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Dravet syndrome is a severe genetic epilepsy primarily caused by de novo mutations in a voltage-activated sodium channel gene (SCN1A). Patients face life-threatening seizures that are largely resistant to available anti-seizure medications. Preclinical Dravet syndrome animal models are a valuable tool to identify candidate anti-seizure medications for these patients. Among these, scn1lab mutant zebrafish, exhibiting spontaneous seizure-like activity, are particularly amenable to large-scale drug screening. Thus far, we have screened more than 3000 drug candidates in scn1lab zebrafish mutants, identifying valproate, stiripentol, and fenfluramine e.g. Food and Drug Administration-approved drugs, with clinical application in the Dravet syndrome population. Successful phenotypic screening in scn1lab mutant zebrafish is rigorous and consists of two stages: (i) a locomotion-based assay measuring high-velocity convulsive swim behaviour and (ii) an electrophysiology-based assay, using in vivo local field potential recordings, to quantify electrographic seizure-like events. Historically, nearly 90% of drug candidates fail during translation from preclinical models to the clinic. With such a high failure rate, it becomes necessary to address issues of replication and false positive identification. Leveraging our scn1lab zebrafish assays is one approach to address these problems. Here, we curated a list of nine anti-seizure drug candidates recently identified by other groups using preclinical Dravet syndrome models: 1-Ethyl-2-benzimidazolinone, AA43279, chlorzoxazone, donepezil, lisuride, mifepristone, pargyline, soticlestat and vorinostat. First-stage locomotion-based assays in scn1lab mutant zebrafish identified only 1-Ethyl-2-benzimidazolinone, chlorzoxazone and lisuride. However, second-stage local field potential recording assays did not show significant suppression of spontaneous electrographic seizure activity for any of the nine anti-seizure drug candidates. Surprisingly, soticlestat induced frank electrographic seizure-like discharges in wild-type control zebrafish. Taken together, our results failed to replicate clear anti-seizure efficacy for these drug candidates highlighting a necessity for strict scientific standards in preclinical identification of anti-seizure medications.

Bioscaffolds with characteristics of the tumor microenvironment is an important substrate to support the formation of multicellular tumor spheroids (MCTS). Conventional biomaterials promote MCTS formation using tumor extracellular matrix (ECM) components and exogenous growth factors, but lack individualized tumor cell niche construction which may restricts cell biology and drug discovery research. Herein, an ECM mimicked fiber composite dual-network hydrogel (FCDNG) was constructed. The 3D nanofibrous framework was introduced into the hydrogel by a "dispersion-swelling" method and an alginate/platelet-rich plasma (PRP) dual-network hydrogel was constructed by a simple "one-step" activation process. The scaffold can well control the physicochemical conditions that mimic the ECM structure and biomimetic mechanical properties. The fibrin formed by PRP can promote tumor cell proliferation, angiogenesis and cancer stem cell enrichment. Meanwhile, FCDNG has suitable degradation properties to meet the matrix remodeling requirements during the formation of MCTS. Tumor cells cultured in FCDNG had enhanced tumor stemness, proliferation, and resistance to chemotherapeutic agents, and thus providing an effective strategy for clinical drug evaluation. [ABSTRACT FROM AUTHOR]

AMIGO2 adheres to liver endothelium and induces liver metastasis. We revealed that genetically altering AMIGO2 expression in tumor cells affects their liver metastatic potential, depending on the AMIGO2 expression level. The aim of this study was to prevent liver metastasis by pharmacologically suppressing AMIGO2 expression. For screening, we used the mouse LV12 cells because of their affinity to adhere to liver endothelium and metastasize the liver owing to elevated AMIGO2 expression. Of the 285 compounds tested, 17 reduced AMIGO2 mRNA expression. We subsequently screened for compounds that inhibited tumor cell adhesion to liver endothelium and identified five compounds that inhibit three signaling pathways (MEK, JAK, and JNK). Treatment with these compounds inhibited liver metastasis of LV12 cells. Next, we used clinically available signal inhibitors (MEK inhibitor trametinib, JAK inhibitor ruxolitinib, and JNK inhibitor SP600125), and found that ruxolitinib inhibits AMIGO2 expression more stably. Furthermore, ruxolitinib inhibited the adhesion of LV12 cells to liver endothelium and suppressed liver metastasis. Using the MKN45 gastric cancer cells, we confirmed that ruxolitinib could prevent liver metastasis of human cancer cells. These results demonstrate that pharmacological inhibition of AMIGO2 expression in tumor cells is a promising novel strategy to prevent and control liver metastasis. [ABSTRACT FROM AUTHOR]

[Display omitted] Due to the complexity of regulatory networks of disease-related biomarkers, developing simple, sensitive, and accurate methods has remained challenging for precise diagnosis. Herein, an "AND" logic gates DNA molecular machine (LGDM) was constructed, which was powered by the catalytic hairpin assembly (CHA). It was coupled with dual-emission CdTe quantum dots (QDs)-based cation exchange reaction (CER) for label-free, sensitive, and ratiometric fluorescence detection of APE1 and miRNA biomarkers. Benefiting from synergistic signal amplification strategies and a ratiometric fluorometric output mode, this LGDM enables accurate logic computing with robust and significant output signals from weak inputs. It offers improved sensitivity and selectivity even in cell extracts. Using dual-emission spectra CdTe QDs, with a ratiometric signal output mode, ensured good stability and effectively prevented false-positive signals from intrinsic biological interferences compared to the approach relying on a single signal output mode, which enabled the LGDM to achieve rapid, efficient, and accurate natural drug screening against APE1 inhibitors in vitro and cells. The developed method provides impetus to streamline research related to miRNA and APE1, offering significant promise for widespread application in drug development and clinical analysis. [ABSTRACT FROM AUTHOR]

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, necessitating innovative research methodologies to improve treatment outcomes and develop novel strategies. The advent of three-dimensional (3D) cell cultures has marked a significant advancement in lung cancer research, offering a more physiologically relevant model compared to traditional two-dimensional (2D) cultures. This review elucidates the various types of 3D cell culture models currently used in lung cancer pharmacology, including spheroids, organoids and engineered tissue models, having pivotal roles in enhancing our understanding of lung cancer biology, facilitating drug development, and advancing precision medicine. 3D cell culture systems mimic the complex spatial architecture and microenvironment of lung tumours, providing critical insights into the cellular and molecular mechanisms of tumour progression, metastasis and drug responses. Spheroids, derived from commercialized cell lines, effectively model the tumour microenvironment (TME), including the formation of hypoxic and nutrient gradients, crucial for evaluating the penetration and efficacy of anti-cancer therapeutics. Organoids and tumouroids, derived from primary tissues, recapitulate the heterogeneity of lung cancers and are instrumental in personalized medicine approaches, supporting the simulation of in vivo pharmacological responses in a patient-specific context. Moreover, these models have been co-cultured with various cell types and biomimicry extracellular matrix (ECM) components to further recapitulate the heterotypic cell-cell and cell-ECM interactions present within the lung TME. 3D cultures have been significantly contributing to the identification of novel therapeutic targets and the understanding of resistance mechanisms against conventional therapies. Therefore, this review summarizes the latest findings in drug research involving lung cancer 3D models, together with the common laboratory-based assays used to study drug effects. Additionally, the integration of 3D cell cultures into lung cancer drug development workflows and precision medicine is discussed. This integration is pivotal in accelerating the translation of laboratory findings into clinical applications, thereby advancing the landscape of lung cancer treatment. By closely mirroring human lung tumours, these models not only enhance our understanding of the disease but also pave the way for the development of more effective and personalized therapeutic strategies. [ABSTRACT FROM AUTHOR]

We utilize patient tumor material to generate short-term bladder cancer patient–derived organoid (PDO) cultures for ex vivo drug testing, show that these PDOs retain the molecular and cellular characteristics of the primary tissue, and identify a multiomic signature for gemcitabine response. Predicting response to therapy for each patient's tumor is critical to improving long-term outcomes for muscle-invasive bladder cancer. This study aims to establish ex vivo bladder cancer patient–derived organoid (PDO) models that are representative of patients' tumors and determine the potential efficacy of standard of care and curated experimental therapies. Tumor material was collected prospectively from consented bladder cancer patients to generate short-term PDO models, which were screened against a panel of clinically relevant drugs in ex vivo three-dimensional culture. Multiomic profiling was utilized to validate the PDO models, establish the molecular characteristics of each tumor, and identify potential biomarkers of drug response. Gene expression (GEX) patterns between paired primary tissue and PDO samples were assessed using Spearman's rank correlation coefficients. Molecular correlates of therapy response were identified using Pearson correlation coefficients and Kruskal-Wallis tests with Dunn's post hoc pairwise comparison testing. A total of 106 tumors were collected from 97 patients, with 65 samples yielding sufficient material for complete multiomic molecular characterization and PDO screening with six to 32 drugs/combinations. Short-term PDOs faithfully represent the tumor molecular characteristics, maintain diverse cell types, and avoid shifts in GEX-based subtyping that accompany long-term PDO cultures. Utilizing an integrative approach, novel correlations between ex vivo drug responses and genomic alterations, GEX, and protein expression were identified, including a multiomic signature of gemcitabine response. The positive predictive value of ex vivo drug responses and the novel multiomic gemcitabine response signature need to be validated in future studies. Short-term PDO cultures retain the molecular characteristics of tumor tissue and avoid shifts in expression-based subtyping that have plagued long-term cultures. Integration of multiomic profiling and ex vivo drug screening data identifies potential predictive biomarkers, including a novel signature of gemcitabine response. Better models are needed to predict patient response to therapy in bladder cancer. We developed a platform that uses short-term culture to best mimic each patient's tumor and assess potential sensitivity to therapeutics. [ABSTRACT FROM AUTHOR]

Cell‐based microarrays are widely used in the fields of drug discovery and toxicology. Precise gradient generation and automated drug feeding are essential for high‐throughput screening of live cells in tiny droplets. However, most existing technologies either require sophisticated robotic equipment or cause mechanical/physiological interference with cells. Here, a heterogeneous organohydrogel is presented for automated gradient drug feeding, while ensuring minimal interference with cells. The heterogeneous organohydrogel comprises three crucial components. The bottom surface can automatically generate gradients functioning as a gradient generator, the organohydrogel bulk allows unidirectional transport of drugs without backflow, and the top surface with hydrophilic arrays can firmly anchor the cell‐based droplet array to evaluate the concentration‐dependent bioeffects of drugs accurately. Such a unique structure enables universal screening of different cell types and drugs dissolved in different solvents, requiring neither additional accessories nor arduous drug functionalization. The heterogeneous organohydrogel with unprecedented automation and non‐interference possesses the enormous potential to be a next‐generation platform for drug screening. [ABSTRACT FROM AUTHOR]

AbstractBackgroundMethodsResultsConclusionDrug use in Danish prisons has previously not been investigated in detail using confirmatory, laboratory analysis. The objective of the present quality study, initiated by the Danish Prison and Probation Service, was to i) evaluate the performance of an initial, on-site drug screening strategy; ii) gain insights into emerging drug trends; and iii) suggest evidence-based strategies for future drug testing.Over a two-year period, routine urine samples (n = 1952 from 710 inmates) from three Danish prisons were subjected to comprehensive drug testing. Immunoassay screening was conducted on-site. A parallel sample aliquot was forwarded to laboratory analysis by confirmatory methods: High-performance liquid chromatography and tandem mass spectrometry (LC-MS/MS) and gas chromatography and mass spectrometry (GC-MS) targeting 56 drugs-of-abuse/medical drugs, 26 key metabolites, 41 new psychoactive substances (NPS), including specific biomarkers for heroin, crack cocaine, or ethanol (a total of 123 target analytes/sample).The on-site immunoassay method showed a sensitivity from 66 to 100%; specificity was above 98%; accuracy was above 95%. Laboratory analysis detected compounds not screened for including tramadol, oxycodone, buprenorphine, ketamine, MDMA, 4-fluoroamphetamine, and GHB. The prevalence of drug use was in the order: cannabis > ethanol > cocaine > benzodiazepines > amphetamine.The performance of the immunoassay was found acceptable; however, the screening program was inadequate for detecting other significant substances. Based on these findings, a broader screening method will be implemented in future at Danish Prisons to minimize false negative results. The data did not indicate a trend of using NPS in Danish prisons. [ABSTRACT FROM AUTHOR]

Tsg101 is implicated in tumorigenesis and viral budding, and its inhibition through peptide binding is a potential therapeutic strategy. We utilized the crystal structure of the Tsg101‐PSAP complex from the protein databank in molecular dynamics studies on peptide‐Tsg101 interactions. To enhance peptide stability against enzymatic degradation, we designed peptides with L‐form terminal prolines and D‐form middle amino acids. These peptides also featured acetylated proline at the N‐terminus and amidated C‐terminus, increasing resistance to proteases. Virtual screening of 400 amino acid combinations identified promising peptide candidates and specific binding sites. Subsequent molecular dynamics simulations focused on the peptide PywP, which displayed strong binding stability at a novel Tsg101 site. Further simulations with variations of the D‐form amino acid ′w' showed that 18 of 21 tested peptides, notably PyeP and PytP, remained firmly bound, highlighting their potential as Tsg101 inhibitors. These peptides also contain hydrophilic residues, potentially improving solubility and therapeutic delivery. [ABSTRACT FROM AUTHOR]

Background: Gliomas, the most prevalent type of primary brain tumor, stand out as one of the most aggressive and lethal types of human cancer. Methods & Results: To uncover potential prognostic markers, we employed the weighted correlation network analysis (WGCNA) on the Chinese Glioma Genome Atlas (CGGA) 693 dataset to reveal four modules significantly associated with glioma clinical traits, primarily involved in immune function, cell cycle regulation, and ribosome biogenesis. Using the least absolute shrinkage and selection operator (LASSO) regression algorithm, we identified 11 key genes and developed a prognostic risk score model, which exhibits precise prognostic prediction in the CGGA 325 dataset. More importantly, we also validated the model in 12 glioma patients with overall survival (OS) ranging from 4 to 132 months using mRNA sequencing and immunohistochemical analysis. The analysis of immune infiltration revealed that patients with high-risk scores exhibit a heightened immune infiltration, particularly immune suppression cells, along with increased expression of immune checkpoints. Furthermore, we explored potentially effective drugs targeting 11 key genes for gliomas using the library of integrated network-based cellular signatures (LINCS) L1000 database, identifying that in vitro, both torin-1 and clofarabine exhibit promising anti-glioma activity and inhibitory effect on the cell cycle, a significant pathway enriched in the identified glioma modules. Conclusions: In conclusion, our study provides valuable insights into molecular mechanisms and identifying potential therapeutic targets for gliomas. [ABSTRACT FROM AUTHOR]

KRAS G12D mutation is prevalent in various cancers and is associated with poor prognosis. This study aimed to identify potential drug candidates targeting KRAS G12D using combined machine learning, virtual screening, molecular docking, and molecular dynamics (MD) simulations. The training and test sets are constructed based on a selection of inhibitors targeting the KRAS G12D mutant from the ChEMBL library. A random forest machine learning algorithm is developed to predict potential KRAS G12D binders. Molecular docking and the MM/PBSA binding energy are used to identify the lead compounds. The compound NPC489264 is identified as the top candidate, exhibiting favorable docking energy for the KRAS G12D mutant (−13.16 kcal mol−1). A hydrogen bond between the mutated Asp12 residue in the KRAS G12D mutant and NPC489264 is found to be a key interaction between these 2 molecules. MD simulations and MM/PBSA analysis revealed the strong binding affinity of NPC489264 to the G12D mutant (−5.49 kcal mol−1) compared to the wild type (10.17 kcal mol−1). These findings suggest that NPC489264 is a promising lead compound for further development of KRAS G12D‐targeted cancer therapies. [ABSTRACT FROM AUTHOR]

Summary: The intertwined interactions various immune cells have with epithelial cells in our body require sophisticated experimental approaches to be studied. Due to the limitations of immortalized cell lines and animal models, there is an increasing demand for human in vitro model systems to investigate the microenvironment of immune cells in normal and in pathological conditions. Organoids, which are self-renewing, 3D cellular structures that are derived from stem cells, have started to provide gap-filling tissue modelling solutions. In this review, we first demonstrate with some of the available examples how organoid-based immune cell co-culture experiments can advance disease modelling of cancer, inflammatory bowel disease, and tissue regeneration. Then, we argue that to achieve both complexity and scale, organ-on-chip models combined with cutting-edge microfluidics-based technologies can provide more precise manipulation and readouts. Finally, we discuss how genome editing techniques and the use of patient-derived organoids and immune cells can improve disease modelling and facilitate precision medicine. To achieve maximum impact and efficiency, these efforts should be supported by novel infrastructures such as organoid biobanks, organoid facilities, as well as drug screening and host-microbe interaction testing platforms. All these together or in combination can allow researchers to shed more detailed, and often patient-specific, light on the crosstalk between immune cells and epithelial cells in health and disease. Potential use and translational applications of patient-derived organoids are very diverse. Such models have revolutionized research in immunological diseases. Co-culture of organoids and immune cells can be used to model diseases, test genetic and environmental factors, and screen drugs or compounds with health-promoting or homeostasis-restoring potentials. Graphical Abstract [ABSTRACT FROM AUTHOR]

Drug efflux—a process primarily facilitated by efflux pumps such as multidrug resistance proteins (MRPs)—plays a pivotal role in cellular resistance to chemotherapies. Conventional approaches to assess drug efflux are predominantly conducted in vitro and often lack pump specificity. Here we report the bioorthogonal reporter inhibiting efflux (BRIEF) strategy, which enables the recording of pump‐specific drug efflux in living cells. In BRIEF, a specific substrate is engineered as a bioorthogonal efflux probe (BEP) for specific pumps. The cellular concentration and protein labeling level of the probe can be augmented when the test drug is transported by the same pumps. Serendipitously, we discovered that per‐O‐acetylated unnatural monosaccharides, initially designed for metabolic glycan labeling, are exported by some MRPs. Using Ac4GlcNAl as a BEP, we studied the structure‐efflux relationship of flavonoids and identified small molecules, including tannic acid, cholesterol and gallic acid, as novel MRP substrates in high‐throughput screening. Tannic acid, known for anti‐tumor and anti‐SARS‐CoV‐2 properties, showed increased efficacy upon MRP inhibition. Additionally, BRIEF was adapted to assess p‐glycoprotein‐mediated efflux using Rhodamine 123 as a BEP, leveraging its light‐activatable proximity labeling ability. BRIEF provides a versatile approach to investigate drug efflux and enhance chemotherapy strategies. [ABSTRACT FROM AUTHOR]

A research letter published in the journal Circulation discusses the LMNA Q353R mutation, which is associated with dilated cardiomyopathy. The mutation causes DNA damage accumulation in the heart, leading to premature aging and poor prognosis. The study found that vitamin D2 showed efficacy in reducing DNA damage in patient-specific cardiomyocytes. Another study investigated the mechanism by which the mutation causes DNA damage and found that abnormal localization of the vitamin D receptor leads to reduced DNA repair. The intervention with vitamin D2 can reduce DNA damage and improve cardiac function. This research provides insights into potential treatments for LMNA-mutant cardiomyopathy using vitamin D. [Extracted from the article]

Breast cancer is the most common malignant tumor in women. Due to the high heterogeneity of breast cancer cells, traditional in vitro research models still have major limitations. Therefore, it is urgent to establish an experimental model that can accurately simulate the characteristics of human breast cancer. Breast cancer organoid technology emerged as the times required, that is, to construct tissue analogs with organ characteristics by using a patient's tumor tissue through 3D culture in vitro. Since the breast cancer organoid can fully preserve the histology and genetic characteristics of the original tumor, it provides a reliable model for preclinical drug screening, establishment of breast cancer organoid biobanks, research into the mechanisms of tumor development, and determination of cancer targets. It has promoted personalized treatment for clinical breast cancer patients. This article mainly focuses on recent research progress and applications of organoid technology in breast cancer, discussing the current limitations and prospects of breast cancer organoid technology. [ABSTRACT FROM AUTHOR]

In recent years, 3D bioprinting technology has developed rapidly, becoming an essential tool in the fields of cancer research, tissue engineering, disease modeling and mechanistic studies. This paper reviewed the fundamental principles of bioprinting technology and its current applications in cancer research and tissue engineering. Bioprinting is an additive manufacturing technology that constructs complex three-dimensional tissue structures by digitally controlling the layer-by-layer deposition of biomaterials and living cells. The core steps of bioprinting include designing a 3D model, selecting appropriate bioprinting techniques and materials, printing layer by layer, followed by post-processing involving cell culture and functionalization. In cancer research, 3D bioprinting can create complex tumor models that simulate the tumor microenvironment, revealing new mechanisms of tumor initiation and progression. Traditional in vitro models, such as 2D cell cultures or animal models, often fail to accurately replicate the complexity of human tumors. However, 3D bioprinted tumor models, which mimic the dynamic interactions between tumor cells and their environment such as immune cells, stroma and blood vessels, offer a more biomimetic platform for studying tumor growth, invasion and metastasis. These models provide a research platform that closely mirrors actual tumor behavior. Additionally, Bioprinted models and scaffolds can be leveraged in personalized precision therapies by efficiently constructing patient-specific 3D models from their own cells. These models enable the prediction of patient’s sensitivity to drugs and radiotherapy. Additionally, localized scaffolds can be developed to meet individual patient needs, allowing for the formulation of appropriate drug types and dosages. Furthermore, 3D-printed scaffolds can support drug delivery by targeting specific areas, reducing drug-related side effects. They can also be used to facilitate local immunotherapy, cytokine therapy, cancer vaccines, and chimeric antigen receptor cell therapy, enhancing therapeutic outcomes. In tissue engineering, traditional tissue repair methods often struggle to address the complex requirements of constructing intricate tissue structures. 3D bioprinting offers a novel solution by enabling the creation of complex tissue architectures and promoting tissue regeneration. Basic tissues, such as bone, cartilage and skin, which have higher regenerative capacities, are gradually being incorporated into clinical practice. Significant progress has also been made in the repair and reconstruction of more complex organs like the liver and heart, though considerable challenges remain before these advancements can be fully translated into clinical applications. Finally, this paper discussed the current challenges and future directions of 3D bioprinting in these fields, aiming to provide reference for researchers. [ABSTRACT FROM AUTHOR]

In recent years, with rapid development of technology of regenerative medicine and tissue engineering, brain organoids, as an innovative in vitro model system, have become a hot spot in neuroscience research and drug development. Brain organoids simulate the complex structure and function of the human brain in terms of reproducing key processes of brain development in vitro, providing an unprecedented platform for understanding the mechanisms of neurological diseases and of evaluating drug efficacy and toxicity. This review summarizes the latest research progress in brain organoid technology, particularly its application in drug development and in exploring challenges and orientation of future development. [ABSTRACT FROM AUTHOR]

There is a paucity of data on the effect of preinjury substance (alcohol, drugs) abuse on the risk of delirium in patients with traumatic brain injury (TBI). This study aimed to assess the incidence of delirium among patients with blunt TBI in association with different substances. We analyzed the 2020 American College of Surgeons–Trauma Quality Improvement Program. We included all adult (≥18 y) patients with blunt TBI who had a recorded substance (drugs and alcohol) screening. Our primary outcome was the incidence of delirium. A total of 72,901 blunt TBI patients were identified. The mean (standard deviation) age was 56 (20) years and 68.0% were males. The median (interquartile range) injury severity score was 17 (10-25). Among the study population, 23.1% tested positive for drugs (Stimulants: 3.0%; Depressants: 2.9%, hallucinogens: 5.1%, Cannabinoids: 13.4%, TCAs: 0.1%), and 22.8% tested positive for Alcohol. Overall, 1856 (2.5%) experienced delirium. On univariate analysis, patients who developed delirium were more likely to have positive drug screening results. On multivariable regression analyses, positive screen tests for isolated stimulants (adjusted odds ratio [aOR]: 1.340, P = 0.018), tricyclic antidepressants (aOR: 3.107, P = 0.019), and cannabinoids (aOR: 1.326, P ≤ 0.001) were independently associated with higher odds of developing delirium. Nearly one-fourth of adult patients with blunt TBI had an initial positive substance screening test. Patients with positive results for isolated stimulants, tricyclic antidepressants, and cannabinoids were at a higher risk of developing delirium, whereas this association was not evident with other drugs and alcohol-positive tests. These findings emphasize the need for early drug screening in TBI patients and close monitoring of patients with positive screening tests. [ABSTRACT FROM AUTHOR]

Mitoribosomes are essential for the production of biological energy. The Human Mitoribosomal Small Subunit unit (MRPS) family, responsible for encoding mitochondrial ribosomal small subunits, is actively engaged in protein synthesis within the mitochondria. Intriguingly, MRPS family genes appear to play a role in cancer. A multistep process was employed to establish a risk model associated with MRPS genes, aiming to delineate the immune and pharmacogenomic landscapes in clear cell renal cell carcinoma (ccRCC). MRPScores were computed for individual patients to assess their responsiveness to various treatment modalities and their susceptibility to different therapeutic targets and drugs. While MRPS family genes have been implicated in various cancers as oncogenes, our findings reveal a contrasting tumor suppressor role for MRPS genes in ccRCC. Utilizing an MRPS‐related risk model, we observed its excellent prognostic capability in predicting survival outcomes for ccRCC patients. Remarkably, the subgroup with high MRPS‐related scores (MRPScore) displayed poorer prognosis but exhibited a more robust response to immunotherapy. Through in silico screening of 2183 drug targets and 1646 compounds, we identified two targets (RRM2 and OPRD1) and eight agents (AZ960, carmustine, lasalocid, SGI‐1776, AZD8055_1059, BPD.00008900_1998, MK.8776_2046, and XAV939_1268) with potential therapeutic implications for high‐MRPScore patients. Our study represents the pioneering effort in proposing that molecular classification, diagnosis, and treatment strategies can be formulated based on MRPScores. Indeed, a high MRPScore profile appears to elevate the risk of tumor progression and mortality, potentially through its influence on immune regulation. This suggests that the MRPS‐related risk model holds promise as a prognostic predictor and may offer novel insights into personalized therapeutic strategies. [ABSTRACT FROM AUTHOR]

Since many microfluidic devices have limited drug dose order of gradients and incorporate 2D cell culture, we here present a multi-layered platform with linear and logarithmic gradients with 3D-cell culturing chambers. By employing Hagen–Poiseuille flow resistance equation and the parallel electric schematics, we determined the appropriate channel dimensions to achieve the desired target concentrations (100%, 50%, 20%, 10%, 5%, 2%, 1%, 0%). To validate the gradient formation against theoretical values, we introduced a solution containing fluorescein into the microfluidic chip. Moreover, cell culturing chambers were spaced out laterally for every 9 mm, aligning with the dimensions with the standard plate reader, providing enhanced usability. Vertical layout of the chip minimized the lateral dimension required for housing various components while maintaining a favorable height for imaging. By preventing the need to use external tubing to connect concentration gradient generator and cell culturing chamber modules, our platform holds promise in facilitating the integration of microfluidics into drug evaluation processes. To demonstrate use of this flexible platform, we tested two chemotherapy drugs against human bladder cancer cells (T24) embedded in 3D fibrin gel and evaluated their cell viability and proliferation rate. IC50 values were extracted for cells exposed to varying doses of cisplatin, gemcitabine, and gemcitabine with a fixed cisplatin dose, confirming the enhanced apoptosis of the bladder cancer cells and the advantages of combination chemotherapy. This simple multi-layered device may accelerate screening of anti-cancer drugs for a specific cell type by extracting optimal dosage for two drugs. [ABSTRACT FROM AUTHOR]

Collecting duct carcinoma (CDC) is an aggressive rare subtype of kidney cancer with unmet clinical needs. Little is known about its underlying molecular alterations and etiology, primarily due to its rarity, and lack of preclinical models. This study aims to comprehensively characterize molecular alterations in CDC and identify its therapeutic vulnerabilities. Through whole-exome and transcriptome sequencing, we identified KRAS hotspot mutations (G12A/D/V) in 3/13 (23%) of the patients, in addition to known TP53, NF2 mutations. 3/13 (23%) patients carried a mutational signature (SBS22) caused by aristolochic acid (AA) exposures, known to be more prevalent in Asia, highlighting a geologically specific disease etiology. We further discovered that cell cycle-related pathways were the most predominantly dysregulated pathways. Our drug screening with our newly established CDC preclinical models identified a CDK9 inhibitor LDC000067 that specifically inhibited CDC tumor growth and prolonged survival. Our study not only improved our understanding of oncogenic molecular alterations of Asian CDC, but also identified cell-cycle machinery as a therapeutic vulnerability, laying the foundation for clinical trials to treat patients with such aggressive cancer. Synopsis: Collecting duct carcinoma (CDC) is an aggressive kidney cancer without effective treatment. Our study not only enhanced our scientific understanding of the oncogenic alterations prevalent in Asian CDC, but has also identified cell-cycle machinery as a potential target for therapeutic intervention. Mutations in KRAS hotspot and TP53 were predominantly identified in Asian CDC patients, shedding light on the genetic landscape of this cancer. Aristolochic acid (AA) mutational signature was identified in CDC tumors, providing valuable insights for cancer prevention strategies. Dysregulation of cell-cycle machinery was observed in both Caucasian and Asian CDC patients, indicating similar disease pathobiology. We have established a CDC patient-derived xenograft (PDX) and cell line models to facilitate drug screening and testing. Through our screening efforts, we have identified and validated a CDK9 inhibitor, LDC000067, which specifically inhibited CDC tumor growth and improved overall survival. Collecting duct carcinoma (CDC) is an aggressive kidney cancer without effective treatment. Our study not only enhanced our scientific understanding of the oncogenic alterations prevalent in Asian CDC, but has also identified cell-cycle machinery as a potential target for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Lactate is a critical regulatory factor secreted by tumors, influencing tumor development, metastasis, and clinical prognosis. Precise analysis of tumor-cell-secreted lactate is pivotal for early cancer diagnosis. This study describes a paper-based microfluidic chip to enable the detection of lactate levels secreted externally by living cells. Under optimized conditions, the lactate biosensor can complete the assay in less than 30 min. In addition, the platform can be used to distinguish lactate secretion levels in different cell lines and can be applied to the screening of antitumor drugs. Through enzymatic chemical conversion, this platform generates fluorescent signals, enabling qualitative assessment under a handheld UV lamp and quantitative analysis via grayscale intensity measurements using ImageJ (Ver. 1.50i) software. The paper-based platform presented in this study is rapid and highly sensitive and does not necessitate other costly and intricate instruments, thus making it applicable in resource-constrained areas and serving as a valuable tool for investigating cell lactate secretion and screening various anti-cancer drugs. [ABSTRACT FROM AUTHOR]

Recent advances in three-dimensional (3D) culturing and nanotechnology offer promising pathways to overcome the limitations of drug screening, particularly for tumors like neuroblastoma. In this study, we develop a high-throughput microfluidic chip that integrates a concentration gradient generator (CGG) with a 3D co-culture system, constructing the vascularized microenvironment in tumors by co-culturing neuroblastoma (SY5Y cell line) and human brain microvascular endothelial cells (HBMVECs) within a decellularized extracellular matrix (dECM) hydrogels. The automated platform enhances the simulation of the tumor microenvironment and allows for the precise control of the concentrations of nanomedicines, which is crucial for evaluating therapeutic efficacy. The findings demonstrate that the high-throughput platform can significantly accelerate drug discovery. It efficiently screens and analyzes drug interactions in a biologically relevant setting, potentially revolutionizing the drug screening process. [ABSTRACT FROM AUTHOR]

Abstract AMIGO2 adheres to liver endothelium and induces liver metastasis. We revealed that genetically altering AMIGO2 expression in tumor cells affects their liver metastatic potential, depending on the AMIGO2 expression level. The aim of this study was to prevent liver metastasis by pharmacologically suppressing AMIGO2 expression. For screening, we used the mouse LV12 cells because of their affinity to adhere to liver endothelium and metastasize the liver owing to elevated AMIGO2 expression. Of the 285 compounds tested, 17 reduced AMIGO2 mRNA expression. We subsequently screened for compounds that inhibited tumor cell adhesion to liver endothelium and identified five compounds that inhibit three signaling pathways (MEK, JAK, and JNK). Treatment with these compounds inhibited liver metastasis of LV12 cells. Next, we used clinically available signal inhibitors (MEK inhibitor trametinib, JAK inhibitor ruxolitinib, and JNK inhibitor SP600125), and found that ruxolitinib inhibits AMIGO2 expression more stably. Furthermore, ruxolitinib inhibited the adhesion of LV12 cells to liver endothelium and suppressed liver metastasis. Using the MKN45 gastric cancer cells, we confirmed that ruxolitinib could prevent liver metastasis of human cancer cells. These results demonstrate that pharmacological inhibition of AMIGO2 expression in tumor cells is a promising novel strategy to prevent and control liver metastasis.

In recent years, with rapid development of technology of regenerative medicine and tissue engineering, brain organoids, as an innovative in vitro model system, have become a hot spot in neuroscience research and drug development. Brain organoids simulate the complex structure and function of the human brain in terms of reproducing key processes of brain development in vitro, providing an unprecedented platform for understanding the mechanisms of neurological diseases and of evaluating drug efficacy and toxicity. This review summarizes the latest research progress in brain organoid technology, particularly its application in drug development and in exploring challenges and orientation of future development.

Primary liver cancer is a leading cause of death worldwide. To create advanced treatments for primary liver cancer, studies have utilized models such as 2D cell culture and in vivo animal models. Recent developments in cancer organoids have created the possibility for 3D in vitro cultures that recapitulates the cancer cell structure and operation as well as the tumor microenvironment (TME). However, before organoids can be directly translated to clinical use, tissue processing and culture medium must be standardized with unified protocols to decrease variability in results. Herein, we present the wide variety of published methodologies used to derive liver cancer organoids from patient tumor tissues. Additionally, we summarize validation methodologies for organoids in terms of marker expression levels with immunohistochemistry as well as the presence of mutations and variants through RNA-sequencing. Primary liver cancer organoids have exciting applications allowing for faster drug testing at a larger scale. Primary liver cancer organoids also assisit in uncovering new mechanisms. Through the coculture of different immune cells and cancer organoids, organoids are now better able to recapitulate the liver cancer TME. In addition, it further aids in the investigation of drug development and drug resistance. Lastly, we posit that the usage of liver cancer organoids in animal models provides researchers a methodology to overcome the current limitations of culture systems.

Abstract Collecting duct carcinoma (CDC) is an aggressive rare subtype of kidney cancer with unmet clinical needs. Little is known about its underlying molecular alterations and etiology, primarily due to its rarity, and lack of preclinical models. This study aims to comprehensively characterize molecular alterations in CDC and identify its therapeutic vulnerabilities. Through whole-exome and transcriptome sequencing, we identified KRAS hotspot mutations (G12A/D/V) in 3/13 (23%) of the patients, in addition to known TP53, NF2 mutations. 3/13 (23%) patients carried a mutational signature (SBS22) caused by aristolochic acid (AA) exposures, known to be more prevalent in Asia, highlighting a geologically specific disease etiology. We further discovered that cell cycle-related pathways were the most predominantly dysregulated pathways. Our drug screening with our newly established CDC preclinical models identified a CDK9 inhibitor LDC000067 that specifically inhibited CDC tumor growth and prolonged survival. Our study not only improved our understanding of oncogenic molecular alterations of Asian CDC, but also identified cell-cycle machinery as a therapeutic vulnerability, laying the foundation for clinical trials to treat patients with such aggressive cancer.

Abstract Primary liver cancer (PLC) is one of the most common malignant gastrointestinal tumors worldwide. Limited by the shortage of liver transplantation donors and the heterogeneity of tumors, patients with liver cancer lack effective treatment options, which leads to rapid progression and metastasis. Currently, preclinical models of PLC fall short of clinical reality and are limited in their response to disease progression and the effectiveness of drug therapy. Organoids are in vitro three-dimensional cultured preclinical models with a high degree of heterogeneity that preserve the histomorphological and genomic features of primary tumors. Liver cancer organoids have been widely used for drug screening, new target discovery, and precision medicine; thus representing a promising tool to study PLC. Here, we summarize the progress of research on liver cancer organoids and their potential application as disease models. This review provides a comprehensive introduction to this emerging technology and offers new ideas for researchers to explore in the field of precision medicine.

Abstract Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors.

Drug discovery is a sophisticated process that incorporates scientific innovations and cutting-edge technologies. Compared to traditional bioactivity-based screening methods, encoding and display technologies for combinatorial libraries have recently advanced from proof-of-principle experiments to promising tools for pharmaceutical hit discovery due to their high screening efficiency, throughput, and resource minimization. This review systematically summarizes the development history, typology, and prospective applications of encoding and displayed technologies, including phage display, ribosomal display, mRNA display, yeast cell display, one-bead one-compound, DNA-encoded, peptide nucleic acid-encoded, and new peptide-encoded technologies, and examples of preclinical and clinical translation. We discuss the progress of novel targeted therapeutic agents, covering a spectrum from small-molecule inhibitors and nonpeptidic macrocycles to linear, monocyclic, and bicyclic peptides, in addition to antibodies. We also address the pending challenges and future prospects of drug discovery, including the size of screening libraries, advantages and disadvantages of the technology, clinical translational potential, and market space. This review is intended to establish a comprehensive high-throughput drug discovery strategy for scientific researchers and clinical drug developers.

John D Rodriguez,1,2 Samantha Kerti,3 Adam Hamm,3 George W Ousler,1 Ethan Bensinger,1,2 Sadie Burnham,1,2 Mark B Abelson1,2,4,5 1Ora, Inc, Andover, MA, USA; 2Andover Eye Institute, Andover, MA, USA; 3Statistics and Data Corporation, Tempe, AZ, USA; 4Ophthalmology, Harvard Medical School, Cambridge, MA, USA; 5Mass Eye and Ear, Boston, MA, USACorrespondence: John D Rodriguez, Email jrodriguez@oraclinical.comPurpose: The absence of a standardized diagnostic method for clinical signs of Dry Eye Disease (DED) complicates clinical trials for future treatments. This paper evaluated Lissamine Green (LG) conjunctival staining as a valid, stable and modifiable endpoint for both clinical practice and clinical trials.Methods: Screening and pre-randomization data from two identically designed clinical trials for DED resulted in a pooled dataset of 494 subjects. Inclusion was based on reported symptoms, lissamine green (LG) conjunctival staining, Fluorescein (Fl) corneal and conjunctival staining, and Schirmer’s Test (ST). Outcome measures were assessed based on the modifiability of LG staining to exposure to a Controlled Adverse Environment (CAE®), correlation of LG to Fl staining, relative variation of LG staining scores and Schirmer test scores, and the correlation of LG staining with symptom scores.Results: The modifiability of LG conjunctival staining to environmental exposure was demonstrated, with nasal LG and FL staining displaying the most similar percent change. Nasal LG conjunctival staining scores for subjects with ST scores of less than 8mm were significantly higher than for subjects with ST greater than 8mm. LG staining scores were more consistent (25% change from baseline threshold) than ST scores. Finally, statistically significant correlations were found between LG staining and a number of symptom scores.Conclusion: This evaluation demonstrates the superiority of the utilization of a clinical endpoint focused on ocular surface damage. The reproducibility and modifiability of LG conjunctival staining to controlled adverse environment, coupled with its significant correlation with symptoms, positions it as an exemplary clinical sign endpoint for clinical management and in clinical trials. Our findings advocate for the adoption of LG conjunctival staining as a primary endpoint in both clinical research and drug development, offering a more effective means of identifying and addressing ocular surface damage in the realm of DED.Keywords: dry eye, conjunctiva, stain, lissamine green clinical trials, controlled adverse environment, disease models, drug screening, dry eye disease, efficacy endpoints

Pancreatic cancer is a worldwide medical and health problem. Due to its high heterogeneity and malignant phenotype, the 5-year survival rate of pancreatic cancer is only 7.2%, which is a serious threat to human health. The biological mechanism and drug development research of pancreatic cancer often rely on the traditional two-dimensional culture models (cell lines) and patient-derived xenograft models. However, cell lines lack the three-dimensional environment and heterogeneity of the tumor, while xenograft models have the disadvantages of long culture time, low success rate and difficulty in carrying out high-throughput drug screening. There is an urgent need to develop three-dimensional culture models that can highly reflect the characteristics and molecular variation of pancreatic cancer. As a three-dimensional culture model developed in recent years, human-derived pancreatic cancer organoids are multicellular units extracted from tissue samples and embedded in extracellular matrix gels after mechanical and enzymatic digestion, which can reproduce the histological characteristics and organ characteristics of the original patient, and even have the functions of the original organ. With the continuous development and improvement of pancreatic cancer organoids culture system, its simple, economical and stable culture technology has been gradually established, which promotes the application of human pancreatic cancer organoids to high-throughput drug screening, individualized precision treatment and deeper pathogenesis and targeted drug development research. At the same time, human-derived pancreatic cancer organoids are also a novel semi-in vivo model for the study of clinical molecular typing of pancreatic cancer, especially for the study of etiology, molecular characteristics, histomorphology and somatic mutation burden of patients with high mutation rate and high heterogeneity. The construction of human pancreatic cancer organoid biobank with large sample size is a new platform for biology, basic medicine and clinical science oncology research, which provides a reliable resource for the in-depth study of the pathogenesis of pancreatic cancer and the development of treatment strategies. In summary, the research progress of human pancreatic cancer organoids promotes the application of laboratory models that recapitulate the characteristics of clinical patients, improves the connection between basic laboratory research and clinical patients, and provides clinical sources for drug screening, pathogenesis research, individualized treatment strategies and the construction of biobanks. Therefore, this article reviewed the latest research progress of human pancreatic cancer organoids, in order to provide reference for researchers engaged in the research of human pancreatic cancer organoids.

Background and purpose: Colorectal carcinoma (CRC) is a common malignant tumor with incidence and mortality rates second only to gastric cancer and esophageal cancer among digestive system malignancies. Increasing evidence suggests that immune cells play a significant role in the occurrence and development of CRC. The aim of this study was to construct a prognostic model related to immune cell-associated genes to predict the prognosis of CRC patients and enable precise management. Methods: Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) data, along with clinical information for colorectal cancer, were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Differential genes of immune cell subtypes were extracted, and genes related to prognosis were screened in TCGA data using Cox regression and LASSO regression, with external validation using GSE39582 and GSE41258. The prognostic model was used to analyze chemotherapy drug sensitivity, assess immunotherapy efficacy, analyze pathways related to risk scores, and perform clinical correlation analysis. Finally, the expression levels of model genes were validated in 10 fresh frozen CRC tissues with post-operative pathological examination and cell lines using real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) and immunohistochemistry. All samples were approved by the Fudan University Shanghai Cancer Center Ethics Committee (No. 050432-4-2108*). Results: We defined 16 cell clusters based on the scRNA-seq dataset (GSE161277) and labeled these clusters as different cell types using the R package celldex. Differential analysis of immune cell subtypes yielded 374 differentially expressed genes. Using univariate Cox and LASSO analyses, we constructed a 9-gene risk prognostic model in CRC. This risk model exhibited reliable prognostic prediction performance and played an important role in predicting anti-tumor drug sensitivity, immunotherapy efficacy, potential molecular mechanisms, and clinical characteristics. Patients with high-risk scores had a lower probability of benefiting from immunotherapy. Conclusion: We constructed a 9-gene risk prognostic model based on the heterogeneity of immune cells in the CRC tumor microenvironment, which predicted the survival and treatment outcomes of CRC patients.

Microfluidic is a technology that allows the precise control of fluid in a micro-channel. With its advantages of high throughput and low cost, microfluidic technology has achieved good performance in various fields in recent years. Arthritis is a general term for a variety of joint diseases, which can be clinically manifested as joint pain and swelling, seriously affecting people's physical and mental health. At present, the causes of arthritis disease are still unknown, and existing disease models and treatment methods are still limited, so more treatments need to be developed. Microfluidic organ chip is a cutting-edge technology to build a bionic human organ model, which can reflect the structure and function characteristics of human organs by simulating the physiological environment of tissues and cells in vitro. This paper reviews the application of microfluidic technology in the modeling and treatment of arthritis, hoping to open up a new vision for the study of arthritis.

Primary liver cancer (PLC) is one of the most common malignant gastrointestinal tumors worldwide. Limited by the shortage of liver transplantation donors and the heterogeneity of tumors, patients with liver cancer lack effective treatment options, which leads to rapid progression and metastasis. Currently, preclinical models of PLC fall short of clinical reality and are limited in their response to disease progression and the effectiveness of drug therapy. Organoids are in vitro three-dimensional cultured preclinical models with a high degree of heterogeneity that preserve the histomorphological and genomic features of primary tumors. Liver cancer organoids have been widely used for drug screening, new target discovery, and precision medicine; thus representing a promising tool to study PLC. Here, we summarize the progress of research on liver cancer organoids and their potential application as disease models. This review provides a comprehensive introduction to this emerging technology and offers new ideas for researchers to explore in the field of precision medicine. [ABSTRACT FROM AUTHOR]

Organoid technology has been developed rapidly in the past decade, which involves the exploration of the mechanism of development, regeneration and various diseases, and intersects among multiple disciplines. Thousands of literature on 3D-culture or organoids have been published in the research areas of cell biology tissue engineering, nanoscience, oncology and so on, resulting in it being challenging for researchers to timely summarize these studies. Bibliometric statistics is a helpfulway to help researchers clarify the above issues efficiently andmanage the whole landscape systematically. In our study, all original articles on organoids were included in the Web of Science database from January 2009 to May 2024, and related information was collected and analyzed using Excel software, "bibliometrix" packages of the R software, VOSviewer and CiteSpace. As results, a total of 6222 papers were included to classify the status quo of the organoids and predict future research areas. Our findings highlight a growing trend in publications related to organoids, with the United States and Netherlands leading in this field. The University of California System, Harvard University, Utrecht University and Utrecht University Medical Center have emerged as pivotal contributors and the key authors in the field include Clevers, H, Beekman, JM and Spence JR. Our results also revealed that the research hotspots and trends of organoids mainly focused on clinical treatment, drug screening, and the application of materials and technologies such as "hydrogel" and "microfluidic technology" in organoids. Next, we had an in-depth interpretation of the development process of organoid research area, including the emergence of technology, the translation from bench to bedsides, the profiles of the most widely studied types of organoids, the application of materials and technologies, and the emerging organoid-immune co-cultures trends. Furthermore,we also discussed the pitfalls, challenges and prospects of organoid technology. In conclusion, this study provides readers straightforward and convenient access to the organoid research field. [ABSTRACT FROM AUTHOR]

Thiosemicarbazones and their metal complexes have been studied for their biological activities against bacteria, cancer cells and protozoa. Short-term in vitro treatment with one gold (III) complex (C3) and its salicyl-thiosemicarbazone ligand (C4) selectively inhibited proliferation of T. gondii. Transmission Electron Microscopy (TEM) detected transient structural alterations in the parasitophorous vacuole membrane and the tachyzoite cytoplasm, but the mitochondrial membrane potential appeared unaffected by these compounds. Proteins potentially interacting with C3 and C4 were identified using differential affinity chromatography coupled with mass spectrometry (DAC-MS). Moreover, long-term in vitro treatment was performed to investigate parasitostatic or parasiticidal activity of the compounds. DAC-MS identified 50 ribosomal proteins binding both compounds, and continuous drug treatments for up to 6 days caused the loss of efficacy. Parasite tolerance to both compounds was, however, rapidly lost in their absence and regained shortly after re-exposure. Proteome analyses of six T. gondii ME49 clones adapted to C3 and C4 compared to the non-adapted wildtype revealed overexpression of ribosomal proteins, of two transmembrane proteins involved in exocytosis and of an alpha/beta hydrolase fold domain-containing protein. Results suggest that C3 and C4 may interfere with protein biosynthesis and that adaptation may be associated with the upregulated expression of tachyzoite transmembrane proteins and transporters, suggesting that the in vitro drug tolerance in T. gondii might be due to reversible, non-drug specific stress-responses mediated by phenotypic plasticity. [ABSTRACT FROM AUTHOR]

Cancer is a leading cause of death worldwide. Around one-third of the total global cancer incidence and mortality are related to gastrointestinal (GI) cancers. Over the past few years, rapid developments have been made in patient-derived organoid (PDO) models for gastrointestinal cancers. By closely mimicking the molecular properties of their parent tumors in vitro, PDOs have emerged as powerful tools in personalized medicine and drug discovery. Here, we review the current literature on the application of PDOs of common gastrointestinal cancers in the optimization of drug treatment strategies in the clinic and their rising importance in pre-clinical drug development. We discuss the advantages and limitations of gastrointestinal cancer PDOs and outline the microfluidics-based strategies that improve the throughput of PDO models in order to extract the maximal benefits in the personalized medicine and drug discovery process. [ABSTRACT FROM AUTHOR]

Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors. [ABSTRACT FROM AUTHOR]

Variants (pathogenic) of the LMNA gene are a common cause of familial dilated cardiomyopathy (DCM), which is characterised by early-onset atrioventricular (AV) block, atrial fibrillation and ventricular tachyarrhythmias (VTs), and progressive heart failure. The unstable internal nuclear lamina observed in LMNA-related DCM is a consequence of the disassembly of lamins A and C. This suggests that LMNA variants produce truncated or alternative forms of protein that alter the nuclear structure and the signalling pathway related to cardiac muscle diseases. To date, the pathogenic mechanisms and phenotypes of LMNA-related DCM have been studied using different platforms, such as patient-specific induced pluripotent stem-cell-derived cardiomyocytes (iPSC-CMs) and transgenic mice. In this review, point variants in the LMNA gene that cause autosomal dominantly inherited forms of LMNA-related DCM are summarised. In addition, potential therapeutic targets based on preclinical studies of LMNA variants using transgenic mice and human iPSC-CMs are discussed. They include mitochondria deficiency, variants in nuclear deformation, chromatin remodelling, altered platelet-derived growth factor and ERK1/2-related pathways, and abnormal calcium handling. [ABSTRACT FROM AUTHOR]

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD. [ABSTRACT FROM AUTHOR]

Context: Accurately predicting plasma protein binding rate (PPBR) and oral bioavailability (OBA) helps to better reveal the absorption and distribution of drugs in the human body and subsequent drug design. Although machine learning models have achieved good results in prediction accuracy, they often suffer from insufficient accuracy when dealing with data with irregular topological structures. Methods: In view of this, this study proposes a pharmacokinetic parameter prediction framework based on graph convolutional networks (GCN), which predicts the PPBR and OBA of small molecule drugs. In the framework, GCN is first used to extract spatial feature information on the topological structure of drug molecules, in order to better learn node features and association information between nodes. Then, based on the principle of drug similarity, this study calculates the similarity between small molecule drugs, selects different thresholds to construct datasets, and establishes a prediction model centered on the GCN algorithm. The experimental results show that compared with traditional machine learning prediction models, the prediction model constructed based on the GCN method performs best on PPBR and OBA datasets with an inter-molecular similarity threshold of 0.25, with MAE of 0.155 and 0.167, respectively. In addition, in order to further improve the accuracy of the prediction model, GCN is combined with other algorithms. Compared to using a single GCN method, the distribution of the predicted values obtained by the combined model is highly consistent with the true values. In summary, this work provides a new method for improving the rate of early drug screening in the future. [ABSTRACT FROM AUTHOR]

Drug discovery is a sophisticated process that incorporates scientific innovations and cutting-edge technologies. Compared to traditional bioactivity-based screening methods, encoding and display technologies for combinatorial libraries have recently advanced from proof-of-principle experiments to promising tools for pharmaceutical hit discovery due to their high screening efficiency, throughput, and resource minimization. This review systematically summarizes the development history, typology, and prospective applications of encoding and displayed technologies, including phage display, ribosomal display, mRNA display, yeast cell display, one-bead one-compound, DNA-encoded, peptide nucleic acid-encoded, and new peptide-encoded technologies, and examples of preclinical and clinical translation. We discuss the progress of novel targeted therapeutic agents, covering a spectrum from small-molecule inhibitors and nonpeptidic macrocycles to linear, monocyclic, and bicyclic peptides, in addition to antibodies. We also address the pending challenges and future prospects of drug discovery, including the size of screening libraries, advantages and disadvantages of the technology, clinical translational potential, and market space. This review is intended to establish a comprehensive high-throughput drug discovery strategy for scientific researchers and clinical drug developers. Encoding and display technologies for combinatorial libraries have gained popularity in drug discovery landscapes, attributed to their enhanced screening efficiency, throughput, and contribution to reducing drug discovery timelines and expenditures. [Display omitted] [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) has emerged as a significant threat to public health, particularly in infections caused by critically important Gram-negative bacteria. The development of novel antibiotics has its limitations, and therefore it is crucial to explore alternative strategies to effectively combat infections with resistant pathogens. In this context, the present study investigated the antibacterial potency of 560 compounds against the multidrug-resistant (MDR) strains of Klebsiella pneumoniae and Serratia marcescens. The evaluated compounds were selected from the Pandemic Response Box (PRB) and COVID Box (CB) and subjected to assays to determine the inhibitory concentration (IC), minimum bactericidal concentration (MBC), and biofilm formation. Further, the effects of these compounds on membrane integrity were assessed through protein quantification. Several of the evaluated compounds, including fusidic acid, MMV1580853, and MMV1634399, exhibited a significant reduction in biofilm formation and growth in K. pneumoniae. Trimethoprim exhibited potential against S. marcescens. The IC values of the compounds indicated significant microbial growth inhibition at various concentrations. These findings underscore the potency of the existing antibiotics and novel compounds in combating the MDR strains of bacteria. The importance of reconsidering the known antibiotics and utilizing drug repositioning strategies to address the increasing risk of AMR is highlighted. [ABSTRACT FROM AUTHOR]

Fluorescence flow cytometry is a powerful instrument to distinguish cells or particles labelled with high-specificity fluorophores. However, traditional flow cytometry is complex, bulky, and inconvenient for users to adjust fluorescence channels. In this paper, we present a modular fluorescence flow cytometry (M-FCM) system in which fluorescence channels can be flexibly arranged. Modules for particle focusing and fluorescence detection were developed. After hydrodynamical focusing, the cells were measured in the detection modules, which were integrated with in situ illumination and fluorescence detection. The signal-to-noise ratio of the detection reached to 33.2 dB. The crosstalk among the fluorescence channels was eliminated. The M-FCM system was applied to evaluate cell viability in drug screening, agreeing well with the commercial cytometry. The modular cytometry presents several outstanding features: flexibility in setting fluorescence channels, cost efficiency, compact construction, ease of operation, and the potential to upgrade for multifunctional measurements. The modular cytometry provides a multifunctional platform for various biophysical measurements, e.g., electrical impedance and refractive-index detection. The proposed work paves an innovative avenue for the multivariate analysis of cellular characteristics. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) spheroid models are crucial for cancer research, offering more accurate insights into tumour biology and drug responses than traditional 2D cell cultures. However, inconsistent and low-throughput spheroid production has hindered their application in drug screening. Here, we present an automated high-throughput platform for a spheroid selection, fabrication, and sorting system (SFSS) to produce uniform gelatine-encapsulated spheroids (GESs) with high efficiency. SFSS integrates advanced imaging, analysis, photo-triggered fabrication, and microfluidic sorting to precisely control spheroid size, shape, and viability. Our data demonstrate that our SFSS can produce over 50 GESs with consistent size and circularity in 30 min with over 97% sorting accuracy while maintaining cell viability and structural integrity. We demonstrated that the GESs can be used for drug screening and potentially for various assays. Thus, the SFSS could significantly enhance the efficiency of generating uniform spheroids, facilitating their application in drug development to investigate complex biological systems and drug responses in a more physiologically relevant context. [ABSTRACT FROM AUTHOR]

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) have emerged as a promising tool for studying cardiac physiology and drug responses. However, their use is largely limited by an immature phenotype and lack of high-throughput analytical methodology. In this study, we developed a high-throughput testing platform utilizing hPSC-CMs to assess the cardiotoxicity and effectiveness of drugs. Following an optimized differentiation and maturation protocol, hPSC-CMs exhibited mature CM morphology, phenotype, and functionality, making them suitable for drug testing applications. We monitored intracellular calcium dynamics using calcium imaging techniques to measure spontaneous calcium oscillations in hPSC-CMs in the presence or absence of test compounds. For the cardiotoxicity test, hPSC-CMs were treated with various compounds, and calcium flux was measured to evaluate their effects on calcium dynamics. We found that cardiotoxic drugs withdrawn due to adverse drug reactions, including encainide, mibefradil, and cetirizine, exhibited toxicity in hPSC-CMs but not in HEK293-hERG cells. Additionally, in the effectiveness test, hPSC-CMs were exposed to ATX-II, a sodium current inducer for mimicking long QT syndrome type 3, followed by exposure to test compounds. The observed changes in calcium dynamics following drug exposure demonstrated the utility of hPSC-CMs as a versatile model system for assessing both cardiotoxicity and drug efficacy. Overall, our findings highlight the potential of hPSC-CMs in advancing drug discovery and development, which offer a physiologically relevant platform for the preclinical screening of novel therapeutics. [ABSTRACT FROM AUTHOR]

In this study, we screened a chemical library to find potent anticancer compounds that are less cytotoxic to non-cancerous cells. This study revealed that pyrazole PTA-1 is a potent anticancer compound. Additionally, we sought to elucidate its mechanism of action (MOA) in triple-negative breast cancer cells. Cytotoxicity was analyzed with the differential nuclear staining assay (DNS). Additional secondary assays were performed to determine the MOA of the compound. The potential MOA of PTA-1 was assessed using whole RNA sequencing, Connectivity Map (CMap) analysis, in silico docking, confocal microscopy, and biochemical assays. PTA-1 is cytotoxic at a low micromolar range in 17 human cancer cell lines, demonstrating less cytotoxicity to non-cancerous human cells, indicating a favorable selective cytotoxicity index (SCI) for the killing of cancer cells. PTA-1 induced phosphatidylserine externalization, caspase-3/7 activation, and DNA fragmentation in triple-negative breast MDA-MB-231 cells, indicating that it induces apoptosis. Additionally, PTA-1 arrests cells in the S and G2/M phases. Furthermore, gene expression analysis revealed that PTA-1 altered the expression of 730 genes at 24 h (198 upregulated and 532 downregulated). A comparison of these gene signatures with those within CMap indicated a profile similar to that of tubulin inhibitors. Subsequent studies revealed that PTA-1 disrupts microtubule organization and inhibits tubulin polymerization. Our results suggest that PTA-1 is a potent drug with cytotoxicity to various cancer cells, induces apoptosis and cell cycle arrest, and inhibits tubulin polymerization, indicating that PTA-1 is an attractive drug for future clinical cancer treatment. [ABSTRACT FROM AUTHOR]

The article discusses the role of pharmacogenomics in pediatric oncology research and treatment, highlighting the importance of personalized medicine to optimize drug efficacy and minimize toxicity in children with cancer. It emphasizes the need for precision oncology and follow-up care strategies to improve outcomes and quality of life for pediatric cancer patients. The text also explores the impact of genetic variations on drug responses, such as in the case of methotrexate therapy for acute lymphoblastic leukemia, and the potential benefits of integrating pharmacogenomic knowledge into clinical practice. [Extracted from the article]