Rationale: Siglec15 is an emerging target for normalization cancer immunotherapy. However, pan-cancer anti-Siglec15 treatment is not yet validated and the potential role of Siglec15 in bladder cancer (BLCA) remains elusive. Methods: We comprehensively evaluated the expression pattern and immunological role of Siglec15 using pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas. We then systematically correlated Siglec15 with immunological characteristics in the BLCA tumor microenvironment (TME), including immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T cell inflamed score. We also analyzed the role of Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA. Our results were validated in several public cohorts as well as our BLCA tumor microarray cohort, the Xiangya cohort. We developed an immune risk score (IRS), validated it, and tested its ability to predict the prognosis and response to cancer immunotherapy. Results: We found that Siglec15 was specifically overexpressed in the TME of various cancers. We hypothesize that Siglec15 designs a non-inflamed TME in BLCA based on the evidence that Siglec15 negatively correlated with immunomodulators, TIICs, cancer immunity cycles, immune checkpoints, and T cell inflamed score. Bladder cancer with high Siglec15 expression was not sensitive to cancer immunotherapy, but exhibited a higher incidence of hyperprogression. High Siglec15 levels indicated a luminal subtype of BLCA characterized by lower immune infiltration, lower response to cancer immunotherapy and neoadjuvant chemotherapy, but higher response to anti-angiogenic therapy and targeted therapies such as blocking Siglec15, β-catenin, PPAR-γ, and FGFR3 pathways. Notably, a combination of anti-Siglec15 and cancer immunotherapy may be a more effective strategy than monotherapy. IRS can accurately predict the prognosis and response to cancer immunotherapy. Conclusions: Anti-Siglec15 immunotherapy might be suitable for BLCA treatment as Siglec15 correlates with a non-inflamed TME in BLCA. Siglec15 could also predict the molecular subtype and the response to several treatment options.

Background Depicting the heterogeneity and functional characteristics of the tumor microenvironment (TME) is necessary to achieve precision medicine for bladder cancer (BLCA). Although classical molecular subtypes effectively reflect TME heterogeneity and characteristics, their clinical application is limited by several issues. Methods In this study, we integrated the Xiangya cohort and multiple external BLCA cohorts to develop a novel 5-methylcytosine (5mC) regulator-mediated molecular subtype system and a corresponding quantitative indicator, the 5mC score. Unsupervised clustering was performed to identify novel 5mC regulator-mediated molecular subtypes. The principal component analysis was applied to calculate the 5mC score. Then, we correlated the 5mC clusters (5mC score) with classical molecular subtypes, immunophenotypes, clinical outcomes, and therapeutic opportunities in BLCA. Finally, we performed pancancer analyses on the 5mC score. Results Two 5mC clusters, including 5mC cluster 1 and cluster 2, were identified. These novel 5mC clusters (5mC score) could accurately predict classical molecular subtypes, immunophenotypes, prognosis, and therapeutic opportunities of BLCA. 5mC cluster 1 (high 5mC score) indicated a luminal subtype and noninflamed phenotype, characterized by lower anticancer immunity but better prognosis. Moreover, 5mC cluster 1 (high 5mC score) predicted low sensitivity to cancer immunotherapy, neoadjuvant chemotherapy, and radiotherapy, but high sensitivity to antiangiogenic therapy and targeted therapies, such as blocking the β-catenin, FGFR3, and PPAR-γ pathways. Conclusions The novel 5mC regulator-based subtype system reflects many aspects of BLCA biology and provides new insights into precision medicine in BLCA. Furthermore, the 5mC score may be a generalizable predictor of immunotherapy response and prognosis in pancancers.

BackgroundBladder cancer (BLCA) is one of the most common urinary malignancies with poor prognosis. There is an unmet need to develop novel robust tools to predict prognosis and treatment efficacy for BLCA.MethodsThe hypoxia-related genes were collected from the Molecular Signatures Database. The TCGA-BLCA cohort was downloaded from the Cancer Genome Atlas and then was randomly divided into training and internal validation sets. Two external validation cohorts were gathered from Gene Expression Omnibus. Also, another independent validation cohort (Xiangya cohort) was collected from our hospital. The Cox regression model with the LASSO algorithm was applied to develop the hypoxia risk score. Then, we correlated the hypoxia risk score with the clinical outcomes, the tumor microenvironment (TME) immune characteristics, and the efficacy prediction for several treatments, which included cancer immunotherapy, chemotherapy, radiotherapy, and targeted therapies.ResultsHypoxia risk score was an independent prognostic factor. A high-risk score indicated an inflamed TME based on the evidence that hypoxia risk score positively correlated with the activities of several cancer immunity cycles and the infiltration levels of many tumor-infiltrating immune cells, such as CD8 + T cells, Dendritic cells, and NK cells. Consistently, the hypoxia risk score was positively related to the expression of several immune checkpoints, such as PD-L1, PD-1, CTLA-4, and LAG-3, as well as the T cell inflamed score. Furthermore, the hypoxia risk score positively correlated with the enrichment scores of most immunotherapy-positive gene signatures. Therefore, patients with higher risk score may be more sensitive to cancer immunotherapy. Meanwhile, the hypoxia risk score was positively related to the sensitivities of several chemotherapeutic drugs, including Cisplatin, Docetaxel, Paclitaxel, Bleomycin, Camptothecin, and Vinblastine. Similarly, the enrichment scores for radiotherapy-predicted pathways and EGFR ligands were higher in the high-risk score group. Conversely, the enrichment scores of several immunosuppressive oncogenic pathways were significantly higher in the low-risk score group, such as the WNT-β-catenin network, PPARG network, and FGFR3 network.ConclusionsWe developed and validated a new hypoxia risk score, which could predict the clinical outcomes and the TME immune characteristics of BLCA. In general, the hypoxia risk score may aid in the precision medicine for BLCA.

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RNA modification of N6-methyladenosine (m6A) plays critical roles in various biological processes, such as cancer development, inflammation, and the anticancer immune response. However, the role played by a comprehensive m6A modification pattern in regulating anticancer immunity in kidney renal clear cell carcinoma (KIRC) has not been fully elucidated. In this study, we identified two independent m6A modification patterns with distinct biological functions, immunological characteristics, and prognoses in KIRC. Next, we developed an m6A score algorithm to quantify an individual's m6A modification pattern, which was independently validated in external cohorts. The m6A cluster 1 and low m6A score groups were characterized by a hot tumor microenvironment with an increased infiltration level of cytotoxic immune cells, higher tumor mutation burden, higher immune checkpoint expression, and decreased stroma-associated signature enrichment. In general, the m6A cluster 1 and low m6A score groups reflected an inflammatory phenotype, which may be more sensitive to anticancer immunotherapy. The m6A cluster 2 and high m6A score groups indicated a non-inflammatory phenotype, which may not be sensitive to immunotherapy but rather to targeted therapy. In this study, we first identified m6A clusters and m6A scores to elucidate immune phenotypes and to predict the prognosis and immunotherapy response in KIRC, which can guide urologists for making more precise clinical decisions.