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黑色素瘤中BRAF突变相关基因表达特征的确认。

Confirmation of a BRAF mutation-associated gene expression signature in melanoma.

作者信息

Johansson Peter, Pavey Sandra, Hayward Nicholas

机构信息

Queensland Institute of Medical Research, Herston, QLD, Australia.

出版信息

Pigment Cell Res. 2007 Jun;20(3):216-21. doi: 10.1111/j.1600-0749.2007.00375.x.

DOI:10.1111/j.1600-0749.2007.00375.x
PMID:17516929
Abstract

Mutations in the BRAF oncogene occur in the majority of melanomas, leading to the activation of the mitogen-activated protein kinase pathway and the transcription of downstream effectors. As BRAF and its effectors could be good melanoma therapy targets, defining the repertoire of genes that are differentially regulated because of BRAF mutational activation is an important objective. Towards this goal, we and others have attempted to determine whether a BRAF mutation-associated gene expression profile exists. Results have been mixed, with some groups reporting a BRAF-signature and another group not. Here we resolve this issue and confirm that while gene-by-gene correlations fail to reveal a specific gene(s) whose expression correlates with BRAF status, a BRAF signature can be distinguished by analysis of global expression patterns. Specifically, we have here applied support vector machine (SVM) analysis to Affymetrix microarray data from a panel of 63 melanoma cell lines. SVMs found a BRAF signature in training samples and predicted BRAF mutation status with high accuracy (AUC=0.840) in the remaining samples. We verified this is a generalized BRAF signature by repeating the analysis in three published microarray datasets, and again found that SVMs predicted BRAF mutation well (Philadelphia: AUC=0.788; Zurich: AUC=0.688; Mannheim: AUC=0.686). An ensemble of 300 SVMs trained on our data also predicted BRAF mutation status in two of the three published datasets (Philadelphia AUC=0.778; Zurich AUC=0.719; Mannheim AUC=0.564). Taken together, these data support the existence of a BRAF mutation-specific expression signature.

摘要

BRAF癌基因的突变存在于大多数黑色素瘤中,导致丝裂原活化蛋白激酶途径的激活以及下游效应分子的转录。由于BRAF及其效应分子可能是黑色素瘤治疗的良好靶点,因此确定因BRAF突变激活而差异调节的基因库是一个重要目标。为了实现这一目标,我们和其他人试图确定是否存在与BRAF突变相关的基因表达谱。结果不一,一些研究小组报告了BRAF特征,而另一个小组则没有。在这里,我们解决了这个问题,并确认虽然逐个基因的相关性未能揭示其表达与BRAF状态相关的特定基因,但通过对全局表达模式的分析可以区分BRAF特征。具体而言,我们在此将支持向量机(SVM)分析应用于来自63个黑色素瘤细胞系的Affymetrix微阵列数据。SVM在训练样本中发现了BRAF特征,并在其余样本中以高精度(AUC = 0.840)预测BRAF突变状态。我们通过在三个已发表的微阵列数据集中重复分析验证了这是一个广义的BRAF特征,并且再次发现SVM能够很好地预测BRAF突变(费城:AUC = 0.788;苏黎世:AUC = 0.688;曼海姆:AUC = 0.686)。在我们的数据上训练的300个SVM的集合也在三个已发表的数据集中的两个中预测了BRAF突变状态(费城AUC = 0.778;苏黎世AUC = 0.719;曼海姆AUC = 0.564)。综上所述,这些数据支持存在BRAF突变特异性表达特征。

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