An APOBEC Cytidine Deaminase Mutagenesis Pattern is Widespread in Human Cancers

By S. Roberts, M. Lawrence, L. Klimczak, Sara A. Grimm, D. Fargo, P. Stojanov, Adam Kiezun, G. Kryukov, Scott L. Carter, G. Saksena and 5 more. Nature Genetics, 2013

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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.

Subfields: Cancer Research, Molecular Biology, Oncology

View Paper: https://www.semanticscholar.org/paper/064001d7e5f49ffbd77c3edb4e092f6f5b834db8

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Citations in the corpus

Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes (2020, background): “…list due to incomplete phasing sensitivity and read coverage, the database provides the most comprehensive set of estimates of MNV allele frequencies to date, valuable for further analysis of mutational mechanisms as well as the interpretation of MNVs in rare disease and cancer genomics 52,53 .”
Comprehensive Analysis of Hypermutation in Human Cancer (2017, positive): “…Hypermutation in Human Cancer, Cell (2017), https://doi.org/ 10.1016/j.cell.2017.09.048 of apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) family members, has been shown to result in increased levels of C to T transitions in a wide range of cancers (Roberts et al., 2013).”
Maftools: efficient and comprehensive analysis of somatic variants in cancer (2018, methodology): “For APOBEC-based enrichment analysis, we integrated the method described by Roberts et al. (2013) to estimate an enrichment score, which defines the strength of APOBEC-related mutagenic processes for every tumor sample in MAF.”
Clinical implications of the intrinsic molecular subtypes of breast cancer. (2015, background): “Interestingly, the HER2enriched subtype has been found uniquely enriched for tumours with high frequency of APOBEC3B-associated mutations [33].”
Integrated Genomic Characterization of Papillary Thyroid Carcinoma (2014, background): “Ten tumors with the highest mutation densities (>1/Mb) were enriched for mutations associated with the APOBEC process (Roberts et al., 2013) (Mann-Whitney p = 4 3 10 5), similar to bladder cancer (Cancer Genome Atlas Research Network, 2014).”
Chromothripsis and kataegis induced by telomere crisis (2015, neutral): “Second, the clusters exhibited a pronounced preference for C>T and C>G mutations occurring in a TpC context (Figures 6E and 6F), the classic signature of APOBEC3A/B activity (Roberts et al., 2013; Burns et al., 2013a; Burns et al., 2013b; reviewed in Roberts andGordenin, 2014).”
ImmPort: disseminating data to the public for the future of immunology (2014, background): “We and others have shown that integrating across publicly available datasets can yield important new diagnostics [19], drug targets [20], causal factors [21], and even new therapeutic uses for drugs [22, 23].”
Heterogeneity of genomic evolution and mutational profiles in multiple myeloma (2014, neutral): “Recent reports suggested that different processes are operative in MM 15–17 , but their relative representation in each sample, the dynamics of their contribution over time and their relation to clinical features are unknown.”
Spatial and temporal diversity in genomic instability processes defines lung cancer evolution (2014, background): “Moreover, while both exogenous mutational processes, such as smoking (10-12) and endogenous processes, such as upregulation of APOBEC cytidine deaminases (13-15), have been found to contribute to the large mutational burden in NSCLC, the temporal dynamics of these processes and their contribution to”