New Ref-1/APE1 targeted inhibitors demonstrating improved potency for clinical applications in multiple cancer types.

AP endonuclease-1/Redox factor-1 (APE1/Ref-1 or Ref-1) is a multifunctional protein that is overexpressed in most aggressive cancers and impacts various cancer cell signaling pathways. Ref-1's redox activity plays a significant role in activating transcription factors (TFs) such as NFκB, HIF1α, STAT3 and AP-1, which are crucial contributors to the development of tumors and metastatic growth. Therefore, development of potent, selective inhibitors to target Ref-1 redox function is an appealing approach for therapeutic intervention. A first-generation compound, APX3330 successfully completed phase I clinical trial in adults with progressing solid tumors with favorable response rate, pharmacokinetics (PK), and minimal toxicity. These positive results prompted us to develop more potent analogs of APX3330 to effectively target Ref-1 in solid tumors. In this study, we present structure-activity relationship (SAR) identification and validation of lead compounds that exhibit a greater potency and a similar or better safety profile to APX3330. In order to triage and characterize the most potent and on-target second-generation Ref-1 redox inhibitors, we assayed for PK, mouse and human S9 fraction metabolic stability, in silico ADMET properties, ligand-based WaterLOGSY NMR measurements, pharmacodynamic markers, cell viability in multiple cancer cell types, and two distinct 3-dimensional (3D) cell killing assays (Tumor-Microenvironment on a Chip and 3D spheroid). To characterize the effects of Ref-1 inhibition in vivo, global proteomics was used following treatment with the top four analogs. This study identified and characterized more potent inhibitors of Ref-1 redox function (that outperformed APX3330 by 5-10-fold) with PK studies demonstrating efficacious doses for translation to clinic.

Tumor-Microenvironment-on-Chip Platform for Assessing Drug Response in 3D Dynamic Culture.

Microphysiological systems involving microfluidic 3D culture of cancer cells have emerged as a versatile toolkit to study tumor biological problems and evaluate potential treatment strategies. Incorporation of microfluidic technologies in 3D tissue culture offers opportunities for realistic simulation of tumor microenvironment in vitro by facilitating a dynamic culture environment mimicking features of human physiology such as reconstituted ECM, interstitial flow, and gradients of drugs and biomacromolecules. This protocol describes development of 3D microfluidic cell culture based on Tumor-Microenvironment-on-Chip (T-MOC) platform modeling tumor blood and lymphatic capillary vessels and the interstitial space in between. Based on earlier applications of T-MOC for transport characteristics, drug response, and tumor-stroma interactions in mammary carcinoma and pancreatic adenocarcinoma, this protocol provides detailed description of device fabrication, on-chip 3D culture, and drug treatment assays. This protocol can easily be adapted for applications involving other cancer types.

A Systems Approach to Biomechanics, Mechanobiology, and Biotransport.

The human body represents a collection of interacting systems that range in scale from nanometers to meters. Investigations from a systems perspective focus on how the parts work together to enact changes across spatial scales, and further our understanding of how systems function and fail. Here, we highlight systems approaches presented at the 2022 Summer Biomechanics, Bio-engineering, and Biotransport Conference in the areas of solid mechanics; fluid mechanics; tissue and cellular engineering; biotransport; and design, dynamics, and rehabilitation; and biomechanics education. Systems approaches are yielding new insights into human biology by leveraging state-of-the-art tools, which could ultimately lead to more informed design of therapies and medical devices for preventing and treating disease as well as rehabilitating patients using strategies that are uniquely optimized for each patient. Educational approaches can also be designed to foster a foundation of systems-level thinking.

Advanced manufacturing of nanoparticle formulations of drugs and biologics using microfluidics.

Numerous innovative nanoparticle formulations of drugs and biologics, named nano-formulations, have been developed in the last two decades. However, methods for their scaled-up production are still lagging, as the amount needed for large animal tests and clinical trials is typically orders of magnitude larger. This manufacturing challenge poses a critical barrier to successfully translating various nano-formulations. This review focuses on how microfluidics technology has become a powerful tool to overcome this challenge by synthesizing various nano-formulations with improved particle properties and product purity in large quantities. This microfluidic-based manufacturing is enabled by microfluidic mixing, which is capable of the precise and continuous control of the synthesis of nano-formulations. We further discuss the specific applications of hydrodynamic flow focusing, a staggered herringbone micromixer, a T-junction mixer, a micro-droplet generator, and a glass capillary on various types of nano-formulations of polymeric, lipid, inorganic, and nanocrystals. Various separation and purification microfluidic methods to enhance the product purity are reviewed, including acoustofluidics, hydrodynamics, and dielectrophoresis. We further discuss the challenges of microfluidics being used by broader research and industrial communities. We also provide future outlooks of its enormous potential as a decentralized approach for manufacturing nano-formulations.

Inkjet-printed morphogenesis of tumor-stroma interface using bi-cellular bioinks of collagen-poly(N-isopropyl acrylamide-co-methyl methacrylate) mixture.

Recent advances in biomaterials and 3D printing/culture methods enable various tissue-engineered tumor models. However, it is still challenging to achieve native tumor-like characteristics due to lower cell density than native tissues and prolonged culture duration for maturation. Here, we report a new method to create tumoroids with a mechanically active tumor-stroma interface at extremely high cell density. This method, named "inkjet-printed morphogenesis" (iPM) of the tumor-stroma interface, is based on a hypothesis that cellular contractile force can significantly remodel the cell-laden polymer matrix to form densely-packed tissue-like constructs. Thus, differential cell-derived compaction of tumor cells and cancer-associated fibroblasts (CAFs) can be used to build a mechanically active tumor-stroma interface. In this methods, two kinds of bioinks are prepared, in which tumor cells and CAFs are suspended respectively in the mixture of collagen and poly (N-isopropyl acrylamide-co-methyl methacrylate) solution. These two cellular inks are inkjet-printed in multi-line or multi-layer patterns. As a result of cell-derived compaction, the resulting structure forms tumoroids with mechanically active tumor-stroma interface at extremely high cell density. We further test our working hypothesis that the morphogenesis can be controlled by manipulating the force balance between cellular contractile force and matrix stiffness. Furthermore, this new concept of "morphogenetic printing" is demonstrated to create more complex structures beyond current 3D bioprinting techniques.

Experimental and computational analysis of the injection-induced mechanical changes in the skin microenvironment during subcutaneous injection of biologics.

Subcutaneous (SQ) injection is an effective delivery route for various biologics, including proteins, antibodies, and vaccines. However, pain and discomfort induced during SQ injection pose a notable challenge for the broader and routine use of biologics. Understanding the underlying mechanism and quantification of injection-induced pain and discomfort (IPD) are urgently needed. A crucial knowledge gap is what changes in the skin tissue microenvironment are induced by the SQ injection, which may ultimately cause the IPD. In this study, thus, a hypothesis is postulated that the injection of biologics solution through the skin tissue microenvironment induces spatiotemporal mechanical changes. Specifically, the injection leads to tissue swelling and subsequent increases in the interstitial fluid pressure (IFP) and matrix stress around the injection site, which ultimately causes the IPD. To test this hypothesis, an engineered SQ injection model is developed capable of measuring tissue swelling during SQ injection. The injection model consists of a skin equivalent with quantum dot-labeled fibroblasts, which enables the measurement of injection-induced spatiotemporal deformation. The IFP and matrix stress are further estimated by computational analysis approximating the skin equivalent as a nonlinear poroelastic material. The result confirms significant injection-induced tissue swelling and increases in IFP and matrix stress. The extent of deformation is correlated to the injection rate. The results also suggest that the size of biologics particulates significantly affects the pattern and extent of the deformation. The results are further discussed to propose a quantitative understanding of the injection-induced changes in the skin microenvironment.

Optically induced electrothermal microfluidic tweezers in bio-relevant media.

Non-contact micro-manipulation tools have enabled invasion-free studies of fragile synthetic particles and biological cells. Rapid electrokinetic patterning (REP) traps target particles/cells, suspended in an electrolyte, on an electrode surface. This entrapment is electrokinetic in nature and thus depends strongly on the suspension medium's properties. REP has been well characterized for manipulating synthetic particles suspended in low concentration salt solutions (~ 2 mS/m). However, it is not studied as extensively for manipulating biological cells, which introduces an additional level of complexity due to their limited viability in hypotonic media. In this work, we discuss challenges posed by isotonic electrolytes and suggest solutions to enable REP manipulation in bio-relevant media. Various formulations of isotonic media (salt and sugar-based) are tested for their compatibility with REP. REP manipulation is observed in low concentration salt-based media such as 0.1× phosphate buffered saline (PBS) when the device electrodes are passivated with a dielectric layer. We also show manipulation of murine pancreatic cancer cells suspended in a sugar-based (8.5% w/v sucrose and 0.3% w/v dextrose) isotonic medium. The ability to trap mammalian cells and deposit them in custom patterns enables high-impact applications such as determining their biomechanical properties and 3D bioprinting for tissue scaffolding.

A timescale-guided microfluidic synthesis of tannic acid-FeIII network nanocapsules of hydrophobic drugs.

Many drugs are poorly water-soluble and suffer from low bioavailability. Metal-phenolic network (MPN), a hydrophilic thin layer such as tannic acid (TA)-FeIII network, has been recently used to encapsulate hydrophobic drugs to improve their bioavailability. However, it remains challenging to synthesize nanocapsules of a wide variety of hydrophobic drugs and to scale up the production in a continuous manner. Here, we present a microfluidic synthesis method to continuously produce TA-FeIII network nanocapsules of hydrophobic drugs. We hypothesize that nanocapsules can continuously be formed only when the microfluidic mixing timescale is shorter than the drug's nucleation timescale. The hypothesis was tested on three hydrophobic drugs - paclitaxel, curcumin, and vitamin D with varying solubility and nucleation timescale. The proposed mechanism was validated by successfully predicting the synthesis outcomes. The microfluidically-synthesized nanocapsules had well-controlled sizes of 100-200 nm, high drug loadings of 40-70%, and a throughput of up to 70 mg hr-1 per channel. The release kinetics, cellular uptake, and cytotoxicity were further evaluated. The effect of coating constituents on nanocapsule properties were characterized. Fe content of nanocapsules was reported. The stability of nanocapsules at different temperatures and pHs were also tested. The results suggest that the present method can provide a quantitative guideline to predictively design a continuous synthesis scheme for hydrophobic drug encapsulation via MPN nanocapsules with scaled-up capability.

Predictive Design and Analysis of Drug Transport by Multiscale Computational Models Under Uncertainty.

Computational modeling of drug delivery is becoming an indispensable tool for advancing drug development pipeline, particularly in nanomedicine where a rational design strategy is ultimately sought. While numerous in silico models have been developed that can accurately describe nanoparticle interactions with the bioenvironment within prescribed length and time scales, predictive design of these drug carriers, dosages and treatment schemes will require advanced models that can simulate transport processes across multiple length and time scales from genomic to population levels. In order to address this problem, multiscale modeling efforts that integrate existing discrete and continuum modeling strategies have recently emerged. These multiscale approaches provide a promising direction for bottom-up in silico pipelines of drug design for delivery. However, there are remaining challenges in terms of model parametrization and validation in the presence of variability, introduced by multiple levels of heterogeneities in disease state. Parametrization based on physiologically relevant in vitro data from microphysiological systems as well as widespread adoption of uncertainty quantification and sensitivity analysis will help address these challenges.

Cells function as a ternary logic gate to decide migration direction under integrated chemical and fluidic cues.

Cells sense various environmental cues and subsequently process intracellular signals to decide their migration direction in many physiological and pathological processes. Although several signaling molecules and networks have been identified in these directed migrations, it still remains ambiguous to predict the migration direction under multiple and integrated cues, specifically chemical and fluidic cues. Here, we investigated the cellular signal processing machinery by reverse-engineering directed cell migration under integrated chemical and fluidic cues. We imposed controlled chemical and fluidic cues to cells using a microfluidic platform and analyzed the extracellular coupling of the cues with respect to the cellular detection limit. Then, the cell's migratory behavior was reverse-engineered to build a cellular signal processing system as a logic gate, which is based on a "selection" gate. This framework is further discussed with a minimal intracellular signaling network of a shared pathway model. The proposed framework of the ternary logic gate suggests a systematic view to understand how cells decode multiple cues and make decisions about the migration direction.

Microphysiological systems as reliable drug discovery and evaluation tools: Evolution from innovation to maturity.

Microphysiological systems (MPSs), also known as organ-on-chip or disease-on-chip, have recently emerged to reconstitute the in vivo cellular microenvironment of various organs and diseases on in vitro platforms. These microfluidics-based platforms are developed to provide reliable drug discovery and regulatory evaluation testbeds. Despite recent emergences and advances of various MPS platforms, their adoption of drug discovery and evaluation processes still lags. This delay is mainly due to a lack of rigorous standards with reproducibility and reliability, and practical difficulties to be adopted in pharmaceutical research and industry settings. This review discusses the current and potential use of MPS platforms in drug discovery processes while considering the context of several key steps during drug discovery processes, including target identification and validation, preclinical evaluation, and clinical trials. Opportunities and challenges are also discussed for the broader dissemination and adoption of MPSs in various drug discovery and regulatory evaluation steps. Addressing these challenges will transform long and expensive drug discovery and evaluation processes into more efficient discovery, screening, and approval of innovative drugs.

Deduction of signaling mechanisms from cellular responses to multiple cues.

Cell signaling networks are complex and often incompletely characterized, making it difficult to obtain a comprehensive picture of the mechanisms they encode. Mathematical modeling of these networks provides important clues, but the models themselves are often complex, and it is not always clear how to extract falsifiable predictions. Here we take an inverse approach, using experimental data at the cell level to deduce the minimal signaling network. We focus on cells' response to multiple cues, specifically on the surprising case in which the response is antagonistic: the response to multiple cues is weaker than the response to the individual cues. We systematically build candidate signaling networks one node at a time, using the ubiquitous ingredients of (i) up- or down-regulation, (ii) molecular conversion, or (iii) reversible binding. In each case, our method reveals a minimal, interpretable signaling mechanism that explains the antagonistic response. Our work provides a systematic way to deduce molecular mechanisms from cell-level data.

A scaling law of particle transport in inkjet-printed particle-laden polymeric drops.

Hydrogels with embedded functional particulates are widely used to create soft materials with innovative functionalities. In order to advance these soft materials to functional devices and machines, critical technical challenges are the precise positioning of particulates within the hydrogels and the construction of the hydrogels into a complex geometry. Inkjet printing is a promising method for addressing these challenges and ultimately achieving hydrogels with voxelized functionalities, so-called digital hydrogels. However, the development of the inkjet printing process primarily relies on empirical optimization of its printing and curing protocol. In this study, a general scaling law is proposed to predict the transport of particulates within the hydrogel during inkjet printing. This scaling law is based on a hypothesis that water-matrix interaction during the curing of inkjet-printed particle-laden polymeric drops determines the intra-drop particle distribution. Based on the hypothesis, a dimensionless similarity parameter of the water-matrix interaction is proposed, determined by the hydrogel's water evaporation coefficient, particle size, and mechanical properties. The hypothesis was tested by correlating the intra-drop particle distribution to the similarity parameter. The results confirmed the scaling law capable of guiding ink formulation and printing and curing protocol.

Signal processing capacity of the cellular sensory machinery regulates the accuracy of chemotaxis under complex cues.

Chemotaxis is ubiquitous in many biological processes, but it still remains elusive how cells sense and decipher multiple chemical cues. In this study, we postulate a hypothesis that the chemotactic performance of cells under complex cues is regulated by the signal processing capacity of the cellular sensory machinery. The underlying rationale is that cells in vivo should be able to sense and process multiple chemical cues, whose magnitude and compositions are entangled, to determine their migration direction. We experimentally show that the combination of transforming growth factor-ß and epidermal growth factor suppresses the chemotactic performance of cancer cells using independent receptors to sense the two cues. Based on this observation, we develop a biophysical framework suggesting that the antagonism is caused by the saturation of the signal processing capacity but not by the mutual repression. Our framework suggests the significance of the signal processing capacity in the cellular sensory machinery.

Engineering of a functional pancreatic acinus with reprogrammed cancer cells by induced PTF1a expression.

A pancreatic acinus is a functional unit of the exocrine pancreas producing digest enzymes. Its pathobiology is crucial to pancreatic diseases including pancreatitis and pancreatic cancer, which can initiate from pancreatic acini. However, research on pancreatic acini has been significantly hampered due to the difficulty of culturing normal acinar cells in vitro. In this study, an in vitro model of the normal acinus, named pancreatic acinus-on-chip (PAC), is developed using reprogrammed pancreatic cancer cells. The developed model is a microfluidic platform with an epithelial duct and acinar sac geometry microfabricated by a newly developed two-step controlled "viscous-fingering" technique. In this model, human pancreatic cancer cells, Panc-1, reprogrammed to revert to the normal state upon induction of PTF1a gene expression, are cultured. Bioinformatic analyses suggest that, upon induced PTF1a expression, Panc-1 cells transition into a more normal and differentiated acinar phenotype. The microanatomy and exocrine functions of the model are characterized to confirm the normal acinus phenotypes. The developed model provides a new and reliable testbed to study the initiation and progression of pancreatic cancers.

Ref-1 redox activity alters cancer cell metabolism in pancreatic cancer: exploiting this novel finding as a potential target.

BACKGROUND: Pancreatic cancer is a complex disease with a desmoplastic stroma, extreme hypoxia, and inherent resistance to therapy. Understanding the signaling and adaptive response of such an aggressive cancer is key to making advances in therapeutic efficacy. Redox factor-1 (Ref-1), a redox signaling protein, regulates the conversion of several transcription factors (TFs), including HIF-1α, STAT3 and NFκB from an oxidized to reduced state leading to enhancement of their DNA binding. In our previously published work, knockdown of Ref-1 under normoxia resulted in altered gene expression patterns on pathways including EIF2, protein kinase A, and mTOR. In this study, single cell RNA sequencing (scRNA-seq) and proteomics were used to explore the effects of Ref-1 on metabolic pathways under hypoxia. METHODS: scRNA-seq comparing pancreatic cancer cells expressing less than 20% of the Ref-1 protein was analyzed using left truncated mixture Gaussian model and validated using proteomics and qRT-PCR. The identified Ref-1's role in mitochondrial function was confirmed using mitochondrial function assays, qRT-PCR, western blotting and NADP assay. Further, the effect of Ref-1 redox function inhibition against pancreatic cancer metabolism was assayed using 3D co-culture in vitro and xenograft studies in vivo. RESULTS: Distinct transcriptional variation in central metabolism, cell cycle, apoptosis, immune response, and genes downstream of a series of signaling pathways and transcriptional regulatory factors were identified in Ref-1 knockdown vs Scrambled control from the scRNA-seq data. Mitochondrial DEG subsets downregulated with Ref-1 knockdown were significantly reduced following Ref-1 redox inhibition and more dramatically in combination with Devimistat in vitro. Mitochondrial function assays demonstrated that Ref-1 knockdown and Ref-1 redox signaling inhibition decreased utilization of TCA cycle substrates and slowed the growth of pancreatic cancer co-culture spheroids. In Ref-1 knockdown cells, a higher flux rate of NADP + consuming reactions was observed suggesting the less availability of NADP + and a higher level of oxidative stress in these cells. In vivo xenograft studies demonstrated that tumor reduction was potent with Ref-1 redox inhibitor similar to Devimistat. CONCLUSION: Ref-1 redox signaling inhibition conclusively alters cancer cell metabolism by causing TCA cycle dysfunction while also reducing the pancreatic tumor growth in vitro as well as in vivo.

An engineered pancreatic cancer model with intra-tumoral heterogeneity of driver mutations.

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease with significant intra-tumoral heterogeneity (ITH). Currently, no reliable PDAC tumor model is available that can present ITH profiles in a controlled manner. We develop an in vitro microfluidic tumor model mimicking the heterogeneous accumulation of key driver mutations of human PDAC using cancer cells derived from genetically engineered mouse models. These murine pancreatic cancer cell lines have KPC (Kras and Trp53 mutations) and KIC genotypes (Kras mutation and Cdkn2a deletion). Also, the KIC genotypes have two distinct phenotypes - mesenchymal or epithelial. The tumor model mimics the ITH of human PDAC to study the effects of ITH on the gemcitabine response. The results show gemcitabine resistance induced by ITH. Remarkably, it shows that cancer cell-cell interactions induce the gemcitabine resistance potentially through epithelial-mesenchymal-transition. The tumor model can provide a useful testbed to study interaction mechanisms between heterogeneous cancer cell subpopulations.

Subtype-specific characterization of breast cancer invasion using a microfluidic tumor platform.

Understanding progression of breast cancers to invasive ductal carcinoma (IDC) can significantly improve breast cancer treatments. However, it is still difficult to identify genetic signatures and the role of tumor microenvironment to distinguish pathological stages of pre-invasive lesion and IDC. Presence of multiple subtypes of breast cancers makes the assessment more challenging. In this study, an in-vitro microfluidic assay was developed to quantitatively assess the subtype-specific invasion potential of breast cancers. The developed assay is a microfluidic platform in which a ductal structure of epithelial cancer cells is surrounded with a three-dimensional (3D) collagen matrix. In the developed platform, two triple negative cancer subtypes (MDA-MB-231 and SUM-159PT) invaded into the surrounding matrix but the luminal A subtype, MCF-7, did not. Among invasive subtypes, SUM-159PT cells showed significantly higher invasion and degradation of the surrounding matrix than MDA-MB-231. Interestingly, the cells cultured on the platform expressed higher levels of CD24 than in their conventional 2D cultures. This microfluidic platform may be a useful tool to characterize and predict invasive potential of breast cancer subtypes or patient-derived cells.

A Biomimetic Tumor Model of Heterogeneous Invasion in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a complex, heterogeneous, and genetically unstable disease. Its tumor microenvironment (TME) is complicated by heterogeneous cancer cell populations and strong desmoplastic stroma. This complex and heterogeneous environment makes it challenging to discover and validate unique therapeutic targets. Reliable and relevant in vitro PDAC tumor models can significantly advance the understanding of the PDAC TME and may enable the discovery and validation of novel drug targets. In this study, an engineered tumor model is developed to mimic the PDAC TME. This biomimetic model, named ductal tumor-microenvironment-on-chip (dT-MOC), permits analysis and experimentation on the epithelial-mesenchymal transition (EMT) and local invasion with intratumoral heterogeneity. This dT-MOC is a microfluidic platform where a duct of murine genetically engineered pancreatic cancer cells is embedded within a collagen matrix. The cancer cells used carry two of the three mutations of KRAS, CDKN2A, and TP53, which are key driver mutations of human PDAC. The intratumoral heterogeneity is mimicked by co-culturing these cancer cells. Using the dT-MOC model, heterogeneous invasion characteristics, and response to transforming growth factor-beta1 are studied. A mechanism of EMT and local invasion caused by the interaction between heterogeneous cancer cell populations is proposed.

Engineering of biomaterials for tumor modeling.

Development of biomaterials mimicking tumor and its microenvironment has recently emerged for the use of drug discovery, precision medicine, and cancer biology. These biomimetic models have developed by reconstituting tumor and stroma cells within the 3D extracellular matrix. The models are recently extended to recapitulate the in vivo tumor microenvironment, including biological, chemical, and mechanical conditions tailored for specific cancer type and its microenvironment. In spite of the recent emergence of various innovative engineered tumor models, many of these models are still early stage to be adapted for cancer research. In this article, we review the current status of biomaterials engineering for tumor models considering three main aspects - cellular engineering, matrix engineering, and engineering for microenvironmental conditions. Considering cancer-specific variability in these aspects, our discussion is focused on pancreatic cancer, specifically pancreatic ductal adenocarcinoma (PDAC). In addition, we further discussed the current challenges and future opportunities to create reliable and relevant tumor models.