Abstract

The molecular classification of muscle-invasive bladder cancer (MIBC) based on transcriptomic signatures has been extensively studied. The complementary nature of information provided by different molecular profiles motivated us to refine MIBC classification by aggregating multi-omics data. We generated a consensus ensemble through ten multi-omics integrative clustering approaches on 396 MIBCs from TCGA. A total of 701 MIBCs from different sequencing technologies were used for external validation. Associations between subtypes and prognosis, molecular profiles, the tumour microenvironment, and potential response to frontline therapies were further analyzed. Nearest template prediction and random forest classification were used to develop a predictive signature/classifier for MIBC refinement. We identified four integrative consensus subtypes of MIBC, which were further designated basal-inflamed, basal-noninflamed, luminal-excluded and luminal-desert by immune profiling. Of note, the refinement of basal-like MIBC classification adds to the literature by identifying a basal-noninflamed MIBC subtype presenting with a significantly poor outcome and a global immune-cold phenotype, which might be triggered by Chr4 deletion and high activation of the oncogenic NRF2 pathway. In contrast, basal-inflamed MIBC showed high immunocyte infiltration and high expression of potential targets for immunotherapy. Using an external metastatic MIBC cohort in which patients received anti-PD-L1 treatment, we suggested that basal-inflamed MIBC had a higher likelihood of responding to immunotherapy than other MIBCs. The R package "refineMIBC" was offered as a research tool to refine MIBC from a single-sample perspective (https://github.com/xlucpu/refineMIBC). This consensus ensemble refines the intrinsic MIBC subtypes, which provides a blueprint for the clinical development of rational targeted and immunotherapeutic strategies.