimated based on the mixing ratio of PBS and deionized water; the maximum discrepancies were 8.02% and 1.85%, respectively. Depth profiling was conducted using four-layered porcine tissue to verify the effectiveness of the discrimination capability of the μEoN-DP. The magnitude and phase between dissimilar porcine tissues (fat and muscle) were clearly discriminated at the optimal frequency of 1 MHz. Two kinds of simulations, one with SPL and the other with complete passivation layer (CPL), were performed, and it was verified that the SPL was advantageous over CPL in the discrimination of biotissues in terms of sensor output.