NPJ Antimicrob Resist. 2025 Feb 18;3(1):9. doi: 10.1038/s44259-024-00070-3.

ABSTRACT

Antimicrobial resistance (AMR) poses a growing global health threat. Nanomedicine, combined with drug repurposing, may help extend the effective lifespan of current and new antimicrobials. This review, presents an Australian perspective on nanotechnology-based therapies, highlighting scientific and clinical challenges. Early consideration of the potential barriers to market access may help to accelerate research translation, regulatory approval and patient access to nano-antimicrobial (NAM) drugs for resistant pathogens, not only in Australia, but globally.

PMID:39966608 | DOI:10.1038/s44259-024-00070-3

Neurotherapeutics. 2025 Feb 17:e00553. doi: 10.1016/j.neurot.2025.e00553. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) presents significant challenges in drug discovery and development due to its complex and poorly understood pathology and etiology. Digital twins (DTs) are recently developed virtual real-time representations of physical entities that enable rapid assessment of the bidirectional interaction between the virtual and physical domains. With recent advances in artificial intelligence (AI) and the growing accumulation of multi-omics and clinical data, application of DTs in healthcare is gaining traction. Digital twin technology, in the form of multiscale virtual models of patients or organ systems, can track health status in real time with continuous feedback, thereby driving model updates that enhance clinical decision-making. Here, we posit an additional role for DTs in drug discovery, with particular utility for complex diseases like AD. In this review, we discuss salient challenges in AD drug development, including complex disease pathology and comorbidities, difficulty in early diagnosis, and the current high failure rate of clinical trials. We also review DTs and discuss potential applications for predicting AD progression, discovering biomarkers, identifying new drug targets and opportunities for drug repurposing, facilitating clinical trials, and advancing precision medicine. Despite significant hurdles in this area, such as integration and standardization of dynamic medical data and issues of data security and privacy, DTs represent a promising approach for revolutionizing drug discovery in AD.

PMID:39965994 | DOI:10.1016/j.neurot.2025.e00553

Int J Biol Macromol. 2025 Feb 16:141057. doi: 10.1016/j.ijbiomac.2025.141057. Online ahead of print.

ABSTRACT

Of all isoforms, human carbonic anhydrase II (PF00194; EC 4.2.1.1), which is mostly found in red cells, kidneys, and the eyes, plays a pivotal role in numerous physiological processes, and its dysregulation has been linked to the wide range of illnesses, such as glaucoma. Finding new inhibitors that target Carbonic anhydrase II, therefore has great potential in drug discovery. Using drug repurposing approach, this study focused on the investigation of different drugs as Carbonic anhydrase II inhibitors and their structural studies using X-ray crystallography. For this purpose, 100 different drugs were evaluated for bovine and human carbonic anhydrase II inhibitory activity. Among all, two drugs, i.e. acetohexamide (1) and levosulpiride (54) were found to be active, with IC50 = 437.0 ± 0.2 and 1128 ± 0.75 μM, respectively. Mechanistic studies suggested that both drugs are competitive inhibitors of the human carbonic anhydrase II enzyme. The X-ray crystal structure analysis revealed that acetohexamide (1) interacts via terminal acetyl group with the active site residues of the carbonic anhydrase II enzyme, and showed strong hydrogen bonding with Zn, His94, His119, and Asn67. The sulfonamide group of levosulpiride was involved in strong hydrogen bonding with Zn, His94, His119, and Thr199. From in vivo studies, we found that carbonic anhydrase activity was significantly inhibited by the intraperitoneal administration of levosulpiride for up to 5 h. Our findings provide comprehensive insights for the optimization of the pharmacological profile of these drugs, and provide avenues for the exploration of different derivatives of these drugs with enhanced efficacy and fewer adverse effects.

PMID:39965680 | DOI:10.1016/j.ijbiomac.2025.141057

J Am Med Inform Assoc. 2025 Feb 18:ocaf035. doi: 10.1093/jamia/ocaf035. Online ahead of print.

ABSTRACT

OBJECTIVE: This study addresses the significant challenges posed by emerging SARS-CoV-2 variants, particularly in developing diagnostics and therapeutics. Drug repurposing is investigated by identifying critical regulatory proteins impacted by the virus, providing rapid and effective therapeutic solutions for better disease management.

MATERIALS AND METHODS: We employed a comprehensive approach combining mathematical modeling and efficient parameter estimation to study the transient responses of regulatory proteins in both normal and virus-infected cells. Proportional-integral-derivative (PID) controllers were used to pinpoint specific protein targets for therapeutic intervention. Additionally, advanced deep learning models and molecular docking techniques were applied to analyze drug-target and drug-drug interactions, ensuring both efficacy and safety of the proposed treatments. This approach was applied to a case study focused on the cytokine storm in COVID-19, centering on Angiotensin-converting enzyme 2 (ACE2), which plays a key role in SARS-CoV-2 infection.

RESULTS: Our findings suggest that activating ACE2 presents a promising therapeutic strategy, whereas inhibiting AT1R seems less effective. Deep learning models, combined with molecular docking, identified Lomefloxacin and Fostamatinib as stable drugs with no significant thermodynamic interactions, suggesting their safe concurrent use in managing COVID-19-induced cytokine storms.

DISCUSSION: The results highlight the potential of ACE2 activation in mitigating lung injury and severe inflammation caused by SARS-CoV-2. This integrated approach accelerates the identification of safe and effective treatment options for emerging viral variants.

CONCLUSION: This framework provides an efficient method for identifying critical regulatory proteins and advancing drug repurposing, contributing to the rapid development of therapeutic strategies for COVID-19 and future global pandemics.

PMID:39965087 | DOI:10.1093/jamia/ocaf035

Front Public Health. 2025 Feb 3;13:1520467. doi: 10.3389/fpubh.2025.1520467. eCollection 2025.

ABSTRACT

Rare diseases, affecting millions globally, pose a significant healthcare burden despite impacting a small population. While approximately 70% of all rare diseases are genetic and often begin in childhood, diagnosis remains slow and only 5% have approved treatments. The UN emphasizes improved access to primary care (diagnostic and potentially therapeutic) for these patients and their families. Next-generation sequencing (NGS) offers hope for earlier and more accurate diagnoses, potentially leading to preventative measures and targeted therapies. In here, we explore the therapeutic landscape for rare diseases, analyzing drugs in development and those already approved by the European Medicines Agency (EMA). We differentiate between orphan drugs with market exclusivity and repurposed existing drugs, both crucial for patients. By analyzing market size, segmentation, and publicly available data, this comprehensive study aims to pave the way for improved understanding of the treatment landscape and a wider knowledge accessibility for rare disease patients.

PMID:39963479 | PMC:PMC11830808 | DOI:10.3389/fpubh.2025.1520467

Med Biol Eng Comput. 2025 Feb 17. doi: 10.1007/s11517-025-03325-x. Online ahead of print.

ABSTRACT

Computational drug repositioning approaches should be investigated for the identification of new treatments for Alzheimer's patients as a huge amount of omics data has been produced during pre-clinical and clinical studies. Here, we investigated a gene network in Alzheimer's patients to detect a proper therapeutic target. We screened the targets of different drugs (34,006 compounds) using data available in the Connectivity Map database. Then, we analyzed transcriptome profiles of Alzheimer's patients to discover a network of gene-drugs based on mutual information, representing an index of dependence among genes. This study identified a network consisting of 25 genes and compounds and interconnected biological processes using computational approaches. The results also highlight the diagnostic role of the 25 genes since we obtained good classification performances using a neural network model. We also suggest 12 repurposable drugs (like KU-60019, AM-630, CP55940, enflurane, ginkgolide B, linopirdine, apremilast, ibudilast, pentoxifylline, roflumilast, acitretin, and tamibarotene) interacting with 6 genes (ATM, CNR1, GLRB, KCNQ2, PDE4B, and RARA), that we linked to retrograde endocannabinoid signaling, synaptic vesicle cycle, morphine addiction, and homologous recombination.

PMID:39961913 | DOI:10.1007/s11517-025-03325-x

J Bioinform Comput Biol. 2024 Dec;22(6):2450028. doi: 10.1142/S0219720024500288. Epub 2025 Feb 1.

ABSTRACT

The prediction of drug-target affinity (DTA) is crucial for efficiently identifying potential targets for drug repurposing, thereby reducing resource wastage. In this paper, we propose a novel graph-based deep learning model for DTA that leverages adaptive structure-aware pooling for graph processing. Our approach integrates a self-attention mechanism with an enhanced graph neural network to capture the significance of each node in the graph, marking a significant advancement in graph feature extraction. Specifically, adjacent nodes in the 2D molecular graph are aggregated into clusters, with the features of these clusters weighted according to their attention scores to form the final molecular representation. In terms of model architecture, we utilize both global and hierarchical pooling, and assess the performance of the model on multiple benchmark datasets. The evaluation results on the KIBA dataset show that our model achieved the lowest mean squared error (MSE) of 0.126, which is a 0.5% reduction compared to the best-performing baseline method. Additionally, to validate the generalization capabilities of the model, we conduct comparative experiments on regression and binary classification tasks. The results demonstrate that our model outperforms previous models in both types of tasks.

PMID:39961610 | DOI:10.1142/S0219720024500288

Ageing Res Rev. 2025 Feb 15:102693. doi: 10.1016/j.arr.2025.102693. Online ahead of print.

ABSTRACT

Repurposing the existing drugs for the management of both common and rare diseases is increasingly appealing due to challenges such as high attrition rates, economic, and the slow pace of discovering and improving new drugs. Drug repurposing involves the utilization of existing medications to treat diseases for which they were not originally intended. Despite encountering scientific and economic challenges, the pharmaceutical industry is intrigued by the potential to uncover new indications for medications. Medication repurposing is applicable across different stages of drug development, with the greatest potential observed when the drug has undergone prior safety testing. In this review, strategies for repurposing drugs for Parkinson's disease (PD) are outlined, a neurodegenerative disorder predominantly impacting dopaminergic neurons in the substantia nigra pars compacta region. PD is a debilitating neurodegenerative condition marked by an amalgam of motor and non-motor symptoms. Despite the availability of certain symptomatic treatments, particularly targeting motor symptoms, there remains a lack of established drugs capable of modifying the course of PD, leading to its unchecked progression. Although standard drug discovery initiatives focusing on treatments that relieve diseases have yielded valuable understanding into the underlying mechanisms of PD, none of the numerous promising candidates identified in preclinical studies have successfully transitioned into clinically effective medications. Due to the substantial expenses associated with drug discovery endeavors, it is understandable that there has been a notable shift towards reprofiling strategies. Assessing the efficacy of an existing medication offers the additional advantage of circumventing the requirement for preclinical safety assessments and formulation enhancements, consequently streamlining the process and reducing both the duration of time and financial investments involved in bringing a treatment to clinical fruition. Furthermore, repurposed drugs may benefit from lower rates of failure, presenting an additional potential advantage. various strategies for repurposing drugs are available to researchers in the field of PD. Some of these strategies have demonstrated effectiveness in identifying appropriate drugs for clinical trials, thereby providing validation for such techniques. This review provides an overview of the diverse strategies employed for drug reprofiling from approaches that emphasise on single-gene transcriptional investigations to comprehensive epidemiological correlation analysis. Additionally, instances of previous or current research endeavors employing each strategy has been discussed. For strategies not yet implemented in PD research, their efficacy is demonstrated using examples from other disorders. In this review, we assess the safety and efficacy potential of prominent candidates repurposed as potential treatments for modifying the course of PD undergoing advanced clinical trials.

PMID:39961372 | DOI:10.1016/j.arr.2025.102693

Elife. 2025 Feb 17;13:RP95952. doi: 10.7554/eLife.95952.

ABSTRACT

Despite exciting developments in cancer immunotherapy, its broad application is limited by the paucity of targetable antigens on the tumor cell surface. As an intrinsic cellular pathway, nonsense-mediated decay (NMD) conceals neoantigens through the destruction of the RNA products from genes harboring truncating mutations. We developed and conducted a high-throughput screen, based on the ratiometric analysis of transcripts, to identify critical mediators of NMD in human cells. This screen implicated disruption of kinase SMG1's phosphorylation of UPF1 as a potential disruptor of NMD. This led us to design a novel SMG1 inhibitor, KVS0001, that elevates the expression of transcripts and proteins resulting from human and murine truncating mutations in vitro and murine cells in vivo. Most importantly, KVS0001 concomitantly increased the presentation of immune-targetable human leukocyte antigens (HLA) class I-associated peptides from NMD-downregulated proteins on the surface of human cancer cells. KVS0001 provides new opportunities for studying NMD and the diseases in which NMD plays a role, including cancer and inherited diseases.

PMID:39960487 | DOI:10.7554/eLife.95952

J Clin Invest. 2025 Feb 17;135(4):e174081. doi: 10.1172/JCI174081.

ABSTRACT

Dilated cardiomyopathy (DCM) due to genetic disorders results in decreased myocardial contractility, leading to high morbidity and mortality rates. There are several therapeutic challenges in treating DCM, including poor understanding of the underlying mechanism of impaired myocardial contractility and the difficulty of developing targeted therapies to reverse mutation-specific pathologies. In this report, we focused on K210del, a DCM-causing mutation, due to 3-nucleotide deletion of sarcomeric troponin T (TnnT), resulting in loss of Lysine210. We resolved the crystal structure of the troponin complex carrying the K210del mutation. K210del induced an allosteric shift in the troponin complex resulting in distortion of activation Ca2+-binding domain of troponin C (TnnC) at S69, resulting in calcium discoordination. Next, we adopted a structure-based drug repurposing approach to identify bisphosphonate risedronate as a potential structural corrector for the mutant troponin complex. Cocrystallization of risedronate with the mutant troponin complex restored the normal configuration of S69 and calcium coordination. Risedronate normalized force generation in K210del patient-induced pluripotent stem cell-derived (iPSC-derived) cardiomyocytes and improved calcium sensitivity in skinned papillary muscles isolated from K210del mice. Systemic administration of risedronate to K210del mice normalized left ventricular ejection fraction. Collectively, these results identify the structural basis for decreased calcium sensitivity in K210del and highlight structural and phenotypic correction as a potential therapeutic strategy in genetic cardiomyopathies.

PMID:39959972 | DOI:10.1172/JCI174081

In Silico Pharmacol. 2025 Feb 13;13(1):27. doi: 10.1007/s40203-025-00307-7. eCollection 2025.

ABSTRACT

The global spread of monkeypox, caused by the double-stranded DNA monkeypox virus (MPXV), has underscored the urgent need for effective antiviral treatments. In this study, we aim to identify a potent inhibitor for MPXV DNA polymerase (DNAP), a critical enzyme in the virus replication process. Using a computational drug repurposing approach, we performed a virtual screening of 1615 FDA-approved drugs based on drug-likeness and molecular docking against DNAP. Among these, 1430 compounds met Lipinski's rule of five for drug-likeness, with Doxycycline emerging as the most promising competitive inhibitor, binding strongly to the DNAP active site with a binding affinity of - 9.3 kcal/mol. This interaction involved significant hydrogen bonds, electrostatic interactions, and hydrophobic contacts, with Doxycycline demonstrating a stronger affinity than established antivirals for smallpox, including Cidofovir, Brincidofovir, and Tecovirimat. Stability and flexibility analyses through a 200 ns molecular dynamics simulation and normal mode analysis confirmed the robustness of Doxycycline binding to DNAP. Overall, our results suggest Doxycycline as a promising candidate for monkeypox treatment, though additional experimental and clinical studies are needed to confirm its therapeutic potential and clinical utility.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-025-00307-7.

PMID:39958784 | PMC:PMC11825436 | DOI:10.1007/s40203-025-00307-7

Mini Rev Med Chem. 2025 Feb 14. doi: 10.2174/0113895575360959250117073046. Online ahead of print.

ABSTRACT

Sleep disorders and the resultant sleep deprivation (SD) are very common nowadays, resulting in depressed mood, poor memory and concentration, and various important changes in health, performance and safety. They may provoke further impairment of the cell lining of the blood vessels, as acting as a risk factor for cardiovascular disease (CVD) onset and progression. SD may lead to low neuronal regaining and plasticity, drastically affecting brain function. Thus, SD is a known risk factor for mental, behavioral and developmental disorders. Due to the inflammatory and oxidative stressful nature of SD, immune response modulation and antioxidants could be another therapeutic approach, apart from the already known symptomatic treatment with sedatives. Additionally, many drugs approved for other indications and under investigation, have been revisited due to their wide array of pharmacological activities. This review summarizes the main aspects of SD pathology and SD interrelated comorbidities and presents direct and indirect antioxidant molecules and drugs with multi-targeting potential that could assist in the prevention or management of these factors. A number of research groups have investigated well-known antioxidant compounds with multi-targeting cores, combining structural characteristics with properties including antiinflammatory, metal chelatory, gene transcription and immune modulatory that may add towards the effective SD and its associated comorbidities treatment.

PMID:39957704 | DOI:10.2174/0113895575360959250117073046

Eur J Immunol. 2025 Feb;55(2):e202451225. doi: 10.1002/eji.202451225.

ABSTRACT

Regulatory T cells (Tregs) are a subset of T cells defined by the expression of Forkhead box protein P3 (FoxP3) playing a crucial role in regulating effector T cell activity. Tregs accumulate in the tumor microenvironment facilitating tumor growth. Thus, targeting FoxP3+ Tregs could improve cancer immunotherapies. Here, we conducted a high-throughput, phenotypic screening of a drug repurposing library to identify compounds downregulating FoxP3 expression in human primary T cells. We identified the tyrosine kinase inhibitor bosutinib and the STAT3 inhibitor nifuroxazide effectively downregulating FoxP3 expression. To identify more potent compounds, structural analogs of these two compounds were searched and validated. These analogs were found to reduce FoxP3 expression in a similar- or more potent manner than the original hits. All compounds inhibited Treg suppressive functions and reduced the expression of Treg activation markers. Importantly, bosutinib disrupted FAK and CaMKII signaling more potently in Tregs, whilst nifuroxazide and its analog NA16 targeted STAT3 protein levels more effectively in Tregs. Additionally, bosutinib and NA16 targeted effector Tregs more effectively than other Treg subsets. In summary, bosutinib, nifuroxazide, and their analogs inhibited FoxP3 expression, Treg suppressive abilities, and Treg activation effectively, which could serve as tools for the improvement of current cancer immunotherapies.

PMID:39955647 | DOI:10.1002/eji.202451225

Cell Rep Methods. 2025 Feb 10:100990. doi: 10.1016/j.crmeth.2025.100990. Online ahead of print.

ABSTRACT

The need for a deeper understanding of adverse drug reaction (ADR) mechanisms is vital for improving drug safety and repurposing. This study introduces Drug Adverse Reaction Mechanism Explainer (DREAMER), a network-based framework that uses a comprehensive knowledge graph to uncover molecular mechanisms underlying ADRs and disease phenotypes. By examining shared phenotypes of drugs and diseases and their effects on protein-protein interaction networks, DREAMER identifies proteins linked to ADR mechanisms. Applied to 649 ADRs, DREAMER identified molecular mechanisms for 67 ADRs, including ventricular arrhythmia and metabolic acidosis, and emphasized pathways like GABAergic signaling and coagulation proteins in personality disorders and intracranial hemorrhage. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol, ranolazine, and diltiazem as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes, emphasizing the importance of network-based analyses with integrative data for enhancing drug safety and accelerating the discovery of novel therapeutic strategies.

PMID:39954672 | DOI:10.1016/j.crmeth.2025.100990

Expert Opin Drug Discov. 2025 Feb 15. doi: 10.1080/17460441.2025.2465373. Online ahead of print.

ABSTRACT

INTRODUCTION: Bladder cancer presents a significant health problem worldwide, with environmental and genetic factors contributing to its incidence. Histologically, it can be classified as carcinoma in situ, non-muscle invasive and muscle-invasive carcinoma, each one with distinct genetic alterations impacting prognosis and response to therapy. While traditional transurethral resection is commonly performed in carcinoma in situ and non-muscle invasive carcinoma, it often fails to prevent recurrence or progression to more aggressive phenotypes, leading to the frequent need for additional treatment such as intravesical chemotherapy or immunotherapy. Despite the advances made in recent years, treatment options for bladder cancer are still lacking due to the complex nature of this disease. So, animal models may hold potential for addressing these limitations, because they not only allow the study of disease progression but also the evaluation of therapies and the investigation of drug repositioning.

AREAS COVERED: This review discusses the use of animal models over the past decade, highlighting key discoveries and discussing advantages and disadvantages for new drug discovery.

EXPERT OPINION: Over the past decade animal models have been employed to evaluate new mechanisms underlying the responses to standard therapies, aiming to optimize bladder cancer treatment. The authors propose that molecular engineering techniques and AI may hold promise for the future development of more precise and effective targeted therapies in bladder cancer.

PMID:39954010 | DOI:10.1080/17460441.2025.2465373

Virol J. 2025 Feb 15;22(1):38. doi: 10.1186/s12985-025-02647-4.

ABSTRACT

BACKGROUND: Repurposing off-label drugs during epidemics or pandemics with unknown/known pathogens, particularly when their side effects and complications are already known, can be a strategic approach, as seen during the COVID-19 pandemic. Developing surrogate in vitro experimental models (passage-to-passage), which mimic epidemic/pandemic-like transmission (human-to-human), may enhance this repurposing process. This study evaluates montelukast sodium (MLS), a US FDA-approved leukotriene receptor antagonist for asthma, to explore its potential repurposing antiviral effects against bovine respiratory syncytial virus (BRSV), which has basic similarities to human respiratory syncytial virus (HRSV) as both belong to the Pneumoviridae family.

METHODS: An in vitro serial passage model was developed using MDBK cells infected with a local wild-type strain of BRSV (43TR2018). The cytotoxicity of MLS was assessed via the trypan blue exclusion method, identifying non-toxic concentrations. The impact of MLS on viral spread and infectivity was measured through TCID50 values over 10 passages. Viral loads were confirmed by nested RT-PCR and quantified using qPCR, while apoptosis, necrosis, and nitric oxide production were evaluated through staining and nitrite assays. Data were analyzed using ANOVA and Tukey's test (p < 0.05).

RESULTS: Control cells exhibited 97.16% viability, with 10 µM and 20 µM MLS concentrations maintaining viabilities of 89.2% and 87.3%, respectively. Viral titers significantly decreased at higher concentrations of MLS (up to 99.94% inhibition). Apoptosis rates decreased in MLS-treated cells, and live cell percentages improved, especially at 20 µM. Nitric oxide levels showed no significant differences across groups.

CONCLUSION: MLS demonstrated a dose-dependent antiviral effect against BRSV, achieving 99% viral inhibition properties in MDBK cells. These promising results warrant further investigation into the antiviral mechanisms of MLS.

PMID:39953515 | DOI:10.1186/s12985-025-02647-4

J Biomed Inform. 2025 Feb 12:104786. doi: 10.1016/j.jbi.2025.104786. Online ahead of print.

ABSTRACT

OBJECTIVE: Drug repurposing accelerates therapeutic development by finding new indications for approved drugs. However, accounting for individual patient differences is challenging. This study introduces a Precision Drug Repurposing (PDR) framework at single-patient resolution, integrating individual-level data with a foundational biomedical knowledge graph to enable personalized drug discovery.

METHODS: We developed a framework integrating patient-specific data from the UK Biobank (Polygenic Risk Scores, biomarker expressions, and medical history) with a comprehensive biomedical knowledge graph (61,146 entities, 1,246,726 relations). Using Alzheimer's Disease as a case study, we compared three diverse patient-specific models with a foundational model through standard link prediction metrics. We evaluated top predicted candidate drugs using patient medication history and literature review.

RESULTS: Our framework maintained the robust prediction capabilities of the foundational model. The integration of patient data, particularly Polygenic Risk Scores (PRS), significantly influenced drug prioritization (Cohen's d = 1.05 for scoring differences). Ablation studies demonstrated PRS's crucial role, with effect size decreasing to 0.77 upon removal. Each patient model identified novel drug candidates that were missed by the foundational model but showed therapeutic relevance when evaluated using patient's own medication history. These candidates were further supported by aligned literature evidence with the patient-level genetic risk profiles based on PRS.

CONCLUSION: This exploratory study demonstrates a promising approach to precision drug repurposing by integrating patient-specific data with a foundational knowledge graph.

PMID:39952626 | DOI:10.1016/j.jbi.2025.104786

Front Microbiol. 2025 Jan 30;16:1554339. doi: 10.3389/fmicb.2025.1554339. eCollection 2025.

NO ABSTRACT

PMID:39949624 | PMC:PMC11822564 | DOI:10.3389/fmicb.2025.1554339

Cell Mol Bioeng. 2025 Jan 23;18(1):71-82. doi: 10.1007/s12195-024-00841-y. eCollection 2025 Feb.

ABSTRACT

PURPOSE: Cervical and endometrial cancers pose significant challenges in women's healthcare due to their high mortality rates and limited treatment options. High throughput screening (HTS) of cervical and endometrial cancer in vitro models offers a promising avenue for drug repurposing and broadening patient treatment options. Traditional two-dimensional (2D) cell-based screenings have limited capabilities to capture crucial multicellular interactions, that are improved upon in three dimensional (3D) multicellular tissue engineered models. However, manual fabrication of the 3D platforms is both time consuming and subject to variability. Thus, the goal of this study was to utilize automated cell dispensing to fabricate 3D cell-based HTS platforms using the HP D100 Single Cell Dispenser to dispense cervical and endometrial cancer cells.

METHODS: We evaluated the effects of automated dispensing of the cancer cell lines by tuning the dispensing protocol to align with cell size measured in solution and the minimum cell number for acceptable cell viability and proliferation. We modified our previously reported coculture models of cervical and endometrial cancer to be in a 384 well plate format and measured microvessel length and cancer cell invasion.

RESULTS: Automatically and manually dispensed cells were directly compared revealing minimal differences between the dispensing methods. These findings suggest that automated dispensing of cancer cells minimally affects cell behavior and can be deployed to decrease in vitro model fabrication time.

CONCLUSIONS: By streamlining the manufacturing process, automated dispensing holds promise for enhancing efficiency and scalability of 3D in vitro HTS platforms, ultimately contributing to advancement in cancer research and treatment.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12195-024-00841-y.

PMID:39949489 | PMC:PMC11813830 | DOI:10.1007/s12195-024-00841-y

Sci Rep. 2025 Feb 13;15(1):5365. doi: 10.1038/s41598-025-89128-4.

ABSTRACT

Ulcerative colitis (UC), a chronic inflammatory bowel disease, significantly increases the risk of colon adenocarcinoma (COAD). Disulfidptosis, a novel form of programmed cell death, has been implicated in various diseases, including UC. This study investigates the expression of disulfidptosis-related genes, particularly CD2AP and MYH10, in UC and COAD. Through analysis of public datasets, we found MYH10 significantly upregulated and CD2AP downregulated in UC compared to healthy controls, with consistent patterns in COAD. Immune infiltration analysis revealed correlations between these genes and specific immune cell types, suggesting their roles in immune modulation. Molecular docking showed strong binding affinities of UC drugs such as budesonide and sulfasalazine with CD2AP and MYH10. Connectivity Map analysis identified additional drug candidates, including simvastatin and mephenytoin, which may be repurposed for UC and COAD therapy. These findings suggest disulfidptosis-related genes as potential biomarkers and therapeutic targets, linking chronic inflammation to cancer progression.

PMID:39948102 | DOI:10.1038/s41598-025-89128-4