Int J Gynecol Cancer. 2022 Sep 22:ijgc-2022-003585. doi: 10.1136/ijgc-2022-003585. Online ahead of print.

ABSTRACT

OBJECTIVE: Drug repurposing is an alternative development pathway that utilizes the properties of drugs approved for other diseases and builds on available safety and pharmacological data to develop the drug as a potential treatment for other diseases. A literature-based approach was performed to identify drug repurposing opportunities in cervical cancer to inform future research and trials.

METHODS: We queried PubMed for each drug included in two databases (ReDO_DB and CDcervix_DB, which include 300+ non-cancer drugs and 200+ cancer drugs not used in cervical cancer, respectively) and manually assessed all abstracts for relevance and activity in cervix cancer, and type of evidence. Subsequently, we also performed a search of clinical trial databases where we generated a list of registered trials in cervical cancer with all drugs from our databases.

RESULTS: Of the 534 drugs from both databases, 174 (33%) had at least one relevant abstract or registered trial in cervical cancer. 94 (18%) drugs had at least human data available, and 52 (10%) drugs were evaluated in registered trials. To prioritize drugs to consider for future trials, all 174 drugs were further assessed for strength of scientific rationale, feasibility for integration in cervical cancer standard of care, evidence of radiosensitization, and potential mechanism of action. Out of the 174 drugs, 38 (22%) potential drug candidates were selected.

CONCLUSION: This study resulted in a list of candidate drugs for potential evaluation in cervical cancer. Many drugs might warrant additional (pre)clinical investigation, which could be done in a coordinated manner using platform trials.

PMID:36137575 | DOI:10.1136/ijgc-2022-003585

Biophys Chem. 2022 Sep 11;290:106891. doi: 10.1016/j.bpc.2022.106891. Online ahead of print.

ABSTRACT

The COVID-19 pandemic created an unprecedented global healthcare emergency prompting the exploration of new therapeutic avenues, including drug repurposing. A large number of ongoing studies revealed pervasive issues in clinical research, such as the lack of accessible and organised data. Moreover, current shortcomings in clinical studies highlighted the need for a multi-faceted approach to tackle this health crisis. Thus, we set out to explore and develop new strategies for drug repositioning by employing computational pharmacology, data mining, systems biology, and computational chemistry to advance shared efforts in identifying key targets, affected networks, and potential pharmaceutical intervention options. Our study revealed that formulating pharmacological strategies should rely on both therapeutic targets and their networks. We showed how data mining can reveal regulatory patterns, capture novel targets, alert about side-effects, and help identify new therapeutic avenues. We also highlighted the importance of the miRNA regulatory layer and how this information could be used to monitor disease progression or devise treatment strategies. Importantly, our work bridged the interactome with the chemical compound space to better understand the complex landscape of COVID-19 drugs. Machine and deep learning allowed us to showcase limitations in current chemical libraries for COVID-19 suggesting that both in silico and experimental analyses should be combined to retrieve therapeutically valuable compounds. Based on the gathered data, we strongly advocate for taking this opportunity to establish robust practices for treating today's and future infectious diseases by preparing solid analytical frameworks.

PMID:36137310 | DOI:10.1016/j.bpc.2022.106891

Med Sci (Basel). 2022 Aug 31;10(3):48. doi: 10.3390/medsci10030048.

ABSTRACT

The high cost and time for developing a new drug or repositioning a partially-developed drug has fueled interest in "repurposing" drugs. Drug repurposing is particularly of interest for Alzheimer's disease (AD) or AD-related dementias (ADRD) because there are no unrestricted disease-modifying treatments for ADRD. We have designed and pilot tested a 3-Step Medication-Wide Association Study Plus (MWAS+) approach to rigorously accelerate the identification of drugs with a high potential to be repurposed for delaying and preventing AD/ADRD: Step 1 is a hypothesis-free exploration; Step 2 is mechanistic filtering; And Step 3 is hypothesis testing using observational data and prospective cohort design. Our results demonstrated the feasibility of the MWAS+ approach. The Step 1 analysis identified potential candidate drugs including atorvastatin and GLP1. The literature search in Step 2 found evidence supporting the mechanistic plausibility of the statin-ADRD association. Finally, Step 3 confirmed our hypothesis that statin may lower the risk of incident ADRD, which was statistically significant using a target trial design that emulated randomized controlled trials.

PMID:36135833 | DOI:10.3390/medsci10030048

Curr Oncol. 2022 Sep 10;29(9):6508-6522. doi: 10.3390/curroncol29090512.

ABSTRACT

The Raf-MEK-ERK signaling network has been the subject of intense research due to its role in the development of human cancers, including pediatric neuroblastoma (NB). MEK and ERK are the central components of this signaling pathway and are attractive targets for cancer therapy. Approximately 3-5% of the primary NB samples and about 80% of relapsed samples contain mutations in the Raf-MEK-ERK pathway. In the present study, we analyzed the NB patient datasets and revealed that high RAF and MEK expression leads to poor overall survival and directly correlates with cancer progression and relapse. Further, we repurposed a specific small-molecule MEK inhibitor CI-1040 to inhibit the Raf-MEK-ERK pathway in NB. Our results show that CI-1040 potently inhibits NB cell proliferation and clonogenic growth in a dose-dependent manner. Inhibition of the Raf-MEK-ERK pathway by CI-1040 significantly enhances apoptosis, blocks cell cycle progression at the S phase, inhibits expression of the cell cycle-related genes, and significantly inhibits phosphorylation and activation of the ERK1/2 protein. Furthermore, CI-1040 significantly inhibits tumor growth in different NB 3D spheroidal tumor models in a dose-dependent manner and by directly inhibiting spheroidal tumor cells. Overall, our findings highlight that direct inhibition of the Raf-MEK-ERK pathway is a novel therapeutic approach for NB, and further developing repurposing strategies using CI-1040 is a clinically tractable strategy for effectively treating NB.

PMID:36135081 | DOI:10.3390/curroncol29090512

J Biomol Struct Dyn. 2022 Sep 22:1-9. doi: 10.1080/07391102.2022.2124453. Online ahead of print.

ABSTRACT

Drug repurposing is a method to identify novel therapeutic agents from the existing drugs and clinical compounds. In the present comprehensive work, molecular docking, virtual screening and dynamics simulations were carried out for ten cancer types viz breast, colon, central nervous system, leukaemia, melanoma, ovarian, prostate, renal and lung (non-small and small cell) against validated eighteen kinase targets. The study aims to understand the action of chemotherapy drugs mechanism through binding interactions against selected targets via comparative docking simulations with the state-art molecular modelling suits such as MOE, Cresset-Flare, AutoDock Vina, GOLD and GLIDE. Chemotherapeutic drugs (n = 112) were shortlisted from standard drug databases with appropriate chemoinformatic filters. Based on docking studies it was revealed that leucovorin, nilotinib, ellence, thalomid and carfilzomib drugs possessed potential against other cancer targets. A library was built to enumerate novel molecules based on the scaffold and functional groups extracted from known drugs and clinical compounds. Twenty novel molecules were prioritised further based on drug-like attributes. These were cross docked against 1MQ4 Aurora-A Protein Kinase for prostate cancer and 4UYA Mitogen-activated protein kinase for renal cancer. All docking programs yielded similar results but interestingly AutoDock Vina yielded the lowest RMSD with the native ligand. To further validate the final docking results at atomistic level, molecular dynamics simulations were performed to ascertain the stability of the protein-ligand complex. The study enables repurposing of drugs and lead identification by employing a host of structure and ligand based virtual screening tools and techniques.Communicated by Ramaswamy H. Sarma.

PMID:36134605 | DOI:10.1080/07391102.2022.2124453

Front Oncol. 2022 Sep 5;12:989167. doi: 10.3389/fonc.2022.989167. eCollection 2022.

ABSTRACT

Neutrophil extracellular traps (NETs) have recently been identified to play a crucial role in cancer metastasis. However, the therapeutic target in NETs of melanoma cancer metastasis is still unknown. In this work, we screened a collection of 231 small molecule compounds. We identified ivermectin (IVM), a widely used antiparasitic drug, significantly inhibits neutrophil extracellular traps (NETs) formation after cathepsin B (CTSB) treatment. In vivo, IVM treatment showed no effects of melanoma tumor growth, while the orthotopic melanoma to lung metastasis was significantly suppressed by IVM. Serum level of myeloperoxidase-DNA and neutrophil elastase-DNA were suppressed after IVM treatment. Tumor infiltrated myeloid-derived suppressor cells (MDSCs) were significantly suppressed while tumor infiltrated CD8+T cells in lung was increased after IVM treatment in mouse melanoma model. Mechanistically, IVM targeted a pyroptotic driving factor gasdermin D (GSDMD), and exhibited a Kd of 267.96 nM by microscale thermophoresis (MST) assay. Furthermore, the direct interaction of IVM and GSDMD significantly suppressed GSDMD oligomerization, which are essential for GSDMD-dependent NETs formation. In vitro, treatment with CTSB in bone marrow neutrophils significantly promotes NETs formation, and the release of extracellular DNA was significantly suppressed by IVM pretreatment. Collectively, our results reveal that with the regulation role of IVM in neutrophils and NETs, IVM may potentially be used as a viable therapeutic approach for the treatment of melanoma cancer metastasis.

PMID:36132145 | PMC:PMC9484526 | DOI:10.3389/fonc.2022.989167

J Biomol Struct Dyn. 2022 Sep 21:1-15. doi: 10.1080/07391102.2022.2125076. Online ahead of print.

ABSTRACT

Breast cancer (BC) is prevalent worldwide and is a leading cause of death among women. However, cell-surface glucose-regulated protein 78 (cs-GRP78) is overexpressed in several types of cancer and during pathogen infections. This study examines two well-known BC drugs approved by the FDA as BC treatments to GRP78. The first type consists of inhibitors of cyclin-based kinases 4/6, including abemaciclib, palbociclib, ribociclib, and dinaciclib. In addition, tunicamycin, and doxorubicin, which are among the most effective anticancer drugs for early and late-stage BC, are tested against GRP78. As (-)-epiGallocatechin gallate inhibits GRP78, it is also being evaluated (used as positive control). Thus, using molecular dynamics simulation approaches, this study aims to examine the advantages of targeting GRP78, which represents a promising cancer therapy regime. In light of recent advances in computational drug response prediction models, this study aimed to examine the benefits of GRP78 targeting, which represents a promising cancer therapy regime, by utilizing combined molecular docking and molecular dynamics simulation approaches. The simulated protein (50 ns) was docked with the drugs, then a second round of dynamics simulation was performed for 100 ns. After that, the binding free energies were calculated from 30 to 100 ns for each complex during the simulation period. These findings demonstrate the efficacy of abemaciclib, ribociclib, and tunicamycin in binding to the nucleotide-binding domain of the GRP78, paving the way for elucidating the mode of interactions between these drugs and cancer (and other stressed) cells that overexpress GRP78. Communicated by Ramaswamy H. Sarma.

PMID:36129131 | DOI:10.1080/07391102.2022.2125076

Cancer Cell Int. 2022 Sep 20;22(1):289. doi: 10.1186/s12935-022-02713-9.

ABSTRACT

BACKGROUND: The emergence of de novo or intrinsic trastuzumab resistance is exceedingly high in breast cancer that is HER2 positive and correlates with an abundant cancer stem cell (CSC)-like population. We sought to examine the capacity of β-escin, an anti-inflammatory drug, to address trastuzumab resistance in HER2-positive breast cancer cells.

METHODS: The effect of β-escin on trastuzumab-resistant and -sensitive cell lines in vitro was evaluated for apoptosis, expression of HER2 family members, and impact on CSC-like properties. An in vivo model of trastuzumab-resistant JIMT-1 was used to examine the efficacy and toxicity of β-escin.

RESULTS: β-escin induced mitochondrial-mediated apoptosis accompanied by reactive oxygen species (ROS) production and increased active p18Bax fragmentation, leading to caspase-3/-7 activation. Attenuation of CSC-related features by β-escin challenge was accompanied by marked reductions in CD44high/CD24low stem-like cells and aldehyde dehydrogenase 1 (ALDH1) activity as well as hindrance of mammosphere formation. β-escin administration also significantly retarded tumor growth and angiogenesis in a trastuzumab-resistant JIMT-1 xenograft model via downregulation of CSC-associated markers and intracellular domain HER2. Importantly, β-escin selectively inhibited malignant cells and was less toxic to normal mammary cells, and no toxic effects were found in liver and kidney function in animals.

CONCLUSIONS: Taken together, our findings highlight β-escin as a promising candidate for the treatment of trastuzumab-resistant HER2-positive breast cancers.

PMID:36127671 | DOI:10.1186/s12935-022-02713-9

Biomed Pharmacother. 2022 Sep 17;155:113713. doi: 10.1016/j.biopha.2022.113713. Online ahead of print.

ABSTRACT

Liver cancer is the fifth most widespread in the world, with a high fatality rate and poor prognosis.However,surgicalresction,thermal/radiofrequencyablation,chemo/radioembolization and pathway targeting to the cancer cells are all possible options for treating Liver Carcinoma. Unfortunately, once the tumour has developed and spread, diagnosis often occurs too late. The targeted therapy has demonstrated notable, albeit modest, efficacy in some patients with advanced HCC. This demonstrates the necessity of creating additional focused treatments and, in pursuit of this end, the need to find ever-more pathways as prospective targets. Despite the critical need, there are currently no Wnt signalling directed therapy on the research field, only a few methods have progressed beyond the early stage of clinical studies. In the present study, we report that repurposing of drug previously licensed for other diseases is one possible strategy inhibit malignant cell proliferation and renewal by removing individuals protein expression in the Wnt/β-catenin pathway. Particularly β-catenin complex is present in Liver cancer, where tumour necrosis factor is indispensable for the complex formation and β-catenin interactions are disrupted upon drug in nano-carrier through nanotechnology. This study findings not only highlight that repurposing drug could improve liver cancer treatment outcomes but also focused to character traits and functions of the Wnt signalling cascade's molecular targets and how they could be used to get anti-tumour results method to targeting Wnt/β-catenin in liver carcinoma.

PMID:36126453 | DOI:10.1016/j.biopha.2022.113713

Brief Bioinform. 2022 Sep 19:bbac384. doi: 10.1093/bib/bbac384. Online ahead of print.

ABSTRACT

Drug repositioning (DR) is a promising strategy to discover new indicators of approved drugs with artificial intelligence techniques, thus improving traditional drug discovery and development. However, most of DR computational methods fall short of taking into account the non-Euclidean nature of biomedical network data. To overcome this problem, a deep learning framework, namely DDAGDL, is proposed to predict drug-drug associations (DDAs) by using geometric deep learning (GDL) over heterogeneous information network (HIN). Incorporating complex biological information into the topological structure of HIN, DDAGDL effectively learns the smoothed representations of drugs and diseases with an attention mechanism. Experiment results demonstrate the superior performance of DDAGDL on three real-world datasets under 10-fold cross-validation when compared with state-of-the-art DR methods in terms of several evaluation metrics. Our case studies and molecular docking experiments indicate that DDAGDL is a promising DR tool that gains new insights into exploiting the geometric prior knowledge for improved efficacy.

PMID:36125202 | DOI:10.1093/bib/bbac384

J Biomol Struct Dyn. 2022 Sep 20:1-8. doi: 10.1080/07391102.2022.2123393. Online ahead of print.

ABSTRACT

There is an urgent requirement for drug discovery and more importantly drug repositioning due to infectious new Severe Acute Respiratory Syndrome coronavirus 2. As per the recent report published in the journal L'Encéphale in May 2020, there is a planned ReCoVery Study examining the repurposing the chlorpromazine for the treatment of COVID-19. Here, we apply a combined Raman microspectroscopy and DFT-MD approach to investigate the structural dynamics of the Chlorpromazine (CPZ) drug with dipalmitoylphosphatidylcholine (DPPC) lipid bilayer, identifying the specific position of the drug in the DPPC lipid bilayer. The intensity ratios of the Raman peaks I2935/I2880, I1097/I1064 and I1097/I1129 are representative of the interaction of drugs with lipid alkyl chains and furnish conformation of lipid alkyl chains. Raman imaging microscopy for the study of the distribution of CPZ inside the lipid vesicles is reported. We also investigated the influence of order and disorder ratio in the CPZ on the DPPC liposomes prepared on phase transition temperature. HIGHLIGHTSDrug-membrane interactions using micromolar concentrations of both lipid and drugs.Neuroleptic drug and DPPC vesicles composed of DPPC/drug mixtures reveal qualitative differences between the Raman spectraThe temperature-controlled Raman microspectroscopic study has demonstrated that below phase-transition temperature, the fatty acid chains of the phospholipids are stiff and packed in a highly ordered array.DFT and MD simulations to understand molecular interactions, structural dynamics, and Raman spectra.Above phase-transition temperature, the chains are disordered and possess more motional freedom.Communicated by Ramaswamy H. Sarma.

PMID:36124814 | DOI:10.1080/07391102.2022.2123393

Bioinformatics. 2022 Sep 16;38(Supplement_2):ii75-ii81. doi: 10.1093/bioinformatics/btac496.

ABSTRACT

MOTIVATION: Machine-learning-based prediction of compound-protein interactions (CPIs) is important for drug design, screening and repurposing. Despite numerous recent publication with increasing methodological sophistication claiming consistent improvements in predictive accuracy, we have observed a number of fundamental issues in experiment design that produce overoptimistic estimates of model performance.

RESULTS: We systematically analyze the impact of several factors affecting generalization performance of CPI predictors that are overlooked in existing work: (i) similarity between training and test examples in cross-validation; (ii) synthesizing negative examples in absence of experimentally verified negative examples and (iii) alignment of evaluation protocol and performance metrics with real-world use of CPI predictors in screening large compound libraries. Using both state-of-the-art approaches by other researchers as well as a simple kernel-based baseline, we have found that effective assessment of generalization performance of CPI predictors requires careful control over similarity between training and test examples. We show that, under stringent performance assessment protocols, a simple kernel-based approach can exceed the predictive performance of existing state-of-the-art methods. We also show that random pairing for generating synthetic negative examples for training and performance evaluation results in models with better generalization in comparison to more sophisticated strategies used in existing studies. Our analyses indicate that using proposed experiment design strategies can offer significant improvements for CPI prediction leading to effective target compound screening for drug repurposing and discovery of putative chemical ligands of SARS-CoV-2-Spike and Human-ACE2 proteins.

AVAILABILITY AND IMPLEMENTATION: Code and supplementary material available at https://github.com/adibayaseen/HKRCPI.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:36124806 | DOI:10.1093/bioinformatics/btac496

Brief Bioinform. 2022 Sep 17:bbac402. doi: 10.1093/bib/bbac402. Online ahead of print.

ABSTRACT

A transcriptional regulatory network (TRN) is a collection of transcription regulators with their associated downstream genes, which is highly condition-specific. Understanding how cell states can be programmed through small molecules/drugs or conditions by modulating the whole gene expression system granted us the potential to amend abnormal cells and cure diseases. Condition Orientated Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/home) is a library of condition (small molecule/drug treatments and gene knockdowns)-based transcriptional regulatory sub-networks (TRSNs) that come with an online TRSN matching tool. It allows users to browse condition-associated TRSNs or match those TRSNs by inputting transcriptomic changes of interest. CORN utilizes transcriptomic changes data after specific conditional treatment in cells, and in vivo transcription factor (TF) binding data in cells, by combining TF binding information and calculations of significant expression alterations of TFs and genes after the conditional treatments, TRNs under the effect of different conditions were constructed. In short, CORN associated 1805 different types of specific conditions (small molecule/drug treatments and gene knockdowns) to 9553 TRSNs in 25 human cell lines, involving 204TFs. By linking and curating specific conditions to responsive TRNs, the scientific community can now perceive how TRNs are altered and controlled by conditions alone in an organized manner for the first time. This study demonstrated with examples that CORN can aid the understanding of molecular pathology, pharmacology and drug repositioning, and screened drugs with high potential for cancer and coronavirus disease 2019 (COVID-19) treatments.

PMID:36124777 | DOI:10.1093/bib/bbac402

Drug Discov Today. 2022 Sep 16:103366. doi: 10.1016/j.drudis.2022.103366. Online ahead of print.

ABSTRACT

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp3 carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development. Teaser.

PMID:36122862 | DOI:10.1016/j.drudis.2022.103366

Int J Biol Macromol. 2022 Sep 16:S0141-8130(22)02017-7. doi: 10.1016/j.ijbiomac.2022.09.086. Online ahead of print.

ABSTRACT

Since the inception of COVID-19 pandemic in December 2019, socio-economic crisis begins to rise globally and SARS-CoV-2 was responsible for this outbreak. With this outbreak, currently, world is in need of effective and safe eradication of COVID-19. Hence, in this study anti-SAR-Co-2 potential of FDA approved marine drugs (Biological macromolecules) data set is explored computationally using machine learning algorithm of Flare by Cresset Group, Field template, 3D-QSAR and activity Atlas model was generated against FDA approved M-pro SARS-CoV-2 repurposed drugs including Nafamostat, Hydroxyprogesterone caporate, and Camostat mesylate. Data sets were categorized into active and inactive molecules on the basis of their structural and biological resemblance with repurposed COVID-19 drugs. Then these active compounds were docked against the five different M-pro proteins co-crystal structures. Highest LF VS score of Holichondrin B against all main protease co-crystal structures ranked it as lead drug. Finally, this new technique of drug repurposing remained efficient to explore the anti-SARS-CoV-2 potential of FDA approved marine drugs.

PMID:36122771 | DOI:10.1016/j.ijbiomac.2022.09.086

Antiviral Res. 2022 Sep 16:105417. doi: 10.1016/j.antiviral.2022.105417. Online ahead of print.

ABSTRACT

Naturally evolved immune-escape PreS2 mutant is an oncogenic caveat of liver cirrhosis and hepatocellular carcinoma (HCC) during chronic hepatitis B virus (HBV) infection. PreS2 mutant is prevalent in above 50% of patients with HCC. In addition, intrahepatic expression of PreS2 mutant large surface antigen (PreS2-LHBS) induces endoplasmic reticulum stress, mitochondria dysfunction, cytokinesis failure, and subsequent chromosome hyperploidy. As PreS2-LHBS has no enzymatic activity, the development of PreS2-specific inhibitors can be challenging. In this study, we aim to identify inhibitors of PreS2-LHBS via the induction of protein-specific degradation. We set up a large-scale protein stability reporter platform and applied an FDA-approved drug library for the screening. We identified ABT199 as a negative modulator of PreS2-LHBS, which induced the degradation of PreS2-LHBS without affecting the general cell viability in both hepatoma and immortalized hepatocytes. Next, by affinity purification screening, we found that PreS2-LHBS interacted with HSC70, a microautophagy mediating chaperone. Simultaneously, inhibitions of lysosomal degradation or microautophagy restored the expression of PreS2-LHBS, suggesting microautophagy is involved in ABT199-induced PreS2-LHBS degradation. Notably, a 24-hr treatment of ABT199 was sufficient for the reduction of DNA damage and cytokinesis failure in PreS2-LHBS expressing hepatocytes. In addition, a persistent treatment of ABT199 for 3 weeks reversed chromosome hyperploidy in PreS2-LHBS cells and suppressed anchorage-independent growth of HBV-positive hepatoma cells. Together, this study identified ABT-199 as a negative modulator of PreS2-LHBS via mediating microautophagy. Our results indicated that long-term inhibition of PreS2-LHBS may serve as a novel strategy for the therapeutic prevention of HBV-mediated HCC.

PMID:36122619 | DOI:10.1016/j.antiviral.2022.105417

Esophagus. 2022 Sep 19. doi: 10.1007/s10388-022-00948-z. Online ahead of print.

ABSTRACT

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a malignant cancer with a poor prognosis. Chemoradiotherapy is one of the most important strategies for patients with locally advanced unresectable ESCC; however, its therapeutic effect is unsatisfactory. Tumor-initiating cells (TICs) have been reported to be resistant to conventional chemotherapy and radiotherapy so far. Therefore, we aimed to develop a treatment strategy targeting TICs in ESCC to improve radiosensitivity.

METHODS: First, we validated aldehyde dehydrogenase 1 (ALDH1) as a TIC marker and investigated its ability to mediate resistance in human ESCC cell lines using flow cytometry, Western blotting, and functional analyses. Then, we focused on disulfiram (DSF), an aldehyde dehydrogenase inhibitor, used to treat alcohol use disorder. We investigated the effect of DSF and copper (II) D-gluconate (Cu) on the radiosensitivity of ESCC in xenograft mouse models.

RESULTS: ALDH1-positive cells showed an upregulation of SOX2 and Nanog, exhibiting much stronger tumor-initiating properties than ALDH1-negative cells. Furthermore, inhibition of ALDH1 attenuated the tumor-initiating properties of ESCC cell lines. Our results also showed that ALDH1-positive cells were resistant to chemotherapy and radiotherapy, and the inhibition of ALDH1 led to the mitigation of therapeutic resistance. Our in vitro and in vivo studies revealed that the DSF/Cu complex could radiosensitize ALDH1-positive ESCC cells and downregulate the phosphoinositide 3-kinase/Akt pathway.

CONCLUSION: ALDH1 inhibition by the DSF/Cu complex enhances the radiosensitivity of TICs in ESCC. The drug repositioning approach using disulfiram is a potential treatment option to overcome radioresistance in patients with locally advanced ESCC.

PMID:36121574 | DOI:10.1007/s10388-022-00948-z

J Biomol Struct Dyn. 2022 Sep 19:1-14. doi: 10.1080/07391102.2022.2123397. Online ahead of print.

ABSTRACT

Multidrug resistance (MDR) is a fundamental reason for the fiasco of carcinoma chemotherapy. A wide variety of anticarcinoma drugs are expelled from neoplasm cells through the ATP-binding cassette (ABC) transporter superfamily, rendering the neoplasm cells resistant to treatment. The ATP-binding cassette transporter G2 (ABCG2, gene symbol BCRP) is an ABC efflux transporter that plays a key function in MDR to antineoplastic therapies. For these reasons, the identification of medicaments as BCRP inhibitors could assist in discovering better curative approaches for breast cancer therapy. Because of the deficiency of prospective BCRP inhibitors, the SuperDRUG2 database was virtually screened for inhibitor activity towards the BCRP transporter using molecular docking computations. The most potent drug candidates were then characterized utilizing molecular dynamics (MD) simulations. Furthermore, molecular mechanics-generalized Born surface area (MM-GBSA) binding affinities of the most potent drug candidates were estimated. Based on the MM-GBSA binding affinities throughout 150 ns MD simulations, three drugs-namely zotarolimus (SD002595), temsirolimus (SD003393), and glecaprevir (SD006009)-revealed greater binding affinities towards BCRP transporter compared to the co-crystallized BWQ ligand with ΔGbinding values of -86.6 ± 5.6, -79.5 ± 8.0, -75.8 ± 4.6 and -59.5 ± 4.1 kcal/mol, respectively. The steadiness of these promising drugs bound with BCRP transporter was examined utilizing their structural and energetical analyses throughout a 150 ns MD simulation. To imitate the physiological environment, 150 ns MD simulations for the identified drugs bound with BCRP transporter were conducted in the 1-palmitoyl-2-oleoyl-phosphatidylcholine lipid bilayer. These findings identify zotarolimus, temsirolimus and glecaprevir as auspicious anti-MDR drug leads that warrant further experimental assays.Communicated by Ramaswamy H. Sarma.

PMID:36120948 | DOI:10.1080/07391102.2022.2123397

ACS Omega. 2022 Aug 31;7(36):31999-32013. doi: 10.1021/acsomega.2c02983. eCollection 2022 Sep 13.

ABSTRACT

Drug-metabolizing enzyme (DME)-mediated pharmacokinetic resistance of some clinically approved anticancer agents is one of the main reasons for cancer treatment failure. In particular, some commonly used anticancer medicines, including docetaxel, tamoxifen, imatinib, cisplatin, and paclitaxel, are inactivated by CYP1B1. Currently, no approved drugs are available to treat this CYP1B1-mediated inactivation, making the pharmaceutical industries strive to discover new anticancer agents. Because of the extreme complexity and high risk in drug discovery and development, it is worthwhile to come up with a drug repurposing strategy that may solve the resistance problem of existing chemotherapeutics. Therefore, in the current study, a drug repurposing strategy was implemented to find the possible CYP1B1 inhibitors using machine learning (ML) and structure-based virtual screening (SB-VS) approaches. Initially, three different ML models were developed such as support vector machines (SVMs), random forest (RF), and artificial neural network (ANN); subsequently, the best-selected ML model was employed for virtual screening of the selleckchem database to identify potential CYP1B1 inhibitors. The inhibition potency of the obtained hits was judged by analyzing the crucial active site amino acid interactions against CYP1B1. After a thorough assessment of docking scores, binding affinities, as well as binding modes, four compounds were selected and further subjected to in vitro analysis. From the in vitro analysis, it was observed that chlorprothixene, nadifloxacin, and ticagrelor showed promising inhibitory activity toward CYP1B1 in the IC50 range of 0.07-3.00 μM. These new chemical scaffolds can be explored as adjuvant therapies to address CYP1B1-mediated drug-resistance problems.

PMID:36120033 | PMC:PMC9476183 | DOI:10.1021/acsomega.2c02983

Front Oncol. 2022 Sep 2;12:965261. doi: 10.3389/fonc.2022.965261. eCollection 2022.

ABSTRACT

Well differentiated and dedifferentiated liposarcomas (WDLPS and DDLPS) are tumors of the adipose tissue poorly responsive to conventional cytotoxic chemotherapy which currently remains the standard-of-care. The dismal prognosis of the DDLPS subtype indicates an urgent need to identify new therapeutic targets to improve the patient outcome. The amplification of the two driver genes MDM2 and CDK4, shared by WDLPD and DDLPS, has provided the rationale to explore targeting the encoded ubiquitin-protein ligase and cell cycle regulating kinase as a therapeutic approach. Investigation of the genomic landscape of WD/DDLPS and preclinical studies have revealed additional potential targets such as receptor tyrosine kinases, the cell cycle kinase Aurora A, and the nuclear exporter XPO1. While the therapeutic significance of these targets is being investigated in clinical trials, insights into the molecular characteristics associated with dedifferentiation and progression from WDLPS to DDLPS highlighted additional genetic alterations including fusion transcripts generated by chromosomal rearrangements potentially providing new druggable targets (e.g. NTRK, MAP2K6). Recent years have witnessed the increasing use of patient-derived cell and tumor xenograft models which offer valuable tools to accelerate drug repurposing and combination studies. Implementation of integrated "multi-omics" investigations applied to models recapitulating WD/DDLPS genetics, histologic differentiation and biology, will hopefully lead to a better understanding of molecular alterations driving liposarcomagenesis and DDLPS progression, as well as to the identification of new therapies tailored on tumor histology and molecular profile.

PMID:36119484 | PMC:PMC9479065 | DOI:10.3389/fonc.2022.965261