Exome sequencing identifies recurrent mutations in NF1 and RASopathy genes in sun-exposed melanomas

Journal name:
Nature Genetics
Year published:
Published online


We report on whole-exome sequencing (WES) of 213 melanomas. Our analysis established NF1, encoding a negative regulator of RAS, as the third most frequently mutated gene in melanoma, after BRAF and NRAS. Inactivating NF1 mutations were present in 46% of melanomas expressing wild-type BRAF and RAS, occurred in older patients and showed a distinct pattern of co-mutation with other RASopathy genes, particularly RASA2. Functional studies showed that NF1 suppression led to increased RAS activation in most, but not all, melanoma cases. In addition, loss of NF1 did not predict sensitivity to MEK or ERK inhibitors. The rebound pathway, as seen by the induction of phosphorylated MEK, occurred in cells both sensitive and resistant to the studied drugs. We conclude that NF1 is a key tumor suppressor lost in melanomas, and that concurrent RASopathy gene mutations may enhance its role in melanomagenesis.

At a glance


  1. Melanoma mutational landscape (n = 213).
    Figure 1: Melanoma mutational landscape (n = 213).

    Top 11 melanoma-driver genes that reach genome-wide significance according to background mutation-frequency estimation. Purple, metastatic melanoma; green, patients over 65 years old; red, mutations at recurrent positions; dark blue, inactivating mutations (nonsense, splice, indel); light blue, predicted harmful mutations. Brown and darker orange represent sun-exposed tumors and tumors of unknown origin, respectively. Mutations in HRAS and KRAS are marked in light orange and yellow, respectively. Mutation counts correspond to novel mutations that are not found in repositories of common human variants.

  2. NF1 expression and NRAS activity.
    Figure 2: NF1 expression and NRAS activity.

    (a) Protein blot showing NF1 expression in melanoma cells (YU designation) relative to that in normal human melanocytes (NBMEL) derived from a single newborn foreskin; β-actin was used as a loading control. NF1 mutations are indicated at the top, and BRAF mutations at the bottom. The wild-type NF1 (WT) melanomas YUHOIN and YUDATE displayed LOH. All the melanoma cell lines represented in this panel are NRAS wild type. The reproducibility data and protein expression in additional representative melanoma cell lines are presented in Supplementary Figure 4. (b) NRAS activity as determined by NRAS-GTP pulldown assay showing active NRAS-GTP and total NRAS detected in lysates. The same results were obtained with pan-RAS antibodies (data not shown). (c) Ranking of NRAS activity with BRAF, NRAS and NF1 mutation and expression status. We derived numbers by scanning the bands and quantitating the bands' intensity relative to input NRAS using ImageJ and normalizing against the NRASQ61R YUFIC melanoma. FS, frame shift.

  3. Growth responses to selumetinib and SCH772984.
    Figure 3: Growth responses to selumetinib and SCH772984.

    (ad) Growth of NF1-mutant (a,c) and of triple–wild-type (brown), BRAFV600-mutant (blue) and NRAFSQ61-mutant (red) melanoma cell lines (b,d). In a, the NF1 mutants YURKEN, YUTICA and YUSAMIR (dashed lines) are double-mutant cell lines (BRAFV600E, NRASQ61R and BRAFV600E, respectively) that express normal levels of NF1. The rest of the lines are null for NF1 (Fig. 2a). The selumetinib experiments were repeated at least twice. The data represent cell viability (CellTiter-Glo luminescent assay) as a percentage of the control at the end of 72 h of treatment. Each measurement is the average of triplicate or quadruplet wells. Error bars denote s.e.m.

  4. Changes in MEK1/2 and ERK phosphorylation in response to selumetinib.
    Figure 4: Changes in MEK1/2 and ERK phosphorylation in response to selumetinib.

    Normal human melanocytes (NBMEL) and melanoma cell lines were untreated (0) or treated with 100 nM selumetinib for 1, 6 and 24 h. The panels show protein blots probed with the indicated antibodies. (a) Normal melanocytes and NF1-mutant melanoma cell lines that are wild type for BRAF and NRAS. (b) Melanoma cell lines that are NF1, NRAS or BRAF mutants, as indicated. Numbers on the bottom show the IC50 in response to selumetinib (Fig. 3). The types of NF1 and RAC1 mutations are indicated for each cell line at the top. All the cell lines in b express wild-type RAC1. Figure 2a and Supplementary Figure 4 show the corresponding levels of NF1 expression. The results represent one of two similar experiments.


  1. Davis, M.J. et al. RAC1P29S is a spontaneously activating cancer-associated GTPase. Proc. Natl. Acad. Sci. USA 110, 912917 (2013).
  2. Hodis, E. et al. A landscape of driver mutations in melanoma. Cell 150, 251263 (2012).
  3. Krauthammer, M. et al. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nat. Genet. 44, 10061014 (2012).
  4. Gold, H.L. et al. PP6C hotspot mutations in melanoma display sensitivity to Aurora kinase inhibition. Mol. Cancer Res. 12, 433439 (2014).
  5. Hammond, D. et al. Melanoma-associated mutations in protein phosphatase 6 cause chromosome instability and DNA damage owing to dysregulated Aurora-A. J. Cell Sci. 126, 34293440 (2013).
  6. Prickett, T.D. et al. Exon capture analysis of G protein–coupled receptors identifies activating mutations in GRM3 in melanoma. Nat. Genet. 43, 11191126 (2011).
  7. Stark, M.S. et al. Frequent somatic mutations in MAP3K5 and MAP3K9 in metastatic melanoma identified by exome sequencing. Nat. Genet. 44, 165169 (2012).
  8. Huang, F.W. et al. Highly recurrent TERT promoter mutations in human melanoma. Science 339, 957959 (2013).
  9. Horn, S. et al. TERT promoter mutations in familial and sporadic melanoma. Science 339, 959961 (2013).
  10. Martin, M. et al. Exome sequencing identifies recurrent somatic mutations in EIF1AX and SF3B1 in uveal melanoma with disomy 3. Nat. Genet. 45, 933936 (2013).
  11. Harbour, J.W. et al. Frequent mutation of BAP1 in metastasizing uveal melanomas. Science 330, 14101413 (2010).
  12. Vogelstein, B. et al. Cancer genome landscapes. Science 339, 15461558 (2013).
  13. Lawrence, M.S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214218 (2013).
  14. Cancer Genome Atlas Network. Genomic classification of cutaneous melanoma. Cell 161, 16811696 (2015).
  15. Guen, V.J. et al. CDK10/cyclin M is a protein kinase that controls ETS2 degradation and is deficient in STAR syndrome. Proc. Natl. Acad. Sci. USA 110, 1952519530 (2013).
  16. Chou, C.H. et al. GSK3β regulates Bcl2L12 and Bcl2L12A anti-apoptosis signaling in glioblastoma and is inhibited by LiCl. Cell Cycle 11, 532542 (2012).
  17. Gartner, J.J. et al. Whole-genome sequencing identifies a recurrent functional synonymous mutation in melanoma. Proc. Natl. Acad. Sci. USA 110, 1348113486 (2013).
  18. Zang, Z.J. et al. Exome sequencing of gastric adenocarcinoma identifies recurrent somatic mutations in cell adhesion and chromatin remodeling genes. Nat. Genet. 44, 570574 (2012).
  19. McHugh, J.B., Fullen, D.R., Ma, L., Kleer, C.G. & Su, L.D. Expression of polycomb group protein EZH2 in nevi and melanoma. J. Cutan. Pathol. 34, 597600 (2007).
  20. Dillon, S.C., Zhang, X., Trievel, R.C. & Cheng, X. The SET-domain protein superfamily: protein lysine methyltransferases. Genome Biol. 6, 227 (2005).
  21. Duns, G. et al. Histone methyltransferase gene SETD2 is a novel tumor suppressor gene in clear cell renal cell carcinoma. Cancer Res. 70, 42874291 (2010).
  22. Wei, X. et al. Exome sequencing identifies GRIN2A as frequently mutated in melanoma. Nat. Genet. 43, 442446 (2011).
  23. Wu, Q. et al. 27-Hydroxycholesterol promotes cell-autonomous, ER-positive breast cancer growth. Cell Rep. 5, 637645 (2013).
  24. Yan, H. et al. IDH1 and IDH2 mutations in gliomas. N. Engl. J. Med. 360, 765773 (2009).
  25. Jin, G. et al. Disruption of wild-type IDH1 suppresses D-2-hydroxyglutarate production in IDH1-mutated gliomas. Cancer Res. 73, 496501 (2013).
  26. Yarwood, S., Bouyoucef-Cherchalli, D., Cullen, P.J. & Kupzig, S. The GAP1 family of GTPase-activating proteins: spatial and temporal regulators of small GTPase signalling. Biochem. Soc. Trans. 34, 846850 (2006).
  27. Chen, P.C. et al. Next-generation sequencing identifies rare variants associated with Noonan syndrome. Proc. Natl. Acad. Sci. USA 111, 1147311478 (2014).
  28. Ratner, N. & Miller, S.J.A. RASopathy gene commonly mutated in cancer: the neurofibromatosis type 1 tumour suppressor. Nat. Rev. Cancer 15, 290301 (2015).
  29. Kontaridis, M.I., Swanson, K.D., David, F.S., Barford, D. & Neel, B.G. PTPN11 (Shp2) mutations in LEOPARD syndrome have dominant negative, not activating, effects. J. Biol. Chem. 281, 67856792 (2006).
  30. Tartaglia, M. et al. Diversity and functional consequences of germline and somatic PTPN11 mutations in human disease. Am. J. Hum. Genet. 78, 279290 (2006).
  31. Lepri, F. et al. SOS1 mutations in Noonan syndrome: molecular spectrum, structural insights on pathogenic effects, and genotype-phenotype correlations. Hum. Mutat. 32, 760772 (2011).
  32. Tartaglia, M. et al. Gain-of-function SOS1 mutations cause a distinctive form of Noonan syndrome. Nat. Genet. 39, 7579 (2007).
  33. Roberts, A.E. et al. Germline gain-of-function mutations in SOS1 cause Noonan syndrome. Nat. Genet. 39, 7074 (2007).
  34. Pandit, B. et al. Gain-of-function RAF1 mutations cause Noonan and LEOPARD syndromes with hypertrophic cardiomyopathy. Nat. Genet. 39, 10071012 (2007).
  35. Stowe, I.B. et al. A shared molecular mechanism underlies the human rasopathies Legius syndrome and Neurofibromatosis-1. Genes Dev. 26, 14211426 (2012).
  36. Brems, H. et al. Review and update of SPRED1 mutations causing Legius syndrome. Hum. Mutat. 33, 15381546 (2012).
  37. Ostman, A., Hellberg, C. & Bohmer, F.D. Protein-tyrosine phosphatases and cancer. Nat. Rev. Cancer 6, 307320 (2006).
  38. Ko, J.M., Kim, J.M., Kim, G.H. & Yoo, H.W. PTPN11, SOS1, KRAS, and RAF1 gene analysis, and genotype-phenotype correlation in Korean patients with Noonan syndrome. J. Hum. Genet. 53, 9991006 (2008).
  39. Tanoue, T., Adachi, M., Moriguchi, T. & Nishida, E. A conserved docking motif in MAP kinases common to substrates, activators and regulators. Nat. Cell Biol. 2, 110116 (2000).
  40. Janakiraman, M. et al. Genomic and biological characterization of exon 4 KRAS mutations in human cancer. Cancer Res. 70, 59015911 (2010).
  41. Johnson, D.B. et al. Combined BRAF (dabrafenib) and MEK inhibition (trametinib) in patients with BRAFV600-mutant melanoma experiencing progression with single-agent BRAF inhibitor. J. Clin. Oncol. 32, 36973704 (2014).
  42. Chapman, P.B. et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N. Engl. J. Med. 364, 25072516 (2011).
  43. Whittaker, S.R. et al. A genome-scale RNA interference screen implicates NF1 loss in resistance to RAF inhibition. Cancer Discov. 3, 350362 (2013).
  44. Nissan, M.H. et al. Loss of NF1 in cutaneous melanoma is associated with RAS activation and MEK dependence. Cancer Res. 74, 23402350 (2014).
  45. Ranzani, M. et al. BRAF/NRAS wild-type melanoma, NF1 status and sensitivity to trametinib. Pigment Cell Melanoma Res. 28, 117119 (2015).
  46. Magi, A. et al. EXCAVATOR: detecting copy number variants from whole-exome sequencing data. Genome Biol. 14, R120 (2013).
  47. Beroukhim, R. et al. Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc. Natl. Acad. Sci. USA 104, 2000720012 (2007).
  48. Ji, Z., Flaherty, K.T. & Tsao, H. Targeting the RAS pathway in melanoma. Trends Mol. Med. 18, 2735 (2012).
  49. Shibuya, M. VEGFR and type-V RTK activation and signaling. Cold Spring Harb. Perspect. Biol. 5, a009092 (2013).
  50. Johannessen, C.M. et al. COT drives resistance to RAF inhibition through MAP kinase pathway reactivation. Nature 468, 968972 (2010).
  51. Watson, I.R. et al. The RAC1 P29S hotspot mutation in melanoma confers resistance to pharmacological inhibition of RAF. Cancer Res. 74, 48454852 (2014).
  52. Newton, A.C. & Trotman, L.C. Turning off AKT: PHLPP as a drug target. Annu. Rev. Pharmacol. Toxicol. 54, 537558 (2014).
  53. Dong, L. et al. Oncogenic suppression of PHLPP1 in human melanoma. Oncogene 33, 47564766 (2014).
  54. Gallino, G. et al. Association between cutaneous melanoma and neurofibromatosis type 1: analysis of three clinical cases and review of the literature. Tumori 86, 7074 (2000).
  55. Seminog, O.O. & Goldacre, M.J. Risk of benign tumours of nervous system, and of malignant neoplasms, in people with neurofibromatosis: population-based record-linkage study. Br. J. Cancer 108, 193198 (2013).
  56. De Schepper, S. et al. Somatic mutation analysis in NF1 cafe au lait spots reveals two NF1 hits in the melanocytes. J. Invest. Dermatol. 128, 10501053 (2008).
  57. Johnson, M.R., Look, A.T., DeClue, J.E., Valentine, M.B. & Lowy, D.R. Inactivation of the NF1 gene in human melanoma and neuroblastoma cell lines without impaired regulation of GTP.Ras. Proc. Natl. Acad. Sci. USA 90, 55395543 (1993).
  58. Andersen, L.B. et al. Mutations in the neurofibromatosis 1 gene in sporadic malignant melanoma cell lines. Nat. Genet. 3, 118121 (1993).
  59. Marees, T. et al. Cancer mortality in long-term survivors of retinoblastoma. Eur. J. Cancer 45, 32453253 (2009).
  60. Nyström, A.M. et al. A severe form of Noonan syndrome and autosomal dominant cafe-au-lait spots—evidence for different genetic origins. Acta Paediatr. 98, 693698 (2009).
  61. Prada, C.E. et al. Lethal presentation of neurofibromatosis and Noonan syndrome. Am. J. Med. Genet. A 155A, 13601366 (2011).
  62. Thiel, C. et al. Independent NF1 and PTPN11 mutations in a family with neurofibromatosis-Noonan syndrome. Am. J. Med. Genet. A 149A, 12631267 (2009).
  63. Stites, E.C., Trampont, P.C., Haney, L.B., Walk, S.F. & Ravichandran, K.S. Cooperation between noncanonical Ras network mutations. Cell Rep. 10, 307316 (2015).
  64. Halaban, R. et al. PLX4032, a selective BRAF(V600E) kinase inhibitor, activates the ERK pathway and enhances cell migration and proliferation of BRAF melanoma cells. Pigment Cell Melanoma Res. 23, 190200 (2010).
  65. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 17541760 (2009).
  66. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 20782079 (2009).

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Author information


  1. Program in Computational Biology and Bioinformatics, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Michael Krauthammer &
    • Perry Evans
  2. Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Michael Krauthammer,
    • Natapol Pornputtapong,
    • James P McCusker &
    • Marcus Bosenberg
  3. Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Yong Kong
  4. Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Antonella Bacchiocchi,
    • Elaine Cheng,
    • Robert Straub,
    • Merdan Serin,
    • Marcus Bosenberg &
    • Ruth Halaban
  5. School of Public Health, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Cen Wu &
    • Shuangge Ma
  6. Department of Surgery, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Stephan Ariyan &
    • Deepak Narayan
  7. Comprehensive Cancer Center Section of Medical Oncology, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Mario Sznol &
    • Harriet M Kluger
  8. Yale Center for Genome Analysis, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Shrikant Mane
  9. Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Shrikant Mane &
    • Richard P Lifton
  10. Department of Pharmacology, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Joseph Schlessinger
  11. Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Richard P Lifton


M.K. and R.H. designed and performed the research, analyzed and interpreted the data, and wrote the manuscript. R.P.L. and J.S. designed the experiments. A.B., E.C., R.S. and M. Serin conducted the experiments. M.K., Y.K., P.E., J.P.M., S. Mane and N.P. analyzed the data from whole-exome sequencing. S. Ma and C.W. performed statistical analysis. M.B. evaluated the tumor percentage in the clinical specimens. S.A., D.N., M. Sznol and H.M.K. provided the clinical specimens and clinical annotation, as well as input in writing the manuscript.

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The authors declare no competing financial interests.

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