Bladder cancer (BLCA) is a heterogeneous disease, and there are many classical molecular subtypes that reflect tumor immune microenvironment (TME) heterogeneity but their clinical utility is limited and correct individual treatment and prognosis cannot be predicted based on them. To find reliable and effective biomarkers and tools for predicting patients’ clinical responses to several therapies, we developed a new systemic indicator of molecular vasculogenic mimicry (VM)–related genes mediated by molecular subtypes based on the Xiangya cohort and additional external BLCA cohorts using a random forest algorithm. A correlation was then done between the VM_Score and classical molecular subtypes, clinical outcomes, immunophenotypes, and treatment options for BLCA. With the VM_Score, it is possible to predict classical molecular subtypes, immunophenotypes, prognosis, and therapeutic potential of BLCA with high accuracy. The VM_Scores of high levels indicate a more anticancer immune response but a worse prognosis due to a more basal and inflammatory phenotype. The VM_Score was also found associated with low sensitivity to antiangiogenic and targeted therapies targeting the FGFR3, β-catenin, and PPAR-γ pathways but with high sensitivity to cancer immunotherapy, neoadjuvant chemotherapy, and radiotherapy. A number of aspects of BLCA biology were reflected in the VM_Score, providing new insights into precision medicine. Additionally, the VM_Score may be used as an indicator of pan-cancer immunotherapy response and prognosis.

The gut microbiota is a large symbiotic community of anaerobic and facultative aerobic bacteria inhabiting the human intestinal tract, and its activities significantly affect human health. Increasing evidence has suggested that the gut microbiome plays an important role in tumor-related immune regulation. In the tumor microenvironment (TME), the gut microbiome and its metabolites affect the differentiation and function of immune cells regulating the immune evasion of tumors. The gut microbiome can indirectly influence individual responses to various classical tumor immunotherapies, including immune checkpoint inhibitor therapy and adoptive immunotherapy. Microbial regulation through antibiotics, prebiotics, and fecal microbiota transplantation (FMT) optimize the composition of the gut microbiome, improving the efficacy of immunotherapy and bringing a new perspective and hope for tumor treatment.

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Background: ACER2 is a critical gene regulating cancer cell growth and migration, whereas the immunological role of ACER2 in the tumor microenvironment (TME) is scarcely reported. Thus, we lucubrate the potential performance of ACER2 in bladder cancer (BLCA).Methods: We initially compared ACER2 expressions in BLCA with normal urothelium tissues based on data gathered from the Cancer Genome Atlas (TCGA) and our Xiangya cohort. Subsequently, we systematically explored correlations between ACER2 with immunomodulators, anti-cancer immune cycles, tumor-infiltrating immune cells, immune checkpoints and the T-cell inflamed score (TIS) to further confirm its immunological role in BLCA TME. In addition, we performed ROC analysis to illustrate the accuracy of ACER2 in predicting BLCA molecular subtypes and explored the response to several cancer-related treatments. Finally, we validated results in an immunotherapy cohort and Xiangya cohort to ensure the stability of our study.Results: Compared with normal urinary epithelium, ACER2 was significantly overexpressed in several cell lines and the tumor tissue of BLCA. ACER2 can contribute to the formation of non-inflamed BLCA TME supported by its negative correlations with immunomodulators, anti-cancer immune cycles, tumor-infiltrating immune cells, immune checkpoints and the TIS. Moreover, BLCA patients with high ACER2 expression were inclined to the luminal subtype, which were characterized by insensitivity to neoadjuvant chemotherapy, chemotherapy and radiotherapy but not to immunotherapy. Results in the IMvigor210 and Xiangya cohort were consistent.Conclusion: ACER2 could accurately predict the TME and clinical outcomes for BLCA. It would be served as a promising target for precision treatment in the future.