Cancer-driven dynamics of immune cells in a microfluidic environment

Bridging the gap between tumor-on-chip and clinics: a systematic review of 15 years of studies

Over the past 15 years, the field of oncology research has witnessed significant progress in the development of new cell culture models, such as tumor-on-chip (ToC) systems. In this comprehensive overview, we present a multidisciplinary perspective by bringing together physicists, biologists, clinicians, and experts from pharmaceutical companies to highlight the current state of ToC research, its unique features, and the challenges it faces. To offer readers a clear and quantitative understanding of the ToC field, we conducted an extensive systematic analysis of more than 300 publications related to ToC from 2005 to 2022. ToC offer key advantages over other in vitro models by enabling precise control over various parameters. These parameters include the properties of the extracellular matrix, mechanical forces exerted on cells, the physico-chemical environment, cell composition, and the architecture of the tumor microenvironment. Such fine control allows ToC to closely replicate the complex microenvironment and interactions within tumors, facilitating the study of cancer progression and therapeutic responses in a highly representative manner. Importantly, by incorporating patient-derived cells or tumor xenografts, ToC models have demonstrated promising results in terms of clinical validation. We also examined the potential of ToC for pharmaceutical industries in which ToC adoption is expected to occur gradually. Looking ahead, given the high failure rate of clinical trials and the increasing emphasis on the 3Rs principles (replacement, reduction, refinement of animal experimentation), ToC models hold immense potential for cancer research. In the next decade, data generated from ToC models could potentially be employed for discovering new therapeutic targets, contributing to regulatory purposes, refining preclinical drug testing and reducing reliance on animal models.

Quantifying heterogeneity to drug response in cancer-stroma kinetics

A crucial challenge in medicine is choosing which drug (or combination) will be the most advantageous for a particular patient. Usually, drug response rates differ substantially, and the reasons for this response unpredictability remain ambiguous. Consequently, it is central to classify features that contribute to the observed drug response variability. Pancreatic cancer is one of the deadliest cancers with limited therapeutic achievements due to the massive presence of stroma that generates an environment that enables tumor growth, metastasis, and drug resistance. To understand the cancer-stroma cross talk within the tumor microenvironment and to develop personalized adjuvant therapies, there is a necessity for effective approaches that offer measurable data to monitor the effect of drugs at the single-cell level. Here, we develop a computational approach, based on cell imaging, that quantifies the cellular cross talk between pancreatic tumor cells (L3.6pl or AsPC1) and pancreatic stellate cells (PSCs), coordinating their kinetics in presence of the chemotherapeutic agent gemcitabine. We report significant heterogeneity in the organization of cellular interactions in response to the drug. For L3.6pl cells, gemcitabine sensibly decreases stroma-stroma interactions but increases stroma-cancer interactions, overall enhancing motility and crowding. In the AsPC1 case, gemcitabine promotes the interactions among tumor cells, but it does not affect stroma-cancer interplay, possibly suggesting a milder effect of the drug on cell dynamics.

Advancements in melanoma cancer metastasis models

Metastatic melanoma is a complex and deadly disease. Due to its complexity, the development of novel therapeutic strategies to inhibit metastatic melanoma remains an outstanding challenge. Our ability to study metastasis is advanced with the development of in vitro and in vivo models that better mimic the different steps of the metastatic cascade beginning from primary tumor initiation to final metastatic seeding. In this review, we provide a comprehensive summary of in vitro models, in vivo models, and in silico platforms to study the individual steps of melanoma metastasis. Furthermore, we highlight the advantages and limitations of each model and discuss the challenges of how to improve current models to enhance translation for melanoma cancer patients and future therapies.

The Applications and Challenges of the Development of In Vitro Tumor Microenvironment Chips

The tumor microenvironment (TME) plays a critical, yet mechanistically elusive role in tumor development and progression, as well as drug resistance. To better understand the pathophysiology of the complex TME, a reductionist approach has been employed to create in vitro microfluidic models called "tumor chips". Herein, we review the fabrication processes, applications, and limitations of the tumor chips currently under development for use in cancer research. Tumor chips afford capabilities for real-time observation, precise control of microenvironment factors (e.g. stromal and cellular components), and application of physiologically relevant fluid shear stresses and perturbations. Applications for tumor chips include drug screening and toxicity testing, assessment of drug delivery modalities, and studies of transport and interactions of immune cells and circulating tumor cells with primary tumor sites. The utility of tumor chips is currently limited by the ability to recapitulate the nuances of tumor physiology, including extracellular matrix composition and stiffness, heterogeneity of cellular components, hypoxic gradients, and inclusion of blood cells and the coagulome in the blood microenvironment. Overcoming these challenges and improving the physiological relevance of in vitro tumor models could provide powerful testing platforms in cancer research and decrease the need for animal and clinical studies.

From simplicity to complexity in current melanoma models

Despite the recent impressive clinical success of immunotherapy against melanoma, development of primary and adaptive resistance against immune checkpoint inhibitors remains a major issue in a large number of treated patients. This highlights the need for melanoma models that replicate the tumor's intricate dynamics in the tumor microenvironment (TME) and associated immune suppression to study possible resistance mechanisms in order to improve current and test novel therapeutics. While two-dimensional melanoma cell cultures have been widely used to perform functional genomics screens in a high-throughput fashion, they are not suitable to answer more complex scientific questions. Melanoma models have also been established in a variety of experimental (humanized) animals. However, due to differences in physiology, such models do not fully represent human melanoma development. Therefore, fully human three-dimensional in vitro models mimicking melanoma cell interactions with the TME are being developed to address this need for more physiologically relevant models. Such models include melanoma organoids, spheroids, and reconstructed human melanoma-in-skin cultures. Still, while major advances have been made to complement and replace animals, these in vitro systems have yet to fully recapitulate human tumor complexity. Lastly, technical advancements have been made in the organ-on-chip field to replicate functions and microstructures of in vivo human tissues and organs. This review summarizes advancements made in understanding and treating melanoma and specifically aims to discuss the progress made towards developing melanoma models, their applications, limitations, and the advances still needed to further facilitate the development of therapeutics.

A roadmap for translational cancer glycoimmunology at single cell resolution

Cancer cells can evade immune responses by exploiting inhibitory immune checkpoints. Immune checkpoint inhibitor (ICI) therapies based on anti-CTLA-4 and anti-PD-1/PD-L1 antibodies have been extensively explored over the recent years to unleash otherwise compromised anti-cancer immune responses. However, it is also well established that immune suppression is a multifactorial process involving an intricate crosstalk between cancer cells and the immune systems. The cancer glycome is emerging as a relevant source of immune checkpoints governing immunosuppressive behaviour in immune cells, paving an avenue for novel immunotherapeutic options. This review addresses the current state-of-the-art concerning the role played by glycans controlling innate and adaptive immune responses, while shedding light on available experimental models for glycoimmunology. We also emphasize the tremendous progress observed in the development of humanized models for immunology, the paramount contribution of advances in high-throughput single-cell analysis in this context, and the importance of including predictive machine learning algorithms in translational research. This may constitute an important roadmap for glycoimmunology, supporting careful adoption of models foreseeing clinical translation of fundamental glycobiology knowledge towards next generation immunotherapies.

Immunotherapy discovery on tumor organoid-on-a-chip platforms that recapitulate the tumor microenvironment

Cancer immunotherapy has achieved remarkable success over the past decade by modulating patients' own immune systems and unleashing pre-existing immunity. However, only a minority of cancer patients across different cancer types are able to benefit from immunotherapy treatment; moreover, among those small portions of patients with response, intrinsic and acquired resistance remains a persistent challenge. Because the tumor microenvironment (TME) is well recognized to play a critical role in tumor initiation, progression, metastasis, and the suppression of the immune system and responses to immunotherapy, understanding the interactions between the TME and the immune system is a pivotal step in developing novel and efficient cancer immunotherapies. With unique features such as low reagent consumption, dynamic and precise fluid control, versatile structures and function designs, and 3D cell co-culture, microfluidic tumor organoid-on-a-chip platforms that recapitulate key factors of the TME and the immune contexture have emerged as innovative reliable tools to investigate how tumors regulate their TME to counteract antitumor immunity and the mechanism of tumor resistance to immunotherapy. In this comprehensive review, we focus on recent advances in tumor organoid-on-a-chip platforms for studying the interaction between the TME and the immune system. We first review different factors of the TME that recent microfluidic in vitro systems reproduce to generate advanced tools to imitate the crosstalk between the TME and the immune system. Then, we discuss their applications in the assessment of different immunotherapies' efficacy using tumor organoid-on-a-chip platforms. Finally, we present an overview and the outlook of engineered microfluidic platforms in investigating the interactions between cancer and immune systems, and the adoption of patient-on-a-chip models in clinical applications toward personalized immunotherapy.

Mimicking Tumor Microenvironment by 3D Bioprinting: 3D Cancer Modeling

The tumor microenvironment typically comprises cancer cells, tumor vasculature, stromal components like fibroblasts, and host immune cells that assemble to support tumorigenesis. However, preexisting classic cancer models like 2D cell culture methods, 3D cancer spheroids, and tumor organoids seem to lack essential tumor microenvironment components. 3D bioprinting offers enormous advantages for developing in vitro tumor models by allowing user-controlled deposition of multiple biomaterials, cells, and biomolecules in a predefined architecture. This review highlights the recent developments in 3D cancer modeling using different bioprinting techniques to recreate the TME. 3D bioprinters enable fabrication of high-resolution microstructures to reproduce TME intricacies. Furthermore, 3D bioprinted models can be applied as a preclinical model for versatile research applications in the tumor biology and pharmaceutical industries. These models provide an opportunity to develop high-throughput drug screening platforms and can further be developed to suit individual patient requirements hence giving a boost to the field of personalized anti-cancer therapeutics. We underlined the various ways the existing studies have tried to mimic the TME, mimic the hallmark events of cancer growth and metastasis within the 3D bioprinted models and showcase the 3D drug-tumor interaction and further utilization of such models to develop personalized medicine.

The Patient-Derived Cancer Organoids: Promises and Challenges as Platforms for Cancer Discovery

The cancer burden is rapidly increasing in most countries, and thus, new anticancer drugs for effective cancer therapy must be developed. Cancer model systems that recapitulate the biological processes of human cancers are one of the cores of the drug development process. PDCO has emerged as a unique model that preserves the genetic, physiological, and histologic characteristics of original cancer, including inter- and intratumoral heterogeneities. Due to these advantages, the PCDO model is increasingly investigated for anticancer drug screening and efficacy testing, preclinical patient stratification, and precision medicine for selecting the most effective anticancer therapy for patients. Here, we review the prospects and limitations of PDCO compared to the conventional cancer models. With advances in culture success rates, co-culture systems with the tumor microenvironment, organoid-on-a-chip technology, and automation technology, PDCO will become the most promising model to develop anticancer drugs and precision medicine.

An Agent-Based Interpretation of Leukocyte Chemotaxis in Cancer-on-Chip Experiments

The present paper was inspired by recent developments in laboratory experiments within the framework of cancer-on-chip technology, an immune-oncology microfluidic chip aiming at studying the fundamental mechanisms of immunocompetent behavior. We focus on the laboratory setting where cancer is treated with chemotherapy drugs, and in this case, the effects of the treatment administration hypothesized by biologists are: the absence of migration and proliferation of tumor cells, which are dying; the stimulation of the production of chemical substances (annexin); the migration of leukocytes in the direction of higher concentrations of chemicals. Here, following the physiological hypotheses made by biologists on the phenomena occurring in these experiments, we introduce an agent-based model reproducing the dynamics of two cell populations (agents), i.e., tumor cells and leukocytes living in the microfluidic chip environment. Our model aims at proof of concept, demonstrating that the observations of the biological phenomena can be obtained by the model on the basis of the explicit assumptions made. In this framework, close adherence of the computational model to the biological results, as shown in the section devoted to the first calibration of the model with respect to available observations, is successfully accomplished.

Understanding and improving cellular immunotherapies against cancer: From cell-manufacturing to tumor-immune models

The tumor microenvironment (TME) is shaped by dynamic metabolic and immune interactions between precancerous and cancerous tumor cells and stromal cells like epithelial cells, fibroblasts, endothelial cells, and hematopoietically-derived immune cells. The metabolic states of the TME, including the hypoxic and acidic niches, influence the immunosuppressive phenotypes of the stromal and immune cells, which confers resistance to both host-mediated tumor killing and therapeutics. Numerous in vitro TME platforms for studying immunotherapies, including cell therapies, are being developed. However, we do not yet understand which immune and stromal components are most critical and how much model complexity is needed to answer specific questions. In addition, scalable sourcing and quality-control of appropriate TME cells for reproducibly manufacturing these platforms remain challenging. In this regard, lessons from the manufacturing of immunomodulatory cell therapies could provide helpful guidance. Although immune cell therapies have shown unprecedented results in hematological cancers and hold promise in solid tumors, their manufacture poses significant scale, cost, and quality control challenges. This review first provides an overview of the in vivo TME, discussing the most influential cell populations in the tumor-immune landscape. Next, we summarize current approaches for cell therapies against cancers and the relevant manufacturing platforms. We then evaluate current immune-tumor models of the TME and immunotherapies, highlighting the complexity, architecture, function, and cell sources. Finally, we present the technical and fundamental knowledge gaps in both cell manufacturing systems and immune-TME models that must be addressed to elucidate the interactions between endogenous tumor immunity and exogenous engineered immunity.

Estimation Algorithm for a Hybrid PDE–ODE Model Inspired by Immunocompetent Cancer-on-Chip Experiment

The present work is motivated by the development of a mathematical model mimicking the mechanisms observed in lab-on-chip experiments, made to reproduce on microfluidic chips the in vivo reality. Here we consider the Cancer-on-Chip experiment where tumor cells are treated with chemotherapy drug and secrete chemical signals in the environment attracting multiple immune cell species. The in silico model here proposed goes towards the construction of a “digital twin” of the experimental immune cells in the chip environment to better understand the complex mechanisms of immunosurveillance. To this aim, we develop a tumor-immune microfluidic hybrid PDE–ODE model to describe the concentration of chemicals in the Cancer-on-Chip environment and immune cells migration. The development of a trustable simulation algorithm, able to reproduce the immunocompetent dynamics observed in the chip, requires an efficient tool for the calibration of the model parameters. In this respect, the present paper represents a first methodological work to test the feasibility and the soundness of the calibration technique here proposed, based on a multidimensional spline interpolation technique for the time-varying velocity field surfaces obtained from cell trajectories.

Engineered in vitro tumor models for cell-based immunotherapy

Tumor immunotherapy is rapidly evolving as one of the major pillars of cancer treatment. Cell-based immunotherapies, which utilize patient's own immune cells to eliminate cancer cells, have shown great promise in treating a range of malignancies, especially those of hematopoietic origins. However, their performance on a broader spectrum of solid tumor types still fall short of expectations in the clinical stage despite promising preclinical assessments. In this review, we briefly introduce cell-based immunotherapies and the inhibitory mechanisms in tumor microenvironments that may have contributed to this discrepancy. Specifically, a major obstacle to the clinical translation of cell-based immunotherapies is in the lack of preclinical models that can accurately assess the efficacies and mechanisms of these therapies in a (patho-)physiologically relevant manner. Lately, tissue engineering and organ-on-a-chip tools and microphysiological models have allowed for more faithful recapitulation of the tumor microenvironments, by incorporating crucial tumor tissue features such as cellular phenotypes, tissue architecture, extracellular matrix, physical parameters, and their dynamic interactions. This review summarizes the existing engineered tumor models with a focus on tumor immunology and cell-based immunotherapy. We also discuss some key considerations for the future development of engineered tumor models for immunotherapeutics. STATEMENT OF SIGNIFICANCE: Cell-based immunotherapies have shown great promise in treating hematological malignancies and some epithelial tumors. However, their performance on a broader spectrum of solid tumor types still fall short of expectations. Major obstacles include the inhibitory mechanisms in tumor microenvironments (TME) and the lack of preclinical models that can accurately assess the efficacies and mechanisms of cellular therapies in a (patho-)physiologically relevant manner. In this review, we introduce recent progress in tissue engineering and microphysiological models for more faithful recapitulation of TME for cell-based immunotherapies, and some key considerations for the future development of engineered tumor models. This overview will provide a better understanding on the role of engineered models in accelerating immunotherapeutic discoveries and clinical translations.

Meet me halfway: Are in vitro 3D cancer models on the way to replace in vivo models for nanomedicine development?

The complexity and diversity of the biochemical processes that occur during tumorigenesis and metastasis are frequently over-simplified in the traditional in vitro cell cultures. Two-dimensional cultures limit researchers' experimental observations and frequently give rise to misleading and contradictory results. Therefore, in order to overcome the limitations of in vitro studies and bridge the translational gap to in vivo applications, 3D models of cancer were developed in the last decades. The three dimensions of the tumor, including its cellular and extracellular microenvironment, are recreated by combining co-cultures of cancer and stromal cells in 3D hydrogel-based growth factors-inclusive scaffolds. More complex 3D cultures, containing functional blood vasculature, can integrate in the system external stimuli (e.g. oxygen and nutrient deprivation, cytokines, growth factors) along with drugs, or other therapeutic compounds. In this scenario, cell signaling pathways, metastatic cascade steps, cell differentiation and self-renewal, tumor-microenvironment interactions, and precision and personalized medicine, are among the wide range of biological applications that can be studied. Here, we discuss a broad variety of strategies exploited by scientists to create in vitro 3D cancer models that resemble as much as possible the biology and patho-physiology of in vivo tumors and predict faithfully the treatment outcome.

Microfluidic technologies for immunotherapy studies on solid tumours

Immunotherapy is a powerful and targeted cancer treatment that exploits the body's immune system to attack and eliminate cancerous cells. This form of therapy presents the possibility of long-term control and prevention of recurrence due to the memory capabilities of the immune system. Various immunotherapies are successful in treating haematological malignancies and have dramatically improved outcomes in melanoma. However, tackling other solid tumours is more challenging, mostly because of the immunosuppressive tumour microenvironment (TME). Current in vitro models based on traditional 2D cell monolayers and animal models, such as patient-derived xenografts, have limitations in their ability to mimic the complexity of the human TME. As a result, they have inadequate translational value and can be poorly predictive of clinical outcome. Thus, there is a need for robust in vitro preclinical tools that more faithfully recapitulate human solid tumours to test novel immunotherapies. Microfluidics and lab-on-a-chip technologies offer opportunities, especially when performing mechanistic studies, to understand the role of the TME in immunotherapy, and to expand the experimental throughput when using patient-derived tissue through its miniaturization capabilities. This review first introduces the basic concepts of immunotherapy, presents the current preclinical approaches used in immuno-oncology for solid tumours and then discusses the underlying challenges. We provide a rationale for using microfluidic-based approaches, highlighting the most recent microfluidic technologies and methodologies that have been used for studying cancer-immune cell interactions and testing the efficacy of immunotherapies in solid tumours. Ultimately, we discuss achievements and limitations of the technology, commenting on potential directions for incorporating microfluidic technologies in future immunotherapy studies.

In-vitro tumor microenvironment models containing physical and biological barriers for modelling multidrug resistance mechanisms and multidrug delivery strategies

The complexity and heterogeneity of the three-dimensional (3D) tumor microenvironment have brought challenges to tumor studies and cancer treatment. The complex functions and interactions of cells involved in tumor microenvironment have led to various multidrug resistance (MDR) and raised challenges for cancer treatment. Traditional tumor models are limited in their ability to simulate the resistance mechanisms and not conducive to the discovery of multidrug resistance and delivery processes. New technologies for making 3D tissue models have shown the potential to simulate the 3D tumor microenvironment and identify mechanisms underlying the MDR. This review overviews the main barriers against multidrug delivery in the tumor microenvironment and highlights the advances in microfluidic-based tumor models with the success in simulating several drug delivery barriers. It also presents the progress in modeling various genetic and epigenetic factors involved in regulating the tumor microenvironment as a noticeable insight in 3D microfluidic tumor models for recognizing multidrug resistance and delivery mechanisms. Further correlation between the results obtained from microfluidic drug resistance tumor models and the clinical MDR data would open up avenues to gain insight into the performance of different multidrug delivery treatment strategies.

Tissues and Tumor Microenvironment (TME) in 3D: Models to Shed Light on Immunosuppression in Cancer

Immunosuppression in cancer has emerged as a major hurdle to immunotherapy efforts. Immunosuppression can arise from oncogene-induced signaling within the tumor as well as from tumor-associated immune cells. Understanding various mechanisms by which the tumor can undermine and evade therapy is critical in improving current cancer immunotherapies. While mouse models have allowed for the characterization of key immune cell types and their role in tumor development, extrapolating these mechanisms to patients has been challenging. There is need for better models to unravel the effects of genetic alterations inherent in tumor cells and immune cells isolated from tumors on tumor growth and to investigate the feasibility of immunotherapy. Three-dimensional (3D) organoid model systems have developed rapidly over the past few years and allow for incorporation of components of the tumor microenvironment such as immune cells and the stroma. This bears great promise for derivation of patient-specific models in a dish for understanding and determining the impact on personalized immunotherapy. In this review, we will highlight the significance of current experimental models employed in the study of tumor immunosuppression and evaluate current tumor organoid-immune cell co-culture systems and their potential impact in shedding light on cancer immunosuppression.

Oncoimmunology Meets Organs-on-Chip

Oncoimmunology represents a biomedical research discipline coined to study the roles of immune system in cancer progression with the aim of discovering novel strategies to arm it against the malignancy. Infiltration of immune cells within the tumor microenvironment is an early event that results in the establishment of a dynamic cross-talk. Here, immune cells sense antigenic cues to mount a specific anti-tumor response while cancer cells emanate inhibitory signals to dampen it. Animals models have led to giant steps in this research context, and several tools to investigate the effect of immune infiltration in the tumor microenvironment are currently available. However, the use of animals represents a challenge due to ethical issues and long duration of experiments. Organs-on-chip are innovative tools not only to study how cells derived from different organs interact with each other, but also to investigate on the crosstalk between immune cells and different types of cancer cells. In this review, we describe the state-of-the-art of microfluidics and the impact of OOC in the field of oncoimmunology underlining the importance of this system in the advancements on the complexity of tumor microenvironment.

Mass-Preserving Approximation of a Chemotaxis Multi-Domain Transmission Model for Microfluidic Chips

The present work is inspired by the recent developments in laboratory experiments made on chips, where the culturing of multiple cell species was possible. The model is based on coupled reaction-diffusion-transport equations with chemotaxis and takes into account the interactions among cell populations and the possibility of drug administration for drug testing effects. Our effort is devoted to the development of a simulation tool that is able to reproduce the chemotactic movement and the interactions between different cell species (immune and cancer cells) living in a microfluidic chip environment. The main issues faced in this work are the introduction of mass-preserving and positivity-preserving conditions, involving the balancing of incoming and outgoing fluxes passing through interfaces between 2D and 1D domains of the chip and the development of mass-preserving and positivity preserving numerical conditions at the external boundaries and at the interfaces between 2D and 1D domains.

Engineered models of tumor metastasis with immune cell contributions

Most cancer deaths are due to tumor metastasis rather than the primary tumor. Metastasis is a highly complex and dynamic process that requires orchestration of signaling between the tumor, its local environment, distant tissue sites, and immune system. Animal models of cancer metastasis provide the necessary systemic environment but lack control over factors that regulate cancer progression and often do not recapitulate the properties of human cancers. Bioengineered "organs-on-a-chip" that incorporate the primary tumor, metastatic tissue targets, and microfluidic perfusion are now emerging as quantitative human models of tumor metastasis. The ability of these systems to model tumor metastasis in individualized, patient-specific settings makes them uniquely suitable for studies of cancer biology and developmental testing of new treatments. In this review, we focus on human multi-organ platforms that incorporate circulating and tissue-resident immune cells in studies of tumor metastasis.

Engineering approaches for studying immune-tumor cell interactions and immunotherapy

This review describes recent research that has advanced our understanding of the role of immune cells in the tumor microenvironment (TME) using advanced 3D in vitro models and engineering approaches. The TME can hinder effective eradication of tumor cells by the immune system, but immunotherapy has been able to reverse this effect in some cases. However, patient-to-patient variability in response suggests that we require deeper understanding of the mechanistic interactions between immune and tumor cells to improve response and develop novel therapeutics. Reconstruction of the TME using engineered 3D models allows high-resolution observation of cell interactions while allowing control of conditions such as hypoxia, matrix stiffness, and flow. Moreover, patient-derived organotypic models are an emerging tool for prediction of drug efficacy. This review highlights the importance of modeling and understanding the immune TME and describes new tools for identifying new biological targets, drug testing, and strategies for personalized medicine.

3D Tumor Models and Their Use for the Testing of Immunotherapies

Over the past decade, immunotherapy has become a powerful and evident tool in the fight against cancers. Notably, the rise of checkpoint blockade using monoclonal antibodies (anti-CTLA4, anti-PD1) to avoid interaction between inhibitory molecules allowed the betterment of patient care. Indeed, immunotherapies led to increased overall survival in forms of cutaneous melanoma or lung cancer. However, the percentage of patients responding varies from 20 to 40% depending on the type of cancer and on the expression of the target molecules by the tumor. This is due to the tumor microenvironment which allows the acquisition of resistance mechanisms to immunotherapies by tumor cells. These are closely linked to the architecture and cellular composition of the tumor microenvironment. This one acts on different parameters such as the immune cells infiltrate its composition and therefore, favors the recruitment of immunosuppressive cells as well as the tumor expression of checkpoint inhibitors such as Programmed Death Ligand-1 (PD-L1). Therefore, the analysis and modeling of the complexity of the microenvironment is an important parameter to consider, not only in the search for new therapies but also for the identification and stratification of patients likely to respond to immunotherapy. This is why the use of 3D culture models, reflecting the architecture and cellular composition of a tumor, is essential in immuno-oncology studies. Nowadays, there are several 3-D culture methods such as spheroids and organoids, which are applicable to immuno-oncology. In this review we evaluate 3D culture models as tools for the development of treatments in the field of immuno-oncology.

Advanced cell culture techniques for cancer research

The incessant increase number of cancer cases, motivates scientists to constantly develop and search for new therapies. Along with the dynamic development of anti-cancer drugs and therapies, we are witnessing huge progress in the world of science - the development of personalized medicine. An inseparable element is also a very strong trend in the development of new in vitro animal models for chemotherapeutic research. Cell cultures are commonly undertaken by research models before animal testing. They are the basis for the development of new diagnostic and cancer treatments. It should be emphasized that basic research is a strong foundation for any therapy introduced. This chapter provides an overview of the modern cell culture techniques that are currently developing, which allow the introduction of modern models that reflect the organs and physiological system. Currently available cell culture methods are a key aspect of studying these interactions, however, a method that eliminates the limitations of standard methods is still being sought.

Immune Organs and Immune Cells on a Chip: An Overview of Biomedical Applications

Understanding the immune system is of great importance for the development of drugs and the design of medical implants. Traditionally, two-dimensional static cultures have been used to investigate the immune system in vitro, while animal models have been used to study the immune system’s function and behavior in vivo. However, these conventional models do not fully emulate the complexity of the human immune system or the human in vivo microenvironment. Consequently, many promising preclinical findings have not been reproduced in human clinical trials. Organ-on-a-chip platforms can provide a solution to bridge this gap by offering human micro-(patho)physiological systems in which the immune system can be studied. This review provides an overview of the existing immune-organs-on-a-chip platforms, with a special emphasis on interorgan communication. In addition, future challenges to develop a comprehensive immune system-on-chip model are discussed.

Evaluation of cytotoxic T lymphocyte-mediated anticancer response against tumor interstitium-simulating physical barriers

Tumor antigen-specific cytotoxic T lymphocyte (CTL) is a promising agent for cancer therapy. Most solid tumors are characterized by increased interstitial fluid pressure (IFP) and dense collagen capsule, which form physical barriers to impede cancer treatment. However, it remains unclear how CTL-mediated anticancer response is affected at the presence of these obstacles. Using a microfluidic-based platform mimicking these obstacles, we investigated the migration characteristics and performance of anticancer response of CTLs targeting hepatic cancer cells via antigen-specific and allogeneic recognition. The device consisted of slit channels mimicking the narrow interstitial paths constrained by the fibrous capsule and increased IFP was simulated by applying hydrostatic pressure to the tumor center. We found that antigen-specificity of CTLs against the targeted cancer cells determined the cytotoxic efficacy of the CTLs but did not significantly affect the success rate in CTLs that attempted to infiltrate into the tumor center. When increased IFP was present in the tumor center, CTL recruitment to tumor peripheries was promoted but success of infiltration was hindered. Our results highlight the importance of incorporating the physical characteristics of tumor interstitum into the development of CTL-based cancer immunotherapy.

Cell and tissue engineering in lymph nodes for cancer immunotherapy

In cancer, lymph nodes (LNs) coordinate tumor antigen presentation necessary for effective antitumor immunity, both at the levels of local cellular interactions and tissue-level organization. In this review, we examine how LNs may be engineered to improve the therapeutic outcomes of cancer immunotherapy. At the cellular scale, targeting the LNs impacts the potency of cancer vaccines, immune checkpoint blockade, and adoptive cell transfer. On a tissue level, macro-scale biomaterials mimicking LN features can function as immune niches for cell reprogramming or delivery in vivo, or be utilized in vitro to enable preclinical testing of drugs and vaccines. We additionally review strategies to induce ectopic lymphoid sites reminiscent of LNs that may improve antitumor T cell priming.

How single-cell immunology is benefiting from microfluidic technologies

The immune system is a complex network of specialized cells that work in concert to protect against invading pathogens and tissue damage. Imbalances in this network often result in excessive or absent immune responses leading to allergies, autoimmune diseases, and cancer. Many of the mechanisms and their regulation remain poorly understood. Immune cells are highly diverse, and an immune response is the result of a large number of molecular and cellular interactions both in time and space. Conventional bulk methods are often prone to miss important details by returning population-averaged results. There is a need in immunology to measure single cells and to study the dynamic interplay of immune cells with their environment. Advances in the fields of microsystems and microengineering gave rise to the field of microfluidics and its application to biology. Microfluidic systems enable the precise control of small volumes in the femto- to nanoliter range. By controlling device geometries, surface chemistry, and flow behavior, microfluidics can create a precisely defined microenvironment for single-cell studies with spatio-temporal control. These features are highly desirable for single-cell analysis and have made microfluidic devices useful tools for studying complex immune systems. In addition, microfluidic devices can achieve high-throughput measurements, enabling in-depth studies of complex systems. Microfluidics has been used in a large panel of biological applications, ranging from single-cell genomics, cell signaling and dynamics to cell-cell interaction and cell migration studies. In this review, we give an overview of state-of-the-art microfluidic techniques, their application to single-cell immunology, their advantages and drawbacks, and provide an outlook for the future of single-cell technologies in research and medicine.

A brief history of organoids

In vitro cell cultures are crucial research tools for modeling human development and diseases. Although the conventional monolayer cell cultures have been widely used in the past, the lack of tissue architecture and complexity of such model fails to inform the true biological processes in vivo. Recent advances in the organoid technology have revolutionized the in vitro culture tools for biomedical research by creating powerful three-dimensional (3D) models to recapitulate the cellular heterogeneity, structure, and functions of the primary tissues. Such organoid technology enables researchers to recreate human organs and diseases in a dish and thus holds great promises for many translational applications such as regenerative medicine, drug discovery, and precision medicine. In this review, we provide an overview of the organoid history and development. We discuss the strengths and limitations of organoids as well as their potential applications in the laboratory and the clinic.

Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments

We describe a novel method to achieve a universal, massive, and fully automated analysis of cell motility behaviours, starting from time-lapse microscopy images. The approach was inspired by the recent successes in application of machine learning for style recognition in paintings and artistic style transfer. The originality of the method relies i) on the generation of atlas from the collection of single-cell trajectories in order to visually encode the multiple descriptors of cell motility, and ii) on the application of pre-trained Deep Learning Convolutional Neural Network architecture in order to extract relevant features to be used for classification tasks from this visual atlas. Validation tests were conducted on two different cell motility scenarios: 1) a 3D biomimetic gels of immune cells, co-cultured with breast cancer cells in organ-on-chip devices, upon treatment with an immunotherapy drug; 2) Petri dishes of clustered prostate cancer cells, upon treatment with a chemotherapy drug. For each scenario, single-cell trajectories are very accurately classified according to the presence or not of the drugs. This original approach demonstrates the existence of universal features in cell motility (a so called “motility style”) which are identified by the DL approach in the rationale of discovering the unknown message in cell trajectories.

Organoid models of gastrointestinal cancers in basic and translational research

Cancer is a major public health problem worldwide. Gastrointestinal cancers account for approximately one-third of the total global cancer incidence and mortality. Historically, the mechanisms of tumour initiation and progression in the gastrointestinal tract have been studied using cancer cell lines in vitro and animal models. Traditional cell culture methods are associated with a strong selection of aberrant genomic variants that no longer reflect the original tumours in terms of their (metastatic) behaviour or response to therapy. Organoid technology has emerged as a powerful alternative method for culturing gastrointestinal tumours and the corresponding normal tissues in a manner that preserves their genetic, phenotypic and behavioural traits. Importantly, accumulating evidence suggests that organoid cultures have great value in predicting the outcome of therapy in individual patients. Herein, we review the current literature on organoid models of the most common gastrointestinal cancers, including colorectal cancer, gastric cancer, oesophageal cancer, liver cancer and pancreatic cancer, and their value in modelling tumour initiation, metastatic progression and therapy response. We also explore the limitations of current organoid models and discuss how they could be improved to maximally benefit basic and translational research in the future, especially in the fields of drug discovery and personalized medicine.

Application of microfluidic technology in cancer research and therapy

Cancer is a heterogeneous disease that requires a multimodal approach to diagnose, manage and treat. A better understanding of the disease biology can lead to identification of novel diagnostic/prognostic biomarkers and the discovery of the novel therapeutics with the goal of improving patient outcomes. Employing advanced technologies can facilitate this, enabling better diagnostic and treatment for cancer patients. In this regard, microfluidic technology has emerged as a promising tool in the studies of cancer, including single cancer cell analysis, modeling angiogenesis and metastasis, drug screening and liquid biopsy. Microfluidic technologies have opened new ways to study tumors in the preclinical and clinical settings. In this chapter, we highlight novel application of this technology in area of fundamental, translational and clinical cancer research.

A statistical inference approach to reconstruct intercellular interactions in cell migration experiments

Migration of cells can be characterized by two prototypical types of motion: individual and collective migration. We propose a statistical inference approach designed to detect the presence of cell-cell interactions that give rise to collective behaviors in cell motility experiments. This inference method has been first successfully tested on synthetic motional data and then applied to two experiments. In the first experiment, cells migrate in a wound-healing model: When applied to this experiment, the inference method predicts the existence of cell-cell interactions, correctly mirroring the strong intercellular contacts that are present in the experiment. In the second experiment, dendritic cells migrate in a chemokine gradient. Our inference analysis does not provide evidence for interactions, indicating that cells migrate by sensing independently the chemokine source. According to this prediction, we speculate that mature dendritic cells disregard intercellular signals that could otherwise delay their arrival to lymph vessels.

Models for Monocytic Cells in the Tumor Microenvironment

Monocytes (Mos) are immune cells that critically regulate cancer, enabling tumor growth and modulating metastasis. Mos can give rise to tumor-associated macrophages (TAMs) and Mo-derived dendritic cells (moDCs), all of which shape the tumor microenvironment (TME). Thus, understanding their roles in the TME is key for improved immunotherapy. Concurrently, various biological and mechanical factors including changes in local cytokines, extracellular matrix production, and metabolic changes in the TME affect the roles of monocytic cells. As such, relevant TME models are critical to achieve meaningful insight on the precise functions, mechanisms, and effects of monocytic cells. Notably, murine models have yielded significant insight into human Mo biology. However, many of these results have yet to be confirmed in humans, reinforcing the need for improved in vitro human TME models for the development of cancer interventions. Thus, this chapter (1) summarizes current insight on the tumor biology of Mos, TAMs, and moDCs, (2) highlights key therapeutic applications relevant to these cells, and (3) discusses various TME models to study their TME-related activity. We conclude with a perspective on the future research trajectory of this topic.

Organoid of ovarian cancer: genomic analysis and drug screening

Ovarian cancer is the most common malignant tumors of the female reproductive system, and its standard treatments are cytoreductive surgery and platinum-based adjuvant chemotherapy. Great advances have been achieved in novel treatment strategies, including targeted therapy and immunotherapy. However, ovarian cancer has the highest mortality rate among gynecological tumors due to therapeutic resistance and the gap between preclinical data and actual clinical efficacy. Organoids are a 3D culture model that markedly affects gene analysis, drug screening, and drug sensitivity determination of tumors, especially when used in targeted therapy and immunotherapy. In addition, organoid can lead to advances in the preclinical research of ovarian cancer due to its convenient cultivation, good genetic stability, and high homology with primary tumors.

Engineered fluidic systems to understand lymphatic cancer metastasis

The majority of all cancers metastasize initially through the lymphatic system. Despite this, the mechanisms of lymphogenous metastasis remain poorly understood and understudied compared to hematogenous metastasis. Over the past few decades, microfluidic devices have been used to model pathophysiological processes and drug interactions in numerous contexts. These devices carry many advantages over traditional 2D in vitro systems, allowing for better replication of in vivo microenvironments. This review highlights prominent fluidic devices used to model the stages of cancer metastasis via the lymphatic system, specifically within lymphangiogenesis, vessel permeability, tumor cell chemotaxis, transendothelial migration, lymphatic circulation, and micrometastases within the lymph nodes. In addition, we present perspectives for the future roles that microfluidics might play within these settings and beyond.

Cancer Modeling-on-a-Chip with Future Artificial Intelligence Integration

Cancer is one of the leading causes of death worldwide, despite the large efforts to improve the understanding of cancer biology and development of treatments. The attempts to improve cancer treatment are limited by the complexity of the local milieu in which cancer cells exist. The tumor microenvironment (TME) consists of a diverse population of tumor cells and stromal cells with immune constituents, microvasculature, extracellular matrix components, and gradients of oxygen, nutrients, and growth factors. The TME is not recapitulated in traditional models used in cancer investigation, limiting the translation of preliminary findings to clinical practice. Advances in 3D cell culture, tissue engineering, and microfluidics have led to the development of "cancer-on-a-chip" platforms that expand the ability to model the TME in vitro and allow for high-throughput analysis. The advances in the development of cancer-on-a-chip platforms, implications for drug development, challenges to leveraging this technology for improved cancer treatment, and future integration with artificial intelligence for improved predictive drug screening models are discussed.

High-throughput analysis of cell-cell crosstalk in ad hoc designed microfluidic chips for oncoimmunology applications

Understanding the interactions between immune and cancer cells occurring within the tumor microenvironment is a prerequisite for successful and personalized anti-cancer therapies. Microfluidic devices, coupled to advanced microscopy systems and automated analytical tools, can represent an innovative approach for high-throughput investigations on immune cell-cancer interactions. In order to study such interactions and to evaluate how therapeutic agents can affect this crosstalk, we employed two ad hoc fabricated microfluidic platforms reproducing advanced 2D or 3D tumor immune microenvironments. In the first type of chip, we confronted the capacity of tumor cells embedded in Matrigel containing one drug or Matrigel containing a combination of two drugs to attract differentially immune cells, by fluorescence microscopy analyses. In the second chip, we investigated the migratory/interaction response of naïve immune cells to danger signals emanated from tumor cells treated with an immunogenic drug, by time-lapse microscopy and automated tracking analysis. We demonstrate that microfluidic platforms and their associated high-throughput computed analyses can represent versatile and smart systems to: (i) monitor and quantify the recruitment and interactions of the immune cells with cancer in a controlled environment, (ii) evaluate the immunogenic effects of anti-cancer therapeutic agents and (iii) evaluate the immunogenic efficacy of combinatorial regimens with respect to single agents.

The influence of spatial and temporal resolutions on the analysis of cell-cell interaction: a systematic study for time-lapse microscopy applications

Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized algorithms and unravel the effects of targeted therapies. We study the influence of spatial and temporal resolutions of time-lapse videos on motility and interaction descriptors with computational models that mimic the interaction dynamics among cells. We show that the experimental set-up of time-lapse microscopy has a direct impact on the cell tracking algorithm and on the derived numerical descriptors. We also show that, when comparing kinematic descriptors in two diverse experimental conditions, too low resolutions may alter the descriptors’ discriminative power, and so the statistical significance of the difference between the two compared distributions. The conclusions derived from the computational models were experimentally confirmed by a series of video-microscopy acquisitions of co-cultures of unlabelled human cancer and immune cells embedded in 3D collagen gels within microfluidic devices. We argue that the experimental protocol of acquisition should be adapted to the specific kind of analysis involved and to the chosen descriptors in order to derive reliable conclusions and avoid biasing the interpretation of results.

Three-Dimensional Organoids in Cancer Research: The Search for the Holy Grail of Preclinical Cancer Modeling

Most solid tumors become therapy resistant and will relapse, with no durable treatment option available. One major impediment to our understanding of cancer biology and finding innovative approaches to cancer treatment stems from the lack of better preclinical tumor models that address and explain tumor heterogeneity and person-to-person differences in therapeutic and toxic responses. Past cancer research has been driven by inadequate in vitro assays utilizing two-dimensional monolayers of cancer cells and animal models. Additionally, animal models do not truly mimic the original human tumor, are time consuming, and usually costly. New preclinical models are needed for innovation in cancer translational research. Hence, it is time to welcome the three-dimensional (3D) organoids: self-organizing cells grown in 3D culture systems mimicking the parent tissues from which the primary cells originate. The 3D organoids offer deeper insights into the crucial cellular processes in tissue and organ formation and pathological processes. Generation of near-perfect physiological microenvironments allow 3D organoids to couple with gene editing tools, such as the clustered regularly interspersed short palindromic repeat (CRISPR)/CRISPR-associated 9 and the transcription activator-like effector nucleases to model human diseases, offering distinct advantages over current models. We explain in this expert review that through recapitulating patients' normal and tumor tissues, organoid technology can markedly advance personalized medicine and help reveal once hidden aspects of cancers. The use of defined tissue- or organ-specific matrices, among other factors, will likely allow organoid technology to realize its potential in innovating many fields of life sciences.

Ex Vivo Tumor-on-a-Chip Platforms to Study Intercellular Interactions within the Tumor Microenvironment

The emergence of immunotherapies and recent FDA approval of several of them makes them a promising therapeutic strategy for cancer. While these advancements underscore the potential of engaging the immune system to target tumors, this approach has so far been efficient only for certain cancers. Extending immunotherapy as a widely acceptable treatment for various cancers requires a deeper understanding of the interactions of tumor cells within the tumor microenvironment (TME). The immune cells are a key component of the TME, which also includes other stromal cells, soluble factors, and extracellular matrix-based cues. While in vivo studies function as a gold standard, tissue-engineered microphysiological tumor models can offer patient-specific insights into cancer-immune interactions. These platforms, which recapitulate cellular and non-cellular components of the TME, enable a systematic understanding of the contribution of each component toward disease progression in isolation and in concert. Microfluidic-based microphysiological platforms recreating these environments, also known as "tumor-on-a-chip," are increasingly being utilized to study the effect of various elements of TME on tumor development. Herein are reviewed advancements in tumor-on-a-chip technology that are developed and used to understand the interaction of tumor cells with other surrounding cells, including immune cells, in the TME.

Exact results for the first-passage properties in a class of fractal networks

In this work, we consider a class of recursively grown fractal networks G_n(t) whose topology is controlled by two integer parameters, t and n. We first analyse the structural properties of G_n(t) (including fractal dimension, modularity, and clustering coefficient), and then we move to its transport properties. The latter are studied in terms of first-passage quantities (including the mean trapping time, the global mean first-passage time, and Kemeny's constant), and we highlight that their asymptotic behavior is controlled by the network's size and diameter. Remarkably, if we tune n (or, analogously, t) while keeping the network size fixed, as n increases (t decreases) the network gets more and more clustered and modular while its diameter is reduced, implying, ultimately, a better transport performance. The connection between this class of networks and models for polymer architectures is also discussed.

Towards the development of human immune-system-on-a-chip platforms

Organ-on-a-chip (OoCs) platforms could revolutionize drug discovery and might ultimately become essential tools for precision therapy. Although many single-organ and interconnected systems have been described, the immune system has been comparatively neglected, despite its pervasive role in the body and the trend towards newer therapeutic products (i.e., complex biologics, nanoparticles, immune checkpoint inhibitors, and engineered T cells) that often cause, or are based on, immune reactions. In this review, we recapitulate some distinctive features of the immune system before reviewing microfluidic devices that mimic lymphoid organs or other organs and/or tissues with an integrated immune system component.

Studying TCR T cell anti-tumor activity in a microfluidic intrahepatic tumor model

Adoptive cell therapy (ACT) is showing promising results in clinical trials but many challenges remain in understanding the key role of the tumor microenvironment. These challenges constitute a major barrier to advancing the field. Therefore, it is crucial to perform preclinical tests of the developed ACT strategies in a fast and reproducible way to assess the potential for patient therapy. Here, we describe the development of an intrahepatic tumor model in a microfluidic device for screening T cell-based immunotherapeutic strategies and the role of monocytes in these therapies. This system can be used to test also the effects of supporting cytokine administration and changes in oxygen level that are typically found in a liver tumor microenvironment. As a result, these 3D microfluidic assays provide a means to quantify T cell anti-tumor activity under different conditions to optimize existing therapeutic strategies or the design of new ones.

Organoids Provide an Important Window on Inflammation in Cancer

Inflammation is a primary driver of cancer initiation and progression. However, the complex and dynamic nature of an inflammatory response make this a very difficult process to study. Organoids are a new model system where complex multicellular structures of primary cells can be grown in a 3D matrix to recapitulate the biology of the parent tissue. This experimental model offers several distinct advantages over alternatives including the ability to be genetically engineered, implanted in vivo and reliably derived from a wide variety of normal and cancerous tissue from patients. Furthermore, long-term organoid cultures reproduce many features of their source tissue, including genetic and epigenetic alterations and drug sensitivity. Perhaps most significantly, cancer organoids can be cocultured in a variety of different systems with a patients’ own immune cells, uniquely permitting the study of autologous cancer-immune cell interactions. Experiments with such systems promise to shed light on the mechanisms governing inflammation-associated cancer while also providing prognostic information on an individual patient’s responsiveness to immunotherapeutic anti-cancer drugs. Thanks to their ability to capture important features of the complex relationship between a cancer and its microenvironment, organoids are poised to become an essential tool for unraveling the mechanisms by which inflammation promotes cancer.

The Current Landscape of 3D In Vitro Tumor Models: What Cancer Hallmarks Are Accessible for Drug Discovery?

Cancer prognosis remains a lottery dependent on cancer type, disease stage at diagnosis, and personal genetics. While investment in research is at an all-time high, new drugs are more likely to fail in clinical trials today than in the 1970s. In this review, a summary of current survival statistics in North America is provided, followed by an overview of the modern drug discovery process, classes of models used throughout different stages, and challenges associated with drug development efficiency are highlighted. Then, an overview of the cancer hallmarks that drive clinical progression is provided, and the range of available clinical therapies within the context of these hallmarks is categorized. Specifically, it is found that historically, the development of therapies is limited to a subset of possible targets. This provides evidence for the opportunities offered by novel disease-relevant in vitro models that enable identification of novel targets that facilitate interactions between the tumor cells and their surrounding microenvironment. Next, an overview of the models currently reported in literature is provided, and the cancer biology they have been used to explore is highlighted. Finally, four priority areas are suggested for the field to accelerate adoption of in vitro tumour models for cancer drug discovery.

Personalized Cancer Medicine: An Organoid Approach

Personalized cancer therapy applies specific treatments to each patient. Using personalized tumor models with similar characteristics to the original tumors may result in more accurate predictions of drug responses in patients. Tumor organoid models have several advantages over pre-existing models, including conserving the molecular and cellular composition of the original tumor. These advantages highlight the tremendous potential of tumor organoids in personalized cancer therapy, particularly preclinical drug screening and predicting patient responses to selected treatment regimens. Here, we highlight the advantages, challenges, and translational potential of tumor organoids in personalized cancer therapy and focus on gene-drug associations, drug response prediction, and treatment selection. Finally, we discuss how microfluidic technology can contribute to immunotherapy drug screening in tumor organoids.

Recent advances in microfluidic technologies for cell-to-cell interaction studies

Microfluidic cell cultures are ideally positioned to become the next generation of in vitro diagnostic tools for biomedical research, where key biological processes such as cell signalling and dynamic cell-to-cell interactions can be reliably analysed under reproducible physiological cell culture conditions. In the last decade, a large number of microfluidic cell analysis systems have been developed for a variety of applications including drug target optimization, drug screening and toxicological testing. More recently, advanced in vitro microfluidic cell culture systems have emerged that are capable of replicating the complex three-dimensional architectures of tissues and organs and thus represent valid biological models for investigating the mechanism and function of human tissue structures, as well as studying the onset and progression of diseases such as cancer. In this review, we present the most important developments in single-cell, 2D and 3D microfluidic cell culture systems for studying cell-to-cell interactions published over the last 6 years, with a focus on cancer research and immunotherapy, vascular models and neuroscience. In addition, the current technological development of microdevices with more advanced physiological cell microenvironments that integrate multiple organ models, namely, the so-called body-, human- and multi-organ-on-a-chip, is reviewed.

Organs on chip approach: a tool to evaluate cancer -immune cells interactions

In this paper we discuss the applicability of numerical descriptors and statistical physics concepts to characterize complex biological systems observed at microscopic level through organ on chip approach. To this end, we employ data collected on a microfluidic platform in which leukocytes can move through suitably built channels toward their target. Leukocyte behavior is recorded by standard time lapse imaging. In particular, we analyze three groups of human peripheral blood mononuclear cells (PBMC): heterozygous mutants (in which only one copy of the FPR1 gene is normal), homozygous mutants (in which both alleles encoding FPR1 are loss-of-function variants) and cells from 'wild type' donors (with normal expression of FPR1). We characterize the migration of these cells providing a quantitative confirmation of the essential role of FPR1 in cancer chemotherapy response. Indeed wild type PBMC perform biased random walks toward chemotherapy-treated cancer cells establishing persistent interactions with them. Conversely, heterozygous mutants present a weaker bias in their motion and homozygous mutants perform rather uncorrelated random walks, both failing to engage with their targets. We next focus on wild type cells and study the interactions of leukocytes with cancerous cells developing a novel heuristic procedure, inspired by Lyapunov stability in dynamical systems.