Clustered Mutations in Human Cancer


Mutations are the frequent cause of cancer. They are mostly viewed as independent events distributed randomly across chromosomes. However, mutation distribution can be affected by permanent or transient features of genome structure and function. The extreme form of nonrandom distributions is a mutation cluster with multiple mutations concentrated in a tiny fraction of the genome. Multiple lesions in abnormally long regions of transient single‐stranded deoxyribonucleic acid (DNA) can cause mutation clusters, which have been found in a majority of human cancer types. Mutation spectra indicated that many clusters in cancer genomes were caused by a subclass of apolipoprotein B mRNA‐editing polypeptide‐like (APOBEC) cytidine deaminases. These enzymes function to restrict retroviruses and retrotransposons by converting cytidine to uridine in single‐stranded complementary DNAs (cDNAs). The simple mutation spectra in clusters aided in highlighting APOBECs among the complex set of mutagenic mechanisms operating throughout many cancer genomes. Thus, clusters are an analytical tool for deciphering cancer mutation mechanisms.

Key Concepts:

  • Mutation clusters are unusually tightly spaced groups of mutations.

  • Error‐prone translesion synthesis across multiple lesions in single‐stranded DNA is a mechanism of clustered mutagenesis.

  • Mutation clusters have been found across many types of human cancers.

  • Strand‐coordinated clusters can be a tool for deciphering mutagenic mechanisms operating in cancer.

  • Mutations in C‐ or G‐coordinated clusters in human cancers are caused by a subclass of APOBEC cytidine deaminases normally serving to restrict viral and endogenous retroelements.

  • APOBEC‐induced mutation clusters as well as single mutations are widespread through many types of human cancers.

Keywords: APOBEC ; mutation cluster; kataegis; DNA damage; DNA repair; hypermutation

Figure 1.

Clusters can result from hypermutation in long regions of ssDNA. (a) DSB followed by 5'→3' degradation (resection) eliminates one DNA strand, thus leaving regions of ssDNA around a DSB. DNA lesions could occur in both ssDNA (yellow stars) and dsDNA (grey stars). DSB with long resected ends can be repaired by homologous recombination with a sister chromatid or with an ectopic homologous region elsewhere in the genome. Shown are short oligonucleotides used to repair artificially created DSB in yeast (Yang et al., ). Restoration to dsDNA involves error‐prone TLS. Mutations generated by error‐prone TLS (blue squares) can be copied by excision repair of lesions (not shown), creating mutant sequence in the second DNA strand. Mutagenic lesions from an agent with base specificity could result in a single type of base mutated exclusively (or predominantly) on one side of the break (strand‐coordinated mutations). Note that this same base specificity would switch to a complementary base on the other side of the break. Indeed, such ‘switching’ mutation clusters were observed in Roberts et al. (). (b) ssDNA can be generated by resection at a telomere that has lost its protein cap. Modelling this process, a controlled transient uncapping allowing 5′→3′ resection has been achieved by shifting a temperature‐sensitive cdc13–1 yeast mutant to nonpermissive temperature (Yang et al., ; Burch et al., ; Chan et al., ). Returning yeast to permissive temperature after applying DNA damage allowed restoration of normal dsDNA at the telomere in a process that involved error‐prone TLS and resulted in mutation clusters. (c) Transient ssDNA can be formed at dysfunctional replication forks, if synthesis of one out of two nascent strands is uncoupled from the proceeding of the replicative helicase. In support of this mechanism, switching of mutation strand specificity in mutation clusters was observed in the yeast strains lacking TOF1 (homologue of hTIMELESS) or CSM3 (homologue of hTIPIN) responsible for the replication fork integrity (Roberts et al., ).

Figure 2.

Mutation clusters in yeast. (a) An example of complete strand coordination of mutations in clusters obtained by controlled telomere uncapping combined with transient expression of APOBEC3G cytidine deaminase in cdc13–1 yeast strains lacking uracil‐DNA glycolsylase (Ung1) (reproduced from Figure 3B of Chan et al., , with modifications). Each thin horizontal line represents a cluster. Small black circles represent individual base substitutions identified in a strand that was transiently lacking the complement. All mutations are C→T in agreement with cytidines being converted to uridines by APOBEC3G and after round of replication being cemented as thymidines in the progeny DNA. Also shown are the positions of open reading frames composing the multigene mutation reporter and distances from the left tip of chromosome V. (b) An example of a mutation cluster found by whole‐genome sequencing of a yeast cell isolated after growth for approximately 25 generations in the presence of alkylating agent methyl methanesulfonate (Roberts et al., ). Thick vertical blue lines represent yeast chromosomes sized proportional to DNA length. Thin yellow lines across chromosomes show positions of mutations. Several lines depicting mutations in a cluster as well as in some other genomic positions are merging because of close positioning. © PLoS.

Figure 3.

Bioinformatics analysis used to identify mutation clusters and cluster‐associated mutation signatures (Roberts et al., ). (a) Detection and classification of mutation clusters. The first step involves filtering out complex mutations, most of which are composed of several very closely spaced changes caused by a single lesion. The second step highlights groups of closely spaced mutations defined as clusters by intermutation distance and the probability to occur by random genomic positioning of the mutations in a dataset. Mutations identical to small nucleotide polymorphisms (SNPs) previously found in the human population (dbSNPs) as well as mutations falling into a SimpleRepeat track (‐bin/hgTrackUi?hgsid=204690969&c=chr8&g=simpleRepeat) are excluded from whole‐genome cluster detection, because they have a greater chance to represent germ line mutations or false positive mutation calls, respectively. Altogether these two categories rarely exceed 15% of all mutation calls. For exome mutation data, where mutation calls are based on very high coverage, only dbSNPs were excluded. (b) Enrichment with the APOBEC mutation signature. Analysis can be applied to the whole‐genome or exome mutation catalogues as well as to a defined part of a catalogue (e.g. to C‐ or G‐coordinated mutation clusters). The number of mutated nucleotides (shown in red) as well as the number of corresponding nucleotides and nucleotide motifs in the immediate (+/− 20 nt) vicinity of mutated bases is counted and used to calculate enrichment (E). MUTATIONS TCW→TTW or TCW→TGW : the number of mutations of cytosines to thymines or guanines in TCW context (including complements); MUTATIONS C→T or C→G : the number of mutations of cytosines to thymines or guanines; CONTEXT C : the number of cytosines (including complements) in the immediate vicinity of the mutated cytosines; CONTEXT TCW : the number of TCW motifs (including complements) in the immediate vicinity of mutated cytosines.

Figure 4.

Mutation clusters in cancers. (a) Mutation clusters identified by Roberts et al. in whole‐genome‐sequenced samples of multiple myelomas (Chapman et al., ), prostate adenocarcinomas (Berger et al., ), head and neck squamous cell carcinomas (HNSCC) (Stransky et al., ) and colorectal adenocarcinomas (Bass et al., ). Clusters are separated by type of strand coordination (‘A‐ or T‐’, ‘G‐ or C‐’ and ‘non’ coordinated). White bars indicate the number of clusters colocalised with breakpoint(s). The number of sequenced samples for each cancer type is shown in parentheses. Colocalisation (schematically shown in a box insert) was registered when the region covered by the cluster plus left and right flanks of 20 000 nucleotides contained at least one breakpoint. Black bars depict the number of clusters not associated with a specific breakpoint. (b) The distribution of mutations within 17 C‐coordinated clusters with greater than 3 mutations from multiple myeloma. Mutated cytosines are categorised by their presence in a TC motif (red diamonds), TCW motif (yellow highlighted red diamonds) or no identified motif (pink circles). Reproduced from Figure 6C of Roberts et al. (). © Cell Press. (c) An example of kataegis (mutation clusters) graphically represented as ‘rainfall’ plots. Each dot represents a single somatic mutation in a lung cancer sample. Dots are ordered on the horizontal axis according to the rank of the mutation's position in the human genome. The vertical axis denotes the genomic distance of each mutation from the previous mutation. Arrowheads indicate clusters of mutations in a kataegis event. Reproduced from Figure 6 of Alexandrov et al. () with modifications. © Nature Publishing Group.

Figure 5.

The APOBEC mutagenesis pattern is widespread across several types of human cancers. (a) The fold enrichment of the APOBEC mutagenesis signature as determined within each of 2680 whole‐exome‐sequenced tumours, representing 14 cancer types. Samples were first categorised by the statistical significance of the APOBEC mutation pattern (see Figure and text) and then by fold enrichment for samples with and FDR‐corrected q‐value <0.05. Pie charts show the distribution of fold‐enrichment categories within a given type. The colour code for fold‐enrichment categories is shown above the charts. Samples displaying Benjamini–Hochberg corrected q‐values >0.05 are represented in black. These samples are excluded from the scatter graphs. (b) Fractional load of APOBEC mutation signature. The colour scale to the right of the graph indicates the number of APOBEC signature mutations for samples with q<0.05. Horizontal dashed lines in (a) and (b) indicate effects expected for random mutagenesis. Cancer types are abbreviated as in TCGA. Abbreviations: CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; BLCA, bladder urothelial carcinoma; HNSC, head and neck squamous cell carcinoma; BRCA, breast invasive carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; UCEC, uterine corpus endometrioid carcinoma; OC, ovarian serous cystadenocarcinoma; STAD, stomach adenocarcinoma; READ, rectum adenocarcinoma; COAD, colon adenocarcinoma; PRAD, prostate adenocarcinoma; KIRC, kidney renal clear cell carcinoma; and LAML, acute myeloid leukaemia (LAML). Cancer types to the left of vertical solid line show statistically significant presence of samples with APOBEC mutagenesis pattern in Roberts et al. () as well as in Alexandrov et al. (). Cancer types to the right of vertical dashed line did not show statistically significant presence of samples with APOBEC mutagenesis pattern in Roberts et al. () as well as in Alexandrov et al. (). APOBEC mutagenesis pattern in UCEC was on the marginal level in Roberts et al. () analysis, whereas it was highlighted as carrying APOBEC mutation signature in Alexandrov et al. (). Reproduced from Figure 2 from Roberts et al. () with modification. © Nature Publishing Group.



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Roberts, Steven A, and Gordenin, Dmitry A(Jan 2014) Clustered Mutations in Human Cancer. In: eLS. John Wiley & Sons Ltd, Chichester. [doi: 10.1002/9780470015902.a0024941]