Abstract
We have used microarray gene expression profiling and machine learning to predict the presence of BRAF mutations in a panel of 61 melanoma cell lines. The BRAF gene was found to be mutated in 42 samples (69%) and intragenic mutations of the NRAS gene were detected in seven samples (11%). No cell line carried mutations of both genes. Using support vector machines, we have built a classifier that differentiates between melanoma cell lines based on BRAF mutation status. As few as 83 genes are able to discriminate between BRAF mutant and BRAF wild-type samples with clear separation observed using hierarchical clustering. Multidimensional scaling was used to visualize the relationship between a BRAF mutation signature and that of a generalized mitogen-activated protein kinase (MAPK) activation (either BRAF or NRAS mutation) in the context of the discriminating gene list. We observed that samples carrying NRAS mutations lie somewhere between those with or without BRAF mutations. These observations suggest that there are gene-specific mutation signals in addition to a common MAPK activation that result from the pleiotropic effects of either BRAF or NRAS on other signaling pathways, leading to measurably different transcriptional changes.
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Acknowledgements
We thank Patrik Edén and Javed Khan for valuable assistance, and Cathy Davern and Michelle Down for culturing some of the melanoma cell lines. We also thank Yidong Chen, NHGRI, for access to the software used to generate the MDS figure. This work was supported by the National Health and Medical Research Council of Australia Grant Number 199600, the Swedish Research Council and the Knut and Alice Wallenberg Foundation through the Swegene consortium.
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Supplementary material can be viewed at the following URL: http://www.qimr.edu.au/research/labs/nickh/Pavey-et-al-Supporting-Information.pdf
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Pavey, S., Johansson, P., Packer, L. et al. Microarray expression profiling in melanoma reveals a BRAF mutation signature. Oncogene 23, 4060–4067 (2004). https://doi.org/10.1038/sj.onc.1207563
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DOI: https://doi.org/10.1038/sj.onc.1207563
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