Skip to main content

Thank you for visiting 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:

XPO1-dependent nuclear export is a druggable vulnerability in KRAS-mutant lung cancer

This article has been updated


The common participation of oncogenic KRAS proteins in many of the most lethal human cancers, together with the ease of detecting somatic KRAS mutant alleles in patient samples, has spurred persistent and intensive efforts to develop drugs that inhibit KRAS activity1. However, advances have been hindered by the pervasive inter- and intra-lineage diversity in the targetable mechanisms that underlie KRAS-driven cancers, limited pharmacological accessibility of many candidate synthetic-lethal interactions and the swift emergence of unanticipated resistance mechanisms to otherwise effective targeted therapies. Here we demonstrate the acute and specific cell-autonomous addiction of KRAS-mutant non-small-cell lung cancer cells to receptor-dependent nuclear export. A multi-genomic, data-driven approach, utilizing 106 human non-small-cell lung cancer cell lines, was used to interrogate 4,725 biological processes with 39,760 short interfering RNA pools for those selectively required for the survival of KRAS-mutant cells that harbour a broad spectrum of phenotypic variation. Nuclear transport machinery was the sole process-level discriminator of statistical significance. Chemical perturbation of the nuclear export receptor XPO1 (also known as CRM1), with a clinically available drug, revealed a robust synthetic-lethal interaction with native or engineered oncogenic KRAS both in vitro and in vivo. The primary mechanism underpinning XPO1 inhibitor sensitivity was intolerance to the accumulation of nuclear IκBα (also known as NFKBIA), with consequent inhibition of NFκB transcription factor activity. Intrinsic resistance associated with concurrent FSTL5 mutations was detected and determined to be a consequence of YAP1 activation via a previously unappreciated FSTL5–Hippo pathway regulatory axis. This occurs in approximately 17% of KRAS-mutant lung cancers, and can be overcome with the co-administration of a YAP1–TEAD inhibitor. These findings indicate that clinically available XPO1 inhibitors are a promising therapeutic strategy for a considerable cohort of patients with lung cancer when coupled to genomics-guided patient selection and observation.

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

Access options

Buy this article

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

Figure 1: Synthetic-lethal genetic interactions in KRAS-mutant NSCLC cells.
Figure 2: Selective sensitivity of KRAS-mutant NSCLC cells to chemical inhibition of the nuclear transport receptor XPO1.
Figure 3: Selective addiction to NFκB activity specifies sensitivity to XPO1 inhibition.
Figure 4: Concurrent mutations in FSTL5 are associated with intrinsic resistance of KRAS-mutant lines to XPO1 inhibitors and are mechanistically coupled to YAP1 activation.

Similar content being viewed by others

Accession codes


Gene Expression Omnibus

Change history

  • 05 October 2016

    The address details for Karyopharm Therapeutics were corrected.


  1. Cox, A. D., Fesik, S. W., Kimmelman, A. C., Luo, J. & Der, C. J. Drugging the undruggable RAS: mission possible? Nat. Rev. Drug Discov. 13, 828–851 (2014)

    Article  CAS  Google Scholar 

  2. Barbie, D. A. et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature 462, 108–112 (2009)

    Article  CAS  ADS  Google Scholar 

  3. Luo, J. et al. A genome-wide RNAi screen identifies multiple synthetic lethal interactions with the RAS oncogene. Cell 137, 835–848 (2009)

    Article  CAS  Google Scholar 

  4. Kumar, M. S. et al. The GATA2 transcriptional network is requisite for RAS oncogene-driven non-small cell lung cancer. Cell 149, 642–655 (2012)

    Article  CAS  Google Scholar 

  5. Scholl, C. et al. Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells. Cell 137, 821–834 (2009)

    Article  CAS  Google Scholar 

  6. Frey, B. J. & Dueck, D. Clustering by passing messages between data points. Science 315, 972–976 (2007)

    Article  CAS  ADS  MathSciNet  Google Scholar 

  7. Kim, H. S. et al. Systematic identification of molecular subtype-selective vulnerabilities in non-small-cell lung cancer. Cell 155, 552–566 (2013)

    Article  CAS  Google Scholar 

  8. Whitehurst, A. W. et al. Synthetic lethal screen identification of chemosensitizer loci in cancer cells. Nature 446, 815–819 (2007)

    Article  CAS  ADS  Google Scholar 

  9. Jackson, A. L. et al. Widespread siRNA “off-target” transcript silencing mediated by seed region sequence complementarity. RNA 12, 1179–1187 (2006)

    Article  CAS  Google Scholar 

  10. Etchin, J. et al. KPT-330 inhibitor of CRM1 (XPO1)-mediated nuclear export has selective anti-leukaemic activity in preclinical models of T-cell acute lymphoblastic leukaemia and acute myeloid leukaemia. Br. J. Haematol. 161, 117–127 (2013)

    Article  CAS  Google Scholar 

  11. Lapalombella, R. et al. Selective inhibitors of nuclear export show that CRM1/XPO1 is a target in chronic lymphocytic leukemia. Blood 120, 4621–4634 (2012)

    Article  CAS  Google Scholar 

  12. Neggers, J. E. et al. Identifying drug-target selectivity of small-molecule CRM1/XPO1 inhibitors by CRISPR/Cas9 genome editing. Chem. Biol. 22, 107–116 (2015)

    Article  CAS  Google Scholar 

  13. Abdul Razak, A. R. et al. First-in-class, first-in-human phase I study of selinexor, a selective inhibitor of nuclear export, in patients with advanced solid tumors. J. Clin. Oncol. (2016)

  14. Cheng, Y. et al. XPO1 (CRM1) inhibition represses STAT3 activation to drive a survivin-dependent oncogenic switch in triple-negative breast cancer. Mol. Cancer Ther. 13, 675–686 (2014)

    Article  CAS  Google Scholar 

  15. Meylan, E. et al. Requirement for NF-κB signalling in a mouse model of lung adenocarcinoma. Nature 462, 104–107 (2009)

    Article  CAS  ADS  Google Scholar 

  16. Bassères, D. S., Ebbs, A., Cogswell, P. C. & Baldwin, A. S. IKK is a therapeutic target in KRAS-induced lung cancer with disrupted p53 activity. Genes Cancer 5, 41–55 (2014)

    PubMed  PubMed Central  Google Scholar 

  17. Wuerzberger-Davis, S. M. et al. Nuclear export of the NF-κB inhibitor IκBα is required for proper B cell and secondary lymphoid tissue formation. Immunity 34, 188–200 (2011)

    Article  CAS  Google Scholar 

  18. Burke, J. R. et al. BMS-345541 is a highly selective inhibitor of IκB kinase that binds at an allosteric site of the enzyme and blocks NF-κB-dependent transcription in mice. J. Biol. Chem. 278, 1450–1456 (2003)

    Article  CAS  Google Scholar 

  19. Zender, L. et al. An oncogenomics-based in vivo RNAi screen identifies tumor suppressors in liver cancer. Cell 135, 852–864 (2008)

    Article  CAS  Google Scholar 

  20. Fitamant, J. et al. YAP inhibition restores hepatocyte differentiation in advanced HCC, leading to tumor regression. Cell Rep. 10, 1692–1707 (2015)

    Article  CAS  Google Scholar 

  21. Kapoor, A. et al. YAP1 activation enables bypass of oncogenic KRAS addiction in pancreatic cancer. Cell 158, 185–197 (2014)

    Article  CAS  Google Scholar 

  22. Lin, L. et al. The Hippo effector YAP promotes resistance to RAF- and MEK-targeted cancer therapies. Nat. Genet. 47, 250–256 (2015)

    Article  CAS  Google Scholar 

  23. Shao, D. D. et al. KRAS and YAP1 converge to regulate EMT and tumor survival. Cell 158, 171–184 (2014)

    Article  CAS  Google Scholar 

  24. Yu, F.X., Zhao, B., & Guan, K.L. Hippo pathway in organ size control, tissue homeostasis, and cancer. Cell 163, 811–828 (2015)

    Article  CAS  Google Scholar 

  25. Mo, J. S. et al. Cellular energy stress induces AMPK-mediated regulation of YAP and the Hippo pathway. Nat. Cell Biol. 17, 500–510 (2015)

    Article  CAS  Google Scholar 

  26. Singh, N. K., Seo, B. Y., Vidyasagar, M., White, M. A. & Kim, H. S. siMacro: a fast and easy data processing tool for cell-based genomewide siRNA screens. Genomics Inform. 11, 55–57 (2013)

    Article  Google Scholar 

  27. Shigematsu, H. et al. Somatic mutations of the HER2 kinase domain in lung adenocarcinomas. Cancer Res. 65, 1642–1646 (2005)

    Article  CAS  Google Scholar 

  28. Yamamoto, H. et al. PIK3CA mutations and copy number gains in human lung cancers. Cancer Res. 68, 6913–6921 (2008)

    Article  CAS  Google Scholar 

  29. Phelps, R. M. et al. NCI-Navy Medical Oncology Branch cell line data base. J. Cell. Biochem. Suppl. 24, 32–91 (1996)

    Article  CAS  Google Scholar 

  30. Shigematsu, H. et al. Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J. Natl. Cancer Inst. 97, 339–346 (2005)

    Article  CAS  Google Scholar 

  31. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003)

    Article  CAS  Google Scholar 

  32. Bruckova, L. et al. Proliferative potential and phenotypic analysis of long-term cultivated human granulosa cells initiated by addition of follicular fluid. J. Assist. Reprod. Genet. 28, 939–950 (2011)

    Article  Google Scholar 

  33. DuPage, M., Dooley, A. L. & Jacks, T. Conditional mouse lung cancer models using adenoviral or lentiviral delivery of Cre recombinase. Nat. Protocols 4, 1064–1072 (2009)

    Article  CAS  Google Scholar 

  34. Sun, M. et al. HER family receptor abnormalities in lung cancer brain metastases and corresponding primary tumors. Clin. Cancer Res. 15, 4829–4837 (2009)

    Article  CAS  Google Scholar 

  35. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009)

    Article  Google Scholar 

Download references


We thank J. Luo for sharing primary data; C. Marcireau for sharing information on merlin expression status in NSCLC lines; C. Xian, S. Zhang, B. Massant, and L.Bral for technical support. This work was supported by grants from the NCI, CPRIT and UT-Lung SPORE.

Author information

Authors and Affiliations



J.K. and M.A.W. designed the experiments. J.K. performed the experiments with assistance from G.M. E.M. and H.S.K. performed bioinformatic analysis. H.S.K., S.M., S.W., M.R. and B.A.P. conducted the siRNA screen. N.V., P.P.S., B.G. and J.D.M aided preclinical mouse models. R.E.F. and J.D.M. provided the cell doubling times. J.R.-C., P.V., C.-W.B.C. and I.I.W. aided clinical studies. Y.L., W.S. and E.B. provided KPT compounds, advice and bioanalytical data for KPT-330 in mouse plasma. J.E.N. and D.D. generated XPO1C528 cells. J.K. and M.A.W. wrote the manuscript.

Corresponding author

Correspondence to Michael A. White.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information

Nature thanks I. Macara, A. Vivancos and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Two-dimensional APC projection of 106 NSCLC lines based on whole-genome mRNA expression variation.

High-resolution, annotated version of Fig. 1a.

Extended Data Figure 2 Synthetic-lethal genetic interactions in KRAS-mutant NSCLC cells.

a, Distribution of the variation in mRNA expression among KRAS-mutant lines (red curve, n = 37), KRAS-wild-type lines (blue curve, n = 69) and all NSCLC lines (green curve). b, Top-ranked gene sets (FDR < 0.2, Kolmogorov–Smirnov P < 1 × 10−16) returned by functional GSEA. c, Genes present in leading edge gene representation among the gene sets in b. Known components of nuclear transport machinery (indicated in d) are labelled in blue. d, Biological process representation of the leading-edge synthetic-lethal gene-depletion targets. e, Cumulative distributions of the viability Z-scores for siRNA pools, targeting genes in d, among KRAS-mutant versus KRAS-wild-type cell lines. Kolmogorov–Smirnov test P value is indicated. f, Cumulative distributions of log2 difference scores for depletion of shRNAs in KRAS-mutant versus KRAS-wild-type cells. Red, shRNAs targeting genes encoding nuclear transport machinery from e; black, all other shRNAs. Kolmogorov–Smirnov test P value is indicated. Data obtained from a previous study3. g, Cell viability after UBB depletion (a broadly toxic siRNA target that serves as a positive transfection control) in KRAS-mutant versus wild-type lines. Unpaired t-test was used for the comparison. h, Rescue of XPO1 siRNA toxicity by ectopic expression of a mutant XPO1 cDNA designed to be resistant to XPO1 siRNA number 4. Lamin A/C is shown as a loading control.

Source data

Extended Data Figure 3 Selective sensitivity of KRAS-mutant NSCLC cells to chemical inhibition of the nuclear transport receptor XPO1.

a, Structures of SINE compounds (XPO1 inhibitors), KPT-185 and KPT-330. b, Enrichment of short doubling times in KRAS-mutant versus wild-type NSCLC lines. Box plots indicate median and IQR. Unpaired t-test was used for the comparison. c, The 8-point dose–response viability curves for the indicated panel of NSCLC lines following a 72-h exposure to KPT-185. Mean ± s.d. (n = 3) is shown. d, Correlation of sensitivity to the XPO1 inhibitors KPT-330 and KPT-185. AUCs from c and Fig. 2a. Red, KRAS mutant; blue, KRAS wild type. Pearson correlation P value is indicated. e, Response of KRAS-mutant versus KRAS-wild-type cohorts to XPO1 inhibitors. Box plots indicate median values and IQR, an unpaired t-test was used for the comparison. f, Scatter plot of cell-line doubling time versus KPT-185 sensitivity. Pearson correlation P value is indicated. g, Sequencing chromatogram of XPO1 genomic DNA of genome-edited cells. The C528S substitution was induced by CRISPR/Cas9-induced homologous recombination. Three synonymous mutations were simultaneously introduced near the PAM site (underlined) in order to prevent re-cutting of the recombined DNA. h, Selective sensitivity of KRAS-mutant lines to KPT-330 at doses over 400% higher than bioactive in vivo concentrations. Post-confluent cells were exposed to KPT-330 for 5 days. i, Response of KRASG12V-expressing lung epithelia (HBEC30KP), versus wild-type parental epithelia (HBEC30), to KPT-185 and KPT-330. Left, mean ± s.d., n = 3; right, monolayer assay is as in h. j, Cytotoxic effect of 2 μM KPT-330 on the indicated NRAS-mutant cell lines. Monolayer assay is as in h. k, Lung tumour burden pre- and post-treatment as indicated by magnetic resonance images. Two mice presenting with exceptionally high initial tumour burden were treated with 10 mg kg−1 KPT-330 five times per week. Lungs were imaged with serial transverse magnetic resonance sections on treatment day 0 and again on day 21.

Source data

Extended Data Figure 4 Selective addiction to NFκB activity specifies sensitivity to XPO1 inhibition.

a, Top five gene sets that significantly discriminate XPO1-inhibitor-sensitive lines from XPO1-inhibitor-resistant lines. NFκB target gene sets are indicated in blue. b, Top 50 differentially expressed genes ranked by signal-to-noise (S2N) ratio. Known NFκB targets are indicated in red (16/133; hypergeometric P < 1 × 10−16). c, Top 3 gene sets that are downregulated by a 12-h exposure to an XPO1 inhibitor. NFκB target gene sets are indicated in blue. d, Enrichment plot of NFκB target genes (KPT-185-treated versus DMSO-treated). e, Evidence for attenuated NFκB signalling in XPO1-inhibitor-resistant NRAS-mutant cell lines. Empirical cumulative distributions of NFκB target gene expression (from b) are shown for NRAS-mutant cell lines versus KRAS-mutant cell lines as indicated. Yellow, NRAS-mutant/XPO1-inhibitor-resistant lines (H2087, H1299 and HCC1195, shown in Extended Data Fig. 3j); red, KRAS-mutant/XPO1-inhibitor-sensitive line (shown in Figs 2, 3). Yellow versus red, P < 0.01 using Kolmogorov–Smirnov test. f, Immunoblot of IκBα 48 h post-transfection of siNFKBIA/siNFKBIB (targeting genes that express IκBα/IκBβ) for confirmation of target depletion. Histone H3 is shown as a loading control. g, IκB-dependent sensitivity to KPT-185. Cells were exposed to the indicated concentrations of XPO1 inhibitors for 72 h 24 h post-transfection with the indicated siRNA. Mean and range (n = 2). h, Intolerance to ectopic nuclear accumulation of IκBα in XPO1-inhibitor-sensitive cells. Left, y axis indicates fold change in the percentage of GFP-positive nuclei of GFP-IκB-NES-mutant-positive cells normalized to GFP-empty-vector-positive cells. Bars indicate mean ± s.d. for three independent experiments (*P < 0.05, Unpaired t-test). Right, 293T cells transfected with the indicated plasmids to confirm plasmid transfection efficiency and localization of ectopically expressed proteins. Cells were fixed and photographed 48 h post-transfection. i, Positive correlation between sensitivity to KPT-185 and BMS-345541 (P < 0.01, Pearson correlation). Dose–response curves of a panel of NSCLC lines following a 72-h exposure to BMS-345541. Mean ± s.d. (n = 3). AUCs of KPT-185 were determined from Extended Data Fig. 3c. Red labels, KRAS mutant/XPO1-inhibitor sensitive; green labels, KRAS mutant/XPO1-inhibitor resistant; blue labels, KRAS wild type. j, Dose–response curves of a panel of NSCLC lines following a 72-h exposure to Trametinib. Mean and range (n = 2). Label colours as in i. k, Dose–response curves of a panel of NSCLC lines following a 72-h exposure to KPT-185 combined with the indicated concentrations of Trametinib. Mean and range (n = 2). l, Subcellular localization of IκBα in the presence of 1 μM KPT-185. Cells were exposed to KPT-185 for 24 h. Label colours are as in i.

Source data

Extended Data Figure 5 Concurrent mutations in FSTL5 are associated with intrinsic resistance of KRAS-mutant lines to XPO1 inhibitor.

a, Eight-point dose–response viability curves for H2122 and H2030 following a 72-h exposure to KPT-185. Mean ± s.d. (n = 3). Data are overlaid with responses of the indicated lines from Extended Data Fig. 3c for comparison. b, KPT-185 dose–response curves. Mean ± s.d. (n = 3). c, FSTL5 Sanger-sequencing chromatograms of detected FSTL5 variants in the indicated cell lines. d, Map of somatic alterations in FSTL5 detected in all cancers (TCGA), lung adenocarcinoma (TCGA), lung squamous (TCGA), NSCLC cell lines (this study), and human lung tumour samples, 1805 and 1930 (this study). e, Tumour suppressor genes identified in an oncogenomics-based in vivo RNAi screen19. Among the genes targeted by 36 shRNAs overrepresented during HCC tumour development, Fstl5 was the third ranked gene suppressed by >1 enriched shRNA. The y axis indicates number of shRNAs per gene among the 36 enriched shRNAs. The x axis indicates shRNA specific reads over a total 2,307 sequence reads. f, g, KPT-185 dose–response of cells transfected with the indicated siRNAs as in Extended Data Fig. 4g. f shows KRAS-mutant/FSTL5-wild-type lines, g shows KRAS-mutant/FSTL5 mutant lines. Mean and range (n = 2). h, Relative ectopic expression of FSTL5 mRNA. Cells were infected with retrovirus carrying the indicated plasmids. Following a 7-day puromycin selection, cells were collected for qPCR. Mean and range (n = 2).

Source data

Extended Data Figure 6 Concurrent mutations in FSTL5 are mechanistically coupled to YAP1 activation.

a, Expression of FSTL5 mRNA (left) and YAP1 protein (right) following transfection with the indicated siRNAs targeting FSTL5. Cells were collected 72 h post-transfection for parallel qPCR and immunoblotting. Mean and range (n = 2). b, Intersection of the FSTL5-dependent and LATS-dependent gene expression programs in KRAS-mutant/XPO1-inhibitor-sensitive NSCLC lines. To evaluate the enrichment of YAP-responsive genes within the FSTL5-dependent gene expression network, quantitative whole-genome transcript arrays were prepared with mRNA isolated from the indicated cell lines treated with the indicated siRNAs 72 h post-transfection. LATS1/2 depletion was used to activate YAP-dependent gene expression. All arrays were normalized to corresponding control siRNA-treated samples. Euler plots indicate genes up- or downregulated at least twofold in response to siFSTL5, siLATS or both; hypergeometric P values are indicated. c, YAP1 fluorescence micrographs and representative YAP1 immunohistochemistry. H2009 and H2030 cell lines were used as a negative and positive control for YAP1 staining, respectively. d, Stably overexpressed YAP1 in KRAS-mutant/XPO1-inhibitor-sensitive lines. Cells were infected with the indicated retroviral vector, selected with hygromycin and then collected for immunoblotting. e, Induction of XPO1-inhibitor resistance by YAP1 overexpression. Proliferating cells stably expressing indicated plasmids were exposed to XPO1 inhibitors for 3 days. Mean ± range (n = 2). f, Immunoblot of the indicated proteins in KRAS-mutant/XPO1-inhibitor-resistant lines following a 24-h exposure to 1 mm AICAR. AICAR resulted in accumulation of phospho-acetyl-CoA-carboxlyase (pACC), an indicator of AMPK activation in all the lines tested except A549. A549 is known to be non-responsive to AICAR owing to the absence of LKB1 (also known as STK11) expression7. g, Subcellular localization of YAP1 in response to 0.5 or 1 mm AICAR. Cells were exposed to AICAR for 24 h. Cytoplasmic accumulation of YAP1 was observed in response to AICAR exposure in H2030, but not in A549. h, Resistance of KRAS-wild-type lines to KPT-330 in combination with AICAR. Post-confluent cells were exposed to the indicated compounds for 3 days. i, Induction of XPO1 inhibitor-sensitivity by YAP1 and TEAD2 depletion. 48 h post-transfection with the indicated siRNAs, cells were exposed to the indicated concentrations of XPO1 inhibitors for 3 days. Mean and range (n = 2). j, Cytotoxic effect of 2 μM KPT-330 on indicated cell lines. Post-confluent cells were exposed to KPT-330 for 5 days. Red labels, KRAS-mutant/XPO1-inhibitor-sensitive; green labels, KRAS-mutant/XPO1-inhibitor-resistant; blue labels, KRAS wild type. k, Evidence for NFκB pathway activation in H1648 cells. Empirical cumulative distributions of NFκB target gene expression (from Extended Data Fig. 4b) are shown for H1648 versus KRAS-wild-type cell lines as indicated. Blue, KRAS-wild-type/XPO1-inhibitor-resistant lines (H2882, HCC15, H1395, H1993 and HCC95 shown in Figs 2 and 3); yellow, KRAS-wild-type/XPO1-inhibitor-sensitive line H1648 (shown in j). Cancer Cell Line Encyclopedia data indicates that H1648 harbours genomic amplification of IKBKB. Blue versus yellow, P < 0.01, Kolmogorov–Smirnov test. l, Merlin expression is absent in Calu1 cells. m, Cytotoxic effect of the indicated compounds on the indicated cell lines. Post-confluent cells were treated as in h. HCC515 harbours a somatic mutation in LATS1.

Source data

Supplementary information

Supplementary Figure 1

This file contains the Source data for gel images. (PDF 1445 kb)

Supplementary Tables

This file contains Supplementary Tables 1-8. (XLSX 32388 kb)

PowerPoint slides

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, J., McMillan, E., Kim, H. et al. XPO1-dependent nuclear export is a druggable vulnerability in KRAS-mutant lung cancer. Nature 538, 114–117 (2016).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer