ArticleDigestive diseases and sciences2022
A microRNA Signature Identifies Patients at Risk of Barrett Esophagus Progression to Dysplasia and Cancer.
Article in Digestive diseases and sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Tissue Systems Pathology Test Predicts Risk of Progression in Patients With Barrett's Esophagus: Systematic Review and Meta-Analysis.Journal of clinical gastroenterology · 2026Pooled it
- MiRNA expression analysis from circulating exosomes in Barrett's esophagus patients with visceral obesity.Scientific reports · 2025Article
- Insight into the Role of the miR-584 Family in Human Cancers.International journal of molecular sciences · 2024Review
- Epigenetic Alterations from Barrett's Esophagus to Esophageal Adenocarcinoma.International journal of molecular sciences · 2023Review
- Management of nondysplastic Barrett's esophagus: When to survey? When to ablate?Therapeutic advances in chronic disease · 2022Review
- An miRNA Signature Predicts Grading of Pancreatic Neuroendocrine Neoplasms.Cancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundProgression of Barrett esophagus (BE) to esophageal adenocarcinoma occurs among a minority of BE patients. To date, BE behavior cannot be predicted on the basis of histologic features.
aimsWe compared BE samples that did not develop dysplasia or carcinoma upon follow-up of ≥ 7 years (BE nonprogressed [BEN]) with BE samples that developed carcinoma upon follow-up of 3 to 4 years (BE progressed [BEP]).
methodsThe NanoString nCounter miRNA assay was used to profile 24 biopsy samples of BE, including 13 BENs and 11 BEPs. Fifteen samples were randomly selected for miRNA prediction model training; nine were randomly selected for miRNA validation.
resultsUnpaired t tests with Welch's correction were performed on 800 measured miRNAs to identify the most differentially expressed miRNAs for cases of BEN and BEP. The top 12 miRNAs (P < .003) were selected for principal component analyses: miR-1278, miR-1301, miR-1304-5p, miR-517b-3p, miR-584-5p, miR-599, miR-103a-3p, miR-1197, miR-1256, miR-509-3-5p, miR-544b, miR-802. The 12-miRNA signature was first self-validated on the training dataset, resulting in 7 out of the 7 BEP samples being classified as BEP (100% sensitivity) and 7 out of the 8 BEN samples being classified as BEN (87.5% specificity). Upon validation, 4 out of the 4 BEP samples were classified as BEP (100% sensitivity) and 4 out of the 5 BEN samples were classified as BEN (80% specificity). Twenty-four samples were evaluated, and 22 cases were correctly classified. Overall accuracy was 91.67%.
conclusionUsing miRNA profiling, we have identified a 12-miRNA signature able to reliably differentiate cases of BEN from BEP.
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