| 孟凡伟,宗 丹,葛宜枝,等.基于转录组数据食管癌铜死亡相关基因筛选及预后模型的构建[J].肿瘤学杂志,2023,29(7):592-605. |
| 基于转录组数据食管癌铜死亡相关基因筛选及预后模型的构建 |
| Screening of Cuproptososis-Related Genes and Construction of A Prognosis Risk Model for Esophageal Carcinoma Based on Transcriptome Data |
| 投稿时间：2023-03-01 |
| DOI：10.11735/j.issn.1671-170X.2023.07.B008 |
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| 中文关键词: 铜死亡 基因 食管癌 预后 生物信息学 |
| 英文关键词:cuproptososis gene esophageal carcinoma prognosis bioinformatics |
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| 摘要点击次数: 480 |
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| 中文摘要: |
| 摘 要： ［目的］ 基于转录组数据筛选食管癌铜死亡相关基因，构建预后模型，并探讨其临床价值。［方法］ 从TCGA和GEO数据库下载食管癌转录组、基因表达和临床数据，对铜死亡相关基因进行鉴定。基于铜死亡相关基因表达量，对TCGA和GEO合并数据进行共识聚类，筛选差异基因，并进行Cox分析和LASSO回归分析，筛选预后基因并构建预后风险模型。基于风险评分及临床因素构建列线图，预测患者的生存率。［结果］ 通过对49个铜死亡相关基因的鉴定，有26个基因在肿瘤组织及正常组织中差异表达。经多因素分析及LASSO回归分析，筛选出6个有预后价值的风险基因（PLEKHA7、GATM、F2RL2、TFF3、DKK1、CLIC3），并构建了6基因预后模型。基于预后模型的高风险组患者生存率明显低于低风险组，ROC曲线下面积（AUC）为0.916，验证了风险模型具有良好的预测性能。不同风险评分与患者的肿瘤微环境及药物敏感性密切相关。列线图预测了食管癌患者1年、3年和5年的生存概率分别为91.6%、62.4%和56.3%，校准曲线证实其预测的准确性。［结论］ 基于铜死亡相关基因的6基因预后风险模型可以较好地预测食管癌的预后，可能是风险分层、免疫治疗评估和药物敏感性分析有用的生物标志物。 |
| 英文摘要: |
| Abstract：［Objective］ To screen the genes associated with cuproptososis and to construct a prognosis risk model for esophageal carcinoma based on transcriptome data. ［Methods］ Transcriptome， gene expression and clinical data of esophageal carcinoma were downloaded from TCGA and GEO databases to screen cuproptososis-related genes. Based on the expression of cuproptososis related genes， the combined data of TCGA and GEO were consensus clustered， differential genes were screened and Cox analysis and LASSO regression analysis were performed. A prognostic risk models were constructed and the clinical value of the constructed model in patients with esophageal carcinoma assessed. ［Results］ A total of 49 cuproptososis-related genes were identified， among which 26 genes were expressed differently in tumor tissues and normal tissues. Multivariate analysis and LASSO regression analysis showed that 6 genes related to prognostic risk were screened(PLEKHA7， GATM， F2RL2， TFF3， DKK1， CLIC3)， based of which a prediction model was constructed. According to the prognostic model patients were classified as high risk and low risk groups， the survival of high-risk group was significantly lower than that of the low-risk group. The area under the ROC curve(AUC) of the model for predicting prognosis of patients was 0.916. The risk scores were closely related to the tumor microenvironment and drug sensitivity of patients. The 1-year， 3-year， and 5-year survival probabilities of esophageal carcinoma patients predicted by the nomogram were 91.6%， 62.4%， and 56.3%， respectively. The calibration curve confirmed the accuracy of the prediction. ［Conclusion］ The prognostic risk model constructed with 6 cuproptososis-related genes can well predict the prognosis of esophageal carcinoma， which may be used for risk stratification， immunotherapy evaluation and drug susceptibility analysis. |
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