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Background  SUMOylation is an important component of post-translational protein modifications (PTMs), and bladder cancer (BCa) is the ninth most common cancer around the world. But the comprehensive role of SUMOylation in shaping tumor microenvironment (TME) and influencing tumor clinicopathological features and also the prognosis of patients remains unclear.    Methods  Using the data downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), we comprehensively evaluated the SUMOylation patterns of 570 bladder cancer samples, and systematically correlated these SUMOylation patterns with TME immune cell infiltrating characteristics. The SUMO score was constructed to quantify SUMOylation patterns of individuals using principal component analysis (PCA) algorithms.    Results  Two distinct SUMOylation patterns and gene clusters were finally determined. Significant differences in the prognosis of patients were found among two different SUMOylation patterns and gene clusters, so were in the mRNA transcriptome and the landscape of TME immune cell infiltration. We also established a set of scoring system named SUMO score to quantify the SUMOylation pattern of individuals with BCa, which was discovered to be tightly connected with tumor clinicopathological characteristics and could predict the prognosis of patients with BCa. Moreover, SUMO score was a considerable predictive indicator for the survival outcome independent of tumor mutation burden (TMB) and low SUMO score was related to better response to immunotherapy using PD-1 blockade. We also found that there existed a significant relationship between sensitivity to commonly used chemotherapy drugs and SUMO score. Finally, a nomograph based on five features, namely, SUMO score, age, gender, T category, and M category was constructed to predict the survival probability of patients with BCa in 1, 3, and 5 years, respectively.    Conclusions  Our work demonstrated and overviewed the complicated regulation mechanisms of SUMOylation in bladder cancer, and better understanding and evaluating SUMOylation patterns could be helpful in guiding clinical therapeutic strategy and improving the prognosis of patients with BCa.

SUMOylation Pattern Predicts Prognosis and Indicates Tumor Microenvironment Infiltration Characterization in Bladder Cancer