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首页> 外文期刊>DNA and Cell Biology >Detection of Novel Genomic Markers for Predicting Prognosis in Hepatocellular Carcinoma Patients by Integrative Analysis of Copy Number Aberrations and Gene Expression Profiles: Results from a Long-Term Follow-Up
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Detection of Novel Genomic Markers for Predicting Prognosis in Hepatocellular Carcinoma Patients by Integrative Analysis of Copy Number Aberrations and Gene Expression Profiles: Results from a Long-Term Follow-Up

机译:通过拷贝数畸变和基因表达谱的综合分析检测可预测肝细胞癌患者预后的新型基因组标记:长期随访的结果

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摘要

The aim of this study was to explore novel genomic biomarkers predicting hepatocellular carcinoma (HCC) prognosis by integrative analysis of DNA copy number aberrations (CNAs) and gene expression profiles. Array comparative genomic hybridization and expression array were performed on 45 and 31 HCC samples, respectively. To identify functionally important genes, concordant results of DNA copy number and gene expression were retrieved by integrative analysis. Cox regression analysis indicated that the CNAs in 192 genomic regions were significantly associated with overall survival (OS; p<0.05). Integrative analysis capturing concordant results demonstrated that the low expression of TLE4 (p=0.041) and XPA (p=0.006) was associated with poor OS. In the analysis of tumor recurrence, 514 genomic regions with CNAs were associated with recurrence. Integrative analysis revealed that the overexpression of 16 genes, including FGR (p=0.003), RELA (p=0.049), LTBP3 (p=0.050), and RIN1 (p=0.023), was significantly associated with shorter time to tumor recurrence. On multivariate analysis, FGR and XPA were independent risk factors of early recurrence and poor OS, respectively. Integrated analysis of CNAs and gene expression profiles correlated with long-term follow-up data successfully identified potential prognostic markers predicting survival and tumor recurrence in patients with HCC who underwent surgical resection.
机译:这项研究的目的是通过对DNA拷贝数畸变(CNA)和基因表达谱的综合分析,探索预测肝细胞癌(HCC)预后的新型基因组生物标记。分别在45和31个HCC样品上进行了阵列比较基因组杂交和表达阵列。为了鉴定功能上重要的基因,通过综合分析检索了DNA拷贝数和基因表达的一致结果。 Cox回归分析表明192个基因组区域的CNA与总体生存率显着相关(OS; p <0.05)。捕获一致结果的综合分析表明,TLE4(p = 0.041)和XPA(p = 0.006)的低表达与不良OS相关。在肿瘤复发的分析中,有514个具有CNA的基因组区域与复发相关。整合分析显示,包括FGR(p = 0.003),RELA(p = 0.049),LTBP3(p = 0.050)和RIN1(p = 0.023)在内的16个基因的过度表达与较短的肿瘤复发时间显着相关。在多变量分析中,FGR和XPA分别是早期复发和OS不良的独立危险因素。与长期随访数据相关的CNA和基因表达谱的综合分析成功地确定了潜在的预后标志物,这些标志物可预测接受手术切除的HCC患者的生存率和肿瘤复发。

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