ArticleBMC gastroenterology2022
CD10 and Das1: a biomarker study using immunohistochemistry to subtype gastric intestinal metaplasia.
Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 16 citations in OpenAlex.
- Stage-Specific Mucin Reprogramming Across the Gastric Cancer Cascade: Unveiling Molecular Mechanisms and Novel Therapeutic Vulnerabilities.Biomolecules · 2026Review
- Spatial transcriptomics defines IM-crypt as a premalignant niche with bidirectional divergence in early gastric carcinogenesis.Communications biology · 2026Article
- Identification and verification of SPP1 in anoikis as a prognostic biomarker for intestinal metaplasia and gastric cancer.Scientific reports · 2026Article
- Multi-bioinformatics revealed potential biomarkers and repurposed drugs for gastric adenocarcinoma-related gastric intestinal metaplasia.NPJ systems biology and applications · 2024Article
- METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics.Nature communications · 2024Article
- Refining the diagnostic utility of OLFM4 in gastric cancer precursors: a call for rigorous methodologies.Molecular cancer · 2024Article
- OLFM4 promotes the progression of intestinal metaplasia through activation of the MYH9/GSK3β/β-catenin pathway.Molecular cancer · 2024Article
- An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers.Cancer research communications · 2023Article
- Gastric Intestinal Metaplasia: Challenges and the Opportunity for Precision Prevention.Cancers · 2023Review
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7 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundIntestinal metaplasia (IM) is considered a key pivot point in the Correa model of gastric cancer (GC). It is histologically subtyped into the complete and incomplete subtypes, the latter being associated with a greater risk of progression. However, the clinical utility of IM subtyping remains unclear, partially due to the absence of reliable defining biomarkers.
methodsBased on gene expression data and existing literature, we selected CD10 and Das1 as candidate biomarkers to distinguish complete and incomplete IM glands in tissues from patients without GC (IM-GC) and patients with GC (IM + GC). Immunohistochemical staining of individually subtyped IM glands was scored after blinding by two researchers using tissue belonging to both IM-GC and IM + GC patients. Whole tissue Das1 staining was further assessed using digital image quantification (cellSens Dimension, Olympus).
resultsAcross both cohorts CD10 stained the IM brush border and was shown to have a high sensitivity (87.5% and 94.9% in IM-GC and IM + GC patients respectively) and specificity (100.0% and 96.7% respectively) with an overall AUROC of 0.944 for complete IM glands. By contrast Das1 stained mainly goblet cells and the apical membrane of epithelial cells, mostly of incomplete IM glands with a low sensitivity (28.6% and 29.3% in IM-GC and IM + GC patients respectively) but high specificity (98.3% and 85.1% respectively) and an overall AUROC of 0.603 for incomplete IM glands. A combined logistic regression model showed a significant increase in AUROC for detecting complete IM glands (0.955 vs 0.970). Whole tissue digital quantification of Das1 staining showed a significant association with incomplete IM compared to complete IM, both in IM-GC and in IM + GC patients (p = 0.016 and p = 0.009 respectively, Mann-Whitney test and unpaired t test used). Additionally, complete IM in IM + GC patients exhibited significantly more Das1 staining than in IM-GC patients (p = 0.019, Mann-Whitney test).
conclusionsThese findings suggest that CD10 is an outstanding biomarker for complete IM and Das1 may be useful as a secondary biomarker for IM glands at greater risk of progression irrespective of IM subtype. Overall, the clinical use of these biomarkers could lead to improved patient stratification and targeted surveillance.
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