RESUMO
The recurrence of cancer following chemotherapy treatment is a major cause of death across solid and hematologic cancers. In B-cell acute lymphoblastic leukemia (B-ALL), relapse after initial chemotherapy treatment leads to poor patient outcomes. Here we test the hypothesis that chemotherapy-treated versus control B-ALL cells can be characterized based on cellular physical phenotypes. To quantify physical phenotypes of chemotherapy-treated leukemia cells, we use cells derived from B-ALL patients that are treated for 7 days with a standard multidrug chemotherapy regimen of vincristine, dexamethasone, and L-asparaginase (VDL). We conduct physical phenotyping of VDL-treated versus control cells by tracking the sequential deformations of single cells as they flow through a series of micron-scale constrictions in a microfluidic device; we call this method Quantitative Cyclical Deformability Cytometry. Using automated image analysis, we extract time-dependent features of deforming cells including cell size and transit time (TT) with single-cell resolution. Our findings show that VDL-treated B-ALL cells have faster TTs and transit velocity than control cells, indicating that VDL-treated cells are more deformable. We then test how effectively physical phenotypes can predict the presence of VDL-treated cells in mixed populations of VDL-treated and control cells using machine learning approaches. We find that TT measurements across a series of sequential constrictions can enhance the classification accuracy of VDL-treated cells in mixed populations using a variety of classifiers. Our findings suggest the predictive power of cell physical phenotyping as a complementary prognostic tool to detect the presence of cells that survive chemotherapy treatment. Ultimately such complementary physical phenotyping approaches could guide treatment strategies and therapeutic interventions. Insight box Cancer cells that survive chemotherapy treatment are major contributors to patient relapse, but the ability to predict recurrence remains a challenge. Here we investigate the physical properties of leukemia cells that survive treatment with chemotherapy drugs by deforming individual cells through a series of micron-scale constrictions in a microfluidic channel. Our findings reveal that leukemia cells that survive chemotherapy treatment are more deformable than control cells. We further show that machine learning algorithms applied to physical phenotyping data can predict the presence of cells that survive chemotherapy treatment in a mixed population. Such an integrated approach using physical phenotyping and machine learning could be valuable to guide patient treatments.
Assuntos
Asparaginase , Leucemia , Humanos , Vincristina/uso terapêutico , Recidiva , Fenótipo , Leucemia/tratamento farmacológico , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêuticoRESUMO
Cancer cell mechanotype changes are newly recognized cancer phenotypic events, whereas metastatic cancer cells show decreased cell stiffness and increased deformability relative to normal cells. To further examine how cell mechanotype changes in early stages of cancer transformation and progression, an in vitro multi-step human urothelial cell carcinogenic model was used to measure cellular Young's modulus, deformability, and transit time using single-cell atomic force microscopy, microfluidic-based deformability cytometry, and quantitative deformability cytometry, respectively. Measurable cell mechanotype changes of stiffness, deformability, and cell transit time occur early in the transformation process. As cells progress from normal, to preinvasive, to invasive cells, Young's modulus of stiffness decreases and deformability increases gradually. These changes were confirmed in three-dimensional cultured microtumor masses and urine exfoliated cells directly from patients. Using gene screening and proteomics approaches, we found that the main molecular pathway implicated in cell mechanotype changes appears to be epithelial to mesenchymal transition.
RESUMO
Immune cells can sense and respond to biophysical cues - from dynamic forces to spatial features - during their development, activation, differentiation and expansion. These biophysical signals regulate a variety of immune cell functions such as leukocyte extravasation, macrophage polarization, T cell selection and T cell activation. Recent studies have advanced our understanding on immune responses to biophysical cues and the underlying mechanisms of mechanotransduction, which provides rational basis for the design and development of immune-modulatory therapeutics. This review discusses the recent progress in mechanosensing and mechanotransduction of immune cells, particularly monocytes/macrophages and T lymphocytes, and features new biomaterial designs and biomedical devices that translate these findings into biomedical applications.
Assuntos
Materiais Biocompatíveis , Mecanotransdução Celular , Biofísica , Diferenciação Celular , MacrófagosRESUMO
DYT1 dystonia is a neurological movement disorder that is caused by a loss-of-function mutation in the DYT1/TOR1A gene, which encodes torsinA, a conserved luminal ATPases-associated with various cellular activities (AAA+) protein. TorsinA is required for the assembly of functional linker of nucleoskeleton and cytoskeleton (LINC) complexes, and consequently the mechanical integration of the nucleus and the cytoskeleton. Despite the potential implications of altered mechanobiology in dystonia pathogenesis, the role of torsinA in regulating cellular mechanical phenotype, or mechanotype, in DYT1 dystonia remains unknown. Here, we define the deformability of mouse fibroblasts lacking functional torsinA as well as human fibroblasts isolated from DYT1 dystonia patients. We find that the deletion of torsinA or the expression of torsinA containing the DYT1 dystonia-causing ΔE302/303 (ΔE) mutation results in more deformable cells. We observe a similar increased deformability of mouse fibroblasts that lack lamina-associated polypeptide 1 (LAP1), which interacts with and stimulates the ATPase activity of torsinA in vitro, as well as with the absence of the LINC complex proteins, Sad1/UNC-84 1 (SUN1) and SUN2, lamin A/C, or lamin B1. Consistent with these findings, we also determine that DYT1 dystonia patient-derived fibroblasts are more compliant than fibroblasts isolated from unafflicted individuals. DYT1 dystonia patient-derived fibroblasts also exhibit increased nuclear strain and decreased viability following mechanical stretch. Taken together, our results establish the foundation for future mechanistic studies of the role of cellular mechanotype and LINC-dependent nuclear-cytoskeletal coupling in regulating cell survival following exposure to mechanical stresses.
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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 ß-adrenoceptors (ß-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 ß-AR signaling on macrophage deformability is dependent on actin-related proteins 2/3, indicating that stress hormone signaling through ß-AR shifts actin organization to favor branched structures rather than linear unbranched actin filaments. These findings show that through remodeling of the actin cytoskeleton, ß-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 ß-adrenergic receptors regulates macrophage mechanotype and function.
Assuntos
Forma Celular , Macrófagos/efeitos dos fármacos , Receptores Adrenérgicos beta/metabolismo , Citoesqueleto de Actina/metabolismo , Agonistas Adrenérgicos beta/farmacologia , Antagonistas Adrenérgicos beta/farmacologia , Linhagem Celular Tumoral , Humanos , Isoproterenol/farmacologia , Macrófagos/citologia , Macrófagos/metabolismo , Propranolol/farmacologia , Transdução de SinaisRESUMO
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.