ArticleFrontiers in immunology2024
Development and validation of a glycolysis-associated gene signature for predicting the prognosis, immune landscape, and drug sensitivity in bladder cancer.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Prognostic and immunological implications of a mitophagy-associated gene signature in bladder cancer.Translational andrology and urology · 2026Article
- Immune checkpoint inhibitors in bladder cancer: from mechanistic insights to emerging combination frontlines.Clinical and experimental medicine · 2026Review
- Aerobic glycolysis in bladder cancer: research advances and targeted therapy potential.Frontiers in oncology · 2026Review
- Comprehensive Exploration of NOTCH2NLA Across Cancers and Its Potential Roles in Prognosis and Immune System Interactions.Current medicinal chemistry · 2026Article
- Machine learning-based signature for prognosis and drug sensitivity in hepatocellular carcinoma using glycolysis-related gene.Oncology letters · 2026Article
- Review
- Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer.Biology direct · 2025Article
- ADME gene-driven prognostic model for bladder cancer: a breakthrough in predicting survival and personalized treatment.Hereditas · 2025Article
- Gene signature for response prediction to immunotherapy and prognostic markers in metastatic urothelial carcinoma.Frontiers in immunology · 2025Article
- Serum pyruvate and lactate predict immunotherapy efficacy in advanced gastric cancer: a prospective biomarker study.Frontiers in immunology · 2025Observational
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Abstract
Background: Bladder cancer (BCa) is one of the most common malignancies worldwide, and its prognostication and treatment remains challenging. The fast growth of various cancer cells requires reprogramming of its energy metabolism using aerobic glycolysis as a major energy source. However, the prognostic and therapeutic value of glycolysis-related genes in BCa remains to be determined. Methods: The fused merge dateset from TCGA, GSE13507 and GSE31684 were used for the analysis of glycolysis-related genes expression or subtyping; and corresponding clinical data of these BCa patients were also collected. In the merge cohort, we constructed a 18 multigene signature using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The four external cohorts (i.e., IMvigor210, GSE32894, GSE48276 and GSE48075) of BCa patients were used to validate the accuracy. We evaluated immune infiltration using seven published algorithms: CIBERSORT, QUANTISEQ, XCELL, TIMER, CIBERSORT-ABS, EPIC, and MCPCOUNTER. Subsequently, in order to analyze the correlation between risk groups(scores) and overall survival, recognised immunoregolatory cells or common chemotherapeutic agents, clinicopathological data and immune checkpoint-related genes of BCa patients, Wilcox rank test, chi-square test, cox regression and spearman's correlation were performed. Results: Conspicuously, we could see that CD8+ T, cancer associated fibroblast, macrophage M2, NK, endothelial cells and so on were significantly dysregulated between the two risk groups. In addition, compared with the low-risk group, high-risk group predicted poor prognosis and relatively weak sensitivity of chemotherapy. Additionally, we also found that the expression level of partial genes in the model was significantly correlated with objective responses to anti-PD-1 or anti-PD-L1 treatment in the IMvigor210, GSE111636, GSE176307, GSE78220 or GSE67501 cohort; and its expression level was also varied in different objective response cases receiving tislelizumab combined with low-dose nab-paclitaxel therapy based on our mRNA sequencing (TRUCE-01). According to "GSEA" algorithm of R package "clusterProfiler", the most significantly enriched HALLMARK, KEGG pathway and GO term was separately the 'Epithelial Mesenchymal Transition', 'Ecm Receptor Interaction' and 'MF_Extracellular_matrix_structural_constitunet' in the high- vs. low-risk group. Subsequently, we verified the protein and mRNA expression of interested model-related genes from the Human Protein Atlas (HPA) and 10 paired BCa tissues collected by us. Furthermore, Conclusion: In summary, the glycolysis-associated gene signature established by us exhibited a high predictive performance for the prognosis, immunotherapeutic responsiveness, and chemotherapeutic sensitivity of BCa. And, The model also might function as a chemotherapy and immune checkpoint inhibitor (ICI) treatment guidance.
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