Development and validation of a glycolysis-associated gene signature for predicting the prognosis, immune landscape, and drug sensitivity in bladder cancer

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. 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. 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 Huma