APL Bioengineering

Breast cancer remains the leading cause of cancer-related mortality among women worldwide. Tumor biomechanics are not merely a symptom: they represent a functional signature with translational relevance in diagnostic, prognostic, and therapeutic resistance. Despite this, few experimental models are engineered to systematically investigate these physical properties across biological systems. Here, this study presents a multimodal biomechanical platform combining engineered 3D breast cancer spheroids with ex vivo tissue analysis to profiling and compare viscoelastic behavior or of healthy and tumoral environments. Rheometry and compression testing revealed a consistent mechanical shift in tumor-derived samples marked by increased stiffness and force-dependent nonlinear behavior, mirroring the ECM remodeling typical of aggressive phenotypes. This increased rigidity may adversely affect chemotherapy effectiveness by hindering drug delivery and altering cellular mechanotransduction. These biomechanical fingerprints enable quantitative discrimination between healthy and cancerous tissues and can serve as a surrogate maker of malignancy. By supporting the development of mechanics-informed diagnostic tools, our platform offers a reproducible, clinically relevant framework to integrate biomechanical screening into translational breast cancer pipelines. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/680332v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@2c87a3org.highwire.dtl.DTLVardef@17cecc8org.highwire.dtl.DTLVardef@9d56d3org.highwire.dtl.DTLVardef@1af509a_HPS_FORMAT_FIGEXP M_FIG C_FIG Translational Impact StatementWe propose a multimodal experimental approach that combines in vitro 3D breast-cancer models and ex vivo tissue analysis to measure and compare the viscoelastic properties of healthy and malignant breast tissues. By using mechanical behaviour as a fingerprint, this framework discriminates tumour tissue from its healthy counterpart. Revealing how tumour stiffness impacts drug delivery and therapy resistance, the approach provides a clinically relevant tool to inform diagnosis and optimise treatment strategies.

Cell mechanics can serve as an important biomarker for cell state and phenotype, such as metastatic ability. While some molecular mechanisms underlying cell mechanical properties have been investigated through targeted analyses, a genome-wide study of human genes and gene networks that modulate cell biophysical properties has not been attempted. In this work, we combined a microfluidic stiffness-based sorting device with a genome-scale CRISPR knockout (GeCKO) screen in order to investigate the effect of individual gene knockouts on cell stiffening and cell softening across the entire protein-coding genome. We processed approximately 150 million Cas9-expressing ovarian cancer cells that had been transduced with a library of 76,000 single guide RNAs (sgRNAs) against the 19,000 protein-coding genes in the genome. The cells were sorted into 5 mechanical subsets. We identified 7 gene knockouts that were significantly depleted in the softer subsets and over 700 gene knockouts that were significantly enriched in the stiffer subsets. Of these significant genes of interest, we selected 3 genes that were highly expressed in our ovarian cancer cell line with greater than 100-fold enrichment in the stiff outlet and resulted in significant changes in ovarian cancer patient survival. These genes, PIK3R4, CCDC88A, and GSK3B, when knocked out result in a significant and predicted increase in cell stiffness. This study is the first to explore the relation between human gene expression and cell mechanics at the genome-scale to generate datasets at the intersection between cell genotype, mechanotype, and phenotype for metastatic cancer cells. The method could also be applied to study the effect of genes on other biophysical cell processes as well as for identifying pathways for the control of cellular mechanics across many cell types.

In pancreatic ductal adenocarcinoma (PDAC), tumour associated macrophages (TAMs) are a heterogeneous immune cell population that interact with cancer cells to promote malignancy, chemo-resistance, and immunosuppression. Aside from TAMs, hypoxia is a prominent feature of PDAC that can rewire cells to survive and enhance malignancy in the tumour microenvironment (TME). Deciphering the interactions between macrophages, cancer cells and hypoxia could lead to the development of effective immune-targeted therapies for PDAC. However, there are only a few models that physiologically recapitulate the PDAC TME and allow for meaningful interrogation of cancer-immune cell interactions in hypoxia. Here, we develop a model of primary macrophages and PDAC patient organoid-derived cells by adapting TRACER, a paper-based, engineered 3D model that allows snapshot analysis of cellular response in hypoxia. In this study, we establish a direct co-culture method of primary macrophages and PDAC organoid cells in TRACER and demonstrate that TRACER co-cultures generate hypoxic gradients and show expected phenotypic responses to this hypoxic gradient. Moreover, we report for the first time in a human in vitro model that hypoxic macrophages exert a graded chemoprotective effect on gemcitabine-treated PDAC organoid cells, and that interactions between cancer cells and macrophages from the inner layers of TRACER indirectly attenuate the inflammatory response of donor-derived T-cells. Overall, the TRACER co-culture system is a novel, fully human 3D in vitro cancer-immune model for evaluating the response of macrophages and cancer cells in a hypoxic gradient.

The lymph node (LN) performs essential roles in immunosurveillance throughout the body. Developing in vitro models of this key tissue is of great importance to enhancing physiological relevance in immunoengineering. The LN consists of stromal populations and immune cells, which are highly organized and bathed in constant interstitial flow. The stroma, notably the fibroblastic reticular cells (FRCs) and the lymphatic endothelial cells (LECs), play crucial roles in guiding T cell migration and are known to be sensitive to fluid flow. During inflammation, interstitial fluid flow rates drastically increase in the LN. It is unknown how these altered flow rates impact crosstalk and cell behavior in the LN, and most existing in vitro models focus on the interactions between T cells, B cells, and dendritic cells rather than with the stroma. To address this gap, we developed a human engineered model of the LN stroma consisting of FRC-laden hydrogel above a monolayer of LECs in a tissue culture insert with gravity-driven interstitial flow. We found that FRCs had enhanced coverage and proliferation in response to high flow rates, while LECs experienced decreased barrier integrity. We added CD4+ and CD8+ T cells and found that their egress was significantly decreased in the presence of interstitial flow, regardless of magnitude. Interestingly, 3.0 {micro}m/s flow, but not 0.8 {micro}m/s flow, correlated with enhanced inflammatory cytokine secretion in the LN stroma. Overall, we demonstrate that interstitial flow is an essential consideration in the lymph node for modulating LN stroma morphology, T cell migration, and inflammation.

Understanding cancer cell mechanics allows for the identification of novel disease mechanisms, diagnostic biomarkers, and targeted therapies. In this study, we utilized our previously established fluid shear stress assay to investigate and compare the viscoelastic properties of normal immortalized human astrocytes (IHAs) and invasive human glioblastoma (GBM) cells when subjected to physiological levels of shear stress that are present in the brain microenvironment. We used a parallel-flow microfluidic shear system and a camera-coupled optical microscope to expose single cells to fluid shear stress and monitor the resulting deformation in real-time, respectively. From the video-rate imaging, we fed cell deformation information from digital image correlation into a three-parameter generalized Maxwell model to quantify the nuclear and cytoplasmic viscoelastic properties of single cells. We further quantified actin cytoskeleton density and alignment in IHAs and GBM cells via immunofluorescence microscopy and image analysis techniques. Results from our study show that contrary to the behavior of many extracranial cells, normal and cancerous brain cells do not exhibit significant differences in their viscoelastic behavior. Moreover, we also found that the viscoelastic properties of the nucleus and cytoplasm as well as the actin cytoskeletal densities of both brain cell types are similar. Our work suggests that malignant GBM cells exhibit unique mechanical behaviors not seen in other cancer cell types. These results warrant future study to elucidate the distinct biophysical characteristics of the brain and reveal novel mechanical attributes of GBM and other primary brain tumors.

Biophysical properties of the cellular microenvironment, including stiffness and geometry, influence cell fate. Recent findings have implicated geometric confinement as an important regulator of cell fate determination. Our understanding of how mechanical signals direct cell fate is based primarily on two-dimensional (2D) studies. To investigate the role of confinement on stem cell fate in three-dimensional (3D) culture, we fabricated a single cell microwell culture platform and used it to investigate how niche volume and stiffness affect human mesenchymal stem cell (hMSC) fate. The viability and proliferation of hMSCs in confined 3D microniches were compared with the fate of unconfined cells in 2D culture. Physical confinement biased hMSC fate, and this influence was modulated by the niche volume and stiffness. The rate of cell death increased, and proliferation markedly decreased upon 3D confinement. We correlated the observed differences in hMSC fate to YES-associated protein (YAP) localization. In 3D microniches, hMSCs displayed primarily cytoplasmic YAP localization, indicating reduced mechanical activation upon confinement. These results demonstrate that 3D geometric confinement can be an important regulator of cell fate, and that confinement sensing is linked to canonical mechanotransduction pathways.

Colorectal cancer (CRC) is the second most common cause of cancer-related mortality. At the molecular level, CRC is associated with genetic mutations and epigenetic modifications that dysregulate various signaling networks. From the biophysical viewpoint, invasive and metastatic cell migration need to be empowered by mechanical forces. In this study, we analyze the dynamic deformation of patient-derived CRC organoids in Fourier space and demonstrate how organoids with protooncogene BRAF mutation exhibit deformation phenotypes at an early stage. The organoids with BRAFmut have significantly lower elasticity and higher viscosity than those with BRAFWT, which mathematically indicated as the weakening of cell-cell adhesion. Immunohistochemical images, qRT-PCR, and TCGA data analysis confirm the downregulation of E-cadherin (CDH1) in BRAFmut organoids as well as in BRAFmut CRC, suggesting that the decrease in cell-cell adhesion in BRAFmut CRC facilitates invasive and metastatic migration. Notably, the recovery of CDH1 expression by pharmacological inhibition of DNA methylation can quantitatively be detected as the change in mechanical properties, suggesting that the complementary combination of dynamic phenotyping, mathematical modelling, and molecular-level analyses has a potential to unravel the mechanistic causality of the critical gene mutation and CRCs prognosis and the response to therapeutic interventions.

Proper placental vascularization is vital for pregnancy outcomes, but assessing it with animal models and human explants has limitations. Here, we present a 3D in vitro model of human placenta terminal villi that includes fetal mesenchyme and vascular endothelium. By co-culturing HUVEC, placental fibroblasts, and pericytes in a macro-fluidic chip with a flow reservoir, we generate fully perfusable fetal microvessels. Pressure-driven flow is crucial for the growth and remodeling of these microvessels, resulting in early formation of interconnected placental vascular networks and maintained viability. Computational fluid dynamics simulations predict shear forces, which increase microtissue stiffness, decrease diffusivity and enhance barrier function as shear stress rises. Mass-spec analysis reveals the deposition of numerous extracellular proteins, with flow notably enhancing the expression of matrix stability regulators, proteins associated with actin dynamics, and cytoskeleton organization. Our model provides a powerful tool for deducing complex in vivo parameters, such as shear stress on developing vascularized placental tissue, and holds promise for unraveling gestational disorders related to the vasculature.

Engineering tissues with an embedded vasculature of well-controlled topology remains one of the basic problems in biofabrication. Still, little is known about the evolution of topological characteristics of vascular networks over time. Here, we perform a high-throughput day-by-day analysis of tens of microvasculatures that sprout from endothelial-cell coated micrometric beads embedded in an external fibrin gel. We use the bead-assays to systematically analyze (i) macroscopic observables such as the overall length and area of the sprouts, (ii) microscopic observables such as the lengths of segments or the branching angles and their distributions, as well as (iii) general measures of network complexity such as the average number of bifurcations per branch. We develop a custom angiogenic image analysis toolkit and track the evolution of the networks for at least 14 days of culture under various conditions, e.g., in the presence of fibroblasts or with added endothelial growth factor (VEGF). We find that the evolution always consists of three stages: (i) an inactive stage in which cells remain bound to the beads, (ii) a sprouting stage in which the sprouts rapidly elongate and bifurcate, and (iii) the maturation stage in which the growth slows down. We show that higher concentrations of VEGF lead to an earlier onset of sprouting and to a higher number of primary branches, yet without significantly affecting the speed of growth of the individual sprouts. We find that the mean branching angle is weakly dependent on VEGF and typically in the range of 60-75 degrees suggesting that, by comparison with the available Laplacian growth models, the sprouts tend to follow local VEGF gradients. Finally, we observe an exponential distribution of segment lengths, which we interpret as a signature of stochastic branching at a constant bifurcation rate (per unit branch length). Our results, due to high statistical relevance, may serve as a benchmark for predictive models and reveal how the external means of control, such as VEGF concentration, could be used to control the morphology of the vascular networks. We provide guidelines for the fabrication of optimized microvasculatures with potential applications in drug testing or regenerative medicine.

Atherosclerosis is an arterial disease characterized by intravascular plaques. Disease hallmarks are vessel stenosis and hyperplasia, eventually escalating into plaque rupture and acute clinical presentations. Innate immune cells and local variations in hemodynamics are core players in the pathology, but their mutual relationship has never been investigated before due to the lack of modeling systems with adequate degree of complexity. Here, we combined computational fluid dynamics and tissue-engineering to achieve, for the first time in vitro, full atherosclerotic plaque development. Our model incorporates induced pluripotent stem cell-derived populations into small-caliber arteries that are cultured in atheroprone conditions. Using machine-learning-aided immunophenotyping, molecular and nanoprobe-based tensile analyses, we found that immune cells, extracellular matrix components and tensional state were comparable between in vitro and ex vivo human lesions. Our results provide further insights into the relation between hemodynamics and inflammation, introducing a versatile, scalable modeling tool to study atherosclerosis onset and progression.

The intrinsic complexity of biological processes often hides the role of dynamic microenvironmental cues in the development of pathological states. The use of micro-physiological systems (MPS) offers new technological platforms designed to model the dynamics of tissue-specific microenvironments in vitro and to holistically understand healthy and pathological states. In our previous works, we reported on engineering breast critical tumor microenvironment features, including matrix stiffness, pH, and fluid flow, and use the MPSs to study breast cancer cells phenotypes. By studying different microenvironments mimicking normal and tumor breast tissues, we obtained high-dimensional data using two distinctive human breast cell lines (i.e., MDA-MB231, MCF-7) investigating biomarkers commonly used in cancer in vitro models as cell proliferation, epithelial-to-mesenchymal transition (EMT), and breast cancer stem cell markers (B-CSC). We herein report on a new approach used to explore the complexity of MPSs and the high dimensional datasets: we introduce an innovative machine learning (ML) based platform employing unsupervised k-means clustering and feature extraction to identify key markers that differentiated invasive from non-invasive breast cell phenotypes. This novel data-driven approach streamlines experimental design and emphasizes the translational potential of integrating MPS-derived insights with ML to refine prognostic tools and personalize therapeutic strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/643499v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@4f947eorg.highwire.dtl.DTLVardef@9e1aedorg.highwire.dtl.DTLVardef@1f9fe8corg.highwire.dtl.DTLVardef@1b6b91d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Mechanomics describes the adaptation of mesenchymal stem cells (MSCs) to their mechanical environment, via cytoskeletal remodeling, as well as changes in shape and volume, ultimately resulting in emergent lineage commitment. Here we elucidated effects of exogenous microtubule stabilization, using paclitaxel (PAX), on stem cells capacity to sense and adapt to changes in their local mechanical environment. We studied the interplay between the living, evolving cells and their mechanical environment using established experimental and computational tools for respective delivery and prediction of shape and volume changing stresses. Stiffened and volumetrically larger microtubule-stabilized MSCs and their experienced significantly different normal and shear stress compared to control cells when exposed to identical bulk laminar flow (0.2 dyn/cm2) for one hour. These spatiotemporal mechanical cues transduced to the nucleus via the cytoskeleton, triggering significantly different changes in gene expression indicative of emergent lineage commitment than those observed in control cells. Using a paired computational model, we further predicted a range of mechanoadaptation responses of microtubule-stabilized cells to scaled up flow magnitudes (1 and 2 dyn/cm2). Hence, MSCs adapt to as well as modulate their own mechanical environment via cytoskeletal remodeling and lineage commitment - microtubule stabilization changes not only MSCs mechanoadaptive machinery, their capacity to adapt, and their lineage commitment, but also their mechanical environment. Taken as a whole, these studies corroborate our working hypothesis that MSCs and their mechanoadaptive machinery serve as sensors and actuators, intrinsically linked to their lineage potential via mechanoadaptive feedback loops which are sensitive to exogenous modulation via biochemical and biophysical means. ClassificationBiological Systems Engineering, Computational Simulations, Cell Biology, Biophysics

Alveolar macrophages (AMs) are the major sentinel immune cells in human alveoli and play a central role in eliciting host inflammatory responses upon distal lung viral infection. Here, we incorporated peripheral human monocyte-derived macrophages within a microfluidic human Lung Alveolus Chip that recreates the human alveolar-capillary interface under an air-liquid interface along with vascular flow to study how residential AMs contribute to the human pulmonary response to viral infection. When Lung Alveolus Chips that were cultured with macrophages were infected with influenza H3N2, there was a major reduction in viral titers compared to chips without macrophages; however, there was significantly greater inflammation and tissue injury. Pro-inflammatory cytokine levels, recruitment of immune cells circulating through the vascular channel, and expression of genes involved in myelocyte activation were all increased, and this was accompanied by reduced epithelial and endothelial cell viability and compromise of the alveolar tissue barrier. These effects were partially mediated through activation of pyroptosis in macrophages and release of pro-inflammatory mediators, such as interleukin (IL)-1{beta}, and blocking pyroptosis via caspase-1 inhibition suppressed lung inflammation and injury on-chip. These findings demonstrate how integrating tissue resident immune cells within human Lung Alveolus Chip can identify potential new therapeutic targets and uncover cell and molecular mechanisms that contribute to the development of viral pneumonia and acute respiratory distress syndrome (ARDS).

Brain cells are influenced by continuous fluid shear stress driven by varying hydrostatic and osmotic pressure conditions, depending on the brains pathophysiological conditions. While all brain cells are sensitive to the subtle changes in various physicochemical factors in the microenvironment, microglia, the resident brain immune cells, exhibit the most dramatic morphodynamic transformation. However, little is known about the phenotypic alterations in microglia in response to the changes in fluid shear stress. In this study, we first established a flow-controlled microenvironment to investigate the effects of shear flow on microglial phenotypes, including morphology, motility, and activation states. Microglia exhibited two distinct morphologies with different migratory phenotypes in a static condition: bipolar cells that oscillate along their long axis and unipolar cells that migrate persistently. When exposed to flow, a significant fraction of bipolar cells showed unstable oscillation with an increased amplitude of oscillation and a decreased frequency, which consequently led to the phenotypic transformation of oscillating cells into migrating cells. Interestingly, the level of pro-inflammatory genes increased in response to shear stress, while there were no significant changes in the level of anti-inflammatory genes. Our findings suggest that an interstitial fluid-level stimulus can cause a dramatic phenotypic shift in microglia toward pro-inflammatory states, shedding light on pathological outbreaks of severe brain diseases. Given that the fluidic environment in the brain can be locally disrupted in pathological circumstances, the mechanical stimulus by a fluid flow should also be considered a crucial element in regulating the immune activities of the microglia in brain diseases. Statement of SignificanceCellular morphology and motility are important factors that encompass the alterations in protein and gene-level expressions within cells. In pathological conditions, microglia, the resident brain immune cells, are known to undergo morphodynamic transformations in response to various physicochemical stimuli. Besides the commonly known soluble biochemical factors in the microenvironment, the differential flow characteristics of ISF have been linked to several neurological diseases, such as Alzheimers, Parkinsons, and brain tumors. Microglial cells, which are extremely sensitive to subtle changes in extracellular stimuli, have been identified as key players in these pathological conditions. Despite its importance, however, it has been challenging to study the sole effect of a shear flow on microglia. We investigated the morphodynamic features of microglia in response to precisely controlled interstitial-level fluid flow conditions using a microfluidic system in which isolated microglia are monitored in real-time while the undesirable effects from other extracellular factors are minimized.

Diet influences the levels of small molecules that circulate in plasma and interstitial fluid, altering the biochemical composition of the tumor microenvironment (TME). These circulating nutrients have been associated with how tumors grow and respond to treatment, but it remains difficult to parse their direct effects on cancer cells. Here, we combine a three-dimensional (3D) microfluidic tumor model with physiologically relevant culture media to investigate how concentrations of circulating nutrients influence tumor growth, cancer cell invasion, and overall tumor metabolism. Human triple-negative breast cancer cells cultured in 2D under media conditions mimicking five different dietary states show no observable differences in proliferation or morphology. Nonetheless, those exposed to high-fat conditions exhibit increased metabolic activity and upregulate genes associated with motility and extracellular matrix remodeling. In the 3D microfluidic model, high-fat conditions accelerate tumor growth and invasion and induce the formation of hollow cavities. Surprisingly, the presence of these cavities does not correlate with an increase in apoptosis or ferroptosis. Instead, RNA-sequencing analysis revealed that high-fat conditions induce the expression of MMP1, consistent with cavitation via cell invasion. Mimicking the flow of circulating nutrients within the TME can thus be used to identify novel connections between metabolic states and tumor phenotype.

The tumor microenvironment (TME), which is composed of various cell types and the extracellular matrix (ECM), plays crucial roles in cancer progression and treatment outcomes. However, the impact of the mechanical properties of the ECM, specifically collagen fibril alignment and crosslinking, on macrophage behavior and polarization is less understood. To investigate this, we reconstituted 3D collagen matrices to mimic the physical characteristics of the TME. Our results demonstrated that stiffening the matrix through the alignment or crosslinking of collagen fibrils promotes macrophage polarization toward the anti-inflammatory M2 phenotype. This phenotype is characterized by increased expression of CD105 and CD206 and a distinct cytokine secretion profile. The increased stiffness and aligned fibrils activate mechanotransduction pathways, notably integrin {beta}1 and PI3K signaling, leading to increased IL-4 secretion, which acts in an autocrine manner to further promote M2 polarization. Interestingly, these stiffened microenvironments also suppressed the proinflammatory response. In coculture experiments with breast cancer cell lines (MDA-MB-231 and MCF-7), macrophages within stiffened or aligned matrices significantly increased cancer cell proliferation and invasion. These findings suggest that the mechanical properties of the ECM, specifically its alignment and crosslinking, create a more favorable environment for tumor progression by modulating macrophage activity. Overall, our study underscores the critical role of ECM mechanics in shaping immune cell behavior within the TME, highlighting the potential for therapies that target ECM properties and macrophage polarization to inhibit cancer progression and enhance treatment efficacy.

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a 3D tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the modelling approach. Using the proposed workflow, we demonstrate that we can indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally.

We demonstrate a statistical modeling technique to recognize T cell responses to different external environmental conditions using membrane distributions of T cell receptors. We transformed fluorescence images of T cell receptors from each T cell into estimated model parameters of a partial differential equation. The model parameters enabled the construction of an accurate classification model using linear discrimination techniques. We further demonstrated that the technique successfully differentiated immobilized T cells on non-activating and activating surfaces. Compared to machine learning techniques, our statistical technique relies upon robust image-derived statistics and achieves effective classification with a limited sample size and a minimal computational footprint. The technique provides an effective strategy to quantitatively characterize the global distribution of membrane receptors under various physiological and pathological conditions.

In vitro microphysiological systems (MPS) are needed to replicate events in the lymph node (LN) leading to humoral immunity against new immune threats, but current lymphoid MPS focus largely on recall responses from memory lymphocytes. Here, an LN MPS was developed from primary, naive human lymphocytes in microfluidic 3D culture to model interactions and antibody production at the LN T cell--B cell border. Naive CD4+ T cells exhibited CCL21-dependent chemotaxis, chemokinesis, and activation in the MPS, and were skewed to a T follicular helper (pre-Tfh) phenotype. IgM secretion was induced in co-culture with activated B cells in the presence of a superantigen, staphylococcal enterotoxin B (SEB); micropatterning confirmed that the interaction required physical proximity. SEB-dependence of IgM secretion was greatest at a 1:5 T:B ratio, while seeding more pre-Tfh cells accelerated plasmablast differentiation and clustering. On-chip co-cultures at a 1:5 T:B ratio developed large lymphoid clusters containing CD38+ plasmablasts and CD138+ plasma cells after 15 days, with response varying between donors. Significant plasmablast induction in T-B co-cultures did not require the pre-Tfh phenotype, but pre-Tfh cells were required for inducing IgM secretion. We envision that this LN MPS will enable predictions and mechanistic analyses of human humoral immunity in vitro.

Controlling the multiscale organization of vasculature within diverse geometries is essential for shaping tissue-specific and organ-specific architectures. Nevertheless, how geometrical characteristics of surrounding tissues influence vessel morphology and blood flow remains unclear. Where the regulation of vascular organization by mechanical signals associated with fluid flow is well known, this study postulates that the organization of developing vasculature can also be regulated by mechanical signals connected to the confinement and thus the deformation of surrounding tissues. To test the Shape-Induced Vascular Adaptation (SIVA) concept, fertilized chicken egg contents containing developing vasculature were cultured within engineered eggshell platforms of different shapes. Our findings demonstrate that the vascularized chick chorioallantoic membrane (CAM) adapts to the shape of engineered eggshell, long before reaching its boundaries. This adaptation affects the organization of the vascular network within the CAM, affecting parameters such as vessel area, branching, orientation, length, diameter and endpoints. Specifically, we observed that sharp corners in the engineered eggshell led to more elongated vascular structures. To further explore the dynamic nature of this phenomenon, a proof-of-concept experiment was performed using a shape-shifting engineered eggshell that deforms the egg content from circle to square shape. Using this shape-shifting prototype, we observed a direct effect of eggshell deformation on the vessel morphology and flow dynamics in a time-dependent manner. Overall, our exovo experimental platform provides a unique opportunity to study how mechanical stimuli such as shape influence the spatial and temporal organization of developing vascularized tissues. By subjecting these tissues to various static and dynamic conditions, we induced both local and global changes in their organization. This class of perturbation provides us with an additional tool which can be used for shaping vascular organization within developing tissues and to engineer tissues with geometrically tunable vessel structures.