Cancer genomes harbor numerous genomic alterations and many cancers accumulate thousands of nucleotide sequence variations. A prominent fraction of these mutations arises as a consequence of the off-target activity of DNA/RNA editing cytosine deaminases followed by the replication/repair of edited sites by DNA polymerases (pol), as deduced from the analysis of the DNA sequence context of mutations in different tumor tissues. We have used the weight matrix (sequence profile) approach to analyze mutagenesis due to Activation Induced Deaminase (AID) and two error-prone DNA polymerases. Control experiments using shuffled weight matrices and somatic mutations in immunoglobulin genes confirmed the power of this method. Analysis of somatic mutations in various cancers suggested that AID and DNA polymerases η and θ contribute to mutagenesis in contexts that almost universally correlate with the context of mutations in A:T and G:C sites during the affinity maturation of immunoglobulin genes. Previously, we demonstrated that AID contributes to mutagenesis in (de)methylated genomic DNA in various cancers. Our current analysis of methylation data from malignant lymphomas suggests that driver genes are subject to different (de)methylation processes than non-driver genes and, in addition to AID, the activity of pols η and θ contributes to the establishment of methylation-dependent mutation profiles. This may reflect the functional importance of interplay between mutagenesis in cancer and (de)methylation processes in different groups of genes. The resulting changes in CpG methylation levels and chromatin modifications are likely to cause changes in the expression levels of driver genes that may affect cancer initiation and/or progression.

Center for Collaborative Research in Health Disparities RCMI Program University of Puerto Rico San Juan Puerto Rico

Coordinating Center for Clinical Trials National Cancer Institute National Institutes of Health Bethesda MD United States

Department Microbiology and Molecular Genetics University of California Davis Davis CA United States

Department of Genetics and Biotechnology Saint Petersburg State University Saint Petersburg Russia

Department of Microbiology and Pathology Biochemistry and Molecular Biology Genetics Cell Biology and Anatomy University of Nebraska Medical Center Omaha NE United States

Department of Pathology and Molecular Medicine School of Medicine Queen's University Kingston ON Canada

Eppley Institute for Research in Cancer and Allied Diseases Omaha NE United States

Institute of Medical Genetics Cardiff University Cardiff United Kingdom

Integrated Informatics Services Core RCMI University of Puerto Rico San Juan Puerto Rico

Life Science Research Centre Faculty of Science University of Ostrava Ostrava Czechia

Martsinovsky Institute of Medical Parasitology Tropical and Vector Borne Diseases Sechenov 1st Moscow State Medical University Moscow Russia

National Center for Biotechnology Information National Library of Medicine National Institutes of Health Bethesda MD United States

Zobrazit více v PubMed

Alexandrov L. B., Kim J., Haradhvala N. J., Huang M. N., Tian Ng A. W., Wu Y., et al. (2020). The repertoire of mutational signatures in human cancer. Nature 578 94–101. PubMed PMC

Alexandrov L. B., Nik-Zainal S., Wedge D. C., Aparicio S. A., Behjati S., Biankin A. V., et al. (2013). Signatures of mutational processes in human cancer. Nature 500 415–421. PubMed PMC

Alexandrov L. B., Stratton M. R. (2014). Mutational signatures: the patterns of somatic mutations hidden in cancer genomes. Curr. Opin. Genet. Dev. 24 52–60. 10.1016/j.gde.2013.11.014 PubMed DOI PMC

Alsøe L., Sarno A., Carracedo S., Domanska D., Dingler F., Lirussi L., et al. (2017). Uracil accumulation and mutagenesis dominated by cytosine deamination in CpG dinucleotides in mice lacking UNG and SMUG1. Sci. Rep. 7:7199. PubMed PMC

Arana M. E., Seki M., Wood R. D., Rogozin I. B., Kunkel T. A. (2008). Low-fidelity DNA synthesis by human DNA polymerase theta. Nucleic Acids Res. 36 3847–3856. 10.1093/nar/gkn310 PubMed DOI PMC

Bhattacharya P., Grigera F., Rogozin I. B., McCarty T., Morse H. C., III, Kenter A. L. (2008). Identification of murine B cell lines that undergo somatic hypermutation focused to A:T and G:C residues. Eur. J. Immunol. 38 227–239. 10.1002/eji.200737664 PubMed DOI PMC

Brambati A., Barry R. M., Sfeir A. (2020). DNA polymerase theta (Polθ) - an error-prone polymerase necessary for genome stability. Curr. Opin. Genet. Dev. 60 119–126. 10.1016/j.gde.2020.02.017 PubMed DOI PMC

Brinkman A. B., Nik-Zainal S., Simmer F., Rodriguez-Gonzalez F. G., Smid M., Alexandrov L. B., et al. (2019). Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation. Nat. Commun. 10:1749. PubMed PMC

Brown A. L., Li M., Goncearenco A., Panchenko A. R. (2019). Finding driver mutations in cancer: elucidating the role of background mutational processes. PLoS Comput. Biol. 15:e1006981. 10.1371/journal.pcbi.1006981 PubMed DOI PMC

Casali P., Pal Z., Xu Z., Zan H. (2006). DNA repair in antibody somatic hypermutation. Trends Immunol. 27 313–321. 10.1016/j.it.2006.05.001 PubMed DOI PMC

Cheng F., Zhao J., Zhao Z. (2016). Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes. Brief. Bioinform. 17 642–656. 10.1093/bib/bbv068 PubMed DOI PMC

Cooper D. N., Youssoufian H. (1988). The CpG dinucleotide and human genetic disease. Hum Genet 78 151–155. 10.1007/bf00278187 PubMed DOI

Coulondre C., Miller J. H., Farabaugh P. J., Gilbert W. (1978). Molecular basis of base substitution hotspots in Escherichia coli. Nature 274 775–780. 10.1038/274775a0 PubMed DOI

Dietlein F., Weghorn D., Taylor-Weiner A., Richters A., Reardon B., Liu D., et al. (2020). Identification of cancer driver genes based on nucleotide context. Nat. Genet. 52 208–218. 10.1038/s41588-019-0572-y PubMed DOI PMC

Dörner T., Lipsky P. E. (2001). Smaller role for pol η? Nat. Immunol. 2 982–984. 10.1038/ni1101-982 PubMed DOI

Dunaway K. W., Islam M. S., Coulson R. L., Lopez S. J., Vogel Ciernia A., Chu R. G., et al. (2016). Cumulative impact of polychlorinated biphenyl and large chromosomal duplications on DNA methylation, chromatin, and expression of autism candidate genes. Cell Rep. 17 3035–3048. 10.1016/j.celrep.2016.11.058 PubMed DOI PMC

Geisheker M. R., Heymann G., Wang T., Coe B. P., Turner T. N., Stessman H. A. F., et al. (2017). Hotspots of missense mutation identify neurodevelopmental disorder genes and functional domains. Nat. Neurosci. 20 1043–1051. 10.1038/nn.4589 PubMed DOI PMC

Gelfand M. S. (1995). Prediction of function in DNA sequence analysis. J. Comput. Biol. 2 87–115. 10.1089/cmb.1995.2.87 PubMed DOI

Geschwind D. H., State M. W. (2015). Gene hunting in autism spectrum disorder: on the path to precision medicine. Lancet. Neurol. 14 1109–1120. 10.1016/s1474-4422(15)00044-7 PubMed DOI PMC

Goncearenco A., Rager S. L., Li M., Sang Q. X., Rogozin I. B., Panchenko A. R. (2017). Exploring background mutational processes to decipher cancer genetic heterogeneity. Nucleic Acids Res. 45 W514–W522. PubMed PMC

Granadillo Rodriguez M., Flath B., Chelico L. (2020). The interesting relationship between APOBEC3 deoxycytidine deaminases and cancer: a long road ahead. Open Biol. 10:200188. 10.1098/rsob.200188 PubMed DOI PMC

Green M. R., Kihira S., Liu C. L., Nair R. V., Salari R., Gentles A. J., et al. (2015). Mutations in early follicular lymphoma progenitors are associated with suppressed antigen presentation. Proc. Natl. Acad. Sci. U.S.A. 112 E1116–E1125. PubMed PMC

Howe E. A., Sinha R., Schlauch D., Quackenbush J. (2011). RNA-Seq analysis in MeV. Bioinformatics 27 3209–3210. 10.1093/bioinformatics/btr490 PubMed DOI PMC

Islam S. M. A., Alexandrov L. B. (2021). Bioinformatic methods to identify mutational signatures in cancer. Methods Mol. Biol. 2185 447–473. 10.1007/978-1-0716-0810-4_28 PubMed DOI

Jiao X., Sherman B. T., Huang D. W., Stephens R., Baseler M. W., Lane H. C., et al. (2012). DAVID-WS: a stateful web service to facilitate gene/protein list analysis. Bioinformatics 28 1805–1806. 10.1093/bioinformatics/bts251 PubMed DOI PMC

Loohuis L. O., Witzel A., Mishra B. (2014). Improving detection of driver genes: power-law null model of copy number variation in cancer. IEEE/ACM Trans. Comput. Biol. Bioinform. 11 1260–1263. 10.1109/tcbb.2014.2351805 PubMed DOI

Luque-Baena R. M., Urda D., Gonzalo Claros M., Franco L., Jerez J. M. (2014). Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords. J. Biomed. Inform. 49 32–44. 10.1016/j.jbi.2014.01.006 PubMed DOI

Martomo S. A., Saribasak H., Yokoi M., Hanaoka F., Gearhart P. J. (2008). Reevaluation of the role of DNA polymerase θ in somatic hypermutation of immunoglobulin genes. DNA Repair 7 1603–1608. 10.1016/j.dnarep.2008.04.002 PubMed DOI PMC

Matsuda T., Bebenek K., Masutani C., Rogozin I. B., Hanaoka F., Kunkel T. A. (2001). Error rate and specificity of human and murine DNA polymerase eta. J. Mol. Biol. 312 335–346. PubMed

Mayorov V. I., Rogozin I. B., Adkison L. R., Gearhart P. J. (2005). DNA polymerase eta contributes to strand bias of mutations of A versus T in immunoglobulin genes. J. Immunol. 174 7781–7786. 10.4049/jimmunol.174.12.7781 PubMed DOI

Milstein C., Neuberger M. S., Staden R. (1998). Both DNA strands of antibody genes are hypermutation targets. Proc. Natl. Acad. Sci. U.S.A. 95 8791–8794. 10.1073/pnas.95.15.8791 PubMed DOI PMC

Neri F., Rapelli S., Krepelova A., Incarnato D., Parlato C., Basile G., et al. (2017). Intragenic DNA methylation prevents spurious transcription initiation. Nature 543 72–77. 10.1038/nature21373 PubMed DOI

Neuberger M. S., Rada C. (2007). Somatic hypermutation: activation-induced deaminase for C/G followed by polymerase η for A/T. J. Exp. Med. 204 7–10. 10.1084/jem.20062409 PubMed DOI PMC

Oliver J., Garcia-Aranda M., Chaves P., Alba E., Cobo-Dols M., Onieva J. L., et al. (2021). Emerging noninvasive methylation biomarkers of cancer prognosis and drug response prediction. Semin. Cancer. Biol. 10.1016/j.semcancer.2021.03.012 PubMed DOI

Pavlov Y. I., Rogozin I. B., Galkin A. P., Aksenova A. Y., Hanaoka F., Rada C., et al. (2002). Correlation of somatic hypermutation specificity and A-T base pair substitution errors by DNA polymerase η during copying of a mouse immunoglobulin κ light chain transgene. Proc. Natl. Acad. Sci. U.S.A. 99 9954–9959. 10.1073/pnas.152126799 PubMed DOI PMC

Petljak M., Alexandrov L. B. (2016). Understanding mutagenesis through delineation of mutational signatures in human cancer. Carcinogenesis 37 531–540. 10.1093/carcin/bgw055 PubMed DOI

Pham P., Calabrese P., Park S. J., Goodman M. F. (2011). Analysis of a single-stranded DNA-scanning process in which activation-induced deoxycytidine deaminase (AID) deaminates C to U haphazardly and inefficiently to ensure mutational diversity. J. Biol. Chem. 286 24931–24942. 10.1074/jbc.m111.241208 PubMed DOI PMC

Pilzecker B., Jacobs H. (2019). Mutating for good: DNA damage responses during somatic hypermutation. Front. Immunol. 10:438. 10.3389/fimmu.2019.00438 PubMed DOI PMC

Rahbari R., Wuster A., Lindsay S. J., Hardwick R. J., Alexandrov L. B., Turki S. A., et al. (2016). Timing, rates and spectra of human germline mutation. Nat. Genet. 48 126–133. 10.1038/ng.3469 PubMed DOI PMC

Revy P., Muto T., Levy Y., Geissmann F., Plebani A., Sanal O., et al. (2000). Activation-induced cytidine deaminase (AID) deficiency causes the autosomal recessive form of the hyper-IgM syndrome (HIGM2). Cell 102 565–575. 10.1016/s0092-8674(00)00079-9 PubMed DOI

Roberts S. A., Gordenin D. A. (2014). Hypermutation in human cancer genomes: footprints and mechanisms. Nat. Rev. Cancer 14 786–800. 10.1038/nrc3816 PubMed DOI PMC

Roberts S. A., Lawrence M. S., Klimczak L. J., Grimm S. A., Fargo D., Stojanov P., et al. (2013). An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat. Genet. 45 970–976. 10.1038/ng.2702 PubMed DOI PMC

Rogozin I. B., Diaz M. (2004). Cutting edge: DGYW/WRCH is a better predictor of mutability at G:C bases in Ig hypermutation than the widely accepted RGYW/WRCY motif and probably reflects a two-step activation-induced cytidine deaminase-triggered process. J. Immunol. 172 3382–3384. 10.4049/jimmunol.172.6.3382 PubMed DOI

Rogozin I. B., Gertz E. M., Baranov P. V., Poliakov E., Schaffer A. A. (2018a). Genome-wide changes in protein translation efficiency are associated with autism. Genome Biol. Evol. 10 1902–1919. 10.1093/gbe/evy146 PubMed DOI PMC

Rogozin I. B., Goncearenco A., Lada A. G., De S., Yurchenko V., Nudelman G., et al. (2018b). DNA polymerase η mutational signatures are found in a variety of different types of cancer. Cell Cycle 17 348–355. 10.1080/15384101.2017.1404208 PubMed DOI PMC

Rogozin I. B., Lada A. G., Goncearenco A., Green M. R., De S., Nudelman G., et al. (2016). Activation induced deaminase mutational signature overlaps with CpG methylation sites in follicular lymphoma and other cancers. Sci. Rep. 6:38133. PubMed PMC

Rogozin I. B., Pavlov Y. I., Bebenek K., Matsuda T., Kunkel T. A. (2001). Somatic mutation hotspots correlate with DNA polymerase eta error spectrum. Nat. Immunol. 2 530–536. 10.1038/88732 PubMed DOI

Rogozin I. B., Pavlov Y. I., Goncearenco A., De S., Lada A. G., Poliakov E., et al. (2018c). Mutational signatures and mutable motifs in cancer genomes. Brief. Bioinform. 19 1085–1101. PubMed PMC

Rogozin I. B., Roche-Lima A., Lada A. G., Belinky F., Sidorenko I. A., Glazko G. V., et al. (2019). Nucleotide weight matrices reveal ubiquitous mutational footprints of AID/APOBEC deaminases in human cancer genomes. Cancers 11:211. 10.3390/cancers11020211 PubMed DOI PMC

Sanders S. J., He X., Willsey A. J., Ercan-Sencicek A. G., Samocha K. E., Cicek A. E., et al. (2015). Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron 87 1215–1233. PubMed PMC

Scandaglia M., Barco A. (2019). Contribution of spurious transcription to intellectual disability disorders. J. Med. Genet. 56 491–498. 10.1136/jmedgenet-2018-105668 PubMed DOI

Seplyarskiy V. B., Soldatov R. A., Popadin K. Y., Antonarakis S. E., Bazykin G. A., Nikolaev S. I. (2016). APOBEC-induced mutations in human cancers are strongly enriched on the lagging DNA strand during replication. Genome Res. 26 174–182. 10.1101/gr.197046.115 PubMed DOI PMC

Shanak S., Helms V. (2020). DNA methylation and the core pluripotency network. Dev. Biol. 464 145–160. 10.1016/j.ydbio.2020.06.001 PubMed DOI

Sina A. A., Carrascosa L. G., Liang Z., Grewal Y. S., Wardiana A., Shiddiky M. J. A., et al. (2018). Epigenetically reprogrammed methylation landscape drives the DNA self-assembly and serves as a universal cancer biomarker. Nat. Commun. 9:4915. PubMed PMC

Soldatos T. G., Perdigao N., Brown N. P., Sabir K. S., O’Donoghue S. I. (2015). How to learn about gene function: text-mining or ontologies? Methods 74 3–15. 10.1016/j.ymeth.2014.07.004 PubMed DOI

Staden R. (1984). Computer methods to locate signals in nucleic acid sequences. Nucleic Acids Res. 12 505–519. 10.1093/nar/12.1part2.505 PubMed DOI PMC

Stratton M. R., Campbell P. J., Futreal P. A. (2009). The cancer genome. Nature 458 719–724. PubMed PMC

Swanton C., McGranahan N., Starrett G. J., Harris R. S. (2015). APOBEC enzymes: mutagenic fuel for cancer evolution and heterogeneity. Cancer Discov. 5 704–712. 10.1158/2159-8290.cd-15-0344 PubMed DOI PMC

Tokheim C., Karchin R. (2019). CHASMplus reveals the scope of somatic missense mutations driving human cancers. Cell Syst. 9 9–23. 10.1016/j.cels.2019.05.005 PubMed DOI PMC

Wang J. H., Zhao L. F., Lin P., Su X. R., Chen S. J., Huang L. Q., et al. (2014). GenCLiP 2.0: a web server for functional clustering of genes and construction of molecular networks based on free terms. Bioinformatics 30 2534–2536. 10.1093/bioinformatics/btu241 PubMed DOI

Wood R. D., Doublié S. (2016). DNA polymerase θ (POLQ), double-strand break repair, and cancer. DNA Repair 44 22–32. 10.1016/j.dnarep.2016.05.003 PubMed DOI PMC

Zan H., Shima N., Xu Z., Al-Qahtani A., Evinger Iii A. J., Zhong Y., et al. (2005). The translesion DNA polymerase θ plays a dominant role in immunoglobulin gene somatic hypermutation. EMBO J. 24 3757–3769. 10.1038/sj.emboj.7600833 PubMed DOI PMC