A microfluidic technique to probe cell deformability

A constriction channel analysis of astrocytoma stiffness and disease progression

Studies have demonstrated that cancer cells tend to have reduced stiffness (Young's modulus) compared to their healthy counterparts. The mechanical properties of primary brain cancer cells, however, have remained largely unstudied. To investigate whether the stiffness of primary brain cancer cells decreases as malignancy increases, we used a microfluidic constriction channel device to deform healthy astrocytes and astrocytoma cells of grade II, III, and IV and measured the entry time, transit time, and elongation. Calculating cell stiffness directly from the experimental measurements is not possible. To overcome this challenge, finite element simulations of the cell entry into the constriction channel were used to train a neural network to calculate the stiffness of the analyzed cells based on their experimentally measured diameter, entry time, and elongation in the channel. Our study provides the first calculation of stiffness for grades II and III astrocytoma and is the first to apply a neural network analysis to determine cell mechanical properties from a constriction channel device. Our results suggest that the stiffness of astrocytoma cells is not well-correlated with the cell grade. Furthermore, while other non-central-nervous-system cell types typically show reduced stiffness of malignant cells, we found that most astrocytoma cell lines had increased stiffness compared to healthy astrocytes, with lower-grade astrocytoma having higher stiffness values than grade IV glioblastoma. Differences in nucleus-to-cytoplasm ratio only partly explain differences in stiffness values. Although our study does have limitations, our results do not show a strong correlation of stiffness with cell grade, suggesting that other factors may play important roles in determining the invasive capability of astrocytoma. Future studies are warranted to further elucidate the mechanical properties of astrocytoma across various pathological grades.

Stress hormone signaling through β-adrenergic receptors regulates macrophage mechanotype and function

Critical functions of immune cells require them to rapidly change their shape and generate forces in response to cues from their surrounding environment. However, little is known about how soluble factors that may be present in the microenvironment modulate key aspects of cellular mechanobiology-such as immune cell deformability and force generation-to impact functions such as phagocytosis and migration. Here we show that signaling by soluble stress hormones through β-adrenoceptors (β-AR) reduces the deformability of macrophages; this is dependent on changes in the organization of the actin cytoskeleton and is associated with functional changes in phagocytosis and migration. Pharmacologic interventions reveal that the impact of β-AR signaling on macrophage deformability is dependent on actin-related proteins 2/3, indicating that stress hormone signaling through β-AR shifts actin organization to favor branched structures rather than linear unbranched actin filaments. These findings show that through remodeling of the actin cytoskeleton, β-AR-mediated stress hormone signaling modulates macrophage mechanotype to impact functions that play a critical role in immune response.-Kim, T.-H., Ly, C., Christodoulides, A., Nowell, C. J., Gunning, P. W., Sloan, E. K., Rowat, A. C. Stress hormone signaling through β-adrenergic receptors regulates macrophage mechanotype and function.

Integrated automated particle tracking microfluidic enables high-throughput cell deformability cytometry for red cell disorders

Investigating individual red blood cells (RBCs) is critical to understanding hematologic diseases, as pathology often originates at the single-cell level. Many RBC disorders manifest in altered biophysical properties, such as deformability of RBCs. Due to limitations in current biophysical assays, there exists a need for high-throughput analysis of RBC deformability with single-cell resolution. To that end, we present a method that pairs a simple in vitro artificial microvasculature network system with an innovative MATLAB-based automated particle tracking program, allowing for high-throughput, single-cell deformability index (sDI) measurements of entire RBC populations. We apply our technology to quantify the sDI of RBCs from healthy volunteers, Sickle cell disease (SCD) patients, a transfusion-dependent beta thalassemia major patient, and in stored packed RBCs (pRBCs) that undergo storage lesion over 4 weeks. Moreover, our system can also measure cell size for each RBC, thereby enabling 2D analysis of cell deformability vs cell size with single cell resolution akin to flow cytometry. Our results demonstrate the clear existence of distinct biophysical RBC subpopulations with high interpatient variability in SCD as indicated by large magnitude skewness and kurtosis values of distribution, the "shifting" of sDI vs RBC size curves over transfusion cycles in beta thalassemia, and the appearance of low sDI RBC subpopulations within 4 days of pRBC storage. Overall, our system offers an inexpensive, convenient, and high-throughput method to gauge single RBC deformability and size for any RBC population and has the potential to aid in disease monitoring and transfusion guidelines for various RBC disorders.

A scalable filtration method for high throughput screening based on cell deformability

Cell deformability is a label-free biomarker of cell state in physiological and disease contexts ranging from stem cell differentiation to cancer progression. Harnessing deformability as a phenotype for screening applications requires a method that can simultaneously measure the deformability of hundreds of cell samples and can interface with existing high throughput facilities. Here we present a scalable cell filtration device, which relies on the pressure-driven deformation of cells through a series of pillars that are separated by micron-scale gaps on the timescale of seconds: less deformable cells occlude the gaps more readily than more deformable cells, resulting in decreased filtrate volume which is measured using a plate reader. The key innovation in this method is that we design customized arrays of individual filtration devices in a standard 96-well format using soft lithography, which enables multiwell input samples and filtrate outputs to be processed with higher throughput using automated pipette arrays and plate readers. To validate high throughput filtration to detect changes in cell deformability, we show the differential filtration of human ovarian cancer cells that have acquired cisplatin-resistance, which is corroborated with cell stiffness measurements using quantitative deformability cytometry. We also demonstrate differences in the filtration of human cancer cell lines, including ovarian cancer cells that overexpress transcription factors (Snail, Slug), which are implicated in epithelial-to-mesenchymal transition; breast cancer cells (malignant versus benign); and prostate cancer cells (highly versus weekly metastatic). We additionally show how the filtration of ovarian cancer cells is affected by treatment with drugs known to perturb the cytoskeleton and the nucleus. Our results across multiple cancer cell types with both genetic and pharmacologic manipulations demonstrate the potential of this scalable filtration device to screen cells based on their deformability.

Characterizing Deformability of Drug Resistant Patient-Derived Acute Lymphoblastic Leukemia (ALL) Cells Using Acoustic Tweezers

The role of cell mechanics in cancer cells is a novel research area that has resulted in the identification of new mechanisms of therapy resistance. Single beam acoustic (SBA) tweezers are a promising technology for the quantification of the mechanical phenotype of cells. Our previous study showed that SBA tweezers can be used to quantify the deformability of adherent breast cancer cell lines. The physical properties of patient-derived (primary) pre-B acute lymphoblastic leukemia (ALL) cells involved in chemotherapeutic resistance have not been widely investigated. Here, we demonstrate the feasibility of analyzing primary pre-B ALL cells from four cases using SBA tweezers. ALL cells showed increased deformability with increasing acoustic pressure of the SBA tweezers. Moreover, ALL cells that are resistant to chemotherapeutic drugs were more deformable than were untreated ALL cells. We demonstrated that SBA tweezers can quantify the deformability of nonadherent leukemia cells and discriminate this mechanical phenotype in chemotherapy-resistant leukemia cells in a contact- and label-free manner.

Microfluidic generation of transient cell volume exchange for convectively driven intracellular delivery of large macromolecules

Efficient intracellular delivery of target macromolecules remains a major obstacle in cell engineering and other biomedical applications. We discovered a unique cell biophysical phenomenon of transient cell volume exchange by using microfluidics to rapidly and repeatedly compress cells. This behavior consists of brief, mechanically induced cell volume loss followed by rapid volume recovery. We harness this behavior for high-throughput, convective intracellular delivery of large polysaccharides (2000 kDa), particles (100 nm), and plasmids while maintaining high cell viability. Successful proof of concept experiments in transfection and intracellular labeling demonstrated potential to overcome the most prohibitive challenges in intracellular delivery for cell engineering.

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.

Quantitative Deformability Cytometry: Rapid, Calibrated Measurements of Cell Mechanical Properties

Advances in methods that determine cell mechanical phenotype, or mechanotype, have demonstrated the utility of biophysical markers in clinical and research applications ranging from cancer diagnosis to stem cell enrichment. Here, we introduce quantitative deformability cytometry (q-DC), a method for rapid, calibrated, single-cell mechanotyping. We track changes in cell shape as cells deform into microfluidic constrictions, and we calibrate the mechanical stresses using gel beads. We observe that time-dependent strain follows power-law rheology, enabling single-cell measurements of apparent elastic modulus, E_a, and power-law exponent, β. To validate our method, we mechanotype human promyelocytic leukemia (HL-60) cells and thereby confirm q-DC measurements of E_a = 0.53 ± 0.04 kPa. We also demonstrate that q-DC is sensitive to pharmacological perturbations of the cytoskeleton as well as differences in the mechanotype of human breast cancer cell lines (E_a = 2.1 ± 0.1 and 0.80 ± 0.19 kPa for MCF-7 and MDA-MB-231 cells). To establish an operational framework for q-DC, we investigate the effects of applied stress and cell/pore-size ratio on mechanotype measurements. We show that E_a increases with applied stress, which is consistent with stress stiffening behavior of cells. We also find that E_a increases for larger cell/pore-size ratios, even when the same applied stress is maintained; these results indicate strain stiffening and/or dependence of mechanotype on deformation depth. Taken together, the calibrated measurements enabled by q-DC should advance applications of cell mechanotype in basic research and clinical settings.

Stiffness of pancreatic cancer cells is associated with increased invasive potential

Metastasis is a fundamentally physical process in which cells are required to deform through narrow gaps as they invade surrounding tissues and transit to distant sites. In many cancers, more invasive cells are more deformable than less invasive cells, but the extent to which mechanical phenotype, or mechanotype, can predict disease aggressiveness in pancreatic ductal adenocarcinoma (PDAC) remains unclear. Here we investigate the invasive potential and mechanical properties of immortalized PDAC cell lines derived from primary tumors and a secondary metastatic site, as well as noncancerous pancreatic ductal cells. To investigate how invasive behavior is associated with cell mechanotype, we flow cells through micron-scale pores using parallel microfiltration and microfluidic deformability cytometry; these results show that the ability of PDAC cells to passively transit through pores is only weakly correlated with their invasive potential. We also measure the Young's modulus of pancreatic ductal cells using atomic force microscopy, which reveals that there is a strong association between cell stiffness and invasive potential in PDAC cells. To determine the molecular origins of the variability in mechanotype across our PDAC cell lines, we analyze RNAseq data for genes that are known to regulate cell mechanotype. Our results show that vimentin, actin, and lamin A are among the most differentially expressed mechanoregulating genes across our panel of PDAC cell lines, as well as a cohort of 38 additional PDAC cell lines. We confirm levels of these proteins across our cell panel using immunoblotting, and find that levels of lamin A increase with both invasive potential and Young's modulus. Taken together, we find that stiffer PDAC cells are more invasive than more compliant cells, which challenges the paradigm that decreased cell stiffness is a hallmark of metastatic potential.

Cancer cells become less deformable and more invasive with activation of β-adrenergic signaling

Invasion by cancer cells is a crucial step in metastasis. An oversimplified view in the literature is that cancer cells become more deformable as they become more invasive. β-adrenergic receptor (βAR) signaling drives invasion and metastasis, but the effects on cell deformability are not known. Here, we show that activation of β-adrenergic signaling by βAR agonists reduces the deformability of highly metastatic human breast cancer cells, and that these stiffer cells are more invasive in vitro We find that βAR activation also reduces the deformability of ovarian, prostate, melanoma and leukemia cells. Mechanistically, we show that βAR-mediated cell stiffening depends on the actin cytoskeleton and myosin II activity. These changes in cell deformability can be prevented by pharmacological β-blockade or genetic knockout of the β₂-adrenergic receptor. Our results identify a β₂-adrenergic-Ca²⁺-actin axis as a new regulator of cell deformability, and suggest that the relationship between cell mechanical properties and invasion might be dependent on context.

Tumour-suppressor microRNAs regulate ovarian cancer cell physical properties and invasive behaviour

The activities of pathways that regulate malignant transformation can be influenced by microRNAs (miRs). Recently, we showed that increased expression of five tumour-suppressor miRs, miR-508-3p, miR-508-5p, miR-509-3p, miR-509-5p and miR-130b-3p, correlate with improved clinical outcomes in human ovarian cancer patients, and that miR-509-3p attenuates invasion of ovarian cancer cell lines. Here, we investigate the mechanism underlying this reduced invasive potential by assessing the impact of these five miRs on the physical properties of cells. Human ovarian cancer cells (HEYA8, OVCAR8) that are transfected with miR mimics representing these five miRs exhibit decreased invasion through collagen matrices, increased cell size and reduced deformability as measured by microfiltration and microfluidic assays. To understand the molecular basis of altered invasion and deformability induced by these miRs, we use predicted and validated mRNA targets that encode structural and signalling proteins that regulate cell mechanical properties. Combined with analysis of gene transcripts by real-time PCR and image analysis of F-actin in single cells, our results suggest that these tumour-suppressor miRs may alter cell physical properties by regulating the actin cytoskeleton. Our findings provide biophysical insights into how tumour-suppressor miRs can regulate the invasive behaviour of ovarian cancer cells, and identify potential therapeutic targets that may be implicated in ovarian cancer progression.