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A catalogue of somatic NRF2 gain-of-function mutations in cancer

Identification and characterization of somatic mutations in cancer have important prognostication and treatment implications. Genes encoding the Nuclear factor (erythroid-derived 2)-like 2 (NRF2) transcription factor and its negative regulator, Kelch-like ECH-associated protein 1 (KEAP1), are freque...

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Detalles Bibliográficos
Autores principales: Kerins, Michael John, Ooi, Aikseng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110754/
https://www.ncbi.nlm.nih.gov/pubmed/30150714
http://dx.doi.org/10.1038/s41598-018-31281-0
Descripción
Sumario:Identification and characterization of somatic mutations in cancer have important prognostication and treatment implications. Genes encoding the Nuclear factor (erythroid-derived 2)-like 2 (NRF2) transcription factor and its negative regulator, Kelch-like ECH-associated protein 1 (KEAP1), are frequently mutated in cancer. These mutations drive constitutive NRF2 activation and correlate with poor prognosis. Despite its apparent significance, a comprehensive catalogue of somatic NRF2 mutations across different tumor types is still lacking. Here, we catalogue NRF2 mutations in The Cancer Genome Atlas (TCGA) database. 226 unique NRF2-mutant tumors were identified from 10,364 cases. NRF2 mutations were found in 21 out of the 33 tumor types. A total of 11 hotspots were identified. Of these, mutation to the R34 position was most frequent. Notably, R34 and D29 mutations were overrepresented in bladder, lung, and uterine cancers. Analyses of corresponding RNA sequencing data using a de novo derived gene expression classifier showed that the R34 mutations drive constitutive NRF2 activation with a selection pressure biased against the formation of R34L. Of all R34 mutants, R34L conferred the least degree of protein stabilization, suggesting a pro-tumor NRF2 half-life threshold. Our findings offer a comprehensive catalogue of NRF2 mutations in cancer that can help prognostication and NRF2 research.