Complex 3D Systems Research Articles

Bioprinting of Cells, Organoids and Organs-on-a-Chip Together with Hydrogels Improves Structural and Mechanical Cues.

The 3D bioprinting technique has made enormous progress in tissue engineering, regenerative medicine and research into diseases such as cancer. Apart from individual cells, a collection of cells, such as organoids, can be printed in combination with various hydrogels. It can be hypothesized that 3D bioprinting will even become a promising tool for mechanobiological analyses of cells, organoids and their matrix environments in highly defined and precisely structured 3D environments, in which the mechanical properties of the cell environment can be individually adjusted. Mechanical obstacles or bead markers can be integrated into bioprinted samples to analyze mechanical deformations and forces within these bioprinted constructs, such as 3D organoids, and to perform biophysical analysis in complex 3D systems, which are still not standard techniques. The review highlights the advances of 3D and 4D printing technologies in integrating mechanobiological cues so that the next step will be a detailed analysis of key future biophysical research directions in organoid generation for the development of disease model systems, tissue regeneration and drug testing from a biophysical perspective. Finally, the review highlights the combination of bioprinted hydrogels, such as pure natural or synthetic hydrogels and mixtures, with organoids, organoid-cell co-cultures, organ-on-a-chip systems and organoid-organ-on-a chip combinations and introduces the use of assembloids to determine the mutual interactions of different cell types and cell-matrix interferences in specific biological and mechanical environments.

A Hybrid 2D-to-3D in vitro Differentiation Platform Improves Outcomes of Cerebral Cortical Organoid Generation in hiPSCs.

Three-dimensional (3D) cerebral cortical organoids are popular in vitro cellular model systems widely used to study human brain development and disease, compared to traditional stem cell-derived methods that use two-dimensional (2D) monolayer cultures. Despite the advancements made in protocol development for cerebral cortical organoid derivation over the past decade, limitations due to biological, mechanistic, and technical variables remain in generating these complex 3D cellular systems. Building from our previously established differentiation system, we have made modifications to our existing 3D cerebral cortical organoid protocol that resolve several of these technical and biological challenges when working with diverse groups of human induced pluripotent stem cell (hiPSC) lines. This improved protocol blends a 2D monolayer culture format for the specification of neural stem cells and expansion of neuroepithelial progenitor cells with a 3D system for improved self-aggregation and subsequent organoid development. Furthermore, this "hybrid" approach is amenable to both an accelerated cerebral cortical organoid protocol as well as an alternative long-term differentiation protocol. In addition to establishing a hybrid technical format, this protocol also offers phenotypic and morphological characterization of stage-specific cellular profiles using antibodies and fluorescent-based dyes for live cell imaging. © 2024 Wiley Periodicals LLC. Basic Protocol 1: hiPSC-based 2D monolayer specification into neural stem cells (NSCs) Basic Protocol 2: Serial passaging and 2D monolayer expansion of neuroepithelial progenitor cells (NPCs) Support Protocol 1: Direct cryopreservation and rapid thawing of NSCs and NPCs Basic Protocol 3: Bulk aggregation of 3D neurospheres and accelerated cerebral cortical organoid differentiation Alternate Protocol 1: Bulk aggregation of 3D neurospheres and long-term cerebral cortical organoid differentiation Support Protocol 2: High-throughput 3D neurosphere formation and 2D neurosphere migration assay Support Protocol 3: LIVE/DEAD stain cell imaging assay of 3D neurospheres Support Protocol 4: NeuroFluor NeuO live cell dye for 3D cerebral cortical organoids.

Tunable Conductive Composite for Printed Sensors and Embedded Circuits

Multimaterial 3D printing is an attractive route for low‐cost fabrication of electronic systems having different types of embedded devices. Herein, tunable thermoplastic polyurethane (TPU)‐based conductive composite filaments are presented for development of either strain sensors or different circuit elements. The filaments are developed with two filler materials, namely, silver and multiwalled carbon nanotubes (MWCNT). The influences of filler aspect ratio (AR), concentration, functionalization, and morphology on the composites' mechanical, thermal, and electrical properties are studied. Printed tracks of the 10 wt% high‐AR MWCNT/TPU filament exhibit a maximum electrical conductivity of 0.92 S cm−1 and withstand powers >1 W and currents >100 mA. The filament shows negligible change in impedance over the frequency range 1 kHz–1 MHz and a change in the resistance of <5% with 90° bending. Conversely, printed tracks using filaments with 3 wt% low‐AR MWCNT exhibit a change in resistance of ≈30% with 90° bending, allowing a clear distinction between various bending angles, and thus could be used for embedded strain/bend sensors. These results suggest that, with the correct optimization, multimaterial additive manufacturing can be utilized with tunable conductive filaments to fabricate complex 3D electronic systems by constructing reliable circuit tracks, bendable interconnects, and sensors.

Hierarchical active learning for defect localization in 3D systems

Aim: Advanced sensing and imaging is capable to retrieve rich information of complex systems, which can be integrated with underlying physics to develop a personalized simulation framework to discern system internal property for defect localization. Simulation-based defect localization involves modeling the heterogeneous 3D physical systems and calibrating spatial-varying model parameters. In this paper, we aim to develop an effective simulation-based active learning framework for defect localization in complex 3D systems. Methods: We develop a Hierarchical Gaussian Process (GP)-based Active Learning (HGPAL) framework to estimate the spatial-varying model parameters for reliable defect localization in complex 3D systems. We first develop a GP regression model on the 2D embedding of a 3D geometry to capture the geometric information. Second, we propose a Hierarchical GP-based active learning approach composed of master GP and sub-GP modeling to account for the system heterogeneity and further estimate the spatial-varying model parameter for defect localization. Results: We evaluate the performance of the proposed HGPAL framework in a 3D body-heart system to identify and localize infarct in the heart. Numerical experiments demonstrate the effectiveness of our HGPAL framework for 3D defect localization. Conclusion: This study successfully developed and tested an HGPAL framework for defect localization in complex 3D systems. The results suggest that this approach can efficiently and accurately localize defects in 3D systems, demonstrating its potential for practical applications in precision engineering system design and healthcare treatment planning.

Impact of surface reflectivity on the ultra-fast laser melting of silicon-germanium alloys

Ultraviolet nanosecond laser annealing (LA) is a powerful tool where strongly confined heating and melting are desirable. In semiconductor technologies the importance of LA increases with the increasing complexity of the proposed integration schemes. Optimizing the LA process along with the experimental design is challenging, especially when complex 3D nanostructured systems with various shapes and phases are involved. Within this context, reliable simulations of laser melting are required for optimizing the process parameters while reducing the number of experimental tests. This gives rise to a virtual Design of Experiments (DoE). Si1−xGex alloys are nowadays used for their compatibility with silicon devices enabling to engineer properties such as strain, carrier mobilities and bandgap. In this work, the laser melting process of relaxed and strained Si1−xGex is simulated with a finite element method/phase field approach. Particularly, we calibrated the dielectric functions of the alloy for its crystalline and liquid phase using experimental data. We highlighted the importance of reproducing the exact reflectivity of the interface between air and the material in its different aggregation states, to correctly mimic the process. We indirectly discovered intriguing features on the optical behaviour of melt silicon-germanium.

3D Evolution of Detachment Fault Systems in Necking Domains: Insights From the Klakk Fault Complex and the Frøya High, Mid‐Norwegian Rifted Margin

AbstractDetachment fault systems typically record displacements in the order of 10s of kilometers. The principles that control the growth of smaller magnitude normal faults are not fully applicable to the evolution of detachment fault systems. We use interpretation of 2D and 3D seismic reflection data from the mid‐Norwegian rifted margin to investigate how the structural evolution of a detachment fault interacted with the effects of isostatic footwall rollback to produce complex 3D geometries and control the configuration of associated supradetachment basins. We further investigate the effects of lateral interaction and linkage of extensional detachment faults on the necking domain configuration. In our study area, the domain‐bounding Klakk Fault Complex demonstrates how successive incision may induce a complex structural relief in response to faulting and fault plane folding. We interpret the previously proposed metamorphic core complex within its footwall as an extension‐parallel turtleback‐structure. The now eroded turtleback is flanked by a major supradetachment basin, connecting two main basin segments. We attribute footwall‐ and turtleback exhumation to Middle Jurassic‐Early Cretaceous rifting. The study area further demonstrates how detachment fault geometries can change during rifting and lead to the formation of younger, successively incising fault splays. Lateral linkage between the original detachment fault plane and these fault splays enables displacement along a detachment fault system consisting of fault segments generated at different stages in time. Implicitly, detachment faults are complex 3D systems that change configuration during their evolution, perpetually controlling associated basin formation, footwall configuration, subsidence and uplift patterns.

Footprints: Stamping hallmarks of lung cancer with patient-derived models, from molecular mechanisms to clinical translation.

The conventional two-dimensional (2D) tumor cell lines in Petri dishes have played an important role in revealing the molecular biological mechanism of lung cancer. However, they cannot adequately recapitulate the complex biological systems and clinical outcomes of lung cancer. The three-dimensional (3D) cell culture enables the possible 3D cell interactions and the complex 3D systems with co-culture of different cells mimicking the tumor microenvironments (TME). In this regard, patient-derived models, mainly patient-derived tumor xenograft (PDX) and patient-derived organoids discussed hereby, are with higher biological fidelity of lung cancer, and regarded as more faithful preclinical models. The significant Hallmarks of Cancer is believed to be the most comprehensive coverage of current research on tumor biological characteristics. Therefore, this review aims to present and discuss the application of different patient-derived lung cancer models from molecular mechanisms to clinical translation with regards to the dimensions of different hallmarks, and to look to the prospects of these patient-derived lung cancer models.

Selecting the right therapeutic target for kidney disease

Kidney disease is a complex disease with several different etiologies and underlying associated pathophysiology. This is reflected by the lack of effective treatment therapies in chronic kidney disease (CKD) that stop disease progression. However, novel strategies, recent scientific breakthroughs, and technological advances have revealed new possibilities for finding novel disease drivers in CKD. This review describes some of the latest advances in the field and brings them together in a more holistic framework as applied to identification and validation of disease drivers in CKD. It uses high-resolution 'patient-centric' omics data sets, advanced in silico tools (systems biology, connectivity mapping, and machine learning) and 'state-of-the-art' experimental systems (complex 3D systems in vitro, CRISPR gene editing, and various model biological systems in vivo). Application of such a framework is expected to increase the likelihood of successful identification of novel drug candidates based on strong human target validation and a better scientific understanding of underlying mechanisms.

Shape programming via discretizing the surface into cross-structured pixel units

Shape-morphing systems have a wide range of application scenarios. Its potential for controlling transformation into arbitrary three-dimensional (3D) shapes needs to be realized. This study aimed to develop a novel programming control strategy. A flat sheet obtained by discretizing the curved surface with cross-structure units without in-plane strain interference can be deformed into an arbitrary 3D space surface model. The division of the deformable and central fixed parts of the cross-structure prevents deformation interference. Fused filament fabrication pre-programmed four-dimensional printing technology was used to control the deformable part transformation. The self-developed software performed the flattening, discretization, and optimization of the target surface to generate a printed plane model composed of a cross-structure. A self-developed slicing tool completed the printing process. The finite element simulation results of the sample model were consistent with those of the target surface. The experimental results of the model deformation confirmed the effectiveness and accuracy of the approach. The novel programming control strategy for printing arbitrarily complex 3D deformation systems exhibited high theoretical precision. Its universality promotes development of the shape-morphing system manufacturing field.

Antimicrobial volatiles emitted by members of the nest microbiome of social spiders.

Microbes produce and respond to a range of structurally and functionally diverse volatiles. Many microbial volatiles have antimicrobial properties. Since volatiles can diffuse through complex 3D systems like spider nests, they are promising pathogen protection for social arthropods. Here, we analyzed the volatilomes of five nest microbiome members of the Namibian, social spider Stegodyphus dumicola, namely the bacteria Massilia sp. IC2-278, Massilia sp. IC2-477, Sphingomonas sp. IC-11, Streptomyces sp. IC-207, and the fungus Aureobasidium sp. CE_32, and tested their antimicrobial activity against two putative spider pathogens, namely Bacillus thuringiensis and Purpureocillium lilacinum. Most nest microbiome members released volatilomes with antibacterial and/or antifungal activities under in vitro conditions. The analysis of their volatilomes using GC/Q-TOF revealed that they include numerous antimicrobial volatiles. We tested the antimicrobial activity of five pure volatile compounds found in the volatilomes and revealed that all of them were antibacterial and/or antifungal. We could not identify the same antimicrobial volatiles as in a previous in situ study, but our results indicate that social spider-associated microorganisms as a source of antimicrobial volatiles are important for pathogen inhibition. Additionally, we showed the influence of the volatilomes on the antibiotic sensitivity of B. thuringiensis offering novel approaches to counter antibiotic resistance.

Identification of A2BAR as a potential target in colorectal cancer using novel fluorescent GPCR ligands

G-protein coupled receptors (GPCRs) have been largely targeted in a wide range of diseases, but few therapies have been directed against GPCRs in the field of cancer, partly because of the lack of effective target identification strategies. Here, using colorectal cancer (CRC) as a model, we explored the gene expression of a panel of GPCRs in tumor and stromal cells, identifying specific gene sets defining each cellular compartment. We selected the adenosine receptor 2B (A2BAR), specifically expressed in cancer cell lines compared with stromal cells, to explore the use of fluorescent ligands that can be used for target visualization. Fluorescent probes allowed semi-quantitative receptor mapping in living cells and validated the specific expression of A2BAR in CRC cell lines. As well, fluorescent ligands were effective at monitoring real-time A2BAR receptor labeling using live-imaging modalities, and displayed high efficiency when used to label complex 3D cellular systems such as tumor spheroids. Finally, we validated A2BAR as a potential pharmacological tool in CRC, using selective antagonists, finding a reduction in tumor cell proliferation. This proof-of-concept study suggests the use of fluorescent ligands for GPCR characterization through imaging, and as possible new tools used for target validation in drug screening methodologies.

Abstract 3836: Mapping the interactome of the endogenous metalloproteinase inhibitor TIMP2 using extracellular proximity labeling (ePL)

Abstract Tissue inhibitors of metalloproteinases (TIMPs) are a family of endogenous proteins that were initially defined by their ability to inhibit the enzymatic activity of matrix metalloproteinases (MMPs), the major mediators of ECM breakdown and turnover. TIMPs are important regulators of ECM structure, function and homeostasis. Since their original discovery, additional MMP-independent functions have been attributed to TIMP family members leading to their designation as multifunctional proteins with discrete functional domains. TIMP2 is a unique family member, with a broad expression profile that is expressed in both normal and diseased tissues, even in those with minimal metalloproteinase activity. Understanding the functional transformation of matrisome regulators, like TIMP-2, during the dynamic evolution of tissue microenvironments associated with disease progression is essential to the development of ECM targeted therapeutics. This knowledge may also garner understanding of therapeutic resistance and the failure of conventional and next-generation cancer therapies. Interactome studies are predominantly performed in non-living systems, and very rarely performed in complex culture systems such as 3D spheroids/co-cultures. To investigate the TIMP-2 interactome in complex biological systems we recently developed carboxyl- and amino-terminal fusion genes of TIMP-2 with the promiscuous biotinylating peptides BioID2 and TurboID. Packaged for retroviral delivery, this system gives us great flexibility in assessing the TIMP-2 interactome in simple versus complex 3D co-culture systems. We show, for the first time, that conditions can be optimized to support proximity labeling reactions in the extracellular milieu, representing an important technical resource for extracellular matrix biologists. Using this method, we identify novel interacting partners for TIMP-2 that provide insight into the tissue-specific actions of this protein in both healthy and diseased tissues. Citation Format: David Peeney, Sadeechya Gurung, Yueqin Liu, Carolyn Lazaroff, Christopher Richie, William G. Stetler-Stevenson. Mapping the interactome of the endogenous metalloproteinase inhibitor TIMP2 using extracellular proximity labeling (ePL) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3836.

Triggering the nanophase separation of albumin through multivalent binding to glycogen for drug delivery in 2D and 3D multicellular constructs.

Engineered nanoparticles for the encapsulation of bioactive agents hold promise to improve disease diagnosis, prevention and therapy. To advance this field and enable clinical translation, the rational design of nanoparticles with controlled functionalities and a robust understanding of nanoparticle-cell interactions in the complex biological milieu are of paramount importance. Herein, a simple platform obtained through the nanocomplexation of glycogen nanoparticles and albumin is introduced for the delivery of chemotherapeutics in complex multicellular 2D and 3D systems. We found that the dendrimer-like structure of aminated glycogen nanoparticles is key to controlling the multivalent coordination and phase separation of albumin molecules to form stable glycogen-albumin nanocomplexes. The pH-responsive glycogen scaffold conferred the nanocomplexes the ability to undergo partial endosomal escape in tumour, stromal and immune cells while albumin enabled nanocomplexes to cross endothelial cells and carry therapeutic agents. Limited interactions of nanocomplexes with T cells, B cells and natural killer cells derived from human blood were observed. The nanocomplexes can accommodate chemotherapeutic drugs and release them in multicellular 2D and 3D constructs. The drugs loaded on the nanocomplexes retained their cytotoxic activity, which is comparable with the activity of the free drugs. Cancer cells were found to be more sensitive to the drugs in the presence of stromal and immune cells. Penetration and cytotoxicity of the drug-loaded nanocomplexes in tumour mimicking tissues were validated using a 3D multicellular-collagen construct in a perfusion bioreactor. The results highlight a simple and potentially scalable strategy for engineering nanocomplexes made entirely of biological macromolecules with potential use for drug delivery.

Application of LDH assay for therapeutic efficacy evaluation of ex vivo tumor models

The current standard preclinical oncology models are not able to fully recapitulate therapeutic targets and clinically relevant disease biology, evidenced by the 90% attrition rate of new therapies in clinical trials. Three-dimensional (3D) culture systems have the potential to enhance the relevance of preclinical models. However, the limitations of currently available cellular assays to accurately evaluate therapeutic efficacy in these models are hindering their widespread adoption. We assessed the compatibility of the lactate dehydrogenase (LDH) assay in 3D spheroid cultures against other commercially available readout methods. We developed a standardized protocol to apply the LDH assay to ex vivo cultures, considering the impact of culture growth dynamics. We show that accounting for growth rates and background release levels of LDH are sufficient to make the LDH assay a suitable methodology for longitudinal monitoring and endpoint assessment of therapeutic efficacy in both cell line-derived xenografts (xenospheres) and patient-derived explant cultures. This method has the added value of being non-destructive and not dependent on reagent penetration or manipulation of the parent material. The establishment of reliable readout methods for complex 3D culture systems will further the utility of these tumor models in preclinical and co-clinical drug development studies.

How Mechanical Forces Change the Human Endometrium during the Menstrual Cycle in Preparation for Embryo Implantation.

The human endometrium is characterized by exceptional plasticity, as evidenced by rapid growth and differentiation during the menstrual cycle and fast tissue remodeling during early pregnancy. Past work has rarely addressed the role of cellular mechanics in these processes. It is becoming increasingly clear that sensing and responding to mechanical forces are as significant for cell behavior as biochemical signaling. Here, we provide an overview of experimental evidence and concepts that illustrate how mechanical forces influence endometrial cell behavior during the hormone-driven menstrual cycle and prepare the endometrium for embryo implantation. Given the fundamental species differences during implantation, we restrict the review to the human situation. Novel technologies and devices such as 3D multifrequency magnetic resonance elastography, atomic force microscopy, organ-on-a-chip microfluidic systems, stem-cell-derived organoid formation, and complex 3D co-culture systems have propelled the understanding how endometrial receptivity and blastocyst implantation are regulated in the human uterus. Accumulating evidence has shown that junctional adhesion, cytoskeletal rearrangement, and extracellular matrix stiffness affect the local force balance that regulates endometrial differentiation and blastocyst invasion. A focus of this review is on the hormonal regulation of endometrial epithelial cell mechanics. We discuss potential implications for embryo implantation.

Unveiling the third dimension in morphometry with automated quantitative volumetric computations

As computed tomography and related technologies have become mainstream tools across a broad range of scientific applications, each new generation of instrumentation produces larger volumes of more-complex 3D data. Lagging behind are step-wise improvements in computational methods to rapidly analyze these new large, complex datasets. Here we describe novel computational methods to capture and quantify volumetric information, and to efficiently characterize and compare shape volumes. It is based on innovative theoretical and computational reformulation of volumetric computing. It consists of two theoretical constructs and their numerical implementation: the spherical wave decomposition (SWD), that provides fast, accurate automated characterization of shapes embedded within complex 3D datasets; and symplectomorphic registration with phase space regularization by entropy spectrum pathways (SYMREG), that is a non-linear volumetric registration method that allows homologous structures to be correctly warped to each other or a common template for comparison. Together, these constitute the Shape Analysis for Phenomics from Imaging Data (SAPID) method. We demonstrate its ability to automatically provide rapid quantitative segmentation and characterization of single unique datasets, and both inter-and intra-specific comparative analyses. We go beyond pairwise comparisons and analyze collections of samples from 3D data repositories, highlighting the magnified potential our method has when applied to data collections. We discuss the potential of SAPID in the broader context of generating normative morphologies required for meaningfully quantifying and comparing variations in complex 3D anatomical structures and systems.

Three-Dimensional Cell Cultures as a Research Platform in Lung Diseases and COVID-19.

Background:Chronic respiratory diseases (CRD) are a major public health problem worldwide. In the current epidemiological context, CRD have received much interest when considering their correlation with greater susceptibility to SARS-Cov-2 and severe disease (COVID-19). Increasingly more studies have investigated pathophysiological interactions between CRD and COVID-19. Area covered:Animal experimentation has decisively contributed to advancing our knowledge of CRD. Considering the increase in ethical restrictions in animal experimentation, researchers must focus on new experimental alternatives. Two-dimensional (2D) cell cultures have complemented animal models and significantly contributed to advancing research in the life sciences. However, 2D cell cultures have several limitations in studies of cellular interactions. Three-dimensional (3D) cell cultures represent a new and robust platform for studying complex biological processes and are a promising alternative in regenerative and translational medicine. Expert opinion:Three-dimensional cell cultures are obtained by combining several types of cells in integrated and self-organized systems in a 3D structure. These 3D cell culture systems represent an efficient methodological approach in studies of pathophysiology and lung therapy. More recently, complex 3D culture systems, such as lung-on-a-chip, seek to mimic the physiology of a lung in vivo through a microsystem that simulates alveolar-capillary interactions and exposure to air. The present review introduces and discusses 3D lung cultures as robust platforms for studies of the pathophysiology of CRD and COVID-19 and the mechanisms that underlie interactions between CRD and COVID-19.

Abstract PO004: Reverse-engineering the tumor microenvironment through microfluidics and bioengineered in vitro models

Abstract Scope: Solid tumors are complex 3D systems where environmental gradients and cellular interactions shape tumor evolution and patient outcome. In this work, we developed bioengineered microfluidic in vitro models to study how environmental factors affect immune exhaustion. Methods: In this work, we fabricated a microfluidic model that mimicked the tumor architecture to study tumor-immune interactions. Breast cancer cells were cultured as a dense mass and embedded in a 3D collagen hydrogel inside the microfluidic device. The model also included two lateral lumens on the flanks, allowing us to seed endothelial cells and mimicking the cylindrical structure of blood vessels. These biomimetic blood vessels were used to perfuse culture media, antibodies (e.g., anti-PD-1, immunocytokines), or immune cells (e.g., natural killer cells, CD4 T cells). We used a combination of fluorescence and multi-photon microscopy to monitor antibody and immune cell extravasation, migration, and tumor clearance in real-time. We retrieved the cells from the model (i.e., endothelial, tumor, CD4, and natural killer cells) to analyze them by RT-qPCR and functional assays (e.g., proliferation rate, migration speed, natural killer cell killing potential). Results: The results demonstrated that tumor metabolism rapidly led to nutrient starvation and acidic pH in the inner regions of the model. Consequently, tumor cells showed different metabolism and proliferation rates near the biomimetic vessels compared with the core of the model. We used metabolic inhibitors targeting multiple metabolic pathways (e.g., glycolysis) to selectively destroy tumor cells depending on their location in the model. Real-time microscopy revealed that natural killer cells were able to detect the presence of tumor cells from several hundreds of microns away, exhibiting directional migration towards the tumor cells. Molecular analysis revealed that as natural killer cells reached inner regions, they exhibited progressive signs of immune exhaustion (e.g., upregulation of PD-1, downregulation of granzymes). Interestingly, when retrieved from the model and cultured alone in traditional flasks, natural killer cells remained exhausted for an extended time, highlighting the long-lasting effects of the tumor microenvironment. The use of antibodies (e.g., anti-PD-1), immunocytokines (e.g., IL-2-coupled antibody), or metabolic inhibitors (e.g., IDO-1 inhibitors) partially prevented natural killer cell exhaustion at the core, improving their killing potential. Conclusions: tumor-immune interactions in the tumor microenvironment are extremely complex. Bioengineered microfluidic models offered a versatile tool to monitor the natural killer cell exhaustion, allowing us to identify multiple molecular factors driving the process. We used this knowledge to test several drugs and antibodies to prevent natural killer cell exhaustion and improve tumor killing. Citation Format: Jose M. Ayuso, Mehtab Farooqui, Maria Virumbrales-Munoz, Shujah Rehman, Melissa C. Skala, David J. Beebe. Reverse-engineering the tumor microenvironment through microfluidics and bioengineered in vitro models [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO004.

Modeling the Early Steps of Ovarian Cancer Dissemination in an Organotypic Culture of the Human Peritoneal Cavity.

The majority of ovarian cancer patients present clinically with wide-spread metastases throughout the peritoneal cavity, metastasizing to the mesothelium-lined peritoneum and visceral adipose depots within the abdomen. This unique metastatic tumor microenvironment is comprised of multiple cell types, including mesothelial cells, fibroblasts, adipocytes, macrophages, neutrophils, and T lymphocytes. Modeling advancements, including complex 3D systems and organoids, coupled with 2D cocultures, in vivo mouse models, and ex vivo human tissue cultures have greatly enhanced our understanding of the tumor-stroma interactions that are required for successful metastasis of ovarian cancer cells. However, advanced multifaceted model systems that incorporate frequency and spatial distribution of all cell types present in the tumor microenvironment of ovarian cancer are needed to enhance our knowledge of ovarian cancer biology in order to identify methods for preventing and treating metastatic disease. This review highlights the utility of recently developed modeling approaches, summarizes some of the resulting progress using these techniques, and suggests how these strategies may be implemented to elucidate signaling processes among cell types of the tumor microenvironment that promote ovarian cancer metastasis.

Functional optimization of fluidic devices with differentiable stokes flow

We present a method for performance-driven optimization of fluidic devices. In our approach, engineers provide a high-level specification of a device using parametric surfaces for the fluid-solid boundaries. They also specify desired flow properties for inlets and outlets of the device. Our computational approach optimizes the boundary of the fluidic device such that its steady-state flow matches desired flow at outlets. In order to deal with computational challenges of this task, we propose an efficient, differentiable Stokes flow solver. Our solver provides explicit access to gradients of performance metrics with respect to the parametric boundary representation. This key feature allows us to couple the solver with efficient gradient-based optimization methods. We demonstrate the efficacy of this approach on designs of five complex 3D fluidic systems. Our approach makes an important step towards practical computational design tools for high-performance fluidic devices.