Thomassen Mads, Tan Qihua, Eiriksdottir Freyja, Bak Martin, Cold Søren, Kruse Torben A
Department of Biochemistry, Pharmacology, and Genetics, Odense University Hospital, Odense, Denmark.
Clin Cancer Res. 2007 Sep 15;13(18 Pt 1):5355-60. doi: 10.1158/1078-0432.CCR-07-0249.
In the low-risk group of breast cancer patients, a subgroup experiences metastatic recurrence of the disease. The aim of this study was to examine the performance of gene sets, developed mainly from high-risk tumors, in a group of low-malignant tumors.
Twenty-six tumors from low-risk patients and 34 low-malignant T2 tumors from patients with slightly higher risk have been examined by genome-wide gene expression analysis. Nine prognostic gene sets were tested in this data set.
A 32-gene profile (HUMAC32) that accurately predicts metastasis has previously been developed from this data set. In the present study, six of the eight other gene sets have prognostic power in the low-malignant patient group, whereas two have no prognostic value. Despite a relatively small overlap between gene sets, there is high concordance of classification of samples. This, together with analysis of functional gene groups, indicates that the same pathways may be represented by several of the gene sets. However, the results suggest that low-risk patients may be classified more accurately with gene signatures developed especially for this patient group.
Several gene sets, mainly developed in high-risk cancers, predict metastasis from low-malignant cancer.
在乳腺癌低风险患者群体中，有一部分会出现疾病的转移性复发。本研究的目的是检验主要从高风险肿瘤中开发的基因集在一组低恶性肿瘤中的表现。
通过全基因组基因表达分析，对26例低风险患者的肿瘤以及34例风险稍高患者的低恶性T2肿瘤进行了检测。在该数据集中测试了9个预后基因集。
此前已从该数据集中开发出一种能准确预测转移的32基因谱（HUMAC32）。在本研究中，其他八个基因集中有六个在低恶性患者组中具有预后能力，而另外两个没有预后价值。尽管基因集之间的重叠相对较小，但样本分类的一致性很高。这与功能基因组分析一起表明，几个基因集可能代表相同的通路。然而，结果表明，使用专门为此患者群体开发的基因特征可能能更准确地对低风险患者进行分类。
几个主要在高风险癌症中开发的基因集可预测低恶性癌症的转移。
