[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

A melanocyte lineage program confers resistance to MAP kinase pathway inhibition

Nature volume 504, pages 138–142 (2013)Cite this article

Subjects

Abstract

Malignant melanomas harbouring point mutations (Val600Glu) in the serine/threonine-protein kinase BRAF (BRAF(V600E)) depend on RAF–MEK–ERK signalling for tumour cell growth1. RAF and MEK inhibitors show remarkable clinical efficacy in BRAF(V600E) melanoma2,3; however, resistance to these agents remains a formidable challenge2,4. Global characterization of resistance mechanisms may inform the development of more effective therapeutic combinations. Here we carried out systematic gain-of-function resistance studies by expressing more than 15,500 genes individually in a BRAF(V600E) melanoma cell line treated with RAF, MEK, ERK or combined RAF–MEK inhibitors. These studies revealed a cyclic-AMP-dependent melanocytic signalling network not previously associated with drug resistance, including G-protein-coupled receptors, adenyl cyclase, protein kinase A and cAMP response element binding protein (CREB). Preliminary analysis of biopsies from BRAF(V600E) melanoma patients revealed that phosphorylated (active) CREB was suppressed by RAF–MEK inhibition but restored in relapsing tumours. Expression of transcription factors activated downstream of MAP kinase and cAMP pathways also conferred resistance, including c-FOS, NR4A1, NR4A2 and MITF. Combined treatment with MAPK-pathway and histone-deacetylase inhibitors suppressed MITF expression and cAMP-mediated resistance. Collectively, these data suggest that oncogenic dysregulation of a melanocyte lineage dependency can cause resistance to RAF–MEK–ERK inhibition, which may be overcome by combining signalling- and chromatin-directed therapeutics.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Near-genome-scale functional rescue screens for resistance to RAF, MEK and ERK inhibitors.
Figure 2: Candidate resistance genes segregate into validating protein classes.
Figure 3: A cyclic AMP signalling network mediates resistance to RAF, MEK and ERK inhibitors.
Figure 4: Candidate resistance genes are transcriptional effectors of the MAPK and cAMP pathways.

Similar content being viewed by others

References

  1. Solit, D. B. et al. BRAF mutation predicts sensitivity to MEK inhibition. Nature 439, 358–362 (2006)

    Article  ADS  CAS  PubMed  Google Scholar 

  2. Chapman, P. B. et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N. Engl. J. Med. 364, 2507–2516 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Flaherty, K. T. et al. Combined BRAF and MEK inhibition in melanoma with BRAF V600 mutations. N. Engl. J. Med. 367, 1694–1703 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Flaherty, K. T. et al. Improved survival with MEK inhibition in BRAF-mutated melanoma. N. Engl. J. Med. 367, 107–114 (2012)

    CAS  PubMed  Google Scholar 

  5. Yang, X. et al. A public genome-scale lentiviral expression library of human ORFs. Nature Methods 8, 659–661 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Johannessen, C. M. et al. COT drives resistance to RAF inhibition through MAP kinase pathway reactivation. Nature 468, 968–972 (2010)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wood, K. C. et al. MicroSCALE screening reveals genetic modifiers of therapeutic response in melanoma. Sci. Signal. 5, rs4 (2012)

    Article  PubMed  PubMed Central  Google Scholar 

  8. Aronov, A. M. et al. Structure-guided design of potent and selective pyrimidylpyrrole inhibitors of extracellular signal-regulated kinase (ERK) using conformational control. J. Med. Chem. 52, 6362–6368 (2009)

    Article  CAS  PubMed  Google Scholar 

  9. Crews, C. M., Alessandrini, A. & Erikson, R. L. The primary structure of MEK, a protein kinase that phosphorylates the ERK gene product. Science 258, 478–480 (1992)

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Girotti, M. R. et al. Inhibiting EGF receptor or SRC family kinase signaling overcomes BRAF inhibitor resistance in melanoma. Cancer Discov. 3, 158–167 (2012)

    Article  PubMed  PubMed Central  Google Scholar 

  11. Kyriakis, J. M. et al. Raf-1 activates MAP kinase-kinase. Nature 358, 417–421 (1992)

    Article  ADS  CAS  PubMed  Google Scholar 

  12. Patriotis, C., Makris, A., Chernoff, J. & Tsichlis, P. N. Tpl-2 acts in concert with Ras and Raf-1 to activate mitogen-activated protein kinase. Proc. Natl Acad. Sci. USA 91, 9755–9759 (1994)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  13. Pham, C. D., Arlinghaus, R. B., Zheng, C. F., Guan, K. L. & Singh, B. Characterization of MEK1 phosphorylation by the v-Mos protein. Oncogene 10, 1683–1688 (1995)

    CAS  PubMed  Google Scholar 

  14. Pierce, K. L., Premont, R. T. & Lefkowitz, R. J. Seven-transmembrane receptors. Nature Rev. Mol. Cell Biol. 3, 639–650 (2002)

    Article  CAS  Google Scholar 

  15. Hayward, N. K. Genetics of melanoma predisposition. Oncogene 22, 3053–3062 (2003)

    Article  CAS  PubMed  Google Scholar 

  16. Walton, K. M., Rehfuss, R. P., Chrivia, J. C., Lochner, J. E. & Goodman, R. H. A dominant repressor of cyclic adenosine 3′,5′-monophosphate (cAMP)-regulated enhancer-binding protein activity inhibits the cAMP-mediated induction of the somatostatin promoter in vivo. Mol. Endocrinol. 6, 647–655 (1992)

    CAS  PubMed  Google Scholar 

  17. Ahn, S. et al. A dominant-negative inhibitor of CREB reveals that it is a general mediator of stimulus-dependent transcription of c-fos. Mol. Cell. Biol. 18, 967–977 (1998)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Dumaz, N. et al. In melanoma, RAS mutations are accompanied by switching signaling from BRAF to CRAF and disrupted cyclic AMP signaling. Cancer Res. 66, 9483–9491 (2006)

    Article  CAS  PubMed  Google Scholar 

  19. Garraway, L. A. et al. Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 436, 117–122 (2005)

    Article  ADS  CAS  PubMed  Google Scholar 

  20. Jané-Valbuena, J. et al. An oncogenic role for ETV1 in melanoma. Cancer Res. 70, 2075–2084 (2010)

    Article  PubMed  PubMed Central  Google Scholar 

  21. Hemesath, T. J., Price, E. R., Takemoto, C., Badalian, T. & Fisher, D. E. MAP kinase links the transcription factor Microphthalmia to c-Kit signalling in melanocytes. Nature 391, 298–301 (1998)

    Article  ADS  CAS  PubMed  Google Scholar 

  22. Wu, M. et al. c-Kit triggers dual phosphorylations, which couple activation and degradation of the essential melanocyte factor Mi. Genes Dev. 14, 301–312 (2000)

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Hodgkinson, C. A. et al. Mutations at the mouse microphthalmia locus are associated with defects in a gene encoding a novel basic-helix-loop-helix-zipper protein. Cell 74, 395–404 (1993)

    Article  CAS  PubMed  Google Scholar 

  24. Yokoyama, S. et al. Pharmacologic suppression of MITF expression via HDadenyl cyclase inhibitors in the melanocyte lineage. Pigment Cell Melanoma Res. 21, 457–463 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Haq, R. et al. BCL2A1 is a lineage-specific antiapoptotic melanoma oncogene that confers resistance to BRAF inhibition. Proc. Natl Acad. Sci. USA 110, 4321–4326 (2013)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  26. Smith, M. P. et al. Effect of SMURF2 targeting on susceptibility to MEK inhibitors in melanoma. J. Natl. Cancer Inst. 105, 33–46 (2013)

    Article  CAS  PubMed  Google Scholar 

  27. Frederick, D. T. et al. BRAF inhibition is associated with enhanced melanoma antigen expression and a more favorable tumor microenvironment in patients with metastatic melanoma. Clinical Cancer Res. 19, 1225–1231 (2013)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Institutes of Health (NIH) Director’s New Innovator Award (DP2 OD002750, L.A.G.), Melanoma Research Alliance (L.A.G.), Starr Cancer Consortium (L.A.G.), Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (L.A.G.), the NCI Skin Cancer SPORE (P50CA93683, L.A.G.) and the LINCS Program (U54 HG006093).

Author information

Author notes

  1. Laura A. Johnson

    Present address: Present address: Graduate Program in Cell and Molecular Physiology, Sackler School of Graduate Biomedical Sciences, School of Medicine, Tufts University, 145 Harrison Avenue, Boston, Massachusetts 02111, USA.,

Authors and Affiliations

  1. The Broad Institute of Harvard University and Massachusetts Institute of Technology, 7 Cambridge Center, Cambridge, 02142, Massachusetts, USA

    Cory M. Johannessen, Laura A. Johnson, Federica Piccioni, Aisha Townes, Melanie K. Donahue, Rajiv Narayan, David E. Root & Levi A. Garraway

  2. Department of Medical Oncology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, Massachusetts 02115, USA,

    Cory M. Johannessen, Laura A. Johnson & Levi A. Garraway

  3. Harvard Medical School, 25 Shattuck Street, Boston, 02115, Massachusetts, USA

    Cory M. Johannessen & Levi A. Garraway

  4. Department of Surgical Oncology, Medical Oncology and Dermatology, Massachusetts General Hospital, 55 Fruit Street, Boston, Massachusetts 02114, USA,

    Dennie T. Frederick, Keith T. Flaherty & Jennifer A. Wargo

Authors
  1. Cory M. Johannessen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Laura A. Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Federica Piccioni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aisha Townes
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dennie T. Frederick
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Melanie K. Donahue
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rajiv Narayan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Keith T. Flaherty
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jennifer A. Wargo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. David E. Root
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Levi A. Garraway
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

C.M.J. and L.A.G. designed the experiments. C.M.J. and L.A.J. performed primary and validation screens, with technical assistance from F.P. and supervision by D.E.R. All experimental follow-up studies were performed by C.M.J. A.T. performed quantitative PCR with reverse transcription (RT–PCR) experiments. M.K.D. generated gene signatures and R.N. analysed results. Clinical samples were collected or experiments performed by C.M.J., F.D.T., K.T.F., J.A.W. C.M.J. and L.A.G. wrote the manuscript. All authors discussed results and edited the manuscript.

Corresponding author

Correspondence to Levi A. Garraway.

Ethics declarations

Competing interests

L.A.G. is a consultant for Foundation Medicine, Novartis, Boehringer Ingelheim, Millennium (Takeda) and Onyx Pharmaceuticals; L.A.G. receives research support from Novartis; L.A.G. is an equity holder in Foundation Medicine. J.A.W. receives research support from Roche-Genentech. K.T.F. is a consultant for GlaxoSmithKline.

Extended data figures and tables

Extended Data Figure 1 A systematic, functional approach to identifying drug-resistance genes.

Schematic outlining the experimental approach taken to identify membrane-to-nucleus signalling pathways that mediate resistance to MAPK-pathway inhibitors. Resulting data were used to identify gene networks capable of mediating drug resistance.

Extended Data Figure 2 Near-genome-scale ORF and cDNA screens identify candidate MAPK-pathway inhibitor resistance genes.

a, Histogram of infection efficiency in A375 cells observed in the primary resistance screens. Per cent of total ORFs above and below 65% infection efficiency are noted (red, dashed line). b, Histogram of the z score of A375-cell viability in DMSO observed in the primary resistance screen. Total ORFs above, below and within the indicated z-score thresholds are noted. c, Scatter plots and correlation (R) of A375-cell viability (raw luminescence values) in the primary resistance screens. Colours distinguish viral screening plates. d, Heat map summary of controls and candidate resistance genes identified in primary resistance screens. Protein class and ORF class are indicated (positive control, red; negative control, yellow; experimental ORF, black). Asterisk identifies two genes whose empirical sequence is significantly divergent from its annotated reference sequence.

Extended Data Figure 3 Patterns of drug resistance induced by candidate resistance genes.

a, Heat map displaying the per cent rescue (viability in drug/viability in DMSO) for each candidate resistance ORF and control ORFs in the presence of log-fold concentrations of the indicated MAPK-pathway inhibitor. These data were used to generate drug-sensitivity curves. b, The area under the curve calculated for the drug sensitivity curves in a (red dashed lines denote significance thresholds). c, Heat map showing ERK phosphorylation data for all candidate resistance genes and controls in A375 cells. d, Matrix of genes ectopically expressed in A375 cells (vertical axis) versus treatment condition (horizontal axis). Sensitivity is defined as yielding an area under the curve z score of <1.96, resistance is defined as z > 1.96 (P < 0.05). e, Venn diagram showing the overlap of validated resistance genes, grouped by MAPK-pathway inhibitor, in A375 cells. f, Schematic showing the number of validated genes that confer resistance or sensitivity to indicated MAPK inhibitors.

Extended Data Figure 4 Broad validation of candidate resistance genes in a panel of BRAF(V600E)-mutant melanoma cell lines.

a, Drug sensitivity curves for PLX4720, AZD6244 and VRT11E in the panel of eight BRAF(V600E)-mutant malignant melanoma cell lines used for the primary and validation screening experiments (described in Fig. 2). Error bars represent s.d. of mean, n = 6 technical replicates. b, Western blot analysis following treatment with indicated MAPK inhibitors in the panel of eight BRAF(V600E)-mutant malignant melanoma cell lines used in a. c, Box plot of all candidate and control ORF infection efficiencies in the panel of eight cell lines used in the validation screening experiments. Centre line represents the median value, box defines the 25th–75th percentile and whiskers define the 5–95% confidence interval. Outliers are shown as individual data points. d, Summary of the cellular viability (relative to DMSO) of negative and neutral control genes observed in validation screens. Bar graph shows the average viability (relative to that of DMSO treatment) of each cell line when expressing the 59 negative and neutral control genes included in all validation screening experiments. Error bars represent s.d. of mean, each measured in technical duplicates. e, Average composite rescue score of each class of proteins identified among the resistance candidates (relates to Fig. 2). Number of genes within each protein class is shown in parentheses. f, ADCY9 was identified as a resistance candidate in the primary resistance screen, but was a DNA failure in our independent prep of candidate virus. Therefore, ADCY9 was not included in the high throughput validation screens, but was included in all subsequent validation work. These data show that ADCY9 is able to confer resistance to all tested MAPK inhibitors to a similar degree as forskolin and IBMX treatment. Error bars represent s.d. of mean, n = 6 technical replicates. g, Western blot analysis of the expression of V5-epitope tagged eGFP and ADCY9 in WM266.4.

Extended Data Figure 5 Cyclic AMP induces CREB and ATF1 phosphorylation and induces MAPK-pathway inhibitor resistance.

a, Mean fold-change in intracellular cAMP following treatment with forskolin plus IBMX (FSK/I) or dibutyryl cAMP plus IBMX (cAMP/I) using a competitive cAMP ELISA (n = 2 technical replicates, representative of 2 independent experiments). b, Bar graphs showing the change in the half-maximal inhibitory concentration (GI50) of BRAF(V600E)-mutant cell lines treated with escalating doses of indicated MAPK-pathway inhibitor in the presence of vehicle (DMSO), FSK/I or cAMP/I. c, Relative cell viability (per cent of DMSO) following FSK/I or cAMP/I treatment in the absence of MAPK-pathway inhibitor treatment. Error bars represent s.d. of mean, n = 8 technical replicates. Data are representative of 2 independent experiments. d, Number of viable cells treated with the indicated compounds in the presence of vehicle (DMSO) or FSK/I. Error bars represent s.d. of mean, n = 3 technical replicates. e, Immunoblot analysis of WM983b cells following pre-treatment with the PKA inhibitor H89 and stimulation with FSK/I. f, Viability of WM266.4 cells treated with the indicated compounds and doses in the presence of vehicle (DMSO) or FSK/I. Error bars represent s.d. of mean, n = 6 technical replicates.

Extended Data Figure 6 Candidate GPCR–PKA pathway genes induce cyclic AMP, and CREB and ATF1 phosphorylation.

a, Western blot of BRAF(V600E)-mutant melanoma cell lines stimulated with forskolin and IBMX (FSK/I) or dibutyryl cAMP plus IBMX (cAMP/I). b, western blot analysis of WM266.4 cells treated with AZD6244, followed by stimulation with FSK/I. c, Western blot analysis of 293T lysates transfected with indicated genes or stimulated with FSK/I. d, Quantification of immunoblot analyses of 293T transiently transfected with the indicated expression constructs, pre-treated with IBMX (arbitrary units, n = 2 biological replicates). e, Mean control or candidate gene-induced cAMP production was measured following transfection of 293T with indicated expression constructs or treatment with FSK/I. cAMP levels were determined using an immuno-competition assay in the presence (red bars) or absence (black bars) of IBMX (n = 2 technical replicates, data are representative of 3 independent experiments). The green dashed line represents levels of cAMP in negative controls (eGFP, luciferase, LacZ). f, Western blot analysis of WM266.4 cells expressing indicated constructs and treated with AZD6244 and/or FSK/I.

Extended Data Figure 7 CREB activity is regulated in the context of drug treatment in patient biopsies.

a, Summary of patient sample characteristics. b, Immunoblot analysis of lysates extracted from BRAF(V600E)-mutant human tumours biopsied pre-initiation of treatment (P), following 10 to 14 days of MAPK-inhibitor treatment (on-treatment, O) or following relapse (R). MAPK-inhibitor therapy is noted (vemurafenib, RAF inhibitor; dabrafenib, RAF inhibitor; tremetinib, MEK inhibitor). c, Comparison of quantified phosphorylated CREB (pCREB) and pATF1 from b, shown as individual tumours. d, Statistical analysis of pATF1 and pCREB as in c, normalized to pre-treatment levels. Samples analysed are restricted to the subset of the biopsies that are patient matched, lesion-matched and treatment-paired *P < 0.0023, by one-tailed t-test. e, Immunoblot analysis of WM266.4 cells following treatment with forskolin and IBMX (FSK/I) or dibutyryl cAMP and IBMX (cAMP/I) in the presence of vehicle (DMSO) or indicated MAPK inhibitors.

Extended Data Figure 8 Identification of candidate resistance genes that are co-regulated by MAPK- and cAMP–PKA signalling pathways.

a, Candidate and neutral control genes containing cAMP response elements (CREs) were identified using gene sets extracted from MSigDB. Fold enrichment of the percentage of CRE-containing genes in candidates in relation to all genes screened for each gene set are noted. b, Matrix of CRE and candidate genes indicates the presence (black box) or absence (white box) of indicated CRE. Composite resistance score for each gene (summarized in Fig. 2c) is noted. Red dashed line indicates a composite resistance score of 50. c, Global endogenous mRNA expression (Log2 RMA) of candidate and neutral control genes across a panel of melanoma cell lines. Red arrows identify the four genes hypothesized to be regulated by both the MAPK-pathway and the cAMP–PKA–CREB pathway in melanoma: MITF, FOS, NR4A1 and NR4A2. Asterisks identify the subset of cell lines used in for validation and primary screens.

Extended Data Figure 9 cAMP–PKA regulation of MITF mediates resistance to MAPK pathway inhibition.

a, Immunoblot analysis of WM266.4 cells treated as indicated. b, Quantification in lysates from WM266.4 cells treated as indicated. Arrow indicates the slower migrating, phosphorylated form of MITF. Error bars represent s.d. of mean, n = 3 biological replicates. c, Western blot analysis of WM266.4 cells following treatment with AZD6244 and stimulated for the indicated times with forskolin and IBMX (FSK/I). FSK/I was washed out of the cells and replenished with normal growth media. Cell lysates were collected at the indicated times. d, Immunoblot analysis of WM266.4 cells following treatment with FSK/I for the indicated times in the presence of vehicle (DMSO) or MEK inhibitors. Genes identified in resistance screens are underlined. e, Immunoblot analysis of a panel of BRAF(V600E)-mutant malignant melanoma cell lines following treatment with AZD6244 in the presence of vehicle (DMSO), FSK/I or dibutyryl cAMP and IBMX (cAMP/I). f, Immunoblot analysis of WM266.4 cells following treatment with FSK/I in the presence of vehicle (DMSO) or indicated MAPK-pathway inhibitor. g, Gene signatures for all candidates and controls were generated in A375 cells and compared to the signatures of the cAMP-stimulating small molecule, colforsin. Individual genes are grouped as candidates or neutral controls, with each gene represented by a vertical line. Genes are ranked by similarity with colforsin, with number 1 being the most similar. A subset of the most similar genes is noted. h, Immunoblot analysis of WM266.4 cells after viral expression of the indicated genes or treatment with FSK/I in the presence of vehicle (DMSO) or AZD6244.

Extended Data Figure 10 Inhibition of PKA or MITF impairs cAMP-mediated resistance to MAPK pathway inhibitors.

a, Cell viability of WM266.4 cells expressing a control shRNA (shLuciferase) or shRNAs targeting MITF treated with indicated MAPK inhibitors and concomitant treatment with either DMSO or forskolin and IBMX (FSK/I). Error bars represent s.d. of mean, n = 6 technical replicates, data are representative of 2 independent experiments. b, Western blot analysis of WM266.4 cells expressing the shRNA constructs used in a. c, Western blot analysis of WM266.4 cells treated with AZD6244, followed by pre-treatment with DMSO or H89 and subsequent stimulation with FSK/I for the indicated times. d, Immunoblot analysis of lysates extracted from human BRAF(V600E)-positive melanoma biopsies. Biopsies were obtained before treatment (P), on MAPK-inhibitor treatment for 10 to 14 days (on-treatment, O) or following relapse (R). e, Immunoblot analysis of WM266.4 cells treated with the indicated concentration of HDAC inhibitor. f, Immunoblot analysis of SKMEL19 and SKMEL28 in the presence of vehicle (DMSO) or AZD6244, followed by treatment with the indicated HDAC inhibitor (panobinostat; Pan, vorinostat; Vor) and subsequent stimulation with FSK/I. g, Drug-sensitivity curves of panobinostat and vorinostat in WM266.4 cells expressing LacZ or the melanocyte-specific isoform of MITF (MITFm). Error bars represent s.d. of mean, n = 3 technical replicates.

PowerPoint slides

Source data

Rights and permissions

Reprints and permissions

About this article

Cite this article

Johannessen, C., Johnson, L., Piccioni, F. et al. A melanocyte lineage program confers resistance to MAP kinase pathway inhibition. Nature 504, 138–142 (2013). https://doi.org/10.1038/nature12688

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature12688

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing