ArticleDiscover oncology2025
Identification of PD-L1-related biomarkers for selecting gastric adenocarcinoma patients for PD-1/PD-L1 inhibitor therapy.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Novel Liquid Biopsy in Gastrointestinal Cancers.Journal of gastroenterology and hepatology · 2026Review
- A bibliometric analysis of resistance to PD-1/PD-L1 inhibitors.Frontiers in immunology · 2026Article
- The research progress of the synergistic effect of Epstein-Barr virus andFrontiers in oncology · 2026Review
- Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
PD-1/PD-L1 inhibitors have been used to treat gastric cancer, and PD-L1 expression has been identified as a biomarker for predicting the effectiveness of immunotherapy in the treatment of gastric cancer. However, PD-L1 expression prediction for immunotherapy response is inaccurate, and improved response biomarkers are required. Thus, it is important to identify additional biomarkers that can predict the responses to PD-1/PD-L1 monoclonal antibodies in gastric cancer. In this study, GO and KEGG enrichment analysis of 142 DEGs co-expressed with PD-L1 were performed, and 41 genes were identified based on the intersection of the mRNA-significant GO term network and the mRNA-significant signalling pathway network. Further intersection analysis of the 41 candidate genes and 137 positive immunotherapy response genes indicated that BATF2 significantly affects the overall survival of GC patients. The transcription factor prediction for BATF2 identified additional potential predictors and therapeutic targets for GC. STAT and IRF family members were predicted to be transcription factors for BATF2. In addition, BATF2 knockdown significantly promoted GC cell growth, and PD-L1 expression was upregulated in si-BATF2-treated MKN-45 cells. Thus, BATF2 may serve as a biomarker for predicting the efficacy of PD-L1 blockade therapy in GC. BATF2 acts as a tumour suppressor gene during the development of GC. BATF2 is closely related to PD-L1 expression in GC, and high BATF2 expression positively correlates with low PD-L1 expression. BATF2 can be used as a potential biomarker and therapeutic target for responding to anti-PD-1 and anti-PD-L1 immunotherapies in GC.
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Registered trials
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