ArticleJAMA network open2019
Development and Validation of an Esophageal Squamous Cell Carcinoma Detection Model by Large-Scale MicroRNA Profiling.
Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 42 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
42 citing papers in PubMed, 1 synthesis or guideline pooled it, 76 citations in OpenAlex.
- Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Upper Gastrointestinal Cancers: A Systematic Review.Advances in therapy · 2021Pooled it
- Changes in Multiple microRNA Levels with Antidepressant Treatment Are Associated with Remission and Interact with Key Pathways: A Comprehensive microRNA Analysis.International journal of molecular sciences · 2023Trial
- Advances in multi-omics for esophageal squamous cell carcinoma: diagnostic, prognostic, and therapeutic perspectives.Protein & cell · 2026Review
- The advancements in organoids: Potential and challenges in researching the esophagus and esophageal squamous cell carcinoma.Genes & diseases · 2026Review
- miRBiT: a rules-based single-sample serum miRNA classifier for pan-cancer detection with multi-cohort validation.Briefings in bioinformatics · 2026Article
- MicroRNAs in Esophageal Cancer: Implications for Diagnosis, Progression, Prognosis and Chemoresistance.International journal of molecular sciences · 2026Review
- Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach.BMC medical genomics · 2025Article
- Development of a novel circulating miRNA panel for early detection of esophageal cancer.American journal of translational research · 2025Article
- Early Cancer Detection via Multi-microRNA Profiling of Urinary Exosomes Captured by Nanowires.Analytical chemistry · 2024Article
- Noninvasive multi-cancer detection using blood-based cell-free microRNAs.Scientific reports · 2024Article
- Article
- Integrated analysis of diverse cancer types reveals a breast cancer-specific serum miRNA biomarker through relative expression orderings analysis.Breast cancer research and treatment · 2024Article
- DNA methylation markers in esophageal cancer.Frontiers in genetics · 2024Review
- circSSPO boosts growth of esophageal squamous cell carcinoma through upregulation of micrRNA-6820-5p-mediated KLK8 and PKD1 expression.Cell biology and toxicology · 2023Article
- Construct of qualitative diagnostic biomarkers specific for glioma by pairing serum microRNAs.BMC genomics · 2023Article
- An integrated analysis of dysregulated SCD1 in human cancers and functional verification of miR-181a-5p/SCD1 axis in esophageal squamous cell carcinoma.Computational and structural biotechnology journal · 2023Article
- A Novel Plasma-Based Methylation Panel for Upper Gastrointestinal Cancer Early Detection.Cancers · 2022Article
- Identification of circulating microRNAs as potential biomarkers for hepatic necroinflammation in patients with autoimmune hepatitis.BMJ open gastroenterology · 2022Article
- Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids.Communications biology · 2022Article
- CancerMIRNome: an interactive analysis and visualization database for miRNome profiles of human cancer.Nucleic acids research · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
14 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Patients with late-stage esophageal squamous cell carcinoma (ESCC) have a poor prognosis. Noninvasive screening tests using serum microRNAs (miRNAs) to accurately detect early-stage ESCC are needed to improve mortality. Objective: To establish a model using serum miRNAs to distinguish patients with ESCC from noncancer controls. Design, Setting, and Participants: In this case-control study, serum miRNA expression profiles of patients with ESCC (n = 566) and control patients without cancer (n = 4965) were retrospectively analyzed to establish a diagnostic model, which was tested in a training set and confirmed in a validation set. Patients histologically diagnosed as having ESCC who did not receive prior therapy or have a past or concurrent cancer other than ESCC were enrolled from the National Cancer Center Hospital in Tokyo, Japan. Between October 2010 and November 2015, control samples were collected from the National Cancer Center Biobank, the Biobank of the National Center for Geriatrics and Gerontology, and the general population undergoing routine health examination. Data analysis was performed between August 2015 and October 2018. Serum samples were randomly divided into discovery and validation sets. Main Outcomes and Measures: The expression of 2565 miRNAs was assessed in each sample. The discriminant model (named the EC index) was evaluated in the training set using Fisher linear discriminant analysis with a greedy algorithm. Receiver operating characteristic curve analysis evaluated the diagnostic ability of the model in the validation set. Results: In the training set, 283 patients with esophageal cancer (median age, 67 years [range, 37-90 years]; 83.4% male) were compared with 283 control patients (median age, 54 years [range, 22-100 years]; 43.1% male), and the EC index was constructed using 6 miRNAs (miR-8073, miR-6820-5p, miR-6794-5p, miR-3196, miR-744-5p, and miR-6799-5p). The area under the receiver operating characteristic curve was 1.00, with sensitivity of 1.00 and specificity of 0.98. The validation set included 283 patients (median age, 66 years [range, 42-87 years]; 83.0% male) and 4682 control patients (median age, 68 years [range, 20-98 years]; 44.7% male), and the area under the receiver operating characteristic curve for the EC index was 1.00, with sensitivity of 0.96 and specificity of 0.98. Conclusions and Relevance: What appears to be novel serum miRNA discriminant model was developed for the diagnosis of ESCC. A multicenter prospective study is ongoing to confirm the present observations.
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