Comput Biol Med. 2024 Mar 13;173:108292. doi: 10.1016/j.compbiomed.2024.108292. Online ahead of print.

ABSTRACT

Lung cancer is one of the most common malignant tumors around the world, which has the highest mortality rate among all cancers. Traditional Chinese medicine (TCM) has attracted increased attention in the field of lung cancer treatment. However, the abundance of ingredients in Chinese medicines presents a challenge in identifying promising ingredient candidates and exploring their mechanisms for lung cancer treatment. In this work, two network-based algorithms were combined to calculate the network relationships between ingredient targets and lung cancer targets in the human interactome. Based on the enrichment analysis of the constructed disease module, key targets of lung cancer were identified. In addition, molecular docking and enrichment analysis of the overlapping targets between lung cancer and ingredients were performed to investigate the potential mechanisms of ingredient candidates against lung cancer. Ten potential ingredients against lung cancer were identified and they may have similar effect on the development of lung cancer. The results obtained from this study offered valuable insights and provided potential avenues for the development of novel drugs aimed at treating lung cancer.

PMID:38513387 | DOI:10.1016/j.compbiomed.2024.108292

Elife. 2024 Mar 21;12:RP91157. doi: 10.7554/eLife.91157.

ABSTRACT

Host-directed therapy (HDT) is an emerging approach to overcome antimicrobial resistance in pathogenic microorganisms. Specifically, HDT targets host-encoded factors required for pathogen replication and survival without interfering with microbial growth or metabolism, thereby eliminating the risk of resistance development. By applying HDT and a drug repurposing approach, we demonstrate that (R)-DI-87, a clinical-stage anticancer drug and potent inhibitor of mammalian deoxycytidine kinase (dCK), mitigates Staphylococcus aureus abscess formation in organ tissues upon invasive bloodstream infection. Mechanistically, (R)-DI-87 shields phagocytes from staphylococcal death-effector deoxyribonucleosides that target dCK and the mammalian purine salvage pathway-apoptosis axis. In this manner, (R)-DI-87-mediated protection of immune cells amplifies macrophage infiltration into deep-seated abscesses, a phenomenon coupled with enhanced pathogen control, ameliorated immunopathology, and reduced disease severity. Thus, pharmaceutical blockade of dCK represents an advanced anti-infective intervention strategy against which staphylococci cannot develop resistance and may help to fight fatal infectious diseases in hospitalized patients.

PMID:38512723 | DOI:10.7554/eLife.91157

Expert Opin Pharmacother. 2024 Mar 21. doi: 10.1080/14656566.2024.2333372. Online ahead of print.

ABSTRACT

INTRODUCTION: Schistosomiasis, one of the current Neglected Tropical Diseases (NTDs) affects over 230 million people globally, with nearly 700 million at risk in more than 74 countries. Praziquantel (PZQ) has served as the primary treatment for the past four decades; however, its effectiveness is limited as it solely eliminates adult worms. In regions where infections are frequent, PZQ exhibits only temporary efficacy and has restricted potential to disrupt the prolonged transmission of the disease.

AREAS COVERED: A comprehensive exploration using the PubMed database was conducted to review current pharmacotherapy approaches for schistosomiasis. This review also encompasses recent research findings related to potential novel therapeutics and the repurposing of existing drugs.

EXPERT OPINION: Current schistosoma treatment strategies, primarily relying on PZQ, face challenges like temporary effectiveness and limited impact on disease transmission. Drug repurposing, due to economic constraints, is decisive for NTDs. Despite PZQ's efficacy, its failure to prevent reinfection highlights the need for complementary strategies, especially in regions with persistent environmental foci. Integrating therapies against diverse schistosome stages boosts efficacy and impedes resistance. Uncovering novel agents is essential to address resistance concerns in tackling this neglected tropical disease. Integrated strategies present a comprehensive approach to navigate the complex challenges.

PMID:38511392 | DOI:10.1080/14656566.2024.2333372

Comput Struct Biotechnol J. 2024 Mar 1;23:1129-1143. doi: 10.1016/j.csbj.2024.02.027. eCollection 2024 Dec.

ABSTRACT

We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.

PMID:38510973 | PMC:PMC10950807 | DOI:10.1016/j.csbj.2024.02.027

iScience. 2024 Mar 2;27(4):109388. doi: 10.1016/j.isci.2024.109388. eCollection 2024 Apr 19.

ABSTRACT

Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disease signatures based on endometrial gene expression data to identify potential therapeutics from existing drugs, based on expression reversal. Of 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308 (9.8%) were in common; however, 221 out of 299 drugs identified, (73.9%) were shared. We selected fenoprofen, an uncommonly prescribed NSAID that was the top therapeutic candidate for further investigation. When testing fenoprofen in an established rat model of endometriosis, fenoprofen successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a therapeutic that could be utilized more frequently for endometriosis and suggest the utility of the aforementioned computational drug repurposing approach for endometriosis.

PMID:38510116 | PMC:PMC10952035 | DOI:10.1016/j.isci.2024.109388

Genome Med. 2024 Mar 20;16(1):42. doi: 10.1186/s13073-024-01314-7.

ABSTRACT

BACKGROUND: Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs.

METHODS: Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs.

RESULTS: scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment.

CONCLUSIONS: We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

PMID:38509600 | DOI:10.1186/s13073-024-01314-7

Expert Opin Ther Pat. 2024 Mar 20:1-10. doi: 10.1080/13543776.2024.2332663. Online ahead of print.

ABSTRACT

INTRODUCTION: Carbonic anhydrases (CAs, EC 4.2.1.1) play a pivotal role in the regulation of carbon dioxide , bicarbonate, and hydrogen ions within bacterial cells, ensuring pH homeostasis and facilitating energy production. We conducted a systematic literature search (PubMed, Web of Science, and Google Scholar) to examine the intricate interplay between CAs and bacterial metabolism, revealing the potential of CA inhibitors (CAIs) as innovative therapeutic agents against pathogenic bacteria.

AREA COVERED: Inhibition of bacterial CAs was explored in various pathogens, emphasizing the CA roles in microbial virulence, survival, and adaptability. Escherichia coli, a valid and convenient model microorganism, was recently used to investigate the effects of acetazolamide (AAZ) on the bacterial life cycle. Furthermore, the effectiveness of CAIs against pathogenic bacteria has been further substantiated for Vancomycin-Resistant Enterococci (VRE) and antibiotic-resistant Neisseria gonorrhoeae strains.

EXPERT OPINION: CAIs target bacterial metabolic pathways, offering alternatives to conventional therapies. They hold promise against drug-resistant microorganisms such as VRE and N. gonorrhoeae strains. CAIs offer promising avenues for addressing antibiotic resistance and underscore their potential as novel antibacterial agents. Recognizing the central role of CAs in bacterial growth and pathogenicity will pave the way for innovative infection control and treatment strategies possibly also for other antibiotic resistant species.

PMID:38506448 | DOI:10.1080/13543776.2024.2332663

Bol Med Hosp Infant Mex. 2024;81(1):53-72. doi: 10.24875/BMHIM.23000016.

ABSTRACT

This work aimed to show which treatments showed efficacy against coronavirus disease 2019 (COVID-19); therefore, the results of 37 clinical trials started in 2020 and completed in 2021 are reviewed and discussed here. These were selected from databases, excluding vaccines, computational studies, in silico, in vitro, and those with hyperimmune sera from recovered patients. We found 34 drugs, one vitamin, and one herbal remedy with pharmacological activity against symptomatic COVID-19. They reduced mortality, disease progression, or recovery time. For each treatment, the identifier and type of trial, the severity of the disease, the sponsor, the country where the trial was conducted, and the trial results are presented. The drugs were classified according to their mechanism of action. Several drugs that reduced mortality also reduced inflammation in the most severe cases. These include some that are not considered anti-inflammatory, such as Aviptadil, pyridostigmine bromide, anakinra, imatinib, baricitinib, and bevacizumab, as well as the combination of ivermectin, aspirin, dexamethasone, and enoxaparin. Nigella sativa seeds with honey have also been reported to have therapeutic activity. On the other hand, tofacitinib, novaferon with ritonavir, and lopinavir were also effective, as well as in combination with antiviral therapies such as danoprevir with ritonavir. The natural products colchicine and Vitamin D3 were only effective in patients with mild-to-moderate COVID-19, as was hydroxychloroquine. Drug repositioning has been the main tool in the search for effective therapies by expanding the pharmacological options available to patients.

PMID:38503318 | DOI:10.24875/BMHIM.23000016

Int J Nanomedicine. 2024 Mar 14;19:2639-2653. doi: 10.2147/IJN.S442143. eCollection 2024.

ABSTRACT

INTRODUCTION: We previously identified niclosamide as a promising repurposed drug candidate for hepatocellular carcinoma (HCC) treatment. However, it is poorly water soluble, limiting its tissue bioavailability and clinical application. To overcome these challenges, we developed an orally bioavailable self-microemulsifying drug delivery system encapsulating niclosamide (Nic-SMEDDS).

METHODS: Nic-SMEDDS was synthesized and characterized for its physicochemical properties, in vivo pharmacokinetics and absorption mechanisms, and in vivo therapeutic efficacy in an orthotopic patient-derived xenograft (PDX)-HCC mouse model. Niclosamide ethanolamine salt (NEN), with superior water solubility, was used as a positive control.

RESULTS: Nic-SMEDDS (5.6% drug load) displayed favorable physicochemical properties and drug release profiles in vitro. In vivo, Nic-SMEDDS displayed prolonged retention time and plasma release profile compared to niclosamide or NEN. Oral administration of Nic-SMEDDS to non-tumor bearing mice improved niclosamide bioavailability and Cmax by 4.1- and 1.8-fold, respectively, compared to oral niclosamide. Cycloheximide pre-treatment blocked niclosamide absorption from orally administered Nic-SMEDDS, suggesting that its absorption was facilitated through the chylomicron pathway. Nic-SMEDDS (100 mg/kg, bid) showed greater anti-tumor efficacy compared to NEN (200 mg/kg, qd); this correlated with higher levels (p < 0.01) of niclosamide, increased caspase-3, and decreased Ki-67 in the harvested PDX tissues when Nic-SMEDDS was given. Biochemical analysis at the treatment end-point indicated that Nic-SMEDDS elevated lipid levels in treated mice.

CONCLUSION: We successfully developed an orally bioavailable formulation of niclosamide, which significantly enhanced oral bioavailability and anti-tumor efficacy in an HCC PDX mouse model. Our data support its clinical translation for the treatment of solid tumors.

PMID:38500681 | PMC:PMC10946447 | DOI:10.2147/IJN.S442143

Parasite Immunol. 2024 Mar;46(3):e13030. doi: 10.1111/pim.13030.

ABSTRACT

In previous studies, the inhibitory effect of chloroquine on NLRP3 inflammasome and heme production was documented. This may be employed as a double-bladed sword in schistosomiasis (anti-inflammatory and parasiticidal). In this study, chloroquine's impact on schistosomiasis mansoni was investigated. The parasitic load (worm/egg counts and reproductive capacity index [RCI]), i-Nos/Arg-1 expression, splenomegaly, hepatic insult and NLRP3-immunohistochemical expression were assessed in infected mice after receiving early and late repeated doses of chloroquine alone or dually with praziquantel. By early treatment, the least RCI was reported in dually treated mice (41.48 ± 28.58) with a significant reduction in worm/egg counts (3.50 ± 1.29/2550 ± 479.58), compared with either drug alone. A marked reduction in the splenic index was achieved by prolonged chloroquine administration (alone: 43.15 ± 5.67, dually: 36.03 ± 5.27), with significantly less fibrosis (15 ± 3.37, 14.25 ± 2.22) than after praziquantel alone (20.5 ± 2.65). Regarding inflammation, despite the praziquantel-induced significant decrease in NLRP3 expression, the inhibitory effect was marked after dual and chloroquine administration (liver: 3.13 ± 1.21/3.45 ± 1.23, spleen: 5.7 ± 1.6/4.63 ± 2.41). i-Nos RNA peaked with early/late chloroquine administration (liver: 68.53 ± 1.8/57.78 ± 7.14, spleen: 63.22 ± 2.06/62.5 ± 3.05). High i-Nos echoed with a parasiticidal and hepatoprotective effect and may indicate macrophage-1 polarisation. On the flip side, the chloroquine-induced low Arg-1 seemed to abate immune tolerance and probably macrophage-2 polarisation. Collectively, chloroquine synergised the praziquantel-schistosomicidal effect and minimised tissue inflammation, splenomegaly and hepatic fibrosis.

PMID:38498004 | DOI:10.1111/pim.13030

Brief Bioinform. 2024 Jan 22;25(2):bbae054. doi: 10.1093/bib/bbae054.

ABSTRACT

The escalating drug addiction crisis in the United States underscores the urgent need for innovative therapeutic strategies. This study embarked on an innovative and rigorous strategy to unearth potential drug repurposing candidates for opioid and cocaine addiction treatment, bridging the gap between transcriptomic data analysis and drug discovery. We initiated our approach by conducting differential gene expression analysis on addiction-related transcriptomic data to identify key genes. We propose a novel topological differentiation to identify key genes from a protein-protein interaction network derived from DEGs. This method utilizes persistent Laplacians to accurately single out pivotal nodes within the network, conducting this analysis in a multiscale manner to ensure high reliability. Through rigorous literature validation, pathway analysis and data-availability scrutiny, we identified three pivotal molecular targets, mTOR, mGluR5 and NMDAR, for drug repurposing from DrugBank. We crafted machine learning models employing two natural language processing (NLP)-based embeddings and a traditional 2D fingerprint, which demonstrated robust predictive ability in gauging binding affinities of DrugBank compounds to selected targets. Furthermore, we elucidated the interactions of promising drugs with the targets and evaluated their drug-likeness. This study delineates a multi-faceted and comprehensive analytical framework, amalgamating bioinformatics, topological data analysis and machine learning, for drug repurposing in addiction treatment, setting the stage for subsequent experimental validation. The versatility of the methods we developed allows for applications across a range of diseases and transcriptomic datasets.

PMID:38499497 | DOI:10.1093/bib/bbae054

Arch Biochem Biophys. 2024 Mar 16:109958. doi: 10.1016/j.abb.2024.109958. Online ahead of print.

ABSTRACT

The aryl hydrocarbon receptor (AhR) functions as a vital ligand-activated transcription factor, governing both physiological and pathophysiological processes. Notably, it responds to xenobiotics, leading to a diverse array of outcomes. In the context of drug repurposing, we present here a combined approach of utilizing structure-based virtual screening and molecular dynamics simulations. This approach aims to identify potential AhR modulators from Drugbank repository of clinically approved drugs. By focusing on the AhR PAS-B binding pocket, our screening protocol included binding affinities calculations, complex stability, and interactions within the binding site as a filtering method. Comprehensive evaluations of all DrugBank small molecule database revealed ten promising hits. This included flibanserin, butoconazole, luliconazole, naftifine, triclabendazole, rosiglitazone, empagliflozin, benperidol, nebivolol, and zucapsaicin. Each exhibiting diverse binding behaviors and remarkably very low binding free energy. Experimental studies further illuminated their modulation of AhR signaling, and showing that they are consistently reducing AhR activity, except for luliconazole, which intriguingly enhances the AhR activity. This work demonstrates the possibility of using computational modelling as a quick screening tool to predict new AhR modulators from extensive drug libraries. Importantly, these findings hold immense therapeutic potential for addressing AhR-associated disorders. Consequently, it offers compelling prospects for innovative interventions through drug repurposing.

PMID:38499054 | DOI:10.1016/j.abb.2024.109958

medRxiv [Preprint]. 2024 Mar 8:2024.03.07.24303921. doi: 10.1101/2024.03.07.24303921.

ABSTRACT

The co-occurrence of insulin resistance (IR)-related metabolic conditions with neuropsychiatric disorders is a complex public health challenge. Evidence of the genetic links between these phenotypes is emerging, but little is currently known about the genomic regions and biological functions that are involved. To address this, we performed Local Analysis of [co]Variant Association (LAVA) using large-scale (N=9,725-933,970) genome-wide association studies (GWASs) results for three IR-related conditions (type 2 diabetes mellitus, obesity, and metabolic syndrome) and nine neuropsychiatric disorders. Subsequently, positional and expression quantitative trait locus (eQTL)-based gene mapping and downstream functional genomic analyses were performed on the significant loci. Patterns of negative and positive local genetic correlations (|r g |=0.21-1, p FDR <0.05) were identified at 109 unique genomic regions across all phenotype pairs. Local correlations emerged even in the absence of global genetic correlations between IR-related conditions and Alzheimer's disease, bipolar disorder, and Tourette's syndrome. Genes mapped to the correlated regions showed enrichment in biological pathways integral to immune-inflammatory function, vesicle trafficking, insulin signalling, oxygen transport, and lipid metabolism. Colocalisation analyses further prioritised 10 genetically correlated regions for likely harbouring shared causal variants, displaying high deleterious or regulatory potential. These variants were found within or in close proximity to genes, such as SLC39A8 and HLA-DRB1 , that can be targeted by supplements and already known drugs, including omega-3/6 fatty acids, immunomodulatory, antihypertensive, and cholesterol-lowering drugs. Overall, our findings underscore the complex genetic landscape of IR-neuropsychiatric multimorbidity, advocating for an integrated disease model and offering novel insights for research and treatment strategies in this domain.

HIGHLIGHTS: Local genetic correlations found even in the absence of global correlations.Both positive and negative local correlations found for IR-neuropsychiatric pairs.Enrichment for immune, and insulin signalling pathways, among others.Pinpointed shared likely causal variants within 10 genomic regions.Identified therapeutic targets, e.g., SLC39A8 and HLA-DRB1, for drug repurposing.

PMID:38496672 | PMC:PMC10942494 | DOI:10.1101/2024.03.07.24303921

Bioinform Adv. 2023 Aug 23;3(1):vbad113. doi: 10.1093/bioadv/vbad113. eCollection 2023.

ABSTRACT

MOTIVATION: Structured vocabularies for drugs and diseases represent, besides their primary use for annotating scientific literature or scientific information in general, a valuable resource for visualizing aggregated information. The Medical Subject Headings (MeSH) and Anatomical Therapeutic Chemical (ATC) ontologies are widely used structured vocabularies for diseases and drugs, respectively. Their hierarchical tree-like structure can be used as a basis for creating intuitive visual displays for specific diseases and drugs within their higher-order classifications. Such displays are helpful means to contextualize diseases and drugs in various settings such as in drug repositioning. However, there are few tools that can harness the potential of these structured ontologies to create informative visual representations without extensive programming and data processing skills.

RESULTS: We have developed OntoloViz, a Graphical User Interface (GUI) for visualizing annotated lists of drugs or diseases in the context of their MeSH or ATC ontologies in an intuitively interpretable sunburst layout. Minimum input is a list of disease or drug names. Users in addition have the option to specify numerical parameters for the input lists to enhance the visualization, e.g. to visualize term frequencies. The GUI allows values to be propagated upwards in the respective ontology tree structure thus facilitating exploration of gene and drug lists. We present two use cases for OntoloViz, namely (i) a graphical representation of clinically tested drugs for coronavirus disease (COVID-19) based on ATC Classification and (ii) a graphical representation of literature annotation of human diseases on the MeSH ontology.

AVAILABILITY AND IMPLEMENTATION: The OntoloViz package can be retrieved from PyPi. The source code along with test data, template, and documentations are available at GitHub (https://github.com/Delta4AI/OntoloViz).

PMID:38496343 | PMC:PMC10941809 | DOI:10.1093/bioadv/vbad113

Cancer Med. 2024 Mar;13(5):e7049. doi: 10.1002/cam4.7049.

ABSTRACT

BACKGROUND: Due to encouraging pre-clinical data and supportive observational studies, there has been growing interest in applying cardiovascular drugs (including aspirin, angiotensin-converting enzyme [ACE] inhibitors, statins, and metformin) approved to treat diseases such as hypertension, hyperlipidemia, and diabetes mellitus to the field of oncology. Moreover, given growing costs with cancer care, these medications have offered a potentially more affordable avenue to treat or prevent recurrence of cancer. We sought to investigate the anti-cancer effects of drugs repurposed from cardiology or anti-inflammatories to treat cancer. We specifically evaluated the following drug classes: HMG-CoA reductase inhibitors (statins), cyclo-oxygenase inhibitors, aspirin, metformin, and both angiotensin receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors. We also included non-steroidal anti-inflammatory drugs (NSAIDs) because they exert a similar mechanism to aspirin by blocking prostaglandins and reducing inflammation that is thought to promote the development of cancer.

METHODS: We performed a systematic literature review using PubMed and Web of Science with search terms including "aspirin," "NSAID," "statin" (including specific statin drug names), "metformin," "ACE inhibitors," and "ARBs" (including specific anti-hypertensive drug names) in combination with "cancer." Searches were limited to human studies published between 2000 and 2023.

MAIN OUTCOMES AND MEASURES: The number and percentage of studies reported positive results and pooled estimates of overall survival, progression-free survival, response, and disease-free survival.

RESULTS: We reviewed 3094 titles and included 67 randomized clinical trials. The most common drugs that were tested were metformin (n = 21; 30.9%), celecoxib (n = 20; 29.4%), and simvastatin (n = 8; 11.8%). There was only one study that tested cardiac glycosides and none that studied ACE inhibitors. The most common tumor types were non-small-cell lung cancer (n = 19; 27.9%); breast (n = 8; 20.6%), colorectal (n = 7; 10.3%), and hepatocellular (n = 6; 8.8%). Most studies were conducted in a phase II trial (n = 38; 55.9%). Most studies were tested in metastatic cancers (n = 49; 72.1%) and in the first-line setting (n = 36; 521.9%). Four studies (5.9%) were stopped early because of difficulty with accrual. The majority of studies did not demonstrate an improvement in either progression-free survival (86.1% of studies testing progression-free survival) or in overall survival (94.3% of studies testing overall survival). Progression-free survival was improved in five studies (7.4%), and overall survival was improved in three studies (4.4%). Overall survival was significantly worse in two studies (3.8% of studies testing overall survival), and progression-free survival was worse in one study (2.8% of studies testing progression-free survival).

CONCLUSIONS AND RELEVANCE: Despite promising pre-clinical and population-based data, cardiovascular drugs and anti-inflammatory medications have overall not demonstrated benefit in the treatment or preventing recurrence of cancer. These findings may help guide future potential clinical trials involving these medications when applied in oncology.

PMID:38491813 | DOI:10.1002/cam4.7049

Sci Rep. 2024 Mar 15;14(1):6280. doi: 10.1038/s41598-024-55801-3.

ABSTRACT

Amiodarone repositioning in cancer treatment is promising, however toxicity limits seem to arise, constraining its exploitability. Notably, amiodarone has been investigated for the treatment of ovarian cancer, a tumour known for metastasizing within the peritoneal cavity. This is associated with an increase of fatty acid oxidation, which strongly depends on CPT1A, a transport protein which has been found overexpressed in ovarian cancer. Amiodarone is an inhibitor of CPT1A but its role still has to be explored. Therefore, in the present study, amiodarone was tested on ovarian cancer cell lines with a focus on lipid alteration, confirming its activity. Moreover, considering that drug delivery systems could lower drug side effects, microfluidics was employed for the development of drug delivery systems of amiodarone obtaining simultaneously liposomes with a high payload and amiodarone particles. Prior to amiodarone loading, microfluidics production was optimized in term of temperature and flow rate ratio. Moreover, stability over time of particles was evaluated. In vitro tests confirmed the efficacy of the drug delivery systems.

PMID:38491077 | DOI:10.1038/s41598-024-55801-3

Virus Res. 2024 Mar 13:199356. doi: 10.1016/j.virusres.2024.199356. Online ahead of print.

ABSTRACT

Coronaviruses contain one of the largest genomes among the RNA viruses, coding for 14-16 non-structural proteins (nsp) that are involved in proteolytic processing, genome replication and transcription, and four structural proteins that build the core of the mature virion. Due to conservation across coronaviruses, nsps form a group of promising drug targets as their inhibition directly affects viral replication and, therefore, progression of infection. A minimal but fully functional replication and transcription complex was shown to be formed by one RNA-dependent RNA polymerase (nsp12), one nsp7, two nsp8 accessory subunits, and two helicase (nsp13) enzymes. Our approach involved, targeting nsp12 and nsp13 to allow multiple starting point to interfere with virus infection progression. Here we report a combined in-vitro repurposing screening approach, identifying new and confirming reported SARS-CoV-2 nsp12 and nsp13 inhibitors.

PMID:38490582 | DOI:10.1016/j.virusres.2024.199356

PLoS One. 2024 Mar 15;19(3):e0298127. doi: 10.1371/journal.pone.0298127. eCollection 2024.

ABSTRACT

BACKGROUND: Ovarian Cancer (OC) stands as the most lethal gynecological malignancy, presenting an urgent clinical challenge in the quest to improve response rates. One approach to address this challenge is through drug repurposing, exemplified by the investigation of metabolic-modulating drugs such as Metformin (MTF) and Simvastatin (SIM). This study aims to explore the molecular mechanisms contributing to the potential synergistic anti-cancer effects between MTF and SIM on ovarian cancer cells.

METHODS: We assessed the effects of the combination on the proliferation and viability of two cell lines OVCAR-3 and SKOV-3. IC50 concentrations of MTF and SIM were determined using a proliferation assay, followed by subtoxic concentrations to explore the potential synergistic effects on the viability of both cell lines. Transcriptomic analysis was conducted on OVCAR-3 treated cells, and the findings were validated by assessing the expression levels of differentially expressed genes (DEGs) through real-time PCR in both cell lines SK-OV-3 and OVCAR-3.

RESULTS: Cytotoxicity analysis guided the selection of treatment concentrations as such MTF 10 mM and SIM 5 μM. The combined treatment of MTF and SIM demonstrated a synergistic inhibition of proliferation and viability in both cell lines. In OVCAR-3, exclusive identification of 507 DEGs was seen in the combination arm. Upregulation of FOXO3, RhoA, and TNFα, along with downregulation of PIK3R1, SKP2, and ATP6V1D levels, was observed in OVCAR-3 treated cells. Real-time PCR validation confirmed the consistency of expression levels for the mentioned DEGs.

CONCLUSION: Our data strongly supports the presence of synergy between MTF and SIM in OC cells. The combination's effect is associated with the dysregulation of genes in the key regulators AMPK and mTOR alongside other interconnected pathways.

PMID:38489280 | DOI:10.1371/journal.pone.0298127

Biofactors. 2024 Mar 15. doi: 10.1002/biof.2050. Online ahead of print.

ABSTRACT

Currently, a diagnosis with KRAS mutant pancreatic ductal adenocarcinoma (PDAC) means a death warrant, so finding efficient therapeutic options is a pressing issue. Here, we presented that pharmacologic ascorbate, chloroquine and resveratrol co-treatment exerted a synergistic cytotoxic effect on PDAC cell lines. The observed synergistic cytotoxicity was a general feature in all investigated cancer cell lines independent of the KRAS mutational status and seems to be independent of the autophagy inhibitory effect of chloroquine. Furthermore, it seems that apoptosis and necroptosis are also not likely to play any role in the cytotoxicity of chloroquine. Both pharmacologic ascorbate and resveratrol caused double-strand DNA breaks accompanied by cell cycle arrest. It seems resveratrol-induced cytotoxicity is independent of reactive oxygen species (ROS) generation and accompanied by a significant elevation of caspase-3/7 activity, while pharmacologic ascorbate-induced cytotoxicity shows strong ROS dependence but proved to be caspase-independent. Our results are particularly important since ascorbate and resveratrol are natural compounds without significant harmful effects on normal cells, and chloroquine is a known antimalarial drug that can easily be repurposed.

PMID:38488303 | DOI:10.1002/biof.2050

Sci Rep. 2024 Mar 14;14(1):6180. doi: 10.1038/s41598-024-56524-1.

ABSTRACT

Long non-coding RNA (lncRNA) regulates many physiological processes by acting as competitive endogenous RNA (ceRNA). The dysregulation of lncRNA X-inactive specific transcript (XIST) has been shown in various human disorders. However, its role in the pathogenesis of polycystic ovary syndrome (PCOS) is yet to be explored. This study aimed to explore the underlying mechanism of XIST in the pathogenesis of PCOS, specifically through dataset functional analysis. GEO PCOS datasets including RNA-seq, microarray, and miRNA-seq in granulosa cells (GCs) and blood, were examined and comprehensively analyzed. Enrichment analysis, ROC curve constructions, lncRNA-miRNA-mRNA interaction network analyses, and qRT-PCR validation were performed followed by a series of drug signature screenings. Our results revealed significant dysregulation in the expression of 1131 mRNAs, 30 miRNAs, and XIST in GCs of PCOS patients compared to healthy individuals. Of the120 XIST-correlated upregulated genes, 25 were enriched in inflammation-related pathways. Additionally, 5 miRNAs were identified as negative regulators of XIST-correlated genes. Accordingly, a ceRNA network containing XIST-miRNAs-mRNAs interactions was constructed. Furthermore, 6 genes, including AQP9, ETS2, PLAU, PLEK, SOCS3, and TNFRSF1B served as both GCs and blood-based biomarkers. By analyzing the number of interactions among XIST, miRNAs, and mRNAs, we pinpointed ETS2 as the pivotal gene within the ceRNA network. Our findings reveal a novel XIST- hsa-miR-146a-5p, hsa-miR-144-3p, and hsa-miR-1271-5p-ETS2 axis that comprehensively elucidates the XIST-associated mechanism underlying PCOS onset. qRT-PCR analysis further confirmed the, overexpression of both XIST and ETS2 . Furthermore, our results demonstrated that XIST and ETS2 were correlated with some assisted reproductive technologies outcomes. Finally, we identified two novel compounds including, methotrexate/folate and threonine using drug-gene interaction databases for PCOS management. These findings provide novel insights into the molecular etiology, diagnosis, and potential therapeutic interventions for PCOS.

PMID:38486041 | DOI:10.1038/s41598-024-56524-1