Evaluation Of Drug Efficacy Research Articles

Hyperspectral analysis to assess gametocytogenesis stage progression in malaria-infected human erythrocytes.

Developments of anti-gametocyte drugs have been delayed due to insufficient understanding of gametocyte biology. We report a systematic workflow of data processing algorithms to quantify changes in the absorption spectrum and cell morphology of single malaria-infected erythrocytes. These changes may serve as biomarkers instrumental for the future development of antimalarial strategies, especially for anti-gametocyte drug design and testing. Image-based biomarkers may also be useful for nondestructive, label-free malaria detection and drug efficacy evaluation in resource-limited communities. We extend the application of hyperspectral microscopy to provide detailed insights into gametocyte stage progression through the quantitative analysis of absorbance spectra and cell morphology in malaria-infected erythrocytes. Malaria-infected erythrocytes at asexual and different gametocytogenesis stages were imaged through hyperspectral confocal microscopy. The preprocessing of the hyperspectral data cubes to transform them to color images and spectral angle mapper (SAM) analysis were first used to segment hemoglobin (Hb)- and hemozoin (Hz)-abundant areas within the host erythrocytes. Correlations between changes in cell morphology and increasing Hz-abundant areas of the infected erythrocytes were then examined to test their potential as optical biomarkers to determine the progression of infection, involving transitions from asexual to various gametocytogenesis stages. Following successful segmentation of Hb- and Hz-abundant areas in malaria-infected erythrocytes through SAM analysis, a modest correlation between the segmented Hz-abundant area and cell shape changes over time was observed. A significant increase in both the areal fraction of Hz and the ellipticity of the cell confirms that the Hz fraction change correlates with the progression of gametocytogenesis. Our workflow enables the quantification of changes in host cell morphology and the relative contents of Hb and Hz at various parasite growth stages. The quantified results exhibit a trend that both the segmented areal fraction of intracellular Hz and the ellipticity of the host cell increase as gametocytogenesis progresses, suggesting that these two metrics may serve as useful biomarkers to determine the stage of gametocytogenesis.

Animal models of cisplatin-induced neuropathic pain.

Cisplatin chemotherapy has been used as the main treatment for different types of cancer. However, cisplatin chemotherapy-induced peripheral neuropathic pain (CIPNP) seriously affects the treatment process and quality of life of patients. In addition, it impacts the underlying mechanism and prevention and treatment strategies, indicating that drug selection and efficacy evaluation need to be further investigated. Furthermore, an animal model that is more consistent with the pathological mechanism needs to be developed. In this study, we describe and discuss the methods of developing and detecting CIPNP models in rats and mice induced by cisplatin chemotherapy. The aim was to improve the modeling rate and develop animal models that are more consistent with the developmental pattern of the disease. In addition, the study provides ideal reference animal models for clinical research and drug discovery and development.

Utilizing Tissues Self-Assembled in Fiber Optic-Based "Chinese Guzheng Strings" for Contractility Sensing and Drug Efficacy Evaluation: A Practical Approach.

Recent advances in drug design and compound synthesis have highlighted the increasing need for effective methods of toxicity evaluation. A specialized force sensor, known as the light wavelength-encoded "Chinese guzheng" is developed. This innovative sensor is equipped with optical fiber strings and utilizes a wavelength-encoded fiber Bragg grating (FBG) that is chemically etched to reduce its diameter. This design allows the sensor to detect minimal forces as low as l µN. This sensor is successfully applied to monitor human-induced pluripotent stem cell-derived human-engineered heart tissue (hEHT) models that can self-assemble and contact optical fiber-based strings. The sensor detects micro newton contraction forces in real-time by measuring the wavelength drift resulting from hEHT contractions. In addition, the sensor is precise and durable, exhibiting a fatigue resistance of up to 800000 cycles, making it suitable for long-term monitoring. The device effectively measured the contractile force of the hEHTs under various physiological conditions, including natural contraction, electrical stimulation, and stretching. Moreover, multichannel detection enables the study and demonstration of short- and long-term effectiveness of multiple drugs. This breakthrough sensor addresses the critical need for high-precision real-time monitoring in drug evaluation and provides a solid foundation for screening drugs to treat cardiomyopathy.

Organ-on-a-chip: Quo vademus? Applications and regulatory status.

Organ-on-a-chip systems, also referred to as microphysiological systems (MPS), represent an advance in bioengineering microsystems designed to mimic key aspects of human organ physiology and function. Drawing inspiration from the intricate and hierarchical architecture of the human body, these innovative platforms have emerged as invaluable in vitro tools with wide-ranging applications in drug discovery and development, as well as in enhancing our understanding of disease physiology. The facility to replicate human tissues within physiologically relevant three-dimensional multicellular environments empowers organ-on-a-chip systems with versatility throughout different stages of the drug development process. Moreover, these systems can be tailored to mimic specific disease states, facilitating the investigation of disease progression, drug responses, and potential therapeutic interventions. In particular, they can demonstrate, in early-phase pre-clinical studies, the safety and toxicity profiles of potential therapeutic compounds. Furthermore, they play a pivotal role in the in vitro evaluation of drug efficacy and the modeling of human diseases. One of the most promising prospects of organ-on-a-chip technology is to simulate the pathophysiology of specific subpopulations and even individual patients, thereby being used in personalized medicine. By mimicking the physiological responses of diverse patient groups, these systems hold the promise of revolutionizing therapeutic strategies, guiding them towards tailored intervention to the unique needs of each patient. This review presents the development status and evolution of microfluidic platforms that have facilitated the transition from cells to organs recreated on chips and some of the opportunities and applications offered by organ-on-a-chip technology. Additionally, the current potential and future perspectives of these microphysiological systems and the challenges this technology still faces are discussed.

GENI as an AMPK Activator Binds α and γ Subunits and Improves the Memory Dysfunction of Alzheimer's Disease Mouse Models via Autophagy and Neuroprotection.

Geniposidic 4-isoamyl ester (GENI) with anti-aging effects is a new iridoid glycoside derivative from Gardenia jasminoides Ellis found in our previous study. In this study, to indicate whether this compound has anti-Alzheimer's disease (AD) effect, the galactose-induced AD mice and naturally aging mice with AD were used to do drug efficacy evaluation. Furthermore, the Western blot, small interfering RNA (siRNA), drug affinity responsive target stability (DARTS), cellular thermal shift assay (CESTA), liquid chromatography-tandem mass spectrometry (LC/MS-MS), adenosine 5'-monophosphate-activated protein kinase (AMPK) mutants and surface plasmon resonance (SPR) analysis were utilized to clarify the mechanism of action and identify target protein of this molecule. GENI exerts anti-AD efficacy in galactose-induced AD mice and naturally aging mice with AD through neuroprotection and modification of autophagy and neuron inflammation. Moreover, AMPK as the target protein of GENI to produce an anti-AD effect is identified and the ASP148, ASP157, and ASP166 of the AMPK α subunit and lysine (LYS)148, aspartic acid (ASP)156, LYS309, and ASP316 in the AMPK γ subunit as binding sites are confirmed. Meanwhile, the AMPK/unc-51-like autophagy-activating kinase 1 (ULK1)/microtubule-associated protein 1 light chain 3 beta (LC3B) and AMPK/mammalian target of rapamycin (mTOR) signaling pathways involved in anti-AD effects of GENI. The findings provide a new perspective on treating neurodegenerative diseases by activating AMPK for the energy metabolism disorder.

Development of a diagnostic and drug evaluation system for acute inflammation using a novel [89Zr]DTPA-sorbitol probe.

Non-invasive imaging techniques employing biomarkers with high selectivity for inflammation are essential not only for the early diagnosis and prevention of chronic inflammatory diseases but also for guiding appropriate drug therapy and enabling real-time evaluation of anti-inflammatory drug efficacy. In this study, we conjugated radioactive zirconium to sorbitol, a compound that can selectively target inflammation, and evaluated its inflammation-specific uptake and potential for assessing anti-inflammatory treatment efficacy in a mouse inflammation model. Pharmacokinetic analysis demonstrated that radiolabeled sorbitol achieved maximal uptake in inflamed tissues within 1 h. Positron emission tomography imaging further confirmed its utility in monitoring therapeutic effects during anti-inflammatory drug treatment. Our findings suggest that [89Zr]DTPA-sorbitol is a promising radioprobe for targeting rapid systemic inflammation, particularly in tissues demonstrating minimal non-specific uptake, such as the brain, heart, and lung tissues. Additionally, it holds significant potential for the in vivo evaluation of anti-inflammatory drug efficacy.

Safety and efficacy assessments using human iPS cell-derived cardiomyocytes

The delay and loss of drugs are serious problems in Japan. To overcome this issue, it is important to strengthen drug development capabilities. For drug development, the establishment and advancement of non-clinical testing methods are necessary for safe and effective clinical trials. Recently, the movement toward alternatives to animal testing has accelerated internationally. New Approach Methodologies (NAMs), such as human inducible pluripotent stem cell (hiPSC) technology and in silico modeling & simulation, are considered valuable for drug development. It has been demonstrated that hiPSC-derived cardiomyocytes (hiPSC-CMs) are useful tools to assess drug-induced cardiotoxicity, including arrhythmia and cardiac contractile dysfunction, leading to the use of hiPSC-CMs in the drug review process. Advancing hiPSC technologies have enabled the generation of mature hiPSC-CMs and engineered heart tissues, which are expected to provide novel information in drug safety and efficacy evaluation. Furthermore, it would be possible to establish the non-clinical evaluation that takes into account individual differences by developing hiPSCs bearing characteristics specific to certain populations, such as pediatrics or rare disease patients. Here, we present the recent findings and future perspectives on non-clinical evaluation using hiPSC technology.

Priors and decision thresholds in phase 2 and phase 3 randomized controlled trials evaluating drug efficacy using Bayesian methods: a systematic review.

To describe the priors and decision thresholds in phase 2 and 3 RCTs evaluating drug efficacy using Bayesian methods. A systematic review of phase 2 and 3 RCTs evaluating drug efficacy through Bayesian inference was conducted across the MEDLINE, EMBASE and Cochrane databases, with no date restrictions until September 2022. The type of prior used for the analysis of the primary endpoint and its characteristics (type and parameters of the distribution, justification, sensitivity analysis), the use of a posterior probability decision threshold defined a priori, and its value, were extracted. From 1161 articles screened, 69 articles were ultimately included, encompassing a total of 91 comparisons, as some trials assessed multiple primary endpoints or treatments. The prior was assigned to treatment effect in 51% of cases (n=46), to each arm in 37% (n=34), and was not explicitly defined in 12% (n=11). Prior distribution was described (with its parameters) in 59% of cases (n=54). A decision threshold was set a priori in 68% of results (n=62), and its value ranged from 70% to 99% (median 95%). The inconsistent description of priors, along with the wide variation and occasional absence of decision thresholds, underscore the need for clear guidelines on the use and reporting of Bayesian methods.

Efficient in vitro assay for evaluating drug efficacy and synergy against emerging SARS-CoV-2 strains.

Novel and repurposed antiviral drugs are available for the treatment of coronavirus disease 2019 (COVID-19). However, antiviral combinations may be more potent and lead to faster viral clearance, but the methods for screening antiviral combinations against respiratory viruses are not well established and labor-intensive. Here, we describe a time-efficient (72-96 h) and simple in vitro drug-sensitivity assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using standard 96-well plates. We employ different synergy models (zero interaction potency, highest single agent, Loewe, Bliss) to determine the efficacy of antiviral therapies and synergistic combinations against ancestral and emerging clinical SARS-CoV-2 strains. We found that monotherapy of remdesivir, nirmatrelvir, and active metabolite of molnupiravir (EIDD-1931) demonstrated baseline EC50s within clinically achievable levels of 4.34 mg/L (CI: 3.74-4.94 mg/L), 1.25 mg/L (CI: 1.10-1.45 mg/L), and 0.25 mg/L (CI: 0.20-0.30 mg/L), respectively, against the ancestral SARS-CoV-2 strain. However, their efficacy varied against newer Omicron variants BA.1.1.15 and BA.2, particularly with the protease inhibitor nirmatrelvir. We also found that remdesivir and nirmatrelvir have a consistent, strong synergistic effect (Bliss synergy score >10) at clinically relevant drug concentrations (nirmatrelvir 0.25-1 mg/L with remdesivir 1-4 mg/L) across all SARS-CoV-2 strains tested. This method offers a practical tool that streamlines the identification of effective combination therapies and the detection of antiviral resistance. Our findings support the use of antiviral drug combinations targeting multiple viral components to enhance COVID-19 treatment efficacy, particularly in the context of emerging viral strains.

Integrating Metabolomics, Histopathology, and Cardiac Marker Analysis to Assess Valsartan's Efficacy in Mitigating Dasatinib-Induced Cardiac Toxicity in Sprague-Dawley Rats.

Dasatinib (DASA) is associated with cardiotoxic effects, posing risks to patients. Valsartan (VAL) may offer protective benefits against these effects. This study evaluates the impact of DASA, VAL, and their combination on cardiac health. Wistar rats were treated with DASA, VAL, and a combination of VAL and DASA intraperitoneally every other day for 14 days. Body weight and survival rates were monitored. Serum levels of cardiac biomarkers (CPK, LDH, AST) were analyzed. Histopathological and immunohistochemical analyses assessed myocardial architecture and apoptosis-related protein expression. Metabolomic profiling was conducted using GC-MS to identify metabolic changes across treatment groups. The DASA group experienced significant weight loss and a 50% mortality rate, while the combination group had no mortality. Cardiac biomarkers like CPK, LDH, and AST were elevated in the DASA group but significantly reduced in the VAL + DASA group. Histopathological examination showed significant myocardial injury in the DASA group, with improved cardiac tissue morphology in the combination group. Immunohistochemical analysis revealed altered expression of apoptosis-related proteins, including caspase-3 and BCL-2, with improved levels in the combination group compared to DASA alone. Metabolomic profiling identified significant metabolic shifts, with 15 metabolites differentiating the treatment groups, and the VAL + DASA group mitigated the metabolic disturbances caused by DASA. The study suggesting VAL's potential therapeutic role in managing DASA-induced cardiac toxicity. The combination of VAL with DASA not only improved survival rates and reduced cardiac biomarker levels but also preserved myocardial architecture and normalized metabolic profiles. These findings highlight the importance of integrated approaches in evaluating drug efficacy and suggest VAL as a promising candidate for protecting cardiac function in preclinical models of DASA therapy.

Correlating enzymatic reactivity for different substrates using transferable data-driven collective variables

Machine learning (ML) is transforming the investigation of complex biological processes. In enzymatic catalysis, one significant challenge is identifying the reactive conformations (RC) of the enzyme:substrate complex where the substrate assumes a precise arrangement in the active site necessary to initiate a reaction. Traditional methods are hindered by the complexity of the multidimensional free energy landscape involved in the transition from nonreactive to reactive conformations. Here, we applied ML techniques to address this challenge, focusing on human pancreatic α-amylase, a crucial enzyme in type-II diabetes treatment. Using ML-based collective variables (CVs), we correlated the probability of being in a RC with the experimental catalytic activity of several malto-oligosaccharide substrates. Our findings demonstrate a remarkable transferability of these CVs across various compounds, significantly streamlining the modeling process and reducing both computational demand and manual intervention in setting up simulations for new substrates. This approach not only advances our understanding of enzymatic processes but also holds substantial potential for accelerating drug discovery by enabling rapid and accurate evaluation of drug efficacy across different generations of inhibitors.

Human-Induced Pluripotent Stem Cell-Derived Neural Organoids as a Novel In Vitro Platform for Developmental Neurotoxicity Assessment.

There has been a recent drive to replace in vivo studies with in vitro studies in the field of toxicity testing. Therefore, instead of conventional animal or planar cell culture models, there is an urgent need for in vitro systems whose conditions can be strictly controlled, including cell-cell interactions and sensitivity to low doses of chemicals. Neural organoids generated from human-induced pluripotent stem cells (iPSCs) are a promising in vitro platform for modeling human brain development. In this study, we developed a new tool based on various iPSCs to study and predict chemical-induced toxicity in humans. The model displayed several neurodevelopmental features and showed good reproducibility, comparable to that of previously published models. The results revealed that basic fibroblast growth factor plays a key role in the formation of the embryoid body, as well as complex neural networks and higher-order structures such as layered stacking. Using organoid models, pesticide toxicities were assessed. Cells treated with low concentrations of rotenone underwent apoptosis to a greater extent than those treated with high concentrations of rotenone. Morphological changes associated with the development of neural progenitor cells were observed after exposure to low doses of chlorpyrifos. These findings suggest that the neuronal organoids developed in this study mimic the developmental processes occurring in the brain and nerves and are a useful tool for evaluating drug efficacy, safety, and toxicity.

Flexible concentration control of Newtonian and non-Newtonian fluids in a microfluidic device via AC electrothermal flow

Microfluid preparation at targeted concentration is crucial for lots of applications such as protein crystallization and drug efficacy evaluation. Herein, we report an efficient method to continuously produce Newtonian and non-Newtonian fluids at desired concentrations via AC electrothermal (ACET) flow. Two miscible fluids with different initial concentrations are first injected into the device via two separate inlets. The demanded concentrations are obtained under ACET flow, which mixes the fluids into specific states first and obtain the targeted concentrations at outlet afterwards via the voltage and fluid velocity control. To elucidate the underlying principles of fluid concentration control through the ACET effect, we have developed a three-dimensional numerical model coupling the electric, thermal, flow and concentration fields to perform analyses. Our findings indicate that fluid concentration modulation is significantly impacted by both intrinsic fluid properties and external control parameters, including the fluid's apparent viscosity, conductivity, velocity, and driving voltage. Specifically, as the fluid's apparent viscosity increases, the flow weakens, resulting in a higher driving voltage being required to achieve the targeted fluid concentration. The Joule effect and temperature gradient in fluids intensify with increased fluid conductivity, enhancing the ACET flow and correspondingly reducing the necessary driving voltage for concentration control. The duration of the ACET flow in the microchannel varies with the fluid velocity, subsequently affecting the concentration adjustment. The intensity of the ACET flow augments with an increase in the driving voltage, leading to diverse fluid mixing performances and outlet concentrations as the voltage changes. Overall, the fluid concentration control is directly influenced by fluid properties and can be flexibly adjusted through external control of fluid velocity and voltage. The simplicity of the chip design and the flexibility of concentration control offered by this approach make it highly appealing for a wide range of applications that require precise fluid concentration control.

EPCO-36. INTEGRATIVE DEEP-LEARNING AND PHARMACOGENOMIC PROFILING OF MALIGNANT GLIOMAS USING PATIENT-DERIVED TUMOR CELLS

Abstract Malignant glioma stands as a formidable cancer with limited therapeutic options due to many factors including pronounced genetic heterogeneity, the blood-brain barrier, among others. Precision medicine, tailoring treatment based on a patient’s unique molecular profiles, is a fitting approach for addressing intra- and inter-tumor heterogeneity. Previously, we have shown the advantage of using patient-derived tumor cells (PDCs) to evaluate drug efficacy across various cancer types. Unlike cancer cell lines, which significantly differ from primary tumors, PDCs capture the molecular features of primary tumors, showing predictive clinical responses in a retrospective study. Building on these encouraging results, we have expanded PDC-based drug screening to specifically target malignant gliomas. We have established an initial cohort of over 500 malignant glioma PDCs (~ 370 patients) and screened more than 100 drugs. We have complemented our cohort with molecular profiles, including genomic and transcriptomic data to infer the potential pharmacogenomic associations of malignant gliomas. We constructed a multi-modal deep-learning model that seamlessly integrates molecular features and drug structure to predict the drug sensitivity. By employing an explainable machine learning method, we retrospectively analyzed the model to investigate the potential molecular biomarkers and their contribution to drug sensitivity. Collectively, our study demonstrates the efficacy of using patient-derived tumor cells (PDCs) combined with deep-learning models to predict drug sensitivity in malignant gliomas. This integrative approach can potentially refine personalized treatment strategies and improve clinical outcomes for glioma patients.

Multimodal spatiotemporal drug assessment platform based on a microelectrode neural network chip in Alzheimer’s disease

The pathogenesis of Alzheimer’s disease (AD) remains elusive. The development of new drugs is protracted, costly, and fraught with failure, largely due to the lack of convenient methods for dynamically studying the pathogenesis of AD and evaluating drug efficacy in vitro. There is a dearth of in vitro multi-site assay platforms capable of observing the therapeutic effects of AD drugs at the level of cellular and network. Consequently, an in vitro multimodal spatiotemporal drug assessment platform has been developed based on a neuronal network chip. It has a symmetric distribution of electrode points with two different sizes (10 μm and 30 μm), which are more suitable for the detection of neuronal connections. The multifaceted neurophysiological properties, including single neuron firing pattern, intercellular connection, transmission speed, and neural network communication, were detected in real time. The results demonstrated that the differences between experimental groups in electrophysiological properties, could significantly distinguish the effects of AD representative drug treatment after different levels of neurological injury. The administration of the drug at the initial stage of β-amyloid oligomers (AβOs) toxicity was found to effectively retard the deterioration of neurons and network (early stage: firing rate increased by 8 %; middle stage: cross-correlation coefficient decreased by 27 %; late stage: similarity index remained positive and relative transmission speed decreased by 11 %). The neurophysiological mechanism of drug interaction was further elucidated, which may provide the guidance for the optimal timing of drug administration. Following the further extension of biosensor longevity and the expansion of synchronous multidimensional parameter detection, including impedance and electrochemistry, it is anticipated that this will become a novel platform for the preclinical evaluation and screening of AD drugs.

FXR activation remodels hepatic and intestinal transcriptional landscapes in metabolic dysfunction-associated steatohepatitis.

The escalating obesity epidemic and aging population have propelled metabolic dysfunction-associated steatohepatitis (MASH) to the forefront of public health concerns. The activation of FXR shows promise to combat MASH and its detrimental consequences. However, the specific alterations within the MASH-related transcriptional network remain elusive, hindering the development of more precise and effective therapeutic strategies. Through a comprehensive analysis of liver RNA-seq data from human and mouse MASH samples, we identified central perturbations within the MASH-associated transcriptional network, including disrupted cellular metabolism and mitochondrial function, decreased tissue repair capability, and increased inflammation and fibrosis. By employing integrated transcriptome profiling of diverse FXR agonists-treated mice, FXR liver-specific knockout mice, and open-source human datasets, we determined that hepatic FXR activation effectively ameliorated MASH by reversing the dysregulated metabolic and inflammatory networks implicated in MASH pathogenesis. This mitigation encompassed resolving fibrosis and reducing immune infiltration. By understanding the core regulatory network of FXR, which is directly correlated with disease severity and treatment response, we identified approximately one-third of the patients who could potentially benefit from FXR agonist therapy. A similar analysis involving intestinal RNA-seq data from FXR agonists-treated mice and FXR intestine-specific knockout mice revealed that intestinal FXR activation attenuates intestinal inflammation, and has promise in attenuating hepatic inflammation and fibrosis. Collectively, our study uncovers the intricate pathophysiological features of MASH at a transcriptional level and highlights the complex interplay between FXR activation and both MASH progression and regression. These findings contribute to precise drug development, utilization, and efficacy evaluation, ultimately aiming to improve patient outcomes.

Free Electron Density Gradients Enhanced Biosensor for Ultrasensitive and Accurate Affinity Assessment of the Immunotherapy Drugs.

Accurate affinity assessments play an important role in drug discovery, screening, and efficacy evaluation. Label-free affinity biosensors are recognized as a dependable and standard technology for addressing this challenge. This study constructs a free electron density gradient-enhanced meta-surface plasmon resonance (FED-MSPR) biosensor through a finite-difference time-domain simulation model, the biosensor demonstrates superior detection performance in accurately determining affinity and kinetic rate constants. By controlling the dielectric properties of the metal on the surface of the nanocup arrays, the plasmon resonance effects are easily tuned without changing the nanostructure design. Compared with the single-layer gold chip, the triple-layer FED-MSPR chip demonstrated a four-fold improvement in resolution at the optimal resonance peak. Additionally, the sensitivity and figure of merit (FOM) of the multi-layer chip increased by 3.5 and 7.99 times, respectively. Following modification with high- and low-staggered carboxylation, the noise-signal ratio and baseline stability of the real-time kinetic curves based on these chips are significantly enhanced. The developed carboxylation FED-MSPR platform is successfully used to perform affinity assays for Adalimumab and TNF-α protein, resulting in favorable dynamic curves. These findings validate the proposed FED-MSPR biosensor platform as cost-effective, rapid, sensitive, and label-free, facilitating real-time quality control in drug development.

A chemically defined, mechanically tunable, and bioactive hyaluronic acid/alginate double-network hydrogel for liver cancer organoid construction

Liver cancer organoids replicate the pathophysiology of primary tumors, making them ideal for drug screening and efficacy evaluation. However, their growth in complex, variable, animal-derived matrices hinders practical application. Here, we designed an easily accessible, chemically defined, biocompatible double-network hydrogel (HADR) using methacrylated hyaluronic acid (HAMA), sodium alginate (SA), methacrylamide dopamine (DMA), and c(RGDFC) for liver cancer organoid culture. By optimizing critical extracellular matrix (ECM) parameters, the HADR hydrogel achieves compatibility with the physiological mechanics of the human liver and fosters the adhesion and proliferation of multiple cell types. In vitro drug efficacy tests showed that HepG2 cell line-derived liver cancer organoids exhibited higher IC50 values than 2D cultures, indicating greater drug resistance. Subcutaneous tumor models in nude mice revealed that HADR hydrogels created a microenvironment for HepG2 cells mirroring the natural tumor ECM, leading to increased tumor volume, denser cell arrangement, and concurrent microvascular development. In vivo drug efficacy evaluations indicated that DOX treatment downregulated Ki-67 and MMP-9 expression, inhibiting HepG2 cell proliferation, invasion, and metastasis. These findings demonstrate the potential of HADR hydrogels for liver cancer organoid culture, offering new strategies for personalized drug screening and efficacy evaluation.

Reporter Alleles in hiPSCs: Visual Cues on Development and Disease.

Reporter alleles are essential for advancing research with human induced pluripotent stem cells (hiPSCs), notably in developmental biology and disease modeling. This study investigates the state-of-the-art gene-editing techniques tailored for generating reporter alleles in hiPSCs, emphasizing their effectiveness in investigating cellular dynamics and disease mechanisms. Various methodologies, including the application of CRISPR/Cas9 technology, are discussed for accurately integrating reporter genes into the specific genomic loci. The synthesis of findings from the studies utilizing these reporter alleles reveals insights into developmental processes, genetic disorder modeling, and therapeutic screening, consolidating the existing knowledge. These hiPSC-derived models demonstrate remarkable versatility in replicating human diseases and evaluating drug efficacy, thereby accelerating translational research. Furthermore, this review addresses challenges and future directions in refining the reporter allele design and application to bolster their reliability and relevance in biomedical research. Overall, this investigation offers a comprehensive perspective on the methodologies, applications, and implications of reporter alleles in hiPSC-based studies, underscoring their essential role in advancing both fundamental scientific understanding and clinical practice.

Development of an orthotopic medulloblastoma zebrafish model for rapid drug testing.

Medulloblastoma (MB) is one of the most common malignant brain tumors in children. Current preclinical in vivo model systems for MB have increased our understanding of molecular mechanisms regulating MB development. However, they may not be suitable for large-scale studies. The aim of this study was to investigate if a zebrafish-based xenograft model can recapitulate MB growth and enable rapid drug testing. Nine different MB cell lines or patient-derived cells were transplanted into blastula-stage zebrafish embryos. Tumor development and migration were then monitored using live imaging. RNA sequencing was performed to investigate transcriptome changes after conditioning cells in neural stem cell-like medium. Furthermore, drug treatments were tested in a 96-well format. We demonstrate here that transplantation of MB cells into the blastula stage of zebrafish embryos leads to orthotopic tumor growth that can be observed within 24 hours after transplantation. Importantly, the homing of transplanted cells to the hindbrain region and the aggressiveness of tumor growth are enhanced by pre-culturing cells in a neural stem cell-like medium. The change in culture conditions rewires the transcriptome towards a more migratory and neuronal phenotype, including the expression of guidance molecules SEMA3A and EFNB1, both of which correlate with lower overall survival in MB patients. Furthermore, we highlight that the orthotopic zebrafish MB model has the potential to be used for rapid drug testing. Blastula-stage zebrafish MB xenografts present an alternative to current MB mouse xenograft models, enabling quick evaluation of tumor cell growth, neurotropism, and drug efficacy.