Zhong Like, Zhu Junfeng, Shu Qi, Xu Gaoqi, He Chaoneng, Fang Luo
The Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou, China.
Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, Hangzhou, China.
J Oncol. 2023 Feb 17;2023:5925935. doi: 10.1155/2023/5925935. eCollection 2023.
Cuproptosis, a recently discovered form of cell death, is caused by copper levels exceeding homeostasis thresholds. Although Cu has a potential role in colon adenocarcinoma (COAD), its role in the development of COAD remains unclear.
In this study, 426 patients with COAD were extracted from the Cancer Genome Atlas (TCGA) database. The Pearson correlation algorithm was used to identify cuproptosis-related lncRNAs. Using the univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) was used to select cuproptosis-related lncRNAs associated with COAD overall survival (OS). A risk model was established based on the multivariate Cox regression analysis. A nomogram model was used to evaluate the prognostic signature based on the risk model. Finally, mutational burden and sensitivity analyses of chemotherapy drugs were performed for COAD patients in the low- and high-risk groups.
Ten cuproptosis-related lncRNAs were identified and a novel risk model was constructed. A signature based on ten cuproptosis-related lncRNAs was an independent prognostic predictor for COAD. Mutational burden analysis suggested that patients with high-risk scores had higher mutation frequency and shorter survival.
Constructing a risk model based on the ten cuproptosis-related lncRNAs could accurately predict the prognosis of COAD patients, providing a fresh perspective for future research on COAD.
铜死亡是一种最近发现的细胞死亡形式，由超过稳态阈值的铜水平引起。尽管铜在结肠腺癌（COAD）中具有潜在作用，但其在COAD发生发展中的作用仍不清楚。
在本研究中，从癌症基因组图谱（TCGA）数据库中提取了426例COAD患者。使用Pearson相关算法鉴定与铜死亡相关的长链非编码RNA（lncRNA）。采用单变量Cox回归分析，运用最小绝对收缩和选择算子（LASSO）选择与COAD总生存期（OS）相关的铜死亡相关lncRNA。基于多变量Cox回归分析建立风险模型。使用列线图模型基于风险模型评估预后特征。最后，对低风险和高风险组的COAD患者进行化疗药物的突变负担和敏感性分析。
鉴定出10个与铜死亡相关的lncRNA，并构建了一个新的风险模型。基于10个与铜死亡相关lncRNA的特征是COAD的独立预后预测指标。突变负担分析表明，高风险评分的患者具有更高的突变频率和更短的生存期。
基于10个与铜死亡相关lncRNA构建风险模型可准确预测COAD患者的预后，为未来COAD研究提供新视角。
