Tumour formation involves random mutagenic events and positive evolutionary selection acting on a subset of such events, referred to as driver mutations. A decade of careful surveying of tumour DNA using exome-based analyses has revealed a multitude of protein-coding somatic driver mutations, some of which are clinically actionable. Today, a transition towards whole-genome analysis is well under way, technically enabling the discovery of potential driver mutations occurring outside protein-coding sequences. Mutations are abundant in this vast non-coding space, which is more than 50 times larger than the coding exome, but reliable identification of selection signals in non-coding DNA remains a challenge. In this Review, we discuss recent findings in the field, where the emerging landscape is one in which non-coding driver mutations appear to be relatively infrequent. Nevertheless, we highlight several notable discoveries. We consider possible reasons for the relative absence of non-coding driver events, as well as the difficulties associated with detecting signals of positive selection in non-coding DNA.
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Huang, F. W. et al. Highly recurrent TERT promoter mutations in human melanoma. Science 339, 957–959 (2013).
Horn, S. et al. TERT promoter mutations in familial and sporadic melanoma. Science 339, 959–961 (2013). Together with Huang et al. (2013), this paper establishes non-coding somatic promoter mutations as a mechanism for oncogene activation.
Garraway, L. A. & Lander, E. S. Lessons from the cancer genome. Cell 153, 17–37 (2013).
The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 578, 82–93 (2020).
Rheinbay, E. et al. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature 578, 102–111 (2020). As the largest and most ambitious pan-cancer study of non-coding somatic mutations to date, this large consortium effort confirmed high prevalence of TERT promoter mutations in human cancer and also suggested additional lower-frequency candidates.
Ciriello, G. et al. Emerging landscape of oncogenic signatures across human cancers. Nat. Genet. 45, 1127–1133 (2013).
Corona, R. I. et al. Non-coding somatic mutations converge on the PAX8 pathway in ovarian cancer. Nat. Commun. 11, 2020 (2020).
Hnisz, D. et al. Activation of proto-oncogenes by disruption of chromosome neighborhoods. Science 351, 1454–1458 (2016). This paper establishes disrupted chromatin domain structure as a mechanism for oncogene activation.
Schuster, S. L. & Hsieh, A. C. The untranslated regions of mRNAs in cancer. Trends Cancer 5, 245–262 (2019).
Shuai, S. et al. The U1 spliceosomal RNA is recurrently mutated in multiple cancers. Nature 574, 712–716 (2019).
Suzuki, H. et al. Recurrent noncoding U1 snRNA mutations drive cryptic splicing in SHH medulloblastoma. Nature 574, 707–711 (2019). Together with Shuai et al. (2019), this paper reports a rare functional somatic mutation in a non-coding RNA.
Belkadi, A. et al. Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc. Natl Acad. Sci. USA 112, 5473–5478 (2015).
Zhang, X. & Meyerson, M. Illuminating the noncoding genome in cancer. Nat. Cancer 1, 864–872 (2020).
Khurana, E. et al. Role of non-coding sequence variants in cancer. Nat. Rev. Genet. 17, 93–108 (2016).
Stratton, M. R., Campbell, P. J. & Futreal, P. A. The cancer genome. Nature 458, 719–724 (2009).
Van den Eynden, J., Basu, S. & Larsson, E. Somatic mutation patterns in hemizygous genomic regions unveil purifying selection during tumor evolution. PLoS Genet. 12, e1006506 (2016).
Martincorena, I. et al. Universal patterns of selection in cancer and somatic tissues. Cell 171, 1029–1041.e21 (2017).
McFarland, C. D., Korolev, K. S., Kryukov, G. V., Sunyaev, S. R. & Mirny, L. A. Impact of deleterious passenger mutations on cancer progression. Proc. Natl Acad. Sci. USA 110, 2910–2915 (2013).
Supek, F. & Lehner, B. Scales and mechanisms of somatic mutation rate variation across the human genome. DNA Repair 81, 102647 (2019).
Schuster-Bockler, B. & Lehner, B. Chromatin organization is a major influence on regional mutation rates in human cancer cells. Nature 488, 504–507 (2012).
Supek, F. & Lehner, B. Differential DNA mismatch repair underlies mutation rate variation across the human genome. Nature 521, 81–84 (2015).
Zheng, C. L. et al. Transcription restores DNA repair to heterochromatin, determining regional mutation rates in cancer genomes. Cell Rep. 9, 1228–1234 (2014).
Polak, P. et al. Cell-of-origin chromatin organization shapes the mutational landscape of cancer. Nature 518, 360–364 (2015).
Alexandrov, L. et al. Signatures of mutational processes in human cancer. Nature 500, 415–421 (2013). This paper established the concept of mutational signatures, which are helpful when detecting signals of selection in mutation data and are useful for studying mutational processes active in tumours.
Ikehata, H. & Ono, T. The mechanisms of UV mutagenesis. J. Radiat. Res. 52, 115–125 (2011).
Lawrence, M. S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013).
Gonzalez-Perez, A., Sabarinathan, R. & Lopez-Bigas, N. Local determinants of the mutational landscape of the human genome. Cell 177, 101–114 (2019).
Frigola, J. et al. Reduced mutation rate in exons due to differential mismatch repair. Nat. Genet. 49, 1684–1692 (2017).
Weinhold, N., Jacobsen, A., Schultz, N., Sander, C. & Lee, W. Genome-wide analysis of noncoding regulatory mutations in cancer. Nat. Genet. 46, 1160–1165 (2014).
Fredriksson, N. J., Ny, L., Nilsson, J. A. & Larsson, E. Systematic analysis of noncoding somatic mutations and gene expression alterations across 14 tumor types. Nat. Genet. 46, 1258–1263 (2014).
Denisova, E. et al. Frequent DPH3 promoter mutations in skin cancers. Oncotarget 6, 35922–35930 (2015).
Araya, C. L. et al. Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations. Nat. Genet. 48, 117–125 (2016).
Colebatch, A. J. et al. Clustered somatic mutations are frequent in transcription factor binding motifs within proximal promoter regions in melanoma and other cutaneous malignancies. Oncotarget 7, 66569–66585 (2016).
Fredriksson, N. J. et al. Recurrent promoter mutations in melanoma are defined by an extended context-specific mutational signature. PLoS Genet. 13, e1006773 (2017).
Mao, P. et al. ETS transcription factors induce a unique UV damage signature that drives recurrent mutagenesis in melanoma. Nat. Commun. 9, 2626 (2018).
Elliott, K. et al. Elevated pyrimidine dimer formation at distinct genomic bases underlies promoter mutation hotspots in UV-exposed cancers. PLoS Genet. 14, e1007849 (2018).
Sabarinathan, R., Mularoni, L., Deu-Pons, J., Gonzalez-Perez, A. & Lopez-Bigas, N. Nucleotide excision repair is impaired by binding of transcription factors to DNA. Nature 532, 264–267 (2016).
Perera, D. et al. Differential DNA repair underlies mutation hotspots at active promoters in cancer genomes. Nature 532, 259–263 (2016).
Teng, G. & Papavasiliou, F. N. Immunoglobulin somatic hypermutation. Annu. Rev. Genet. 41, 107–120 (2007).
Migliazza, A. et al. Frequent somatic hypermutation of the 5′ noncoding region of the BCL6 gene in B-cell lymphoma. Proc. Natl Acad. Sci. USA 92, 12520–12524 (1995).
Pasqualucci, L. et al. Hypermutation of multiple proto-oncogenes in B-cell diffuse large-cell lymphomas. Nature 412, 341–346 (2001).
Harris, R. S. & Liddament, M. T. Retroviral restriction by APOBEC proteins. Nat. Rev. Immunol. 4, 868–877 (2004).
Roberts, S. A. et al. Clustered mutations in yeast and in human cancers can arise from damaged long single-strand DNA regions. Mol. Cell 46, 424–435 (2012).
Nik-Zainal, S. et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature 534, 47–54 (2016).
Buisson, R. et al. Passenger hotspot mutations in cancer driven by APOBEC3A and mesoscale genomic features. Science 364, eaaw2872 (2019).
Wu, S. et al. Whole-genome sequencing identifies ADGRG6 enhancer mutations and FRS2 duplications as angiogenesis-related drivers in bladder cancer. Nat. Commun. 10, 720 (2019).
Sun, Y. & Ma, L. New insights into long non-coding RNA MALAT1 in cancer and metastasis. Cancers 11 (2), 216 (2019).
Klec, C., Prinz, F. & Pichler, M. Involvement of the long noncoding RNA NEAT1 in carcinogenesis. Mol. Oncol. 13, 46–60 (2019).
Wedge, D. C. et al. Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets. Nat. Genet. 50, 682–692 (2018).
Fujimoto, A. et al. Whole-genome mutational landscape and characterization of noncoding and structural mutations in liver cancer. Nat. Genet. 48, 500–509 (2016).
Li, S., Shuch, B. M. & Gerstein, M. B. Whole-genome analysis of papillary kidney cancer finds significant noncoding alterations. PLoS Genet. 13, e1006685 (2017).
Imielinski, M., Guo, G. & Meyerson, M. Insertions and deletions target lineage-defining genes in human cancers. Cell 168, 460–472 (2017).
[No authors listed] Cancer genome complexity made simple. Cancer Discov. 10, 480 (2020).
Cieslik, M. & Chinnaiyan, A. M. Global genomics project unravels cancer’s complexity at unprecedented scale. Nature 578, 39–40 (2020).
Li, B. S. et al. MicroRNA-25 promotes gastric cancer migration, invasion and proliferation by directly targeting transducer of ERBB2, 1 and correlates with poor survival. Oncogene 34, 2556–2565 (2015).
Arthur, S. E. et al. Genome-wide discovery of somatic regulatory variants in diffuse large B-cell lymphoma. Nat. Commun. 9, 4001 (2018).
Hornshoj, H. et al. Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival. NPJ Genom. Med. 3, 1 (2018).
Urbanek-Trzeciak, M. O. et al. Pan-cancer analysis of somatic mutations in miRNA genes. EBioMedicine 61, 103051 (2020).
Wang, W., Wei, Z., Lam, T. W. & Wang, J. Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions. Sci. Rep. 1, 55 (2011).
Rheinbay, E. et al. Recurrent and functional regulatory mutations in breast cancer. Nature 547, 55–60 (2017). This paper identifies recurrent functional promoter mutations in a cancer-relevant gene through promoter capture sequencing, highlighting the limitations of regular WGS.
Li, K. et al. Noncoding variants connect enhancer dysregulation with nuclear receptor signaling in hematopoietic malignancies. Cancer Discov. 10, 724–745 (2020).
Dabney, J. & Meyer, M. Length and GC-biases during sequencing library amplification: a comparison of various polymerase-buffer systems with ancient and modern DNA sequencing libraries. Biotechniques 52, 87–94 (2012).
Payne, J. L. & Wagner, A. Mechanisms of mutational robustness in transcriptional regulation. Front. Genet. 6, 322 (2015).
Bell, R. J. et al. Cancer. The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer. Science 348, 1036–1039 (2015).
Kircher, M. et al. Saturation mutagenesis of twenty disease-associated regulatory elements at single base-pair resolution. Nat. Commun. 10, 3583 (2019).
Jung, I. et al. A compendium of promoter-centered long-range chromatin interactions in the human genome. Nat. Genet. 51, 1442–1449 (2019).
Kim, K. et al. Chromatin structure-based prediction of recurrent noncoding mutations in cancer. Nat. Genet. 48, 1321–1326 (2016).
Zhou, S. et al. Noncoding mutations target cis-regulatory elements of the FOXA1 plexus in prostate cancer. Nat. Commun. 11, 441 (2020).
Castro-Giner, F., Ratcliffe, P. & Tomlinson, I. The mini-driver model of polygenic cancer evolution. Nat. Rev. Cancer 15, 680–685 (2015).
Sonawane, A. R. et al. Understanding tissue-specific gene regulation. Cell Rep. 21, 1077–1088 (2017).
Tiong, K. L. & Yeang, C. H. Explaining cancer type specific mutations with transcriptomic and epigenomic features in normal tissues. Sci. Rep. 8, 11456 (2018).
Mansour, M. R. et al. Oncogene regulation. An oncogenic super-enhancer formed through somatic mutation of a noncoding intergenic element. Science 346, 1373–1377 (2014). This paper uncovers an intriguing mechanism for oncogene activation involving de novo formation of a super-enhancer through short somatic indels.
Hu, S. et al. Whole-genome noncoding sequence analysis in T-cell acute lymphoblastic leukemia identifies oncogene enhancer mutations. Blood 129, 3264–3268 (2017).
Liu, Y. et al. Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X. Nat. Genet. 52, 811–818 (2020).
Puente, X. S. et al. Non-coding recurrent mutations in chronic lymphocytic leukaemia. Nature 526, 519–524 (2015).
Liu, E. M. et al. Identification of cancer drivers at CTCF insulators in 1,962 whole genomes. Cell Syst. 8, 446–455.e8 (2019).
Guo, Y. A. et al. Mutation hotspots at CTCF binding sites coupled to chromosomal instability in gastrointestinal cancers. Nat. Commun. 9, 1520 (2018).
Katainen, R. et al. CTCF/cohesin-binding sites are frequently mutated in cancer. Nat. Genet. 47, 818–821 (2015).
Poulos, R. C. et al. Functional mutations form at CTCF-cohesin binding sites in melanoma due to uneven nucleotide excision repair across the motif. Cell Rep. 17, 2865–2872 (2016).
Kaiser, V. B., Taylor, M. S. & Semple, C. A. Mutational biases drive elevated rates of substitution at regulatory sites across cancer types. PLoS Genet. 12, e1006207 (2016).
Zhu, H. et al. Candidate cancer driver mutations in distal regulatory elements and long-range chromatin interaction networks. Mol. Cell 77, 1307–1321.e10 (2020).
Bailey, S. D. et al. Noncoding somatic and inherited single-nucleotide variants converge to promote ESR1 expression in breast cancer. Nat. Genet. 48, 1260–1266 (2016).
Tate, J. G. et al. COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res. 47, D941–D947 (2019).
Vinagre, J. et al. Frequency of TERT promoter mutations in human cancers. Nat. Commun. 4, 2185 (2013).
Guo, Y. A., Chang, M. M. & Skanderup, A. J. MutSpot: detection of non-coding mutation hotspots in cancer genomes. NPJ Genom. Med. 5, 26 (2020).
Canver, M. C. et al. BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis. Nature 527, 192–197 (2015).
Rajagopal, N. et al. High-throughput mapping of regulatory DNA. Nat. Biotechnol. 34, 167–174 (2016).
Diao, Y. et al. A new class of temporarily phenotypic enhancers identified by CRISPR/Cas9-mediated genetic screening. Genome Res. 26, 397–405 (2016).
Diao, Y. et al. A tiling-deletion-based genetic screen for cis-regulatory element identification in mammalian cells. Nat. Methods 14, 629–635 (2017).
Fulco, C. P. et al. Systematic mapping of functional enhancer-promoter connections with CRISPR interference. Science 354, 769–773 (2016).
Korkmaz, G. et al. Functional genetic screens for enhancer elements in the human genome using CRISPR-Cas9. Nat. Biotechnol. 34, 192–198 (2016).
Sanjana, N. E. et al. High-resolution interrogation of functional elements in the noncoding genome. Science 353, 1545–1549 (2016).
Xie, S., Duan, J., Li, B., Zhou, P. & Hon, G. C. Multiplexed engineering and analysis of combinatorial enhancer activity in single cells. Mol. Cell 66, 285–299.e5 (2017).
Shuai, S. et al. Combined burden and functional impact tests for cancer driver discovery using DriverPower. Nat. Commun. 11, 734 (2020).
Lanzos, A. et al. Discovery of cancer driver long noncoding RNAs across 1112 tumour genomes: new candidates and distinguishing features. Sci. Rep. 7, 41544 (2017).
Lochovsky, L., Zhang, J., Fu, Y., Khurana, E. & Gerstein, M. LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations. Nucleic Acids Res. 43, 8123–8134 (2015).
Lochovsky, L., Zhang, J. & Gerstein, M. MOAT: efficient detection of highly mutated regions with the mutations overburdening annotations tool. Bioinformatics 34, 1031–1033 (2018).
Soltis, A. R., Dalgard, C. L., Pollard, H. B. & Wilkerson, M. D. MutEnricher: a flexible toolset for somatic mutation enrichment analysis of tumor whole genomes. BMC Bioinformatics 21, 338 (2020).
Juul, M. et al. ncdDetect2: improved models of the site-specific mutation rate in cancer and driver detection with robust significance evaluation. Bioinformatics 35, 189–199 (2019).
Mularoni, L., Sabarinathan, R., Deu-Pons, J., Gonzalez-Perez, A. & Lopez-Bigas, N. OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations. Genome Biol. 17, 128 (2016).
Umer, H. M. et al. A significant regulatory mutation burden at a high-affinity position of the CTCF motif in gastrointestinal cancers. Hum. Mutat. 37, 904–913 (2016).
Guilhamon, P. & Lupien, M. SMuRF: a novel tool to identify regulatory elements enriched for somatic point mutations. BMC Bioinformatics 19, 454 (2018).
Lawrence, M. S. et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 505, 495–501 (2014).
Hayflick, L. & Moorhead, P. S. The serial cultivation of human diploid cell strains. Exp. Cell Res. 25, 585–621 (1961).
Kim, N. W. et al. Specific association of human telomerase activity with immortal cells and cancer. Science 266, 2011–2015 (1994).
Meyerson, M. et al. hEST2, the putative human telomerase catalytic subunit gene, is up-regulated in tumor cells and during immortalization. Cell 90, 785–795 (1997).
Bouaoun, L. et al. TP53 variations in human cancers: new lessons from the IARC TP53 database and genomics data. Hum. Mutat. 37, 865–876 (2016).
Bell, R. J. et al. Understanding TERT promoter mutations: a common path to immortality. Mol. Cancer Res. 14, 315–323 (2016).
Killela, P. J. et al. TERT promoter mutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal. Proc. Natl Acad. Sci. USA 110, 6021–6026 (2013).
E.L. is supported by grants from the Knut and Alice Wallenberg Foundation, the Swedish Medical Research Council and the Swedish Cancer Society.
The authors declare no competing interests.
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COSMIC Cancer Gene Census: https://cancer.sanger.ac.uk/census
Driver Power: https://github.com/smshuai/DriverPower
UCSC Genome Browser: https://genome.ucsc.edu/
- Point mutations
Single-base changes in the genome.
Small insertions or deletions of DNA bases.
A distal regulatory region bound by transcription factors that aids recruitment of polymerases.
- Passenger mutations
DNA alterations that do not provide a growth advantage.
- Structural variants
Genomic alterations, such as gene duplications, translocations or inversions, affecting a large chromosomal segment, typically greater than 1 kb.
- Neutral selection
Neither positive nor negative selection, that is, lacking influence on cell fitness.
DNA in a tightly packed and condensed form, marked by H3K9 methylation.
- Cyclobutane pyrimidine dimer
The principal ultraviolet-induced DNA damage lesion, resulting from dimerization of neighbouring pyrimidines.
A small regulatory RNA (around 22 bp) that can alter gene expression through mRNA silencing.
- Topologically associating domain
A genomic segment showing a high degree of within-region physical interaction.
- COSMIC Cancer Gene Census
A list of approximately 700 genes known to be mutated and have functional roles in cancer, compiled from decades of research.
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Elliott, K., Larsson, E. Non-coding driver mutations in human cancer. Nat Rev Cancer 21, 500–509 (2021). https://doi.org/10.1038/s41568-021-00371-z