Zhang Changzheng, Zeng Jiayi, Ye Chujin, Tian Kaiwen, Xian Zhiyong
Department of Urology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Department of Urology, Guangdong Provincial People's Hospital's Nanhai Hospital, Foshan, China.
Transl Cancer Res. 2024 Jan 31;13(1):150-172. doi: 10.21037/tcr-23-1383. Epub 2024 Jan 15.
Epigenetic alterations driven by chromatin regulators (CRs) are well-recognized cancer hallmarks. Growing evidence suggests that the imbalance of CRs may lead to the occurrence of various diseases including tumors. However, the role and prognostic value of CRs in clear cell renal cell carcinoma (ccRCC) remain undefined.
Consensus clustering analysis was used to identify different subtypes. Univariate and multivariate Cox regression analysis were performed to identify prognosis-related CRs and constructed a risk model. Transcriptome sequencing was used to verify gene expression levels. Kaplan-Meier survival analysis was used to compare overall survival (OS) between high- and low-risk groups. The area under the curve (AUC) value of the receiver operating characteristic (ROC) curve was used to evaluate the performance of the model. The ESTIMATE algorithm and single-sample gene set enrichment analysis (ssGSEA) were executed to evaluate the immune characteristics of samples. Correlation analysis was used to assess the relationship between risk score and immune checkpoint genes, the relationship between expression levels of CRs and immune cell infiltration and drug therapeutic response. Finally, we also compared differences in drug sensitivity between low- and high-risk groups.
We identified three CRs-related subtypes with different characteristics. A prognostic model was built with four CRs and can precisely predict the OS of patients in different risk groups. The model has good stability and applicability and was further verified in the internal and external dataset. The transcriptomic levels of the four CRs were also validated, and the risk score was an independent prognostic factor for ccRCC. Obvious differences in the immune microenvironment and the expression levels of immune checkpoints were observed in low- and high-risk group. Higher immune activity and immune cell infiltration were found in the high-risk group. Besides, the expression levels of CRs were associated with drug therapeutic response. Patients with high-risk score may be more sensitive to gemcitabine, vinblastine, paclitaxel, axitinib, sunitinib, and temsirolimus.
CRs were strongly associated with the occurrence and development of ccRCC. Targeting CRs may become a new therapeutic strategy for ccRCC. Besides, CRs-related gene signature can predict the prognosis and therapeutic significance of ccRCC, which provides an important reference for clinical decision-making.
由染色质调节因子（CRs）驱动的表观遗传改变是公认的癌症标志。越来越多的证据表明，CRs的失衡可能导致包括肿瘤在内的各种疾病的发生。然而，CRs在透明细胞肾细胞癌（ccRCC）中的作用和预后价值仍不明确。
采用一致性聚类分析来识别不同亚型。进行单因素和多因素Cox回归分析以识别与预后相关的CRs并构建风险模型。利用转录组测序验证基因表达水平。采用Kaplan-Meier生存分析比较高风险组和低风险组的总生存期（OS）。用受试者工作特征（ROC）曲线的曲线下面积（AUC）值评估模型的性能。执行ESTIMATE算法和单样本基因集富集分析（ssGSEA）以评估样本的免疫特征。采用相关性分析评估风险评分与免疫检查点基因之间的关系、CRs表达水平与免疫细胞浸润及药物治疗反应之间的关系。最后，我们还比较了低风险组和高风险组之间的药物敏感性差异。
我们识别出三种具有不同特征的CRs相关亚型。用四个CRs构建了一个预后模型，该模型可以精确预测不同风险组患者的OS。该模型具有良好的稳定性和适用性，并在内部和外部数据集中得到进一步验证。四个CRs的转录组水平也得到了验证，风险评分是ccRCC的独立预后因素。在低风险组和高风险组中观察到免疫微环境和免疫检查点表达水平存在明显差异。高风险组具有更高的免疫活性和免疫细胞浸润。此外，CRs的表达水平与药物治疗反应相关。高风险评分的患者可能对吉西他滨、长春碱、紫杉醇、阿昔替尼、舒尼替尼和替西罗莫司更敏感。
CRs与ccRCC的发生和发展密切相关。靶向CRs可能成为ccRCC的一种新的治疗策略。此外，CRs相关基因特征可以预测ccRCC的预后和治疗意义，为临床决策提供重要参考。
