ArticleBritish journal of cancer2025
Artificial intelligence-driven microRNA signature for early detection of gastric cancer: discovery and clinical functional exploration.
Article in British journal of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- An RNase domain-dependent microRNA detection with DNA-spiked nanocage for accurate cancer diagnosis.Nature communications · 2026Article
- MicroRNAs as master regulators of macrophage function in atherosclerosis: From polarization to therapeutic potential.iScience · 2026Review
- MT1JP/miR-103a-3p induce pyroptosis and regulate the tumor immune microenvironment in gastric cancer.Scientific reports · 2025Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric cancer (GC) is a leading cause of cancer-related deaths worldwide, with late-stage diagnoses frequently leading to poor outcomes. This underscores the need for effective early-stage gastric cancer (ESGC) diagnostics.
methodsWe introduce ESGCmiRD, an innovative artificial intelligence-driven strategy that identifies a miRNA signature for ESGC detection by integrating robust expression patterns, ESGC relevance, and regulatory capabilities of microRNA (miRNA) based on multiple networks. Expression and biological roles of miRNAs in GC were validated and explored via bioinformatics analysis and in vitro studies. miRNA-target interaction was confirmed by dual-luciferase reporter assay. Molecular docking predicted miRNA-drug binding affinities, assessing the miRNA signature's therapeutic potential.
resultsESGCmiRD identified a blood miRNA signature (miR-320b, miR-222-3p, miR-181a-5p, miR-103a-3p, miR-107) for ESGC detection, demonstrated high diagnostic accuracy with AUC values of 0.986, 0.977, 0.815, and 0.811 in the test and three validation sets (GSE211692, TCGA-STAD, and our cohort), respectively. The five miRNAs were overexpressed in ESGC plasma and directly target PTEN, promoting GC cell proliferation, migration, and invasion. Molecular docking suggested Paclitaxel had the strongest potential interaction with these miRNAs.
conclusionThis method identifies a robust miRNA signature for ESGC detection and sheds light on gastric carcinogenesis mechanisms, opening doors for potential therapeutic strategies.
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