Quantitative investigation of calcimimetic R568 on beta-cell adhesion and mechanics using AFM single-cell force spectroscopy

In this study we use a novel approach to quantitatively investigate mechanical and interfacial properties of clonal b-cells using AFM-Single Cell Force Spectroscopy (SCFS). MIN6 cells were incubated for 48 h with 0.5 mMCa2+ ± the calcimimetic R568 (1 lM). AFM-SCFS adhesion and indentation experiments were performed by using modified tipless cantilevers. Hertz contact model was applied to analyse force–displacement (F–d) curves for determining elastic or Young’s modulus (E). Our results show CaSR-evoked increases in cell-to-cell adhesion parameters and E modulus of single cells, demonstrating that cytomechanics have profound effects on cell adhesion characterization

Slow Stress Propagation in Adherent Cells

Mechanical cues influence a wide range of cellular behaviors including motility, differentiation, and tumorigenesis. Although previous studies elucidated the role of specific players such as ion channels and focal adhesions as local mechanosensors, the investigation of how mechanical perturbations propagate across the cell is necessary to understand the spatial coordination of cellular processes. Here we quantify the magnitude and timing of intracellular stress propagation, using atomic force microscopy and particle tracking by defocused fluorescence microscopy. The apical cell surface is locally perturbed by atomic force microscopy cantilever indentation, and distal displacements are measured in three dimensions by tracking integrin-bound fluorescent particles. We observe an immediate response and slower equilibration, occurring over times that increase with distance from perturbation. This distance-dependent equilibration occurs over several seconds and can be eliminated by disruption of the actin cytoskeleton. Our experimental results are not explained by traditional viscoelastic models of cell mechanics, but they are consistent with predictions from poroelastic models that include both cytoskeletal deformation and flow of the cytoplasm. Our combined atomic force microscopy-particle tracking measurements provide direct evidence of slow, distance-dependent dissipative stress propagation in response to external mechanical cues and offer new insights into mechanical models and physiological behaviors of adherent cells

Patient-calibrated agent-based modelling of ductal carcinoma in situ (DCIS):from microscopic measurements to macroscopic predictions of clinical progression

Ductal carcinoma in situ (DCIS)—a significant precursor to invasive breast cancer—is typically diagnosed as microcalcifications in mammograms. However, the effective use of mammograms and other patient data to plan treatment has been restricted by our limited understanding of DCIS growth and calcification. We develop a mechanistic, agent-based cell model and apply it to DCIS. Cell motion is determined by a balance of biomechanical forces. We use potential functions to model interactions with the basement membrane and amongst cells of unequal size and phenotype. Each cell’s phenotype is determined by genomic/proteomic- and microenvironment-dependent stochastic processes. Detailed “sub-models” describe cell volume changes during proliferation and necrosis; we are the first to account for cell calcification. We introduce the first patient-specific calibration method to fully constrain the model based upon clinically-accessible histopathology data. After simulating 45 days of solid-type DCIS with comedonecrosis, the model predicts: necrotic cell lysis acts as a biomechanical stress relief, and is responsible for the linear DCIS growth observed in mammography; the rate of DCIS advance varies with the duct radius; the tumour grows 7 to 10 mm per year—consistent with mammographic data; and the mammographic and (post-operative) pathologic sizes are linearly correlated—in quantitative agreement with the clinical literature. Patient histopathology matches the predicted DCIS microstructure: an outer proliferative rim surrounds a stratified necrotic core with nuclear debris on its outer edge and calcification in the centre. This work illustrates that computational modelling can provide new insight on the biophysical underpinnings of cancer. It may one day be possible to augment a patient’s mammography and other imaging with rigorously-calibrated models that help select optimal surgical margins based upon the patient’s histopathologic data