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Whole-genome landscapes of major melanoma subtypes

Abstract

Melanoma of the skin is a common cancer only in Europeans, whereas it arises in internal body surfaces (mucosal sites) and on the hands and feet (acral sites) in people throughout the world. Here we report analysis of whole-genome sequences from cutaneous, acral and mucosal subtypes of melanoma. The heavily mutated landscape of coding and non-coding mutations in cutaneous melanoma resolved novel signatures of mutagenesis attributable to ultraviolet radiation. However, acral and mucosal melanomas were dominated by structural changes and mutation signatures of unknown aetiology, not previously identified in melanoma. The number of genes affected by recurrent mutations disrupting non-coding sequences was similar to that affected by recurrent mutations to coding sequences. Significantly mutated genes included BRAF, CDKN2A, NRAS and TP53 in cutaneous melanoma, BRAF, NRAS and NF1 in acral melanoma and SF3B1 in mucosal melanoma. Mutations affecting the TERT promoter were the most frequent of all; however, neither they nor ATRX mutations, which correlate with alternative telomere lengthening, were associated with greater telomere length. Most melanomas had potentially actionable mutations, most in components of the mitogen-activated protein kinase and phosphoinositol kinase pathways. The whole-genome mutation landscape of melanoma reveals diverse carcinogenic processes across its subtypes, some unrelated to sun exposure, and extends potential involvement of the non-coding genome in its pathogenesis.

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Figure 1: Mutation burden.
Figure 2: Mutational processes.
Figure 3: Mutations and copy number changes in selected published melanoma driver genes.
Figure 4: Genes and signalling pathways recurrently altered in melanoma.

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Acknowledgements

This work was supported by Melanoma Institute Australia, Bioplatforms Australia, the New South Wales Ministry of Health, Cancer Council NSW, National Health and Medical Research Council of Australia (NHMRC), Cancer Institute NSW, Australian Cancer Research Foundation and the National Collaborative Research Infrastructure Strategy. N.K.H., Nicola W., R.A.S., J.S.W. and K.D.-R. were supported by NHMRC Fellowships, K.N. by a Keith Boden Fellowship, G.V.L. by the University of Sydney Medical Foundation, M.S. by Pfizer Australia, the Victorian Endowment for Knowledge, Science and Innovation and NHMRC, L.B.A. by a J. Robert Oppenheimer Fellowship at Los Alamos National Laboratory, and N.L.-B. by the European Research Council (Consolidator Grant 682398). Biobanking was supported by Melanoma Institute Australia, the Victorian Cancer Agency, Victorian Cancer Biobank, Victorian State Government Operational Infrastructure Support Program, Melanoma Research Alliance and the Melbourne Melanoma Project, and the efforts of patients, clinicians and other staff at health services across Australia. Cell lines were provided via the ABN-Oncology group, supported by NHMRC. Research at Los Alamos National Laboratory was under the auspices of the National Nuclear Security Administration of the US Department of Energy; the Los Alamos National Laboratory Institutional Computing Program was supported by contract DE-AC52-06NA25396. We acknowledge the support of colleagues at Melanoma Institute Australia, Royal Prince Alfred Hospital, NSW Health Pathology, Westmead Institute for Medical Research, Peter MacCallum Cancer Centre and Olivia Newton-John Cancer Research Institute. We thank D. Stetner for computing assistance.

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Authors and Affiliations

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P.A.J., M.A.F., K.N., A.-M.P., L.B.A., A.P., S.K., O.H., C.L., S.W., Q.X., Nick W. K.D.-R. and F.N. analysed genomic data; V.J., P.S., H.K., R.D.P.-I., V.T., G.M.P. and H.B. collected, prepared and analysed samples and data; L.M.S.L., R.A.D. and H.A.P. validated telomere length; L.M., R.S. and N.L.-B. analysed selection on coding and non-coding mutations; A.F., C.A.S., J.Y.Y. and S.-J.S. supported design and planning; J.V.P., Nicola W. and S.M.G. developed and directed the analysis pipeline; J.F.T., M.S., A.B., J.C., J.R.S., R.F.K., P.H., G.V.L., A.J.S., R.P.M.S. and R.E.V. collected samples and data; N.K.H., J.S.W., P.A.J., Nicola W., R.A.S. and G.J.M. designed and directed the study, analysed data and wrote the manuscript, which all authors reviewed.

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Correspondence to Graham J. Mann.

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Extended data figures and tables

Extended Data Figure 1 Copy number and ploidy in melanoma.

a, The proportions of each of the melanoma genomes (n = 183) that were affected by loss (copy number 1 or 0), copy neutral loss of heterozygosity (LOH) and high gain (at least six copies) are shown in the histogram. The melanoma subtype and degree of ploidy are illustrated in the colour bar beneath the histogram. b, c, GISTIC analysis was performed to determine significant regions of recurrent copy number change in the cutaneous (b, n = 140) and acral and mucosal (c, n = 43) tumours.

Extended Data Figure 2 Mutation signatures in melanoma.

Twelve mutation signatures in melanoma were identified taking into account the sequence context immediately before and after the mutation. Each signature is displayed showing the probability for each of the 96 mutation types. a, Three novel signatures, associated with ultraviolet radiation, were identified. These signatures perfectly recapitulate the ultraviolet radiation mutation signature previously extracted from exome sequencing data. Signature 7a is predominately C>T transitions occurring at TpC dinucleotides and, on the basis of similarity with the sequence context, it is most likely owing to the formation of 6,4-photoproducts. Signature 7b is described by C>T transitions at CpC dinucleotides. This sequence context is characteristic for the formation of cyclobutane pyrimidine dimers due to ultraviolet radiation exposure. Signature 7c has a high proportion of C>T substitutions, and high levels of T>C and T>A mutations, demonstrating the ability of ultraviolet radiation to generate both transitions and transversions. The underlying processes damaging DNA and resulting in signature 7c are currently unknown but they could potentially be due to indirect DNA damage. b, Of the nine non-ultraviolet radiation associated signatures, three (signatures 1, 5 and 17) have previously been observed in melanoma and six have been seen in other cancer types but not previously noted in melanoma. Signature 1 is the result of an endogenous mutational process initiated by spontaneous deamination of 5-methylcytosine and is associated with age of the patient. Signature 5 (aetiology unknown) was the dominant signature in tumours with no ultraviolet radiation signature; it is, together with signature 1, the most common signature, observed in diverse cancer types. Signature 17 (aetiology unknown) has been seen in melanoma previously and was here observed in 52 tumours (exclusively cutaneous and acrals). Signature 8 was one of the dominant signatures in tumours with no ultraviolet radiation signature (together with signatures 5 and 1); it has previously been observed in breast cancer and medulloblastoma and was evident in 39 melanomas. Signatures 2 and 13 have been attributed to activity of the AID/APOBEC family of cytidine deaminases and are often observed in the same samples; here, most non-ultraviolet samples showed both signatures, but the highest level of signature 2 was observed in a cluster of four samples in which signatures 2, 7a and 7c were observed. Signature 6 is associated with defective DNA mismatch repair and typically found in microsatellite-unstable tumours; it was observed in one melanoma in this cohort. Signature 18 has been observed frequently in neuroblastoma; it was identified in 13 melanomas. Signature R2 reflects a sequencing artefact.

Extended Data Figure 3 Structural variants clustering on chromosome 11 in acral melanoma.

a, The number and type of structural variant is shown for each tumour (n = 183). b, Chromosomes containing complex rearrangements are shown in red defined as chromosomes with a clustered arrangement of breakpoints (Kolmogorov–Smirnov goodness of fit test, P < 0.0001) and a high density of breakpoints (number of breakpoints exceeds the extreme threshold value of the upper quartile plus 5× interquartile range for the chromosomal distribution of breakpoints). The observed pattern of breakpoint clusters and copy number events was used to classify tumours as BFB-associated, complex, highly rearranged or no clusters of events. TERT promoter mutations are also shown. c, Patterns of structural variants and copy number in all acral melanomas that contained a cluster of structural variants on chromosome 11. Graphs show the most frequent translocations and other structural variants (copy number in red, gain; in green, loss).

Extended Data Figure 4 Fine structure of two structural variants.

a, Circos plot of MELA_0010 shows a cluster of structural variants on chromosomes 5 and 12. The outer coloured ring on the Circos plot represents each chromosome, the next ring is the copy number (red, gain; green, loss), the inner ring is the B-allele frequency, and the structural variants are shown by the lines in the centre of the plot. b, The cluster of rearrangements on chromosome 5 in MELA_0010 are shown from top to bottom: translocations (blue), all other rearrangements, copy number status, log(R ratio) and B-allele frequency. c, The cluster of rearrangements on chromosome 12 in MELA_0010 shows evidence of BFB with loss of telomeric region and inversions with increased copy number. d, Circos plot of MELA_0018 shows a cluster of structural rearrangements on chromosomes 5 and 18. e, f, The cluster of rearrangements in (e) MELA_0018 on chromosome 5 and (f) chromosome 18 are shown from top to bottom: translocations, all other rearrangements, copy number status, log(R ratio) and B-allele frequency.

Extended Data Figure 5 Complex structural rearrangements are frequent in acral melanomas.

Circos plots are shown for all acral melanomas (n = 35) in the study. The outer coloured ring on the Circos plot represents each chromosome, the next ring is the copy number (red, gain; green, loss), the inner ring is the B-allele frequency, and the structural variants are shown by the lines in the centre of the plot. Tumours that contain BFB events, complex rearrangements, highly rearranged genomes or those that contain no clusters of structural variants are indicated.

Extended Data Figure 6 Telomere length and TERT promoter mutations.

a, The relative melanoma telomere length in each tumour compared with the matched normal (n = 183). b, Verification of telomere length in 31 samples by PCR. c, The telomere length was not associated with melanoma subtype (cutaneous, n = 140; acral or mucosal, n = 43). d, Somatic mutations in the promoter of the TERT gene were detected by WGS and/or by capillary sequencing. Mutations were found at −57, −124, −138 and −146 from the ATG site. eg, Tumours with TERT promoter mutations were associated with (Mann–Whitney U-test) (e) telomere length, (f) the number of structural rearrangements and (g) the number of mutations per megabase.

Extended Data Figure 7 Recurrent DPH3, NFKBIE, RPS27 and PES1 promoter mutations.

Height and colour of sticks indicate recurrence and mutant base, respectively. Tandem mutations are indicated with black horizontal bars. a, Recurrent mutations in promoter of DPH3 at loci 8 bp (n = 20), 9 bp (n = 22) and 12 bp (n = 3) upstream from the transcription start site. The ETS transcription factor family core motif is shaded in grey. b, Recurrent mutation (n = 5) at chr6:44,233,400 in the first exon of NFKBIE-001 isoform and 129 bases upstream from the transcription start site of NFKBIE-004, which typically is the expressed transcript in most tissue, including melanoma. Four novel mutations were identified a further 500 kb upstream. c, Recurrent mutations on and upstream from the transcription start site of RPS27. d, Recurrent mutations upstream of PES1.

Extended Data Figure 8 BRAF, RAS and NF1 mutations.

a, b, BRAF somatic mutations were identified in 86 of the 183 samples (47%). V600E substitutions accounted for 48 (56%) of these mutations. Other activating mutations at codons 600 and 601 were less frequent (V600K, n = 17; V600R, n = 2; V600D, n = 1; K601E, n = 2). c, d, NRAS was mutated in 51 (28%) tumours; 49 of these mutations occurred at ‘hotspot’ codons 12, 13 or 61. e, HRAS mutations occurred in eight tumours, five of which were in ‘hotspot’ codons 12, 13 or 61. f, KRAS mutations occurred in four tumours, but none occurred at the commonly activating hotspot codons. g, NF1 aberrations occurred throughout the gene in 32 of 183 (17%) tumours and included point mutations/small indels only (15 nonsense, 1 frameshift, 3 splice site and 4 missense). Structural variants predicted to cause loss of function were frequent within NF1 (structural variant breakpoints indicated by reverse arrows). Some rearrangements were associated with a copy number change (green, loss; red, gain).

Extended Data Figure 9 Candidate RAF1 gene fusions.

WGS data were used to identify genomic rearrangements that could result in a gene fusion product. a, The RAF1 gene and protein are shown. b, A RAF1 gene fusion was detected with a small transcript of CDH3. The gene fusion is expected to produce a protein that retains the ref1 kinase domain. c, A RAF1–GOLGA4 gene fusion was detected, which is expected to produce a protein that retains the ref1 kinase domain. d, Integrative Genomics Viewer view of RAF1–GOLGA4 gene fusion. DNA breakpoints (purple arrows) are marked by discordantly aligned red coloured read pairs that are in an incorrect orientation and too far apart. There is no matching evidence observed in the normal control sample. Supportive evidence for an expressed gene fusion is visible in RNA sequencing data (bottom horizontal panel) where discordantly aligned reads are highlighted in turquoise and the orientation of a junction fusion between exon 11 of GOLGA4 and exon 8 of RAF1 is indicated by the green arrow.

Extended Data Figure 10 Alterations to potentially actionable genes in cutaneous and non-cutaneous melanomas.

Proportion of samples with a somatic variant containing a gene that confers sensitivity to a US Food and Drug Administration-approved or therapeutic agent being used in a clinical trial (in any cancer): non-silent substitution or indel (SNV/indel; dark blue); both SNV/indel and structural variants (light red); structural variants only (dark red) or copy number variation, high-level amplification (green); and deletions (light blue). Genes are ordered by the difference between the frequencies of mutated genes (excluding copy number variation) in cutaneous (n = 140) versus non-cutaneous (n = 43) melanomas, with genes with a higher mutation frequency in cutaneous melanomas on the left.

Supplementary information

Supplementary Table 1

This file contains clinical and mutation data. (XLSX 103 kb)

Supplementary Table 2

This file contains coding mutations (SNV and indel) in melanoma (MAF). This file corrupted and was replaced by a zipped version on the 5 June 2017 to fix the corruption error. (ZIP 12287 kb)

Supplementary Table 3

This file contains structural rearrangements in melanoma. (XLSX 11532 kb)

Supplementary Table 4

This file contains gene promoters frequently mutated in melanoma. (XLSX 140 kb)

Supplementary Table 5

This file contains recurrent 5’ UTR mutations in melanoma. (XLSX 62 kb)

Supplementary Table 6

This file contains recurrent 3’ UTR mutations in melanoma. (XLSX 55 kb)

Supplementary Table 7

This file contains significantly mutated genes. (XLSX 14 kb)

Supplementary Table 8

This file contains the key to Fig 3b: Significantly mutated genes and selected published melanoma driver genes. (XLSX 11 kb)

Supplementary Table 9

This file contains perturbed pathways in melanoma. (XLSX 24 kb)

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Hayward, N., Wilmott, J., Waddell, N. et al. Whole-genome landscapes of major melanoma subtypes. Nature 545, 175–180 (2017). https://doi.org/10.1038/nature22071

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