Department of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK.
Breast Cancer Res Treat. 2011 Jul;128(2):315-26. doi: 10.1007/s10549-010-1073-y. Epub 2010 Aug 10.
Global gene expression profiling studies have classified breast cancer into a number of distinct biological and molecular classes with clinical relevance. The heterogeneous luminal group, which is largely characterised by oestrogen receptor (ER) expression, appears to contain distinct subgroups with differing behaviour. In this study, we analysed 47,293 gene transcripts in 128 invasive breast carcinomas (BC) using Artificial Neural Networks and a cross-validation analysis in combination with an ensemble sample classification to identify genes that can be used to subclassify ER+ luminal tumours. The results were validated using immunohistochemistry on TMAs containing 1,140 invasive breast cancers. Our results showed that the RERG gene is one of the highest ranked genes to differentiate between ER+ luminal-like and ER- non-luminal cancers based on a 10-fold external cross-validation analysis with an average classification accuracy of 89%. This was confirmed in our protein expression studies that showed RERG positive associations with markers of luminal differentiation including ER, luminal cytokeratins (CK19, CK18 and CK7/8) and FOXA1 (P = 0.004) and other markers of good prognosis in BC including small size, lower histologic grade and positive expression of androgen receptor, nuclear BRCA1, FHIT and cell cycle inhibitors p27 and p21. RERG expression was inversely associated with the proliferation marker MIB1 (P = 0.005) and p53. Strong RERG expression showed an association with longer breast cancer specific survival and distant metastasis free interval in the whole series as well as in the ER+ luminal group and these associations were independent of other prognostic variables. In conclusion, we used novel bioinformatics methods to identify candidate genes to characterise ER+ luminal-like breast cancer. RERG gene is a key marker of the luminal BC class and can be used to separate distinct prognostic subgroups.
全球基因表达谱研究已经将乳腺癌分为具有临床相关性的许多不同的生物学和分子类别。以雌激素受体 (ER) 表达为主要特征的异质性管腔组似乎包含具有不同行为的不同亚组。在这项研究中，我们使用人工神经网络 (ANN) 分析了 128 例浸润性乳腺癌 (BC) 中的 47,293 个基因转录本，并结合交叉验证分析和集成样本分类，以鉴定可用于亚分类 ER+管腔肿瘤的基因。结果使用包含 1,140 例浸润性乳腺癌的 TMAs 的免疫组织化学进行验证。我们的结果表明，RERG 基因是区分 ER+管腔样和 ER-非管腔癌的最高排名基因之一，基于 10 倍外部交叉验证分析，平均分类准确率为 89%。这在我们的蛋白表达研究中得到了证实，表明 RERG 与 luminal 分化标志物（包括 ER、管腔细胞角蛋白（CK19、CK18 和 CK7/8）和 FOXA1）以及其他与预后良好相关的标志物呈阳性相关在 BC 中，包括体积小、组织学分级低、雄激素受体、核 BRCA1、FHIT 和细胞周期抑制剂 p27 和 p21 阳性表达。RERG 表达与增殖标志物 MIB1（P = 0.005）和 p53 呈负相关。在整个系列以及 ER+管腔组中，强烈的 RERG 表达与乳腺癌特异性生存和无远处转移间隔较长有关，这些关联独立于其他预后变量。总之，我们使用新的生物信息学方法来鉴定用于表征 ER+管腔样乳腺癌的候选基因。RERG 基因是管腔 BC 类的关键标志物，可用于分离不同的预后亚组。
