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Objective: To evaluate the roles of miR-137 and its target genes in lipid metabolism and prostate tumorigenesis.
Methods: We used a series of bioinformatic approaches to establish the relationship between miR-137 and its target genes. We mapped the metabolic pathways of interest in the Reactome database and identified the central target genes of miR-137 in this pathway using four platforms: Reactome, miRDB, miRmap, and TargetScan. To assess the expression and association with clinical parameters, we obtained information from the UALCAN, OncoDB, and GEPIA2 databases using a dataset of patients with prostate cancer from The Cancer Genome Atlas. For functional enrichment analysis and construction of the protein-protein interaction network, we used the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and STRING.
Results: Our in silico study of The Cancer Genome Atlas database revealed that miR-137 is underexpressed in tumor tissues, and its reduction is associated with poor prognosis. An intriguing set of eight genes within the PPARα pathway: PPARGC1A, PPARGC1B, NCOA1, NCOA2, NCOA3, MED1, MED27, and ESRRA displayed synergy, positive correlations, and synchronized expression patterns in adipose, hepatic, and prostatic tissues, all linked to the enigmatic processes of metabolic regulation. Among the highlighted genes, ESRRA was overexpressed in the malignant environment, whereas its counterparts remained underexpressed. The plot was thickened with associations between the expression of NCOA1, NCOA3, and MED27, lymph node involvement, and the overexpression of several genes linked to advanced prostate cancer stages. An intriguing pattern emerged, with patients exhibiting reduced disease-free survival overexpressing NCOA2, NCOA3, MED27, and ESRRA.
Conclusion: This study elucidates the possibility that miR-137 subtly modulates metabolic genes in prostate cancer, suggesting its latent therapeutic potential as a biomarker for disease progression.
Background: ■ The reduction of miR-137 in tumor tissues is associated with a worse prognosis.
Background: ■ miR-137 has eight oncogenically relevant target genes acting in the PPARα lipid pathway.
Background: ■ NCOA1, NCOA3, MED27, and ESRRA are associated with advanced prostate cancer.
Background: ■ miR-137 exhibits significant clinical potential by repressing the activation of pathways that influence prostate tumorigenesis in hyperstimulated metabolic environments.
Background: Prostate cancer progression is sustained by the simultaneous activation of pathways involving lipid uptake and de novo synthesis. In this context, miR-137 inhibits adipogenic differentiation and may reduce lipid uptake by tumor cells by modulating the PPAR/ p160/ESRRA axis, considerably attenuating metabolic effects and suppressing prostate tumorigenesis.
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http://dx.doi.org/10.31744/einstein_journal/2025AO1601 | DOI Listing |
Exp Ther Med
October 2025
Section of Molecular Pathology and Human Genetics, Department of Internal Medicine, School of Medicine, University of Crete, 71003 Heraklion, Greece.
Immune-related factors may serve an important role in the development of endometriosis, considering the occurrence of substantial abnormalities in the immune system of women with endometriosis, including reduced T-cell reactivity and natural killer cell cytotoxicity, as well as increased numbers and activation of peritoneal macrophages. Moreover, women suffering from endometriosis are at a higher risk for developing various autoimmune diseases as comorbidities of endometriosis. Recent epidemiological data demonstrate that patients with endometriosis have a significantly higher risk (2.
View Article and Find Full Text PDFHealth Sci Rep
September 2025
Department of Dermatology the Union Hospital, Fujian Medical University Fuzhou People's Republic of China.
Background And Aims: Several observational studies have reported inconsistent associations between dyslipidaemia, stains use and atopic dermatitis (AD). Nevertheless, the available data on the effects of -C-lowering as well as TG-lowering drugs remain inconclusive and limited. The aim of this study was to evaluate the causal association of lipid traits and long-term use of lipid-lowering drugs on AD risk.
View Article and Find Full Text PDFInt J Gen Med
September 2025
Department of Geriatrics, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, People's Republic of China.
Background: Sepsis is characterized by profound immune and metabolic perturbations, with glycolysis serving as a pivotal modulator of immune responses. However, the molecular mechanisms linking glycolytic reprogramming to immune dysfunction remain poorly defined.
Methods: Transcriptomic profiles of sepsis were obtained from the Gene Expression Omnibus.
Research (Wash D C)
September 2025
State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, characterized by a high propensity for metastasis, poor prognosis, and limited treatment options. Research has demonstrated a substantial correlation between the expression of protein arginine N-methyltransferase 1 (PRMT1) and enhanced proliferation, metastasis, and poor outcomes in TNBC. However, the specific role of PRMT1 in lung metastasis and chemoresistance remains unclear.
View Article and Find Full Text PDFBiochem Biophys Rep
December 2025
Division of Breast Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, 112, Taiwan.
Purpose: This study aimed to conduct functional proteomics across breast cancer subtypes with bioinformatics analyses.
Methods: Candidate proteins were identified using nanoscale liquid chromatography with tandem mass spectrometry (NanoLC-MS/MS) from core needle biopsy samples of early stage (0-III) breast cancers, followed by external validation with public domain gene-expression datasets (TCGA TARGET GTEx and TCGA BRCA).
Results: Seventeen proteins demonstrated significantly differential expression and protein-protein interaction (PPI) found the strong networks including COL2A1, COL11A1, COL6A1, COL6A2, THBS1 and LUM.