Cellular and Molecular Bioengineering

Tissue engineered constructs are increasingly used for both modeling organs and disease in vitro as well as for therapeutic intervention. In addition to collagen, these constructs commonly include native extracellular matrix proteins (ECM), such as fibronectin and laminin. Given the critical role of inflammatory pathways in disease and in response to implanted materials, it is important to understand the role these proteins play in regulating the inflammatory environment. Fibronectin and laminin influence neutrophil function and endothelial activation in 2D, but their regulation of the inflammatory environment in 3D engineered constructs is not clear. For this study, we used an inflammation-on-a-chip device that includes a model blood vessel surrounded by a collagen I hydrogel with fibronectin and/or laminin. We investigated the additive effects of both proteins and a range of concentrations for each protein to determine concentration dependence. Both fibronectin and laminin have concertation dependent effects on neutrophils and the endothelium. High concentrations (50 {micro}g/mL) of fibronectin reduced neutrophil migration, while 20 {micro}g/mL laminin reduced neutrophil extravasation and migration, potentially due to lower ICAM-1 expression by the endothelium. Interestingly, 50 {micro}g/mL of laminin significantly disrupted endothelial vessel formation and reduced ICAM-1 and VE-cadherin expression, likely due to significant changes in the collagen architecture. The inclusion of fibronectin and laminin, even at physiological levels, results in significant effects on neutrophil behavior, endothelial vessel formation, and collagen architecture. These proteins impact the inflammatory environment and thus need to be considered when modeling diseases and designing therapeutics, especially when neutrophils or an endothelium are involved. Translational Impact StatementThis work uses an inflammation-on-a-chip device to study how fibronectin and laminin impact neutrophil behavior and vascular inflammation as these proteins are commonly used in engineered constructs. We found that fibronectin impairs neutrophil migration, while laminin decreases neutrophil extravasation and migration and at higher concentrations also prevents endothelial vessel formation. Therefore, researchers should be aware that these proteins will alter the inflammatory environment when including them in engineered constructs.

Protein tyrosine phosphatase receptor J (PTPRJ) restrains cell proliferation and migration by dephosphorylating receptor tyrosine kinases (RTKs) including the epidermal growth factor receptor (EGFR). PTPRJ is a purported tumor suppressor, and alterations to its expression and/or function are associated with colorectal, breast, lung, and other cancers. While there is interest in controlling PTPRJ-regulated phenotypes, efforts are limited by the complexity of PTPRJ-mediated signaling. PTPRJ dephosphorylates multiple RTKs, and the degree to which PTPRJ control of signaling and phenotypes depends on local cellular RTK activation profiles is unknown. To probe the context dependence of PTPRJ signaling regulation, we collected signaling measurements across 16 pathway nodes at two time points in a panel of HSC3 carcinoma cells engineered with different PTPRJ expression profiles. Cells were treated with three different RTK ligands, and paired phenotype measurements (viability, wound healing, xCELLigence cell index) were made. Partial least squares regression models were developed to predict relationships between PTPRJ-regulated signaling pathways and cell phenotypes. The model effectively separated contributions to variance arising from the PTPRJ expression background and growth factor context. In testing model predictions, we demonstrated that PTPRJ suppressed MET-induced cell cell proliferation via regulation of a HER3/AKT signaling axis that stabilized PTPRJ expression through an unanticipated feedback mechanism. We also found that PTPRJ regulated HSC3 cell migration via JNK signaling that was preferentially activated by MET. Our results identify new regulatory nodes through which PTPRJ influences cancer cell phenotypes and demonstrates that these processes preferentially occur in the context of distinct RTK activation states.

IntroductionCancer progression is driven not only by tumor cells but also by interactions between the extracellular matrix (ECM), stromal cells, and immune cells within the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are major drivers of ECM remodeling, assembling ECM with aberrant organization. Extra domain A fibronectin (EDA-FN), a cellular FN containing an extra type III domain, is upregulated in the TME. EDA-FN regulates cellular behavior and has been associated with poor patient prognosis. Macrophages are among the most abundant immune cells within the TME, where they contribute to TME remodeling and inflammation to promote cancer cell invasion and metastasis. However, how tumor-associated matrix-specific cues regulate macrophage behavior remains largely understudied. PurposeHere, we developed a fibroblast-derived matrix platform that captures the structural imprint of tumor-associated EDA-enriched matrices and investigated how matrix-specific cues regulate macrophage behavior in the absence of ongoing soluble factor cues. MethodHuman mammary fibroblasts (HMFs) preconditioned in incubated low-serum media (lNC, or control) and MDA-MB231 metastatic breast cancer cell-conditioned media (mTCM) were cultured on polyacrylamide gels of 2 kPa and 20 kPa, respectively, followed by decellularization. Matrix organization, including fiber alignment, width, and intrafibrillar spacing, was quantified from confocal images. Decellularized EDA-FN-enriched matrices were subsequently reseeded with macrophages to assess macrophage morphology, phenotype, and matrix interactions. ResultsThe combined effects of tumor-derived soluble factors and pathological stiffness induced a CAF-like phenotype in HMFs, accompanied by cytoskeletal reorganization and microarchitectural alterations of EDA-FN-enriched matrices. Tumor-associated matrices exhibited increased alignment, narrower fiber width, and enlarged intrafibrillar spacing compared to control matrices. These aberrant, tumor-associated matrix-derived features were associated with altered macrophage behavior, including heterogeneous morphology, enhanced localized EDA-FN matrix loss beneath the cell body, and a hybrid phenotype with a shift toward a CD206-dominant profile. ConclusionsThese findings demonstrate the feasibility of obtaining EDA-FN-enriched matrices to isolate matrix-specific cues for investigating macrophage-ECM interactions. Furthermore, this platform can be leveraged to identify matrix-targeting therapeutic approaches for modulating macrophage function within the TME.

PurposeFibrosis is the pathological remodeling of the extracellular matrix (ECM) that is largely orchestrated by activated fibroblasts. The mechanical properties of the ECM change drastically during fibrosis, and fibroblasts become increasingly activated by mechanical environments that mimic the properties of fibrotic tissues. While the effects of increased elastic modulus (stiffness) on fibroblast activation have been well-studied, the impact of changes in viscoelasticity are less clear. Here, we sought to determine how fibroblast activation is altered by changes in viscoelasticity in a three-dimensional, fibrillar microenvironment. MethodsWe employed 3D alginate collagen I hydrogels with independently tunable stiffness and stress relaxation rates. Dermal fibroblasts were encapsulated in hydrogels with four distinct mechanical profiles (soft: 3 kPa or stiff: 10 kPa, fast stress relaxing: {tau}1/2 {approx} 160 s or slow stress relaxing: {tau}1/2 {approx} 1600 s). We assessed fibroblast activation by changes in cell morphology, expression of key activation markers, and evidence of ECM remodeling. ResultsFibrillar alginate collagen networks enhanced fibroblast spreading, -smooth muscle actin stress fiber formation, and fibroblast activation protein- expression in matrices that were slow relaxing or stiff. The presence of the fibrillar network further enhanced fibroblast activation, independent of the changes driven by matrix viscoelasticity. ECM remodeling was also promoted by slow relaxing matrices, with increased fibronectin deposition and more remodeling of the local collagen fiber network. ConclusionsOur results demonstrate that fibroblast activation is highly responsive to matrix stress relaxation rate, and that models incorporating fibrillar, viscoelastic networks can provide new insights into the role of ECM mechanics driving fibroblast activation.

BackgroundActivated platelets release polyphosphate (polyP), a linear polymer of inorganic phosphate residues, from dense granules. Experiments performed under no-flow conditions show that polyP alters the kinetics of tissue factor (TF) pathway reactions, accelerating FXI activation by thrombin and FV activation by FXa and thrombin, and may impact inhibition by tissue factor pathway inhibitor (TFPI). How polyP influences this pathway in conjunction with platelet deposition under flow remains understudied. ObjectivesTo investigate how polyP-mediated acceleration of FV and FXI activation modulates thrombin generation under flow in TF-initiated coagulation. MethodsWe extended a previously validated mathematical model of platelet deposition and coagulation under flow to examine polyP-mediated effects following a small vascular injury during intravascular clotting. Simulations varied the surface density of TF exposed, wall shear rate, and plasma TFPI concentration. ResultsPolyP shifts the threshold TF density for a thrombin burst to lower TF densities. For TF densities above this threshold, polyP shortens the lag time to thrombin generation in a TF- and shear-rate-dependent manner. Although no explicit effect of polyP on TFPI function was included in the model, thrombin generation was much less sensitive to TFPI concentration with polyP, in a TF-dependent manner. Relative contributions of accelerations of FV and FXI activations depend on incompletely known enhancements by polyP. ConclusionsThe experimentally observed influence of polyP on TFPI function depends on TF density and may arise indirectly from accelerated FV and FXI activation, with the dominant effect arising through accelerated thrombin-mediated conversion of FV to FVa.

Cell-penetrating peptides (CPPs) can deliver biomacromolecular cargos into cells, potentially enabling a new mode of intracellular drug delivery. However, a major problem with CPP-mediated delivery is entrapment of CPPs within endosomes and covalent linkages ensure CPPs and cargos share a common fate. We previously developed a CPP-adaptor system based on reversible, calcium-dependent cargo binding that produces cargo release from adaptors as complexes dissociate following internalization and Ca2+ efflux from early endosomes. Having employed CPP-adaptors with an array of protein cargos of differing charges, it became apparent that positively charged cargos often appeared to dominate internalization and that association with the adaptor had little effect. To systematically address the effects of cargo charge and CPP function, we tested the ability of several adaptors to increase internalization of a set of adaptor binding GFP cargos having net charges of +9, +15, +20, +25 and +36. Intrinsic internalization of these cargos reproduced reported patterns showing that positive charge increases internalization. However, labeling these cargos with a chemical fluorophore revealed that GFP fluorescence grossly underestimated total internalization. Internalization was charge and concentration dependent with more positive cargos showing apparent saturation of internalization at 100-400 nM, well below the concentrations at which covalently linked CPP-cargos are dosed. We tested the ability of 5 adaptors to internalize these cargos. Our prototype adaptor, TAT-CaM, was completely ineffective with the +9 cargo, but internalized moderately charged cargos extremely efficiently at concentrations far below the {micro}M range. A derivative adaptor, TAT-LAH4-CaM, was highly effective with all cargos and produced similar maximal internalization at 100-400 nM. However, two adaptors specifically designed with increased positive charge inhibited internalization of the most positive cargos. One of these, GFP-CaM, based on the supercharged GFP with net charge of +36, did increase internalization of the least positive cargos, demonstrating an adaptor with high affinity for the cell surface can increase internalization of a neutral cargo at very low concentration. The common maximal level of intrinsic GFP cargo internalization correlated with surface loading of these cargos, suggesting a limit to the beneficial effects of increased plasma membrane association. However, TAT-CaM further increased internalization via an apparently distinct mechanism. In this limited study of the interaction of cargo charge and adaptor efficacy, we found diverse behaviors that hint at the power and flexibility possible with adaptor/cargo internalization.

Methods to visualize and quantify the molecular responses of cells to local forces exerted at adhesions are crucial to elucidate how physical forces control cellular behavior. Of the many proteins involved in focal adhesions, vinculin plays a key role in mediating force-sensitive processes. Here, we combined optical tweezers and Forster resonance energy transfer (FRET) microscopy to measure the intensity and FRET efficiency of the vinculin tension sensor, VinTS, in response to a force. Fibroblasts expressing VinTS formed adhesions on fibronectin-coated, 3m-diameter, polystyrene beads. As the beads were displaced by the cell, we applied an optical trap to counteract this movement and increase the traction force required by the cell to maintain the bead displacement. The optical trap stiffness varied from zero (no laser) up to 0.26 pN/nm. In this range, the median bead displacement after 5 min was ~200nm in all trapping conditions inducing counteracting forces in the 10-100pN range. To maintain this displacement, vinculin recruitment increased (up to 35% in relative intensity at high stiffness) while tension increased but more moderately (1-2% decrease in absolute FRET efficiency). For higher trap stiffness, the main response was an increase in vinculin recruitment, while the tension did not increase significantly. The increase in vinculin intensity was correlated with the decrease in FRET efficiency at 0.26 pN/nm but not at lower stiffness. Thus, the presence of the high stiffness optical trap over 5 min appears to induce a positive correlation between vinculin recruitment and vinculin tension. In a few instances, vinculin puncta migrated a few microns away from the bead exceeding the bead movement speed while experiencing an increase in both vinculin intensity and tension. Taken together, the results suggest that combining an optical trap with vinculin tension measurements uncovers novel vinculin dynamics in the presence of a force.

Extracellular vesicles (EVs) are lipid spheres released from cells. Research utilizing EVs has met several hurdles owing to the small size of the majority of EVs and other nanoparticles (<150 nm) and the lack of detection technologies capable of providing high-throughput single particle measurements at this scale. The use of high-throughput single particle measurements is critical for the assessment of EV heterogeneity and abundance which are features often used to assess the development of isolation protocols or particle characterization. The Coulter principle, known in the field as resistive pulse sensing (RPS), has been used for several decades to size and count cells. More recently, this technology has evolved to accommodate nanoparticle analysis. In the last decade a platform utilizing microfluidic resistive pulse sensing (MRPS) has been demonstrated for nanoparticles, offering ergonomic characterization of nanoparticles along with utilizing open format data. To date, assessment of MRPS accuracy and reporting standards have not been assessed. With the aim of increasing data accuracy, ergonomics, and reporting transparency, we developed a microfluidic resistive pulse sensing post-acquisition analysis software (RPSPASS) application for automated cohort calibration, population gating, statistical output, QC plot generation, alternative data file outputs, and standardized reporting templates.

BackgroundDespite improved cancer outcomes with kinase inhibitors (KIs), their cardiotoxicity remains a significant clinical challenge. Current approaches to predict and prevent KI-induced cardiac adverse events (CAEs) are limited by an incomplete understanding of underlying mechanisms, including the contribution of off-target kinase engagement. ObjectivesTo establish links between kinase inhibition profiles and cardiotoxic phenotypes using empirical proteomic data, and to leverage these profiles in machine learning (ML) models capable of predicting KI cardiotoxicity. MethodsWe curated a database connecting kinome-wide target binding profiles of FDA-approved KIs (n=44) with documented incidence rates of six distinct CAEs. Binding profiles were derived from unbiased chemoproteomics and used to assess associations between KI selectivity, specific kinase targets, and CAEs. Profiles were further used to develop ML models to predict CAE risk, with SHAP-based model interpretation applied to identify cardiotoxicity-associated kinases. ResultsKI promiscuity was not a significant predictor of cardiotoxicity across all six CAEs. Frequency analysis revealed that kinases including RET, PDGFRB, and DDR1 are recur-rently inhibited across CAE-linked compounds, with nearly all identified as off-targets not annotated by the FDA. Network and pathway enrichment analyses supported a systems-level model in which cardiotoxicity arises from coordinated disruption of cardiac-relevant signaling networks. ML models achieved 66-84% cross-validated accuracy (ROC-AUC 0.75-0.8) across CAE endpoints, with SHAP analysis identifying PDGFRB, EGFR, and MEK1/2 among the most predictive kinases. ConclusionsProteomic kinome profiling combined with machine learning provides a mechanistically grounded framework for predicting KI cardiotoxicity and supports off-target-aware drug design to minimize cardiovascular risk.

Lymphocyte-extracellular matrix (ECM) interactions occur intermittently throughout the lymphocytes life cycle. Alterations in blood insulin levels following feeding modulates naive lymphocyte trafficking and adhesion to fibronectin via a pathway involving insulin-like growth factor-1 receptor (IGF-1R), phospholipase C gamma 1 (PLC-{gamma}1) and {beta}2 integrin activation. Lymphocytes exert traction forces, on the ECM during the process of extravasation. While these forces are essential for several homeostatic processes, the role of insulin in modulating lymphocyte-derived traction forces upon ECM adhesion is unknown. The aim of the current study was to investigate the effect of insulin on the traction generated by lymphocytes when adhered onto a fibronectin-coated substrate. Jurkat T-cells were placed on a fibronectin layer (50{micro}g/ml, 100{micro}m thickness) coated on polyacrylamide gels of stiffness 400Pa with red fluorescence beads as fiduciary markers. The cellular force generated by Jurkat T-cells was mapped using traction force microscopy. To elucidate the role of PLC-{gamma}1 in cellular force generation, the traction of Jurkat T-cells lacking PLC-{gamma}1, as well as those of a knockout cell where PLC-{gamma}1 was restored were quantified and compared with wild-type Jurkat T-cells. Lack of PLC-{gamma}1 attenuated adhesion when compared to wild-type Jurkat T-cells. Additionally, the traction force generated by each cell type decreased with increasing concentration of extracellular calcium. Treatment of adherent Jurkat T-cells with insulin increased traction in lower extracellular calcium condition while a dip was observed when a high extracellular calcium was present, in comparison to the untreated cells. However, the effect of insulin treatment was lost in the case of Jurkat T-cells lacking PLC-{gamma}1. Together these results indicate that insulin regulates traction force generated by adherent Jurkat T-cells via a process involving PLC-{gamma}1, in a calcium dependent manner.

Accurate cell counting is essential in tissue engineering and cancer research. The ongoing transition towards advanced 3D in vitro tumour models raises a question about the validity of the standard cell counting protocols, particularly in the systems containing extracellular matrix-based scaffolds. Here, we provide a quantitative analysis of the performance of three popular plate reader-based cell counting/viability assays, such as the Alamar Blue, MTT, CellTiter Glo 3D assays, in 2D monolayer and 3D scaffold-based cultures of U251 human glioblastoma cells, including cell-laden Matrigel plugs, and original tissue engineering constructs based on the decellularised sheep brain scaffolds. We quantitatively characterized the assays linearity, precision, biological and technical reproducibility, proportionality, and inter-assay agreement. The study revealed that assays performance is highly platform-dependent, with 2D cultures allowing significantly more precise and reliable measurements than in 3D ECM scaffold-based cultures. The numerical results provided in this study can help researchers make informed decisions when working with 3D scaffold-based in vitro tumour models and for other tissue engineering purposes where precise cell counting is essential. ToC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=184 SRC="FIGDIR/small/720021v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@16018d9org.highwire.dtl.DTLVardef@1ff7d6dorg.highwire.dtl.DTLVardef@838021org.highwire.dtl.DTLVardef@1510d5b_HPS_FORMAT_FIGEXP M_FIG C_FIG

CRISPR-Cas-based diagnostics utilize the Cas enzymes trans-cleavage activity to generate signal and have become popular platforms for sensitive nucleic acid detection. Recently, autocatalytic systems have been demonstrated to improve the time to response and sensitivity in some cases. However, mechanistic description of these assays is limited and optimization relies on simple trial-and-error. In this work, we present the first comprehensive kinetic model that integrates all major biochemical processes involved in these assays, including cleavage reactions, nucleic acid equilibrium kinetics, inhibition of trans-cleavage by single-stranded DNA, and degradation of single-stranded reaction components. We discuss the biochemical foundations and implementation of the ordinary differential equation model, which is built for adaptation to different reaction schemes. We use the full model to investigate the role of nucleic acid stability in assay performance for a typical nucleic acid design and show that our model demonstrates inhibition effects consistent with experimental data. We describe the reaction behavior, derive a simplified analytical model and compare its performance to the full analytical model. Finally, we demonstrate tools developed for rapid in silico optimization to guide the rational design of future target-amplification-free CRISPR-Cas-based autocatalysis assays.

Anticancer drug resistance is challenging to overcome because it can arise through both intrinsic and acquired mechanisms, each driven by distinct cellular machinery. In particular, there is a sharp need for therapies that target hormone-insensitive prostate tumors due to the growing incidence of castration-resistant prostate cancer. Optimizing the pathways that regulate apoptosis in prostate cancer offers a promising strategy to induce apoptosis and inhibit tumor progression, since these mechanisms do not depend on hormonal signaling. Here, we identified strategies to enhance apoptosis in prostate cancer cells. We used several computational tools (including sensitivity analysis, particle swarm optimization, and ImageJ) to design an ordinary differential equation model of caspase-mediated prostate cancer apoptosis signaling. We apply the model to identify key modalities that increase the propensity toward apoptosis across three separate pro-apoptotic drugs (Tocopheryloxybutyrate, Narciclasine, and Celecoxib). Overall, we demonstrate that apoptosis dynamics can be accurately captured in response to each of the three drugs and identify which features of the model represent viable targets for overcoming intrinsic drug resistance.

BackgroundIn the course of testing mAb-based therapies to eradicate the persistent reservoir of HIV infection, we investigated the efficacy and mode of killing of HIV-infected cells by two categories of cytotoxic immunoconjugates (CICs) targeted by the same mAb, an immunotoxin (IT) and antibody-drug conjugate (ADC). MethodsWe performed metabolic and transcriptional analyses of treatment effects on the persistently-infected cell line H9/NL4-3. Cells were treated with CICs consisting of the anti-gp41 mAb 7B2 conjugated to either deglycosylated ricin A chain (dgA) or to the highly cytotoxic anthracycline derivative PNU-159682. At intervals up to 24 hr, intracellular metabolites were quantified by 1H nuclear magnetic resonance spectroscopy, and the transcriptome analyzed by RNA-Seq. ResultsSix hr post treatment, 7B2-dgA elicited both metabolic and transcriptional alterations, whereas 7B2-PNU treated cells did not differ from untreated cells. 7B2-dgA treated cells exhibited elevated intracellular levels of many amino acids, and activation of gene pathways for apoptosis, intracellular signaling, and immune activation. By 24 hr, both 7B2-dgA and 7B2-PNU treated cells differed markedly from untreated. Many of the changes observed following 7B2-PNU treatment at 24 hr were similar to those observed at 6hr following 7B2-dgA, likely indicating processes involved in cell death, but a number of alterations were unique to either IT or ADC treated cells. ConclusionsAn IT and ADC showed both similarities and differences in their cytotoxic effects. These results raise the question of whether the mode of cell killing could be a determinant of clinical efficacy. Although these studies were aimed at targeting the persistent reservoir of HIV infection, they have relevance for the design of CICs to treat cancer and other conditions. SUMMARYThe use of cytotoxic immunoconjugates, wherein an antibody is attached to a cellular poison, is effective in the treatment of cancer and other conditions. We seek to extend these results to treating HIV and other chronic viral infections. We analyzed the molecular mechanisms of cell killing when the same antibody was attached to different toxic structures. We report that each immunoconjugate induced both common and distinct patterns of killing. Such differences may have clinical relevance.

T cell receptors (TCRs) are critical for immune surveillance and successful adaptive immune response against foreign antigens. TCRs drive this key arm of the immune system through recognition of peptide epitopes presented on MHC complexes. However, they are limited due to their stochastic nature and generation via genetic recombination. In silico design of functional TCRs that target defined peptide epitopes would be of considerable utility but has up until now been unsuccessful. Here, we develop an artificial intelligence (AI)-powered approach using a hybrid physics-based simulation and generative AI that successfully engineers TCRs against defined epitopes presented by MHC-I. We use this approach to design TCRs against two cancer antigens, a HERC1 neoantigen and an immunogenic neoepitope in mutant EGFR. We engineer multiple TCRs against the HERC1 neoantigen which activate T cells in response to exposure to peptide-MHC I and kill cancer cells more effectively than a patient-derived TCR. In addition, we used generative AI to design functional TCRs that target the EGFR T790M neoantigen, engineering greater specificity against the mutant sequence. We present an AI-based approach to TCR design with broad utility for efforts to engineer TCRs and for the development of new cell therapies. One sentence summaryArtificial intelligence-based approach enables the directed engineering of functional TCRs with enhanced features that target cancer neoantigens.

In this study, we evaluated the impact of different in vitro 3D culture modelling methods on the activity of doxorubicin (DOX) and 5-fluorouracil (5-FU) in human melanoma spheroids. Human melanoma A375 and IGR39 spheroids were generated using the hanging drop and non-adhesive surface methods. Spheroid growth dynamics were assessed by measuring changes in spheroid diameter. To compare the effects of anticancer drugs in spheroids of different sizes, spheroids of approximately 200 and 400 {micro}m were formed. Drug activity was evaluated based on spheroid growth and cell viability using the MTT assay. A375 spheroids formed using the non-adhesive surface method were more sensitive to DOX than spheroids formed using the hanging drop method. In smaller A375 spheroids, 10 {micro}M 5-FU reduced cell viability more effectively in spheroids formed using the hanging drop method. In contrast, IGR39 spheroids formed by the hanging drop method were more resistant than those formed on a non-adhesive surface. However, in IGR39 spheroids, the effects of DOX and 5-FU on growth and viability did not significantly differ between formation methods. In conclusion, A375 spheroid growth was not significantly influenced by the formation method, whereas IGR39 spheroid growth depended on the method used. A375 spheroids formed on non-adhesive surfaces were more sensitive to DOX, whereas 5-FU activity depended on drug concentration and spheroid size. In IGR39 spheroids, the effects of DOX and 5-FU on growth and viability were largely independent of the spheroid formation method. Based on these results, it can be concluded that the researchers should carefully select the spheroid formation method for their studies, as this may influence the results of the tested compounds effect on their size and viability.

Extracellular matrix (ECM) proteins assemble to form a heterogeneous connective scaffold that supports cells. Physical interactions between cells and the matrix regulate cellular behaviors and influence subsequent tissue construction. However, there is a lack of fundamental understanding regarding the contributions of individual native ECM proteins to the matrix. This gap arises from the need for nanoscopic characterization, which operates on a much smaller length scale than typical assessments in cell and tissue cultures, as well as in tissue reconstruction and clinical implantation. This study aims to systematically investigate how individual ECM proteins affect lipid membranes structurally and mechanically, and how these influences regulate cell migration. Results from Langmuir isotherm analysis, X-ray reflectivity measurements, and cell scratch assays demonstrate that strong collagen adsorption on the membrane surface disrupts lipid packing. However, its rigid network provides a sturdy scaffold for cell adhesion, thereby enhancing cell attachment and promoting cell migration. In contrast, elastin has a minimal structural or mechanical impact on the membrane during both adsorption and compression, but it benefits cells by facilitating migration and reducing the risk of infection. Fibronectin, on the other hand, exhibits complex mechanical responses to compression, characterized by significant structural rearrangements that occur during adsorption. This strong interaction with the membrane can result in excessively high adhesion forces, ultimately limiting cell motility. These findings lay the foundation for the design of artificial scaffolds that can manipulate cellular responses, a critical step toward advancing regenerative medicine and tissue engineering. SignificanceFabricating extracellular matrix (ECM) scaffolds from cells offers advantages over traditional approaches, such as decellularized tissues, which face donor limitations, and artificial scaffolds, which may hinder cellular communication. However, the slow harvesting process of cell-derived ECM has limited its clinical applications. This research is part of a larger mission to engineer ECM prescaffolds on lipid carriers tailored to cell requirements, enhancing ECM production and regulating cell behavior. The first step involves systematically analyzing the structural and mechanical effects of ECM on lipid membranes and how these effects regulate cellular behavior. This work confirms distinct characteristics of ECM proteins, advancing fundamental understanding of cell-matrix interactions and paving the way for scaffold engineering.

Curcumin is a naturally occurring polyphenol that demonstrates considerable anti-cancer activity, however the aqueous insolubility, rapid metabolism and relatively low bioavailability are limiting to its clinical application. As such, a curcumin-magnesium (Cur-Mg) coordination complex was synthesized and subsequently encapsulated within DNA hydrogels (Cur-Mg-Hgel). The Cur-Mg complex was fully characterized using UV-Vis spectroscopy, FTIR and X-ray diffraction (XRD). UV-Vis, FTIR and XRD all support the formation of a coordination complex and suggest a decreased level of crystallinity compared to free curcumin. DNA hydrogels were formed and characterized using atomic force microscopy, rheology and swelling kinetic studies. In vitro cytotoxicity studies utilizing an MTT assay demonstrate dose dependent inhibition of HeLa cell proliferation and a slightly better retention of RPE-1 viability at low concentrations (suggesting some difference in sensitivity) though significant cell death is seen at higher concentrations and both cells. Intracellular production of ROS was measured using the DCFH-DA assay and is seen to increase when HeLa cells are treated with Cur-Mg-Hgel in comparison to un-treated controls. Annexin V/PI staining demonstrates primarily late or early apoptotic activity with minimal necrosis following treatment with Cur-Mg-Hgel. The evidence presented strongly supports the notion that Cur-Mg-Hgel is a ROS-modulating, pro-apoptotic Hydrogel suitable for cancer treatment. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/724072v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@18727aeorg.highwire.dtl.DTLVardef@3e20adorg.highwire.dtl.DTLVardef@d3703eorg.highwire.dtl.DTLVardef@16e260e_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundCytokines are immunomodulatory proteins that play central roles in regulating immune responses and represent attractive targets for cancer therapy. However, as single agents, cytokines have shown limited clinical benefit due to systemic toxicities and a short in vivo half-life. Our group has focused on engineering fusion cytokines (fusokines) that couple two cytokines into a single biologic to reprogram immune cell responses by enforcing non-canonical receptor engagement and signaling. A chimeric IL-6/IL-1{beta} fusokine was engineered to test the hypothesis that enforced co-engagement of IL-6 and IL-1{beta} signaling pathways would confer a gain-of-function phenotype in T cells and promote robust anti-tumor immunity. Here, we describe the immunomodulatory properties of IL6/1 fusokine and a method to deliver this fusokine to produce inhibition of ovarian tumor growth in a pre-clinical mouse model. MethodsLentiviral vectors encoding murine or human IL6/1 were designed using Vector Builder and expressed in either HEK293, CHO or ID8-F3 (p53-/-) cells depending on the downstream experiment to be conducted. IL6/1 expression was validated by ELISA and flow cytometry. Effects of human IL6/1 (hIL6/1) on T cell function (proliferation, memory phenotype, activation induced apoptosis) were monitored by flow cytometry. For in vivo studies, ID8-F3 murine ovarian cancer cells expressing mouse IL6/1 (mIL6/1) were administered intraperitoneally (I.P.) as a cell-based therapy to C57BL/6 female mice bearing established ID8-F3 luciferase tumors. Tumor progression was monitored by bioluminescence (BLI) imaging, and overall survival was evaluated. ResultshIL6/1 significantly enhanced T cell survival and selectively promoted activation and expansion of CD45RO memory T cells. mIL6/1 expressing ID8-F3 cells (ID8IL6/1) demonstrated stable transduction and sustained cytokine secretion. In vivo, ID8IL6/1 cell therapy significantly reduced tumor growth and improved overall survival compared to control groups, with 2 of 8 mice achieving complete tumor clearance. ConclusionThese findings indicate that IL6/1 fusokine enhances T cell survival and proliferation while promoting memory responses. Engineered cancer cells (ID8-F3) expressing mIL6/1 fusokine induced a strong anti-tumor response when delivered as a therapeutic vaccine in ovarian cancer mouse model. What is already known on this topicO_LIFusokines are a class of bifunctional proteins designed to achieve synergistic immune modulation. Previous studies in our lab have shown fusokine exhibit gain-of-function immunomodulating activity. Individually, IL-6 and IL-1{beta} are recognized for their roles in promoting T-cell proliferation and effector function. However, the potential for a fused IL-6/1 fusokine to reprogram the immune system and elicit a superior anti-tumor response in vivo in ovarian cancer model is not yet studied. C_LI What this study addsO_LIThis study develops a novel fusion cytokine (fusokine), combining IL-6 and IL-1{beta}, and demonstrate robust activation of T cells. In a preclinical ovarian cancer model, engineered cancer cells expressing IL6/1 used as a therapeutic vaccine showed significant tumor reduction and improved overall survival. C_LI How this study might affect research, practice or policyO_LIThis study demonstrates that in comparison to individual cytokines, fusokines have greater potential to activate T cell function and when delivered as a cell therapy, achieve clear therapeutic efficacy in an ovarian cancer model. Further translational and clinical studies may enable the development of novel and more effective fusokine cell therapy approaches for patients with ovarian cancer. C_LI

Scaling up microvessel culture systems is essential for producing vascularized clinically relevant tissues, yet current platforms offer little guidance on how to preserve flow conditions during scale-up. Here, we present a computational-experimental framework using computational fluid dynamics (CFD) to guide the design and scaling of microvessel bioreactors. Interstitial flow distributions were pre-dicted in two perfusion-based platforms-a permeable insert and a rhomboidal microfluidic chamber-across multiple scaling factors and hydrostatic pressures. CFD identified IF ranges conducive to vascu-logenesis and quantified how geometry and pressure modulate flow uniformity. Scaled-up bioreactors generated microvessel networks with consistent morphology and connectivity over a 30-fold increase in culture volume, confirming that maintaining equivalent IF ensures reproducible outcomes. The permeable insert platform maintained uniform IF across scales, while the rhomboidal chamber produced spatially varying IF resulting in heterogeneous but physiologically relevant networks. These findings establish CFD as a predictive tool for rationally scaling perfusion bioreactors, enabling microvessel production at clinically relevant scales with controllable morphology. Significance StatementScaling up microvessel bioreactors is critical for engineering large pre-vascularized tissues. However, larger scales may disrupt flow conditions that drive vessel formation. This study demonstrates that computational fluid dynamics (CFD) can predict interstitial flow and guide the rational scale-up while preserving the vasculogenic microenvironment. Experiments across 30+-fold size increase confirmed that matching inter-stitial flow results in morphologically identical microvessel networks. By linking simulation-based design with experimental validation, this work establishes CFD as design tool for scalable perfusion bioreactors for production of microvessel networks at clinically relevant scales.