Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan, Jiangsu, 215316, China.
Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China.
Comput Biol Med. 2022 Oct;149:105988. doi: 10.1016/j.compbiomed.2022.105988. Epub 2022 Aug 20.
Cuproptosis, the mechanism of copper-dependent cell death, is distinct from all other known forms of regulated cell death and dependents on mitochondrial respiration. Cuproptosis promises to be a novel treatment, especially for tumors resistant to conventional therapies. We investigated the changes in cuproptosis-related genes (CRGs) in endometrial cancer (EC) cohorts from the merged Gene Expression Omnibus and the Cancer Genome Atlas databases, which could be divided into three distinct CRGclusters. Patients in CRGcluster C would have higher survival probability (P = 0.007), and higher levels of tumor microenvironment (TME) cell infiltration than other CRGclusters. CRG score was calculated via the results of univariate, multivariate cox analysis and least absolute shrinkage and selection operator regression analysis. Patients were divided into two risk subgroups according to the median risk score. Low-risk patients exhibited a more favorable prognosis, higher immunogenicity, and greater immunotherapy efficacy. Besides, CRG scores were strongly correlated to copy number variation, immunophenoscore, tumor mutation load, cancer stem cell index, microsatellite instability, and chemosensitivity. The c-index of our model is 0.702, which is higher than other four published model. The results proved that our model can distinguish EC patients with high-risk and low-risk and accurately predict the prognosis of EC patients. It will provide new ideas for clinical prognosis and precise treatments.
铜死亡,一种依赖铜的细胞死亡机制,与所有其他已知的调控细胞死亡形式不同,依赖于线粒体呼吸。铜死亡有望成为一种新的治疗方法,特别是对于对传统疗法有抗药性的肿瘤。我们研究了合并基因表达综合数据库和癌症基因组图谱数据库中子宫内膜癌(EC)队列中与铜死亡相关的基因(CRGs)的变化,这些基因可以分为三个不同的 CRG 簇。CRGcluster C 的患者具有更高的生存概率(P = 0.007),并且肿瘤微环境(TME)细胞浸润水平也高于其他 CRG 簇。通过单变量、多变量 cox 分析和最小绝对收缩和选择算子回归分析的结果计算 CRG 评分。根据中位数风险评分将患者分为两个风险亚组。低风险患者表现出更有利的预后、更高的免疫原性和更大的免疫治疗效果。此外,CRG 评分与拷贝数变异、免疫表型评分、肿瘤突变负荷、癌症干细胞指数、微卫星不稳定性和化疗敏感性密切相关。我们模型的 C 指数为 0.702,高于其他四个已发表的模型。结果证明,我们的模型可以区分 EC 患者的高风险和低风险,并准确预测 EC 患者的预后。它将为临床预后和精确治疗提供新的思路。