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Comprehensive pan-cancer single-cell analysis reveals glycolysis-related signatures as predictive biomarkers for immunotherapy response and their role in bladder cancer

Year: 2025
Type: article
Abstract: Glycolysis is a vital metabolic biological process in tumor progression and immune modulation. This study comprehensively investigated the roles of glycolysis in pan-cancer, especially in bladder cancer. Exploration of 34 single-cell RNA sequencing (scRNA-seq) cohorts, eight ICI-treated bulk RNA-seq cohorts, and TCGA bulk pan-cancer RNA-seq cohorts uncovered a Glycolysis.Sig which strongly correlated with immunotherapy response and demonstrated excellent predictive performance in prognosis and immune response. Hub-Glycolysis.Sig exhibited varying interactions with the immune microenvironment based on cancer type. In bladder cancer, higher glycolysis risk scores correlated with poorer prognosis, with distinct immune infiltration characteristics between subtypes. scRNA-seq revealed high glycolysis levels in bladder epithelial cells. COPB2 was highly expressed in bladder cancer, promoting cell proliferation, migration, and glycolytic activity in vitro and in vivo. Our large-scale data analysis confirmed the negative correlation between glycolysis and immunotherapy outcomes, identifying Glycolysis.Sig as a novel predictive biomarker. Hub-Glycolysis.Sig provides clinical insights for bladder cancer therapy strategies, while COPB2 and other potential therapeutic targets facilitate personalized cancer treatment. • Glycolysis.Sig correlated with immunotherapy response and showed predictive performance across pan-cancer datasets. • Hub-Glycolysis.Sig exhibited varying interactions with the immune microenvironment based on cancer type. • In bladder cancer, higher glycolysis risk scores linked to worse prognosis. • Single-cell sequencing showed elevated glycolysis levels in bladder cancer epithelial cells. • COPB2 was overexpressed in bladder cancer, promoting cell proliferation, migration, and glycolysis.
Language: English
Subfield: Oncology
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $3,220
OpenAlex ID: W4408253323
FWCI: 1.438
Cites: 64
Cited by: 4
Related to: 10