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Review
. 2018 Nov 27;19(6):1085-1101.
doi: 10.1093/bib/bbx049.

Mutational signatures and mutable motifs in cancer genomes

Igor B Rogozin  1 , Youri I Pavlov  2 , Alexander Goncearenco  3 , Subhajyoti De  4 , Artem G Lada  5 , Eugenia Poliakov  6 , Anna R Panchenko  3 , David N Cooper  7
Affiliations
Review

Mutational signatures and mutable motifs in cancer genomes

Igor B Rogozin et al. Brief Bioinform. .

Abstract

Cancer is a genetic disorder, meaning that a plethora of different mutations, whether somatic or germ line, underlie the etiology of the 'Emperor of Maladies'. Point mutations, chromosomal rearrangements and copy number changes, whether they have occurred spontaneously in predisposed individuals or have been induced by intrinsic or extrinsic (environmental) mutagens, lead to the activation of oncogenes and inactivation of tumor suppressor genes, thereby promoting malignancy. This scenario has now been recognized and experimentally confirmed in a wide range of different contexts. Over the past decade, a surge in available sequencing technologies has allowed the sequencing of whole genomes from liquid malignancies and solid tumors belonging to different types and stages of cancer, giving birth to the new field of cancer genomics. One of the most striking discoveries has been that cancer genomes are highly enriched with mutations of specific kinds. It has been suggested that these mutations can be classified into 'families' based on their mutational signatures. A mutational signature may be regarded as a type of base substitution (e.g. C:G to T:A) within a particular context of neighboring nucleotide sequence (the bases upstream and/or downstream of the mutation). These mutational signatures, supplemented by mutable motifs (a wider mutational context), promise to help us to understand the nature of the mutational processes that operate during tumor evolution because they represent the footprints of interactions between DNA, mutagens and the enzymes of the repair/replication/modification pathways.

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Figures

Figure 1
Figure 1
Mutational spectrum of human DNA pol η in the lacZ gene without phenotypic selection [86].
Figure 2
Figure 2
Statistical analysis of mutable motifs in sites of somatic mutations and surrounding regions. The excess of mutations in motifs was calculated using the ratio Fm/Fn, where Fm is the fraction of somatic mutations observed in a given mutable motif (the number of mutated motifs divided by the number of mutations), and Fn is the frequency of the motif in the DNA neighborhood of somatic mutations (the number of motif positions divided by the total number of all un-mutated positions in the 120 bp window).
Figure 3
Figure 3
The DNA pol η mutational signature (Signature 9, http://cancer.sanger.ac.uk/cosmic/signatures).
Figure 4
Figure 4
APOBEC3A (A) and APOBEC3B-induced (B) mutation patterns in yeast genomes [56] shown as a logo (weblogo.berkeley.edu). The Position 6 is the mutable position.
Figure 5
Figure 5
The methylation ratio in WRCG mutable motifs and non-WRCG motifs (YCG/CGR and SNCG/CGNS) [32]. The fraction of motifs in each bin (0–20% methylation ratio, 20–40% methylation ratio, etc.) is shown.
Figure 6
Figure 6
Types of mutational clusters. Horizontal black lines, chromosome. Mutations resulting from damage to the top and bottom DNA strands are shown as lighter (red) and darker (blue) circles, respectively. Clusters are indicated by brackets. (A) Strong, clear cluster resulting from the action of ssDNA-specific mutagen on the resected DNA during DSB repair. (B) Cluster of moderate strength with mixed types of mutations. In this case, clusters of different size can be defined based on the threshold parameters of clustering algorithm (compare two brackets). (C) Six individual clones (e.g. cells, tumors or mutants microorganisms) are shown on top. No apparent clustering is observed except for one clone where two mutations of different types are located close to each other. However, on combining all data sets, prominent and likely strand-specific clustering is detected (bottom). This clustering likely represents the general susceptibility of the corresponding genomic region to the ssDNA-specific mutagen. (D) Example of clustering of intermediate power (compare with scheme on the Panel B). This cluster is found on chromosome X of yeast mutant clone induced by PmCDA1 deaminase [57]. Two clusters can be defined based on the algorithm parameters. Dark (blue) rectangles, heterozygous C >T substitutions, which result from deamination of cytosine in the top DNA strand; lighter (red) rectangles, heterozygous G>A substitutions, which result from deamination of cytosines in the bottom DNA strand. Genomic features, as well as chromosomal coordinates, are shown on top. (E) Example of cluster detected in silico by combining mutational data from independent yeast mutant clones induced by PmCDA1 deaminase. Each individual mutant possesses only a single SNV in this genomic region. However, merging data from several clones reveals a region of susceptibility to the mutagen. Color code and labels are as in the Panel D.
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