Title |
Identification of Single Nucleotide Non-coding Driver Mutations in Cancer
|
---|---|
Published in |
Frontiers in Genetics, February 2018
|
DOI | 10.3389/fgene.2018.00016 |
Pubmed ID | |
Authors |
Kok A. Gan, Sebastian Carrasco Pro, Jared A. Sewell, Juan I. Fuxman Bass |
Abstract |
Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview ofin silicoapproaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization. |
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