ArticleBMC bioinformatics2023
Integrated bioinformatics analysis for conducting a prognostic model and identifying immunotherapeutic targets in gastric cancer.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- An Evolutionary Research Framework for the Tumor Microenvironment in Gastric Cancer.Journal of inflammation research · 2026Article
- Identification of prognostic genes associated with tolerogenic dendritic cells in gastric cancer based on transcriptomic data.PloS one · 2026Article
- Causal inference of inflammatory proteins in infertility: a Mendelian randomization study.Frontiers in endocrinology · 2025Article
- Advances in nanomedicine and delivery systems for gastric cancer research.Frontiers in bioengineering and biotechnology · 2025Review
- Identification the Tumor Mechanics-Related Biomarkers in Gastric Cancer Patients Based on Bioinformatics and Machine Learning.International journal of general medicine · 2025Article
- Advances in targeted therapy for human epidermal growth factor receptor 2 positive in advanced gastric cancer.World journal of gastrointestinal oncology · 2024Review
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric cancer is the third leading cause of death from cancer worldwide and has a poor prognosis. Practical risk scores and prognostic models for gastric cancer are lacking. While immunotherapy has succeeded in some cancers, few gastric cancer patients benefit from immunotherapy. Immune genes and the tumor microenvironment (TME) are essential for cancer progression and immunotherapy response. However, the roles of immune genes and the tumor microenvironment in immunotherapy remain unclear. The study aimed to construct a prognostic prediction model and identify immunotherapeutic targets for gastric cancer (GC) patients by exploring immune genes and the tumor microenvironment.
resultsAn immune-related risk score (IRRS) model, including APOH, RNASE2, F2R, DEFB126, CXCL6, and CXCL3 genes, was constructed for risk stratification. Patients in the low-risk group, which was characterized by elevated tumor mutation burden (TMB) have higher survival rate. The risk level was remarkably correlated with tumor-infiltrating immune cells (TIICs), the immune checkpoint molecule expression, and immunophenoscore (IPS). CXCL3 and CXCL6 were significantly upregulated in gastric cancer tissues compared with normal tissues using the UALCAN database and RT-qPCR. The nomogram showed good calibration and moderate discrimination in predicting overall survival (OS) at 1-, 3-, and 5- year for gastric cancer patients using risk-level and clinical characteristics.
conclusionOur findings provided a risk stratification and prognosis prediction tool for gastric cancer patients and further the research into immunotherapy in gastric cancer.
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