1st Department of Pediatrics, Semmelweis University, Budapest, Hungary.
Breast Cancer Res Treat. 2013 Jul;140(2):219-32. doi: 10.1007/s10549-013-2622-y. Epub 2013 Jul 9.
To date, three molecular markers (ER, PR, and CYP2D6) have been used in clinical setting to predict the benefit of the anti-estrogen tamoxifen therapy. Our aim was to validate new biomarker candidates predicting response to tamoxifen treatment in breast cancer by evaluating these in a meta-analysis of available transcriptomic datasets with known treatment and follow-up. Biomarker candidates were identified in Pubmed and in the 2007-2012 ASCO and 2011-2012 SABCS abstracts. Breast cancer microarray datasets of endocrine therapy-treated patients were downloaded from GEO and EGA and RNAseq datasets from TCGA. Of the biomarker candidates, only those identified or already validated in a clinical cohort were included. Relapse-free survival (RFS) up to 5 years was used as endpoint in a ROC analysis in the GEO and RNAseq datasets. In the EGA dataset, Kaplan-Meier analysis was performed for overall survival. Statistical significance was set at p < 0.005. The transcriptomic datasets included 665 GEO-based and 1,208 EGA-based patient samples. All together 68 biomarker candidates were identified. Of these, the best performing genes were PGR (AUC = 0.64, p = 2.3E-07), MAPT (AUC = 0.62, p = 7.8E-05), and SLC7A5 (AUC = 0.62, p = 9.2E-05). Further genes significantly correlated to RFS include FOS, TP53, BTG2, HOXB7, DRG1, CXCL10, and TPM4. In the RNAseq dataset, only ERBB2, EDF1, and MAPK1 reached statistical significance. We evaluated tamoxifen-resistance genes in three independent platforms and identified PGR, MAPT, and SLC7A5 as the most promising prognostic biomarkers in tamoxifen treated patients.
迄今为止，已有三种分子标志物（ER、PR 和 CYP2D6）被用于临床，以预测抗雌激素他莫昔芬治疗的疗效。我们的目的是通过评估这些在具有已知治疗和随访的可用转录组数据集的荟萃分析中，验证新的生物标志物候选物，以预测乳腺癌对他莫昔芬治疗的反应。生物标志物候选物是在 Pubmed 和 2007-2012 年 ASCO 和 2011-2012 年 SABCS 摘要中确定的。从 GEO 和 EGA 下载了内分泌治疗患者的乳腺癌微阵列数据集，并从 TCGA 下载了 RNAseq 数据集。在临床队列中确定或已经验证的生物标志物候选物才被包括在内。在 GEO 和 RNAseq 数据集中，将 5 年无复发生存率（RFS）用作 ROC 分析的终点。在 EGA 数据集中，进行了总体生存率的 Kaplan-Meier 分析。统计显著性设置为 p<0.005。转录组数据集包括 665 个基于 GEO 的和 1208 个基于 EGA 的患者样本。总共确定了 68 个生物标志物候选物。其中，表现最好的基因是 PGR（AUC=0.64，p=2.3E-07）、MAPT（AUC=0.62，p=7.8E-05）和 SLC7A5（AUC=0.62，p=9.2E-05）。与 RFS 显著相关的其他基因包括 FOS、TP53、BTG2、HOXB7、DRG1、CXCL10 和 TPM4。在 RNAseq 数据集中，仅 ERBB2、EDF1 和 MAPK1 达到统计学意义。我们在三个独立的平台上评估了他莫昔芬耐药基因，发现 PGR、MAPT 和 SLC7A5 是他莫昔芬治疗患者最有前途的预后生物标志物。
