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. 2013 Sep;45(9):970-6.
doi: 10.1038/ng.2702. Epub 2013 Jul 14.

An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers

Steven A Roberts  1 , Michael S Lawrence, Leszek J Klimczak, Sara A Grimm, David Fargo, Petar Stojanov, Adam Kiezun, Gregory V Kryukov, Scott L Carter, Gordon Saksena, Shawn Harris, Ruchir R Shah, Michael A Resnick, Gad Getz, Dmitry A Gordenin
Affiliations

An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers

Steven A Roberts et al. Nat Genet. 2013 Sep.

Abstract

Recent studies indicate that a subclass of APOBEC cytidine deaminases, which convert cytosine to uracil during RNA editing and retrovirus or retrotransposon restriction, may induce mutation clusters in human tumors. We show here that throughout cancer genomes APOBEC-mediated mutagenesis is pervasive and correlates with APOBEC mRNA levels. Mutation clusters in whole-genome and exome data sets conformed to the stringent criteria indicative of an APOBEC mutation pattern. Applying these criteria to 954,247 mutations in 2,680 exomes from 14 cancer types, mostly from The Cancer Genome Atlas (TCGA), showed a significant presence of the APOBEC mutation pattern in bladder, cervical, breast, head and neck, and lung cancers, reaching 68% of all mutations in some samples. Within breast cancer, the HER2-enriched subtype was clearly enriched for tumors with the APOBEC mutation pattern, suggesting that this type of mutagenesis is functionally linked with cancer development. The APOBEC mutation pattern also extended to cancer-associated genes, implying that ubiquitous APOBEC-mediated mutagenesis is carcinogenic.

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Conflict of interest statement

Competing Financial Interests

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. APOBEC mutation pattern in clusters
a. Whole-genome datasets. Analysis of all clusters identified among 23 multiple myeloma, 2 head and neck squamous cell carcinoma, 7 prostate carcinoma and 9 colorectal adenocarcinoma datasets. Co-localization of clusters with breakpoints was identified as described in. The category “Close to breakpoints” includes clusters in which at least one mutation falls within 20 kb of a breakpoint. Fold-enrichment (shown above bars) of mutation motifs (mutated base is capitalized) was calculated for all three possible changes of C (or G) as described in On-line Methods. *** corresponds to Bonferroni-corrected q-values < 0.0001 as determined by a one-tailed Fisher’s Exact Test comparing the ratio of the number of C mutations at tCw and the number of C mutations not in the sequence tCw to the analogous ratio for all cytosines within a sample fraction of the genome. The bottom bar shows the numbers and fractions (above appropriate sections of the bar) of three different base substitutions of C (or G). b. Exome data sets. Analysis of clusters identified in 2,680 exomes of 14 different cancer types from TCGA as well as from other published sources, (see details in the On-line Methods). Format and calculations are the same as in (a).
Figure 2
Figure 2. The presence of an APOBEC mutation pattern in exome datasets of different cancer types
Cancer types are abbreviated as in TCGA: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), Bladder Urothelial Carcinoma (BLCA), Head and Neck squamous cell carcinoma (HNSC), Breast invasive carcinoma (BRCA), Lung adenocarcinoma (LUAD), Lung squamous cell carcinoma (LUSC), Uterine Corpus Endometrioid Carcinoma (UCEC), Ovarian serous cystadenocarcinoma (OV), Stomach adenocarcinoma (STAD), Rectum adenocarcinoma (READ), Colon adenocarcinoma (COAD), Prostate adenocarcinoma (PRAD), Kidney renal clear cell carcinoma (KIRC), and Acute Myeloid Leukemia (LAML). The fold enrichment (a) and mutation load (b) of the APOBEC mutation pattern was determined within each of 2,680 whole exome sequenced tumors, representing 14 cancer types. Samples were categorized by the statistical significance of the APOBEC mutation pattern (calculated by one-sided Fisher’s Exact Test comparing the ratio of the number of C→T or →G substitutions and complementary G→A or →C substitutions that occur in and out of the APOBEC _target motif (tCw/wGa) to an analogous ratio for all cytosines or guanines that reside inside and outside of the tCw/wGa motif within a sample fraction of the genome; Benjamini-Hochberg corrected q-value < 0.05) and the magnitude of enrichment. The number of tumor samples in each category is presented on each pie graph in (a). Samples displaying q-values > 0.05 are represented in black. These samples are excluded from the scatter graphs in (a) and (b) that depict the range of enrichments and fractional mutation load, respectively. Color scales indicate the magnitude of enrichment (a) and the number of APOBEC signature mutations (b) for samples with q<0.05. Dashed lines indicate effects expected for random mutagenesis.
Figure 3
Figure 3. APOBEC transcription level positively correlates with the number of APOBEC signature mutations
RNA-seq derived mRNA levels of each APOBEC family member with documented deaminase activity on DNA was standardized relative to TATA-binding protein (TBP). “APOBEC mutations” refers to number of tCw to tTw and tCw to tGw changes. (a) The expression (relative to TBP) of APOBEC3A and 3B was compared to the total number of APOBEC mutations in each exome (blue circles) among 483 breast cancers (“in BRCA”) and 2048 total tumor samples (“in All”) with available RNA-seq data by non-parametric Spearman correlation. Graphs display log transformed values with mutation values augmented by 0.5 to allow depiction of exomes with no observed APOBEC-signature mutations. Spearman coefficients and corresponding q-values (two-sided; corrected for multiple testing error by the Bonferroni method) are indicated. Black lines represent linear regressions. Correlation data for other APOBECs and individual cancer types are shown in Supplementary Figure 11. (b) APOBEC3B transcription relative to TBP in 2048 tumor samples separated by cancer type. Horizontal bars indicate the median expression level within a cancer type. Dashed grey line indicates the median APOBEC3B expression among all cancers analyzed. *** indicates that APOBEC3B expression in a cancer type is elevated (q<0.001 by pairwise two-sided Mann-Whitney comparison of a specific cancer type to the overall distribution and corrected for multiple analyses by the Bonferroni method). Color scales indicate the number of APOBEC-signature mutations in each individual exome. Individual cancer types are abbreviated as in Fig. 2.
Figure 4
Figure 4. APOBEC mutation pattern in exome datasets of four breast cancer subtypes
Cancer types are abbreviated as: luminal A (Lum A), Basal-like, luminal B (Lum B), and HER2-enriched (HER2E). The fold enrichment (a) and mutation load (b) of the APOBEC mutation pattern was determined within each of 507 whole-exome sequenced BRCA tumors. The number of samples above (blue) and below (red) the median for all 507 exomes (dashed red lines) was determined for each cancer subtype. The horizontal black bars indicate the median in each subtype. *** indicates that a cancer type is significantly enriched in samples containing a high presence of the APOBEC mutation pattern (q<0.001 by pairwise two-sided Chi-square comparison of a specific cancer type to the overall distribution and corrected for analysis of multiple subtypes by the Bonferroni method). Color scales indicate the magnitude of enrichment (a) and the number of APOBEC-signature mutations (b).
Figure 5
Figure 5. APOBEC signature mutations among potential cancer drivers
a. The fraction of potential cancer driving mutations that display an APOBEC signature was determined for samples with high (q-value for the enrichment of the APOBEC mutation pattern less than or equal to 0.05; see Fig. 2) and low (q-value >0.05) presence of an exome-wide APOBEC mutation pattern. Mutations were designated as potential cancer drivers by one of three criteria: 1) mutations displaying a Benjamini-Hochberg corrected q-value < 0.05 after CRAVAT analysis 2) mutations that are listed within the COSMIC database and 3) mutations that impact a subset of genes in the Cancer Gene Census whose alteration by missense or nonsense mutations can contribute to cancer. *** indicates p < 0.0001 for a two-sided Chi-square comparing the number of APOBEC and Non-APOBEC signature mutations among potential cancer drivers in samples with high and low presence of the APOBEC mutation pattern for a given criteria defining a driver. Corresponding analysis for non-driver mutations is provided for comparison. The specific mutated genes are presented in Supplementary Table 5.
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Comment in

  • Genetics: APOBEC-a double-edged sword.
    Razzak M. Razzak M. Nat Rev Clin Oncol. 2013 Sep;10(9):488. doi: 10.1038/nrclinonc.2013.138. Epub 2013 Jul 30. Nat Rev Clin Oncol. 2013. PMID: 23897082 No abstract available.
  • APOBEC3B mutagenesis in cancer.
    Kuong KJ, Loeb LA. Kuong KJ, et al. Nat Genet. 2013 Sep;45(9):964-5. doi: 10.1038/ng.2736. Nat Genet. 2013. PMID: 23985681 Free PMC article.
  • Genomics: Mutator catalogues.
    Alderton GK. Alderton GK. Nat Rev Cancer. 2013 Oct;13(10):681. doi: 10.1038/nrc3608. Nat Rev Cancer. 2013. PMID: 24060860 No abstract available.

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