Interpretation of the role of germline and somatic non-coding mutations in cancer: expression and chromatin conformation informed analysis

Background There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of r...

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Bibliographic Details
Published in:Clinical epigenetics 2022-09, Vol.14 (1), p.1-120, Article 120
Main Authors: Pudjihartono, Michael, Perry, Jo K, Print, Cris, O'Sullivan, Justin M, Schierding, William
Format: Article
Language:English
Subjects:
Amino acids
Analysis
Annotations
Binding sites
Breast cancer
Cancer
Cells
Chromatin
Consortia
Development and progression
Gene expression
Gene mutations
Genes
Genetic aspects
Genomes
Health aspects
Melanoma
Mutation
Oncology, Experimental
Regulatory sequences
Review
Risk factors
Telomerase
Transcription factors
Tumorigenesis
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Summary:Background There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of regulatory (non-coding) variants, which have recently been identified as putative somatic drivers and key germline risk factors for cancer development. Comprehensive understanding of non-coding mutations requires understanding their role in the disruption of regulatory elements, which then disrupt key biological functions such as gene expression. Main body We describe how advancements in sequencing technologies have led to the identification of a large number of non-coding mutations with uncharacterized biological significance. We summarize the strategies that have been developed to interpret and prioritize the biological mechanisms impacted by non-coding mutations, focusing on recent annotation of cancer non-coding variants utilizing chromatin states, eQTLs, and chromatin conformation data. Conclusion We believe that a better understanding of how to apply different regulatory data types into the study of non-coding mutations will enhance the discovery of novel mechanisms driving cancer. Keywords: Cancer, Non-coding mutation, Somatic mutation, Germline mutation, GWAS, eQTL, Chromosome conformation, Hi-C
ISSN:1868-7075
1868-7083
1868-7083
1868-7075
DOI:10.1186/s13148-022-01342-3