A paper published online today in Nature Genetics reports that the DNA-specific cytidine deaminase APOBEC3A (or A3A) is likely to be the major driver of APOBEC-mediated mutagenesis in human cancer. This finding is somewhat surprising because another deaminase, APOBECA3B (or A3B), has been considered the more likely mutator based on previous studies. Gene expression levels of APOBEC3B as well as mutagenic signatures in certain cancer types, such as breast cancer, have been consistent with a primary role for A3B in cancer-related mutagenesis. However, results of a recent paper by Serena Nik-Zainal et al. called this into question by showing that breast cancer samples from individuals with germline APOBEC3B deletions showed high levels of mutations consistent with APOBEC-dependent mutagensis.
Now, Dmitry Gordenin and colleagues expressed either A3A or A3B in a yeast reporter strain that allowed them to collect large numbers of mutations induced by these enzymes. Mutations were identified using whole genome sequencing and compared between the two enzymes. They were able to demonstrate that A3A and A3B induce mutations at specific genomic sequence motifs that could be reliably differentiated. Surprisingly, A3A tended to induce many more mutations than A3B, approximately 10-fold more. With the mutagenic signatures of the two enzymes at hand, they were able to show that A3A contributes to APOBEC-dependent mutagenesis in human cancers and may in fact be the primary driver of these mutations.
Click the link below for a video summary of the paper (created in collaboration with the authors):
We asked two authors of the paper, Kin Chan and Dmitry Gordenin, to give us a little more background about this exciting new research:
Given that APOBEC3A is expressed at relatively low levels in cancer samples (compared to APOBEC3B), what motivated you to study the potential role of APOBEC3A in cancer rather than any of the other APOBECs?
From the very beginning, we did not have very much hope that the level of mRNA in tumors at the time of surgical excision would correlate strongly with the detected number of mutations induced by APOBECs in these tumors, because mutations detectable by sequencing would have formed much earlier. We showed that mutation load was only weakly correlated with transcript abundances of both APOBEC3A and APOBEC3B. In fact, we did not particularly favor the APOBEC3A versus APOBEC3B dichotomy model with respect to the identity of the major mutator in cancers when we started our yeast experiments. We just wanted to get more precise estimates of their signatures in our yeast system, which was designed to enrich for accumulation of multiple APOBEC-induced mutation clusters as well as detecting scattered mutations.
Why do you think the distinct signature of APOBEC3A was not identified in previous studies, for example the study by Taylor et al.?
In fact, Taylor et al. did notice differences between mutation signatures of single-strand (ss) DNA-specific APOBEC3A and APOBEC3B cytidine deaminases separately expressed in yeast. However, they had significantly fewer mutations caused by APOBEC3A, which is less of a mutator as compared to APOBEC3B in the proliferating yeast used in that study. Our yeast system was devised to enable the facile study of mutations induced by APOBECs in stretches of ssDNA formed during growth of yeast cultures, along with mutations caused in long persistent stretches of subtelomeric ssDNA formed in response to regulated telomere uncapping. The latter form of ssDNA is hypermutable by APOBECs, which results in formation of mutation clusters (also called kataegis by other groups) that are so characteristic of hypermutation caused by APOBECs in human cancers. It is worth noting that Taylor et al. noticed that some samples of breast cancer had mutation spectra resembling that induced by APOBEC3A, while other spectra were more similar to APOBEC3B’s. However, the statistical approach they used did not provide sufficient power to highlight individual samples with statistically significant enrichment for certain mutation signatures.
A significant factor to our success was the use of an analytical design described in our previous papers (Roberts et al. 2012 and Roberts et al. 2013). The essential idea of this design is that it uses all available mechanistic knowledge emerging from our yeast experiments and from studies of other labs to formulate a stringent statistical hypothesis, which is then used to interrogate cancer datasets. This approach allowed us to compute robust sample-specific p-values even for exome mutation catalogues, which contain around 1% of mutation numbers characteristic of the whole genome mutation load.
Were you surprised by the result that APOBEC3A may be responsible for ten times more mutations in cancer than APOBEC3B?
We certainly were, because when we made this discovery we were thinking that APOBEC3B was more likely to be the major mutator in cancers. But upon re-reading the literature, the finding that APOBEC3A is actually the culprit makes sense: Three groups had independently shown that ectopic overexpression of APOBEC3A causes many DNA breaks while similar overexpression of APOBEC3B made much, much fewer breaks. We think that an important reason for APOBEC3A’s mutagenic prevalence in cancers is that some of these breaks are repaired by mechanisms generating long ssDNA intermediates—in other words, APOBEC3A substrates. This would also be consistent with previous observations that APOBEC-signature mutation clusters frequently co-localized with chromosomal rearrangement breakpoints in cancers.
What are your biggest unanswered questions related to this study?
It is clearly the question about what molecular mechanisms underlie this strong bias towards APOBEC3A in cancer hypermutation. However, this may require years of studies by many excellent labs that have already developed and continue to productively explore this field. Our work not only highlighted the strong influence of APOBEC3A in cancer mutagenesis, but also confirmed that APOBEC3B makes its own contribution, perhaps in even more cancers than APOBEC3A. We are interested to explore new larger data sets of cancer mutations becoming available through the recently announced Pan-cancer Analysis of Whole Genomes project to elucidate the roles of these APOBECs in different cancer types, stages of cancer development and regions of cancer genomes.
How do you see others using these results, either in research or in the clinic?
We hope very much that our findings will stimulate development of new assays to measure protein levels of individual APOBECs in cancers, which may turn out to be a better predictor of hypermutation and of clinically important tumor features. APOBEC3A- and APOBEC3B-specific antibodies required for such assays are still to be developed. Another important area is biochemical studies of both enzymes, which may clarify why one of them can cause DNA breakage, while the other does so only inefficiently. It will also be interesting to identify the interacting proteins that keep APOBEC3A in the cytosol of healthy cells, as this could lead directly to the reasons for APOBEC3A essentially going rogue and entering the nucleus to hypermutate genomic DNA in cancers.
As for clinical applications, determining the APOBEC mutagenesis signature of a tumor could inform decision making on personalized medicine: a tumor where APOBEC3A is actively causing hypermutation might have to be treated very differently from a tumor where there is only APOBEC3B background levels of mutagenesis. Screening for APOBEC signature mutagenesis in cell-free DNA for individuals at high risk (for example, patients with germline deletion of APOBEC3B) might be a useful early warning diagnostic in the near future. Also, it’s straightforward to propose that a specific APOBEC3A inhibitor might be of value for personalized medicine, more so than a broad-spectrum APOBEC inhibitor, which would likely severely compromise innate immune function. In a more speculative sense, the idea of overexpressing an APOBEC in order to kill cancer by hypermutation catastrophe has been around for a while in the field. The latest news in cancer research is that some hypermutated cancers are more susceptible to immune treatment than tumors with lower mutation loads. The suggested explanation is in the creation of neo-antigens that trigger immune attack on the tumor. Interestingly, therapeutic overexpression of APOBEC3A might combine this hypermutation effect with DNA breakage – a feature of several established cancer drugs.