Functional profiling of circulating tumor cells with an integrated vortex capture and single-cell protease activity assay.

Tumor cells are hypothesized to use proteolytic enzymes to facilitate invasion. Whether circulating tumor cells (CTCs) secrete these enzymes to aid metastasis is unknown. A quantitative and high-throughput approach to assay CTC secretion is needed to address this question. We developed an integrated microfluidic system that concentrates rare cancer cells >100,000-fold from 1 mL of whole blood into ∼50,000 2-nL drops composed of assay reagents within 15 min. The system isolates CTCs by size, exchanges fluid around CTCs to remove contaminants, introduces a matrix metalloprotease (MMP) substrate, and encapsulates CTCs into microdroplets. We found CTCs from prostate cancer patients possessed above baseline levels of MMP activity (1.7- to 200-fold). Activity of CTCs was generally higher than leukocytes from the same patient (average CTC/leukocyte MMP activity ratio, 2.6 ± 1.5). Higher MMP activity of CTCs suggests active proteolytic processes that may facilitate invasion or immune evasion and be relevant phenotypic biomarkers enabling companion diagnostics for anti-MMP therapies.

TAPIR: a T-cell receptor language model for predicting rare and novel targets.

T-cell receptors (TCRs) are involved in most human diseases, but linking their sequences with their targets remains an unsolved grand challenge in the field. In this study, we present TAPIR (T-cell receptor and Peptide Interaction Recognizer), a T-cell receptor (TCR) language model that predicts TCR-target interactions, with a focus on novel and rare targets. TAPIR employs deep convolutional neural network (CNN) encoders to process TCR and target sequences across flexible representations (e.g., beta-chain only, unknown MHC allele, etc.) and learns patterns of interactivity via several training tasks. This flexibility allows TAPIR to train on more than 50k either paired (alpha and beta chain) or unpaired TCRs (just alpha or beta chain) from public and proprietary databases against 1933 unique targets. TAPIR demonstrates state-of-the-art performance when predicting TCR interactivity against common benchmark targets and is the first method to demonstrate strong performance when predicting TCR interactivity against novel targets, where no examples are provided in training. TAPIR is also capable of predicting TCR interaction against MHC alleles in the absence of target information. Leveraging these capabilities, we apply TAPIR to cancer patient TCR repertoires and identify and validate a novel and potent anti-cancer T-cell receptor against a shared cancer neoantigen target (PIK3CA H1047L). We further show how TAPIR, when extended with a generative neural network, is capable of directly designing T-cell receptor sequences that interact with a target of interest.

Evaluation of PD-L1 expression on vortex-isolated circulating tumor cells in metastatic lung cancer.

Metastatic non-small cell lung cancer (NSCLC) is a highly fatal and immunogenic malignancy. Although the immune system is known to recognize these tumor cells, one mechanism by which NSCLC can evade the immune system is via overexpression of programmed cell death ligand 1 (PD-L1). Recent clinical trials of PD-1 and PD-L1 inhibitors have returned promising clinical responses. Important for personalizing therapy, patients with higher intensity staining for PD-L1 on tumor biopsies responded better. Thus, there has been interest in using PD-L1 tumor expression as a criterion for patient selection. Currently available methods of screening involve invasive tumor biopsy, followed by histological grading of PD-L1 levels. Biopsies have a high risk of complications, and only allow sampling from limited tumor sections, which may not reflect overall tumor heterogeneity. Circulating tumor cell (CTC) PD-L1 levels could aid in screening patients, and could supplement tissue PD-L1 biopsy results by testing PD-L1 expression from disseminated tumor sites. Towards establishing CTCs as a screening tool, we developed a protocol to isolate CTCs at high purity and immunostain for PD-L1. Monitoring of PD-L1 expression on CTCs could be an additional biomarker for precision medicine that may help in determining response to immunotherapies.

Correction: Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting.

Correction for 'Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting' by Coleman Murray et al., Lab Chip, 2018, 18, 2396-2409.

Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting.

Immunotherapies (IT) require induction, expansion, and maintenance of specific changes to a patient's immune cell repertoire which yield a therapeutic benefit. Recently, mechanistic understanding of these changes at the cellular level has revealed that IT results in complex phenotypic transitions in target cells, and that therapeutic effectiveness may be predicted by monitoring these transitions during therapy. However, monitoring will require unique tools that enable capture, manipulation, and profiling of rare immune cell populations. In this study, we introduce a method of automated and unsupervised separation and processing of rare immune cells, using high-force and multidimensional magnetic ratcheting (MR). We demonstrate capture of target immune cells using samples with up to 1 : 10 000 target cell to background cell ratios from input volumes as small as 25 microliters (i.e. a low volume and low cell frequency sample sparing assay interface). Cell capture is shown to achieve up to 90% capture efficiency and purity, and captured cell analysis is shown using both on-chip culture/activity assays and off-chip ejection and nucleic acid analysis. These results demonstrate that multi-directional magnetic ratcheting offers a unique separation system for dealing with blood cell samples that contain either rare cells or significantly small volumes, and the "sample sparing" capability leads to an expanded spectrum of parameters that can be measured. These tools will be paramount to advancing techniques for immune monitoring under conditions in which both the sample volume and number of antigen-specific target cells are often exceedingly small, including during IT and treatment of allergy, asthma, autoimmunity, immunodeficiency, cell based therapy, transplantation, and infection.

High-throughput physical phenotyping of cell differentiation.

In this report, we present multiparameter deformability cytometry (m-DC), in which we explore a large set of parameters describing the physical phenotypes of pluripotent cells and their derivatives. m-DC utilizes microfluidic inertial focusing and hydrodynamic stretching of single cells in conjunction with high-speed video recording to realize high-throughput characterization of over 20 different cell motion and morphology-derived parameters. Parameters extracted from videos include size, deformability, deformation kinetics, and morphology. We train support vector machines that provide evidence that these additional physical measurements improve classification of induced pluripotent stem cells, mesenchymal stem cells, neural stem cells, and their derivatives compared to size and deformability alone. In addition, we utilize visual interactive stochastic neighbor embedding to visually map the high-dimensional physical phenotypic spaces occupied by these stem cells and their progeny and the pathways traversed during differentiation. This report demonstrates the potential of m-DC for improving understanding of physical differences that arise as cells differentiate and identifying cell subpopulations in a label-free manner. Ultimately, such approaches could broaden our understanding of subtle changes in cell phenotypes and their roles in human biology.

Classification of large circulating tumor cells isolated with ultra-high throughput microfluidic Vortex technology.

Circulating tumor cells (CTCs) are emerging as rare but clinically significant non-invasive cellular biomarkers for cancer patient prognosis, treatment selection, and treatment monitoring. Current CTC isolation approaches, such as immunoaffinity, filtration, or size-based techniques, are often limited by throughput, purity, large output volumes, or inability to obtain viable cells for downstream analysis. For all technologies, traditional immunofluorescent staining alone has been employed to distinguish and confirm the presence of isolated CTCs among contaminating blood cells, although cells isolated by size may express vastly different phenotypes. Consequently, CTC definitions have been non-trivial, researcher-dependent, and evolving. Here we describe a complete set of objective criteria, leveraging well-established cytomorphological features of malignancy, by which we identify large CTCs. We apply the criteria to CTCs enriched from stage IV lung and breast cancer patient blood samples using the High Throughput Vortex Chip (Vortex HT), an improved microfluidic technology for the label-free, size-based enrichment and concentration of rare cells. We achieve improved capture efficiency (up to 83%), high speed of processing (8 mL/min of 10x diluted blood, or 800 µL/min of whole blood), and high purity (avg. background of 28.8±23.6 white blood cells per mL of whole blood). We show markedly improved performance of CTC capture (84% positive test rate) in comparison to previous Vortex designs and the current FDA-approved gold standard CellSearch assay. The results demonstrate the ability to quickly collect viable and pure populations of abnormal large circulating cells unbiased by molecular characteristics, which helps uncover further heterogeneity in these cells.

Label-free enumeration, collection and downstream cytological and cytogenetic analysis of circulating tumor cells.

Circulating tumor cells (CTCs) have a great potential as indicators of metastatic disease that may help physicians improve cancer prognostication, treatment and patient outcomes. Heterogeneous marker expression as well as the complexity of current antibody-based isolation and analysis systems highlights the need for alternative methods. In this work, we use a microfluidic Vortex device that can selectively isolate potential tumor cells from blood independent of cell surface expression. This system was adapted to interface with three protein-marker-free analysis techniques: (i) an in-flow automated image processing system to enumerate cells released, (ii) cytological analysis using Papanicolaou (Pap) staining and (iii) fluorescence in situ hybridization (FISH) targeting the ALK rearrangement. In-flow counting enables a rapid assessment of the cancer-associated large circulating cells in a sample within minutes to determine whether standard downstream assays such as cytological and cytogenetic analyses that are more time consuming and costly are warranted. Using our platform integrated with these workflows, we analyzed 32 non-small cell lung cancer (NSCLC) and 22 breast cancer patient samples, yielding 60 to 100% of the cancer patients with a cell count over the healthy threshold, depending on the detection method used: respectively 77.8% for automated, 60-100% for cytology, and 80% for immunostaining based enumeration.

Research highlights: microfluidic-enabled single-cell epigenetics.

Individual cells are the fundamental unit of life with diverse functions from metabolism to motility. In multicellular organisms, a single genome can give rise to tremendous variability across tissues at the single-cell level due to epigenetic differences in the genes that are expressed. Signals from the local environment or a history of signals can drive these variations, and tissues have many cell types that play separate roles. This epigenetic heterogeneity is of biological importance in normal functions such as tissue morphogenesis and can contribute to development or resistance of cancer, or other disease states. Therefore, an improved understanding of variations at the single cell level are fundamental to understanding biology and developing new approaches to combating disease. Traditional approaches to characterize epigenetic modifications of chromatin or the transcriptome of cells have often focused on blended responses of many cells in a tissue; however, such bulk measures lose spatial and temporal differences that occur from cell to cell, and cannot uncover novel or rare populations of cells. Here we highlight a flurry of recent activity to identify the mRNA profiles from thousands of single-cells as well as chromatin accessibility and histone marks on single to few hundreds of cells. Microfluidics and microfabrication have played a central role in the range of new techniques, and will likely continue to impact their further development towards routine single-cell epigenetic analysis.

Research highlights: manipulating cells inside and out.

We highlight recent work manipulating cells: from whole cells, to intracellular content, and even subcellular gradients in proteins. In the first manuscript, using interdigitated electrode arrays at a controlled tilt angle to a microchannel allows for an array of acoustic nodes that apply force and isolate larger circulating tumor cells from remaining cells in RBC-lysed blood. Moving to the subcellular scale, recent work shows the ability to use rapid bubble generation induced by a pulsed laser to transfect hundreds of thousands of cells in parallel, especially with larger cargo, such as live bacteria. Manipulating at an even finer level, our third highlighted paper applies magnetic nanoparticle-based techniques to the localization of proteins within the cytoplasm in gradient configurations. A recurring theme in the literature is how interfacing at the cellular scale is a key feature enabled by micro & nanotechnology. This feature can be exploited to achieve new capabilities for cell biologists which opens up new fundamental cell biology questions. This matching of scales and the unique advantages are well demonstrated in the articles highlighted.

High efficiency vortex trapping of circulating tumor cells.

Circulating tumor cells (CTCs) are important biomarkers for monitoring tumor dynamics and efficacy of cancer therapy. Several technologies have been demonstrated to isolate CTCs with high efficiency but achieve a low purity from a large background of blood cells. We have previously shown the ability to enrich CTCs with high purity from large volumes of blood through selective capture in microvortices using the Vortex Chip. The device consists of a narrow channel followed by a series of expansion regions called reservoirs. Fast flow in the narrow entry channel gives rise to inertial forces, which direct larger cells into trapping vortices in the reservoirs where they remain circulating in orbits. By studying the entry and stability of particles following entry into reservoirs, we discover that channel cross sectional area plays an important role in controlling the size of trapped particles, not just the orbital trajectories. Using these design modifications, we demonstrate a new device that is able to capture a wider size range of CTCs from clinical samples, uncovering further heterogeneity. This simple biophysical method opens doors for a range of downstream interventions, including genetic analysis, cell culture, and ultimately personalized cancer therapy.

Compartment model predicts VEGF secretion and investigates the effects of VEGF trap in tumor-bearing mice.

Angiogenesis, the formation of new blood vessels from existing vasculature, is important in tumor growth and metastasis. A key regulator of angiogenesis is vascular endothelial growth factor (VEGF), which has been targeted in numerous anti-angiogenic therapies aimed at inhibiting tumor angiogenesis. Systems biology approaches, including computational modeling, are useful for understanding this complex biological process and can aid in the development of novel and effective therapeutics that target the VEGF family of proteins and receptors. We have developed a computational model of VEGF transport and kinetics in the tumor-bearing mouse, which includes three-compartments: normal tissue, blood, and tumor. The model simulates human tumor xenografts and includes human (VEGF121 and VEGF165) and mouse (VEGF120 and VEGF164) isoforms. The model incorporates molecular interactions between these VEGF isoforms and receptors (VEGFR1 and VEGFR2), as well as co-receptors (NRP1 and NRP2). We also include important soluble factors: soluble VEGFR1 (sFlt-1) and α-2-macroglobulin. The model accounts for transport via macromolecular transendothelial permeability, lymphatic flow, and plasma clearance. We have fit the model to available in vivo experimental data on the plasma concentration of free VEGF Trap and VEGF Trap bound to mouse and human VEGF in order to estimate the rates at which parenchymal cells (myocytes and tumor cells) and endothelial cells secrete VEGF. Interestingly, the predicted tumor VEGF secretion rates are significantly lower (0.007-0.023 molecules/cell/s, depending on the tumor microenvironment) than most reported in vitro measurements (0.03-2.65 molecules/cell/s). The optimized model is used to investigate the interstitial and plasma VEGF concentrations and the effect of the VEGF-neutralizing agent, VEGF Trap (aflibercept). This work complements experimental studies performed in mice and provides a framework with which to examine the effects of anti-VEGF agents, aiding in the optimization of such anti-angiogenic therapeutics as well as analysis of clinical data. The model predictions also have implications for biomarker discovery with anti-angiogenic therapies.