Gao Mingde, Guo Haifeng, Xu Haifei, Jin Xiaoxia, Liu Yushan, Chen Zhigang, Wang Xiaolin
Department of Urology, Affiliated Tumor Hospital of Nantong University & Nantong Tumor Hospital, Nantong 226300, China.
Department of Pathology, Affiliated Tumor Hospital of Nantong University & Nantong Tumor Hospital, Nantong 226300, China.
Heliyon. 2024 Jun 17;10(12):e33200. doi: 10.1016/j.heliyon.2024.e33200. eCollection 2024 Jun 30.
To enhance therapeutic approaches, we created a distinctive pattern utilizing the cell demise indicator (CDI) to predict the effectiveness of immunotherapy in individuals with bladder carcinoma (BLCA). Hub prognostic CDIs were identified from the TCGA database using differential gene expression and survival analysis, encompassing 763 genes across 13 death modes. The subtype assessment was employed to evaluate the impact of these genes on the prognosis and immunotherapeutic outcomes in patients with BLCA. The LASSO regression method was used to identify significant CDIs, while Cox regression and nomogram analyses were conducted to explore the impact of CDIs on prognosis. CHMP4C and GSDMB were selected as the hub genes for the following research. Subsequently, These two central genes underwent further investigation to explore their association with immunotherapy, followed by an analysis of their potential regulatory network. Subtype analysis showed that these CDIs were significantly associated with the prognosis and immunotherapy of BLCA patients. The regulatory network in BLCA was evaluated through the establishment of the lncRNA XIST/NEAT1-CDIs-miR-146a-5p/miR-429 axis. Immunohistochemical analysis revealed a significant up-regulation of CHMP4C in bladder cancer tissues, which was strongly associated with an unfavorable prognosis for BLCA patients. Moreover, our findings provide compelling evidence that CHMP4C plays a pivotal role in promoting BLCA progression through the activation of the epithelial-mesenchymal transition (EMT) pathway. These findings highlight the negative impact of CHMP4C on BLCA patient prognosis, while also providing insights into the oncogenic mechanisms and immunotherapy in which CHMP4C may be involved.
为了加强治疗方法,我们创建了一种独特的模式,利用细胞死亡指标(CDI)来预测膀胱癌(BLCA)患者免疫治疗的效果。使用差异基因表达和生存分析从TCGA数据库中鉴定出核心预后CDI,涵盖13种死亡模式的763个基因。采用亚型评估来评估这些基因对BLCA患者预后和免疫治疗结果的影响。使用LASSO回归方法鉴定显著的CDI,同时进行Cox回归和列线图分析以探讨CDI对预后的影响。选择CHMP4C和GSDMB作为后续研究的核心基因。随后,对这两个核心基因进行进一步研究,以探索它们与免疫治疗的关联,接着分析它们潜在的调控网络。亚型分析表明,这些CDI与BLCA患者的预后和免疫治疗显著相关。通过建立lncRNA XIST/NEAT1-CDIs-miR-146a-5p/miR-429轴评估BLCA中的调控网络。免疫组织化学分析显示,膀胱癌组织中CHMP4C显著上调,这与BLCA患者的不良预后密切相关。此外,我们的研究结果提供了有力证据,表明CHMP4C通过激活上皮-间质转化(EMT)途径在促进BLCA进展中起关键作用。这些发现突出了CHMP4C对BLCA患者预后的负面影响,同时也为CHMP4C可能参与的致癌机制和免疫治疗提供了见解。