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Clustered somatic mutations are frequent in transcription factor binding motifs within proximal promoter regions in melanoma and other cutaneous malignancies.


ABSTRACT: Most cancer DNA sequencing studies have prioritized recurrent non-synonymous coding mutations in order to identify novel cancer-related mutations. Although attention is increasingly being paid to mutations in non-coding regions, standard approaches to identifying significant mutations may not be appropriate and there has been limited analysis of mutational clusters in functionally annotated non-coding regions. We sought to identify clustered somatic mutations (hotspot regions across samples) in functionally annotated regions in melanoma and other cutaneous malignancies (cutaneous squamous cell carcinoma, basal cell carcinoma and Merkel cell carcinoma). Sliding window analyses revealed numerous recurrent clustered hotspot mutations in proximal promoters, with some specific clusters present in up to 25% of cases. Mutations in melanoma were clustered within ETS and Sp1 transcription factor binding motifs, had a UV signature and were identified in other cutaneous malignancies. Clinicopathologic correlation and mutation analysis support a causal role for chronic UV irradiation generating somatic mutations in transcription factor binding motifs of proximal promoters.

SUBMITTER: Colebatch AJ 

PROVIDER: S-EPMC5341821 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Clustered somatic mutations are frequent in transcription factor binding motifs within proximal promoter regions in melanoma and other cutaneous malignancies.

Colebatch Andrew J AJ   Di Stefano Leon L   Wong Stephen Q SQ   Hannan Ross D RD   Waring Paul M PM   Dobrovic Alexander A   McArthur Grant A GA   Papenfuss Anthony T AT  

Oncotarget 20161001 41


Most cancer DNA sequencing studies have prioritized recurrent non-synonymous coding mutations in order to identify novel cancer-related mutations. Although attention is increasingly being paid to mutations in non-coding regions, standard approaches to identifying significant mutations may not be appropriate and there has been limited analysis of mutational clusters in functionally annotated non-coding regions. We sought to identify clustered somatic mutations (hotspot regions across samples) in  ...[more]

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