ArticleJournal of translational medicine2021
Establishment of a novel glycolysis-related prognostic gene signature for ovarian cancer and its relationships with immune infiltration of the tumor microenvironment.
Article in Journal of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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35 citing papers in PubMed.
- Outcome-Adaptive Lasso for Cox Proportional Hazards Model.Biometrical journal. Biometrische Zeitschrift · 2026Article
- Comprehensive analysis and validation of the prognostic value of glycosylation- and mitophagy-related genes for head and neck squamous cell carcinoma.Translational cancer research · 2026Article
- A bioinformatics approach to identify potential biomarkers of high-grade ovarian cancer.Journal of the Turkish German Gynecological Association · 2026Article
- Identification of glycolysis -correlative features for predicting prognosis and investigating immune landscape in prostate cancer.BMC cancer · 2026Article
- A diagnostic model of atherosclerosis based on the oxidative stress-glycolysis co-regulatory network.Molecular and cellular biochemistry · 2026Article
- Identification of a Novel Pyroptosis-Related lncRNAs Prognosis Model and Subtypes in Ovarian Cancer.Phenomics (Cham, Switzerland) · 2025Article
- Development of macrophage M2 relate signature for predicting prognosis and immunotherapy response in ovarian cancer.Discover oncology · 2025Article
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- Development of a Multilayered Prognostic Model for Wilms' Tumor Based on Characteristic Lymphocyte Genes.Genetics research · 2025Article
- Pharmacological Mechanism of Mume Fructus in the Treatment of Triple-Negative Breast Cancer Based on Network Pharmacology.Applied biochemistry and biotechnology · 2024Article
- TCEB2/HIF1A signaling axis promotes chemoresistance in ovarian cancer cells by enhancing glycolysis and angiogenesis.European journal of medical research · 2024Article
- Senescence-Related LncRNAs: Pioneering Indicators for Ovarian Cancer Outcomes.Phenomics (Cham, Switzerland) · 2024Review
- Single-cell transcriptome analysis revealed heterogeneity in glycolysis and identified IGF2 as a therapeutic target for ovarian cancer subtypes.BMC cancer · 2024Article
- Establishment of an ovarian cancer exhausted CD8+T cells-related genes model by integrated analysis of scRNA-seq and bulk RNA-seq.European journal of medical research · 2024Article
- From monocyte-derived macrophages to resident macrophages-how metabolism leads their way in cancer.Molecular oncology · 2024Review
- Astragaloside IV inhibits cell viability and glycolysis of hepatocellular carcinoma by regulating KAT2A-mediated succinylation of PGAM1.BMC cancer · 2024Article
- Article
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- SMAD4 inhibits glycolysis in ovarian cancer through PI3K/AKT/HK2 signaling pathway by activating ARHGAP10.Cancer reports (Hoboken, N.J.) · 2024Article
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Abstract
backgroundGlycolysis affects tumor growth, invasion, chemotherapy resistance, and the tumor microenvironment. In this study, we aimed to construct a glycolysis-related prognostic model for ovarian cancer and analyze its relationship with the tumor microenvironment's immune cell infiltration.
methodsWe obtained six glycolysis-related gene sets for gene set enrichment analysis (GSEA). Ovarian cancer data from The Cancer Genome Atlas (TCGA) database and two Gene Expression Omnibus (GEO) datasets were divided into two groups after removing batch effects. We compared the tumor environments' immune components in high-risk and low-risk groups and analyzed the correlation between glycolysis- and immune-related genes. Then, we generated and validated a predictive model for the prognosis of ovarian cancer using the glycolysis-related genes.
resultsOverall, 27/329 glycolytic genes were associated with survival in ovarian cancer, 8 of which showed predictive value. The tumor cell components in the tumor microenvironment did not differ between the high-risk and low-risk groups; however, the immune score differed significantly between groups. In total, 13/24 immune cell types differed between groups, including 10 T cell types and three other immune cell types. Eight glycolysis-related prognostic genes were related to the expression of multiple immune-related genes at varying degrees, suggesting a relationship between glycolysis and immune response.
conclusionsWe identified eight glycolysis-related prognostic genes that effectively predicted survival in ovarian cancer. To a certain extent, the newly identified gene signature was related to the tumor microenvironment, especially immune cell infiltration and immune-related gene expression. These findings provide potential biomarkers and therapeutic targets for ovarian cancer.
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