ArticleScientific reports2018
Computational measurement of tumor immune microenvironment in gastric adenocarcinomas.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global Epidemiology of PD-L1 Expression in Epstein-Barr Virus-Associated Gastric Cancer: A Systematic Review and Meta-Analysis.Journal of gastrointestinal cancer · 2025Pooled it
- A deep learning-derived risk score model from digital pathology to forecast nivolumab outcomes in gastric carcinoma.British journal of cancer · 2026Article
- Deep learning-based radiomics and pathomics for decoding tumor microenvironment and predicting immunotherapy outcomes in gastric cancer.Frontiers in immunology · 2026Review
- PD-L1 expression in EBV associated gastric cancer: a systematic review and meta-analysis.Discover oncology · 2022Review
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- Digital image analysis in pathologist-selected regions of interest predicts survival more accurately than whole-slide analysis: a direct comparison study in 153 gastric carcinomas.The journal of pathology. Clinical research · 2021Article
- Established fibrous peritoneal metastasis in an immunocompetent mouse model similar to clinical immune microenvironment of gastric cancer.BMC cancer · 2020Article
- PD-L1 expression in gastric cancer determined by digital image analyses: pitfalls and correlation with pathologist interpretation.Virchows Archiv : an international journal of pathology · 2020Article
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6 authors.
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Abstract
The use of four groups of tumor immune microenvironments (TME) based on PD-L1 and tumor-infiltrating T lymphocytes (TIL) is a reliable biomarker for anti-PD-1/PD-L1 inhibitor therapy. We classified the TME in 241 gastric cancers which were subdivided according to 40 EBV+, 76 microsatellite instability-high (MSI-H), and 125 EBV-/microsatellite-stable (MSS) subtypes by quantitative image analysis (QIA) and correlated the results with mRNA expression levels. The mean PD-L1 ratio and CD8 ratio in EBV+, MSI-H, and EBV-/MSS GCs were significantly different (P < 0.006). The PD-L1 ratio and CD8 ratio obtained by QIA correlated well with the RNA levels of PD-L1 (r = 0.63) and CD8 (r = 0.67), respectively. The TME were type I (PD-L1
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