ArticleScientific reports2021
Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Proteoglycans in Breast Cancer: Friends and Foes.Biomolecules · 2025Review
- BRCAGenie: A machine learning-driven 43-gene polygenic risk score model for precision prediction of breast cancer survival.Journal of translational medicine · 2025Article
- The Role of the Cell Surface Heparan Sulfate Proteoglycan Syndecan-3 in Breast Cancer Pathophysiology.Cells · 2025Article
- TRanscriptome ANalysis of StratifiEd CohorTs (TRANSECT) enables automated assessment of global gene regulation linked to disparate expression in user defined genes and gene sets.NAR genomics and bioinformatics · 2025Article
- SDC1 is a critical transmembrane proteoglycan in breast cancer.World journal of surgical oncology · 2025Review
- A Glycolysis and gluconeogenesis-related model for breast cancer prognosis.Cancer biomarkers : section A of Disease markers · 2024Article
- Targeting PGK1: A New Frontier in Breast Cancer Therapy Under Hypoxic Conditions.Current issues in molecular biology · 2024Review
- Advances in the understanding of nuclear pore complexes in human diseases.Journal of cancer research and clinical oncology · 2024Review
- Prognostic value of amino acid metabolism-related gene expression in invasive breast carcinoma.Journal of cancer research and clinical oncology · 2023Article
- Revisiting the Syndecans: Master Signaling Regulators with Prognostic and Targetable Therapeutic Values in Breast Carcinoma.Cancers · 2023Review
- Regulation of Adenine Nucleotide Metabolism by Adenylate Kinase Isozymes: Physiological Roles and Diseases.International journal of molecular sciences · 2023Review
- Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model.Scientific reports · 2022Article
- Article
- Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis.Frontiers in genetics · 2022Article
- Effects of Glycolysis-Related Genes on Prognosis and the Tumor Microenvironment of Hepatocellular Carcinoma.Frontiers in pharmacology · 2022Article
- Facts and Perspectives: Implications of tumor glycolysis on immunotherapy response in triple negative breast cancer.Frontiers in oncology · 2022Review
- Increased tumor glycolysis is associated with decreased immune infiltration across human solid tumors.Frontiers in immunology · 2022Article
- Identification of a prognostic risk-scoring model and risk signatures based on glycosylation-associated cluster in breast cancer.Frontiers in genetics · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the most frequently identified tumors and a contributing cause of death in women is breast cancer (BC). Many biomarkers associated with survival and prognosis were identified in previous studies through database mining. Nevertheless, the predictive capabilities of single-gene biomarkers are not accurate enough. Genetic signatures can be an enhanced prediction method. This research analyzed data from The Cancer Genome Atlas (TCGA) for the detection of a new genetic signature to predict BC prognosis. Profiling of mRNA expression was carried out in samples of patients with TCGA BC (n = 1222). Gene set enrichment research has been undertaken to classify gene sets that vary greatly between BC tissues and normal tissues. Cox models for additive hazards regression were used to classify genes that were strongly linked to overall survival. A subsequent Cox regression multivariate analysis was used to construct a predictive risk parameter model. Kaplan-Meier survival predictions and log-rank validation have been used to verify the value of risk prediction parameters. Seven genes (PGK1, CACNA1H, IL13RA1, SDC1, AK3, NUP43, SDC3) correlated with glycolysis were shown to be strongly linked to overall survival. Depending on the 7-gene-signature, 1222 BC patients were classified into subgroups of high/low-risk. Certain variables have not impaired the prognostic potential of the seven-gene signature. A seven-gene signature correlated with cellular glycolysis was developed to predict the survival of BC patients. The results include insight into cellular glycolysis mechanisms and the detection of patients with poor BC prognosis.
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