BTF4/BTNA3.2 and GCS as candidate mRNA prognostic markers in epithelial ovarian cancer

BTF4/BTNA3.2 and GCS as candidate mRNA prognostic markers in epithelial ovarian cancer
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DOI:
10.1158/1055-9965.epi-07-0692
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发表时间:
2008-04-01
影响因子:
3.8
通讯作者:
Mes-Masson, Anne-Marie
Mes-Masson, Anne-Marie
中科院分区:
医学3区
文献类型:
--
作者:
Le Page, Cecile;Ouellet, Veronique;Mes-Masson, Anne-Marie

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本研究旨在通过基于实时定量 PCR (RT-q-PCR) 的测试,确定可靠的预后标志物,以预测高级别浆液性上皮性卵巢癌手术后的患者结果。通过 DNA 微阵列对 17 例浆液性上皮性卵巢癌患者的组织样本进行筛选,以鉴定初次诊断后 18 个月内复发的患者的肿瘤与未复发或 24 个月后复发的患者的肿瘤之间差异表达的基因。在最初的 17 个样本中,通过 RT-q-PCR 验证了基因子集的 RNA 表达。根据这些结果,我们选择了一份完善的清单,并在 41 个浆液性肿瘤的独立样本中进行了测试。表达与复发时间和临床变量相关。微阵列分析确定了 34 个差异表达基因的概况。 RT-q-PCR 验证了最初一组患者中七个基因子集的表达谱。差异基因表达也在一组独立的患者中得到验证。在 Kaplan-Meier 分析(P < 0.05,对数秩检验)和 Cox 单变量以及多变量分析中,低 BTF4 或 GCS 表达与不良结果密切相关,其风险比高于临床变量(如残留病、年龄、分期和分级)。
This study aims to identify reliable prognosis markers to predict patient outcome at surgery in high-grade serous epithelial ovarian cancer by a real-time quantitative PCR (RT-q-PCR)-based test. Seventeen tissue samples from serous epithelial ovarian cancer patients were screened by DNA microarray to identify genes differentially expressed between tumors from patients who relapsed within 18 months and tumors from patients showing no relapse or relapsed after 24 months after initial diagnosis. RNA expression of a subset of genes was validated by RT-q-PCR in the initial set of 17 samples. From these results, a refined list was selected and tested in independent samples from 41 serous tumors. Expression was associated with time to relapse and clinical variables. Microarray analysis identified a profile of 34 differentially expressed genes. RT-q-PCR validated the expression profile of a subset of seven genes in the initial set of patients. Differential gene expression was also validated in an independent set of patients. Low BTF4 or GCS expression was strongly associated with poor outcome in Kaplan-Meier analysis (P < 0.05, log-rank test) and Cox univariate as well as in multivariate analyses with a higher hazard ratio than clinical variables, such as residual disease, age, stage, and grade.