ArticleFrontiers in immunology2023
Prognostic significances of PD-L1- and CTLA-4-positive T cells and positive correlations of immunosuppressive marker expression between cancer tissue and peripheral blood in patients with gastric cancer.
Article in Frontiers in immunology, 2023. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
- Correlation Between SII and Lymphocyte Subsets in Gastric Cancer Patients and Its Prognostic Importance.Immunity, inflammation and disease · 2026Article
- The Neuroimmune Axis in Gastric Cancer: Bridging Neural Regulation, Tumor Microenvironment, and Immunotherapy.Oncology research · 2026Review
- Gastrointestinal tumor personalized immunotherapy: an integrated analysis from molecular genetics to imaging biomarkers.Therapeutic advances in gastroenterology · 2025Review
- Heterogeneity of lymphocyte subsets in predicting immune checkpoint inhibitor treatment response in advanced lung cancer: an analysis across different pathological types, therapeutic drugs, and age groups.Translational lung cancer research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Although tumor, node, metastasis (TNM) staging has been used for prognostic assessment of gastric cancer (GC), the prognosis may vary among patients with the same TNM stage. Recently, the TNM-Immune (TNM-I) classification staging system has been used for prognostic assessment of colorectal cancer based on intra-tumor T-cell status, which is a superior prognostic factor compared with the American Joint Committee on Cancer staging manual. However, an immunoscoring system with prognostic significance for GC has not been established. Method: Here, we evaluated immune phenotypes in cancer and normal tissues, then examined correlations between tissues and peripheral blood. GC patients who underwent gastrectomy at Seoul St. Mary's Hospital between February 2000 and May 2021 were included. We collected 43 peripheral blood samples preoperatively and a pair of gastric mucosal samples postoperatively, including normal and cancer mucosa, which did not influence tumor diagnosis and staging. Tissue microarray samples of GC were collected from 136 patients during surgery. We investigated correlations of immune phenotypes between tissues and peripheral blood using immunofluorescence imaging and flow cytometry, respectively. GC mucosa exhibited an increased number of CD4 Result: The expression levels of immunosuppressive markers were significantly increased in cancer tissues and peripheral blood mononuclear cells. In gastric mucosal tissues and peripheral blood of GC patients, similar immunosuppression phenotypes were observed, including increased numbers of PD-L1- and CTLA-4-positive T cells. Discussion: Therefore, peripheral blood analysis may be an important tool for prognostic assessment of GC patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.