Abstract
In the need to characterise the genomic landscape of cancers and to establish novel biomarkers and therapeutic targets, studies have largely focused on the identification of driver mutations within the protein-coding gene regions, where the most pathogenic alterations are known to occur. However, the noncoding genome is significantly larger than its protein-coding counterpart, and evidence reveals that regulatory sequences also harbour functional mutations that significantly affect the regulation of genes and pathways implicated in cancer. Due to the sheer number of noncoding mutations (NCMs) and the limited knowledge of regulatory element functionality in cancer genomes, differentiating pathogenic mutations from background passenger noise is particularly challenging technically and computationally. Here we review various up-to-date high-throughput sequencing data/studies and in silico methods that can be employed to interrogate the noncoding genome. We aim to provide an overview of available data resources as well as computational and molecular techniques that can help and guide the search for functional NCMs in cancer genomes.
Highlights
Cancer is potentiated with the accumulation of mutations, some of which are inherited in the germline, but the vast majority arise in somatic cells [1]
From our own ongoing analysis, we have found that mutations called in cell lines often do not correspond to patient somatic mutations from whole genome sequencing (WGS) data
Far, published studies have focused on driver mutations residing in the coding genome
Summary
Cancer is potentiated with the accumulation of mutations, some of which are inherited in the germline, but the vast majority arise in somatic cells [1] These variations include single nucleotide substitutions, insertions and deletions (INDELS) and copy number alterations and translocations. A huge body of whole-exome sequencing (WES) projects such as The Cancer Genome Atlas (TCGA), which capture the exon coding regions of the genome, have substantially advanced the understanding of coding mutations in cancer, with key driver genes and mutations established across many cancer types This has led to a wave of targeted precision medicine in various cancers, including chronic myelogenous leukaemia [3], breast [4], lung cancers [5,6] and melanomas [7,8,9]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
