Cancer Med. 2022 Jun 8. doi: 10.1002/cam4.4933. Online ahead of print.

ABSTRACT

BACKGROUND: Non-small cell lung cancer (NSCLC) comprises the majority (~85%) of all lung tumors, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being the most frequently diagnosed histological subtypes. Multi-modal omics profiling has been carried out in NSCLC, but no studies have yet reported a unique metabolite-related gene signature and altered metabolic pathways associated with LUAD and LUSC.

METHODS: We integrated transcriptomics and metabolomics to analyze 30 human lung tumors and adjacent noncancerous tissues. Differential co-expression was used to identify modules of metabolites that were altered between normal and tumor.

RESULTS: We identified unique metabolite-related gene signatures specific for LUAD and LUSC and key pathways aberrantly regulated at both transcriptional and metabolic levels. Differential co-expression analysis revealed that loss of coherence between metabolites in tumors is a major characteristic in both LUAD and LUSC. We identified one metabolic onco-module gained in LUAD, characterized by nine metabolites and 57 metabolic genes. Multi-omics integrative analysis revealed a 28 metabolic gene signature associated with poor survival in LUAD, with six metabolite-related genes as individual prognostic markers.

CONCLUSIONS: We demonstrated the clinical utility of this integrated metabolic gene signature in LUAD by using it to guide repurposing of AZD-6482, a PI3Kβ inhibitor which significantly inhibited three genes from the 28-gene signature. Overall, we have integrated metabolomics and transcriptomics analyses to show that LUAD and LUSC have distinct profiles, inferred gene signatures with prognostic value for patient survival, and identified therapeutic targets and repurposed drugs for potential use in NSCLC treatment.

PMID:35676822 | DOI:10.1002/cam4.4933

Sci Rep. 2022 Jun 8;12(1):9417. doi: 10.1038/s41598-022-13719-8.

ABSTRACT

Lung cancer is the most common cancer in men and women. This cancer is divided into two main types, namely non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Around 85 to 90 percent of lung cancers are NSCLC. Repositioning potent candidate drugs in NSCLC treatment is one of the important topics in cancer studies. Drug repositioning (DR) or drug repurposing is a method for identifying new therapeutic uses of existing drugs. The current study applies a computational drug repositioning method to identify candidate drugs to treat NSCLC patients. To this end, at first, the transcriptomics profile of NSCLC and healthy (control) samples was obtained from the GEO database with the accession number GSE21933. Then, the gene co-expression network was reconstructed for NSCLC samples using the WGCNA, and two significant purple and magenta gene modules were extracted. Next, a list of transcription factor genes that regulate purple and magenta modules' genes was extracted from the TRRUST V2.0 online database, and the TF-TG (transcription factors-target genes) network was drawn. Afterward, a list of drugs targeting TF-TG genes was obtained from the DGIdb V4.0 database, and two drug-gene interaction networks, including drug-TG and drug-TF, were drawn. After analyzing gene co-expression TF-TG, and drug-gene interaction networks, 16 drugs were selected as potent candidates for NSCLC treatment. Out of 16 selected drugs, nine drugs, namely Methotrexate, Olanzapine, Haloperidol, Fluorouracil, Nifedipine, Paclitaxel, Verapamil, Dexamethasone, and Docetaxel, were chosen from the drug-TG sub-network. In addition, nine drugs, including Cisplatin, Daunorubicin, Dexamethasone, Methotrexate, Hydrocortisone, Doxorubicin, Azacitidine, Vorinostat, and Doxorubicin Hydrochloride, were selected from the drug-TF sub-network. Methotrexate and Dexamethasone are common in drug-TG and drug-TF sub-networks. In conclusion, this study proposed 16 drugs as potent candidates for NSCLC treatment through analyzing gene co-expression, TF-TG, and drug-gene interaction networks.

PMID:35676421 | DOI:10.1038/s41598-022-13719-8

Nat Commun. 2022 Jun 8;13(1):3181. doi: 10.1038/s41467-022-30794-7.

ABSTRACT

The RNF43_p.G659fs mutation occurs frequently in colorectal cancer, but its function remains poorly understood and there are no specific therapies directed against this alteration. In this study, we find that RNF43_p.G659fs promotes cell growth independent of Wnt signaling. We perform a drug repurposing library screen and discover that cells with RNF43_p.G659 mutations are selectively killed by inhibition of PI3K signaling. PI3K/mTOR inhibitors yield promising antitumor activity in RNF43659mut isogenic cell lines and xenograft models, as well as in patient-derived organoids harboring RNF43_p.G659fs mutations. We find that RNF43659mut binds p85 leading to increased PI3K signaling through p85 ubiquitination and degradation. Additionally, RNA-sequencing of RNF43659mut isogenic cells reveals decreased interferon response gene expression, that is reversed by PI3K/mTOR inhibition, suggesting that RNF43659mut may alter tumor immunity. Our findings suggest a therapeutic application for PI3K/mTOR inhibitors in treating RNF43_p.G659fs mutant cancers.

PMID:35676246 | DOI:10.1038/s41467-022-30794-7

Microbiol Spectr. 2022 Jun 8:e0088422. doi: 10.1128/spectrum.00884-22. Online ahead of print.

ABSTRACT

Infections caused by drug-resistant bacteria are a serious threat to public health worldwide, and the discovery of novel antibacterial compounds is urgently needed. Here, we screened an FDA-approved small-molecule library and found that crizotinib possesses good antimicrobial efficacy against Gram-positive bacteria. Crizotinib was found to increase the survival rate of mice infected with bacteria and decrease pulmonary inflammation activity in an animal model. Furthermore, it showed synergy with clindamycin and gentamicin. Importantly, the Gram-positive bacteria showed a low tendency to develop resistance to crizotinib. Mechanistically, quantitative proteomics and biochemical validation experiments indicated that crizotinib exerted its antibacterial effects by reducing ATP production and pyrimidine metabolism. A drug affinity responsive target stability study suggested crizotinib targets the CTP synthase PyrG, which subsequently disturbs pyrimidine metabolism and eventually reduces DNA synthesis. Subsequent molecular dynamics analysis showed that crizotinib binding occurs in close proximity to the ATP binding pocket of PyrG and causes loss of function of this CTP synthase. Crizotinib is a promising antimicrobial agent and provides a novel choice for the development of treatment for Gram-positive infections. IMPORTANCE Infections caused by drug-resistant bacteria are a serious problem worldwide. Therefore, there is an urgent need to find novel drugs with good antibacterial activity against multidrug-resistant bacteria. In this study, we found that a repurposed drug, crizotinib, exhibits excellent antibacterial activity against drug-resistant bacteria both in vivo and in vitro via suppressing ATP production and pyrimidine metabolism. Crizotinib was found to disturb pyrimidine metabolism by targeting the CTP synthase PyrG, thus reducing DNA synthesis. This unique mechanism of action may explain the decreased development of resistance by Staphylococcus aureus to crizotinib. This study provides a potential option for the treatment of drug-resistant bacterial infections in the future.

PMID:35674439 | DOI:10.1128/spectrum.00884-22

Stud Health Technol Inform. 2022 Jun 6;290:243-247. doi: 10.3233/SHTI220071.

ABSTRACT

Precision oncology is expected to improve selection of targeted therapies, tailored to individual patients and ultimately improve cancer patients' outcomes. Several cancer genetics knowledge databases have been successfully developed for such purposes, including CIViC and OncoKB, with active community-based curations and scoring of genetic-treatment evidences. Although many studies were conducted based on each knowledge base respectively, the integrative analysis across both knowledge bases remains largely unexplored. Thus, there exists an urgent need for a heterogeneous precision oncology knowledge resource with computational power to support drug repurposing discovery in a timely manner, especially for life-threatening cancer. In this pilot study, we built a heterogeneous precision oncology knowledge resource (POKR) by integrating CIViC and OncoKB, in order to incorporate unique information contained in each knowledge base and make associations amongst biomedical entities (e.g., gene, drug, disease) computable and measurable via training POKR graph embeddings. All the relevant codes, database dump files, and pre-trained POKR embeddings can be accessed through the following URL: https://github.com/shenfc/POKR.

PMID:35673010 | DOI:10.3233/SHTI220071

Nat Commun. 2022 Jun 7;13(1):3258. doi: 10.1038/s41467-022-30956-7.

ABSTRACT

Transcriptome-wide association studies (TWAS) are popular approaches to test for association between imputed gene expression levels and traits of interest. Here, we propose an integrative method PUMICE (Prediction Using Models Informed by Chromatin conformations and Epigenomics) to integrate 3D genomic and epigenomic data with expression quantitative trait loci (eQTL) to more accurately predict gene expressions. PUMICE helps define and prioritize regions that harbor cis-regulatory variants, which outperforms competing methods. We further describe an extension to our method PUMICE +, which jointly combines TWAS results from single- and multi-tissue models. Across 79 traits, PUMICE + identifies 22% more independent novel genes and increases median chi-square statistics values at known loci by 35% compared to the second-best method, as well as achieves the narrowest credible interval size. Lastly, we perform computational drug repurposing and confirm that PUMICE + outperforms other TWAS methods.

PMID:35672318 | DOI:10.1038/s41467-022-30956-7

Struct Chem. 2022 May 27:1-14. doi: 10.1007/s11224-022-01916-0. Online ahead of print.

ABSTRACT

Huge vaccination drives are underway around the world for the ongoing COVID-19 pandemic. However, the search for antiviral drugs is equally crucial. As new drug discovery is a time-consuming process, repurposing of existing drugs or developing drug candidates against SARS-CoV-2 will make the process faster. Considering this, 63 approved and developing antimalarial compounds were selected to screen against main protease (Mpro) and papain-like protease (PLpro) of SARS-CoV-2 using in silico methods to find out possible new drug candidate(s). Out of 63 compounds, epoxomicin showed the best binding affinity against the Mpro with CDocker energy of - 57.511 kcal/mol without any toxic effect. This compound was further taken for molecular dynamic simulation study, where the Mpro-epoxomicin complex was found to be stable with binding free energy - 79.315 kcal/mol. The possible inhibitory potential of the selected compound was determined by 3D-QSAR analysis and found to be 0.4447 µM against SARS-CoV-2 Mpro. Finally, the structure activity relationship of the compound was analyzed and two fragments responsible for overall good binding affinity of the compound at the active site of Mpro were identified. This study suggests a safe antimalarial drug, namely epoxomicin, as a probable inhibitor of SARS-CoV-2 Mpro which needs further validation by in vitro/in vivo studies before clinical use.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11224-022-01916-0.

PMID:35669793 | PMC:PMC9136827 | DOI:10.1007/s11224-022-01916-0

Front Immunol. 2022 May 20;13:870627. doi: 10.3389/fimmu.2022.870627. eCollection 2022.

ABSTRACT

Aberrant activation of the NLRP3 inflammasome promotes the pathogenesis of many inflammatory diseases. The development of the NLRP3 inflammasome inhibitors from existing drugs for new therapeutic purposes is becoming more important. Candesartan is an angiotensin II receptor antagonist widely used as a blood pressure-lowering drug; however, the inhibitory potential of candesartan on the NLRP3 inflammasome has not yet been investigated. We demonstrated that candesartan significantly inhibited the NLRP3 inflammasome and pyroptosis in macrophages. Mechanistic analysis revealed that candesartan inhibited the expression of NLRP3 and proIL-1β by suppressing NF-κB activation and reducing the phosphorylation of ERK1/2 and JNK1/2. Candesartan reduced mitochondrial damage and inhibited the NLRP3 inflammasome assembly by suppressing NLRP3 binding to PKR, NEK7 and ASC. In addition, candesartan inhibited IL-1β secretion partially through autophagy induction. Furthermore, oral administration of candesartan reduced peritoneal neutrophil influx, NLRP3 and ASC expression in peritoneal cells, and lavage fluid concentrations of active caspase-1, IL-1β, IL-6 and MCP-1 in uric acid crystal-injected mice. These results indicated that candesartan has board anti-inflammatory effects and has the potential to be repositioned to ameliorate inflammatory diseases or NLRP3-associated complications.

PMID:35669789 | PMC:PMC9163344 | DOI:10.3389/fimmu.2022.870627

Inform Med Unlocked. 2022;31:100979. doi: 10.1016/j.imu.2022.100979. Epub 2022 Jun 2.

ABSTRACT

The SARS-CoV-2 is one of the most infectious and deadly coronaviruses, which has gripped the world, causing the COVID-19 pandemic. Despite the numerous studies being conducted on this virus, many uncertainties are with the disease. This is exacerbated by the speedy mutations acquired by the viral strain, which enables the disease to present itself differently in different people, introducing new factors of uncertainty. This study aims at the identification of regulatory pathways across two cell lines, namely, the peripheral blood mononuclear cell line (PBMC) and the normal human bronchial epithelial (NHBE) cell line. Both the above-mentioned cell lines were considered because they support viral replication. Furthermore, the NHBE cell line captures vital changes in the lungs, which are the main organs affected by the COVID-19 patients, and the PBMC cell line is closely linked to the body's immune system. RNA-Seq analysis, differential gene expression and gene set enrichment analysis for pathway identification were followed. Pathway analysis throws light upon the various systems affected in the body due to the COVID-19. Gene regulatory networks associated with the significant pathways were also designed. These networks aid in identifying various gene targets, along with their interactions. Studying the functionality of the pathways and the gene interactions associated with them, aided by long COVID studies, will provide immense clarity about the current COVID-19 scenario. In the long term, this will help in the design of therapeutic approaches against the SARS-CoV-2 and can also contribute to drug repurposing studies. Ultimately, this study identifies and analyses the relationship of various undiscovered or lesser explored pathways in the human body to the SARS-CoV-2 and establish a clearer picture of the association to help streamline further studies and approaches.

PMID:35669390 | PMC:PMC9159965 | DOI:10.1016/j.imu.2022.100979

OMICS. 2022 Jun 3. doi: 10.1089/omi.2022.0026. Online ahead of print.

ABSTRACT

Drug repurposing has broad importance in planetary health for therapeutics innovation in infectious diseases as well as common or rare chronic human diseases. Drug repurposing has also proved important to develop interventions against the COVID-19 pandemic. We propose a new approach for drug repurposing involving two-stage prediction and machine learning. First, diseases are clustered by gene expression on the premise that similar patterns of altered gene expression imply critical pathways shared in different disease conditions. Next, drug efficacy is assessed by the reversibility of abnormal gene expression, and results are clustered to identify repurposing targets. To cluster similar diseases, gene expression data from 262 cases of 31 diseases and 268 controls were analyzed by Uniform Manifold Approximation and Projection for Dimension Reduction followed by k-means to optimize the number of clusters. For evaluation, we examined disease-specific gene expression data for inclusion, body myositis, polymyositis, and dermatomyositis (DM), and used LINCS L1000 characteristic direction signatures search engine (L1000CDS2) to obtain lists of small-molecule compounds that reversed the expression patterns of these specifically altered genes as candidates for drug repurposing. Finally, the functions of affected genes were analyzed by Gene Set Enrichment Analysis to examine consistency with expected drug efficacy. Consequently, we found disease-specific gene expression, and importantly, identified 20 drugs such as BMS-387032, phorbol-12-myristate-13-acetate, mitoxantrone, alvocidib, and vorinostat as candidates for repurposing. These were previously noted to be effective against two of the three diseases, and have a high probability of being effective against the other. That is, inclusion body myositis and DM. The two-stage prediction approach to drug repurposing presented here offers innovation to inform future drug discovery and clinical trials in a variety of human diseases.

PMID:35666246 | DOI:10.1089/omi.2022.0026

Mycoses. 2022 Jun 3. doi: 10.1111/myc.13477. Online ahead of print.

ABSTRACT

Candida auris is a drug-resistant pathogen with several reported outbreaks. The treatment of C. auris infections is difficult due to a limited number of available antifungal drugs. Thus, finding alternative drugs through repurposing approaches would be clinically beneficial. A systematic search in PubMed, Scopus, and Web of Science databases as well as Google Scholar up to 1 November 2021, was conducted to find all articles with data regarding the antifungal activity of non-antifungal drugs against the planktonic and biofilm forms of C. auris. During database and hand searching, 290 articles were found, of which 13 were eligible for inclusion in the present study. Planktonic and biofilm forms have been studied in 11 and 8 articles (with both forms examined in 6 articles), respectively. In total, 22 and 12 drugs/compounds have been reported as repositionable against planktonic and biofilm forms of C. auris, respectively. Antiparasitic drugs, with the dominance of miltefosine, were the most common repurposed drugs against both forms of C. auris, followed by anticancer drugs (e.g. alexidine dihydrochloride) against the planktonic form and anti-inflammatory drugs (e.g. ebselen) against the biofilm form of the fungus. A collection of other drugs from various classes have also shown promising activity against C. auris. Following drug repurposing approaches, a number of drugs/compounds from various classes have been found to inhibit the planktonic and biofilm forms of C. auris. Accordingly, drug repurposing is an encouraging approach for discovering potential alternatives to conventional antifungal agents to combat drug resistance in fungi, especially C. auris.

PMID:35665544 | DOI:10.1111/myc.13477

Front Immunol. 2022 May 17;13:920442. doi: 10.3389/fimmu.2022.920442. eCollection 2022.

NO ABSTRACT

PMID:35663988 | PMC:PMC9156861 | DOI:10.3389/fimmu.2022.920442

Drug Discov Today. 2022 May 31:S1359-6446(22)00217-3. doi: 10.1016/j.drudis.2022.05.026. Online ahead of print.

NO ABSTRACT

PMID:35661705 | DOI:10.1016/j.drudis.2022.05.026

Biomed Pharmacother. 2022 Jun;150:113058. doi: 10.1016/j.biopha.2022.113058. Epub 2022 May 2.

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide pandemic with unprecedented economic and societal impact. Currently, several vaccines are available and multitudes of antiviral treatments have been proposed and tested. Although many of the vaccines show clinical efficacy, they are not equally accessible worldwide. Additionally, due to the continuous emergence of new variants and generally short duration of immunity, the development of effective antiviral treatments remains of the utmost importance. Since the emergence of SARS-CoV-2, substantial efforts have been undertaken to repurpose existing drugs for accelerated clinical testing and emergency use authorizations. However, drug-repurposing studies using cellular assays often identify hits that later prove ineffective clinically, highlighting the need for more complex screening models. To this end, we evaluated the activity of single compounds that have either been tested clinically or already undergone extensive preclinical profiling, using a standardized in vitro model of human nasal epithelium. Furthermore, we also evaluated drug combinations based on a sub-maximal concentration of molnupiravir. We report the antiviral activity of 95 single compounds and 30 combinations. We show that only a few single agents are highly effective in inhibiting SARS-CoV-2 replication while selected drug combinations containing 10 µM molnupiravir boosted antiviral activity compared to single compound treatment. These data indicate that molnupiravir-based combinations are worthy of further consideration as potential treatment strategies against coronavirus disease 2019 (COVID-19).

PMID:35658229 | DOI:10.1016/j.biopha.2022.113058

Med Rev (Berl). 2022 Feb 14;2(1):110-113. doi: 10.1515/mr-2021-0017. eCollection 2022 Feb 1.

ABSTRACT

Alzheimer's disease and related dementias (AD/ADRD) affects more than 50 million people worldwide but there is no clear therapeutic option affordable for the general patient population. Recently, drug repositioning studies featuring collaborations between academic institutes, medical centers, and hospitals are generating novel therapeutics candidates against these devastating diseases and filling in an important area for healthcare that is poorly represented by pharmaceutical companies. Such drug repositioning studies converge expertise from bioinformatics, chemical informatics, medical informatics, artificial intelligence, high throughput and high-content screening and systems biology. They also take advantage of multi-scale, multi-modality datasets, ranging from transcriptomic and proteomic data, electronical medical records, and medical imaging to social media information of patient behaviors and emotions and epidemiology profiles of disease populations, in order to gain comprehensive understanding of disease mechanisms and drug effects. We proposed a recursive drug repositioning paradigm involving the iteration of three processing steps of modeling, prediction, and validation to identify known drugs and bioactive compounds for AD/ADRD. This recursive paradigm has the potential of quickly obtaining a panel of robust novel drug candidates for AD/ADRD and gaining in-depth understanding of disease mechanisms from those repositioned drug candidates, subsequently improving the success rate of predicting novel hits.

PMID:35658114 | PMC:PMC9047641 | DOI:10.1515/mr-2021-0017

Front Genet. 2022 May 16;13:921286. doi: 10.3389/fgene.2022.921286. eCollection 2022.

ABSTRACT

[This corrects the article DOI: 10.3389/fgene.2022.792090.].

PMID:35656321 | PMC:PMC9151565 | DOI:10.3389/fgene.2022.921286

Comput Biol Med. 2022 May 27:105669. doi: 10.1016/j.compbiomed.2022.105669. Online ahead of print.

ABSTRACT

GLS1 enzymes (Glutaminase C (GAC) and kidney-type Glutaminase (KGA)) are gaining prominence as a target for tumor treatment including lung, breast, kidney, prostate, and colorectal. To date, several medicinal chemistry studies are being conducted to develop new and effective inhibitors against GLS1 enzymes. Telaglenastat, a drug that targets the allosteric site of GLS1, has undergone clinical trials for the first time for the therapy of solid tumors and hematological malignancies. A comprehensive computational investigation is performed to get insights into the inhibition mechanism of the Telaglenastat. Some novel inhibitors are also proposed against GLS1 enzymes using the drug repurposing approach using 2D-fingerprinting virtual screening method against 2.4 million compounds, application of pharmacokinetics, Molecular Docking, and Molecular Dynamic (MD) Simulations. A TIP3P water box of 10 Å was defined to solvate both enzymes to improve MD simulation reliability. The dynamics results were validated further by the MMGB/PBSA binding free energy method, RDF, and AFD analysis. Results of these computational analysis revealed a stable binding affinity of Telaglenastat, as well as an FDA approved drug Astemizole (IC50 ∼ 0.9 nM) and a novel para position oriented methoxy group containing Chembridge compound (Chem-64284604) that provides an effective inhibitory action against GAC and KGA.

PMID:35654625 | DOI:10.1016/j.compbiomed.2022.105669

Neurology. 2022 Jun 2:10.1212/WNL.0000000000200803. doi: 10.1212/WNL.0000000000200803. Online ahead of print.

NO ABSTRACT

PMID:35654591 | DOI:10.1212/WNL.0000000000200803

Microb Pathog. 2022 May 30:105608. doi: 10.1016/j.micpath.2022.105608. Online ahead of print.

ABSTRACT

The recent pandemic, Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has devastated humanity and is continuing to threaten us. Due to the high transmissibility of this pathogen, researchers are still trying to cope with the treatment and prevention of this disease. Few of them were successful in finding cure for COVID-19 by including repurposed drugs in the treatment. In such pandemic situations, when it is nearly impossible to design and implement a new drug target, previously designed antiviral drugs could help against novel viruses, referred to as drug repurposing/redirecting/repositioning or re-profiling. This review describes the current landscape of the repurposing of antiviral drugs for COVID-19 and the impact of these drugs on our nervous system. In some cases, specific antiviral therapy has been notably associated with neurological toxicity, characterized by peripheral neuropathy, neurocognitive and neuropsychiatric effects within the central nervous system (CNS).

PMID:35654381 | DOI:10.1016/j.micpath.2022.105608

Crit Rev Oncol Hematol. 2022 May 30:103730. doi: 10.1016/j.critrevonc.2022.103730. Online ahead of print.

ABSTRACT

Drug repositioning in cancer has been pursued for years because of slowing drug development, increasing costs, and the availability of drugs licensed for other indications with anticancer effects in the laboratory. Repositioning has encountered obstacles due to generally insufficient single-agent clinical anticancer effects of licensed drugs and a subsequent reluctance by pharmaceutical companies to invest in phase III combination studies with them. Here we review potential machine learning/artificial intelligence (ML/AI) approaches for using real-world data (RWD) that could overcome the limitations of clinical trials and retrospective analyses. We outline a two-tiered filtering approach of identifying top-ranked drugs based on their drug-target binding affinity scores while considering their challenges and matching the top-ranked drugs with their top-ranked specific scenarios from among the multitude of real-world scenarios for efficacy and safety. This approach will generate RWD scenario-specific hypotheses that can be tested in randomized clinical trials with high probabilities of success.

PMID:35654244 | DOI:10.1016/j.critrevonc.2022.103730