Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer

The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wi...

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Bibliographic Details
Published in:PLoS Genetics 2016-03, Vol.12 (3), p.e1005826-e1005826
Main Author: Heyn, Holger
Format: Article
Language:English
Subjects:
Associations
Biology and Life Sciences
Cancer
Deoxyribonucleic acid
DNA
DNA methylation
DNA Methylation - genetics
Epigenetics
Funding
Gene expression
Gene Expression Regulation, Neoplastic
Genetic aspects
Genetic Predisposition to Disease
Genetic variation
Genome-Wide Association Study
Genomes
Genomics
Humans
Leukemia
Medical research
Methods
Mutation
Neoplasms - genetics
Neoplasms - pathology
Observations
Open Reading Frames - genetics
Polymorphism, Single Nucleotide - genetics
Quantitative trait loci
Quantitative Trait Loci - genetics
Regulatory Sequences, Nucleic Acid - genetics
Review
Transcription factors
Validation studies
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Description
Summary:The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wide profiling strategies, alterations outside the coding context entered the focus, and multiple examples highlight the role of gene deregulation as cancer-driving events. This review describes the implication of noncoding alterations in oncogenesis and provides a theoretical framework for the identification of causal somatic variants using quantitative trait loci (QTL) analysis. Assuming that functional noncoding alterations affect quantifiable regulatory processes, somatic QTL studies constitute a valuable strategy to pinpoint cancer gene deregulation. Eventually, the comprehensive identification and interpretation of coding and noncoding alterations will guide our future understanding of cancer biology.
ISSN:1553-7404
1553-7390
1553-7404
DOI:10.1371/journal.pgen.1005826