Frontiers in Pharmacology最新文献

{"title":"Assessment of drug permeability using a small airway microphysiological system.","authors":"Robert M Geiger, Shekh M Rahman, Md Shadiqur Rashid Roni, Catherine Sullenberger, Sabyasachy Mistry, Katherine Shea, Isra Tariq, Omnia A Ismaiel, Murali K Matta, Paula L Hyland, Sasha Berdichevski, Alexandre J S Ribeiro, Ksenia Blinova, Wenlei Jiang, Ross L Walenga, Bryan Newman, Donna A Volpe, Kevin A Ford","doi":"10.3389/fphar.2025.1621775","DOIUrl":"https://doi.org/10.3389/fphar.2025.1621775","url":null,"abstract":"<p><strong>Background: </strong>There is a need to reliably predict the permeability of inhaled compounds during the development of new and generic drugs. A small airway microphysiological system (MPS) that can recapitulate the pulmonary air-liquid interface (ALI) with primary epithelial and vascular endothelial cell layers may provide a more physiologically relevant environment for measuring drug permeability than simpler two-dimensional <i>in vitro</i> cell culture platforms. Therefore, we evaluated the use of a small airway MPS to measure the permeability of inhaled drugs.</p><p><strong>Methodology: </strong>Primary human lung epithelial cells were seeded onto the top channel of the chip and cultured for 14 days at ALI to promote monolayer differentiation, followed by addition of endothelial cells into the bottom channel. Due to the non-specific binding properties of polydimethylsiloxane (PDMS), a drug absorption study was conducted to quantify non-specific binding to the material. Drug permeability was evaluated by passing each compound (10 µM) through the top channel and measuring the amount of drug that permeated into the bottom channel over the time course of 30, 60, 120, and 180 min.</p><p><strong>Results: </strong>Confocal micrographs demonstrated the presence of tight junctions along with basal, goblet, and ciliated cells in the top channel and attachment of endothelial cells in the bottom channel. Insignificant nonspecific binding to the MPS was observed with albuterol sulfate, formoterol fumarate, and olodaterol hydrochloride (HCl), while fluticasone furoate showed significant nonspecific binding as only 6%-44% of the drug was recovered at 30 and 120 min, respectively. As a result, fluticasone furoate was excluded from further analysis. Permeability studies estimated an apparent permeability (P_app) of 1.02 × 10^-6 cm/s for albuterol sulfate, 0.0813 × 10^-6 cm/s for olodaterol HCl, and 2.44 × 10^-6 cm/s for formoterol fumarate.</p><p><strong>Discussion: </strong>Taken together, the small airway MPS recapitulated relevant cell types and many morphological features in the lung. The apparent permeabilities measured indicated that albuterol sulfate and formoterol fumarate would be categorized as highly permeable, while olodaterol HCl would be categorized as a low permeable drug.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1621775"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12312011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Acute kidney injury: from pathology to phytotherapy.","authors":"Ya-Long Feng, Wan-Ying Ma, Yin-Xuan Jiang, Le Shui, Hua Chen, Xue-Zhong Gong","doi":"10.3389/fphar.2025.1649837","DOIUrl":"https://doi.org/10.3389/fphar.2025.1649837","url":null,"abstract":"","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1649837"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12311308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The anticancer activity and mechanisms of She medicine herbs.","authors":"Yunxuan Miao, Yisheng Chen, Qiaofen Lan, Ruogu Chen, Jiajia Zhuang, Haojun Shi, Miao Wang, Jianhui Miao, Chengshou Lin","doi":"10.3389/fphar.2025.1610301","DOIUrl":"https://doi.org/10.3389/fphar.2025.1610301","url":null,"abstract":"<p><p>She Medicine, a traditional therapeutic system from China's She ethnic group, shows promise in cancer treatment. This paper provides a comprehensive review of She medicinal herbs, focusing on their anticancer activities and underlying mechanisms. Compared to widely studied traditional medicines (e.g., Traditional Chinese Medicine), She Medicine exhibits unique ethnopharmacological traits, such as localized plant usage and multi-target mechanisms involving apoptosis induction, immune modulation, and tumor microenvironment regulation. Key herbs like <i>Pimpinella diversifolia</i> and <i>Melastoma dodecandrum</i> showing significant anticancer potential due to their bioactive compounds such as flavonoids, quercetin, and gallic acid. For example, homoharringtonine (HT), a She-derived alkaloid, targets Smad3/TGF-β pathways in non-small cell lung cancer and synergizes with chemotherapy in leukemia treatment, as evidenced by preliminary clinical trials. However, challenges persist, including resource shortages, insufficient mechanistic studies, and a lack of quality control standards. Future research should integrate multi-omics and bioengineering approaches to standardize She Medicine and bridge its traditional use with modern therapies such as immune checkpoint inhibitors. Overall, She medicinal herbs hold great promise for cancer treatment and warrant further exploration to unlock their full potential in modern medicine.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1610301"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310602/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The efficacy and safety of cabazitaxel in the treatment of metastatic castration-resistant prostate cancer: a systematic review and network meta-analysis based on randomized controlled trials.","authors":"Cong Shao, Quan Wan, Jia Guo, Zhuo Chen","doi":"10.3389/fphar.2025.1586650","DOIUrl":"https://doi.org/10.3389/fphar.2025.1586650","url":null,"abstract":"<p><strong>Background: </strong>Cabazitaxel (CAB) has been approved for the treatment of patients with progressed metastatic castration-resistant prostate cancer (mCRPC) after receiving docetaxel. To assess the efficacy and safety of CAB in mCRPC patients through systematic review and network meta-analysis.</p><p><strong>Methods: </strong>Randomized controlled studies on the treatment of mCRPC with CAB in PUBMED, EMBASE, Cochrane, and Web of Science were searched. Relevant studies that met pre-set criteria were determined, and the quality of included studies was evaluated using the National Institutes of Health-Quality Assessment Tool. After the data was extracted, data analysis was conducted in R 4.3.2. Overall survival (OS), progression-free survival (PFS), and serious adverse events (SAEs) were used as the primary outcomes, and HR (hazard ratio) or RR (risk ratio) and their 95% confidence intervals (95% CrI) were calculated as effect sizes.</p><p><strong>Results: </strong>A total of 13 studies were included, involving 5,814 patients. The overall risk of bias for 13 studies was low. The results showed that CAB 25 mg/m² significantly improved OS compared to androgen receptor pathway inhibitor (ARPI) (1.50 [1.30, 1.70]) and MIT (1.40 [1.20, 1.70]), but its efficacy was inferior to Lu-PSMA (0.42 [0.27, 0.67]) and therapeutic drug monitoring (TDM)-CAB (0.51 [0.38, 0.70]). CAB 25 mg/m² could significantly improve PFS compared to CAB + CP (1.40 [1.10, 2.00]), ARPI (1.80 [1.50, 2.30], MIT (1.40 [1.20, 1.60]), but its efficacy was not as good as CAB 20 mg/m² (0.92 [0.82, 1.00]), Lu-PSMA (0.58 [0.41, 0.80]), TDM-CAB (0.67 [0.51, 0.86]). In addition, compared to CAB 25 mg/m², CAB + CP may significantly increase the risk of SAEs (3.10 [1.70, 5.90]).</p><p><strong>Conclusion: </strong>CAB is an effective treatment in mCRPC, and combining it with other treatment methods may enhance efficacy, but attention should be paid to the occurrence of adverse events.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1586650"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310731/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncovering the molecular mechanisms of Qingdu Zengye Decoction in the treatment of nasopharyngeal carcinoma: an integrative investigation.","authors":"Qi Quan, Zeyu Liu, Ran Ding, Yongmiao Lin, Sihe Zhang, Wei Luo, Mengjie Lei, Teng Fan, Xin Su, Yuanyuan Huang, Roujun Peng, Bei Zhang","doi":"10.3389/fphar.2025.1648294","DOIUrl":"https://doi.org/10.3389/fphar.2025.1648294","url":null,"abstract":"<p><strong>Background: </strong>Nasopharyngeal carcinoma (NPC) remains a therapeutic challenge due to its aggressive nature and limited treatment efficacy. Traditional Chinese Medicine, particularly Qingdu Zengye Decoction (QZD), has shown clinical potential, but its mechanistic basis in NPC treatment requires elucidation.</p><p><strong>Purpose: </strong>This study aims to elucidate the mechanisms of action of QZD in the treatment of NPC, focusing on its multi-target regulatory effects on cell apoptosis, oncogenic signaling pathways, and tumor immune microenvironment.</p><p><strong>Methods: </strong>An integrative approach combining computational pharmacology, functional experiments, and single-cell transcriptomic profiling was employed to dissect QZD's anti-NPC mechanisms. Network pharmacology and protein-protein interaction (PPI) analysis was used to identify potential QZD targets. Functional assays (cell proliferation, apoptosis, colony formation) and Western blotting were used to validate key pathways. Molecular docking was applied to assessed ligand-target binding affinities. Single-cell RNA sequencing (scRNA-seq) was used to analyzed spatial expression patterns in NPC tumor samples.</p><p><strong>Results: </strong>QZD suppressed tumor progression by inducing apoptosis through modulating Bax in a dose-dependent manner and inhibiting the PI3K-Akt signaling pathway. Network pharmacology analysis identified AKT1, MTOR, HIF1A, SRC, and ESR1 as core regulatory genes. scRNA-seq revealed compartment-specific target localization: AKT1/ESR1 in tumor cells, SRC/IL6 in myeloid cells, and MTOR/HIF1A across stromal compartments. Molecular docking confirmed strong interactions between QZD compounds (e.g., quercetin, luteolin) and these targets. Upregulation of IL6 was observed and its dual immune-modulatory effects involving tumor suppression and microenvironment reprogramming was suggested.</p><p><strong>Conclusion: </strong>QZD exerts anti-tumor effects in NPC through apoptosis induction, PI3K-Akt pathway suppression, and multi-compartmental tumor microenvironment modulation. Its ability to concurrently target oncogenic signaling and immune regulation positions QZD as a promising therapeutic strategy for advanced NPC.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1648294"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving synergistic drug combination prediction with signature-based gene expression features in oncology.","authors":"Mozhgan Mozaffarilegha, Sajjad Gharaghani","doi":"10.3389/fphar.2025.1614758","DOIUrl":"https://doi.org/10.3389/fphar.2025.1614758","url":null,"abstract":"<p><strong>Background: </strong>Combination therapies play a crucial role in the treatment of complex diseases, such as cancer. They enhance efficacy, minimize resistance, and reduce toxicity by leveraging synergistic effects. However, identifying effective combinations is challenging due to the vast number of possible pairings and the high-priced costs of experimental validation. Machine learning (ML) and deep learning (DL) models have advanced drug synergy prediction by integrating diverse datasets and modeling the interactions between drugs and cell lines. Despite these advancements, most algorithms primarily rely on drug-specific features, such as chemical structures, with limited incorporation of functional drug information and cellular content features.</p><p><strong>Methods: </strong>We propose a novel approach that integrates Drug Resistance Signatures (DRS) as a biologically informed representation of drug information. This approach provides a more comprehensive framework for identifying effective combination therapies. We evaluated the predictive power of DRS features across various machine learning models (LASSO, Random Forest, AdaBoost, and XGBoost) and the deep learning model SynergyX. We compared their performance with that of conventional drug signatures and chemical structure-based descriptors.</p><p><strong>Results: </strong>Our results demonstrate that models incorporating DRS features consistently outperform traditional approaches across all evaluated algorithms. Validation on independent datasets, including ALMANAC, O'Neil, OncologyScreen, and DrugCombDB, confirms the robustness and generalizability of the proposed framework.</p><p><strong>Discussion: </strong>These findings emphasize the importance of integrating resistance-informed transcriptomic features into computational models. By capturing drug functionality in a biologically relevant context, DRS improves both the accuracy and interpretability of drug synergy prediction, offering a powerful strategy for guiding the discovery of effective combination therapies.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1614758"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310685/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shaping national rare diseases definition in Saudi Arabia: outcome from health ecosystem multisectoral workshop.","authors":"Ghada Mohammed Abozaid, Hussain Abdulrahman Al-Omar, Abdulaziz Alrabiah, Hiba Alomary, Amy Jayne McKnight","doi":"10.3389/fphar.2025.1595967","DOIUrl":"https://doi.org/10.3389/fphar.2025.1595967","url":null,"abstract":"<p><strong>Introduction: </strong>Rare diseases are characterized by low prevalence, a profound impact on patients, and significant challenges in accessing treatment. In Saudi Arabia, the absence of an official definition hampers policymaking, resource allocation, and orphan drugs accessibility. This study aimed to address this gap by proposing a definition of rare diseases using inputs and views from a Saudi multi-stakeholder workshop.</p><p><strong>Methods: </strong>A 1-day workshop was hosted in collaboration with the Saudi Health Council in Riyadh on 5 June 2023, involving 59 participants from various sectors, including clinicians, policymakers, patient advocates, and industry professionals. Using the Vevox^® platform, participants engaged in structured activities comprising a demographic survey and 10 interactive voting sessions. Preferred qualitative and quantitative criteria for defining rare diseases were identified and analyzed using descriptive statistics and thematic and content analysis of open-ended questions.</p><p><strong>Results: </strong>The findings indicated a strong preference (96%) for an integrated definition combining qualitative and quantitative criteria. Key qualitative terms such as \"Disease\" (62%), \"Serious\" (53%), and \"Disorder\" (51%) were favored for their clarity and broad applicability. \"Genetic\" etiology was preferred by 91% of participants, citing its relevance and data availability. Patient-centered criteria, including \"life-threatening\" (73%) and \"considerable reduction in quality of life\" (91%), were emphasized. Economic and resource-focused considerations, such as \"Lack of Resources\" and \"Combined Efforts to Prevent\" (each at 60%), reflected key unmet needs in the current healthcare landscape. Among quantitative criteria, \"Prevalence\" (82%) emerged as the most accepted, aligned with international practices, although opinions were mixed on the inclusion of population size thresholds, underscoring the definitional complexity of defining RDs with both precision and flexibility.</p><p><strong>Discussion: </strong>This study provides a foundational basis and scientific root for defining rare diseases in the Saudi context, addressing key gaps in healthcare policies. By integrating evidence-based, patient-centered, and resource-oriented criteria, the proposed definition supports equitable access, improved patient care, and sustainable innovation, in alignment with Saudi Arabia's Vision 2030 goals. Further refinement with broader stakeholder inputs is essential for the successful integration of Saudi healthcare policies.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1595967"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12312012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-enhanced discovery of tsRNA-mRNA regulatory networks: identifying novel diagnostic biomarkers and therapeutic targets in breast cancer.","authors":"Zhongling Ma, Rui Wang, Ming Yuan, Bo Wang, Li Li, Tianfu Zhao, Xinhan Zhao","doi":"10.3389/fphar.2025.1640192","DOIUrl":"https://doi.org/10.3389/fphar.2025.1640192","url":null,"abstract":"<p><strong>Background: </strong>Transfer RNA-derived small RNAs (tsRNAs) represent an emerging class of regulatory molecules with potential as cancer biomarkers. However, their diagnostic utility and regulatory mechanisms in breast cancer remain poorly characterized. This study integrates machine learning algorithms with traditional molecular biology approaches to identify tsRNA-based diagnostic signatures and their downstream targets.</p><p><strong>Methods: </strong>We analyzed miRNA-seq data from 103 matched tumor-normal pairs from TCGA-BRCA as the discovery cohort and GSE117452 as validation. tsRNA profiles were extracted using a custom bioinformatics pipeline. Random forest algorithm was employed to develop a diagnostic model. Correlation analysis and RNAhybrid were used to identify tsRNA-mRNA regulatory relationships. Comprehensive multi-omics analyses including survival, immune infiltration, drug sensitivity, and pathway enrichment were performed for identified targets. Functional validation was conducted in breast cancer cell lines.</p><p><strong>Results: </strong>We identified 297 differentially expressed tsRNAs and developed a four-tsRNA signature (tRF-21-FSXMSL73E, tRF-20-XSXMSL73, tRF-23-FSXMSL730H, tRF-23-YJE76INB0J) achieving AUC of 0.98 in discovery and 0.82 in validation cohorts. tRF-21-FSXMSL73E showed strong correlation with FAM155B expression. Pan-cancer analysis revealed FAM155B overexpression in multiple malignancies with prognostic significance. FAM155B correlated with immune infiltration, drug resistance, and activation of oncogenic pathways. Functional studies confirmed FAM155B promotes breast cancer proliferation and migration.</p><p><strong>Conclusion: </strong>Our machine learning approach successfully identified a robust tsRNA diagnostic signature and uncovered the tsRNA-FAM155B regulatory axis as a novel therapeutic target. This integrated methodology provides a framework for accelerating biomarker discovery by combining computational prediction with traditional validation, advancing precision medicine in breast cancer.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1640192"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310640/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statins and their impact on epigenetic regulation: insights into disease.","authors":"Rafael Tamayo-Trujillo, Patricia Guevara-Ramírez, Santiago Cadena-Ullauri, Viviana A Ruiz Pozo, Elius Paz-Cruz, Ana Karina Zambrano","doi":"10.3389/fphar.2025.1621163","DOIUrl":"https://doi.org/10.3389/fphar.2025.1621163","url":null,"abstract":"<p><p>Statins have been primarily used for the management of low-density lipoprotein cholesterol and cardiovascular diseases However, in recent years, research has identified potential applications beyond cholesterol regulation. Statins exhibit pleiotropic effects, due to their ability to modulate gene expression via epigenetic mechanisms, including DNA methylation, histone acetylation, and microRNA regulation. Clinical studies have correlated these epigenetic changes with various pathological conditions, such as inflammation, atherosclerosis, cancer, diabetes, and autoimmune disorders. Despite encouraging findings, further research is required to fully understand the molecular pathways associated with the epigenetic actions of statins and disease pathogenesis. This review describes the potential role of statins as epigenetic modulators and their relevance in human disease management.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1621163"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12312611/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Progress of targeted FOX family therapy in ovarian cancer.","authors":"Hairong Zhang, Cuiping Gong, Xin Lv","doi":"10.3389/fphar.2025.1604998","DOIUrl":"https://doi.org/10.3389/fphar.2025.1604998","url":null,"abstract":"<p><p>Ovarian cancer (OC) remains one of the most lethal malignancies affecting women, largely due to its asymptomatic onset and the consequent challenges in early detection and diagnosis. This often results in delayed treatment and poor clinical outcomes. Among gynecological cancers, OC exhibits the highest mortality rate. While current therapeutic approaches such as surgery and chemotherapy provide initial clinical benefit, they are frequently undermined by high rates of recurrence and metastasis. Moreover, the pronounced heterogeneity of OC further complicates treatment, highlighting the urgent need for novel therapeutic targets and more effective strategies. The forkhead box (FOX) family of transcription factors comprises a large group of proteins involved in regulating gene expression across various biological processes. Dysregulation of FOX family members has been implicated in aberrant cellular behaviors, including uncontrolled proliferation, resistance to apoptosis, enhanced invasiveness, metastatic potential, and the development of drug resistance. Importantly, the functional roles of individual FOX proteins vary significantly depending on the tumor context, reflecting the functional diversity of this family. This review aims to provide a comprehensive overview of the emerging roles of FOX family members in the pathogenesis and progression of OC, as well as recent advances in FOX-targeted therapeutic strategies.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"16 ","pages":"1604998"},"PeriodicalIF":4.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310647/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144759730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}