Yang Jianfeng, Xu Jin, Gao Qian, Wu Fan, Han Wei, Yu Chao, Shi Youyang, Qiu Yunhua, Chen Yuanbiao, Zhou Xiqiu
Department of Surgery, Shangnan Branch of Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Institute of Regenerative Biology and Medicine, Helmholtz Zentrum München, Munich, Germany.
Front Oncol. 2022 Oct 14;12:1025195. doi: 10.3389/fonc.2022.1025195. eCollection 2022.
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.
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.
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.
This study revealed that increased expression of ADCY2 was significantly correlated with increased tumor heterogeneity, predicting worse survival and immunotherapy response in BCa patients.
膀胱癌(BCa)的发病率和死亡率正在上升,而现有的诊断方法存在局限性。因此,为了早期检测和反应预测,改善预后和治疗策略至关重要。然而,使用现有的诊断方法,在早期阶段检测BCa具有挑战性。因此,迫切需要新的生物标志物来提高早期诊断和治疗效率。
从基因表达综合数据库(GEO)下载基因表达谱和基因甲基化谱数据集。逐步鉴定差异表达基因(DEGs)、差异甲基化基因(DMGs)和甲基化调节的差异表达基因(MeDEGs)。使用在线基因表达谱相互作用分析获得癌症基因组图谱,并使用Kaplan-Meier生存分析得出生存意义。采用基因集富集分析(GSEA)预测DEGs显著参与的标记途径。该研究基于特定基因区域和CpG岛的序列设计,使用亚硫酸氢盐PCR扩增结合亚硫酸氢盐扩增子测序(BSAS)来筛选腺苷酸环化酶2(ADCY2)多个候选区域的甲基化分析。
在本研究中选择了表达显著上调或下调的DEGs和DMGs。采用交集法筛选MeDEGs。然后使用Cytoscape可视化STRING中的相互作用网络组,并构建蛋白质-蛋白质相互作用(PPI)网络以识别关键基因。然后对关键基因进行功能富集分析。为了比较关键基因与BCa患者预后的关系,我们进一步研究了ADCY2,发现ADCY2可能是BCa预后和免疫治疗反应预测中的潜在临床生物标志物。在人BCa 5637和MGH1细胞中,我们使用BSAS技术开发并验证了ADCY2引物的有效性。研究结果表明,ADCY2的表达受启动子区域甲基化的高度调控。
本研究表明,ADCY2表达增加与肿瘤异质性增加显著相关,预测BCa患者的生存和免疫治疗反应较差。