Acta Trop. 2023 Apr 5:106920. doi: 10.1016/j.actatropica.2023.106920. Online ahead of print.

ABSTRACT

Benznidazole and nifurtimox are the drugs currently used for the treatment of Chagas disease, however its side effects may affect patient adherence. In the search for new alternative therapies, we previously identified isotretinoin (ISO), an FDA-approved drug widely used for the treatment of severe acne through a drug repurposing strategy. ISO shows a strong activity against Trypanosoma cruzi parasites in the nanomolar range, and its mechanism of action is through the inhibition of T. cruzi polyamine and amino acid transporters from the Amino Acid/Auxin Permeases (AAAP) family. In this work, a murine model of chronic Chagas disease (C57BL/6J mice), intraperitoneally infected with T. cruzi Nicaragua isolate (DTU TcI), were treated with different oral administrations of ISO: daily doses of 5 mg/kg/day for 30 days and weekly doses of 10 mg/kg during 13 weeks. The efficacy of the treatments was evaluated by monitoring blood parasitemia by qPCR, anti-T. cruzi antibodies by ELISA, and cardiac abnormalities by electrocardiography. No parasites were detected in blood after any of the ISO treatments. The electrocardiographic study of the untreated chronic mice showed a significant decrease in heart rate, while in the treated mice this negative chronotropic effect was not observed. Atrioventricular nodal conduction time in untreated mice was significantly longer than in treated animals. Mice treated even with ISO 10 mg/kg dose every 7 days, showed a significant reduction in anti-T. cruzi IgG levels. In conclusion, the intermittent administration of ISO 10 mg/kg would improve myocardial compromise during the chronic stage.

PMID:37028584 | DOI:10.1016/j.actatropica.2023.106920

IEEE/ACM Trans Comput Biol Bioinform. 2023 Mar 8;PP. doi: 10.1109/TCBB.2023.3254163. Online ahead of print.

ABSTRACT

The computational drug repositioning aims to discover new uses for marketed drugs, which can accelerate the drug development process and play an important role in the existing drug discovery system. However, the number of validated drug-disease associations is scarce compared to the number of drugs and diseases in the real world. Too few labeled samples will make the classification model unable to learn effective latent factors of drugs, resulting in poor generalization performance. In this work, we propose a multi-task self-supervised learning framework for computational drug repositioning. The framework tackles label sparsity by learning a better drug representation. Specifically, we take the drug-disease association prediction problem as the main task, and the auxiliary task is to use data augmentation strategies and contrast learning to mine the internal relationships of the original drug features, so as to automatically learn a better drug representation without supervised labels. And through joint training, it is ensured that the auxiliary task can improve the prediction accuracy of the main task. More precisely, the auxiliary task improves drug representation and serving as additional regularization to improve generalization. Furthermore, we design a multi-input decoding network to improve the reconstruction ability of the autoencoder model. We evaluate our model using three real-world datasets. The experimental results demonstrate the effectiveness of the multi-task self-supervised learning framework, and its predictive ability is superior to the state-of-the-art model.

PMID:37028367 | DOI:10.1109/TCBB.2023.3254163

Crit Care Explor. 2023 Apr 3;5(4):e0893. doi: 10.1097/CCE.0000000000000893. eCollection 2023 Apr.

ABSTRACT

COVID-19 highlighted the need for use of real-world data (RWD) in critical care as a near real-time resource for clinical, research, and policy efforts. Analysis of RWD is gaining momentum and can generate important evidence for policy makers and regulators. Extracting high quality RWD from electronic health records (EHRs) requires sophisticated infrastructure and dedicated resources. We sought to customize freely available public tools, supporting all phases of data harmonization, from data quality assessments to de-identification procedures, and generation of robust, data science ready RWD from EHRs. These data are made available to clinicians and researchers through CURE ID, a free platform which facilitates access to case reports of challenging clinical cases and repurposed treatments hosted by the National Center for Advancing Translational Sciences/National Institutes of Health in partnership with the Food and Drug Administration. This commentary describes the partnership, rationale, process, use case, impact in critical care, and future directions for this collaborative effort.

PMID:37025303 | PMC:PMC10072311 | DOI:10.1097/CCE.0000000000000893

Methods Mol Biol. 2023;2658:127-143. doi: 10.1007/978-1-0716-3155-3_9.

ABSTRACT

Drug target identification is an essential component to antifungal drug development. Many methods, including large chemical library screening, natural product screening, and drug repurposing efforts, can identify compounds with favorable in vitro antifungal activity. However, these approaches will often identify compounds with no known mechanism of action. Herein, we describe a method utilizing the human fungal pathogen Cryptococcus neoformans to identify antifungal drug targets through the isolation of spontaneous resistant mutants, antifungal testing, whole-genome sequencing, and variant analysis.

PMID:37024699 | DOI:10.1007/978-1-0716-3155-3_9

J Chem Inf Model. 2023 Apr 6. doi: 10.1021/acs.jcim.2c01291. Online ahead of print.

ABSTRACT

Drug repurposing or repositioning (DR) refers to finding new therapeutic applications for existing drugs. Current computational DR methods face data representation and negative data sampling challenges. Although retrospective studies attempt to operate various representations, it is a crucial step for an accurate prediction to aggregate these features and bring the associations between drugs and diseases into a unified latent space. In addition, the number of unknown associations between drugs and diseases, which is considered negative data, is much higher than the number of known associations, or positive data, leading to an imbalanced dataset. In this regard, we propose the DrugRep-KG method, which applies a knowledge graph embedding approach for representing drugs and diseases, to address these challenges. Despite the typical DR methods that consider all unknown drug-disease associations as negative data, we select a subset of unknown associations, provided the disease occurs because of an adverse reaction to a drug. DrugRep-KG has been evaluated based on different settings and achieves an AUC-ROC (area under the receiver operating characteristic curve) of 90.83% and an AUC-PR (area under the precision-recall curve) of 90.10%, which are higher than in previous works. Besides, we checked the performance of our framework in finding potential drugs for coronavirus infection and skin-related diseases: contact dermatitis and atopic eczema. DrugRep-KG predicted beclomethasone for contact dermatitis, and fluorometholone, clocortolone, fluocinonide, and beclomethasone for atopic eczema, all of which have previously been proven to be effective in other studies. Fluorometholone for contact dermatitis is a novel suggestion by DrugRep-KG that should be validated experimentally. DrugRep-KG also predicted the associations between COVID-19 and potential treatments suggested by DrugBank, in addition to new drug candidates provided with experimental evidence. The data and code underlying this article are available at https://github.com/CBRC-lab/DrugRep-KG.

PMID:37023229 | DOI:10.1021/acs.jcim.2c01291

Expert Opin Drug Discov. 2023 Apr 6:1-9. doi: 10.1080/17460441.2023.2198700. Online ahead of print.

ABSTRACT

INTRODUCTION: Over the last decades, there has been substantial debate around the apparent drop in productivity in the pharmaceutical sector. The development of second or further medical uses for known drugs is a possible answer to expedite the development of new therapeutic solutions. Computational methods are among the main strategies for exploring drug repurposing opportunities in a systematic manner.

AREAS COVERED: This article reviews three general approximations to systematically discover new therapeutic uses for existing drugs: disease-, target-, and drug-centric approaches, along with some recently reported computational methods associated with them.

EXPERT OPINION: Computational methods are essential for organizing and analyzing the large volume of available biomedical data, which has grown exponentially in the era of big data. The clearest trend in the field involves the use of integrative approaches where different types of data are combined into multipartite networks. Every aspect of computer-guided drug repositioning has currently incorporated state-of-the-art machine learning tools to boost their pattern recognition and predictive capabilities. Remarkably, a majority of the recently reported platforms are publicly available as web apps or open-source software. The introduction of nationwide electronic health records provides invaluable real-world data to detect unknown relationships between approved drug treatments and diseases.

PMID:37021703 | DOI:10.1080/17460441.2023.2198700

J Biomol Struct Dyn. 2023 Apr 5:1-39. doi: 10.1080/07391102.2023.2192797. Online ahead of print.

ABSTRACT

The COVID-19 pandemic has caused adverse health (severe respiratory, enteric and systemic infections) and environmental impacts that have threatened public health and the economy worldwide. Drug repurposing and small molecule multi-target directed herbal medicine therapeutic approaches are the most appropriate exploration strategies for SARS-CoV-2 drug discovery. This study identified potential multi-target-directed Parkia bioactive entities against SARS-CoV-2 receptors (S-protein, ACE2, TMPRSS2, RBD/ACE2, RdRp, MPro, and PLPro) using ADMET, drug-likeness, molecular docking (AutoDock, FireDock and HDOCK), molecular dynamics simulation and MM-PBSA tools. One thousand Parkia bioactive entities were screened out by virtual screening and forty-five bioactive phytomolecules were selected based on favorable binding affinity and acceptable pharmacokinetic and pharmacodynamics properties. The binding affinity values of Parkia phyto-ligands (AutoDock: -6.00--10.40 kcal/mol; FireDock: -31.00--62.02 kcal/mol; and HDOCK: -150.0--294.93 kcal/mol) were observed to be higher than the reference antiviral drugs (AutoDock: -5.90--9.10 kcal/mol; FireDock: -35.64--59.35 kcal/mol; and HDOCK: -132.82--211.87 kcal/mol), suggesting a potent modulatory action of Parkia bioactive entities against the SARS-CoV-2. Didymin, rutin, epigallocatechin gallate, epicatechin-3-0-gallate, hyperin, ursolic acid, lupeol, stigmasta-5,24(28)-diene-3-ol, ellagic acid, apigenin, stigmasterol, and campesterol strongly bound with the multiple targets of the SARS-CoV-2 receptors, inhibiting viral entry, attachment, binding, replication, transcription, maturation, packaging and spread. Furthermore, ACE2, TMPRSS2, and MPro receptors possess significant molecular dynamic properties, including stability, compactness, flexibility and total binding energy. Residues GLU-589, and LEU-95 of ACE2, GLN-350, HIS-186, and ASP-257 of TMPRSS2, and GLU-14, MET-49, and GLN-189 of MPro receptors contributed to the formation of hydrogen bonds and binding interactions, playing vital roles in inhibiting the activity of the receptors. Promising results were achieved by developing multi-targeted antiviral Parkia bioactive entities as lead and prospective candidates under a small molecule strategy against SARS-CoV-2 pathogenesis. The antiviral activity of Parkia bioactive entities needs to be further validated by pre-clinical and clinical trials.

PMID:37021347 | DOI:10.1080/07391102.2023.2192797

iScience. 2023 Mar 21;26(4):106460. doi: 10.1016/j.isci.2023.106460. eCollection 2023 Apr 21.

ABSTRACT

The abundance of biomedical knowledge gained from biological experiments and clinical practices is an invaluable resource for biomedicine. The emerging biomedical knowledge graphs (BKGs) provide an efficient and effective way to manage the abundant knowledge in biomedical and life science. In this study, we created a comprehensive BKG called the integrative Biomedical Knowledge Hub (iBKH) by harmonizing and integrating information from diverse biomedical resources. To make iBKH easily accessible for biomedical research, we developed a web-based, user-friendly graphical portal that allows fast and interactive knowledge retrieval. Additionally, we also implemented an efficient and scalable graph learning pipeline for discovering novel biomedical knowledge in iBKH. As a proof of concept, we performed our iBKH-based method for computational in-silico drug repurposing for Alzheimer's disease. The iBKH is publicly available.

PMID:37020958 | PMC:PMC10068563 | DOI:10.1016/j.isci.2023.106460

Oncogene. 2023 Apr 5. doi: 10.1038/s41388-023-02679-6. Online ahead of print.

ABSTRACT

Ovarian cancer is the leading cause of death among gynecological malignancies. Checkpoint blockade immunotherapy has so far only shown modest efficacy in ovarian cancer and platinum-based chemotherapy remains the front-line treatment. Development of platinum resistance is one of the most important factors contributing to ovarian cancer recurrence and mortality. Through kinome-wide synthetic lethal RNAi screening combined with unbiased datamining of cell line platinum response in CCLE and GDSC databases, here we report that Src-Related Kinase Lacking C-Terminal Regulatory Tyrosine And N-Terminal Myristylation Sites (SRMS), a non-receptor tyrosine kinase, is a novel negative regulator of MKK4-JNK signaling under platinum treatment and plays an important role in dictating platinum efficacy in ovarian cancer. Suppressing SRMS specifically sensitizes p53-deficient ovarian cancer cells to platinum in vitro and in vivo. Mechanistically, SRMS serves as a "sensor" for platinum-induced ROS. Platinum treatment-induced ROS activates SRMS, which inhibits MKK4 kinase activity by directly phosphorylating MKK4 at Y269 and Y307, and consequently attenuates MKK4-JNK activation. Suppressing SRMS leads to enhanced MKK4-JNK-mediated apoptosis by inhibiting MCL1 transcription, thereby boosting platinum efficacy. Importantly, through a "drug repurposing" strategy, we uncovered that PLX4720, a small molecular selective inhibitor of B-RafV600E, is a novel SRMS inhibitor that can potently boost platinum efficacy in ovarian cancer in vitro and in vivo. Therefore, targeting SRMS with PLX4720 holds the promise to improve the efficacy of platinum-based chemotherapy and overcome chemoresistance in ovarian cancer.

PMID:37020040 | DOI:10.1038/s41388-023-02679-6

IEEE/ACM Trans Comput Biol Bioinform. 2023 Jan 5;PP. doi: 10.1109/TCBB.2023.3234331. Online ahead of print.

ABSTRACT

Drug repositioning is an important approach for predicting new disease indications of the existing drugs in drug discovery. A great progress has been achieved in drug repositioning. However, effectively utilizing the localized neighborhood interaction features of drug and disease in drug-disease associations remains challenging. This paper proposes a neighborhood interaction-based method called NetPro for drug repositioning via label propagation. In NetPro, we first formulate the known drug-disease associations, various disease and drug similarities from different perspectives to construct drug-drug and disease-disease networks. Meanwhile we employ the nearest neighbors and their interactions in the constructed networks to devise a new approach for computing drug similarity and disease similarity. To implement the prediction of new drugs or diseases, a preprocessing step is applied to renew the known drug-disease associations using our calculated drug and disease similarities. We then employ a label propagation model to predict drug-disease associations by the drug and disease linear neighborhood similarities derived from the renewed drug-disease associations. The experimental results on three benchmark datasets show that NetPro can effectively identify potential drug-disease associations and achieve better prediction performance than the existing methods. Case studies further demonstrate that NetPro is capable of predicting promising candidate disease indications for drugs.

PMID:37018341 | DOI:10.1109/TCBB.2023.3234331

Eur Neuropsychopharmacol. 2023 Apr 4;71:96-108. doi: 10.1016/j.euroneuro.2023.03.011. Online ahead of print.

ABSTRACT

The World Health Organization has proposed that a search be made for alternatives to vaccines for the prevention and treatment of COVID-19, with one such alternative being selective serotonin reuptake inhibitors (SSRIs). This study thus sought to assess: the impact of previous treatment with SSRI antidepressants on the severity of COVID-19 (risk of hospitalisation, admission to an intensive care unit [ICU], and mortality), its influence on susceptibility to SARS-CoV-2 and progression to severe COVID-19. We conducted a population-based multiple case-control study in a region in the north-west of Spain. Data were sourced from electronic health records. Adjusted odds ratios (aORs) and 95%CIs were calculated using multilevel logistic regression. We collected data from a total of 86,602 subjects: 3060 cases PCR+, 26,757 non-hospitalised cases PCR+ and 56,785 controls (without PCR+). Citalopram displayed a statistically significant decrease in the risk of hospitalisation (aOR=0.70; 95% CI 0.49-0.99, p = 0.049) and progression to severe COVID-19 (aOR=0.64; 95% CI 0.43-0.96, p = 0.032). Paroxetine was associated with a statistically significant decrease in risk of mortality (aOR=0.34; 95% CI 0.12 - 0.94, p = 0.039). No class effect was observed for SSRIs overall, nor was any other effect found for the remaining SSRIs. The results of this large-scale, real-world data study indicate that, citalopram, could be a candidate drug for being repurposed as preventive treatment aimed at reducing COVID-19 patients' risk of progressing to severe stages of the disease.

PMID:37094487 | DOI:10.1016/j.euroneuro.2023.03.011

IEEE Trans Biomed Eng. 2022 Dec 23;PP. doi: 10.1109/TBME.2022.3231835. Online ahead of print.

ABSTRACT

OBJECTIVE: Multicellular tumor spheroids (MCTs) are indispensable models for evaluating drug efficacy for precision cancer therapeutic strategies as well as for repurposing FDA-approved drugs for ovarian cancer. However, current imaging techniques cannot provide effective monitoring of pathological responses due to shallow penetration and experimentally operative destruction. We plan to utilize a noninvasive optical imaging tool to achieve in vivo longitudinal monitoring of the growth of MCTs and therapeutic responses to repurpose three FDA-approved drugs for ovarian cancer therapy.

METHODS: A swept-source optical coherence tomography (SS-OCT) system was used to monitor the volume growth of MCTs over 11 days. Three inhibitors of 2-Methoxyestradiol (2-ME), AZD1208, and R-Ketorolac (R-keto) with concentrations of 1, 10, and 25 µM were employed to treat ovarian MCTs on day 5. Three-dimensional (3D), intrinsic optical attenuation contrast, and degree of uniformity were applied to analyze the therapeutic effect of these inhibitors on ovarian MCTs.

RESULTS: We found that 2-ME, AZD1208, and R-keto with concentration of 10 and 25 µM significantly inhibited the volume growth of ovarian MCTs. There was no effect to necrotic tissues from all concentrations of 2-ME, AZD1208, and R-keto inhibitors from our OCT results. 2-ME and AZD1208 inhibited the growth of high uniformity tissues within MCTs and higher concentrations provided more significant inhibitory effects.

CONCLUSION: Our results indicated that OCT was capable and reliable to monitor the therapeutic effect of inhibitors to ovarian MCTs and it can be used for the rapid characterization of novel therapeutics for ovarian cancers in the future.

PMID:37015385 | DOI:10.1109/TBME.2022.3231835

J Neural Transm (Vienna). 2023 Apr 4. doi: 10.1007/s00702-023-02618-5. Online ahead of print.

ABSTRACT

Therapeutic approaches providing effective medication for Alzheimer's disease (AD) patients after disease onset are urgently needed. Previous studies in AD mouse models and in humans suggested that physical exercise or changed lifestyle can delay AD-related synaptic and memory dysfunctions when treatment started in juvenile animals or in elderly humans before onset of disease symptoms. However, a pharmacological treatment that can reverse memory deficits in AD patients was thus far not identified. Importantly, AD disease-related dysfunctions have increasingly been associated with neuro-inflammatory mechanisms and searching for anti-inflammatory medication to treat AD seems promising. Like for other diseases, repurposing of FDA-approved drugs for treatment of AD is an ideally suited strategy to reduce the time to bring such medication into clinical practice. Of note, the sphingosine-1-phosphate analogue fingolimod (FTY720) was FDA-approved in 2010 for treatment of multiple sclerosis patients. It binds to the five different isoforms of Sphingosine-1-phosphate receptors (S1PRs) that are widely distributed across human organs. Interestingly, recent studies in five different mouse models of AD suggest that FTY720 treatment, even when starting after onset of AD symptoms, can reverse synaptic deficits and memory dysfunction in these AD mouse models. Furthermore, a very recent multi-omics study identified mutations in the sphingosine/ceramide pathway as a risk factor for sporadic AD, suggesting S1PRs as promising drug target in AD patients. Therefore, progressing with FDA-approved S1PR modulators into human clinical trials might pave the way for these potential disease modifying anti-AD drugs.

PMID:37014414 | DOI:10.1007/s00702-023-02618-5

J Gen Virol. 2023 Apr;104(4). doi: 10.1099/jgv.0.001838.

ABSTRACT

Drug repurposing is a valuable source of new antivirals because many compounds used to treat a variety of pathologies can also inhibit viral infections. In this work, we have tested the antiviral capacity of four repurposed drugs to treat Bunyamwera virus (BUNV) infection in cell cultures. BUNV is the prototype of the Bunyavirales order, a large group of RNA viruses that includes important pathogens for humans, animals and plants. Mock- and BUNV-infected Vero and HEK293T cells were treated with non-toxic concentrations of digoxin, cyclosporin A, sunitinib and chloroquine. The four drugs inhibited BUNV infection with varying potency in Vero cells, and all except sunitinib also in HEK293T cells, with digoxin rendering the lowest half maximal inhibitory concentration (IC50). Since digoxin rendered the best results, we selected this drug for a more detailed study. Digoxin is an inhibitor of the Na+/K+ ATPase, a plasma membrane enzyme responsible for the energy-dependent exchange of cytoplasmic Na+ for extracellular K+ in mammalian cells and involved in many signalling pathways. Digoxin was shown to act at an early time point after viral entry reducing the expression of the viral proteins Gc and N. Effects on the cell cycle caused by BUNV and digoxin were also analysed. In Vero cells, digoxin favoured the transition from G1 phase of the cell cycle to S phase, an effect that might contribute to the anti-BUNV effect of digoxin in this cell type. Transmission electron microscopy showed that digoxin impedes the assembly of the characteristic spherules that harbour the BUNV replication complexes and the morphogenesis of new viral particles. Both BUNV and digoxin induce similar changes in the morphology of mitochondria that become more electron-dense and have swollen cristae. The alterations of this essential organelle might be one of the factors responsible for digoxin-induced inhibition of viral infection. Digoxin did not inhibit BUNV infection in BHK-21 cells that have a digoxin-resistant Na+/K+ ATPase, which suggests that the effects of the blockade of this enzyme is a key factor of the antiviral activity of digoxin in BUNV-infected Vero cells.

PMID:37010894 | DOI:10.1099/jgv.0.001838

Front Med (Lausanne). 2023 Mar 16;10:1159815. doi: 10.3389/fmed.2023.1159815. eCollection 2023.

NO ABSTRACT

PMID:37007777 | PMC:PMC10061064 | DOI:10.3389/fmed.2023.1159815

Curr Microbiol. 2023 Apr 1;80(5):160. doi: 10.1007/s00284-023-03242-y.

ABSTRACT

Infectious diseases are among the leading causes of morbidity and mortality worldwide. Combating them becomes more complex when caused by the pathogens of the ESKAPE group, which are Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp. The purpose of this study was to investigate the repositioning potential of the benzodiazepines clonazepam and diazepam individually and in combination with the antibacterial ciprofloxacin against ESKAPE. The minimum inhibitory concentration and minimum bactericidal concentration against seven American Type Culture Collection (ATCC) reference standard strains and 64 ESKAPE clinical isolates were determined. In addition, the interaction with ciprofloxacin was determined by the checkerboard method and fractional inhibitory concentration index (FICI) of clonazepam against 11 ESKAPE and diazepam against five ESKAPE. We also list the results found and their clinical significance. Benzodiazepines showed similar antibacterial activity against Gram-positive and Gram-negative. The checkerboard and FICI results showed a synergistic effect of these drugs when associated with ciprofloxacin against almost all tested isolates. Viewing the clinical cases studied, benzodiazepines have potential as treatment alternatives. The results allow us to conclude that clonazepam and diazepam, when in combination with ciprofloxacin, have promising activity against ESKAPE, therefore, assuming the position of candidates for repositioning.

PMID:37004588 | DOI:10.1007/s00284-023-03242-y

Biomed Pharmacother. 2023 May;161:114491. doi: 10.1016/j.biopha.2023.114491. Epub 2023 Mar 13.

ABSTRACT

Numerous cancers express platelet-derived growth factors (PDGFs) and PDGF receptors (PDGFRs). By directly stimulating tumour cells in an autocrine manner or by stimulating tumour stromal cells in a paracrine manner, the platelet-derived growth factor (PDGF)/platelet-derived growth factor receptor (PDGFR) pathway is crucial in the growth and spread of several cancers. To combat hypoxia in the tumour microenvironment, it encourages angiogenesis. A growing body of experimental data shows that PDGFs target malignant cells, vascular cells, and stromal cells to modulate tumour growth, metastasis, and the tumour microenvironment. To combat medication resistance and enhance patient outcomes in cancers, targeting the PDGF/PDGFR pathway is a viable therapeutic approach. There have been reports of anomalies in the PDGF pathway, including the gain of function point mutations, activating chromosomal translocations, or overexpression or amplification of PDGF receptors (PDGFRs). As a result, it has been shown that targeting the PDGF/PDGFR signaling pathway is an effective method for treating cancer. As a result, this study will concentrate on the regulation of the PDGF/PDGFR signaling system, in particular the current methods and inhibitors used in cancer treatment, as well as the associated therapeutic advantages and side effects.

PMID:37002577 | DOI:10.1016/j.biopha.2023.114491

Biochim Biophys Acta Rev Cancer. 2023 Mar 29:188888. doi: 10.1016/j.bbcan.2023.188888. Online ahead of print.

ABSTRACT

The process of angiogenesis is well described for its potential role in the development of normal ovaries, and physiological functions as well as in the initiation, progression, and metastasis of ovarian cancer (OC). In advanced stages of OC, cancer cells spread outside the ovary to the pelvic, abdomen, lung, or multiple secondary sites. This seriously limits the efficacy of therapeutic options contributing to fatal clinical outcomes. Notably, a variety of angiogenic effectors are produced by the tumor cells to initiate angiogenic processes leading to the development of new blood vessels, which provide essential resources for tumor survival, dissemination, and dormant micro-metastasis of tumor cells. Multiple proangiogenic effectors and their signaling axis have been discovered and functionally characterized for potential clinical utility in OC. In this review, we have provided the current updates on classical and emerging proangiogenic effectors, their signaling axis, and the immune microenvironment contributing to the pathogenesis of OC. Moreover, we have comprehensively reviewed and discussed the significance of the preclinical strategies, drug repurposing, and clinical trials targeting the angiogenic processes that hold promising perspectives for the better management of patients with OC.

PMID:37001618 | DOI:10.1016/j.bbcan.2023.188888

PLoS One. 2023 Mar 31;18(3):e0283743. doi: 10.1371/journal.pone.0283743. eCollection 2023.

ABSTRACT

Peroxisome proliferator-activated receptors (PPARs) are nuclear receptors, and their activation has been proven to treat mild liver fibrosis, reduce steatosis, inflammation, and the extrahepatic effects of chronic liver disease. Considering the significance of the PPARs, it is targeted for the treatment of Non-Alcoholic Steatohepatitis (NASH), for which currently there is no FDA-approved drug. Lanifibranor is a next-generation highly potential indole sulfonamide derivative that is presently in clinical trial phase III as an anti-NASH drug which fully activates PPARα and PPARδ and partially activates PPARγ. In the current study, a comprehensive computational investigation including 3D-QSAR pharmacophore modeling, MD simulations and binding free energy calculations is performed to get insights into the activation mechanism of the Lanifibranor. Furthermore, FDA-approved drugs were explored for repurposing through virtual screening against each PPAR pharmacophore to identify potential drug candidates. Forasartan, Raltitrexed, and Lifitegrast stood out as potential agonists for PPARα (full agonist), PPARγ (partial agonist), and PPARδ (full agonist), respectively. The findings of the study highlighted a lack of hydrogen bond acceptor feature in Raltitrexed and Lanifibranor which is responsible for partial activation of PPARγ that plays a critical role in preventing lipid accumulation. In addition to this, the significant role of AF2 domain in full and partial activation of PPARs through electrostatic interactions was also revealed, that facilitates the anchoring of ligand within the binding cavity. Moreover, common chemical scaffolds (methyl sulfonyl benzene, butyric acid, and chlorobenzene) identified using Fingerprinting technique were presented in this study which hold the potential to aid in the design and development of target specific novel Pan PPAR medications in future.

PMID:37000796 | DOI:10.1371/journal.pone.0283743

Cell Rep. 2023 Mar 30;42(4):112324. doi: 10.1016/j.celrep.2023.112324. Online ahead of print.

ABSTRACT

Patient-derived organoids (PDOs) are widely heralded as a drug-screening platform to develop new anti-cancer therapies. Here, we use a drug-repurposing library to screen PDOs of colorectal cancer (CRC) to identify hidden vulnerabilities within therapy-induced phenotypes. Using a microscopy-based screen that accurately scores drug-induced cell killing, we have tested 414 putative anti-cancer drugs for their ability to switch the EGFRi/MEKi-induced cytostatic phenotype toward cytotoxicity. A majority of validated hits (9/37) are microtubule-targeting agents that are commonly used in clinical oncology, such as taxanes and vinca-alkaloids. One of these drugs, vinorelbine, is consistently effective across a panel of >25 different CRC PDOs, independent of RAS mutational status. Unlike vinorelbine alone, its combination with EGFR/MEK inhibition induces apoptosis at all stages of the cell cycle and shows tolerability and effective anti-tumor activity in vivo, setting the basis for a clinical trial to treat patients with metastatic RAS-mutant CRC.

PMID:37000626 | DOI:10.1016/j.celrep.2023.112324