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首页> 外文期刊>Pigment cell research >Confirmation of a BRAF mutation-associated gene expression signature in melanoma
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Confirmation of a BRAF mutation-associated gene expression signature in melanoma

机译：黑色素瘤中BRAF突变相关基因表达签名的确认

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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.
机译：大多数黑色素瘤中都发生BRAF癌基因的突变，从而导致丝裂原激活的蛋白激酶途径的激活和下游效应子的转录。由于BRAF及其效应子可能是良好的黑色素瘤治疗靶标，因此定义因BRAF突变激活而受到差异调节的基因库是一个重要目标。为了实现这一目标，我们和其他人尝试确定是否存在与BRAF突变相关的基因表达谱。结果好坏参半，有些小组报告了BRAF签名，而另一些小组则没有。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无法揭示其表达与BRAF状态相关的特定基因，但可以通过分析全局表达模式来区分BRAF签名。具体来说，我们在这里将支持向量机（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签名，并在其余样本中以高精度（AUC = 0.840）预测了BRAF突变状态。我们通过在三个已公开的微阵列数据集中重复分析来验证这是广义的BRAF签名，并再次发现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的集合还预测了三个已公开数据集中的两个数据集中的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BRAF突变特异性表达标记的存在。

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