Journal of Translational Medicine最新文献

{"title":"SOX4 accelerates intervertebral disc degeneration via EZH2/NRF2 pathway in response to mitochondrial ROS-dependent NLRP3 inflammasome activation in nucleus pulposus cells.","authors":"Wenzhi Zhao, Yadong Liu, Yunxiang Hu, Guiqi Zhang","doi":"10.1186/s12967-024-05913-1","DOIUrl":"10.1186/s12967-024-05913-1","url":null,"abstract":"<p><strong>Objective: </strong>The transcription factor SRY-related HMG-box 4 (SOX4) has been implicated in intervertebral disc diseases. This study aimed to investigate the role of SOX4 in intervertebral disc degeneration (IDD) and explore the underlying molecular mechanisms.</p><p><strong>Methods: </strong>We established an IDD rat model via surgery and analyzed SOX4 expression using qRT-PCR and Western blotting. Histological evaluation, immunohistochemistry, and Safranin O staining assessed IDD progression. In vitro, an IDD cellular model was constructed using IL-1β-stimulated nucleus pulposus (NP) cells. SOX4 knockdown and overexpression experiments in NP cells examined SOX4 effects on ECM degradation, NLRP3-mediated pyroptosis, and mitochondrial ROS-dependent NLRP3 inflammasome activation. The involvement of the EZH2/NRF2 pathway in SOX4-mediated NLRP3 activation was also examined.</p><p><strong>Results: </strong>SOX4 expression was significantly increased in IDD rats and promoted IDD progression. Knockdown of SOX4 inhibited ECM degradation and NLRP3-mediated pyroptosis in NP cells. In vitro experiments showed that SOX4 promoted ECM degradation by upregulating MMPs and ADAMTS-5 expression, and suppressed collagen II and aggrecan synthesis. SOX4 knockdown inhibited NLRP3-mediated pyroptosis, while overexpression accelerated it in NP cells. Additionally, SOX4 was found to exacerbate mitochondrial ROS-dependent NLRP3 inflammasome activation in NP cells. Further investigation revealed that SOX4 enhanced NLRP3 inflammasome activation by upregulating EZH2 expression and modulating the EZH2/NRF2 pathway, with EZH2 inhibition attenuating SOX4-induced NLRP3 activation.</p><p><strong>Conclusion: </strong>Our findings suggest that SOX4 accelerates IDD progression by promoting NLRP3 inflammasome activation via modulating the EZH2/NRF2 pathway, leading to NP cell pyroptosis and ECM degradation. Targeting SOX4 may represent a potential therapeutic strategy for treating IDD.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"395"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11969779/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780387","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":"Gene therapy shines light on congenital stationary night blindness for future cures.","authors":"Yi Zhang, Siqi Lin, Lingqi Yu, Xiang Lin, Shuai Qu, Qingyang Ye, Mengting Yu, Wenfeng Chen, Wenjie Wu","doi":"10.1186/s12967-025-06392-8","DOIUrl":"10.1186/s12967-025-06392-8","url":null,"abstract":"<p><p>Congenital Stationary Night Blindness (CSNB) is a non-progressive hereditary eye disease that primarily affects the retinal signal processing, resulting in significantly reduced vision under low-light conditions. CSNB encompasses various subtypes, each with distinct genetic patterns and pathogenic genes. Over the past few decades, gene therapy for retinal genetic disorders has made substantial progress; however, effective clinical therapies for CSNB are yet to be discovered. With the continuous advancement of gene-therapy tools, there is potential for these methods to become effective treatments for CSNB. Nonetheless, challenges remain in the treatment of CSNB, including issues related to delivery vectors, therapeutic efficacy, and possible side effects. This article reviews the clinical diagnosis, pathogenesis, and associated mutated genes of CSNB, discusses existing animal models, and explores the application of gene therapy technologies in retinal genetic disorders, as well as the current state of research on gene therapy for CSNB.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"392"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11969737/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780382","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":"5-Methylcytosine RNA modification and its roles in cancer and cancer chemotherapy resistance.","authors":"Fang Li, Tingting Liu, Yajing Dong, Qianqian Gao, Rongzhu Lu, Zhiyong Deng","doi":"10.1186/s12967-025-06217-8","DOIUrl":"10.1186/s12967-025-06217-8","url":null,"abstract":"<p><p>Recent advancements in cancer therapies have improved clinical outcomes, yet therapeutic resistance remains a significant challenge because of its complex mechanisms. Among epigenetic factors, m5C RNA modification is emerging as a key player in cancer drug resistance, similar to the well-known m6A modification. m5C affects RNA metabolism processes, including splicing, export, translation, and stability, thereby influencing drug efficacy. This review highlights the critical roles of m5C in modulating resistance to chemotherapy, targeted therapy, radiotherapy, and immunotherapy. This review also discusses the functions of key regulators, including methyltransferases, demethylases, and m5C-binding proteins, as essential modulators of the m5C epigenetic landscape that contribute to its dynamic and complex regulatory network. Targeting these regulatory components offers a promising strategy to overcome resistance. We highlight the need for further research to elucidate the specific mechanisms by which m5C contributes to resistance and to develop precise m5C-targeted therapies, presenting m5C-focused strategies as potential novel anticancer treatments.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"390"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11966802/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780311","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":"A gene-based predictive model for lymph node metastasis in cervical cancer: superior performance over imaging techniques.","authors":"Dongdong Xu, Xibo Zhao, Dongdong Ye, Chuying Huo, Xuanwei Peng, Yunyun Liu, Huaiwu Lu","doi":"10.1186/s12967-025-06327-3","DOIUrl":"10.1186/s12967-025-06327-3","url":null,"abstract":"<p><strong>Objective: </strong>Lymph node metastasis (LNM) critically impacts the prognosis and treatment decisions of cervical cancer patients. The accuracy and sensitivity of current imaging techniques, such as CT and MRI, are limited in assessing lymph node status. This study aims to develop a more accurate and efficient method for predicting LNM.</p><p><strong>Methods: </strong>Three independent cohorts were merged and divided into training and internal validation groups, with our cohort and those from other centers serving as external validation. A predictive model for LNM in cervical cancer was established using the LASSO regression and multivariate logistic regression. The diagnostic performance of the predictive model was compared with that of CT/MRI in terms of accuracy, sensitivity, specificity, and AUC.</p><p><strong>Results: </strong>Using RNA-seq data, four independent predictive genes (MAPT, EPB41L1, ACSL5, and PRPF4B) were identified through LASSO regression and multivariate logistic regression, and a predictive model was constructed to calculate the LNM risk score. Compared with CT/MRI, the model demonstrated higher diagnostic efficiency, with an accuracy of 0.840 and sensitivity of 0.804, compared to CT/MRI's accuracy of 0.713 and sensitivity of 0.587. The predictive model corrected 81% of misdiagnoses by CT/MRI, demonstrating significant improvements in accuracy and sensitivity.</p><p><strong>Conclusion: </strong>The predictive model developed in this study, based on gene expression data, significantly improves the preoperative assessment accuracy of LNM in cervical cancer. Compared to traditional imaging techniques, this model shows superior sensitivity and accuracy. This study provides a robust foundation for developing precise diagnostic tools, paving the way for future clinical applications in individualized treatment planning.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"397"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11969859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780312","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":"Glucagon-like Peptide-1 receptor agonists for obstructive sleep apnea in patients with obesity and type 2 diabetes mellitus: a systematic review and meta-analysis.","authors":"Ruifeng Yang, Lindong Zhang, Jiangfan Guo, Ning Wang, Qiue Zhang, Zhiwei Qi, Lili Wu, Lingling Qin, Tonghua Liu","doi":"10.1186/s12967-025-06302-y","DOIUrl":"10.1186/s12967-025-06302-y","url":null,"abstract":"<p><p>The systematic review was registered on the PROSPERO website (CRD42024558287). Our objective is to systematically summarise the clinical evidence of glucagon-like peptide-1 receptor agonists (GLP-1 RA) for obstructive sleep apnea (OSA) in patients with Obesity or/and type 2 Diabetes Mellitus (T2DM). This analysis was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. 10 databases and registers Web of Science, Scopus, PubMed, APA PsycInfo, Embase, Ovid, Cochrane Library, CINAHL, Clinicaltrials.gov, and International Clinical Trials Registry Platform (ICTRP) were retrieved from the establishment to July 14, 2024 for related randomized controlled trials (RCT) and non-RCTs. Data were extracted by two investigators separately, and only the RCTs were included in the quantitative synthesis. The outcome was operated by Review Manager 5.4 and Stata 15.0. Ten studies containing eight RCTs and two non-RCTs were included. The efficacy of the GLP-1 RA group in reducing apnea-hypopnea index (AHI) was superior to that of the control group in patients with T2DM (MD = -5.68, 95%CI [-7.97, -3.38], P < 0.00001, I² = 0%). GLP-1 RAs also possessed a tendency to reduce AHI in patients with obesity but more evidence is needed to support the findings due to the inconsistency. In consideration of the enhanced metabolic parameters observed with GLP-1 RAs, they may be recommended as useful hypoglycaemic medication for the management of T2DM with OSA. Patients with obesity and OSA may consider GLP-1 RA as a potential treatment option if the adverse events are deemed tolerable.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"389"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11967144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780383","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":"Impact of metagenomics next-generation sequencing on etiological diagnosis and early outcomes in sepsis.","authors":"Feixiang Xu, Chen Chen, Su Lu, Mingming Xue, Hailin Ding, Yanli Song, Yun Zhang, Keyu Sun, Lunxian Tang, Wei Wang, Meitang Wang, Yan Tang, Dingyu Tan, Chenling Yao, Dongwei Shi, Enqiang Mao, Mian Shao, Youguo Ying, Chunmei Zhou, Lihong Huang, Hu Peng, Zhongshu Kuang, Sanqiang Wang, Qingbian Ma, Si Sun, Dongfeng Guo, Tianwen Gu, Bin Yang, Linhao Ma, Chengjin Gao, Xiaoye Lu, Hong Zhang, Ruilan Wang, Chaoyang Tong, Zhenju Song","doi":"10.1186/s12967-025-06332-6","DOIUrl":"10.1186/s12967-025-06332-6","url":null,"abstract":"<p><strong>Background: </strong>Clinical implications of metagenomics next-generation sequencing (mNGS) in sepsis have not been fully evaluated. This study aimed to determine the diagnostic, therapeutic, and prognostic impacts of mNGS in sepsis.</p><p><strong>Methods: </strong>This multicenter prospective study was conducted at 19 sites in China from 2020 to 2021, and 859 adult patients hospitalized with sepsis were enrolled. The advantages, challenges, knowledge gaps and privacy risks of mNGS were carefully introduced to all participants, and participants chose on their own to either receive conventional microbiological test (CMT) alone (conventional-test-only group, n = 394) or receive mNGS test along with CMT (combined test group, n = 465). For prognostic analysis, the primary endpoint was 28-day mortality. Secondary endpoints included 7-day mortality and average per-day hospital cost. Inverse probability of treatment weighting was used to balance covariates between groups. Concurrent CMT and mNGS results from patients in the combined test group were used for diagnostic analyses. Therapeutic impact of mNGS was evaluated based on subsequent antibiotic adjustment.</p><p><strong>Results: </strong>Compared with composite reference standard, the positive percent agreement of mNGS among infected site samples was significantly higher than that of CMT (92.0% [95% CI, 88.7 to 94.5] vs. 51.1% [95% CI, 45.9 to 56.2], p < 0.001), while the negative percent agreement of mNGS was inferior to that of CMT (39.6% [95% CI, 29.5 to 50.4] vs. 69.2% [95% CI, 58.7 to 78.5], p < 0.001). The mNGS test identified causal microbes in 344 (74.0%) patients, and concomitant antibiotic changes occurred in 136 patients (29.2%). Death by day 7 occurred in 24 of 465 (5.2%) patients in the combined test group and in 34 of 394 (8.6%) patients in the conventional-test-only group (hazard ratio, 0.44 [95% CI, 0.26 to 0.77], p = 0.004). However, no significant difference in 28-day mortality was observed between two study groups (hazard ratio, 0.82 [0.56 to 1.20], p = 0.300).</p><p><strong>Conclusions: </strong>The mNGS test of infected site samples exhibited 40% higher pathogen detection rate than CMT in patients with sepsis, which led to improved etiological diagnosis and tailored antibiotic therapy. Additional use of mNGS halved the risk of early death in 7 days, but did not improve 28-day survival in patients with sepsis.</p><p><strong>Trial registration: </strong>chictr.org.cn Identifier: ChiCTR2000031113. Registered 22 March 2020.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"394"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11969879/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780386","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":"Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy.","authors":"Yuemin Wu, Wei Zhang, Xiao Liang, Pengpeng Zhang, Mengzhe Zhang, Yuqin Jiang, Yanan Cui, Yi Chen, Wenxin Zhou, Qi Liang, Jiali Dai, Chen Zhang, Jiali Xu, Jun Li, Tongfu Yu, Zhihong Zhang, Renhua Guo","doi":"10.1186/s12967-024-06057-y","DOIUrl":"10.1186/s12967-024-06057-y","url":null,"abstract":"<p><strong>Background: </strong>Non-small cell lung cancer (NSCLC) is highly heterogeneous, leading to varied treatment responses and immune-related adverse reactions (irAEs) among patients. Habitat radiomics allows non-invasive quantitative assessment of intratumor heterogeneity (ITH). Therefore, our objective is to employ habitat radiomics techniques to develop a robust approach for predicting the efficacy of Immune checkpoint inhibitors (ICIs) and the likelihood of irAEs in advanced NSCLC patients.</p><p><strong>Methods: </strong>In this retrospective two center study, two independent cohorts of patients with NSCLC were used to develop (n = 248) and validate signatures (n = 95). After applying four kinds of machine learning algorithms to select the key preoperative CT radiomic features, we used clinical, radiomics and habitat radiomic features to develop the clinical signature, radiomics signature and habitat radiomic signature for ICIs prognostics and irAEs prediction. By combining habitat radiomic features with corresponding clinicopathologic information, the nomogram signature was constructed in the training cohort. Next, the internal validation cohort (n = 75) of patients, and the external validation cohort (n = 20) of patients treated with ICIs were included to evaluate the predictive value of the four signatures, and their predictive performance was assessed by the area under operating characteristic curve (AUC).</p><p><strong>Results: </strong>Our study introduces a radiomic nomogram model that integrates clinical and habitat radiomic features to identify patients who may benefit from ICIs or experience irAEs. The Radiomics Nomogram model exhibited superior predictive performance in the training, validation, and external validation sets, with AUCs of 0.923, 0.817, and 0.899, respectively. This model outperformed both the Whole-tumor Radiomics Signature model (AUCs of 0.870, 0.736, and 0.626) and the Habitat Signature model (AUCs of 0.900, 0.804, and 0.808). The radiomics model focusing on tumor sub-regional habitat showed better predictive performance than the model derived from the entire tumor. Decision Curve Analysis (DCA) and calibration curves confirmed the nomogram's effectiveness.</p><p><strong>Conclusion: </strong>By leveraging machine learning to predict the outcomes of ICIs, we can move closer to achieving tailored ICIs for lung cancer. This advancement will assist physicians in selecting and managing subsequent treatment strategies, thereby facilitating clinical decision-making.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"393"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970015/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780384","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 and multi-omics integration: advancing cardiovascular translational research and clinical practice.","authors":"Mingzhi Lin, Jiuqi Guo, Zhilin Gu, Wenyi Tang, Hongqian Tao, Shilong You, Dalin Jia, Yingxian Sun, Pengyu Jia","doi":"10.1186/s12967-025-06425-2","DOIUrl":"10.1186/s12967-025-06425-2","url":null,"abstract":"<p><p>The global burden of cardiovascular diseases continues to rise, making their prevention, diagnosis and treatment increasingly critical. With advancements and breakthroughs in omics technologies such as high-throughput sequencing, multi-omics approaches can offer a closer reflection of the complex physiological and pathological changes in the body from a molecular perspective, providing new microscopic insights into cardiovascular diseases research. However, due to the vast volume and complexity of data, accurately describing, utilising, and translating these biomedical data demands substantial effort. Researchers and clinicians are actively developing artificial intelligence (AI) methods for data-driven knowledge discovery and causal inference using various omics data. These AI approaches, integrated with multi-omics research, have shown promising outcomes in cardiovascular studies. In this review, we outline the methods for integrating machine learning, one of the most successful applications of AI, with omics data and summarise representative AI models developed that leverage various omics data to facilitate the exploration of cardiovascular diseases from underlying mechanisms to clinical practice. Particular emphasis is placed on the effectiveness of using AI to extract potential molecular information to address current knowledge gaps. We discuss the challenges and opportunities of integrating omics with AI into routine diagnostic and therapeutic practices and anticipate the future development of novel AI models for wider application in the field of cardiovascular diseases.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"388"},"PeriodicalIF":6.1,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11966820/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143772679","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":"Bioinformatics analysis and experimental validation of potential targets and pathways in chronic kidney disease associated with renal fibrosis.","authors":"Cui Huimin, Zhao Yuxin, Wang Peng, Gong Wei, Lin Hong, Li Na, Yang Jianjun","doi":"10.1186/s12967-024-06058-x","DOIUrl":"10.1186/s12967-024-06058-x","url":null,"abstract":"<p><strong>Background: </strong>Chronic kidney disease (CKD) has emerged as a major health problem worldwide. Previous studies have shown that specific miRNA expression profiles of patients with CKD are significantly changed. In this study, we aim to elucidate the role of miRNAs as potential biomarkers in CKD progression by integrating bioinformatics analysis with experimental validation, thereby providing medical evidence for the prevention and treatment of CKD.</p><p><strong>Method: </strong>Bioinformatics analysis was used to identify potential targets and pathways in CKD-associated renal fibrosis through randomly obtaining miRNA microarray data related to CKD patients in the Gene Expression Omnibus (GEO) database according to the inclusion and exclusion criteria, conducting pathway enrichment analysis and constructing protein-protein interaction (PPI) networks and miRNA-mRNA network by Cytoscape 3.8.0. In vitro experiments were employed to verify the role and mechanism of miR-223-3p in human renal tubular epithelial cells (HK2) through Quantitative real-time PCR assays, Western blot, Immunofluorescence analysis and Double luciferase reporter gene experiment. Multi-group one-way analysis of variance (ANOVA) and the Dunnett-t test were uesd to analyze the results by SPSS24.0.</p><p><strong>Results: </strong>10 up-regulated and 11 down-regulated miRNAs of CKD patients were screened out. Phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) was the first pathway of pathway enrichment analysis. MiR-223-3p (logFC=-2.047, p = 0.002) was one of the four hub miRNAs. Furthermore, we observed a reduction in α-smooth muscle actin (α-SMA) (p = 0.001) and Collagen type I alpha 1 (Col1-a1) (p = 0.023) levels upon miR-223-3p overexpression, which aligned with our bioinformatics predictions. This downregulation was attributed to the inhibition of nuclear factor kappa-B (NF-κB) nuclear translocation and subsequent decrease in the secretion of inflammatory cytokines, such as interleukin-6 (IL-6) (p = 0.005). Conversely, when CHUK was further overexpressed, the inhibitory effect of miR-223-3p on epithelial-mesenchymal transition (EMT) was attenuated, confirming the specific interaction between miR-223-3p and CHUK.</p><p><strong>Conclusion: </strong>Our findings provide compelling evidence that miR-223-3p acts as a suppressor of EMT in CKD by specifically targeting the CHUK and modulating the PI3K/Akt pathway, which holds great promise as a novel therapeutic target for CKD treatment. Additionally, this study offers a potential avenue for the development of future interventions aimed at halting or reversing the progression of CKD.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"387"},"PeriodicalIF":6.1,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11967072/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143772663","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":"Epithelial-mesenchymal transition orchestrates tumor microenvironment: current perceptions and challenges.","authors":"Yuqi Xie, Xuan Wang, Wenquan Wang, Ning Pu, Liang Liu","doi":"10.1186/s12967-025-06422-5","DOIUrl":"10.1186/s12967-025-06422-5","url":null,"abstract":"<p><p>The epithelial-mesenchymal transition (EMT) is a critical process in cancer progression, facilitating tumor cells to develop invasive traits and augmenting their migratory capabilities. EMT is primed by tumor microenvironment (TME)-derived signals, whereupon cancer cells undergoing EMT in turn remodel the TME, thereby modulating tumor progression and therapeutic response. This review discusses the mechanisms by which EMT coordinates TME dynamics, including secretion of soluble factors, direct cell contact, release of exosomes and enzymes, as well as metabolic reprogramming. Recent evidence also indicates that cells undergoing EMT may differentiate into cancer-associated fibroblasts, thereby establishing themselves as functional constituents of the TME. Elucidating the relationship between EMT and the TME offers novel perspectives for therapeutic strategies to enhance cancer treatment efficacy. Although EMT-directed therapies present significant therapeutic potential, the current lack of effective targeting approaches-attributable to EMT complexity and its microenvironmental context dependency-underscores the necessity for mechanistic investigations and translational clinical validation.</p>","PeriodicalId":17458,"journal":{"name":"Journal of Translational Medicine","volume":"23 1","pages":"386"},"PeriodicalIF":6.1,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11963649/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143772591","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}