Literature DB >> 17516929

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

Peter Johansson1, Sandra Pavey, Nicholas Hayward.   

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.

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Year:  2007        PMID: 17516929     DOI: 10.1111/j.1600-0749.2007.00375.x

Source DB:  PubMed          Journal:  Pigment Cell Res        ISSN: 0893-5785


  41 in total

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Journal:  Clin Cancer Res       Date:  2008-12-15       Impact factor: 12.531

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Authors:  Shengfu Piao; Rani Ojha; Vito W Rebecca; Arabinda Samanta; Xiao-Hong Ma; Quentin Mcafee; Michael C Nicastri; Meghan Buckley; Eric Brown; Jeffrey D Winkler; Phyllis A Gimotty; Ravi K Amaravadi
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