POT1 loss-of-function variants predispose to familial melanoma (original) (raw)

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References

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Acknowledgements

We thank the UK10K Consortium (funded by the Wellcome Trust; WT091310) for access to control data. D.J.A., C.D.R.-E., Z.D., J.Z.L., J.C.T., M.P. and T.M.K. were supported by Cancer Research UK and the Wellcome Trust (WT098051). C.D.R.-E. was also supported by the Consejo Nacional de Ciencia y Tecnología of Mexico. K.A.P. and A.M.D. were supported by Cancer Research UK (grants C1287/A9540 and C8197/A10123) and by the Isaac Newton Trust. N.K.H. was supported by a fellowship from the National Health and Medical Research Council of Australia (NHMRC). L.G.A. was supported by an Australia and New Zealand Banking Group Limited Trustees PhD scholarship. A.L.P. is supported by Cure Cancer Australia. The work was funded in part by the NHMRC and Cancer Council Queensland. The work of N.A.G. was in part supported by the Dutch Cancer Society (UL 2012-5489). M.H., J.A.N.-B. and D.T.B. were supported by Cancer Research UK (programme awards C588/A4994 and C588/A10589 and the Genomics Initiative). C.L.-O., A.J.R. and V.Q. are funded by the Spanish Ministry of Economy and Competitiveness through the Instituto de Salud Carlos III (ISCIII), the Red Temática de Investigación del Cáncer (RTICC) del ISCIII and the Consolider-Ingenio RNAREG Consortium. C.L.-O. is an investigator with the Botín Foundation.

Author information

Author notes

  1. Carla Daniela Robles-Espinoza, Mark Harland, Andrew J Ramsay and Lauren G Aoude: These authors contributed equally to this work.
  2. Nicholas K Hayward, D Timothy Bishop, Julia A Newton-Bishop and David J Adams: These authors jointly directed this work.

Authors and Affiliations

  1. Experimental Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
    Carla Daniela Robles-Espinoza, Zhihao Ding, Jessamy C Tiffen, Mia Petljak, Thomas M Keane & David J Adams
  2. Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
    Mark Harland, Helen Snowden, D Timothy Bishop & Julia A Newton-Bishop
  3. Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología del Principado de Asturias (IUOPA), Universidad de Oviedo, Oviedo, Spain
    Andrew J Ramsay, Víctor Quesada & Carlos López-Otín
  4. Oncogenomics Laboratory, QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
    Lauren G Aoude, Antonia L Pritchard, Jane M Palmer, Judith Symmons, Peter Johansson, Mitchell S Stark, Michael G Gartside & Nicholas K Hayward
  5. Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
    Karen A Pooley
  6. Molecular Epidemiology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
    Grant W Montgomery
  7. Genetic Epidemiology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
    Nicholas G Martin
  8. Statistical Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
    Jimmy Z Liu
  9. Laboratory of Translational Genomics, National Cancer Institute, Bethesda, Maryland, USA
    Jiyeon Choi, Matthew Makowski & Kevin M Brown
  10. Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
    Alison M Dunning
  11. Department of Dermatology, Leiden University Medical Centre, Leiden, The Netherlands
    Nelleke A Gruis

Authors

  1. Carla Daniela Robles-Espinoza
  2. Mark Harland
  3. Andrew J Ramsay
  4. Lauren G Aoude
  5. Víctor Quesada
  6. Zhihao Ding
  7. Karen A Pooley
  8. Antonia L Pritchard
  9. Jessamy C Tiffen
  10. Mia Petljak
  11. Jane M Palmer
  12. Judith Symmons
  13. Peter Johansson
  14. Mitchell S Stark
  15. Michael G Gartside
  16. Helen Snowden
  17. Grant W Montgomery
  18. Nicholas G Martin
  19. Jimmy Z Liu
  20. Jiyeon Choi
  21. Matthew Makowski
  22. Kevin M Brown
  23. Alison M Dunning
  24. Thomas M Keane
  25. Carlos López-Otín
  26. Nelleke A Gruis
  27. Nicholas K Hayward
  28. D Timothy Bishop
  29. Julia A Newton-Bishop
  30. David J Adams

Contributions

C.D.R.-E., M.H., J.A.N.-B., D.T.B., N.K.H. and D.J.A. designed the study and wrote the manuscript. C.D.R.-E., M.H., L.G.A., J.C.T., M.M., J.C., M.P., A.J.R., Z.D., V.Q., A.L.P., J.M.P., J.S., M.S.S., N.G.M., M.G.G., A.M.D., K.A.P., P.J., J.Z.L., K.M.B., C.L.-O. and T.M.K. performed experiments or analysis. N.A.G., G.W.M., H.S. and N.G.M. provided vital biological resources.

Corresponding author

Correspondence toDavid J Adams.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Capillary sequencing of POT1 variants detected by next-generation sequencing.

One sample per variant is shown; variants are indicated with an arrow. (a) Sequencing showing the presence of the variant in an additional member of pedigree UF20 who was not exome sequenced (individual III-2; Fig. 1a). (b) Sequencing of an affected individual of pedigree AF1; note that, in this case, the complementary strand is shown. (c) Sequencing of the POT1 product in a control with wild-type POT1 (top) and a carrier of the splice-acceptor variant (pedigree AF1, individual IV-1; Fig. 1a) (bottom). The boundary between exons 17 and 18 is marked with a dotted red line. The wild-type sequence, in nucleotides and in amino acids, is indicated in black, and the sequence the variant results in is indicated in red. The mutant sequence leads to the introduction of a premature stop codon 11 amino acids downstream of the exon 17–exon 18 boundary. (d) Sequencing of an affected member of pedigree UF31. (e) Sequencing of the carrier member of pedigree UF23.

Supplementary Figure 2 MaxEntScan scores for the splice-acceptor variant detected in a familial melanoma pedigree (AF1).

The location of the scores for the wild-type (black) and mutated (red) sequences are shown against score distributions for real splice donors, real splice acceptors and random genomic sequences.

Supplementary Figure 3 Pedigrees with additional POT1 variants.

(a) Pedigree of family UF31 carrying the p.Gln94Glu change. (b) Pedigree of family UF23 carrying the p.Arg273Leu variant. Types of cancer are indicated under each symbol, and ages of onset are indicated in parentheses. Genotypes for all samples available for testing are shown in blue. All cancers were confirmed by histological analysis with the exception of one case (indicated by an asterisk). CMM, cutaneous malignant melanoma. Circles represent females; squares represent males; diamonds represent individuals of undisclosed sex. Half-filled symbols represent other cancers. The individuals that were sequenced have a red outline.

Supplementary Figure 4 Principal-component analysis showing that the melanoma cases and UK10K controls are ancestry matched.

Plot showing the first and second principal components (PC1 and PC2, respectively). Ancestry was estimated using the 1000 Genomes Project individuals1 and then projected onto the melanoma (gray) and UK10K control (orange) cohorts. Note that controls lying greater than 2 s.d. from the mean PC1 or PC2 scores, calculated using only European individuals in the 1000 Genomes Project data set, are not shown in this plot and were not considered in subsequent analyses. We did not depict three individuals from the QFMP cohort for whom we could not determine the zygosity of the called genotypes.

Supplementary Figure 5 35S gel showing the in vitro translation products of wild-type POT1 and OB domain mutants.

This gel confirms that each in vitro translation reaction successfully produced protein for the electrophoretic mobility shift assay shown in Figure 2b. The p.Tyr89Cys, p.Gln94Glu and p.Arg273Leu POT1 variants were identified by exome sequencing familial melanoma cases. The p.Tyr223Cys variant was somatically acquired in CLL and has previously been shown to be unable to bind to telomeric DNA2. The DNA-protein complexes shown in Figure 2b were visualized by 32P labeling of (TTAGGG)3 single-stranded DNA (Online Methods).

Supplementary Figure 6 Linear model used to adjust bioinformatically calculated telomere lengths for age at blood draw and sex.

Residuals were used as the adjusted relative telomere lengths. Dark circles represent male samples, and light circles represent females. The sex variable is coded as 0 = female, 1 = male. Note that only two dimensions (relative telomere length and age) are shown.

Supplementary Figure 7 Linear model used to adjust PCR mean Δ_C_ t values for age at blood draw and sex.

Residuals were used as the adjusted mean Δ_C_ t values. Dark circles represent male samples, and light circles represent females. The sex variable is coded as 0 = female, 1 = male. Note that only two dimensions (mean Δ_C_ t value and age) are shown.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1, 2 and 4–8 and Supplementary Note (PDF 2264 kb)

Supplementary Table 3

Genes with cosegregating variants from the 28 pedigrees for which we had sequence data for 3 or more members and their GO terms. (XLS 159 kb)

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Robles-Espinoza, C., Harland, M., Ramsay, A. et al. POT1 loss-of-function variants predispose to familial melanoma.Nat Genet 46, 478–481 (2014). https://doi.org/10.1038/ng.2947

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