Abstract
Due to the strong heterogeneity of bladder cancer (BC), there is often substantial variation in the prognosis and efficiency of immunotherapy among BC patients. For the precision treatment and assessment of prognosis, the subtyping of BC plays a critical role. Despite various subtyping methods proposed previously, most of them are based on a limited number of molecules, and none of them is developed on the basis of cell states. In this study, we construct a single-cell atlas by integrating single cell RNA-seq, RNA microarray, and bulk RNA-seq data to identify the absolute proportion of 22 different cell states in BC, including immune and nonimmune cell states derived from tumor tissues. To explore the heterogeneity of BC, BC was identified into four different subtypes in multiple cohorts using an improved consensus clustering algorithm based on cell states. Among the four subtypes, C1 had median prognosis and best overall response rate (ORR), which characterized an immunosuppressive tumor microenvironment. C2 was enriched in epithelial-mesenchymal transition/invasion, angiogenesis, immunosuppression, and immune exhaustion. Surely, C2 performed the worst in prognosis and ORR. C3 with worse ORR than C2 was enriched in angiogenesis and almost nonimmune exhaustion. Displaying an immune effective environment, C4 performed the best in prognosis and ORR. We found that patients with just an immunosuppressive environment are suitable for immunotherapy, but patients with an immunosuppressive environment accompanied by immune exhaustion or angiogenesis may resist immunotherapy. Furthermore, we conducted exploration into the heterogeneity of the transcriptome, mutational profiles, and somatic copy-number alterations in four subtypes, which could explain the significant differences related to cell states in prognosis and ORR. We also found that PD-1 in immune and tumor cells could both influence ORR in BC. The level of TGFβ in a cell state can be opposite to the overall level in the tissues, and the level in a specific cell state could predict ORR more accurately. Thus, our work furthers the understanding of heterogeneity and immunotherapy resistance in BC, which is expected to assist clinical practice and serve as a supplement to the current subtyping method from a novel perspective of cell states.