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基于基因芯片数据鉴定用于预测胃癌患者临床和预后的 5 基因标志物。

Identification of a 5-gene signature for clinical and prognostic prediction in gastric cancer patients upon microarray data.

机构信息

Department of Oncology, Wuhan General Hospital of Guangzhou Command, People's Liberation Army, 627 Wuluo Road, Wuhan 430070, People's Republic of China.

出版信息

Med Oncol. 2013;30(3):678. doi: 10.1007/s12032-013-0678-5. Epub 2013 Aug 3.

Abstract

In this study, we aimed to investigate the clinical and prognostic value of a 5-gene expression signature model for gastric cancer patients upon microarray data. A total of 158 gastric cancer patients were selected, with 33 cases used for microarray analysis as training set and 125 cases for validation real-time quantitative polymerase chain reaction analysis as test set. Unsupervised clustering algorithms and supervised clustering algorithm were used to identify differentially expressed genes. Gene ontology analyses were used to determine functional prediction of gene biomarkers and receiver operating characteristic analyses to verify the specificity and sensitivity of the evaluation. Moreover, the correlation between clinicopathological characteristics and 5-gene expression was evaluated. The results showed that there were poor disease progression and clinic prognosis in the patients with proximal gastric cancer compared with distal gastric cancer, including differentiation grade (P = 0.001), depth of tumor invasion (P < 0.01), lymph node metastasis (P < 0.01), UICC stage (P < 0.01), and survival status (P < 0.01). Furthermore, a 5-gene signature, including cordon-bleu protein-like 1, damage-specific DNA binding protein 1, BCL2-like 13, nuclear receptor coactivator-6, and F-box leucine-rich protein 11, was identified based on the combination of multiple bioinformatics algorithm. The expression of 5-gene signature (HR = 2.35; 95 % confidence interval 1.24-5.06; P = 0.026) and UICC stage (HR = 5.35; 95 % confidence interval 1.36-19.15; P = 0.032) was independent prognostic factors for overall survival in the survival multivariate analysis. Over-expression of the 5-gene signature in patients with proximal gastric cancer is strongly associated with disease progression and poor prognosis, suggesting that might be potential prognostic predictors in gastric cancer.

摘要

在这项研究中,我们旨在通过微阵列数据研究用于胃癌患者的 5 个基因表达特征模型的临床和预后价值。共选择了 158 例胃癌患者,其中 33 例用于微阵列分析作为训练集,125 例用于验证实时定量聚合酶链反应分析作为测试集。使用无监督聚类算法和有监督聚类算法来识别差异表达基因。使用基因本体分析来确定基因生物标志物的功能预测,并使用接收者操作特征分析来验证评估的特异性和敏感性。此外,还评估了临床病理特征与 5 个基因表达之间的相关性。结果表明,与远端胃癌相比,近端胃癌患者的疾病进展和临床预后较差,包括分化程度(P=0.001)、肿瘤侵袭深度(P<0.01)、淋巴结转移(P<0.01)、UICC 分期(P<0.01)和生存状态(P<0.01)。此外,基于多种生物信息学算法的组合,确定了包括 cordon-bleu 蛋白样 1、损伤特异性 DNA 结合蛋白 1、BCL2 样 13、核受体共激活因子-6 和 F-box 亮氨酸丰富蛋白 11 的 5 个基因特征。5 个基因特征的表达(HR=2.35;95%置信区间 1.24-5.06;P=0.026)和 UICC 分期(HR=5.35;95%置信区间 1.36-19.15;P=0.032)是总生存的独立预后因素。在生存多因素分析中,近端胃癌患者的 5 个基因特征表达过度与疾病进展和预后不良密切相关,提示其可能是胃癌的潜在预后预测指标。

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