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Neural crest cells (NCCs) are a multipotent and migratory cell population in the developing embryo that contribute to the formation of a wide range of tissues. Defects in the development, differentiation and migration of NCCs give rise to a class of syndromes and diseases that are known as neurocristopathies. NCC development has historically been studied in a variety of animal models, including xenopus, chick and mouse. In the recent years, there have been efforts to study NCC development and disease in human specific models, with protocols being established to derive NCCs from human pluripotent stem cells (hPSCs), and to further differentiate these NCCs to neural, mesenchymal and other lineages. These differentiation platforms are a valuable tool to gain a better understanding of the molecular mechanisms involved in human neural crest development. The use of induced pluripotent stem cells (iPSCs) derived from patients afflicted with neurocristopathies has also enabled the study of defective human NCC development using these platforms. Here, we review the various strategies that have been used to derive NCCs from hPSCs and to specify NCCs into cranial, trunk, and vagal subpopulations and their derivatives. We will also discuss the potential applications of these human specific NCC platforms, including the use of iPSCs for disease modeling and the potential of NCCs for future regenerative applications.

We have developed a microfluidic-based culture chip to simulate cancer cell migration and invasion across the basement membrane. In this microfluidic chip, a 3D microenvironment is engineered to culture metastatic breast cancer cells (MX1) in a 3D tumor model. A chemo-attractant was incorporated to stimulate motility across the membrane. We validated the usefulness of the chip by tracking the motilities of the cancer cells in the system, showing them to be migrating or invading (akin to metastasis). It is shown that our system can monitor cell migration in real time, as compare to Boyden chambers, for example. Thus, the chip will be of interest to the drug-screening community as it can potentially be used to monitor the behavior of cancer cell motility, and, therefore, metastasis, in the presence of anti-cancer drugs.

We present a novel framework combining single‐cell phenotypic data with single‐cell transcriptomic analysis to identify factors underpinning heterogeneity in antitumor immune response. We developed a pairwise, tumor‐immune discretized interaction assay between natural killer (NK‐92MI) cells and patient‐derived head and neck squamous cell carcinoma (HNSCC) cell lines on a microfluidic cell‐trapping platform. Furthermore we generated a deep‐learning computer vision algorithm that is capable of automating the acquisition and analysis of a large, live‐cell imaging data set (>1 million) of paired tumor‐immune interactions spanning a time course of 24 h across multiple HNSCC lines (n = 10). Finally, we combined the response data measured by Kaplan–Meier survival analysis against NK‐mediated killing with downstream single‐cell transcriptomic analysis to interrogate molecular signatures associated with NK‐effector response. As proof‐of‐concept for the proposed framework, we efficiently identified MHC class I‐driven cytotoxic resistance as a key mechanism for immune evasion in nonresponders, while enhanced expression of cell adhesion molecules was found to be correlated with sensitivity against NK‐mediated cytotoxicity. We conclude that this integrated, data‐driven phenotypic approach holds tremendous promise in advancing the rapid identification of new mechanisms and therapeutic targets related to immune evasion and response.

Osteoarthritis (OA) remains a prevalent disease affecting more than 20% of the global population, resulting in morbidity and lower quality of life for patients. The study of OA pathophysiology remains predominantly in animal models due to the complexities of mimicking the physiological environment surrounding the joint tissue. Recent development in microfluidic organ-on-chip (OoC) systems have demonstrated various techniques to mimic and modulate tissue physiological environments. Adaptations of these techniques have demonstrated success in capturing a joint tissue’s tissue physiology for studying the mechanism of OA. Adapting these techniques and strategies can help create human-specific in vitro models that recapitulate the cellular processes involved in OA. This review aims to comprehensively summarise various demonstrations of microfluidic platforms in mimicking joint microenvironments for future platform design iterations.

Traditional eye irritation assessments, which rely on animal models or ex vivo tissues, face limitations due to ethical concerns, costs, and low throughput. Although numerous in vitro tests have been developed, none have successfully reconciled the need for high experimental throughput with the accurate prediction of irritation potential, attributable to the complexity of irritation mechanisms. Simple cell models, while suitable for high-throughput screening, offer limited mechanistic insights, contrasting with more physiologically relevant but less scalable complex organotypic corneal tissue constructs. This study presents a novel strategy to enhance the predictive accuracy of screening-compatible simple cell models in eye irritation testing. Our method combines the results of two in vitro assays—cell apoptosis and nociceptor (TRPV1) activation—using micropatterned chips to partition human corneal epithelial cells into numerous discrete small populations. Following exposure to test compounds, we measure apoptosis and nociceptor activation responses. The large datasets collected from the cell micropatterns facilitate binarization and statistical fitting to calculate a mathematical probability, which assesses the compound’s potential to cause eye irritation. This method potentially enables the amalgamation of multiple mechanistic readouts into a singular index, providing a more accurate and reliable prediction of eye irritation potential in a format amenable to high-throughput screening.

Microfluidic 3D tissue culture systems are attractive for in vitro drug testing applications due to the ability of these platforms to generate 3D tissue models and perform drug testing at a very small scale. However, the minute cell number and liquid volume impose significant technical challenges to perform quantitative cell viability measurements using conventional colorimetric or fluorometric assays, such as MTS or Alamar Blue. Similarly, live-dead staining approaches often utilize metabolic dyes that typically label the cytoplasm of live cells, which makes it difficult to segment and count individual cells in compact 3D tissue cultures. In this paper, we present a quantitative image-based cell viability (QuantICV) assay technique that circumvents current challenges of performing the quantitative cell viability assay in microfluidic 3D tissue cultures. A pair of cell-impermeant nuclear dyes (EthD-1 and DAPI) were used to sequentially label the nuclei of necrotic and total cell populations, respectively. Confocal microscopy and image processing algorithms were employed to visualize and quantify the cell nuclei in the 3D tissue volume. The QuantICV assay was validated and showed good concordance with the conventional bulk MTS assay in static 2D and 3D tumor cell cultures. Finally, the QuantICV assay was employed as an on-chip readout to determine the differential dose responses of parental and metastatic 3D oral squamous cell carcinoma (OSCC) to Gefitinib in a microfluidic 3D culture device. This proposed technique can be useful in microfluidic cell cultures as well as in a situation where conventional cell viability assays are not available.

Inter-patient and intra-tumour heterogeneity (ITH) have prompted the need for a more personalised approach to cancer therapy. Although patient-derived xenograft (PDX) models can generate drug response specific to patients, they are not sustainable in terms of cost and time and have limited scalability. Tumour Organ-on-Chip (OoC) models are in vitro alternatives that can recapitulate some aspects of the 3D tumour microenvironment and can be scaled up for drug screening. While many tumour OoC systems have been developed to date, there have been limited validation studies to ascertain whether drug responses obtained from tumour OoCs are comparable to those predicted from patient-derived xenograft (PDX) models. In this study, we established a multiplexed tumour OoC device, that consists of an 8 × 4 array (32-plex) of culture chamber coupled to a concentration gradient generator. The device enabled perfusion culture of primary PDX-derived tumour spheroids to obtain dose-dependent response of 5 distinct standard-of-care (SOC) chemotherapeutic drugs for 3 colorectal cancer (CRC) patients. The in vitro efficacies of the chemotherapeutic drugs were rank-ordered for individual patients and compared to the in vivo efficacy obtained from matched PDX models. We show that quantitative correlation analysis between the drug efficacies predicted via the microfluidic perfusion culture is predictive of response in animal PDX models. This is a first study showing a comparative framework to quantitatively correlate the drug response predictions made by a microfluidic tumour organ-on-chip (OoC) model with that of PDX animal models.

Microfluidic organ-on-a-chip (OoC) technology has enabled studies on dynamic physiological conditions as well as being deployed in drug testing applications. A microfluidic pump is an essential component to perform perfusion cell culture in OoC devices. However, it is challenging to have a single pump that can fulfil both the customization function needed to mimic a myriad of physiological flow rates and profiles found in vivo and multiplexing requirements (i.e., low cost, small footprint) for drug testing operations. The advent of 3D printing technology and open-source programmable electronic controllers presents an opportunity to democratize the fabrication of mini-peristaltic pumps suitable for microfluidic applications at a fraction of the cost of commercial microfluidic pumps. However, existing 3D-printed peristaltic pumps have mainly focused on demonstrating the feasibility of using 3D printing to fabricate the structural components of the pump and neglected user experience and customization capability. Here, we present a user-centric programmable 3D-printed mini-peristaltic pump with a compact design and low manufacturing cost (~USD 175) suitable for perfusion OoC culture applications. The pump consists of a user-friendly, wired electronic module that controls the operation of a peristaltic pump module. The peristaltic pump module comprises an air-sealed stepper motor connected to a 3D-printed peristaltic assembly, which can withstand the high-humidity environment of a cell culture incubator. We demonstrated that this pump allows users to either program the electronic module or use different-sized tubing to deliver a wide range of flow rates and flow profiles. The pump also has multiplexing capability as it can accommodate multiple tubing. The performance and user-friendliness of this low-cost, compact pump can be easily deployed for various OoC applications.

Organs-on-chips (OoCs) are systems containing engineered or natural miniature tissues grown inside microfluidic chips. To better mimic human physiology, the chips are designed to control cell microenvironments and maintain tissue-specific functions. Combining advances in tissue engineering and microfabrication, OoCs have gained interest as a next-generation experimental platform to investigate human pathophysiology and the effect of therapeutics in the body. There are as many examples of OoCs as there are applications, making it difficult for new researchers to understand what makes one OoC more suited to an application than another. This Primer is intended to give an introduction to the aspects of OoC that need to be considered when developing an application-specific OoC. The Primer covers guiding principles and considerations to design, fabricate and operate an OoC, as well as subsequent assaying techniques to extract biological information from OoC devices. Alongside this is a discussion of current and future applications of OoC technology, to inform design and operational decisions during the implementation of OoC systems. Organs-on-chips are microfluidic systems containing miniature tissues with the aim of mimicking human physiology for a range of biomedical and therapeutic applications. Leung, de Haan et al. report practical tips to inform design and operational decisions during the implementation of organ-on-a-chip systems.

The generation of structurally standardized human pluripotent stem cell (hPSC)‐derived neural embryonic tissues has the potential to model genetic and environmental mediators of early neurodevelopmental defects. Current neural patterning systems have so far focused on directing cell fate specification spatio‐temporally but not morphogenetic processes. Here, the formation of a structurally reproducible and highly‐organized neuroepithelium (NE) tissue is directed from hPSCs, which recapitulates morphogenetic cellular processes relevant to early neurulation. These include having a continuous, polarized epithelium and a distinct invagination‐like folding, where primitive ectodermal cells undergo E‐to‐N‐cadherin switching and apical constriction as they acquire a NE fate. This is accomplished by spatio‐temporal patterning of the mesoendoderm, which guides the development and self‐organization of the adjacent primitive ectoderm into the NE. It is uncovered that TGFβ signaling emanating from endodermal cells support tissue folding of the prospective NE. Evaluation of NE tissue structural dysmorphia, which is uniquely achievable in the model, enables the detection of apical constriction and cell adhesion dysfunctions in patient‐derived hPSCs as well as differentiating between different classes of neural tube defect‐inducing drugs. This paper reports the generation of a reproducible and highly organized neuroepithelial (NE) tissue by combining human pluripotent stem cell (hPSC) micropatterning and a temporally sequenced induction protocol to specify NE cells in spatial juxtaposition to mesoendoderm cells. By evaluating NE tissue structural dysmorphia in the micropatterned NE model, we can successfully model gene‐ and drug‐induced neurodevelopmental defects.