Leveraging miRNA-mediated expression profiles to predict prognosis and identify distinct molecular subtypes in ovarian cancer: a multi-cohort study

International Immunopharmacology, Journal Year: 2025, Volume and Issue: 150, P. 114303 - 114303

Published: Feb. 16, 2025

Ovarian cancer (OV) remains the deadliest gynecological malignancy, with non-coding RNA-mediated transcriptomic deregulation significantly influencing its prognosis and heterogeneous progression. In this study, we prioritized miRNA-mediated gene expression profiles by identifying key negative correlations between miRNA-mRNA pairs. We developed a machine learning-based index (NCI), incorporating four-gene signature (GAS1, GFPT2, ZFHX4, KCNA1) to predict patient therapeutic response. Validation across multiple datasets revealed that OV patients higher NCI scores had poorer survival outcomes resistance immunotherapy. Additionally, established four-class subtyping taxonomy through unsupervised clustering, validated in four independent datasets. The S1 S3 subtypes were characterized high scores, abundant stromal immune infiltration, subtype exhibiting worst survival. Conversely, S2 showed downregulation of response genes, while S4 displayed epithelial differentiation favourable prognosis. Integrative analyses bulk single-cell data fibroblast proportion compared other subtypes, whereas was marked T cell content. Through ridge regression-based drug sensitivity analyses, candidate therapeutics for each subtype. Notably, demonstrated dasatinib but methotrexate. Finally, user-friendly Shiny-based website facilitate application our prognostic classification models (https://jli-bioinfo.shinyapps.io/NCI_online/). This study establishes critical marker proposes novel molecular framework grounded miRNA-regulated profiles, advancing understanding mechanisms driving heterogeneity.

Language: Английский

MiR-3613-5p targets AQP4 to promote the progression of chronic atrophic gastritis to gastric cancer

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 4, 2025

Introduction: Gastric cancer (GC) exhibits high invasiveness, delayed diagnosis, and poor prognosis. Chronic atrophic gastritis (CAG), an initial stage within the Correa cascade, induces gastric mucosal inflammation atrophy, promoting genetic epigenetic alterations. MicroRNAs (miRNAs) dysregulation has been implicated in tumorigenesis, yet their specific roles CAG progression to GC remain unclear. Methods: Using clinical data from GEO database, we identified miRNAs differentially expressed mucosa serum samples patients. Murine models were established through administration of N-methyl-N-nitrosourea (MNU) high-salt diet (HSD). In vitro functional assays evaluated proliferation migration after miRNA modulation cell lines. MiRNA target validation involved luciferase reporter assays. Results: MiR-3613-5p expression was significantly elevated patients, tissues tumor tissues, human demonstrated increased miR-3613-5p following MNU HSD-induced CAG. Functionally, overexpression promoted vitro, whereas silencing alleviated pathological alterations (atrophy, hyperplasia, inflammatory infiltration) vivo. Mechanistically, inhibited Aquaporin 4 (AQP4) by directly targeting its 3'UTR. Discussion: Our findings provide first evidence that facilitates toward via negative regulation AQP4. These results highlight as a promising biomarker therapeutic target, suggesting antagomiR-3613-5p potential novel strategy prevent carcinogenesis.

Language: Английский

Potential shared gene signatures and molecular mechanisms between recurrent pregnancy loss and ovarian cancer

Frontiers in Oncology, Journal Year: 2024, Volume and Issue: 14

Published: Nov. 14, 2024

Background Ovarian cancer (OV) is the second most prevalent gynecological tumor. Recurrent pregnancy loss (RPL) refers to two or more spontaneous abortions. However, molecular mechanisms underlying both OV and RPL remain poorly understood. This article focuses on exploration of common genetic characteristics their mechanisms. Methods The 71 differentially expressed genes associated with 1427 survival were analyzed, among which 7 important in pathogenesis OV. Then stepAIC analysis was performed simplify model decrease number genes, yielded a final set 5 prognostic coefficients construct risk scoring system. Univariate multivariate Cox analyses conducted verify independent factor for patients. GSEA GO results showed enriched biological pathways high/low groups, thereby revealing characteristics. effect immunotherapy better LR There significantly higher enrichment score stemness tumor aneuploidy HR group. Results A five-gene provided accurate prognosis OV, this system validated using external cohorts. an index Based levels ICs, immune cell infiltration, predicted response, low patients likely benefit from immunotherapies. Conclusions 5-gene can predict patients, draw attention clinicians help stratify into high groups management.

Language: Английский