一种新型铜死亡相关基因签名，用于预测胰腺癌患者的预后。
A Novel Cuproptosis-Associated Gene Signature to Predict Prognosis in Patients with Pancreatic Cancer.
机构信息
The Second School of Clinical Medicine, Lanzhou University, Lanzhou 730030, China.
Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730030, China.
出版信息
Biomed Res Int. 2023 Jan 18;2023:3419401. doi: 10.1155/2023/3419401. eCollection 2023.
BACKGROUND
Pancreatic cancer (PAAD) is a malignant tumor with a poor prognosis and lacks sensitive biomarkers for diagnosis and targeted therapy. Cuproptosis, a recently proposed form of cell death based on cellular copper ion concentration, plays a key role in cancer biology. This study is aimed at constructing a risk model for predicting the prognosis of PAAD patients based on cuproptosis-related genes.
METHODS
Pancreatic-related data from UCSC-TCGA and UCSC-GTEx databases were extracted for analysis, and TCGA-PAAD samples were randomly divided into the training and validation groups. Pearson correlation analysis was used to obtain cuproptosis-related genes coexpressed with 19 copper death genes. Univariate Cox and Lasso regression analyses were used to obtain cuproptosis-related prognostic genes. Multivariate Cox regression analysis was used to construct the final prognostic risk model. The risk score curve, Kaplan-Meier survival curves, and ROC curve were used to evaluate the predictive ability of the Cox risk model. Finally, the functional annotation of the risk model was obtained through enrichment analysis.
RESULTS
The Cox risk model has an eight prognostic cuproptosis-related gene signature. Kaplan-Meier survival curves demonstrated that the high-risk group had a shorter survival time. The ROC curve of the risk score was well created to predict one-, three-, and five-year survival rates, and AUC of the risk score was higher than other clinical characteristics. Cox regression analysis revealed that the risk score has an independent prognostic value for PAAD. GSEA reveals specific tumor pathways associated with the risk model (Myc targets v1, mTORC1 signaling, and E2F targets).
CONCLUSIONS
We constructed a prognostic model containing eight cuproptosis-related genes (AKR1B10, KLHL29, PROM2, PIP5K1C, KIF18B, AMIGO2, MRPL3, and PI4KB) that can accurately predict the prognosis of PAAD patients. The results will provide new perspectives for individualized outcome prediction and new therapy development for PAAD patients.
背景
胰腺癌（PAAD）是一种预后不良的恶性肿瘤，缺乏用于诊断和靶向治疗的敏感生物标志物。铜死亡，一种基于细胞内铜离子浓度的新提出的细胞死亡形式，在癌症生物学中起着关键作用。本研究旨在构建基于铜死亡相关基因预测 PAAD 患者预后的风险模型。
方法
从 UCSC-TCGA 和 UCSC-GTEx 数据库中提取胰腺相关数据进行分析，并将 TCGA-PAAD 样本随机分为训练组和验证组。使用 Pearson 相关分析获得与 19 个铜死亡基因共表达的铜死亡相关基因。使用单因素 Cox 和 Lasso 回归分析获得铜死亡相关预后基因。使用多因素 Cox 回归分析构建最终的预后风险模型。使用风险评分曲线、Kaplan-Meier 生存曲线和 ROC 曲线评估 Cox 风险模型的预测能力。最后，通过富集分析获得风险模型的功能注释。
结果
Cox 风险模型具有 8 个预后铜死亡相关基因特征。Kaplan-Meier 生存曲线表明，高危组的生存时间更短。风险评分的 ROC 曲线很好地预测了 1 年、3 年和 5 年的生存率，并且风险评分的 AUC 高于其他临床特征。Cox 回归分析表明，风险评分对 PAAD 具有独立的预后价值。GSEA 揭示了与风险模型相关的特定肿瘤途径（Myc targets v1、mTORC1 信号和 E2F targets）。
结论
我们构建了一个包含 8 个铜死亡相关基因（AKR1B10、KLHL29、PROM2、PIP5K1C、KIF18B、AMIGO2、MRPL3 和 PI4KB）的预后模型，可准确预测 PAAD 患者的预后。研究结果将为 PAAD 患者的个体化预后预测和新疗法开发提供新的视角。
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