ArticleCancer cytopathology2025
An integrated multi-omics biomarker approach using molecular profiling and microRNAs for evaluation of pancreatic cyst fluid.
Article in Cancer cytopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Pre-analytical Best Practices for RNA Sequencing from Small Biopsies and Cytologic Specimens.Molecular diagnosis & therapy · 2026Review
- Population-specific MicroRNA biomarker discovery in breast ductal carcinoma via explainable graph neural multi-omics modeling.BMC cancer · 2026Article
- Pancreatic Cystic Lesions and Endoscopic Ultrasound Diagnostic Equipment: A Literature Review.Journal of clinical medicine · 2026Review
- FNA-based lipidomics reveals coordinated lipid metabolic remodeling in pancreatic cancer.Frontiers in molecular biosciences · 2026Article
- The clinical significance of circulating microRNAs as biomarkers in lung cancer diagnosis and prognosis.Discover oncology · 2025Review
- Extracellular Vesicles for Clinical Diagnostics: From Bulk Measurements to Single-Vesicle Analysis.ACS nano · 2025Review
- Epigenetic dysregulation in pancreatic cancer: emerging biomarkers and clinical applications.Frontiers in epigenetics and epigenomics · 2025Review
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16 authors.
Funding
Abstract
backgroundClassification and risk stratification of pancreatic cysts are challenging because of limited radiographic and cytomorphologic features. Although molecular profiling has emerged as an ancillary test for pancreatic cyst fluid (PCF), additional high-sensitivity and -specificity biomarkers are still needed for improved classification.
methodsIn this study, PCF from 93 patients, including intraductal papillary mucinous neoplasms (n = 65), mucinous cystic neoplasms (n = 9), serous cystadenomas (n = 9), pancreatic cyst not otherwise specified (n = 8), and pseudocysts (n = 2), were evaluated for biomarkers. Molecular profiling by next-generation sequencing was performed, and a subset of the cases (n = 32) were interrogated with 2083 microRNAs (miRNAs) to evaluate their use for pancreatic cyst risk stratification.
resultsAs independent PCF biomarkers in 32 cases with histologic diagnoses, three miRNAs performed significantly better than mutant KRAS, mutant GNAS, carcinoembryonic antigen (CEA), and serum carbohydrate antigen 19-9 (CA19-9) in discriminating high-risk from low-risk cysts. The three elevated miRNAs in combination with mutant KRAS, mutant GNAS, and serum CA19-9 displayed similar diagnostic performance (miR-4461: area under the curve [AUC], 0.950; 95% confidence interval [CI], 0.800-1; miR-6723-5p: AUC, 0.958; 95% CI, 0.850-1; miR-6755-3p: AUC, 0.942; 95% CI, 0.816-1) in discriminating high-risk from low-risk cysts, when compared to mutant KRAS, mutant GNAS, CEA, and serum CA19-9 (AUC, 0.950; 95% CI, 0.825-1). In the absence of CA19-9, the three-marker panel of KRAS, GNAS, and miRNAs showed marginally improved performance compared with KRAS, GNAS, and CEA, which highlights the potential utility of miRNAs as biomarkers in PCF analysis.
conclusionsThese findings demonstrate that a multiomics biomarker approach with elevated PCF miRNAs with mutant KRAS, mutant GNAS, and serum CA19-9 may help in better detecting high-risk cysts for early clinical intervention.
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