Bioinformatics Core Facility, Swiss Institute of Bioinformatics, Quartier Sorge, Genopode, CH-1015 Lausanne, Switzerland.
J Clin Oncol. 2012 Apr 20;30(12):1288-95. doi: 10.1200/JCO.2011.39.5814. Epub 2012 Mar 5.
Our purpose was development and assessment of a BRAF-mutant gene expression signature for colon cancer (CC) and the study of its prognostic implications.
A set of 668 stage II and III CC samples from the PETACC-3 (Pan-European Trails in Alimentary Tract Cancers) clinical trial were used to assess differential gene expression between c.1799T>A (p.V600E) BRAF mutant and non-BRAF, non-KRAS mutant cancers (double wild type) and to construct a gene expression-based classifier for detecting BRAF mutant samples with high sensitivity. The classifier was validated in independent data sets, and survival rates were compared between classifier positive and negative tumors.
A 64 gene-based classifier was developed with 96% sensitivity and 86% specificity for detecting BRAF mutant tumors in PETACC-3 and independent samples. A subpopulation of BRAF wild-type patients (30% of KRAS mutants, 13% of double wild type) showed a gene expression pattern and had poor overall survival and survival after relapse, similar to those observed in BRAF-mutant patients. Thus they form a distinct prognostic subgroup within their mutation class.
A characteristic pattern of gene expression is associated with and accurately predicts BRAF mutation status and, in addition, identifies a population of BRAF mutated-like KRAS mutants and double wild-type patients with similarly poor prognosis. This suggests a common biology between these tumors and provides a novel classification tool for cancers, adding prognostic and biologic information that is not captured by the mutation status alone. These results may guide therapeutic strategies for this patient segment and may help in population stratification for clinical trials.
本研究旨在开发并评估用于结直肠癌(CC)的 BRAF 突变基因表达特征,并研究其预后意义。
使用来自 PETACC-3(泛欧消化道肿瘤临床试验)临床试验的 668 例 II 期和 III 期 CC 样本,评估 c.1799T>A(p.V600E)BRAF 突变与非 BRAF、非 KRAS 突变(双野生型)癌症之间的差异基因表达,并构建用于高灵敏度检测 BRAF 突变样本的基于基因表达的分类器。该分类器在独立数据集进行验证,并比较分类器阳性和阴性肿瘤的生存率。
在 PETACC-3 和独立样本中,开发了一个基于 64 个基因的分类器,其检测 BRAF 突变肿瘤的敏感性为 96%,特异性为 86%。BRAF 野生型患者(30%的 KRAS 突变,13%的双野生型)存在一种基因表达模式,其总体生存率和复发后生存率与 BRAF 突变患者相似,因此在其突变类别中形成了一个独特的预后亚组。
一种特征性的基因表达模式与 BRAF 突变状态相关,并能准确预测其状态,此外,还鉴定出一群 BRAF 突变样 KRAS 突变和双野生型患者,其预后同样较差。这表明这些肿瘤之间存在共同的生物学特性,并为癌症提供了一种新的分类工具,增加了仅通过突变状态无法捕捉到的预后和生物学信息。这些结果可能为该患者群体的治疗策略提供指导,并有助于临床试验的人群分层。