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Molecular Genomic Profiling of Melanocytic Nevi

  • Andrew J. Colebatch
    Correspondence
    Correspondence: Andrew J. Colebatch, Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia 2050.
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
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  • Peter Ferguson
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
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  • Felicity Newell
    Affiliations
    Queensland Institute of Medical Research, Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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  • Stephen H. Kazakoff
    Affiliations
    Queensland Institute of Medical Research, Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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  • Tom Witkowski
    Affiliations
    Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
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  • Alexander Dobrovic
    Affiliations
    Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia

    School of Cancer Medicine and Molecular Cancer Prevention Program, La Trobe University, Bundoora, Victoria, Australia

    Department of Clinical Pathology, University of Melbourne, Parkville, Victoria, Australia
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  • Peter A. Johansson
    Affiliations
    Queensland Institute of Medical Research, Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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  • Robyn P.M. Saw
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia

    Department of Melanoma and Surgical Oncology, Discipline of Surgery, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
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  • Jonathan R. Stretch
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
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  • Grant A. McArthur
    Affiliations
    Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia

    Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia
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  • Georgina V. Long
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia

    Royal North Shore Hospital, Sydney, New South Wales, Australia
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  • John F. Thompson
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia

    Department of Melanoma and Surgical Oncology, Discipline of Surgery, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
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  • Author Footnotes
    13 These authors contributed equally to this work.
    John V. Pearson
    Footnotes
    13 These authors contributed equally to this work.
    Affiliations
    Queensland Institute of Medical Research, Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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  • Author Footnotes
    13 These authors contributed equally to this work.
    Graham J. Mann
    Footnotes
    13 These authors contributed equally to this work.
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia

    Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
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  • Author Footnotes
    13 These authors contributed equally to this work.
    Nicholas K. Hayward
    Footnotes
    13 These authors contributed equally to this work.
    Affiliations
    Queensland Institute of Medical Research, Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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  • Author Footnotes
    13 These authors contributed equally to this work.
    Nicola Waddell
    Footnotes
    13 These authors contributed equally to this work.
    Affiliations
    Queensland Institute of Medical Research, Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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  • Author Footnotes
    13 These authors contributed equally to this work.
    Richard A. Scolyer
    Footnotes
    13 These authors contributed equally to this work.
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia

    Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
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  • Author Footnotes
    13 These authors contributed equally to this work.
    James S. Wilmott
    Footnotes
    13 These authors contributed equally to this work.
    Affiliations
    Melanoma Institute Australia, The University of Sydney, New South Wales, Australia

    Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
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  • Author Footnotes
    13 These authors contributed equally to this work.
Open ArchivePublished:February 14, 2019DOI:https://doi.org/10.1016/j.jid.2018.12.033
      The benign melanocytic nevus is the most common tumor in humans and rarely transforms into cutaneous melanoma. Elucidation of the nevus genome is required to better understand the molecular steps of progression to melanoma. We performed whole genome sequencing on a series of 14 benign melanocytic nevi consisting of both congenital and acquired types. All nevi had driver mutations in the MAPK signaling pathway, either BRAF V600E or NRAS Q61R/L. No additional definite driver mutations were identified. Somatic mutations in nevi with higher mutation loads showed a predominance of mutational signatures 7a and 7b, consistent with UVR exposure, whereas nevi with lower mutation loads (including all three congenital nevi) had a predominance of the ubiquitous signatures 1 and 5. Two nevi had mutations in promoter regions predicted to bind E26 transformation-specific family transcription factors, as well as subclonal mutations in the TERT promoter. This paper presents whole genome data from melanocytic nevi. We confirm that UVR is involved in the etiology of a subset of nevi. This study also establishes that TERT promoter mutations are present in morphologically benign skin nevi in subclonal populations, which has implications regarding the interpretation of this emerging biomarker in sensitive assays.

      Abbreviations:

      ddPCR (droplet digital PCR), WGS (whole genome sequencing)

      Introduction

      The melanocytic nevus, the commonest tumor occurring in humans, is a benign proliferation of melanocytes, which typically arises in the skin. Melanocytic nevi that are present at birth are designated as congenital nevi, while those arising after birth are termed acquired nevi. Although melanocytic nevi are considered biologically benign, a small proportion (annual rate of between <1 in 200,000 to 1 in 33,000 (
      • Tsao H.
      • Bevona C.
      • Goggins W.
      • Quinn T.
      The transformation rate of moles (melanocytic nevi) into cutaneous melanoma: a population-based estimate.
      ) transform to melanoma. Approximately 30% of melanomas arise within or adjacent to a pre-existing nevus (
      • Lin W.M.
      • Luo S.
      • Muzikansky A.
      • Lobo A.Z.
      • Tanabe K.K.
      • Sober A.J.
      • et al.
      Outcome of patients with de novo versus nevus-associated melanoma.
      ,
      • Pampena R.
      • Kyrgidis A.
      • Lallas A.
      • Moscarella E.
      • Argenziano G.
      • Longo C.
      A meta-analysis of nevus-associated melanoma: prevalence and practical implications.
      ), with genomic analysis confirming the clonal origin of melanomas from adjacent nevi (
      • Shain A.H.
      • Yeh I.
      • Kovalyshyn I.
      • Sriharan A.
      • Talevich E.
      • Gagnon A.
      • et al.
      The genetic evolution of melanoma from precursor lesions.
      ). As such, further genomic analysis of nevi is required to potentially elucidate the mechanisms that lead to transformation of a nevus to melanoma in a small but clinically significant subset of cases.
      Recent studies have demonstrated the frequent occurrence of noncoding driver mutations in cutaneous melanoma, including TERT promoter mutations (
      • Horn S.
      • Figl A.
      • Rachakonda P.S.
      • Fischer C.
      • Sucker A.
      • Gast A.
      • et al.
      TERT promoter mutations in familial and sporadic melanoma.
      ,
      • Huang F.W.
      • Hodis E.
      • Xu M.J.
      • Kryukov G.V.
      • Chin L.
      • Garraway L.A.
      Highly recurrent TERT promoter mutations in human melanoma.
      ), as well as other noncoding mutations occurring within promoters (
      • Fredriksson N.J.
      • Ny L.
      • Nilsson J.A.
      • Larsson E.
      Systematic analysis of noncoding somatic mutations and gene expression alterations across 14 tumor types.
      ,
      • Melton C.
      • Reuter J.A.
      • Spacek D.V.
      • Snyder M.
      Recurrent somatic mutations in regulatory regions of human cancer genomes.
      ,
      • Weinhold N.
      • Jacobsen A.
      • Schultz N.
      • Sander C.
      • Lee W.
      Genome-wide analysis of noncoding regulatory mutations in cancer.
      ). TERT promoter mutations are present in approximately 80% of cutaneous melanomas (
      The Cancer Genome Atlas Network
      Genomic classification of cutaneous melanoma.
      ,
      • Griewank K.G.
      • Murali R.
      • Puig-Butille J.A.
      • Schilling B.
      • Livingstone E.
      • Potrony M.
      • et al.
      TERT promoter mutation status as an independent prognostic factor in cutaneous melanoma.
      ,
      • Hayward N.K.
      • Wilmott J.S.
      • Waddell N.
      • Johansson P.A.
      • Field M.A.
      • Nones K.
      • et al.
      Whole-genome landscapes of major melanoma subtypes.
      ,
      • Heidenreich B.
      • Nagore E.
      • Rachakonda P.S.
      • Garcia-Casado Z.
      • Requena C.
      • Traves V.
      • et al.
      Telomerase reverse transcriptase promoter mutations in primary cutaneous melanoma.
      ) and are C→T transitions, occurring most commonly at one of two positions: chr5:1295228 or chr5:1295250, within the core promoter region. TERT promoter mutations create novel E26 transformation-specific transcription factor binding sites (
      • Bell R.J.
      • Rube H.T.
      • Kreig A.
      • Mancini A.
      • Fouse S.D.
      • Nagarajan R.P.
      • et al.
      Cancer. The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer.
      ,
      • Horn S.
      • Figl A.
      • Rachakonda P.S.
      • Fischer C.
      • Sucker A.
      • Gast A.
      • et al.
      TERT promoter mutations in familial and sporadic melanoma.
      ,
      • Huang F.W.
      • Hodis E.
      • Xu M.J.
      • Kryukov G.V.
      • Chin L.
      • Garraway L.A.
      Highly recurrent TERT promoter mutations in human melanoma.
      ), and promote melanoma cell survival and immortalization through increased telomerase activity, although in a manner that does not prevent telomere shortening (
      • Chiba K.
      • Lorbeer F.K.
      • Shain A.H.
      • McSwiggen D.T.
      • Schruf E.
      • Oh A.
      • et al.
      Mutations in the promoter of the telomerase gene TERT contribute to tumorigenesis by a two-step mechanism.
      ).
      TERT promoter mutations have not been detected in benign nevi (
      • Horn S.
      • Figl A.
      • Rachakonda P.S.
      • Fischer C.
      • Sucker A.
      • Gast A.
      • et al.
      TERT promoter mutations in familial and sporadic melanoma.
      ,
      • Shain A.H.
      • Yeh I.
      • Kovalyshyn I.
      • Sriharan A.
      • Talevich E.
      • Gagnon A.
      • et al.
      The genetic evolution of melanoma from precursor lesions.
      ,
      • Stark M.S.
      • Tan J.M.
      • Tom L.
      • Jagirdar K.
      • Lambie D.
      • Schaider H.
      • et al.
      Whole-exome sequencing of acquired nevi identifies mechanisms for development and maintenance of benign neoplasms.
      ,
      • Vinagre J.
      • Almeida A.
      • Populo H.
      • Batista R.
      • Lyra J.
      • Pinto V.
      • et al.
      Frequency of TERT promoter mutations in human cancers.
      ), suggesting that these mutations might be a useful biomarker of malignancy in melanocytic neoplasms. However, the genomic evaluation of melanocytic precursor lesions adjacent to melanoma indicates relatively early acquisition of TERT promoter mutations during progression from nevus to melanoma (
      • Shain A.H.
      • Yeh I.
      • Kovalyshyn I.
      • Sriharan A.
      • Talevich E.
      • Gagnon A.
      • et al.
      The genetic evolution of melanoma from precursor lesions.
      ,
      • Shain A.H.
      • Joseph N.M.
      • Yu R.
      • Benhamida J.
      • Liu S.
      • Prow T.
      • et al.
      Genomic and transcriptomic analysis reveals incremental disruption of key signaling pathways during melanoma evolution.
      ). In these two studies by
      • Shain A.H.
      • Yeh I.
      • Kovalyshyn I.
      • Sriharan A.
      • Talevich E.
      • Gagnon A.
      • et al.
      The genetic evolution of melanoma from precursor lesions.
      ,
      • Shain A.H.
      • Joseph N.M.
      • Yu R.
      • Benhamida J.
      • Liu S.
      • Prow T.
      • et al.
      Genomic and transcriptomic analysis reveals incremental disruption of key signaling pathways during melanoma evolution.
      melanocytic lesions with morphologic characteristics intermediate between benign nevi and melanomas, corresponding to the nosological entities of dysplastic nevi or melanocytomas, demonstrated TERT promoter mutations.
      In light of the possible significance of noncoding mutations in melanocytic tumor pathogenesis, we sought to comprehensively analyze the entire genomes of a set of benign melanocytic nevi, as well as to evaluate TERT promoter mutation status with maximum sensitivity (since the TERT promoter region is poorly covered by whole genome sequencing [WGS]). Although exome sequencing studies of nevi have been performed (
      • Melamed R.D.
      • Aydin I.T.
      • Rajan G.S.
      • Phelps R.
      • Silvers D.N.
      • Emmett K.J.
      • et al.
      Genomic characterization of dysplastic nevi unveils implications for diagnosis of melanoma.
      ,
      • Stark M.S.
      • Tan J.M.
      • Tom L.
      • Jagirdar K.
      • Lambie D.
      • Schaider H.
      • et al.
      Whole-exome sequencing of acquired nevi identifies mechanisms for development and maintenance of benign neoplasms.
      ), to the best of our knowledge, no WGS analysis of cutaneous nevi has been performed to date.

      Results and Discussion

      Single nucleotide variants in nevus genomes

      We performed WGS of 14 benign melanocytic nevi, of which 3 were congenital and 11 were acquired (Table 1). There were no dysplastic nevi in our study group. The WGS of nevi achieved a mean coverage of 50× (range 45–55×), and of blood samples achieved a mean coverage of 34× (range 28–40×). The total number of somatic single nucleotide variants in the nevus genomes ranged from 181 to 38,437 (median 665) or from 0.1 to 12.2 mutations per megabase. The total number of nonsynonymous mutations varied between 1 and 185 (median 4.5) per sample. The median nonsynonymous mutation load of this set is lower than previously published exome data sets of acquired nevi, with an intermediate range:
      • Stark M.S.
      • Tan J.M.
      • Tom L.
      • Jagirdar K.
      • Lambie D.
      • Schaider H.
      • et al.
      Whole-exome sequencing of acquired nevi identifies mechanisms for development and maintenance of benign neoplasms.
      found deleterious mutation loads of 13–340 (median 89) in cases that were a mix of benign and dysplastic nevi, and
      • Melamed R.D.
      • Aydin I.T.
      • Rajan G.S.
      • Phelps R.
      • Silvers D.N.
      • Emmett K.J.
      • et al.
      Genomic characterization of dysplastic nevi unveils implications for diagnosis of melanoma.
      found a range of 0–46 (median 19) in a set of 19 dysplastic nevi. The low or intermediate loads we identified in comparison to the other published sets are likely to be the result of decreased UV light exposure in our cohort and also the inclusion of congenital nevi and absence of dysplastic nevi.
      Table 1Clinical, pathologic and genetic features of 14 nevi
      CaseAge at excision, ySexSiteSize, mmCongenital/ acquiredArchitectural growth patternBRAF/NRASDeleterious mutations, nDonor ID
      Nevus 156MaleChinNAAcquiredDermalBRAF V600E61MELA_0775
      Nevus 215MaleThigh35CongenitalDermalNRAS Q61R1MELA_0769
      Nevus 316FemaleShoulder30CongenitalCompoundNRAS Q61R1MELA_0770
      Nevus 444MaleCheek8AcquiredDermalNRAS Q61R15MELA_0776
      Nevus 556MaleNANAAcquiredDermalBRAF V600E4MELA_0778
      Nevus 627MaleNeck8AcquiredCompoundBRAF V600E56MELA_0772
      Nevus 739MaleJawNAAcquiredCompoundBRAF V600E4MELA_0781
      Nevus 842FemaleChin3AcquiredCompoundBRAF V600E7MELA_0782
      Nevus 911MaleChin28CongenitalCompoundNRAS Q61L2MELA_0773
      Nevus 1036FemaleJawNAAcquiredDermalBRAF V600E2MELA_0783
      Nevus 1150FemaleTemple6AcquiredCompoundBRAF V600E117MELA_0784
      Nevus 1246FemaleFaceNAAcquiredDermalBRAF V600E4MELA_0785
      Nevus 1359MaleFaceNAAcquiredDermalBRAF V600E185MELA_0786
      Nevus 1431FemaleCheek7AcquiredDermalBRAF V600E5MELA_0787
      Abbreviation: NA, not applicable.
      The mean coverage of 50× in this study is sufficient to detect mutations fixed early in nevogenesis. However, this depth of sequencing coverage will not be able to detect somatic mutations arising within potential subclones at low allelic fractions.

      Driver mutations and noncoding mutations in nevi

      All sequenced nevi had activation of the MAPK pathway, with mutually exclusive mutations in either BRAF or NRAS: four nevi had NRAS mutations (three Q61R and one Q61K) and the remainder (n = 11) had BRAF V600E mutations. All three congenital nevi had NRAS mutations, consistent with prior reports (
      • Bauer J.
      • Curtin J.A.
      • Pinkel D.
      • Bastian B.C.
      Congenital melanocytic nevi frequently harbor NRAS mutations but no BRAF mutations.
      ,
      • Lu C.
      • Zhang J.
      • Nagahawatte P.
      • Easton J.
      • Lee S.
      • Liu Z.
      • et al.
      The genomic landscape of childhood and adolescent melanoma.
      ,
      • Melamed R.D.
      • Aydin I.T.
      • Rajan G.S.
      • Phelps R.
      • Silvers D.N.
      • Emmett K.J.
      • et al.
      Genomic characterization of dysplastic nevi unveils implications for diagnosis of melanoma.
      ).
      No other genes were recurrently mutated among the nevus samples. A collated list of putative driver mutations in melanoma (
      • Zhang T.
      • Dutton-Regester K.
      • Brown K.M.
      • Hayward N.K.
      The genomic landscape of cutaneous melanoma.
      ) was used to assess possible candidate driver mutations in nevi. Nevus case 13, an acquired dermal nevus occurring in a 59-year-old male, was the sample with the highest single nucleotide variant load and had a mutation at the NFKBIE hotspot (chr6:44233400) previously described in desmoplastic melanoma (
      • Shain A.H.
      • Garrido M.
      • Botton T.
      • Talevich E.
      • Yeh I.
      • Sanborn J.Z.
      • et al.
      Exome sequencing of desmoplastic melanoma identifies recurrent NFKBIE promoter mutations and diverse activating mutations in the MAPK pathway.
      ). No other putative driver mutations were identified.
      Previously annotated promoter mutations were evaluated in the nevi. These mutations occur in motifs within active promoters that match E26 transformation-specific transcription factor binding sites and are recurrently mutated in approximately 80% of cutaneous melanomas (
      • Colebatch A.J.
      • Di Stefano L.
      • Wong S.Q.
      • Hannan R.D.
      • Waring P.M.
      • Dobrovic A.
      • et al.
      Clustered somatic mutations are frequent in transcription factor binding motifs within proximal promoter regions in melanoma and other cutaneous malignancies.
      ). In nevus case 11, an acquired compound nevus occurring in a 50-year-old female, promoter mutations were present in SMUG1 and RPL13A; in nevus case 13, promoter mutations were present in C16orf91 and ARHGEF18. No other promoter mutations were present. Recent work has demonstrated that promoter mutations at E26 transformation-specific transcription factor binding sites are a unique signature of UVR that correlate with overall mutation burden (
      • Fredriksson N.J.
      • Elliott K.
      • Filges S.
      • Van den Eynden J.
      • Stahlberg A.
      • Larsson E.
      Recurrent promoter mutations in melanoma are defined by an extended context-specific mutational signature.
      ,
      • Mao P.
      • Brown A.J.
      • Esaki S.
      • Lockwood S.
      • Poon G.M.K.
      • Smerdon M.J.
      • et al.
      ETS transcription factors induce a unique UV damage signature that drives recurrent mutagenesis in melanoma.
      ). These mutations result from increased susceptability for cyclobutane pyrimidine dimer formation due to conformational changes induced in DNA by E26 transformation-specific binding, rather than decreased DNA repair at these sites (
      • Mao P.
      • Brown A.J.
      • Esaki S.
      • Lockwood S.
      • Poon G.M.K.
      • Smerdon M.J.
      • et al.
      ETS transcription factors induce a unique UV damage signature that drives recurrent mutagenesis in melanoma.
      ).

      Mutational signatures in nevi

      Recent large-scale genomics studies performed on a range of different cancer types have revealed multiple mutational signatures, many of which can be attributed to specific etiologic factors, such as carcinogens or DNA repair defects that are implicated in the pathogenesis of the tumor (
      • Alexandrov L.B.
      • Nik-Zainal S.
      • Wedge D.C.
      • Aparicio S.A.
      • Behjati S.
      • Biankin A.V.
      • et al.
      Signatures of mutational processes in human cancer.
      ). However, there is only very limited information currently available on mutational signatures in nevi and what exists is based on whole exome sequencing data (i.e., analyzing approximately 1% of the human genome).
      Our WGS study provided an opportunity to gain more in-depth insights into mutagenic processes important in the pathogenesis of nevi. There are currently 30 curated mutation signatures, defined as the base substitution frequency of each possible single nucleotide variant in the context of 3′ and 5′ flanking bases (yielding a matrix of 96 non-redundant substitutions). Signature 7 was detected in most nevi, accounting for up to 90% of the mutations identified (Figure 1). Signature 7 is dominated by C→T mutations located at dipyrimidine sites, and has been shown to be generated by UVR in vitro (
      • Nik-Zainal S.
      • Kucab J.E.
      • Morganella S.
      • Glodzik D.
      • Alexandrov L.B.
      • Arlt V.M.
      • et al.
      The genome as a record of environmental exposure.
      ). Signature 7 is also the dominant mutation signature present in cutaneous melanoma (
      • Hayward N.K.
      • Wilmott J.S.
      • Waddell N.
      • Johansson P.A.
      • Field M.A.
      • Nones K.
      • et al.
      Whole-genome landscapes of major melanoma subtypes.
      ) and has been found in acquired melanocytic nevi in a study analyzing exome sequence data (
      • Stark M.S.
      • Tan J.M.
      • Tom L.
      • Jagirdar K.
      • Lambie D.
      • Schaider H.
      • et al.
      Whole-exome sequencing of acquired nevi identifies mechanisms for development and maintenance of benign neoplasms.
      ).
      Figure thumbnail gr1
      Figure 1Nevus genome mutational signatures. (a) Absolute contribution of mutational signatures to overall single nucleotide variant count for each nevus. (b) Relative contribution of mutational signatures to total overall single nucleotide variant count for each nevus.
      A previous WGS study of melanoma further divided signature 7 into three signatures: 7a, 7b, and 7c, (
      • Hayward N.K.
      • Wilmott J.S.
      • Waddell N.
      • Johansson P.A.
      • Field M.A.
      • Nones K.
      • et al.
      Whole-genome landscapes of major melanoma subtypes.
      ). Based on the particular base pair substitutions and flanking bases, signature 7a is proposed to be due to 6,4-photoproducts, signature 7b due to cyclobutane pyrimidine dimers, and signature 7c due to indirect DNA damage after UVR. Analysis of the nevi using the subdivided signature 7 demonstrates that the highly mutated nevi are dominated by signatures 7a and 7b, with signature 7c in the three nevi with the highest mutation burdens (Figure 1), similar to the pattern identified in cutaneous melanoma (
      • Hayward N.K.
      • Wilmott J.S.
      • Waddell N.
      • Johansson P.A.
      • Field M.A.
      • Nones K.
      • et al.
      Whole-genome landscapes of major melanoma subtypes.
      ).
      Signatures 1 and 5 were elevated in tumors without evidence of signature 7, including the three congenital nevi. Signature 1 is related to spontaneous deamination of 5-methylcytosine and correlates with age. In contrast, the etiology behind signature 5 is currently unknown. From this study, there are two categories of nevi as distinguished by the mutational signatures observed in the genome: a UVR-high group defined by contributions of signatures 7a, 7b, and 7c, and a UVR-low group defined by signatures 1 and 5; the latter group includes congenital nevi. The UVR-high category, present in those nevi with elevated mutation loads, implies either that there is acquisition of additional mutations in nevi over time after they have initially formed, or that nevi arise from a highly mutated skin-resident melanocyte precursor cell. The former proposal contrasts with a model of nevi as cell cycle arrested senescent proliferations (
      • Michaloglou C.
      • Vredeveld L.C.
      • Soengas M.S.
      • Denoyelle C.
      • Kuilman T.
      • van der Horst C.M.
      • et al.
      BRAFE600-associated senescence-like cell cycle arrest of human naevi.
      ).

      TERT promoter mutations in nevi

      DNA was available from 13 nevi for analysis of the two common TERT promoter mutations using droplet digital PCR (ddPCR). Two nevi had detectable TERT promoter mutations: case 13, an acquired dermal nevus in a 59-year-old male, had a C250T mutation at 0.2% allele fraction (Figure 2), and case 11, an acquired compound nevus in a 50-year-old female had both a C228T mutation at 0.2% allelic fraction and a C250T mutation at 0.2% allelic fraction (Table 2, Table 3). Sanger sequencing of the TERT promoter region of all 14 samples failed to demonstrate mutations (data not shown). This study includes the demonstration of TERT promoter mutations in unequivocally benign nevi, which is, to our knowledge, previously unreported. Previous studies of TERT promoter mutations in benign nevi did not demonstrate either of the two common TERT promoter mutations (
      • Horn S.
      • Figl A.
      • Rachakonda P.S.
      • Fischer C.
      • Sucker A.
      • Gast A.
      • et al.
      TERT promoter mutations in familial and sporadic melanoma.
      ,
      • Shain A.H.
      • Yeh I.
      • Kovalyshyn I.
      • Sriharan A.
      • Talevich E.
      • Gagnon A.
      • et al.
      The genetic evolution of melanoma from precursor lesions.
      ,
      • Stark M.S.
      • Tan J.M.
      • Tom L.
      • Jagirdar K.
      • Lambie D.
      • Schaider H.
      • et al.
      Whole-exome sequencing of acquired nevi identifies mechanisms for development and maintenance of benign neoplasms.
      ,
      • Vinagre J.
      • Almeida A.
      • Populo H.
      • Batista R.
      • Lyra J.
      • Pinto V.
      • et al.
      Frequency of TERT promoter mutations in human cancers.
      ), while TERT promoter mutations were identified in “intermediate” melanocytic lesions (corresponding to dysplastic nevi) (
      • Shain A.H.
      • Yeh I.
      • Kovalyshyn I.
      • Sriharan A.
      • Talevich E.
      • Gagnon A.
      • et al.
      The genetic evolution of melanoma from precursor lesions.
      ). One reason for the difference of our results with previous studies is due to the much higher sensitivity of the ddPCR technique we utilized (
      • Colebatch A.J.
      • Witkowski T.
      • Waring P.M.
      • McArthur G.A.
      • Wong S.Q.
      • Dobrovic A.
      Optimizing amplification of the GC-rich TERT promoter region using 7-Deaza-dGTP for droplet digital PCR quantification of TERT promoter mutations.
      ) compared with the lower sensitivity of prior experimental techniques, such as Sanger sequencing or custom capture sequencing panels. ddPCR for TERT promoter mutations can detect mutant alleles down to an allele fraction of approximately 0.02% (
      • Colebatch A.J.
      • Witkowski T.
      • Waring P.M.
      • McArthur G.A.
      • Wong S.Q.
      • Dobrovic A.
      Optimizing amplification of the GC-rich TERT promoter region using 7-Deaza-dGTP for droplet digital PCR quantification of TERT promoter mutations.
      ), indicating that the identified promoter mutation in the two nevi are within the detection limits of the assay. Similar identification of TERT promoter mutations is already being utilized in some clinical pathology laboratories as a diagnostic adjunct test to assist in distinguishing melanomas from nevi, due to the presence of these mutations in the former and absence in the latter. The detection of TERT promoter mutations in benign lesions in our study, therefore, has implications for sensitive assays that may utilize this mutation as a biomarker of malignancy, in that low levels may be compatible with benign lesions.
      Figure thumbnail gr2
      Figure 2Example of droplet digital PCR droplets for TERT C250T and C250C in nevus 13. Blue droplets are classified as mutant only, green droplets as wild-type only, and orange droplets as double-mutant wild-type combined droplets.
      Table 2Droplet digital PCR results of TERT C228T mutation in 13 nevi
      Case no.TargetTotal droplets, nPositive droplets, nNegative droplets, ncpmP-value
      Result of Fisher's exact test comparing mutant droplets to wild-type controls.
      Nevus 1TERT C228T mut15,075315,0720.230.11
      Nevus 1TERT C228C wt15,0757,7787,297853.62
      Nevus 2TERT C228T mut14,411114,4100.080.641
      Nevus 2TERT C228C wt14,4118,2396,172997.61
      Nevus 3TERT C228T mut14,597214,5950.160.292
      Nevus 3TERT C228C wt14,5973,71210,885345.21
      Nevus 5TERT C228T mut14,546114,5450.080.644
      Nevus 5TERT C228C wt14,5466,3628,184676.63
      Nevus 6TERT C228T mut15,720115,7190.070.672
      Nevus 6TERT C228C wt15,7203,91411,806336.85
      Nevus 7TERT C228T mut16,328116,3270.070.685
      Nevus 7TERT C228C wt16,3286,4489,880591.02
      Nevus 8TERT C228T mut15,212115,2110.080.66
      Nevus 8TERT C228C wt15,2126,2688,944624.83
      Nevus 9TERT C228T mut15,176015,17601
      Nevus 9TERT C228C wt15,1766,1289,048608.44
      Nevus 10TERT C228T mut15,079115,0780.080.657
      Nevus 10TERT C228C wt15,0796,4208,659652.59
      Nevus 11TERT C228T mut17,34813117,2178.92<0.001
      Nevus 11TERT C228C wt17,34816,8045444,073.27
      Nevus 12TERT C228T mut30,812330,8090.110.392
      Nevus 12TERT C228C wt30,81215,57715,235828.6
      Nevus 14TERT C228T mut15,764015,76401
      Nevus 14TERT C228C wt15,7643,50512,259295.85
      Nevus 13TERT C228T mut14,954014,95401
      Nevus 13TERT C228C wt14,9544,12810,826380.03
      SK-MEL28
      SK-MEL28 is the wild-type control.
      TERT C228T mut175,73412175,7220.08NA
      SK-MEL28
      SK-MEL28 is the wild-type control.
      TERT C228C wt175,73465,709110,025550.9
      Abbreviations: cpm, copies per microliter; mut, mutant probe; wt, wild-type probe.
      1 Result of Fisher's exact test comparing mutant droplets to wild-type controls.
      2 SK-MEL28 is the wild-type control.
      Table 3Droplet digital PCR results of TERT C250T mutation in 13 nevi
      Case no.TargetTotal dropletsPositive dropletsNegative dropletscpmP-value
      Result of Fisher's exact test comparing mutant droplets to wild-type controls.
      Nevus 1TERT C250T mut12,777212,7750.180.311
      Nevus 1TERT C250C wt12,7776,1796,598777.51
      Nevus 2TERT C250T mut14,036314,0330.250.144
      Nevus 2TERT C250C wt14,0367,7696,267948.62
      Nevus 3TERT C250T mut15,120115,1190.080.709
      Nevus 3TERT C250C wt15,1203,92911,191354.01
      Nevus 5TERT C250T mut13,166413,1620.360.043
      Nevus 5TERT C250C wt13,1665,9037,263699.82
      Nevus 6TERT C250T mut15,393015,39301
      Nevus 6TERT C250C wt15,3933,89911,494343.63
      Nevus 7TERT C250T mut15,862015,86201
      Nevus 7TERT C250C wt15,8625,65410,208518.53
      Nevus 8TERT C250T mut12,998012,99801
      Nevus 8TERT C250C wt12,9985,9757,023724.24
      Nevus 9TERT C250T mut14,947014,94701
      Nevus 9TERT C250C wt14,9475,4889,459538.29
      Nevus 10TERT C250T mut13,453113,4520.090.669
      Nevus 10TERT C250C wt13,4535,6807,773645.35
      Nevus 11TERT C250T mut15,3491315,3361<0.001
      Nevus 11TERT C250C wt15,3494,69510,654429.55
      Nevus 12TERT C250T mut15,596215,5940.150.392
      Nevus 12TERT C250C wt15,5967,7437,853807.2
      Nevus 14TERT C250T mut16,287116,2860.070.733
      Nevus 14TERT C250C wt16,2873,54612,741288.87
      Nevus 13TERT C250T mut15,9691215,9570.88<0.001
      Nevus 13TERT C250C wt15,9694,43311,536382.56
      SK-MEL28
      SK-MEL28 is the wild-type control.
      TERT C250T mut78,524678,5180.09NA
      SK-MEL28
      SK-MEL28 is the wild-type control.
      TERT C250C wt78,52428,81249,712537.83
      Abbreviations: cpm, copies per microliter; mut, mutant probe; NA, not applicable; wt, wild-type probe.
      1 Result of Fisher's exact test comparing mutant droplets to wild-type controls.
      2 SK-MEL28 is the wild-type control.
      There are two potential explanations for the apparent presence of TERT promoter mutations in a small proportion of benign nevi. The first is that minor subclones with TERT promoter mutations may be present in certain nevi, and these may be part of the mechanism of transformation of benign nevi to melanoma, representing an early focus of transformation that cannot be demonstrated by current morphologic analysis. The presence of such subclones would be consistent with the presence of ongoing mutations in nevi, as discussed in “UVR-high” nevi. The second possibility is that the TERT promoter mutant subclones are contaminants from adjacent keratinocytes. Somatic mutations are present in sun-exposed, morphologically normal skin (
      • Martincorena I.
      • Campbell P.J.
      Somatic mutation in cancer and normal cells.
      ), although TERT has not been examined to date. The two nevi with TERT promoter mutations show evidence of prolonged UVR exposure, with a large contribution of signature 7 to the mutation profile of both. Moreover, the presence of promoter mutations at E26 transformation-specific binding sites in both samples is consistent with prior chronic UV irradiation (
      • Colebatch A.J.
      • Di Stefano L.
      • Wong S.Q.
      • Hannan R.D.
      • Waring P.M.
      • Dobrovic A.
      • et al.
      Clustered somatic mutations are frequent in transcription factor binding motifs within proximal promoter regions in melanoma and other cutaneous malignancies.
      ,
      • Fredriksson N.J.
      • Elliott K.
      • Filges S.
      • Van den Eynden J.
      • Stahlberg A.
      • Larsson E.
      Recurrent promoter mutations in melanoma are defined by an extended context-specific mutational signature.
      ). As such, the adjacent skin would be expected to harbor high mutation loads, which may include TERT promoter mutations. Further experiments are required to evaluate the existence of TERT promoter mutations in sun-exposed skin.
      Our study presents WGS analysis of benign cutaneous nevi and demonstrates that while their mutation load was generally very low, they all carried mutually exclusive driver mutations in MAPK oncogenes BRAF and NRAS. Mutation signature analysis defined two subclasses of nevi, one demonstrating a predominant UVR signature (signatures 7a, 7b, and 7c) and the other, which includes congenital nevi, lacking a UVR signature and driven by signatures 1 and 5. These findings substantially validate the results of prior studies that have investigated the mutational landscape of nevi. Furthermore, utilizing a highly sensitive ddPCR assay, TERT promoter mutations may occasionally be detected in acquired nevi, which has important implications for interpretation of TERT promoter assays being used as diagnostic adjunct testing in clinical practice for the diagnosis of histologically challenging melanocytic tumors.

      Materials and Methods

      Patient cohort

      Eighteen nevi from 18 patients were recruited for this study and all were lesions that were clinically longstanding, showed no clinical features suspicious for melanoma, and were excised for cosmetic reasons at the request of the patient. Following written informed consent, a portion (usually approximately 50%) of the nevus was fresh-frozen for genomic analysis. The remainder of the tumor was processed and evaluated routinely by conventional histopathology.

      Human nevus samples

      The fresh-frozen tissue and blood samples analyzed in the current study were obtained from The Melanoma Institute Australia biospecimen bank with written informed patient consent and Institutional Review Board approval (The Sydney Local Health District Human Research Ethics Committee, Protocol No. X15-0454 and HREC/11/RPAH/444). Cases were selected based on clinical and pathological confirmation of a diagnosis of a benign nevus. Congenital nevi were diagnosed when there was a documented history that they were present at birth.
      Of the 18 nevi obtained for analysis, 2 cases were excluded due to having BRAF mutation allele fractions <5% by ddPCR, while 2 other cases had <100 single nucleotide variants and >40% of somatic calls matching dbSNP entries, indicating low tumor content.

      DNA extractions and whole genome sequencing

      Tumor DNA for WGS was extracted from fresh-frozen tissue using DNeasy Blood and Tissue Kits (69506; Qiagen). Whole blood DNA for WGS was extracted using Flexigene DNA Kits (51206; Qiagen) as described previously (
      • Wilmott J.S.
      • Field M.A.
      • Johansson P.A.
      • Kakavand H.
      • Shang P.
      • De Paoli-Iseppi R.
      • et al.
      Tumour procurement, DNA extraction, coverage analysis and optimisation of mutation-detection algorithms for human melanoma genomes.
      ). WGS was performed on a HiseqX10 instrument (Illumina, San Diego, CA) as described (
      • Hayward N.K.
      • Wilmott J.S.
      • Waddell N.
      • Johansson P.A.
      • Field M.A.
      • Nones K.
      • et al.
      Whole-genome landscapes of major melanoma subtypes.
      ). Somatic mutation calling was performed as described (
      • Hayward N.K.
      • Wilmott J.S.
      • Waddell N.
      • Johansson P.A.
      • Field M.A.
      • Nones K.
      • et al.
      Whole-genome landscapes of major melanoma subtypes.
      ). The BAM files have been deposited in the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/) with accession number EGAS00001001552.

      Signature analysis

      Decomposition of mutational signatures was performed using the deconstructSigs and MutationalPatterns packages for R, version 3.4.2. The set of 30 Catalogue of Somatic Mutations in Cancer mutational signatures was obtained from http://cancer.sanger.ac.uk/cancergenome/assets/signatures_probabilities.txt. Mutational signatures for 7a, 7b, and 7c were extracted from a larger whole genome analysis of cutaneous melanomas (
      • Hayward N.K.
      • Wilmott J.S.
      • Waddell N.
      • Johansson P.A.
      • Field M.A.
      • Nones K.
      • et al.
      Whole-genome landscapes of major melanoma subtypes.
      ).

      ddPCR

      ddPCR was performed on a QX200 Droplet Digital PCR System (Bio-Rad, Hercules, CA). Droplet generation was performed using an AutoDG (Bio-Rad) droplet generator. The PCR step was performed on a C1000 Touch Thermal Cycler (Bio-Rad). After the PCR step, the sealed plate was loaded onto a QX200 Droplet Reader in order to analyze the droplet fluorescent intensity. Initial data analysis was performed using the Quantasoft Pro software suite, version 1.0 (Bio-Rad) in order to evaluate the droplet quality and establish manual thresholds.
      The ddPCR analysis of BRAF V600E was performed according to the method described by
      • Tsao S.C.
      • Weiss J.
      • Hudson C.
      • Christophi C.
      • Cebon J.
      • Behren A.
      • et al.
      Monitoring response to therapy in melanoma by quantifying circulating tumour DNA with droplet digital PCR for BRAF and NRAS mutations.
      , whereas for TERT C228T and C250T ddPCR followed the method described by
      • Colebatch A.J.
      • Witkowski T.
      • Waring P.M.
      • McArthur G.A.
      • Wong S.Q.
      • Dobrovic A.
      Optimizing amplification of the GC-rich TERT promoter region using 7-Deaza-dGTP for droplet digital PCR quantification of TERT promoter mutations.

      Statistics

      For the analysis of mutant droplets in nevi, a Fisher’s exact test was performed comparing these to false-positive droplets from the pooled wild-type samples (SK-MEL28). A P-value of <0.01 was considered significant. Statistical testing was performed in R, version 3.2.0.

      ORCID

      Conflicts of Interest

      Alexander Dobrovic: honoraria from Bio-Rad for speaking (not directly related to this paper). Grant A. McArthur: principal investigator of clinical trials with Genentech/Roche, MSD, BMS, Array BioPharm, Amgen, Pfizer (all revenues paid to institution as reimbursement for trial costs). John F. Thompson: Advisory board membership and honoraria from BMS Australia, GlaxoSmithKline, MSD Australia, and Provectus. The remaining authors state no conflict of interest.

      Acknowledgments

      This work was supported by Melanoma Institute Australia, Bioplatforms Australia, New South Wales Ministry of Health, Cancer Council New South Wales, Program Grants of the National Health and Medical Research Council of Australia, Cancer Institute New South Wales, and by the Australian Cancer Research Foundation. NW, JSW, NKH, GVL, and RAS are supported by National Health and Medical Research Council of Australia Fellowships. The authors gratefully acknowledge the support of colleagues at Melanoma Institute Australia, Royal Prince Alfred Hospital, NSW Health Pathology, the Westmead Institute for Medical Research. PF was supported by the Deborah and John McMurtrie Melanoma Institute Australia Pathology Fellowship. Andrew Colebatch is a recipient of the Postgraduate Research Fellowship 2015 from the Royal College of Pathologists of Australasia Foundation. The Olivia Newton-John Cancer Research Institute received support from the Operational Infrastructure Support Program of the Victorian State Government. GVL is supported by a University of Sydney, Sydney Medical School Foundation Grant.

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