ArticleFrontiers in oncology2020
Bioinformatics Identified 17 Immune Genes as Prognostic Biomarkers for Breast Cancer: Application Study Based on Artificial Intelligence Algorithms.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Comparison of the Cox Proportional Hazards Model and Random Survival Forest Algorithm for Predicting Patient-Specific Survival Probabilities in Clinical Trial Data.Biometrical journal. Biometrische Zeitschrift · 2026Article
- Adaptive variable channel heat dissipation control of ground control station under various work modes.Scientific reports · 2025Article
- Identification of a Potential PGK1 Inhibitor with the Suppression of Breast Cancer Cells Using Virtual Screening and Molecular Docking.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Clinical glycoproteomics: methods and diseases.MedComm · 2024Review
- Single‑cell RNA‑seq necroptosis‑related genes predict the prognosis of breast cancer and affect the differentiation of CD4Molecular and clinical oncology · 2024Article
- Artificial intelligence and bioinformatics: a journey from traditional techniques to smart approaches.Gastroenterology and hepatology from bed to bench · 2024Review
- Cancer Metastasis Prediction and Genomic Biomarker Identification through Machine Learning and eXplainable Artificial Intelligence in Breast Cancer Research.Diagnostics (Basel, Switzerland) · 2023Article
- Identification and validation of a five-gene prognostic signature based on bioinformatics analyses in breast cancer.Heliyon · 2023Article
- Breast Cancer Dataset, Classification and Detection Using Deep Learning.Healthcare (Basel, Switzerland) · 2022Review
- A novel fatty acid metabolism-related gene signature predicts the prognosis, tumor immune properties, and immunotherapy response of colon adenocarcinoma patients.FASEB bioAdvances · 2022Article
- CLEC10A can serve as a potential therapeutic target and its level correlates with immune infiltration in breast cancer.Oncology letters · 2022Article
- Improve individual treatment by comparing treatment benefits: cancer artificial intelligence survival analysis system for cervical carcinoma.Journal of translational medicine · 2022Article
- Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system.BMC bioinformatics · 2022Article
- Identification and characterization of four immune-related signatures in keloid.Frontiers in immunology · 2022Article
- A newly defined basement membrane-related gene signature for the prognosis of clear-cell renal cell carcinoma.Frontiers in genetics · 2022Article
- Mapping intellectual structures and research hotspots in the application of artificial intelligence in cancer: A bibliometric analysis.Frontiers in oncology · 2022Article
- In Silico Identification of Key Genes and Immune Infiltration Characteristics in Epicardial Adipose Tissue from Patients with Coronary Artery Disease.BioMed research international · 2022Article
- Artificial intelligence predictive system of individual survival rate for lung adenocarcinoma.Computational and structural biotechnology journal · 2022Article
- Identification by Bioinformatics Analysis of Potential Key Genes Related to the Progression and Prognosis of Gastric Cancer.Frontiers in oncology · 2022Article
- A Comprehensive Analysis of the Glutathione Peroxidase 8 (GPX8) in Human Cancer.Frontiers in oncology · 2022Article
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4 authors.
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Abstract
An increasing body of evidence supports the association of immune genes with tumorigenesis and prognosis of breast cancer (BC). This research aims at exploring potential regulatory mechanisms and identifying immunogenic prognostic markers for BC, which were used to construct a prognostic signature for disease-free survival (DFS) of BC based on artificial intelligence algorithms. Differentially expressed immune genes were identified between normal tissues and tumor tissues. Univariate Cox regression identified potential prognostic immune genes. Thirty-four transcription factors and 34 immune genes were used to develop an immune regulatory network. The artificial intelligence survival prediction system was developed based on three artificial intelligence algorithms. Multivariate Cox analyses determined 17 immune genes (ADAMTS8, IFNG, XG, APOA5, SIAH2, C2CD2, STAR, CAMP, CDH19, NTSR1, PCDHA1, AMELX, FREM1, CLEC10A, CD1B, CD6, and LTA) as prognostic biomarkers for BC. A prognostic nomogram was constructed on these prognostic genes. Concordance indexes were 0.782, 0.734, and 0.735 for 1-, 3-, and 5- year DFS. The DFS in high-risk group was significantly worse than that in low-risk group. Artificial intelligence survival prediction system provided three individual mortality risk predictive curves based on three artificial intelligence algorithms. In conclusion, comprehensive bioinformatics identified 17 immune genes as potential prognostic biomarkers, which might be potential candidates of immunotherapy targets in BC patients. The current study depicted regulatory network between transcription factors and immune genes, which was helpful to deepen the understanding of immune regulatory mechanisms for BC cancer. Two artificial intelligence survival predictive systems are available at https://zhangzhiqiao7.shinyapps.io/Smart_Cancer_Survival_Predictive_System_16_BC_C1005/ and https://zhangzhiqiao8.shinyapps.io/Gene_Survival_Subgroup_Analysis_16_BC_C1005/. These novel artificial intelligence survival predictive systems will be helpful to improve individualized treatment decision-making.
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