Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Screening tests, particularly liquid biopsy with circulating miRNAs, hold significant potential for non-invasive cancer detection before symptoms manifest. METHODS: This study aimed to identify biomarkers with high sensitivity and specificity for multiple and specific cancer screening. 972 Serum miRNA profiles were compared across thirteen cancer types and healthy individuals using weighted miRNA co-expression network analysis. To prioritize miRNAs, module membership measure and miRNA trait significance were employed. Subsequently, for specific cancer screening, gastric cancer was focused on, using a similar strategy and a further step of preservation analysis. Machine learning techniques were then applied to evaluate two distinct miRNA panels: one for multi-cancer screening and another for gastric cancer classification. RESULTS: The first panel (hsa-miR-8073, hsa-miR-614, hsa-miR-548ah-5p, hsa-miR-1258) achieved 96.1% accuracy, 96% specificity, and 98.6% sensitivity in multi-cancer screening. The second panel (hsa-miR-1228-5p, hsa-miR-1343-3p, hsa-miR-6765-5p, hsa-miR-6787-5p) showed promise in detecting gastric cancer with 87% accuracy, 90% specificity, and 89% sensitivity. CONCLUSIONS: Both panels exhibit potential for patient classification in diagnostic and prognostic applications, highlighting the significance of liquid biopsy in advancing cancer screening methodologies.
Source: BMC Medical Genomics
Institutions: Shiraz University of Medical Sciences, University of Tehran, Pasteur Institute of Iran, Royan Institute, Academic Center for Education, Culture and Research, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University, Shahid Beheshti University of Medical Sciences
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,190
OpenAlex ID: W4407217867
