Blood Cancer J. 2023 Feb 17;13(1):28. doi: 10.1038/s41408-023-00798-7.

ABSTRACT

Monoclonal gammopathy of undetermined significance (MGUS) is a benign hematological condition with the potential to progress to malignant conditions including multiple myeloma and Waldenstrom macroglobulinemia. Medications that modify progression risk have yet to be identified. To investigate, we leveraged machine-learning and electronic health record (EHR) data to screen for drug repurposing candidates. We extracted clinical and laboratory data from a manually curated MGUS database, containing 16,752 MGUS patients diagnosed from January 1, 2000 through December 31, 2021, prospectively maintained at Mayo Clinic. We merged this with comorbidity and medication data from the EHR. Medications were mapped to 21 drug classes of interest. The XGBoost module was then used to train a primary Cox survival model; sensitivity analyses were also performed limiting the study group to those with non-IgM MGUS and those with M-spikes >0.3 g/dl. The impact of explanatory features was quantified as hazard ratios after generating distributions using bootstrapping. Medication data were available for 12,253 patients; those without medications data were excluded. Our model achieved a good fit of the data with inverse probability of censoring weights concordance index of 0.883. The presence of multivitamins, immunosuppression, non-coronary NSAIDS, proton pump inhibitors, vitamin D supplementation, opioids, statins and beta-blockers were associated with significantly lower hazard ratio for MGUS progression in our primary model; multivitamins and non-coronary NSAIDs remained significant across both sensitivity analyses. This work could inform subsequent prospective studies, or similar studies in other disease states.

PMID:36797276 | DOI:10.1038/s41408-023-00798-7

Ann Rheum Dis. 2023 Feb 16:ard-2022-223697. doi: 10.1136/ard-2022-223697. Online ahead of print.

ABSTRACT

OBJECTIVES: The number of susceptibility loci currently associated with vasculitis is lower than in other immune-mediated diseases due in part to small cohort sizes, a consequence of the low prevalence of vasculitides. This study aimed to identify new genetic risk loci for the main systemic vasculitides through a comprehensive analysis of their genetic overlap.

METHODS: Genome-wide data from 8467 patients with any of the main forms of vasculitis and 29 795 healthy controls were meta-analysed using ASSET. Pleiotropic variants were functionally annotated and linked to their target genes. Prioritised genes were queried in DrugBank to identify potentially repositionable drugs for the treatment of vasculitis.

RESULTS: Sixteen variants were independently associated with two or more vasculitides, 15 of them representing new shared risk loci. Two of these pleiotropic signals, located close to CTLA4 and CPLX1, emerged as novel genetic risk loci in vasculitis. Most of these polymorphisms appeared to affect vasculitis by regulating gene expression. In this regard, for some of these common signals, potential causal genes were prioritised based on functional annotation, including CTLA4, RNF145, IL12B, IL5, IRF1, IFNGR1, PTK2B, TRIM35, EGR2 and ETS2, each of which has key roles in inflammation. In addition, drug repositioning analysis showed that several drugs, including abatacept and ustekinumab, could be potentially repurposed in the management of the analysed vasculitides.

CONCLUSIONS: We identified new shared risk loci with functional impact in vasculitis and pinpointed potential causal genes, some of which could represent promising targets for the treatment of vasculitis.

PMID:36797040 | DOI:10.1136/ard-2022-223697

PLoS One. 2023 Feb 16;18(2):e0277652. doi: 10.1371/journal.pone.0277652. eCollection 2023.

ABSTRACT

Chronic kidney disease (CKD) progression may be evoked through dysregulated mitochondrial dynamics enhanced oxidative stress and inflammation contributing to high cardiovascular morbidity and mortality. Previous study has demonstrated sodium thiosulfate (STS, Na2S2O3) could effectively attenuate renal oxidative injury in the animal model of renovascular hypertension. We explored whether the potentially therapeutic effect of STS is available on the attenuating CKD injury in thirty-six male Wistar rats with 5/6 nephrectomy. We determined the STS effect on reactive oxygen species (ROS) amount in vitro and in vivo by an ultrasensitive chemiluminescence-amplification method, ED-1 mediated inflammation, Masson's trichrome stained fibrosis, mitochondrial dynamics (fission and fusion) and two types of programmed cell death, apoptosis and ferroptosis by western blot and immunohistochemistry. Our in vitro data showed STS displayed the strongest scavenging ROS activity at the dosage of 0.1 g. We applied STS at 0.1 g/kg intraperitoneally 5 times/week for 4 weeks to these CKD rats. CKD significantly enhanced the degree in arterial blood pressure, urinary protein, BUN, creatinine, blood and kidney ROS amount, leukocytes infiltration, renal 4-HNE expression, fibrosis, dynamin-related protein 1 (Drp1) mediated mitochondrial fission, Bax/c-caspase 9/c-caspase 3/poly (ADP-ribose) polymerase (PARP) mediated apoptosis, iron overload/ferroptosis and the decreased xCT/GPX4 expression and OPA-1 mediated mitochondrial fusion. STS treatment significantly ameliorated oxidative stress, leukocyte infiltration, fibrosis, apoptosis and ferroptosis and improved mitochondrial dynamics and renal dysfunction in CKD rats. Our results suggest that STS as drug repurposing strategy could attenuate CKD injury through the action of anti-mitochondrial fission, anti-inflammation, anti-fibrosis, anti-apoptotic, and anti-ferroptotic mechanisms.

PMID:36795670 | DOI:10.1371/journal.pone.0277652

PLoS One. 2023 Feb 16;18(2):e0278289. doi: 10.1371/journal.pone.0278289. eCollection 2023.

ABSTRACT

Drug repositioning allows expedited discovery of new applications for existing compounds, but re-screening vast compound libraries is often prohibitively expensive. "Connectivity mapping" is a process that links drugs to diseases by identifying compounds whose impact on expression in a collection of cells reverses the disease's impact on expression in disease-relevant tissues. The LINCS project has expanded the universe of compounds and cells for which data are available, but even with this effort, many clinically useful combinations are missing. To evaluate the possibility of repurposing drugs despite missing data, we compared collaborative filtering using either neighborhood-based or SVD imputation methods to two naive approaches via cross-validation. Methods were evaluated for their ability to predict drug connectivity despite missing data. Predictions improved when cell type was taken into account. Neighborhood collaborative filtering was the most successful method, with the best improvements in non-immortalized primary cells. We also explored which classes of compounds are most and least reliant on cell type for accurate imputation. We conclude that even for cells in which drug responses have not been fully characterized, it is possible to identify unassayed drugs that reverse in those cells the expression signatures observed in disease.

PMID:36795645 | DOI:10.1371/journal.pone.0278289

BMC Bioinformatics. 2023 Feb 15;24(1):52. doi: 10.1186/s12859-023-05181-8.

ABSTRACT

BACKGROUND: Due to the high resource consumption of introducing a new drug, drug repurposing plays an essential role in drug discovery. To do this, researchers examine the current drug-target interaction (DTI) to predict new interactions for the approved drugs. Matrix factorization methods have much attention and utilization in DTIs. However, they suffer from some drawbacks.

METHODS: We explain why matrix factorization is not the best for DTI prediction. Then, we propose a deep learning model (DRaW) to predict DTIs without having input data leakage. We compare our model with several matrix factorization methods and a deep model on three COVID-19 datasets. In addition, to ensure the validation of DRaW, we evaluate it on benchmark datasets. Furthermore, as an external validation, we conduct a docking study on the COVID-19 recommended drugs.

RESULTS: In all cases, the results confirm that DRaW outperforms matrix factorization and deep models. The docking results approve the top-ranked recommended drugs for COVID-19.

CONCLUSIONS: In this paper, we show that it may not be the best choice to use matrix factorization in the DTI prediction. Matrix factorization methods suffer from some intrinsic issues, e.g., sparsity in the domain of bioinformatics applications and fixed-unchanged size of the matrix-related paradigm. Therefore, we propose an alternative method (DRaW) that uses feature vectors rather than matrix factorization and demonstrates better performance than other famous methods on three COVID-19 and four benchmark datasets.

PMID:36793010 | DOI:10.1186/s12859-023-05181-8

BMC Med Inform Decis Mak. 2023 Feb 14;23(1):35. doi: 10.1186/s12911-023-02133-3.

ABSTRACT

BACKGROUND: The measurement of drug similarity has many potential applications for assessing drug therapy similarity, patient similarity, and the success of treatment modalities. To date, a family of computational methods has been employed to predict drug-drug similarity. Here, we announce a computational method for measuring drug-drug similarity based on drug indications and side effects.

METHODS: The model was applied for 2997 drugs in the side effects category and 1437 drugs in the indications category. The corresponding binary vectors were built to determine the Drug-drug similarity for each drug. Various similarity measures were conducted to discover drug-drug similarity.

RESULTS: Among the examined similarity methods, the Jaccard similarity measure was the best in overall performance results. In total, 5,521,272 potential drug pair's similarities were studied in this research. The offered model was able to predict 3,948,378 potential similarities.

CONCLUSION: Based on these results, we propose the current method as a robust, simple, and quick approach to identifying drug similarity.

PMID:36788528 | DOI:10.1186/s12911-023-02133-3

Addiction. 2023 Feb 15. doi: 10.1111/add.16168. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Cocaine Use Disorder (CUD) is a significant public health issue for which there is no Food and Drug Administration (FDA) approved medication. Drug repurposing looks for new cost-effective uses of approved drugs. This study presents an integrated strategy to identify repurposed FDA-approved drugs for CUD treatment.

DESIGN: Our drug repurposing strategy combines artificial intelligence (AI)-based drug prediction, expert panel review, clinical corroboration, and mechanisms of action analysis being implemented in the National Drug Abuse Treatment Clinical Trials Network (CTN). Based on AI-based prediction and expert knowledge, ketamine was ranked as the top candidate for clinical corroboration via electronic health record (EHR) evaluation of CUD patient cohorts prescribed ketamine for anesthesia or depression compared with matched controls who received non-ketamine anesthesia or antidepressants/midazolam. Genetic and pathway enrichment analyses were performed to understand ketamine's potential mechanisms of action in the context of CUD.

SETTING: The study utilized TriNetX to access EHRs from over 90 million patients worldwide. Genetic and functional level analysis used DisGeNet, Search Tool for Interactions of Chemicals, and Kyoto Encyclopedia of Genes and Genomes databases.

PARTICIPANTS: 7,742 CUD patients who received anesthesia (3,871 ketamine-exposed and 3,871 anesthetic-controlled) and 7,910 CUD patients with depression (3,955 ketamine-exposed and 3,955 antidepressant-controlled) were identified after propensity score-matching.

MEASUREMENTS: EHR analysis outcome was a CUD remission diagnosis within 1 year of drug prescription.

FINDINGS: Patients with CUD prescribed ketamine for anesthesia displayed a significantly higher rate of CUD remission compared with matched individuals prescribed other anesthetics (Hazard Ratio (HR): 1.98, 95% confidence interval [CI]: 1.42-2.78). Similarly, CUD patients prescribed ketamine for depression evidenced a significantly higher CUD remission ratio compared with matched patients prescribed antidepressants or midazolam (HR: 4.39, 95% CI: 2.89-6.68). The mechanism of action analysis revealed that ketamine directly targets multiple CUD-associated genes (BDNF, CNR1, DRD2, GABRA2, GABRB3, GAD1, OPRK1, OPRM1, SLC6A3, SLC6A4) and pathways implicated in neuroactive ligand-receptor interaction, cAMP signaling, and cocaine abuse/dependence.

CONCLUSIONS: Ketamine appears to be a potential repurposed drug for treatment of cocaine use disorder.

PMID:36792381 | DOI:10.1111/add.16168

Comput Biol Med. 2023 Feb 11;155:106665. doi: 10.1016/j.compbiomed.2023.106665. Online ahead of print.

ABSTRACT

Thymic epithelial tumors (TETs) are rare malignant tumors, and the molecular mechanisms of both primary and recurrent TETs are poorly understood. Here we established comprehensive proteomic signatures of 15 tumors (5 recurrent and 10 non-recurrent) and 15 pair wised tumor adjacent normal tissues. We then proposed an integrative network approach for studying the proteomics data by constructing protein-protein interaction networks based on differentially expressed proteins and a machine learning-based score, followed by network modular analysis, functional enrichment annotation and shortest path inference analysis. Network modular analysis revealed that primary and recurrent TETs shared certain common molecular mechanisms, including a spliceosome module consisting of RNA splicing and RNA processing, but the recurrent TET was specifically related to the ribosome pathway. Applying the shortest path inference to the collected seed gene module identified that the ribonucleoprotein hnRNPA2B1 probably serves as a potential target for recurrent TET therapy. The drug repositioning combined molecular dynamics simulations suggested that the compound ergotamine could potentially act as a repurposing drug to treat recurrent TETs by targeting hnRNPA2B1. Our study demonstrates the value of integrative network analysis to understand proteotype robustness and its relationships with genotype, and provides hits for further research on cancer therapeutics.

PMID:36791552 | DOI:10.1016/j.compbiomed.2023.106665

Invest New Drugs. 2023 Feb 15. doi: 10.1007/s10637-023-01337-8. Online ahead of print.

ABSTRACT

BACKGROUND: Lung cancer is the leading cause of cancer death worldwide, and EGFR mutation is the most common genetic alteration among Asian patients with lung adenocarcinoma. While osimertinib has been shown to be effective in lung cancer patients with EGFR mutation, the majority of patients eventually develop acquired resistance to treatment. We explored the significance of the cyclin D1 expression in patients with EGFR mutation and the potential efficacy of adding abemaciclib, a cyclin-dependent kinase (CDK) 4/6 inhibitor, simultaneously with osimertinib in vitro.

MATERIALS AND METHODS: Immunohistochemical staining, using an anti-cyclin D1 antibody, of specimens from 83 patients with EGFR mutation (male, n = 27; pStage 0-I, n = 71) who were treated by surgical resection between 2017 and 2020, and the relationship between the cyclin D1 expression and clinicopathological factors was analyzed. Additionally, the combined effect of osimertinib and abemaciclib in lung cancer cell lines were analyzed using a growth inhibition test, and the signaling pathway underlying the combined effect was investigated.

RESULTS: Cyclin D1 was negative in 18.1% of patients with EGFR mutation, and cyclin D1 negativity was associated with pStage ≥ II (p = 0.02), lymph node metastasis (p = 0.001), and lymphatic invasion (p = 0.01). The cyclin D1-negative group had significantly shorter recurrence-free survival (p = 0.02), although this difference disappeared when limited to pN0 patients. In EGFR mutated cell lines, the combination of osimertinib and abemaciclib demonstrated synergistic effects, which were thought to be mediated by the inhibition of AKT phosphorylation.

CONCLUSION: Combination therapy with CDK4/6 inhibitors and EGFR-TKIs may be a promising approach.

PMID:36790603 | DOI:10.1007/s10637-023-01337-8

Brief Funct Genomics. 2023 Feb 14:elac054. doi: 10.1093/bfgp/elac054. Online ahead of print.

ABSTRACT

Primary hyperparathyroidism is caused by solitary parathyroid adenomas (PTAs) in most cases (⁓85%), and it has been previously reported that PTAs are associated with cardiovascular disease (CVD) and type-2 diabetes (T2D). To understand the molecular basis of PTAs, we have investigated the genetic association amongst PTAs, CVD and T2D through an integrative network-based approach and observed a remarkable resemblance. The current study proposed to compare the PTAs-associated proteins with the overlapping proteins of CVD and T2D to determine the disease relationship. We constructed the protein-protein interaction network by integrating curated and experimentally validated interactions in humans. We found the $11$ highly clustered modules in the network, which contain a total of $13$ hub proteins (TP53, ESR1, EGFR, POTEF, MEN1, FLNA, CDKN2B, ACTB, CTNNB1, CAV1, MAPK1, G6PD and CCND1) that commonly co-exist in PTAs, CDV and T2D and reached to network's hierarchically modular organization. Additionally, we implemented a gene-set over-representation analysis over biological processes and pathways that helped to identify disease-associated pathways and prioritize target disease proteins. Moreover, we identified the respective drugs of these hub proteins. We built a bipartite network that helps decipher the drug-target interaction, highlighting the influential roles of these drugs on apparently unrelated targets and pathways. Targeting these hub proteins by using drug combinations or drug-repurposing approaches will improve the clinical conditions in comorbidity, enhance the potency of a few drugs and give a synergistic effect with better outcomes. This network-based analysis opens a new horizon for more personalized treatment and drug-repurposing opportunities to investigate new targets and multi-drug treatment and may be helpful in further analysis of the mechanisms underlying PTA and associated diseases.

PMID:36790356 | DOI:10.1093/bfgp/elac054

Mov Disord. 2023 Feb 14. doi: 10.1002/mds.29349. Online ahead of print.

ABSTRACT

BACKGROUND: Statins represent candidates for drug repurposing in Parkinson's disease (PD). Few studies examined the role of reverse causation, statin subgroups, and dose-response relations based on time-varying exposures.

OBJECTIVES: We examined whether statin use is associated with PD incidence while attempting to overcome the limitations described previously, especially reverse causation.

METHOD: We used data from the E3N cohort study of French women (follow-up, 2004-2018). Incident PD was ascertained using multiple sources and validated by experts. New statin users were identified through linked drug claims. We set up a nested case-control study to describe trajectories of statin prescriptions and medical consultations before diagnosis. We used time-varying multivariable Cox proportional hazards regression models to examine the statins-PD association. Exposure indexes included ever use, cumulative duration/dose, and mean daily dose and were lagged by 5 years to address reverse causation.

RESULTS: The case-control study (693 cases, 13,784 controls) showed differences in case-control trajectories, with changes in the 5 years before diagnosis in cases. Of 73,925 women (aged 54-79 years), 524 developed PD and 11,552 started using statins in lagged analyses. Ever use of any statin was not associated with PD (hazard ratio [HR] = 0.87, 95% confidence interval [CI] = 0.67-1.11). Alternatively, ever use of lipophilic statins was significantly associated with lower PD incidence (HR = 0.70, 95% CI = 0.51-0.98), with a dose-response relation for the mean daily dose (P-linear trend = 0.02). There was no association for hydrophilic statins.

CONCLUSION: Use of lipophilic statins at least 5 years earlier was associated with reduced PD incidence in women, with a dose-response relation for the mean daily dose. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

PMID:36788159 | DOI:10.1002/mds.29349

Int Rev Psychiatry. 2022 Nov-Dec;34(7-8):699-714. doi: 10.1080/09540261.2022.2113369. Epub 2022 Aug 23.

ABSTRACT

Depression has a large burden, but the development of new drugs for its treatment has proved difficult. Progresses in neuroscience have highlighted several physiopathological pathways, notably inflammatory and metabolic ones, likely involved in the genesis of depressive symptoms. A novel strategy proposes to repurpose established medical treatments of known safety and to investigate their potential antidepressant activity. Among numerous candidates, growing evidence suggests that statins may have a positive role in the treatment of depressive disorders, although some have raised concerns about possible depressogenic effects of these widely prescribed medications. This narrative review summarises relevant findings from translational studies implicating many interconnected neurobiological and neuropsychological, cardiovascular, endocrine-metabolic, and immunological mechanisms by which statins could influence mood. Also, the most recent clinical investigations on the effects of statins in depression are presented. Overall, the use of statins for the treatment of depressive symptoms cannot be recommended based on the available literature, though this might change as several larger, methodologically robust studies are being conducted. Nevertheless, statins can already be acknowledged as a driver of innovation in mental health, as they provide a novel perspective to the physical health of people with depression and for the development of more precise antidepressant treatments.

PMID:36786109 | DOI:10.1080/09540261.2022.2113369

Biophys J. 2023 Feb 10;122(3S1):472a-473a. doi: 10.1016/j.bpj.2022.11.2533.

NO ABSTRACT

PMID:36784427 | DOI:10.1016/j.bpj.2022.11.2533

Biophys J. 2023 Feb 10;122(3S1):144a. doi: 10.1016/j.bpj.2022.11.942.

NO ABSTRACT

PMID:36782662 | DOI:10.1016/j.bpj.2022.11.942

Biophys J. 2023 Feb 10;122(3S1):144a. doi: 10.1016/j.bpj.2022.11.941.

NO ABSTRACT

PMID:36782661 | DOI:10.1016/j.bpj.2022.11.941

Purinergic Signal. 2023 Feb 13. doi: 10.1007/s11302-023-09924-3. Online ahead of print.

ABSTRACT

Some non-adenosinergic drugs are reported to also act through adenosine receptors (ARs). We used mouse hypothermia, which can be induced by agonism at any of the four ARs, as an in vivo screen for adenosinergic effects. An AR contribution was identified when a drug caused hypothermia in wild type mice that was diminished in mice lacking all four ARs (quadruple knockout, QKO). Alternatively, an adenosinergic effect was identified if a drug potentiated adenosine-induced hypothermia. Four drugs (dipyridamole, nimodipine, cilostazol, cyclosporin A) increased the hypothermia caused by adenosine. Dipyridamole and nimodipine probably achieved this by inhibition of adenosine clearance via ENT1. Two drugs (cannabidiol, canrenoate) did not cause hypothermia in wild type mice. Four other drugs (nifedipine, ranolazine, ketamine, ethanol) caused hypothermia, but the hypothermia was unchanged in QKO mice indicating non-adenosinergic mechanisms. Zinc chloride caused hypothermia and hypoactivity; the hypoactivity was blunted in the QKO mice. Interestingly, the antidepressant amitriptyline caused hypothermia in wild type mice that was amplified in the QKO mice. Thus, we have identified adenosine-related effects for some drugs, while other candidates do not affect adenosine signaling by this in vivo assay. The adenosine-modulating drugs could be considered for repurposing based on predicted effects on AR activation.

PMID:36781825 | DOI:10.1007/s11302-023-09924-3

Biomater Sci. 2023 Feb 13. doi: 10.1039/d2bm01957d. Online ahead of print.

ABSTRACT

A simple but novel ophthalmic solution based on two approved drugs was developed to reposition existing drugs to treat new diseases. This nanoformulation was developed using the phytochemical drug glycyrrhizin as an amphiphilic nanocarrier to micellarly solubilize empagliflozin (EMP), an oral drug that is widely used to control high blood glucose but has poor water solubility. This novel nanoformulation, which we designated the EMP@glycymicelle ophthalmic solution, was obtained using a simple preparation process. The resulting solution was a clear solution with an EMP encapsulation efficiency of 97.91 ± 0.50%, a small glycymicelle size of 6.659 ± 0.196 nm, and a narrow polydispersity index of 0.226 ± 0.059. The optimized formulation demonstrated that EMP was soluble in water up to 18 mg ml-1 because of its encapsulation within glycymicelles. The EMP@glycymicelle ophthalmic solution exhibited excellent characteristics, including good storage stability, fast in vitro release profiles, improved in vitro antioxidant activity, and no ocular irritation. Ocular permeation evaluation showed that the EMP@glycymicelle ophthalmic solution had strong ocular permeation of EMP, and it reached the posterior segment of mouse eyes after ocular topical administration. The treatment efficacy evaluation showed that the EMP@glycymicelle ophthalmic solution had a significant effect against corneal alkali burns in mice, prompting corneal wound healing, recovering corneal sensitivity, reducing corneal haze, and relieving corneal NV invasion. The mechanism of inhibiting HMGB1 signaling was involved in this strong treatment effect. These results indicated that the EMP@glycymicelle ophthalmic solution provided a new concept of drug repurposing and a promising ocular system for the nano-delivery of EMP with significantly improved in vivo profiles.

PMID:36779571 | DOI:10.1039/d2bm01957d

Expert Rev Precis Med Drug Dev. 2022;7(1):4-16. doi: 10.1080/23808993.2022.2028548. Epub 2022 Jan 24.

ABSTRACT

INTRODUCTION: Cardiovascular disease persists as the leading cause of death worldwide despite continued advances in diagnostics and therapeutics. Our current approach to patients with cardiovascular disease is rooted in reductionism, which presupposes that all patients share a similar phenotype and will respond the same to therapy; however, this is unlikely as cardiovascular diseases exhibit complex heterogeneous phenotypes.

AREAS COVERED: With the advent of high-throughput platforms for omics testing, phenotyping cardiovascular diseases has advanced to incorporate large-scale molecular data with classical history, physical examination, and laboratory results. Findings from genomics, proteomics, and metabolomics profiling have been used to define more precise cardiovascular phenotypes and predict adverse outcomes in population-based and disease-specific patient cohorts. These molecular data have also been utilized to inform drug efficacy based on a patient's unique phenotype.

EXPERT OPINION: Multiscale phenotyping of cardiovascular disease has revealed diversity among patients that can be used to personalize pharmacotherapies and predict outcomes. Nonetheless, precision phenotyping for cardiovascular disease remains a nascent field that has not yet translated into widespread clinical practice despite its many potential advantages for patient care. Future endeavors that demonstrate improved pharmacotherapeutic responses and associated reduction in adverse events will facilitate mainstream adoption of precision cardiovascular phenotyping.

PMID:36778892 | PMC:PMC9913616 | DOI:10.1080/23808993.2022.2028548

Front Microbiol. 2023 Jan 26;14:1112491. doi: 10.3389/fmicb.2023.1112491. eCollection 2023.

ABSTRACT

Mycobacterium tuberculosis is a deadly pathogen, currently the leading cause of death worldwide from a single infectious agent through tuberculosis infections. If the End TB 2030 strategy is to be achieved, additional drugs need to be identified and made available to supplement the current treatment regimen. In addition, drug resistance is a growing issue, leading to significantly lower treatment success rates, necessitating further drug development. Vanoxerine (GBR12909), a dopamine re-uptake inhibitor, was recently identified as having anti-mycobacterial activity during a drug repurposing screening effort. However, its effects on mycobacteria were not well characterized. Herein, we report vanoxerine as a disruptor of the membrane electric potential, inhibiting mycobacterial efflux and growth. Vanoxerine had an undetectable level of resistance, highlighting the lack of a protein target. This study suggests a mechanism of action for vanoxerine, which will allow for its continued development or use as a tool compound.

PMID:36778873 | PMC:PMC9909702 | DOI:10.3389/fmicb.2023.1112491

Cell Genom. 2022 Feb 9;2(2):100100. doi: 10.1016/j.xgen.2022.100100. eCollection 2022 Feb 9.

ABSTRACT

Hirt et al.1 report an automated, high-throughput drug screening platform for organoid cultures to enable repurposing of previously approved drugs for pancreatic cancers harboring specific genetic alterations. The pancreatic cancer organoid biobank also represents a valuable tool to uncover new drug-gene interactions in pancreatic tumors.

PMID:36778660 | PMC:PMC9903715 | DOI:10.1016/j.xgen.2022.100100