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1. Transient Slope: A Metric for Assessing Heterogeneity from the Dielectrophoresis Spectrum

   https://doi.org/10.3390/biophysica4040045  

   Egun, E; Wilson, T; Rashad, Z; Valentine, R; Adams, T (December 2024, Biophysica)

   Cellular heterogeneity, an inherent feature of biological systems, plays a critical role in processes such as development, immune response, and disease progression. Human mesenchymal stem cells (hMSCs) exemplify this heterogeneity due to their multi-lineage differentiation potential. However, their inherent variability complicates clinical use, and there is no universally accepted method for detecting and quantifying cell population heterogeneity. Dielectrophoresis (DEP) has emerged as a powerful electrokinetic technique for characterizing and manipulating cells based on their dielectric properties, offering label-free analysis capabilities. Quantitative information from the DEP spectrum, such as transient slope, measure cells’ transition between negative and positive DEP behaviors. In this study, we employed DEP to estimate transient slope of various cell populations, including relatively homogeneous HEK-293 cells, heterogeneous hMSCs, and cancer cells (PC3 and DU145). Our analysis encompassed hMSCs derived from bone marrow, adipose, and umbilical cord tissue, to capture tissue-specific heterogeneity. Transient slope was assessed using two methods, involving linear trendline fitting to different low-frequency regions of the DEP spectrum. We found that transient slope serves as a reliable indicator of cell population heterogeneity, with more heterogeneous populations exhibiting lower transient slopes and higher standard deviations. Validation using cell morphology, size, and stemness further supported the utility of transient slope as a heterogeneity metric. This label-free approach holds promise for advancing cell sorting, biomanufacturing, and personalized medicine. 

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2. High-Frequency Dielectrophoresis Reveals That Distinct Bio-Electric Signatures of Colorectal Cancer Cells Depend on Ploidy and Nuclear Volume

   https://doi.org/10.3390/mi14091723  

   Duncan, Josie L.; Bloomfield, Mathew; Swami, Nathan; Cimini, Daniela; Davalos, Rafael V. (September 2023, Micromachines)

   Aneuploidy, or an incorrect chromosome number, is ubiquitous among cancers. Whole-genome duplication, resulting in tetraploidy, often occurs during the evolution of aneuploid tumors. Cancers that evolve through a tetraploid intermediate tend to be highly aneuploid and are associated with poor patient prognosis. The identification and enrichment of tetraploid cells from mixed populations is necessary to understand the role these cells play in cancer progression. Dielectrophoresis (DEP), a label-free electrokinetic technique, can distinguish cells based on their intracellular properties when stimulated above 10 MHz, but DEP has not been shown to distinguish tetraploid and/or aneuploid cancer cells from mixed tumor cell populations. Here, we used high-frequency DEP to distinguish cell subpopulations that differ in ploidy and nuclear size under flow conditions. We used impedance analysis to quantify the level of voltage decay at high frequencies and its impact on the DEP force acting on the cell. High-frequency DEP distinguished diploid cells from tetraploid clones due to their size and intracellular composition at frequencies above 40 MHz. Our findings demonstrate that high-frequency DEP can be a useful tool for identifying and distinguishing subpopulations with nuclear differences to determine their roles in disease progression. 

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3. Targeting endocytosis to sensitize cancer cells to programmed cell death

   https://doi.org/10.1042/BST20231332  

   Chan, Emily T; Kural, Cömert (August 2024, Biochemical Society Transactions)

   Evading programmed cell death (PCD) is a hallmark of cancer that allows tumor cells to survive and proliferate unchecked. Endocytosis, the process by which cells internalize extracellular materials, has emerged as a key regulator of cell death pathways in cancer. Many tumor types exhibit dysregulated endocytic dynamics that fuel their metabolic demands, promote resistance to cytotoxic therapies, and facilitate immune evasion. This review examines the roles of endocytosis in apoptotic resistance and immune escape mechanisms utilized by cancer cells. We highlight how inhibiting endocytosis can sensitize malignant cells to therapeutic agents and restore susceptibility to PCD. Strategies to modulate endocytosis for enhanced cancer treatment are discussed, including targeting endocytic regulatory proteins, altering membrane biophysical properties, and inhibiting Rho-associated kinases. While promising, challenges remain regarding the specificity and selectivity of endocytosis-targeting agents. Nonetheless, harnessing endocytic pathways represents an attractive approach to overcome apoptotic resistance and could yield more effective therapies by rendering cancer cells vulnerable to PCD. Understanding the interplay between endocytosis and PCD regulation is crucial for developing novel anticancer strategies that selectively induce tumor cell death. 

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4. Mechanical Evolution of Metastatic Cancer Cells in 3D Microenvironment

   https://doi.org/10.1002/smll.202403242  

   Hilai, Karlin; Grubich, Daniil; Akrawi, Marcus; Zhu, Hui; Zaghloul, Razanne; Shi, Chenjun; Do, Man; Zhu, Dongxiao; Zhang, Jitao (March 2025, Small)

   Abstract Cellular biomechanics plays a critical role in cancer metastasis and tumor progression. Existing studies on cancer cell biomechanics are mostly conducted in flat 2D conditions, where cells’ behavior can differ considerably from those in 3D physiological environments. Despite great advances in developing 3D in vitro models, probing cellular elasticity in 3D conditions remains a major challenge for existing technologies. In this work, optical Brillouin microscopy is utilized to longitudinally acquire mechanical images of growing cancerous spheroids over the period of 8 days. The dense mechanical mapping from Brillouin microscopy enables us to extract spatially resolved and temporally evolving mechanical features that were previously inaccessible. Using an established machine learning algorithm, it is demonstrated that incorporating these extracted mechanical features significantly improves the classification accuracy of cancer cells, from 74% to 95%. Building on this finding, a deep learning pipeline capable of accurately differentiating cancerous spheroids from normal ones solely using Brillouin images have been developed, suggesting the mechanical features of cancer cells can potentially serve as a new biomarker in cancer classification and detection. 

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5. A High-Throughput Microfluidic Cell Sorter Using a Three-Dimensional Coupled Hydrodynamic-Dielectrophoretic Pre-Focusing Module

   https://doi.org/10.3390/mi14101813  

   Aghaamoo, Mohammad; Cardenas-Benitez, Braulio; Lee, Abraham P. (October 2023, Micromachines)

   Beskok, A. (Ed.)

   Dielectrophoresis (DEP) is a powerful tool for label-free sorting of cells, even those with subtle differences in morphological and dielectric properties. Nevertheless, a major limitation is that most existing DEP techniques can efficiently sort cells only at low throughputs (<1 mL h−1). Here, we demonstrate that the integration of a three-dimensional (3D) coupled hydrodynamic-DEP cell pre-focusing module upstream of the main DEP sorting region enables cell sorting with a 10-fold increase in throughput compared to conventional DEP approaches. To better understand the key principles and requirements for high-throughput cell separation, we present a comprehensive theoretical model to study the scaling of hydrodynamic and electrostatic forces on cells at high flow rate regimes. Based on the model, we show that the critical cell-to-electrode distance needs to be ≤10 µm for efficient cell sorting in our proposed microfluidic platform, especially at flow rates ≥ 1 mL h−1. Based on those findings, a computational fluid dynamics model and particle tracking analysis were developed to find optimum operation parameters (e.g., flow rate ratios and electric fields) of the coupled hydrodynamic-DEP 3D focusing module. Using these optimum parameters, we experimentally demonstrate live/dead K562 cell sorting at rates as high as 10 mL h−1 (>150,000 cells min−1) with 90% separation purity, 85% cell recovery, and no negative impact on cell viability. 

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