ABSTRACT
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.
Subject(s)
Cell Separation/instrumentation , Cell Shape/physiology , High-Throughput Screening Assays/instrumentation , Single-Cell Analysis/instrumentation , Cell Line, Tumor , Cell Separation/methods , HumansABSTRACT
The physical properties of cells are promising biomarkers for cancer diagnosis and prognosis. Here we determine the physical phenotypes that best distinguish human cancer cell lines, and their relationship to cell invasion. We use the high throughput, single-cell microfluidic method, quantitative deformability cytometry (q-DC), to measure six physical phenotypes including elastic modulus, cell fluidity, transit time, entry time, cell size, and maximum strain at rates of 102 cells per second. By training a k-nearest neighbor machine learning algorithm, we demonstrate that multiparameter analysis of physical phenotypes enhances the accuracy of classifying cancer cell lines compared to single parameters alone. We also discover a set of four physical phenotypes that predict invasion; using these four parameters, we generate the physical phenotype model of invasion by training a multiple linear regression model with experimental data from a set of human ovarian cancer cells that overexpress a panel of tumor suppressor microRNAs. We validate the model by predicting invasion based on measured physical phenotypes of breast and ovarian human cancer cell lines that are subject to genetic or pharmacologic perturbations. Taken together, our results highlight how physical phenotypes of single cells provide a biomarker to predict the invasion of cancer cells.
Subject(s)
Biomarkers/metabolism , Breast Neoplasms/pathology , Gene Expression Profiling , MicroRNAs/metabolism , Neoplasm Invasiveness , Ovarian Neoplasms/metabolism , Ovarian Neoplasms/pathology , Breast Neoplasms/metabolism , Calibration , Cell Line , Cell Line, Tumor , Cell Size , Elastic Modulus , Female , Gene Expression Regulation, Neoplastic , Humans , MicroRNAs/genetics , Microfluidics , Phenotype , Regression Analysis , Reproducibility of ResultsABSTRACT
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, Ea, and power-law exponent, ß. To validate our method, we mechanotype human promyelocytic leukemia (HL-60) cells and thereby confirm q-DC measurements of Ea = 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 (Ea = 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 Ea increases with applied stress, which is consistent with stress stiffening behavior of cells. We also find that Ea 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.
Subject(s)
Cell Physiological Phenomena , Microfluidic Analytical Techniques , Single-Cell Analysis , Biomechanical Phenomena , Calibration , Cell Line, Tumor , Cell Shape , Computer Simulation , Cytoskeleton/metabolism , Elastic Modulus , Equipment Design , Humans , Lab-On-A-Chip Devices , Microfluidic Analytical Techniques/instrumentation , Microfluidic Analytical Techniques/methods , Models, Biological , Sepharose , Silicone Oils , Single-Cell Analysis/instrumentation , Single-Cell Analysis/methods , ViscosityABSTRACT
Wrinkling of thin films and membranes can occur due to various mechanisms such as growth and/or mismatch between the mechanical properties of the film and substrate. However, the physical origins of dynamic wrinkling in soft membranes are still not fully understood. Here we use milk skin as a tractable experimental system to investigate the physics of wrinkle formation in a thin, poroelastic film. Upon heating milk, a micron-thick hydrogel of denatured proteins and fat globules forms at the air-water interface. Over time, we observe an increase in the total length of wrinkles. By confocal imaging and profilometry, we determine that the composition and thickness of the milk skin appears to be homogeneous over the length scale of the wrinkles, excluding differences in milk skin composition as a major contributor to wrinkling. To explain the physical origins of wrinkle growth, we describe theory that considers the milk skin as a thin, poroelastic film where pressure is generated by the evaporative-driven flow of solvent across the film; this imparts in-plane stresses in the milk skin, which cause wrinkling. Viscous effects can explain the time-dependent growth of wrinkles. Our theoretical predictions of the effects of relative humidity on the total length of wrinkles over time are consistent with our experimental results. Our findings provide insight into the physics of the common phenomenon of milk skin wrinkling, and identify hydration gradients as another physical mechanism that can drive morphological instabilities in soft matter.
ABSTRACT
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. ß-adrenergic receptor (ßAR) signaling drives invasion and metastasis, but the effects on cell deformability are not known. Here, we show that activation of ß-adrenergic signaling by ßAR agonists reduces the deformability of highly metastatic human breast cancer cells, and that these stiffer cells are more invasive in vitro We find that ßAR activation also reduces the deformability of ovarian, prostate, melanoma and leukemia cells. Mechanistically, we show that ßAR-mediated cell stiffening depends on the actin cytoskeleton and myosin II activity. These changes in cell deformability can be prevented by pharmacological ß-blockade or genetic knockout of the ß2-adrenergic receptor. Our results identify a ß2-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.
Subject(s)
Neoplasms/metabolism , Neoplasms/pathology , Receptors, Adrenergic, beta-2/metabolism , Signal Transduction , Actins/metabolism , Calcium/metabolism , Cell Line, Tumor , Cell Movement/drug effects , Humans , Isoproterenol/pharmacology , Models, Biological , Neoplasm Invasiveness , Signal Transduction/drug effectsABSTRACT
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.
Subject(s)
Flow Cytometry/methods , Hardness Tests/methods , Microscopy, Atomic Force/methods , Pancreatic Neoplasms/pathology , Pancreatic Neoplasms/physiopathology , Ultrafiltration/methods , Biomarkers , Carcinoma, Pancreatic Ductal , Cell Line, Tumor , Cell Separation/methods , Elastic Modulus , Hardness , Humans , Lab-On-A-Chip Devices , Neoplasm Invasiveness , Stress, MechanicalABSTRACT
The mechanical phenotype or 'mechanotype' of cells is emerging as a potential biomarker for cell types ranging from pluripotent stem cells to cancer cells. Using a microfluidic device, cell mechanotype can be rapidly analyzed by measuring the time required for cells to deform as they flow through constricted channels. While cells typically exhibit deformation timescales, or transit times, on the order of milliseconds to tens of seconds, transit times can span several orders of magnitude and vary from day to day within a population of single cells; this makes it challenging to characterize different cell samples based on transit time data. Here we investigate how variability in transit time measurements depends on both experimental factors and heterogeneity in physical properties across a population of single cells. We find that simultaneous transit events that occur across neighboring constrictions can alter transit time, but only significantly when more than 65% of channels in the parallel array are occluded. Variability in transit time measurements is also affected by the age of the device following plasma treatment, which could be attributed to changes in channel surface properties. We additionally investigate the role of variability in cell physical properties. Transit time depends on cell size; by binning transit time data for cells of similar diameters, we reduce measurement variability by 20%. To gain further insight into the effects of cell-to-cell differences in physical properties, we fabricate a panel of gel particles and oil droplets with tunable mechanical properties. We demonstrate that particles with homogeneous composition exhibit a marked reduction in transit time variability, suggesting that the width of transit time distributions reflects the degree of heterogeneity in subcellular structure and mechanical properties within a cell population. Our results also provide fundamental insight into the physical underpinnings of transit measurements: transit time depends strongly on particle elastic modulus, and weakly on viscosity and surface tension. Based on our findings, we present a comprehensive methodology for designing, analyzing, and reducing variability in transit time measurements; this should facilitate broader implementation of transit experiments for rapid mechanical phenotyping in basic research and clinical settings.