Identification of adenylate cyclase 2 methylation in bladder cancer with implications for prognosis and immunosuppressive microenvironment - Yang, Jianfeng; Xu, Jin; Gao, Qian; Wu, Fan; Han, Wei; Yu, Chao; Shi, Youyang; Qiu, Yunhua; Chen, Yuanbiao; Zhou, Xiqiu (Frontiers in Oncology, 2022)
Background: The incidence and mortality of bladder cancer (BCa) are increasing, while the existing diagnostic methods have limitations. Therefore, for early detection and response prediction, it is crucial to improve the prognosis and treatment strategies. However, with existing diagnostic methods, detecting BCa in the early stage is challenging. Hence, novel biomarkers are urgently needed to improve early diagnosis and treatment efficiency. Methods: The gene expression profile and gene methylation profile dataset were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), differentially methylated genes (DMGs), and methylation-regulated differentially expressed genes (MeDEGs) were gradually identified. A cancer genome map was obtained using online gene expression profile interaction analysis, and survival implications were produced using Kaplan-Meier survival analysis. GSEA was employed to predict the marker pathways where DEGs were significantly involved. The study used bisulfite PCR amplification combined with bisulfite amplicon sequencing (BSAS) to screen for methylation analysis of multiple candidate regions of the adenylate cyclase 2 (ADCY2) based on the sequence design of specific gene regions and CpG islands. Results: In this study, DEGs and DMGs with significantly up- or down-regulated expression were selected. The intersection method was used to screen the MeDEGs. The interaction network group in STRING was then visualized using Cytoscape, and the PPI network was constructed to identify the key genes. The key genes were then analyzed using functional enrichment. To compare the relationship between key genes and the prognosis of BCa patients, we further investigated ADCY2 and found that ADCY2 can be a potential clinical biomarker in BCa prognosis and immunotherapy response prediction. In human BCa 5637 and MGH1 cells, we developed and verified the effectiveness of ADCY2 primers using BSAS technology. The findings revealed that the expression of ADCY2 is highly regulated by the methylation of the promoter regions. Conclusion: This study revealed that increased expression of ADCY2 was significantly correlated with increased tumor heterogeneity, predicting worse survival and immunotherapy response in BCa patients.