Mapping the tumor microenvironment in bladder cancer and exploring the prognostic genes by single-cell RNA sequencing

Abstract

Despite substantial advances in the treatment using immune checkpoint inhibitors (ICIs), the clinical expected therapeutic effect on bladder cancer has not been achieved, in which the tumor microenvironment (TME) occupies a notable position. In this research, 10X single-cell RNA-sequencing technology was conducted to analyze seven primary bladder tumor tissues (three non-muscle-invasive bladder cancer (NMIBC) and four muscle-invasive bladder cancer (MIBC)) and seven corresponding normal tissues adjacent to cancer; eight various cell types were identified in the bladder cancer (BC) TME, and a complete TME atlas in bladder cancer was made. Moreover, bladder cancer epithelial cells were further subdivided into 14 subgroups, indicating a high intra-tumoral heterogeneity. Additionally, the differences between NMIBC and MIBC were compared based on differential gene expression heatmap, copy number variation (CNV) distribution heatmap, Gene Ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Weighted gene co-expression network analysis (WGCNA), protein–protein interaction (PPI) network mutual analysis, and the Kaplan–Meier survival prognosis analysis were used to identify six key genes associated with the prognosis of bladder cancer: VEGFA, ANXA1, HSP90B1, PSMA7, PRDX6, and PPP1CB. The dynamic change of the expression distribution of six genes on the pseudo-time axis was further verified by cell pseudo-time analysis.