Dataset Information

Mutation-specific RAS oncogenicity explains NRAS codon 61 selection in melanoma.

ABSTRACT: NRAS mutation at codons 12, 13, or 61 is associated with transformation; yet, in melanoma, such alterations are nearly exclusive to codon 61. Here, we compared the melanoma susceptibility of an NrasQ61R knock-in allele to similarly designed KrasG12D and NrasG12D alleles. With concomitant p16INK4a inactivation, KrasG12D or NrasQ61R expression efficiently promoted melanoma in vivo, whereas NrasG12D did not. In addition, NrasQ61R mutation potently cooperated with Lkb1/Stk11 loss to induce highly metastatic disease. Functional comparisons of NrasQ61R and NrasG12D revealed little difference in the ability of these proteins to engage PI3K or RAF. Instead, NrasQ61R showed enhanced nucleotide binding, decreased intrinsic GTPase activity, and increased stability when compared with NrasG12D. This work identifies a faithful model of human NRAS-mutant melanoma, and suggests that the increased melanomagenecity of NrasQ61R over NrasG12D is due to heightened abundance of the active, GTP-bound form rather than differences in the engagement of downstream effector pathways.This work explains the curious predominance in human melanoma of mutations of codon 61 of NRAS over other oncogenic NRAS mutations. Using conditional "knock-in" mouse models, we show that physiologic expression of NRASQ61R, but not NRASG12D, drives melanoma formation.

SUBMITTER: Burd CE

PROVIDER: S-EPMC4258185 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Mutation-specific RAS oncogenicity explains NRAS codon 61 selection in melanoma.

Burd Christin E CE Liu Wenjin W Huynh Minh V MV Waqas Meriam A MA Gillahan James E JE Clark Kelly S KS Fu Kailing K Martin Brit L BL Jeck William R WR Souroullas George P GP Darr David B DB Zedek Daniel C DC Miley Michael J MJ Baguley Bruce C BC Campbell Sharon L SL Sharpless Norman E NE

Cancer discovery 20140924 12

<h4>Unlabelled</h4>NRAS mutation at codons 12, 13, or 61 is associated with transformation; yet, in melanoma, such alterations are nearly exclusive to codon 61. Here, we compared the melanoma susceptibility of an NrasQ61R knock-in allele to similarly designed KrasG12D and NrasG12D alleles. With concomitant p16INK4a inactivation, KrasG12D or NrasQ61R expression efficiently promoted melanoma in vivo, whereas NrasG12D did not. In addition, NrasQ61R mutation potently cooperated with Lkb1/Stk11 loss ...[more]

PMID: 25252692

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Project description:Extracting biologically meaningful information from the continuing flood of genomic data is a major challenge in the life sciences. Codon usage bias (CUB) is a general feature of most genomes and is thought to reflect the effects of both natural selection for efficient translation and mutation bias. Here we present a mechanistically interpretable, Bayesian model (ribosome overhead costs Stochastic Evolutionary Model of Protein Production Rate [ROC SEMPPR]) to extract meaningful information from patterns of CUB within a genome. ROC SEMPPR is grounded in population genetics and allows us to separate the contributions of mutational biases and natural selection against translational inefficiency on a gene-by-gene and codon-by-codon basis. Until now, the primary disadvantage of similar approaches was the need for genome scale measurements of gene expression. Here, we demonstrate that it is possible to both extract accurate estimates of codon-specific mutation biases and translational efficiencies while simultaneously generating accurate estimates of gene expression, rather than requiring such information. We demonstrate the utility of ROC SEMPPR using the Saccharomyces cerevisiae S288c genome. When we compare our model fits with previous approaches we observe an exceptionally high agreement between estimates of both codon-specific parameters and gene expression levels ([Formula: see text] in all cases). We also observe strong agreement between our parameter estimates and those derived from alternative data sets. For example, our estimates of mutation bias and those from mutational accumulation experiments are highly correlated ([Formula: see text]). Our estimates of codon-specific translational inefficiencies and tRNA copy number-based estimates of ribosome pausing time ([Formula: see text]), and mRNA and ribosome profiling footprint-based estimates of gene expression ([Formula: see text]) are also highly correlated, thus supporting the hypothesis that selection against translational inefficiency is an important force driving the evolution of CUB. Surprisingly, we find that for particular amino acids, codon usage in highly expressed genes can still be largely driven by mutation bias and that failing to take mutation bias into account can lead to the misidentification of an amino acid's "optimal" codon. In conclusion, our method demonstrates that an enormous amount of biologically important information is encoded within genome scale patterns of codon usage, accessing this information does not require gene expression measurements, but instead carefully formulated biologically interpretable models.

Dataset Information

Mutation-specific RAS oncogenicity explains NRAS codon 61 selection in melanoma.

Publications

Mutation-specific RAS oncogenicity explains NRAS codon 61 selection in melanoma.

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