Cancer Res Treat. 2025 Apr 15. doi: 10.4143/crt.2025.033. Online ahead of print.

ABSTRACT

PURPOSE: Triple-negative breast cancer (TNBC) is a particularly aggressive subtype of breast cancer, with approximately 30% of patients eventually developing brain metastases (BM), which result in poor outcomes. An understanding of the tumor microenvironment (TME) at both primary and metastatic sites offers insights into the mechanisms underlying BM and potential therapeutic targets.

MATERIALS AND METHOD: Spatial RNA sequencing (spRNA-seq) was performed on primary TNBC and paired BM tissues from three patients, one of whom had previously received immune checkpoint inhibitors before BM diagnosis. Specimen regions were categorized into tumor, proximal, and distal TME based on their spatial locations. Gene expression differences across these zones were analyzed, and immune cell infiltration was estimated using TIMER. A gene module analysis was conducted to identify key gene clusters associated with BM.

RESULTS: Distinct gene expression profiles were noted in the proximal and distal TMEs. In BM, the proximal TME exhibited neuronal gene expression, suggesting neuron-tumor interactions compared to tumor, and upregulation of epithelial genes compared to the distal TME. Immune cell analysis revealed dynamic changes in CD8+ T cells and macrophages across the tumor and TME zones. Gene module analysis identified five key modules, including one related to glycolysis, which correlated with patient survival. Drug repurposing analysis identified potential therapeutic targets, including VEGFA, RAC1, EGLN3, and CAMK1D.

CONCLUSION: This study provides novel insights into the transcriptional landscapes in TNBC BM using spRNA-seq, emphasizing the role of neuron-tumor interactions and immune dynamics. These findings suggest new therapeutic strategies and underscore the importance of further research.

PMID:40241579 | DOI:10.4143/crt.2025.033

BMC Biol. 2025 Apr 16;23(1):101. doi: 10.1186/s12915-025-02206-x.

ABSTRACT

BACKGROUND: Drug-disease association (DDA) prediction aims to identify potential links between drugs and diseases, facilitating the discovery of new therapeutic potentials and reducing the cost and time associated with traditional drug development. However, existing DDA prediction methods often overlook the global relational information provided by other biological entities, and the complex association structure between drug diseases, limiting the potential correlations of drug and disease embeddings.

RESULTS: In this study, we propose HNF-DDA, a subgraph contrastive-driven transformer-style heterogeneous network embedding model for DDA prediction. Specifically, HNF-DDA adopts all-pairs message passing strategy to capture the global structure of the network, fully integrating multi-omics information. HNF-DDA also proposes the concept of subgraph contrastive learning to capture the local structure of drug-disease subgraphs, learning the high-order semantic information of nodes. Experimental results on two benchmark datasets demonstrate that HNF-DDA outperforms several state-of-the-art methods. Additionally, it shows superior performance across different dataset splitting schemes, indicating HNF-DDA's capability to generalize to novel drug and disease categories. Case studies for breast cancer and prostate cancer reveal that 9 out of the top 10 predicted candidate drugs for breast cancer and 8 out of the top 10 for prostate cancer have documented therapeutic effects.

CONCLUSIONS: HNF-DDA incorporates all-pairs message passing and subgraph capture strategies into heterogeneous network embedding, enabling effective learning of drug and disease representations enriched with heterogeneous information, while also demonstrating significant potential for applications in drug repositioning.

PMID:40241152 | DOI:10.1186/s12915-025-02206-x

J Transl Med. 2025 Apr 16;23(1):448. doi: 10.1186/s12967-025-06431-4.

ABSTRACT

BACKGROUND: Oral Lichen Planus (OLP) is a chronic inflammatory disorder that may progress to Oral Squamous Cell Carcinoma (OSCC). Lipid metabolism dysregulation has been implicated in tumor development and immune response modulation. This study aims to explore the role of lipid metabolism, particularly the lipids diacylglycerol (DAG), triacylglycerol (TAG), and phosphatidylcholine (PC), in the progression from OLP to OSCC, and to identify potential therapeutic targets for prevention and treatment.

METHODS: We performed a Mendelian randomization (MR) analysis to investigate the causal relationships between lipid metabolism and the risk of OLP and OSCC. Differential gene expression analysis was conducted to identify key genes related to lipid metabolism. The interactions of lipid species and key genes were examined using drug databases (DrugBank, DGIdb, and TCMSP) to explore potential drug candidates. Enrichment analysis of signaling pathways, including PPAR signaling, was also conducted to understand the underlying mechanisms.

RESULTS: Our MR analysis revealed that DAG exerts a protective effect in OLP (OR < 1), but its role shifts to a risk factor in OSCC (OR > 1), potentially by altering the tumor immune microenvironment. TAG and PI dysregulation also plays a critical role in tumorigenesis. Gene expression analysis identified several key lipid metabolism-related genes, including SLC27A6, FABP3, FABP4, ADIPOQ, and PLIN1, whose expression differed between OLP and OSCC, highlighting their importance in tumor progression. These genes were enriched in the PPAR signaling pathway, suggesting its involvement in tumor growth and immune modulation. Potential drug candidates, such as palm acid (PA), Imatinib, and Curcumin, were identified through drug-repurposing strategies.

CONCLUSION: Lipid metabolism dysregulation plays a crucial role in the progression of OLP to OSCC. Targeting key lipid metabolism pathways and genes, such as DAG, TAG, PI, and the PPAR pathway, may offer promising strategies for early diagnosis and therapeutic intervention. This study provides novel insights into the molecular mechanisms of OLP-to-OSCC progression and suggests potential drug candidates, including natural compounds, for future clinical applications. Further research is needed to validate these findings in clinical settings.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40241125 | DOI:10.1186/s12967-025-06431-4

NPJ Parkinsons Dis. 2025 Apr 16;11(1):77. doi: 10.1038/s41531-025-00933-0.

ABSTRACT

Many drug targets in ongoing Parkinson's disease (PD) clinical trials have strong genetic links. While genome-wide association studies (GWAS) nominate regions associated with disease, pinpointing causal genes is challenging. Our aim was to prioritize additional druggable genes underlying PD GWAS signals. The polygenic priority score (PoPS) integrates genome-wide information from MAGMA gene-level associations and over 57,000 gene-level features. We applied PoPS to East Asian and European PD GWAS data and prioritized genes based on PoPS, distance to the GWAS signal, and non-synonymous credible set variants. We prioritized 46 genes, including well-established PD genes (SNCA, LRRK2, GBA1, TMEM175, VPS13C), genes with strong literature evidence supporting a mechanistic link to PD (RIT2, BAG3, SCARB2, FYN, DYRK1A, NOD2, CTSB, SV2C, ITPKB), and genes relatively unexplored in PD. Many hold potential for drug repurposing or development. We prioritized high-confidence genes with strong links to PD pathogenesis that may represent our next-best candidates for developing disease-modifying therapeutics.

PMID:40240380 | DOI:10.1038/s41531-025-00933-0

Annu Rev Biomed Data Sci. 2025 Apr 16. doi: 10.1146/annurev-biodatasci-101424-120950. Online ahead of print.

ABSTRACT

Drug target identification is the first step in drug development, and its importance is underscored by the fact that, even when using genetic evidence to improve success rates, only a small fraction of lead targets end up approved for use in the clinic. One of the reasons for this is the lack of in-depth understanding of the complexity of human diseases.In this review we argue that network-based approaches, which are able to capture relationships between relevant genes and proteins, and diverse data modalities have high potential for improving drug target identification and drug repurposing. We present the evolution of network-based methods that have been developed for this purpose and discuss the limitations of these approaches that are holding them back from making an impact in the clinic. We finish by presenting our recommendations for overcoming these limitations, for example, by leveraging emerging technologies such as artificial intelligence and knowledge graphs.

PMID:40239307 | DOI:10.1146/annurev-biodatasci-101424-120950

J Neurooncol. 2025 Apr 16. doi: 10.1007/s11060-025-05004-1. Online ahead of print.

ABSTRACT

PURPOSE: This retrospective study aims to show a real-life single-center experience with clinical management of relapsed pediatric ependymomas using results from comprehensive molecular profiling.

METHODS: Eight relapsed ependymomas were tested by whole exome sequencing, RNA sequencing, phosphoproteomic arrays, array comparative genome hybridization, and immunohistochemistry staining for PD-L1 expression and treated with an individualized approach implementing targeted inhibitors, immunotherapy, antiangiogenic metronomic treatment, or other agents. Treatment efficacy was evaluated using progression-free survival (PFS), overall survival (OS), survival after relapse (SAR), and PFS ratios.

RESULTS: Genomic analyses did not reveal any therapeutically actionable alterations. Surgery remained the cornerstone of patient treatment, supplemented by adjuvant radiotherapy. Empiric agents were chosen quite frequently, often involving drug repurposing. In six patients, prolonged PFS after relapse was seen because of immunotherapy, MEMMAT, or empiric agents and is reflected in the PFS ratio ≥ 1. The 5-year OS was 88%, the 10-year OS was 73%, the 2-year SAR was 88%, and the 5-year SAR was 66%.

CONCLUSION: We demonstrated the feasibility and good safety profile. Promising was the effect of immunotherapy on ZFTA-positive ependymomas. However, further research is required to establish the most effective approach for achieving sustained remission in these patients.

PMID:40238025 | DOI:10.1007/s11060-025-05004-1

Clin Transl Sci. 2025 Apr;18(4):e70214. doi: 10.1111/cts.70214.

ABSTRACT

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease. Its progressively expanding, fluid-filled renal cysts eventually lead to end-stage renal disease. Despite the relatively high prevalence, treatment options are currently limited to a single drug approved by the FDA and EMA. Here, we investigated human ADPKD patient-derived three-dimensional cyst cultures (3DCC) as an in vitro model for ADPKD and drug repurposing research. First, we analyzed the proteomes of 3DCC derived from healthy and diseased tissues. We then compared the protein expression profiles with those of reference tissues, mainly from the same patients. We quantified 290 proteins affecting drug disposition and proposed target proteins for drug treatment. Lastly, we investigated the functional response of the quantified target proteins after exposure to repurposing candidates in the 3DCC. Proteomic profiling of human 3DCC reflected previously reported pathophysiological alterations, including aberrant protein expression in inflammation and metabolic reprogramming. While the 3DCCs largely recapitulated the disease phenotype in vitro, drug transporter expression was reduced compared to in vivo conditions. Target proteins for proposed repurposing candidates showed similar expression in vitro and in tissues. Exposure to these repurposing candidates inhibited cyst swelling in vitro, supporting the suitability of the 3DCC for ADPKD drug screening. In summary, our results provide new insights into the ADPKD proteome and offer a starting point for further research to improve treatment options for affected individuals.

PMID:40235151 | DOI:10.1111/cts.70214

Sci Rep. 2025 Apr 15;15(1):12955. doi: 10.1038/s41598-025-97653-5.

ABSTRACT

Ionizing radiation induces DNA damage and impairs genomic integrity, leading to cell death and tissue injuries or carcinogenesis. Medical radiation protectors are essential and necessary. However, there are limited radioprotectors in clinics, which can't meet the growing demand for countering radiation emergencies. Traditional drug discovery approach has been proven expensive and risky. Computational drug repositioning provides an attractive strategy for radioprotector discovery. Here we constructed a systematic workflow to identify repositioning radioprotectors by comparison of biosimilarity between γ-ray and known medicines characterized by gene expression signatures from GEO and LINCS. Using enrichment scoring, medicines with negative scores were considered as candidates of revising or mitigating radiation injuries. Seven approved medicines were identified, and their targets enriched in steroid and estrogen metabolic, chemical carcinogenesis associated pathways. Lenalidomide, an approved medicine for multiple myeloma and anemia, was further verified as a promising potential radioprotector. It increases survival of mice after lethal doses of irradiation by alleviating bone marrow and intestinal injury in vivo, and inhibits apoptosis of cultured irradiated AHH- 1 and IEC- 6 cells in vitro. This study introduces rational drug repositioning to radiation medicine and provides viable candidates for radioprotective therapeutic regimens.

PMID:40234645 | DOI:10.1038/s41598-025-97653-5

Acta Pharmacol Sin. 2025 Apr 15. doi: 10.1038/s41401-025-01539-1. Online ahead of print.

ABSTRACT

Hyperlipidemia, a major risk factor for cardiovascular diseases, is associated with limitations in clinical lipid-lowering medications. Drug repurposing strategies expedite the research process and mitigate development costs, offering an innovative approach to drug discovery. This study employed systematic literature and guidelines review to compile a training set comprising 176 lipid-lowering drugs and 3254 non-lipid-lowering drugs. Multiple machine learning models were developed to predict the lipid-lowering potential of drugs. A multi-tiered validation strategy was implemented, encompassing large-scale retrospective clinical data analysis, standardized animal studies, molecular docking simulations and dynamics analyses. Through a comprehensive screening analysis utilizing machine learning, 29 FDA-approved drugs with lipid-lowering potential were identified. Clinical data analysis confirmed that four candidate drugs, with Argatroban as the representative, demonstrated lipid-lowering effects. In animal experiments, the candidate drugs significantly improved multiple blood lipid parameters. Molecular docking and dynamics simulations elucidated the binding patterns and stability of candidate drugs in interaction with related targets. We successfully identified multiple non-lipid-lowering drugs with lipid-lowering potential by integrating state-of-the-art machine learning techniques with multi-level validation methods, thereby providing new insights into lipid-lowering drugs, establishing a paradigm for AI-based drug repositioning research, and expanding the repertoire of lipid-lowering medications available to clinicians.

PMID:40234619 | DOI:10.1038/s41401-025-01539-1

Biomed Pharmacother. 2025 Apr 14;186:118047. doi: 10.1016/j.biopha.2025.118047. Online ahead of print.

ABSTRACT

In this study, we utilized the yeast two-hybrid system to screen for proteins interacting with USP24. Out of 250 such proteins, functional enrichment analysis using MetaCore™ indicated that 33 of them were involved in lung cancer progression. We then investigated gene expression and survival rates of these 33 proteins in lung cancer patients and cell lines through TCGA databases, Kaplan-Meier Plotter databases, and RNA-seq profile from A549/A549-T24 cells. By employing the patients' survival rate and gene expression profile of these 33 USP24-interacting proteins as gene signatures, we identified 10 potential drugs for inhibiting lung cancer progression or drug resistance via drug repurposing strategy using the Connectivity Map (CMap) database. Of these 10 drugs, six showed similar indicators in Clinical Trials, while the other four candidates (15-delta prostaglandin J2, Astemizole, Trifluoperazine, and 1,4-chrysenequinone) were chosen to evaluate their effect on re-sensitizing cytotoxicity of Taxol and Gefitinib in drug-resistant cancer cells. Experiments demonstrated that treatment with USP24-i-101 and Astemizole alone significantly inhibited drug resistance and re-sensitized the cytotoxicity of Taxol and Gefitinib in drug-resistant lung cancer cells. Notably, combination therapy with USP24-i-101and Astemizole re-sensitized the cytotoxicity of Taxol and Gefitinib in drug-resistant lung cancer, which could benefit in inhibiting drug resistance during cancer therapy.

PMID:40233501 | DOI:10.1016/j.biopha.2025.118047

Cent Nerv Syst Agents Med Chem. 2025 Apr 11. doi: 10.2174/0118715249350698250317041551. Online ahead of print.

ABSTRACT

BACKGROUND: The search for effective treatments for neurodegenerative diseases, particularly Alzheimer's disease, has been fraught with challenges. Alzheimer's disease accounts for 60-80% of dementia cases globally, affecting approximately about 50 million people. Currently, drug repurposing has emerged as a promising strategy in new drug development, attracting significant attention from regulatory agencies, such as the US FDA.

AIM: This study aimed to investigate the potential therapeutic role of dolutegravir in Alzheimer's disease (AD) treatment using a novel network pharmacology approach. Specifically, it explored the interaction of dolutegravir with key molecular targets involved in AD pathology, predicted its effects on relevant biological pathways, and evaluated its viability as a new therapeutic candidate.

OBJECTIVE: This study employed a network pharmacology framework to evaluate dolutegravir, an antiretroviral drug, as a potential treatment for Alzheimer's disease, shedding light on its possible therapeutic mechanisms.

METHOD: A network pharmacology approach was used to predict the drug targets of dolutegravir. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to identify interacting pathways. Additionally, protein- protein interaction (PPI) network analysis was conducted to assess key interactions and molecular docking studies were performed to evaluate the binding affinity of dolutegravir to the predicted targets.

RESULT: PPI network analysis revealed that dolutegravir interacted with several key targets, including BRAF, mTOR, MAPK1, MAPK3, NOS1, BACE1, CAPN1, CASP3, CASP7, CASP8, CHUK, IKBKB, PIK3CA, and PIK3CD. KEGG pathway analysis suggested that dolutegravir could influence amyloid-beta formation, amyloid precursor protein metabolism, and the cellular response to amyloid-beta. Molecular docking results showed the highest binding affinity of dolutegravir for PI3KCD (-8.5 kcal/mol) and MTOR (-8.7 kcal/mol).

CONCLUSION: The findings indicated that dolutegravir holds significant potential in modulating key pathways involved in Alzheimer's disease pathogenesis. These results provide a strong foundation for further investigations into the therapeutic efficacy and safety of dolutegravir in the treatment of Alzheimer's disease. The use of drug repurposing strategies, leveraging Dolutegravir's established pharmacological profile, offers a promising route for accelerated therapeutic development in AD.

PMID:40231534 | DOI:10.2174/0118715249350698250317041551

ACS Appl Bio Mater. 2025 Apr 14. doi: 10.1021/acsabm.5c00362. Online ahead of print.

ABSTRACT

Fruit spoilage caused by oxidation and microbial infection exacerbates resource wastage. Although starch films including chitosan possessed admirable biocompatibility owing to great biodegradability compared with conventional plastics, deficient antibacterial and antioxidant capacity restricted food shelf life. Herein, an environmentally friendly antibacterial film (CS/G-CDs) was constructed by carbon dots derived from Cirsii Herba (CDs), which was formed through high affinity resulting from hydrogen bonding between chitosan molecules and hydroxyl originating from CDs. The prepared CDs presented homogeneous and monodisperse spherical structures with an ultrasmall size, providing favorable conditions for uniform film formation. Encouragingly, the antioxidant capacity of CS/G-CDs increased 5.00-fold, followed by an antibacterial rate of up to 97.0%. Dramatically, CS/G-CDs revealed glorious UV shielding efficacy (99.9% for UVB and 98.2% for UVA), and its preservation time for blueberries was remarkably extended 8 days longer than that of the chitosan film. Overall, Chinese herb-derived antibacterial films exhibited magnified antibacterial/antioxidant properties and great biocompatibility, which provided a promising strategy for sustainable development of packaging materials.

PMID:40227972 | DOI:10.1021/acsabm.5c00362

Cancers (Basel). 2025 Mar 28;17(7):1144. doi: 10.3390/cancers17071144.

ABSTRACT

According to the European Federation of Pharmaceutical Industries and Association (EFPIA), a drug takes about 12-13 years from the first synthesis of a new active substance for the medicinal product to reach the market [...].

PMID:40227656 | DOI:10.3390/cancers17071144

Front Pharmacol. 2025 Mar 28;16:1564911. doi: 10.3389/fphar.2025.1564911. eCollection 2025.

ABSTRACT

Cancer is a leading cause of mortality worldwide, with most conventional treatments lacking efficacy and having significant challenges like drug resistance. Finding new molecules is quite challenging in terms of cost, time and setbacks. Hence, drug repurposing is considered sensible for skipping the long process of drug development. Dibenzazepine carboxamides, as traditional anticonvulsants, primarily function by blocking voltage-gated sodium channels, which not only mitigate seizures but also influence mood disorders through modulation of serotonin and dopamine. Recent studies have uncovered their anticancer properties, demonstrated by both in vitro and in vivo experiments. This review comprehensively examines dibenzazepine's pharmacodynamics, pharmacokinetics, and clinical applications, focusing on their emerging role in oncology. By highlighting the anticancer mechanisms of action-including apoptosis induction, inhibition of HDAC, Wnt/β-Catenin signaling, and Voltage-gated sodium channels, we suggest further research to fully elucidate their therapeutic potential and application in cancer treatment.

PMID:40223925 | PMC:PMC11985771 | DOI:10.3389/fphar.2025.1564911

Proteomics. 2025 Apr 14:e202400241. doi: 10.1002/pmic.202400241. Online ahead of print.

ABSTRACT

Spaceflight poses unique challenges to human health due to exposure to increased levels of cosmic radiation, microgravity, and associated oxidative stress. These environmental factors can lead to cellular damage, inflammation, and a range of health complications, including cardiovascular problems, immune system impairment, and an increased risk of cancer. Nuclear factor erythroid 2-related factor 2 (NRF2) is a critical transcription factor that regulates the body's defense mechanisms against oxidative stress by promoting the expression of antioxidant enzymes. Recent research has shed more light on the critical role of NRF2 in addressing space-related health challenges. In this study, we developed a computational methodology to explore the plasticity of the gene expression profile in flight and postflight conditions, highlighting the genes and corresponding mechanisms that do not return to ground levels and correlate with gene signatures associated with cardiovascular disease (CVD). RNA sequencing (RNA-seq) data from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been used to investigate the cellular effects of microgravity on cardiac function. Gene expression monotonicity studies were performed and linked to genome-wide association studies (GWAS) to highlight the monotonically expressed genes associated with CVD. The selected monotonically expressed genes were also mapped onto the NRF2 network to investigate the impact of spaceflight on human cardiomyocyte function in the context of redox signaling pathways. Based on this knowledge, we used computational drug repurposing methods to suggest a short list of repurposed drug candidates that can be further tested in astronauts for the prevention of CVD. This study provides insights into the molecular and redox signaling alterations in cardiomyocytes induced by spaceflight, laying the foundation for future research aimed at mitigating cardiovascular risks in astronauts and advancing clinical applications on Earth.

PMID:40223711 | DOI:10.1002/pmic.202400241

Expert Opin Drug Discov. 2025 Apr 14:1-10. doi: 10.1080/17460441.2025.2490251. Online ahead of print.

ABSTRACT

INTRODUCTION: The journey from initial drug discovery to approval for respiratory diseases typically spans approximately 10.4 years and cost over $2.8 billion. This intricate process involves five stages: target identification, therapeutic molecule discovery, preclinical testing, clinical trials, and regulatory approval.

AREAS COVERED: This review examines novel drug discovery strategies for chronic obstructive pulmonary disease (COPD), focusing on advanced in vitro models that replicate human lung conditions for accurate drug testing according to the following search string: discovery AND strategy AND COPD. It explores targeted molecular therapies, structure-based drug design, and drug repurposing approaches facilitated by computational analysis. The significance of personalized medicine in tailoring treatments for diverse COPDs is emphasized, highlighting the complexity of the disease and the necessity of these innovative methodologies to improve therapeutic outcomes.

EXPERT OPINION: COPD remains a challenging area, with a significant unmet medical need. Despite previous efforts, few effective therapies exist. Innovative in vitro models, targeted molecular therapies, and drug repurposing strategies are showing promise. Emphasizing advanced preclinical models and repurposing existing drugs could transform treatment paradigms, promoting more effective therapies for complex diseases like COPD. These innovations hold potential for enhancing drug discovery efficiency, leading to personalized and precision medicine approaches.

PMID:40223433 | DOI:10.1080/17460441.2025.2490251

Clin Exp Med. 2025 Apr 13;25(1):117. doi: 10.1007/s10238-025-01631-0.

ABSTRACT

Glioblastoma (GBM) is an aggressive Grade IV brain tumor with a poor prognosis. It results from genetic mutations, epigenetic changes, and factors within the tumor microenvironment (TME). Traditional treatments like surgery, radiotherapy, and chemotherapy provide limited survival benefits due to the tumor's heterogeneity and resistance mechanisms. This review examines novel approaches for treating GBM, focusing on repurposing existing medications such as antipsychotics, antidepressants, and statins for their potential anti-GBM effects. Advances in molecular profiling, including next-generation sequencing, artificial intelligence (AI), and nanotechnology-based drug delivery, are transforming GBM diagnosis and treatment. The TME, particularly GBM stem cells and immune evasion, plays a key role in therapeutic resistance. Integrating multi-omics data and applying precision medicine show promise, especially in combination therapies and immunotherapies, to enhance clinical outcomes. Addressing challenges such as drug resistance, targeting GBM stem cells, and crossing the blood-brain barrier is essential for improving treatment efficacy. While current treatments offer limited benefits, emerging strategies such as immunotherapies, precision medicine, and drug repurposing show significant potential. Technologies like liquid biopsies, AI-powered diagnostics, and nanotechnology could help overcome obstacles like the blood-brain barrier and GBM stem cells. Ongoing research into combination therapies, targeted drug delivery, and personalized treatments is crucial. Collaborative efforts and robust clinical trials are necessary to translate these innovations into effective therapies, offering hope for improved survival and quality of life for GBM patients.

PMID:40223032 | DOI:10.1007/s10238-025-01631-0

Reprod Biol. 2025 Apr 12;25(2):101017. doi: 10.1016/j.repbio.2025.101017. Online ahead of print.

ABSTRACT

PCOS is an endocrine disorder that affects women of reproductive age. The root of PCOS is ovarian dysfunction, which presents as hormonal disturbances affecting normal ovarian function to cause the symptoms and complications of the disease. This dysfunction causes symptoms like impaired maturation of follicles and disorders of various origins with multiple treatment regimens that are not always clear. Therefore, the present review mainly concentrates on the genetic level of ovarian dysfunction of PCOS. The articles were identified through a vigorous literature search where search engines such as PubMed, Google Scholar, databases, and Science Direct were used, and the articles published from 2015 to 2025 were referred. We identified that the key genes involved in the ovarian dysfunctions in PCOS include CYP11A1, CYP17A1, CYP19A1, AR, FSHR, LHCGR, AMH, INSR, SHBG, IRS1, GATA4, ADIPOQ, YAP1, TCF7L2, and DENND1A, which play a role in gonadotropin action, steroidogenesis, and folliculogenesis. Furthermore, epigenetic factors and miRNAs miR-93, 222, 155, 146a, 132, 320, 27a, 483, 21, 378, 17-92 Cluster, and 375, 221 are also involved in it. Abnormal expression of these genes is known to play a critical role in the etiology and pathogenesis of PCOS. Present treatment includes the use of oral contraceptives, anti-androgen agents, insulin-sensitizing agents, and ovulation-inducing agents, and future treatment may consist of miRNA therapy, drug repositioning, and genetic markers that might be used for early identification and better management of ovarian dysfunction. Thus, the current review discusses ovarian dysfunction in PCOS, the involvement of potential genes and epigenetic factors, and miRNAs concerning ovulation and its therapeutic implications.

PMID:40222066 | DOI:10.1016/j.repbio.2025.101017

Sci Rep. 2025 Apr 12;15(1):12698. doi: 10.1038/s41598-025-96284-0.

ABSTRACT

The dengue virus, a member of the arbovirus family, can cause a variety of clinical symptoms. However, there are currently no Food and Drug Administration-approved drugs are currently available for its treatment. We have used RNA-dependent RNA polymerase to identify drug candidates against dengue virus 2 or dengue virus 3. The Smina molecular docking program was used to screen natural compounds and FDA-approved drugs. This study used the pkCSM web server for pharmacokinetic profiling, OSIRIS Data Warrior for physicochemical property assessment, Data Warrior software for cytotoxicity profiling, and molecular dynamics simulations to evaluate the stability of ligand-RdRp interactions. Specifically, the drugs and compounds with the highest negative binding energy and most hydrogen bonds are chlorthalidone, valdecoxib, and ZINC14824819, which interact with the RdRp domain of dengue virus 2, and empagliflozin, netarsudil, and ZINC13375652, which interact with the RdRp domain of dengue virus 3. We propose several FDA-approved drugs and natural compounds that can bind to the RdRp of dengue virus serotypes 2 and 3 and prevent the virus from infecting cells. These compounds show a high level of safety and strong skin and intestinal absorption. Further in vitro and in vivo testing is needed to verify these predictions and assess therapeutic potential.

PMID:40221558 | DOI:10.1038/s41598-025-96284-0

Rev Neurol (Paris). 2025 Apr 10:S0035-3787(25)00495-3. doi: 10.1016/j.neurol.2025.04.003. Online ahead of print.

ABSTRACT

In recent years, the increasing availability of antiseizure medications has not reduced the incidence of drug-resistant epilepsy. Precision medicine offers the potential for mechanism-driven treatments for rare pediatric epilepsies. The concept of precision medicine is not new in the field of epilepsy, as demonstrated by the use of pyridoxine for antiquitin deficiency (pyridoxine-dependent epilepsy) and the ketogenic diet for GLUT1 deficiency syndrome. More recently, preclinical evidence has led to phase 3 clinical trials, such as the use of everolimus to inhibit the mTOR pathway in tuberous sclerosis complex. However, preclinical findings do not always translate into effective treatments, as illustrated by the heterogeneous effects of quinidine in KCNT1-related epilepsy. Currently, an exponential increase in compounds identified at the preclinical level will require clinical trial validation. However, it remains uncertain whether these developments will lead to improved efficacy in drug-resistant epilepsy or have any disease-modifying effects. This article does not explicitly address antisense oligonucleotides or gene therapy.

PMID:40221358 | DOI:10.1016/j.neurol.2025.04.003