Abstract
The present study aimed to analyse the relationship between tumour-infiltrating immune cells (TIICs) and the prognosis of bladder cancer (BC). In the present study, an established computational method (CIBERSORT) was used to analyse the gene expression profile of BC from 409 patients to infer the number of infiltrating immune cells among 22 immune cell subsets. The relationship between each cell type and overall survival (OS) was further analysed. Single-sample GSEA and ESTIMATE algorithms were performed to evaluate the composition of immune microenvironment in each immune cluster. A significant difference in immune cell infiltration between BC and bladder tissue was observed. Increased natural killer and CD8(+) T cell infiltration was associated with longer OS, whereas a higher percentage of M0 macrophages among the total immune cells was associated with shorter OS. The number of M0 macrophages increased with increasing BC stage, whereas the percentage of activated memory CD4(+) and CD8(+) T cells decreased. Patients with BC were divided into three subgroups by hierarchical cluster analysis of immune cells, and each cluster was associated with distinct survival and immune characteristics. The data indicated differences in the cellular composition of TIICs in patients with BC. Moreover, these TIICs were shown to be potential drug targets and reliable prognostic indicators.