ArticleBMC cancer2021
Construction of a microenvironment immune gene model for predicting the prognosis of endometrial cancer.
Article in BMC cancer, 2021. 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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Who cites it
9 citing papers in PubMed.
- Development and validation of a prognostic model based on metabolic risk score to predict overall survival of endometrial cancer in Chinese patients.Journal of gynecologic oncology · 2023Trial
- SRM Represents a Novel Prognosis Biomarker and Correlates With Inflammation and Immune Infiltration in Hepatocellular Carcinoma.Mediators of inflammation · 2026Article
- Knockdown TNF family prognosis index crucial gene PDE4B promoted PANoptosis of ovarian carcinoma cell:Based in vitro and in vivo experiments.Translational oncology · 2025Article
- DNA methylation expression patterns predict outcome of clear cell renal cell carcinoma.Discover oncology · 2025Article
- Risk prediction model of uterine corpus endometrial carcinoma based on immune-related genes.BMC women's health · 2024Article
- MCM10: An effective treatment target and a prognostic biomarker in patients with uterine corpus endometrial carcinoma.Journal of cellular and molecular medicine · 2023Article
- Features of the immunosuppressive tumor microenvironment in endometrial cancer based on molecular subtype.Frontiers in oncology · 2023Review
- Article
- Exploring the role of macrophages in the progression from atypical hyperplasia to endometrial carcinoma through single-cell transcriptomics and bulk transcriptomics analysis.Frontiers in endocrinology · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundInfiltrating immune and stromal cells are important components of the endometrial cancer (EC) microenvironment, which has a significant effect on the biological behavior of EC, suggesting that unique immune-related genes may be associated with the prognosis of EC. However, the association of immune-related genes with the prognosis of EC has not been elucidated. We attempted to identify immune-related genes with potentially prognostic value in EC using The Cancer Genome Atlas database and the relationship between immune microenvironment and EC.
methodsWe analyzed 578 EC samples from TCGA database and used weighted gene co-expression network analysis to screen out immune-related genes. We constructed a protein-protein interaction network and analyzed it using STRING and Cytoscape. Immune-related genes were analyzed through conjoint Cox regression and random forest algorithm analysis were to identify a multi-gene prediction model and stratify low-risk and high-risk groups of EC patients. Based on these data, we constructed a nomogram prediction model to improve prognosis assessment. Evaluation of Immunological, gene mutations and gene enrichment analysis were applied on these groups to quantify additional differences.
resultsUsing conjoint Cox regression and random forest algorithm, we found that TRBC2, TRAC, LPXN, and ARHGAP30 were associated with the prognosis of EC and constructed four gene risk models for overall survival and a consistent nomogram. The time-dependent receiver operating characteristic curve analysis revealed that the area under the curve for 1-, 3-, and 5-y overall survival was 0.687, 0.699, and 0.76, respectively. These results were validated using a validation cohort. Immune-related pathways were mostly enriched in the low-risk group, which had higher levels of immune infiltration and immune status.
conclusionOur study provides new insights for novel biomarkers and immunotherapy targets in EC.
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