Identification of a Poor-Prognosis BRAF-Mutant-Like Population of Patients With Colon Cancer
Identification of a Poor-Prognosis BRAF-Mutant-Like Population of Patients With Colon Cancer
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DOI：
10.1200/jco.2011.39.5814
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发表时间：
2012-04-20
影响因子：
45.3
通讯作者：
Delorenzi, Mauro
中科院分区：
文献类型：
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作者：
Popovici, Vlad;Budinska, Eva;Delorenzi, Mauro
目的建立和评估BRAF突变基因在结肠癌(CC)中的表达特征及其预后意义。材料与方法采用来自Petacc-3(泛欧洲消化道癌症试验)临床试验的668例II期和III期CC样本，评估C.1799T和GT；A(p.V600E)BRAF突变与非BRAF、非KRAS突变癌(双野生型)之间的基因表达差异，并构建一种基于基因表达的分类器，用于检测BRAF突变样本。结果构建了一个基于基因的分类器，用于检测Petacc-3和独立样本中Braf基因突变的肿瘤，其灵敏度和特异度分别为96%和86%。BRAF野生型患者的一个亚群(30%的KRAS突变型，13%的双野生型)表现为基因表达模式，总体存活率和复发后存活率较低，与BRAF突变型患者相似。结论一种基因表达的特征模式与BRAF突变状态有关，并可准确预测BRAF突变状态，此外，还可识别BRAF突变样KRAS突变和同样预后不良的双重野生型患者。这表明这些肿瘤之间存在共同的生物学特征，并为癌症提供了一种新的分类工具，增加了仅靠突变状态无法获取的预后和生物信息。这些结果可能会指导这部分患者的治疗策略，并可能有助于临床试验的人群分层。
PurposeOur purpose was development and assessment of a BRAF-mutant gene expression signature for colon cancer (CC) and the study of its prognostic implications.Materials and MethodsA 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.ResultsA 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.ConclusionA 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.