Receptor tyrosine kinase inhibition leads to regression of acral melanoma by targeting the tumor microenvironment.

Acral melanoma (AM) is an aggressive melanoma variant that arises from palmar, plantar, and nail unit melanocytes. Compared to non-acral cutaneous melanoma (CM), AM is biologically distinct, has an equal incidence across genetic ancestries, typically presents in advanced stage disease, is less responsive to therapy, and has an overall worse prognosis. Independent analysis of published genomic and transcriptomic sequencing identified that receptor tyrosine kinase (RTK) ligands and adapter proteins are frequently amplified, translocated, and/or overexpressed in AM. To target these unique genetic changes, a zebrafish acral melanoma model was exposed to a panel of narrow and broad spectrum multi-RTK inhibitors, revealing that dual FGFR/VEGFR inhibitors decrease acral-analogous melanocyte proliferation and migration. The potent pan-FGFR/VEGFR inhibitor, Lenvatinib, uniformly induces tumor regression in AM patient-derived xenograft (PDX) tumors but only slows tumor growth in CM models. Unlike other multi-RTK inhibitors, Lenvatinib is not directly cytotoxic to dissociated AM PDX tumor cells and instead disrupts tumor architecture and vascular networks. Considering the great difficulty in establishing AM cell culture lines, these findings suggest that AM may be more sensitive to microenvironment perturbations than CM. In conclusion, dual FGFR/VEGFR inhibition may be a viable therapeutic strategy that targets the unique biology of AM.

LVING reveals the intracellular structure of cell growth.

The continuous balance of growth and degradation inside cells maintains homeostasis. Disturbance of this balance by internal or external factors cause state of disease, while effective disease treatments seek to restore this balance. Here, we present a method based on quantitative phase imaging (QPI) based measurements of cell mass and the velocity of mass transport to quantify the balance of growth and degradation within intracellular control volumes. The result, which we call Lagrangian velocimetry for intracellular net growth (LVING), provides high resolution maps of intracellular biomass production and degradation. We use LVING to quantify the growth in different regions of the cell during phases of the cell cycle. LVING can also be used to quantitatively compare the effect of range of chemotherapy drug doses on subcellular growth processes. Finally, we applied LVING to characterize the effect of autophagy on the growth machinery inside cells. Overall, LVING reveals both the structure and distribution of basal growth within cells, as well as the disruptions to this structure that occur during alterations in cell state.

Transferred mitochondria accumulate reactive oxygen species, promoting proliferation.

Recent studies reveal that lateral mitochondrial transfer, the movement of mitochondria from one cell to another, can affect cellular and tissue homeostasis. Most of what we know about mitochondrial transfer stems from bulk cell studies and have led to the paradigm that functional transferred mitochondria restore bioenergetics and revitalize cellular functions to recipient cells with damaged or non-functional mitochondrial networks. However, we show that mitochondrial transfer also occurs between cells with functioning endogenous mitochondrial networks, but the mechanisms underlying how transferred mitochondria can promote such sustained behavioral reprogramming remain unclear. We report that unexpectedly, transferred macrophage mitochondria are dysfunctional and accumulate reactive oxygen species in recipient cancer cells. We further discovered that reactive oxygen species accumulation activates ERK signaling, promoting cancer cell proliferation. Pro-tumorigenic macrophages exhibit fragmented mitochondrial networks, leading to higher rates of mitochondrial transfer to cancer cells. Finally, we observe that macrophage mitochondrial transfer promotes tumor cell proliferation in vivo. Collectively these results indicate that transferred macrophage mitochondria activate downstream signaling pathways in a ROS-dependent manner in cancer cells, and provide a model of how sustained behavioral reprogramming can be mediated by a relatively small amount of transferred mitochondria in vitro and in vivo.

Voltage-dependent volume regulation controls epithelial cell extrusion and morphology.

Epithelial cells work collectively to provide a protective barrier, yet also turn over rapidly by cell death and division. If the number of dying cells does not match those dividing, the barrier would vanish, or tumors can form. Mechanical forces and the stretch-activated ion channel (SAC) Piezo1 link both processes; stretch promotes cell division and crowding triggers cell death by initiating live cell extrusion1,2. However, it was not clear how particular cells within a crowded region are selected for extrusion. Here, we show that individual cells transiently shrink via water loss before they extrude. Artificially inducing cell shrinkage by increasing extracellular osmolarity is sufficient to induce cell extrusion. Pre-extrusion cell shrinkage requires the voltage-gated potassium channels Kv1.1 and Kv1.2 and the chloride channel SWELL1, upstream of Piezo1. Activation of these voltage-gated channels requires the mechano-sensitive Epithelial Sodium Channel, ENaC, acting as the earliest crowd-sensing step. Imaging with a voltage dye indicated that epithelial cells lose membrane potential as they become crowded and smaller, yet those selected for extrusion are markedly more depolarized than their neighbours. Loss of any of these channels in crowded conditions causes epithelial buckling, highlighting an important role for voltage and water regulation in controlling epithelial shape as well as extrusion. Thus, ENaC causes cells with similar membrane potentials to slowly shrink with compression but those with reduced membrane potentials to be eliminated by extrusion, suggesting a chief driver of cell death stems from insufficient energy to maintain cell membrane potential.

Fabrication and validation of an LED array microscope for multimodal, quantitative imaging.

The combination of multiple imaging modalities in a single microscopy system can enable new insights into biological processes. In this work, we describe the construction and rigorous characterization of a custom microscope with multimodal imaging in a single, cost-effective system. Our design utilizes advances in LED technology, robotics, and open-source software, along with existing optical components and precision optomechanical parts to offer a modular and versatile design. This microscope is operated using software written in Arduino and Python and has the ability to run multi-day automated imaging experiments when placed inside of a cell culture incubator. Additionally, we provide and demonstrate methods to validate images taken in brightfield and darkfield, along with validation and optimization for differential phase contrast (DPC) quantitative phase imaging.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine.

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer.

Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time. Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment. We find that QPI EC50 values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies.

Quantitative phase velocimetry measures bulk intracellular transport of cell mass during the cell cycle.

Transport of mass within cells helps maintain homeostasis and is disrupted by disease and stress. Here, we develop quantitative phase velocimetry (QPV) as a label-free approach to make the invisible flow of mass within cells visible and quantifiable. We benchmark our approach against alternative image registration methods, a theoretical error model, and synthetic data. Our method tracks not just individual labeled particles or molecules, but the entire flow of bulk material through the cell. This enables us to measure diffusivity within distinct cell compartments using a single approach, which we use here for direct comparison of nuclear and cytoplasmic diffusivity. As a label-free method, QPV can be used for long-term tracking to capture dynamics through the cell cycle.

Fabrication and Bonding of Refractive Index Matched Microfluidics for Precise Measurements of Cell Mass.

The optical properties of polymer materials used for microfluidic device fabrication can impact device performance when used for optical measurements. In particular, conventional polymer materials used for microfluidic devices have a large difference in refractive index relative to aqueous media generally used for biomedical applications. This can create artifacts when used for microscopy-based assays. Fluorination can reduce polymer refractive index, but at the cost of reduced adhesion, creating issues with device bonding. Here, we present a novel fabrication technique for bonding microfluidic devices made of NOA1348, which is a fluorinated, UV-curable polymer with a refractive index similar to that of water, to a glass substrate. This technique is compatible with soft lithography techniques, making this approach readily integrated into existing microfabrication workflows. We also demonstrate that this material is compatible with quantitative phase imaging, which we used to validate the refractive index of the material post-fabrication. Finally, we demonstrate the use of this material with a novel image processing approach to precisely quantify the mass of cells in the microchannel without the use of cell segmentation or tracking. The novel image processing approach combined with this low refractive index material eliminates an important source of error, allowing for high-precision measurements of cell mass with a coefficient of variance of 1%.

Simultaneous measurement of neurite and neural body mass accumulation via quantitative phase imaging.

Measurement of neuron behavior is crucial for studying neural development and evaluating the impact of potential therapies on neural regeneration. Conventional approaches to imaging neuronal behavior require labeling and do not separately quantify the growth processes that underlie neural regeneration. In this paper we demonstrate the use of quantitative phase imaging (QPI) as a label-free, quantitative measurement of neuron behavior in vitro. By combining QPI with image processing, our method separately measures the mass accumulation rates of soma and neurites. Additionally, the data provided by QPI can be used to separately measure the processes of maturation and formation of neurites. Overall, our approach has the potential to greatly simplify conventional neurite outgrowth measurements, while providing key data on the resources used to produce neurites during neural development.

Cell viscoelasticity is linked to fluctuations in cell biomass distributions.

The viscoelastic properties of mammalian cells can vary with biological state, such as during the epithelial-to-mesenchymal (EMT) transition in cancer, and therefore may serve as a useful physical biomarker. To characterize stiffness, conventional techniques use cell contact or invasive probes and as a result are low throughput, labor intensive, and limited by probe placement. Here, we show that measurements of biomass fluctuations in cells using quantitative phase imaging (QPI) provides a probe-free, contact-free method for quantifying changes in cell viscoelasticity. In particular, QPI measurements reveal a characteristic underdamped response of changes in cell biomass distributions versus time. The effective stiffness and viscosity values extracted from these oscillations in cell biomass distributions correlate with effective cell stiffness and viscosity measured by atomic force microscopy (AFM). This result is consistent for multiple cell lines with varying degrees of cytoskeleton disruption and during the EMT. Overall, our study demonstrates that QPI can reproducibly quantify cell viscoelasticity.

Identifying fates of cancer cells exposed to mitotic inhibitors by quantitative phase imaging.

Cell cycle deregulation is a cancer hallmark that has stimulated the development of mitotic inhibitors with differing mechanisms of action. Quantitative phase imaging (QPI) is an emerging approach for determining cancer cell sensitivities to chemotherapies in vitro. Cancer cell fates in response to mitotic inhibitors are agent- and dose-dependent. Fates that lead to chromosomal instabilities may result in a survival advantage and drug resistance. Conventional techniques for quantifying cell fates are incompatible with growth inhibition assays that produce binary live/dead results. Therefore, we used QPI to quantify post-mitotic fates of G0/G1 synchronized HeLa cervical adenocarcinoma and M202 melanoma cells during 24 h of escalating-dose exposures to mitotic inhibitors, including microtubule inhibitors paclitaxel and colchicine, and an Aurora kinase A inhibitor, VX-680. QPI determined cell fates by measuring changes in cell biomass, morphology, and mean phase-shift. Cell fates fell into three groups: (1) bipolar division from drug failure; (2) cell death or sustained mitotic arrest; and (3) aberrant endocycling or multipolar division. In this proof-of-concept study, colchicine was most effective in producing desirable outcomes of sustained mitotic arrest or death throughout its dosing range, whereas both paclitaxel and VX-680 yielded dose-dependent multipolar divisions or endocycling, respectively. Furthermore, rapid completion of mitosis associated with bipolar divisions whereas prolonged mitosis associated with multipolar divisions or cell death. Overall, QPI measurement of drug-induced cancer cell fates provides a tool to inform the development of candidate agents by quantifying the dosing ranges over which suboptimal inhibitor choices lead to undesirable, aberrant cancer cell fates.

Ampk regulates IgD expression but not energy stress with B cell activation.

Ampk is an energy gatekeeper that responds to decreases in ATP by inhibiting energy-consuming anabolic processes and promoting energy-generating catabolic processes. Recently, we showed that Lkb1, an understudied kinase in B lymphocytes and a major upstream kinase for Ampk, had critical and unexpected roles in activating naïve B cells and in germinal center formation. Therefore, we examined whether Lkb1 activities during B cell activation depend on Ampk and report surprising Ampk activation with in vitro B cell stimulation in the absence of energy stress, coupled to rapid biomass accumulation. Despite Ampk activation and a controlling role for Lkb1 in B cell activation, Ampk knockout did not significantly affect B cell activation, differentiation, nutrient dynamics, gene expression, or humoral immune responses. Instead, Ampk loss specifically repressed the transcriptional expression of IgD and its regulator, Zfp318. Results also reveal that early activation of Ampk by phenformin treatment impairs germinal center formation but does not significantly alter antibody responses. Combined, the data show an unexpectedly specific role for Ampk in the regulation of IgD expression during B cell activation.

Fabrication of Refractive-index-matched Devices for Biomedical Microfluidics.

The use of microfluidic devices has emerged as a defining tool for biomedical applications. When combined with modern microscopy techniques, these devices can be implemented as part of a robust platform capable of making simultaneous complementary measurements. The primary challenge created by the combination of these two techniques is the mismatch in refractive index between the materials traditionally used to make microfluidic devices and the aqueous solutions typically used in biomedicine. This mismatch can create optical artifacts near the channel or device edges. One solution is to reduce the refractive index of the material used to fabricate the device by using a fluorinated polymer such as MY133-V2000 whose refractive index is similar to that of water (n = 1.33). Here, the construction of a microfluidic device made out of MY133-V2000 using soft lithography techniques is demonstrated, using O2 plasma in conjunction with an acrylic holder to increase the adhesion between the MY133-V2000 fabricated device and the polydimethylsiloxane (PDMS) substrate. The device is then tested by incubating it filled with cell culture media for 24 h to demonstrate the ability of the device to maintain cell culture conditions during the course of a typical imaging experiment. Finally, quantitative phase microscopy (QPM) is used to measure the distribution of mass within the live adherent cells in the microchannel. This way, the increased precision, enabled by fabricating the device from a low index of refraction polymer such as MY133-V2000 in lieu of traditional soft lithography materials such as PDMS, is demonstrated. Overall, this approach for fabricating microfluidic devices can be readily integrated into existing soft lithography workflows in order to reduce optical artifacts and increase measurement precision.

Soft lithography fabrication of index-matched microfluidic devices for reducing artifacts in fluorescence and quantitative phase imaging.

Microfluidic devices are widely used for biomedical applications based on microscopy or other optical detection methods. However, the materials commonly used for microfabrication typically have a high refractive index relative to water, which can create artifacts at device edges and limit applicability to applications requiring high precision imaging or morphological feature detection. Here we present a soft lithography method to fabricate microfluidic devices out of MY133-V2000, a UV-curable, fluorinated polymer with low refractive index that is close to that of water (n = 1.33). The primary challenge in the use of this material (and fluorinated materials in general) is the low adhesion of the fluorinated material; we present several alternative fabrication methods we have tested to improve inter-layer adhesion. The close match between the refractive index of this material and aqueous solutions commonly used in biomedical applications enables fluorescence imaging at microchannel or other microfabricated edges without distortion. The close match in refractive index also enables quantitative phase microscopy (QPM) imaging across the full width of microchannels without error-inducing artifacts for measurement of cell biomass. Overall, our results demonstrate the utility of low-refractive index microfluidics for biological applications requiring high precision optical imaging.

Nongenetic origins of cell-to-cell variability in B lymphocyte proliferation.

Rapid antibody production in response to invading pathogens requires the dramatic expansion of pathogen-derived antigen-specific B lymphocyte populations. Whether B cell population dynamics are based on stochastic competition between competing cell fates, as in the development of competence by the bacterium Bacillus subtilis, or on deterministic cell fate decisions that execute a predictable program, as during the development of the worm Caenorhabditis elegans, remains unclear. Here, we developed long-term live-cell microscopy of B cell population expansion and multiscale mechanistic computational modeling to characterize the role of molecular noise in determining phenotype heterogeneity. We show that the cell lineage trees underlying B cell population dynamics are mediated by a largely predictable decision-making process where the heterogeneity of cell proliferation and death decisions at any given timepoint largely derives from nongenetic heterogeneity in the founder cells. This means that contrary to previous models, only a minority of genetically identical founder cells contribute the majority to the population response. We computationally predict and experimentally confirm nongenetic molecular determinants that are predictive of founder cells' proliferative capacity. While founder cell heterogeneity may arise from different exposure histories, we show that it may also be due to the gradual accumulation of small amounts of intrinsic noise during the lineage differentiation process of hematopoietic stem cells to mature B cells. Our finding of the largely deterministic nature of B lymphocyte responses may provide opportunities for diagnostic and therapeutic development.

High-Speed Live-Cell Interferometry: A New Method for Quantifying Tumor Drug Resistance and Heterogeneity.

We report the development of high-speed live-cell interferometry (HSLCI), a new multisample, multidrug testing platform for directly measuring tumor therapy response via real-time optical cell biomass measurements. As a proof of concept, we show that HSLCI rapidly profiles changes in biomass in BRAF inhibitor (BRAFi)-sensitive parental melanoma cell lines and in their isogenic BRAFi-resistant sublines. We show reproducible results from two different HSLCI platforms at two institutions that generate biomass kinetic signatures capable of discriminating between BRAFi-sensitive and -resistant melanoma cells within 24 h. Like other quantitative phase imaging (QPI) modalities, HSLCI is well-suited to noninvasive measurements of single cells and cell clusters, requiring no fluorescence or dye labeling. HSLCI is substantially faster and more sensitive than field-standard growth inhibition assays, and in terms of the number of cells measured simultaneously, the number of drugs tested in parallel, and temporal measurement range, it exceeds the state of the art by more than 10-fold. The accuracy and speed of HSLCI in profiling tumor cell heterogeneity and therapy resistance are promising features of potential tools to guide patient therapeutic selections.

Hybrid random walk-linear discriminant analysis method for unwrapping quantitative phase microscopy images of biological samples.

Standard algorithms for phase unwrapping often fail for interferometric quantitative phase imaging (QPI) of biological samples due to the variable morphology of these samples and the requirement to image at low light intensities to avoid phototoxicity. We describe a new algorithm combining random walk-based image segmentation with linear discriminant analysis (LDA)-based feature detection, using assumptions about the morphology of biological samples to account for phase ambiguities when standard methods have failed. We present three versions of our method: first, a method for LDA image segmentation based on a manually compiled training dataset; second, a method using a random walker (RW) algorithm informed by the assumed properties of a biological phase image; and third, an algorithm which combines LDA-based edge detection with an efficient RW algorithm. We show that the combination of LDA plus the RW algorithm gives the best overall performance with little speed penalty compared to LDA alone, and that this algorithm can be further optimized using a genetic algorithm to yield superior performance for phase unwrapping of QPI data from biological samples.

Live cell interferometry quantifies dynamics of biomass partitioning during cytokinesis.

The equal partitioning of cell mass between daughters is the usual and expected outcome of cytokinesis for self-renewing cells. However, most studies of partitioning during cell division have focused on daughter cell shape symmetry or segregation of chromosomes. Here, we use live cell interferometry (LCI) to quantify the partitioning of daughter cell mass during and following cytokinesis. We use adherent and non-adherent mouse fibroblast and mouse and human lymphocyte cell lines as models and show that, on average, mass asymmetries present at the time of cleavage furrow formation persist through cytokinesis. The addition of multiple cytoskeleton-disrupting agents leads to increased asymmetry in mass partitioning which suggests the absence of active mass partitioning mechanisms after cleavage furrow positioning.

Live-cell mass profiling: an emerging approach in quantitative biophysics.

Cell mass, volume and growth rate are tightly controlled biophysical parameters in cellular development and homeostasis, and pathological cell growth defines cancer in metazoans. The first measurements of cell mass were made in the 1950s, but only recently have advances in computer science and microfabrication spurred the rapid development of precision mass-quantifying approaches. Here we discuss available techniques for quantifying the mass of single live cells with an emphasis on relative features, capabilities and drawbacks for different applications.