ACSM6 overexpression indicates a non-inflammatory tumor microenvironment and predicts treatment response in bladder cancer: results from multiple real-world cohorts.

Background: ACSMs play critical roles in lipid metabolism; however, their immunological function within the tumor microenvironment (TME) remains unclear, especially that of ACSM6. In this study, we investigate the latent effect of ACSM6 on bladder cancer (BLCA). Methods: Several real-world cohorts, including the Xiangya (in-house), The Cancer Genome Atlas (TCGA-BLCA), and IMvigor210 cohorts, with TCGA-BLCA cohort serving as the discovery cohort were compared. We investigated the potential immunological effects of ACSM6 in regulating the BLCA tumor microenvironment by analyzing its correlation with immunomodulators, anti-cancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, we assessed the precision of ACSM6 in predicting BLCA molecular subtypes and responses to several treatments using ROC analysis. To ensure the robustness of our findings, all results were confirmed in two independent external cohorts: the IMvigor210 and Xiangya cohorts. Results: ACSM6 expression was markedly upregulated in BLCA. Our analysis suggests that ACSM6 might have significant impact to promote the formation of a non-inflamed tumor microenvironment because of its negative correlation with immunomodulators, anticancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, high ACSM6 expression levels in BLCA may predict the luminal subtype, which is typically associated with resistance to chemotherapy, neoadjuvant chemotherapy, and radiotherapy. These findings were consistent across both the IMvigor210 and Xiangya cohorts. Conclusion: ACSM6 has the potential to serve as a valuable predictor of the tumor microenvironment phenotypes and treatment outcomes in BLCA, thereby contributing to more precise treatment.

A novel platelet risk score for stratifing the tumor immunophenotypes, treatment responses and prognosis in bladder carcinoma: results from real-world cohorts.

Background: Although the durable efficacy of immune checkpoint inhibitors (ICIs) in BLCA has been confirmed in numerous studies, not all patients benefit from their application in the clinic. Platelets are increasingly being found to be closely associated with cancer progression and metastasis; however, their comprehensive role in BLCA remains unclear. Methods: We comprehensively explored platelet expression patterns in BLCA patients using an integrated set of 244 related genes. Correlations between these platelet patterns with tumor microenvironment (TME) subtypes, immune characteristics and immunotherapy efficacies were explored. In addition, a platelet risk score (PRS) was generated for individual prognosis and verified the ability to predict prognosis, precise TME phenotypes, and immunotherapy efficacies. Results: Genes were clustered into two patterns that represented different TME phenotypes and had the ability to predict immunotherapy efficacy. We constructed a PRS that could predict individual prognosis with satisfactory accuracy using TCGA-BLCA. The results remained consistent when PRS was validated in the GSE32894 and Xiangya cohort. Moreover, we found that our PRS was positively related to tumor-infiltrating lymphocytes (TILs) in the TCGA-BLCA and Xiangya cohort. As expected, patients with higher PRS exhibited more sensitive to immunotherapy than patients with lower PRS. Finally, we discovered that a high PRS indicated a basal subtype of BLCA, whereas a low PRS indicated a luminal subtype. Conclusion: Platelet-related genes could predict TME phenotypes in BLCA. We constructed a PRS that could predict the TME, prognosis, immunotherapy efficacy, and molecular subtypes in BLCA.

ACER2 forms a cold tumor microenvironment and predicts the molecular subtype in bladder cancer: Results from real-world cohorts.

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.

GATA3 Predicts the Tumor Microenvironment Phenotypes and Molecular Subtypes for Bladder Carcinoma.

Aims: GATA3 is a key player in antitumor immunology, and continuous studies show that it might be a key biomarker for bladder cancer (BLCA). Thus, we lucubrate the immunological role of GATA3 in BLCA. Main Methods: We initially used pan-cancer analysis to analyze the expression pattern and immunological function of GATA3 with data gathered from the TCGA (The Cancer Genome Atlas). Then, in the BLCA tumor microenvironment (TME), we comprehensively associated GATA3 with immunomodulators, cancer immune cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T-cell inflamed scores(TIS). The role of GATA3 in predicting BLCA molecular subtypes and responsiveness to various treatment regimens was also investigated. We confirmed our findings in an external cohort and the Xiangya-Pingkuang cohort to guarantee the correctness of our study. Key Findings: GATA3 was preferentially expressed in the TME of numerous malignancies, including BLCA. High GATA3 expression was adversely connected with immunological aspects such as immunomodulators, cancer immune cycles, TIICs, immune checkpoints, and TIS in the BLCA TME. In addition, high GATA3 was more likely to be a luminal subtype, which meant it was less susceptible to cancer immunotherapy and neoadjuvant chemotherapy but more sensitive to targeted treatments. Significance: GATA3 may aid in the precision treatment for BLCA because it can accurately predict the clinical outcomes and the TME characteristics of BLCA.

An IFN-γ-related signature predicts prognosis and immunotherapy response in bladder cancer: Results from real-world cohorts.

Bladder cancer (BLCA) is featured with high incidence and mortality. Whether the IFN-γ signaling could be used as an immunotherapy determinant for BLCA has not been fully confirmed. In this study, the transcriptome data and clinical information of BLCA samples were collected from The Cancer Genome Atlas (TCGA). Besides, four immunotherapy cohorts including IMvigor210 cohort, Gide cohort, Van Allen cohort, and Lauss cohort were collected. The Xiangya real-world cohort was used for independent validation. An IFN-γ-related signature was developed and validated in BLCA for predicting prognosis, mutation, tumor microenvironment status, and immunotherapy response. This is the first study focusing on the comprehensive evaluation of predictive values on the IFN-γ-related signature in BLCA. The potential clinical application of the IFN-γ-related signature was expected to be further validated with more prospective clinical cohorts.

A Robust Hypoxia Risk Score Predicts the Clinical Outcomes and Tumor Microenvironment Immune Characters in Bladder Cancer.

Background: Bladder 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. Methods: The 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. Results: Hypoxia 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-ß-catenin network, PPARG network, and FGFR3 network. Conclusions: We 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.

A Novel TGF-ß Risk Score Predicts the Clinical Outcomes and Tumour Microenvironment Phenotypes in Bladder Cancer.

Background: The TGF-ß pathway plays critical roles in numerous malignancies. Nevertheless, its potential role in prognosis prediction and regulating tumour microenvironment (TME) characteristics require further elucidation in bladder cancer (BLCA). Methods: TGF-ß-related genes were comprehensively summarized from several databases. The TCGA-BLCA cohort (training cohort) was downloaded from the Cancer Genome Atlas, and the independent validation cohorts were gathered from Xiangya Hospital (Xinagya cohort) and Gene Expression Omnibus. Initially, we identified differentially expressed TGF-ß genes (DEGs) between cancer and normal tissues. Subsequently, univariate Cox analysis was applied to identify prognostic DEGs, which were further used to develop the TGF-ß risk score by performing LASSO and multivariate Cox analyses. Then, we studied the role of the TGF-ß risk score in predicting prognosis and the TME phenotypes. In addition, the role of the TGF-ß risk score in guiding precision treatments for BLCA has also been assessed. Results: We successfully constructed a TGF-ß risk score with an independent prognostic prediction value. A high TGF-ß risk score indicated an inflamed TME, which was supported by the positive relationships between the risk score, enrichment scores of anticancer immunity steps, and the infiltration levels of tumour-infiltrating immune cells. In addition, the risk score positively correlated with the expression of several immune checkpoints and the T cell inflamed score. Consistently, the risk score was positively related to the enrichment scores of most immunotherapy-positive pathways. In addition, the sensitivities of six common chemotherapeutic drugs were positively associated with the risk score. Furthermore, higher risk score indicated higher sensitivity to radiotherapy and EGFR-targeted therapy. On the contrary, patients with low-risk scores were more sensitive to targeted therapies, including the blockade of FGFR3 and WNT-ß-catenin networks. Conclusions: We first constructed and validated a TGF-ß signature that could predict the prognosis and TME phenotypes for BLCA. More importantly, the TGF-ß risk score could aid in individual precision treatment for BLCA.