Semmelweis University, 1st Department of Gynecology, Budapest.
Int J Cancer. 2012 Jul 1;131(1):95-105. doi: 10.1002/ijc.26364. Epub 2011 Dec 2.
Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort.
卵巢癌全基因组表达谱分析可识别失调基因，这些基因可作为组织学亚型和生存的分子标志物。我们的研究目的是在独立环境中验证先前的候选标志物，并鉴定能够作为卵巢癌进展的生物标志物的单个基因。由于 GEO 中现在有多个数据集，我们能够进行真正的荟萃分析。首先，下载了 829 个样本（11 个数据集），并评估了 16 个先前发表的基因集的预测能力。其中，有 8 个能够区分组织学亚型，但没有一个能够预测生存。为了克服先前研究中的差异，我们使用 829 个样本来识别新的预测因子。然后，我们收集了 64 个卵巢癌样本（中位无复发生存期 24.5 个月），并对与组织学亚型和生存相关的最佳 40 个基因进行了 TaqMan 实时聚合酶链反应（RT-PCR）分析。超过 90%的与亚型相关的基因得到了确认。激素受体（PGR 和 ESR2）和 TSPAN8 有效预测了总生存期。MAPT 和 SNCG 预测了无复发生存期。总之，我们在大型卵巢样本数据集的荟萃分析中成功验证了几个基因集。此外，在临床队列中验证了几个单独的基因。
