Biomed Pharmacother. 2023 Dec 15;170:116013. doi: 10.1016/j.biopha.2023.116013. Online ahead of print.

ABSTRACT

The Wnt/β-catenin pathway's significance in cancer initiation, progression, and stem cell biology underscores its therapeutic potential. However, the clinical application of Wnt inhibitors remains limited due to challenges posed by off-target effects and complex cross-talk of Wnt signaling with other pathways. In this study, we leveraged a zebrafish model to perform a robust and rapid drug screening of 773 FDA-approved compounds to identify Wnt/β-catenin inhibitors with minimal toxicity. Utilizing zebrafish expressing a Wnt reporter, we identified several drugs that suppressed Wnt signaling without compromising zebrafish development. The efficacy of the top hit, Erlotinib, extended to human cells, where it blocked Wnt/β-catenin signaling downstream of the destruction complex. Notably, Erlotinib treatment reduced self-renewal in human T-cell Acute Lymphoblastic Leukemia cells, which rely on active β-catenin signaling for maintenance of leukemia-initiating cells. Erlotinib also reduced leukemia-initiating cell frequency and delayed disease formation in zebrafish models. This study underscores zebrafish's translational potential in drug discovery and repurposing and highlights a new use for Erlotinib as a Wnt inhibitor for cancers driven by aberrant Wnt/β-catenin signaling.

PMID:38104416 | DOI:10.1016/j.biopha.2023.116013

BMC Cancer. 2023 Dec 16;23(1):1242. doi: 10.1186/s12885-023-11689-2.

ABSTRACT

BACKGROUND: Despite the diverse genetic mutations in head and neck cancer, the chemotherapy outcome for this cancer has not improved for decades. It is urgent to select prognostic factors and therapeutic targets for oropharyngeal cancer to establish precision medicine. Recent studies have identified PSMD1 as a potential prognostic marker in several cancers. We aimed to assess the prognostic significance of PSMD1 expression in oropharyngeal squamous cell carcinoma (OPSCC) patients using immunohistochemistry.

METHODS: We studied 64 individuals with OPSCC tissue from surgery at Seoul National University Bundang Hospital between April 2008 and August 2017. Immunostaining analysis was conducted on the tissue microarray (TMA) sections (4 μm) for p16 and PSMD1. H-score, which scale from 0 to 300, was calculated from each nucleus, cytoplasm, and cellular expression. Clinicopathological data were compared with Chi-squared test, Fisher's exact test, t-test, and logistic regression. Survival data until 2021 were achieved from national statistical office of Korea. Kaplan-Meier method and cox-regression model were used for disease-specific survival (DSS) analysis.

RESULTS: H-score of 90 in nucleus was appropriate cutoff value for 'High PSMD1 expression' in OPSCC. Tonsil was more frequent location in low PSMD1 group (42/52, 80.8%) than in high PSMD1 group (4/12, 33.3%; P = .002). Early-stage tumor was more frequent in in low PSMD1 group (45/52, 86.5%) than in high PSMD1 group (6/12, 50%; P = .005). HPV was more positive in low PSMD1 group (43/52, 82.7%) than in high PSMD1 group (5/12, 41.7%; P = .016). Patients with PSMD1 high expression showed poorer DSS than in patients with PSMD1 low expression (P = .006 in log rank test). In multivariate analysis, PSMD1 expression, pathologic T staging, and specimen age were found to be associated with DSS (P = .011, P = .025, P = .029, respectively).

CONCLUSIONS: In our study, we established PSMD1 as a negative prognostic factor in oropharyngeal squamous cell carcinoma, indicating its potential as a target for targeted therapy and paving the way for future in vitro studies on drug repositioning.

PMID:38104103 | DOI:10.1186/s12885-023-11689-2

Interdiscip Sci. 2023 Dec 16. doi: 10.1007/s12539-023-00593-9. Online ahead of print.

ABSTRACT

Drug repositioning is critical to drug development. Previous drug repositioning methods mainly constructed drug-disease heterogeneous networks to extract drug-disease features. However, these methods faced difficulty when we are using structurally simple models to deal with complex heterogeneous networks. Therefore, in this study, the researchers introduced a drug repositioning method named DRDSA. The method utilizes a deep sparse autoencoder and integrates drug-disease similarities. First, the researchers constructed a drug-disease feature network by incorporating information from drug chemical structure, disease semantic data, and existing known drug-disease associations. Then, we learned the low-dimensional representation of the feature network using a deep sparse autoencoder. Finally, we utilized a deep neural network to make predictions on new drug-disease associations based on the feature representation. The experimental results show that our proposed method has achieved optimal results on all four benchmark datasets, especially on the CTD dataset where AUC and AUPR reached 0.9619 and 0.9676, respectively, outperforming other baseline methods. In the case study, the researchers predicted the top ten antiviral drugs for COVID-19. Remarkably, six out of these predictions were subsequently validated by other literature sources. Schematic diagrams of data processing and DRDSA model. A Construction of drug and disease feature vectors, B The workflow of DRDSA model.

PMID:38103130 | DOI:10.1007/s12539-023-00593-9

J Chem Inf Model. 2023 Dec 16. doi: 10.1021/acs.jcim.3c01665. Online ahead of print.

ABSTRACT

Drug repositioning plays a key role in disease treatment. With the large-scale chemical data increasing, many computational methods are utilized for drug-disease association prediction. However, most of the existing models neglect the positive influence of non-Euclidean data and multisource information, and there is still a critical issue for graph neural networks regarding how to set the feature diffuse distance. To solve the problems, we proposed SiSGC, which makes full use of the biological knowledge information as initial features and learns the structure information from the constructed heterogeneous graph with the adaptive selection of the information diffuse distance. Then, the structural features are fused with the denoised similarity information and fed to the advanced classifier of CatBoost to make predictions. Three different data sets are used to confirm the robustness and generalization of SiSGC under two splitting strategies. Experiment results demonstrate that the proposed model achieves superior performance compared with the six leading methods and four variants. Our case study on breast neoplasms further indicates that SiSGC is trustworthy and robust yet simple. We also present four drugs for breast cancer treatment with high confidence and further give an explanation for demonstrating the rationality. There is no doubt that SiSGC can be used as a beneficial supplement for drug repositioning.

PMID:38103039 | DOI:10.1021/acs.jcim.3c01665

Respir Res. 2023 Dec 15;24(1):315. doi: 10.1186/s12931-023-02621-0.

ABSTRACT

BACKGROUND: The two-way communications along the gut-lung axis influence the immune function in both gut and lung. However, the shared genetic characteristics of lung function with gastrointestinal tract (GIT) diseases remain to be investigated.

METHODS: We first investigated the genetic correlations between three lung function traits and four GIT diseases. Second, we illustrated the genetic overlap by genome-wide pleiotropic analysis (PLACO) and further pinpointed the relevant tissue and cell types by partitioning heritability. Furthermore, we proposed pleiotropic genes as potential drug targets by drug database mining. Finally, we evaluated the causal relationships by epidemiologic observational study and Mendelian randomization (MR) analysis.

RESULTS: We found lung function and GIT diseases were genetically correlated. We identified 258 pleiotropic loci, which were enriched in gut- and lung-specific regions marked by H3K4me1. Among these, 16 pleiotropic genes were targets of drugs, such as tofacitinib and baricitinib targeting TYK2 for the treatment of ulcer colitis and COVID-19, respectively. We identified a missense variant in TYK2, exhibiting a shared causal effect on FEV1/FVC and inflammatory bowel disease (rs12720356, PPLACO=1.38 × 10- 8). These findings suggested TYK2 as a promising drug target. Although the epidemiologic observational study suggested the protective role of lung function in the development of GIT diseases, no causalities were found by MR analysis.

CONCLUSIONS: Our study suggested the shared genetic characteristics between lung function and GIT diseases. The pleiotropic variants could exert their effects by modulating gene expression marked by histone modifications. Finally, we highlighted the potential of pleiotropic analyses in drug repurposing.

PMID:38102678 | DOI:10.1186/s12931-023-02621-0

Int J Biol Macromol. 2023 Dec 13:128667. doi: 10.1016/j.ijbiomac.2023.128667. Online ahead of print.

ABSTRACT

Streptococcus pyogenes (Group A Streptococcus - GAS) is a human pathogen causing wide range of infections and toxin-mediated diseases in human beings of all age groups with fatality of 10-30 %. The limited success of antibiotics and the non-availability of vaccines makes GAS a global burden. The multi-subunit RNA polymerase (RNAP) is a validated bacterial therapeutic target as it is involved in transcription and can arrest growth. Of the five subunits of this enzyme complex, the β'-subunit (RpoC) has attracted specific attention as a drug target, particularly in the switch region. Here we attempt to repurpose non-antimicrobial drugs to act as RpoC inhibitors against S. pyogenes. In this study, 1826 FDA approved drugs have been identified through high-throughput virtual screening. Free Energy Perturbation (FEP) based binding free energy calculations have been performed at the final step of the virtual screening funnel to ensure high accuracy in silico results. Three compounds identified have been tested for susceptibility of S. pyogenes MTCC 442 strain and two antibiotic-resistant clinical isolates of S. pyogenes using microdilution assay. Among the three, two drugs Amlodipine Besylate (Amd) and Ranitidine hydrochloride (Rnt) have shown inhibition against all the tested strains and its mechanism of interaction with RpoC has been studied. The docked complexes were analyzed to understand the binding mode of the drugs to the target. Classical Molecular Dynamics studies for RpoC-Rnt complex and the two stable conformations of RpoC-Amd complex was carried out. Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (RoG) and Solvent Accessible Surface Area (SASA) of the complexes were plotted and studied. The thermodynamic parameters of protein-drug were experimentally determined using Isothermal Titration Calorimetry (ITC). Infrared spectroscopic studies and Fluorescence quenching studies provided insights into the secondary structural changes in RpoC on binding to the drugs.

PMID:38101681 | DOI:10.1016/j.ijbiomac.2023.128667

SLAS Discov. 2023 Dec 13:S2472-5552(23)00093-X. doi: 10.1016/j.slasd.2023.12.003. Online ahead of print.

ABSTRACT

Three-dimensional (3D) cell culture technology has been steadily studied since the 1990's due to its superior biocompatibility compared to the conventional two-dimensional (2D) cell culture technology, and has recently developed into an organoid culture technology that further improved biocompatibility. Since the 3D culture of human cell lines in artificial scaffolds was demonstrated in the early 90's, 3D cell culture technology has been actively developed owing to various needs in the areas of disease research, precision medicine, new drug development, and some of these technologies have been commercialized. In particular, 3D cell culture technology is actively being applied and utilized in drug development and cancer-related precision medicine research. Drug development is a long and expensive process that involves multiple steps-from target identification to lead discovery and optimization, preclinical studies, and clinical trials for approval for clinical use. Cancer ranks first among life-threatening diseases owing to intra-tumoral heterogeneity associated with metastasis, recurrence, and treatment resistance, ultimately contributing to treatment failure and adverse prognoses. Therefore, there is an urgent need for the development of efficient drugs using 3D cell culture techniques that can closely mimic in vivo cellular environments and customized tumor models that faithfully represent the tumor heterogeneity of individual patients. This review discusses 3D cell culture technology focusing on research trends, commercialization status, and expected effects developed until recently. We aim to summarize the great potential of 3D cell culture technology and contribute to expanding the base of this technology.

PMID:38101575 | DOI:10.1016/j.slasd.2023.12.003

Pathol Res Pract. 2023 Dec 13;253:155038. doi: 10.1016/j.prp.2023.155038. Online ahead of print.

ABSTRACT

Lung cancer is one of the leading causes of death worldwide, whereby the major contributing factors are cigarette smoking and exposure to environmental pollutants. Despite the availability of numerous treatment options, including chemotherapy, the five-year survival rate is still extremely low, highlighting the urgent need to develop novel, more effective therapeutic strategies. In this context, the repurposing of previously approved drugs is an advantage in terms of time and resources invested. Ribavirin is an antiviral drug approved for the treatment of hepatitis C, which shows potential for repurposing as an anticancer agent. Among the many signaling molecules promoting carcinogenesis, the interleukins (ILs) IL-6 and IL-8 are interesting therapeutic targets as they promote a variety of cancer hallmarks such as cell proliferation, migration, metastasis, and angiogenesis. In the present study, we show that ribavirin significantly downregulates the expression of IL-6 and IL-8 in vitro in A549 human lung adenocarcinoma cells. The results of this study shed light on the anticancer mechanisms of ribavirin, providing further proof of its potential as a repurposed drug for the treatment of lung cancer.

PMID:38101157 | DOI:10.1016/j.prp.2023.155038

Expert Opin Emerg Drugs. 2023 Dec 15. doi: 10.1080/14728214.2023.2296079. Online ahead of print.

ABSTRACT

INTRODUCTION: Despite the recent full FDA approval of lecanemab, there is currently no disease modifying therapy (DMT) that can efficiently slow down the progression of Alzheimer's disease (AD) in the general population. This statement emphasizes the need to identify novel DMTs in the shortest time possible to prevent a global epidemic of AD cases as the world population experiences an increase in lifespan.

AREAS COVERED: Here, we review several classes of anti-cancer drugs that have been or are being investigated in Phase II/III clinical trials for AD, including immunomodulatory drugs, RXR agonists, sex hormone therapies, tyrosine kinase inhibitors, and monoclonal antibodies.

EXPERT OPINION: Given the overall course of brain pathologies during the progression of AD, we express a great enthusiasm for the repositioning of anti-cancer drugs as possible AD DMTs. We anticipate an increasing number of combinatorial therapy strategies to tackle AD symptoms and their underlying pathologies. However, we strongly encourage improvements in clinical trial study designs to better assess target engagement and possible efficacy over sufficient periods of drug exposure.

PMID:38100555 | DOI:10.1080/14728214.2023.2296079

J Invest Dermatol. 2023 Dec 14:S0022-202X(23)03111-1. doi: 10.1016/j.jid.2023.10.030. Online ahead of print.

ABSTRACT

Pachyonychia congenita (PC) is a dominantly inherited genetic disorder of cornification. PC stands out among other genodermatoses because despite its rarity, it has been the focus of a very large number of pioneering translational research efforts over the past 2 decades, mostly driven by a patient support organization, the Pachyonychia Congenita Project. These efforts have laid the ground for innovative strategies that may broadly impact approaches to the management of other inherited cutaneous and noncutaneous diseases. This article outlines current avenues of research in PC, expected outcomes, and potential hurdles.

PMID:38099888 | DOI:10.1016/j.jid.2023.10.030

Mol Inform. 2023 Dec 14. doi: 10.1002/minf.202300206. Online ahead of print.

ABSTRACT

Fungal infections caused by Candida are still a public health concern. Particularly, the resistance to traditional chemotherapeutic agents is a major issue that requires efforts to develop new therapies. One of the most interesting approaches to finding new active compounds is drug repurposing aided by computational methods. In this work, two databases containing anticandidal agents and drugs were studied employing cheminformatics and compared by similarity methods. The results showed 36 drugs with high similarities to some candicidals. From these drugs, trimetozin, osalmid and metochalcone were evaluated against C. albicans (18804), C. glabrata (90030), and miconazole-resistant strain C. glabrata (32554). Osalmid and metochalcone were the best, with activity in the micromolar range. These findings represent an opportunity to continue with the research on the potential antifungal application of osalmid and metochalcone as well as the design of structurally related derivatives.

PMID:38095132 | DOI:10.1002/minf.202300206

Front Behav Neurosci. 2023 Nov 29;17:1257881. doi: 10.3389/fnbeh.2023.1257881. eCollection 2023.

ABSTRACT

Calorie restriction (CR) is considered an effective intervention for anxiety, aging, and obesity. We investigated the effects of short- and long-term CR on behavior as well as transcriptome profiles in the hypothalamus, amygdala, prefrontal cortex, pituitary, and adrenal glands of Hooded Wistar and Long Evans male rats. A reduction in anxiety-like behavior, as assessed via the elevated plus maze, was observed in both short- and long-term CR. Despite this, short- and long-term CR regulated different sets of genes, leading to distinct transcriptomic signatures. The employed models were able to simultaneously analyze categorical and numerical variables, evaluating the effect of tissue type along with expression data. In all tissues, transcription factors, zinc finger protein 45-like and zinc finger BTB domain-containing two, were the top selected genes by the models in short and long-term CR treatments, respectively. Text mining identified associations between genes of the short-term CR signature and neurodegeneration, stress, and obesity and between genes of the long-term signature and the nervous system. Literature mining-based drug repurposing showed that alongside known CR mimetics such as resveratrol and rapamycin, candidates not typically associated with CR mimetics may be repurposed based on their interaction with transcriptomic signatures of CR. This study goes some way to unravelling the global effects of CR and opens new avenues for treatment for emotional disorders, neurodegeneration, and obesity.

PMID:38094940 | PMC:PMC10716537 | DOI:10.3389/fnbeh.2023.1257881

Front Pharmacol. 2023 Nov 29;14:1333747. doi: 10.3389/fphar.2023.1333747. eCollection 2023.

NO ABSTRACT

PMID:38094888 | PMC:PMC10716446 | DOI:10.3389/fphar.2023.1333747

Biochem Biophys Res Commun. 2023 Dec 4;692:149354. doi: 10.1016/j.bbrc.2023.149354. Online ahead of print.

ABSTRACT

Aging is an intricate process characterized by the gradual deterioration of the physiological integrity of a living organism. This unfortunate phenomenon inevitably leads to a decline in functionality and a heightened susceptibility to the ultimate fate of mortality. Therefore, it is of utmost importance to implement interventions that possess the capability to reverse or preempt age-related pathology. Caloric restriction mimetics (CRMs) refer to a class of molecules that have been observed to elicit advantageous outcomes on both health and longevity in various model organisms and human subjects. Notably, these compounds offer a promising alternative to the arduous task of adhering to a caloric restriction diet and mitigate the progression of the aging process and extend the duration of life in laboratory animals and human population. A plethora of molecular signals have been linked to the practice of caloric restriction, encompassing Insulin-like Growth Factor 1 (IGF1), Mammalian Target of Rapamycin (mTOR), the Adenosine Monophosphate-Activated Protein Kinase (AMPK) pathway, and Sirtuins, with particular emphasis on SIRT1. Therefore, this review will center its focus on several compounds that act as CRMs, highlighting their molecular targets, chemical structures, and mechanisms of action. Moreover, this review serves to underscore the significant relationship between post COVID-19 syndrome, antiaging, and importance of utilizing CRMs. This particular endeavor will serve as a comprehensive guide for medicinal chemists and other esteemed researchers, enabling them to meticulously conceive and cultivate novel molecular entities with the potential to function as efficacious antiaging pharmaceutical agents.

PMID:38091837 | DOI:10.1016/j.bbrc.2023.149354

Int J Nanomedicine. 2023 Dec 6;18:7267-7285. doi: 10.2147/IJN.S438388. eCollection 2023.

ABSTRACT

PURPOSE: Rheumatoid arthritis (RA) is a highly prevalent form of autoimmune disease that affects nearly 1% of the global population by causing severe cartilage damage and inflammation. Despite its prevalence, previous efforts to prevent the perpetuation of RA have been hampered by therapeutics' cytotoxicity and poor delivery to target cells. The present study exploited drug repositioning and nanotechnology to convert metformin, a widely used antidiabetic agent, into an anti-rheumatoid arthritis drug by designing poly(lactic-co-glycolic acid) (PLGA)-based spheres. Moreover, this study also explored the thermal responsiveness of the IL-22 receptor, a key regulator of Th-17, to incorporate photothermal therapy (PTT) into the nanodrug treatment.

MATERIALS AND METHODS: PLGA nanoparticles were synthesized using the solvent evaporation method, and metformin and indocyanine green (ICG) were encapsulated in PLGA in a dropwise manner. The nanodrug's in vitro anti-inflammatory properties were examined in J744 and FLS via real-time PCR. PTT was induced by an 808 nm near-infrared (NIR) laser, and the anti-RA effects of the nanodrug with PTT were evaluated in DBA/1 collagen-induced arthritis (CIA) mice models. Further evaluation of anti-RA properties was carried out using flow cytometry, immunofluorescence analysis, and immunohistochemical analysis.

RESULTS: The encapsulation of metformin into PLGA allowed the nanodrug to enter the target cells via macropinocytosis and clathrin-mediated endocytosis. Metformin-encapsulated PLGA (PLGA-MET) demonstrated promising anti-inflammatory effects by decreasing the expression of pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α), increasing the expression of anti-inflammatory cytokines (IL-10 and IL-4), and promoting the polarization of M1 to M2 macrophages in J774 cells. The treatment of the nanodrug with PTT exhibited more potent anti-inflammatory effects than free metformin or PLGA-MET in CIA mice models.

CONCLUSION: These results demonstrated that PLGA-encapsulated metformin treatment with PTT can effectively ameliorate inflammation in a spatiotemporal manner.

PMID:38090362 | PMC:PMC10711299 | DOI:10.2147/IJN.S438388

J Biomol Struct Dyn. 2023 Dec 13:1-13. doi: 10.1080/07391102.2023.2293276. Online ahead of print.

ABSTRACT

The emergence of new Mycobacterium tuberculosis (Mtb) strains resistant to the key drugs currently used in the clinic for tuberculosis treatment can substantially reduce the probability of therapy success, causing the relevance and importance of studies on the development of novel potent antibacterial agents targeting different vulnerable spots of Mtb. In this study, 28,860 compounds from the library of bioactive molecules were screened to identify novel potential inhibitors of β-ketoacyl-acyl carrier protein synthase I (KasA), one of the key enzymes involved in the biosynthesis of mycolic acids of the Mtb cell wall. In doing so, we used a structure-based virtual screening approach to drug repurposing that included high-throughput docking of the C171Q KasA enzyme with compounds from the library of bioactive molecules including the FDA-approved drugs and investigational drug candidates, assessment of the binding affinity for the docked ligand/C171Q KasA complexes, and molecular dynamics simulations followed by binding free energy calculations. As a result, post-modeling analysis revealed 6 top-ranking compounds exhibiting a strong attachment to the malonyl binding site of the enzyme, as evidenced by the values of binding free energy which are significantly lower than those predicted for the KasA inhibitor TLM5 used in the calculations as a positive control. In light of the data obtained, the identified compounds are suggested to form a good basis for the development of new antitubercular molecules of clinical significance with activity against the KasA enzyme of Mtb.Communicated by Ramaswamy H. Sarma.

PMID:38088766 | DOI:10.1080/07391102.2023.2293276

BMC Med Genomics. 2023 Dec 12;16(1):328. doi: 10.1186/s12920-023-01745-y.

ABSTRACT

BACKGROUND: In recent years, drug screening has been one of the most significant challenges in the field of personalized medicine, particularly in cancer treatment. However, several new platforms have been introduced to address this issue, providing reliable solutions for personalized drug validation and safety testing. In this study, we developed a personalized drug combination protocol as the primary input to such platforms.

METHODS: To achieve this, we utilized data from whole-genome expression profiles of 6173 breast cancer patients, 312 healthy individuals, and 691 drugs. Our approach involved developing an individual pattern of perturbed gene expression (IPPGE) for each patient, which was used as the basis for drug selection. An algorithm was designed to extract personalized drug combinations by comparing the IPPGE and drug signatures. Additionally, we employed the concept of drug repurposing, searching for new benefits of existing drugs that may regulate the desired genes.

RESULTS: Our study revealed that drug combinations obtained from both specialized and non-specialized cancer medicines were more effective than those extracted from only specialized medicines. Furthermore, we observed that the individual pattern of perturbed gene expression (IPPGE) was unique to each patient, akin to a fingerprint.

CONCLUSIONS: The personalized drug combination protocol developed in this study offers a methodological interface between drug repurposing and combination drug therapy in cancer treatment. This protocol enables personalized drug combinations to be extracted from hundreds of drugs and thousands of drug combinations, potentially offering more effective treatment options for cancer patients.

PMID:38087279 | DOI:10.1186/s12920-023-01745-y

Cancer Cell Int. 2023 Dec 12;23(1):321. doi: 10.1186/s12935-023-03176-2.

ABSTRACT

BACKGROUND: Artificial intelligence (AI) is capable of integrating a large amount of related information to predict therapeutic relationships such as disease treatment with known drugs, gene expression, and drug-target binding. AI has gained increasing attention as a promising tool for next-generation drug development.

METHODS: An AI method was used for drug repurposing and target identification for cancer. Among 8 survived candidates after background checking, N-(1-propyl-1H-1,3-benzodiazol-2-yl)-3-(pyrrolidine-1-sulfonyl) benzamide (Z29077885) was newly selected as an new anti-cancer drug, and the anti-cancer efficacy of Z29077885 was confirmed using cell viability, western blot, cell cycle, apoptosis assay in MDA-MB 231 and A549 in vitro. Then, anti-tumor efficacy of Z29077885 was validated in an in vivo A549 xenograft in BALB/c nude mice.

RESULTS: First, we discovered an antiviral agent, Z29077885, as a new anticancer drug candidate using the AI deep learning method. Next, we demonstrated that Z29077885 inhibits Serine/threonine kinase 33 (STK33) enzymatic function in vitro and showed the anticancer efficacy in various cancer cells. Then, we found enhanced apoptosis via S-phase cell cycle arrest as the mechanism underlying the anticancer efficacy of Z29077885 in both lung and breast cancer cells. Finally, we confirmed the anti-tumor efficacy of Z29077885 in an in vivo A549 xenograft.

CONCLUSIONS: In this study, we used an AI-driven screening strategy to find a novel anticancer medication targeting STK33 that triggers cancer cell apoptosis and cell cycle arrest at the s phase. It will pave a way to efficiently discover new anticancer drugs.

PMID:38087254 | DOI:10.1186/s12935-023-03176-2

Signal Transduct Target Ther. 2023 Dec 13;8(1):451. doi: 10.1038/s41392-023-01713-z.

ABSTRACT

Amyotrophic lateral sclerosis (ALS) is a devastating fatal neurodegenerative disease with no cure. Receptor-interacting protein kinase 1 (RIPK1) has been proposed to mediate pathogenesis of ALS. Primidone has been identified as an old drug that can also inhibit RIPK1 kinase. We conducted a drug-repurposing biomarker study of primidone as a RIPK1 inhibitor using SOD1G93A mice and ALS patients. SOD1G93A mice treated with primidone showed significant delay of symptomatic onset and improved motor performance. One-hundred-sixty-two ALS participants dosed daily with primidone (62.5 mg) completed 24-week follow-up. A significant reduction was showed in serum levels of RIPK1 and IL-8, which were significantly higher in ALS patients than that of healthy controls (P < 0.0001). Serum RIPK1 levels were correlated positively with the severity of bulbar symptoms (P < 0.05). Our study suggests that serum levels of RIPK1 and IL-8 in peripheral can be used as clinical biomarkers for the activation of RIPK1 in central nervous system in human ALS patients. Repurposing primidone may provide a promising therapeutic strategy for ALS. The effect of primidone for the treatment of other inflammatory diseases may also be considered, since the activation of RIPK1 has been implicated in mediating a variety of inflammatory diseases including COVID-19-associated cytokine release syndrome (CRS). (ChiCTR2200060149).

PMID:38086800 | DOI:10.1038/s41392-023-01713-z

Nat Commun. 2023 Dec 11;14(1):8180. doi: 10.1038/s41467-023-43929-1.

ABSTRACT

Target trial emulation is the process of mimicking target randomized trials using real-world data, where effective confounding control for unbiased treatment effect estimation remains a main challenge. Although various approaches have been proposed for this challenge, a systematic evaluation is still lacking. Here we emulated trials for thousands of medications from two large-scale real-world data warehouses, covering over 10 years of clinical records for over 170 million patients, aiming to identify new indications of approved drugs for Alzheimer's disease. We assessed different propensity score models under the inverse probability of treatment weighting framework and suggested a model selection strategy for improved baseline covariate balancing. We also found that the deep learning-based propensity score model did not necessarily outperform logistic regression-based methods in covariate balancing. Finally, we highlighted five top-ranked drugs (pantoprazole, gabapentin, atorvastatin, fluticasone, and omeprazole) originally intended for other indications with potential benefits for Alzheimer's patients.

PMID:38081829 | DOI:10.1038/s41467-023-43929-1