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.

  • Article
  • Published:

Transposon mutagenesis identifies genes driving hepatocellular carcinoma in a chronic hepatitis B mouse model

Nature Genetics volume 46, pages 24–32 (2014)Cite this article

Subjects

Abstract

The most common risk factor for developing hepatocellular carcinoma (HCC) is chronic infection with hepatitis B virus (HBV). To better understand the evolutionary forces driving HCC, we performed a near-saturating transposon mutagenesis screen in a mouse HBV model of HCC. This screen identified 21 candidate early stage drivers and a very large number (2,860) of candidate later stage drivers that were enriched for genes that are mutated, deregulated or functioning in signaling pathways important for human HCC, with a striking 1,199 genes being linked to cellular metabolic processes. Our study provides a comprehensive overview of the genetic landscape of HCC.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: Liver-SB/HBsAg mice have chronic liver inflammation and accelerated formation of HCC.
Figure 2: Identification of driver genes for HCC in the liver-SB/HBV screen.
Figure 3: Many liver-SB/HBV CIS genes are deregulated or mutated in human cancer.
Figure 4: Liver-SB/HBV CIS genes drive tumorigenesis through conserved cancer signaling pathways.
Figure 5: Mapping of genomic and metabonomic data to metabolic pathways disrupted in HCC.
Figure 6: Quantitative changes in pyruvate metabolism can be detected by hyperpolarized carbon-13 magnetic resonance spectroscopy in vivo.

Similar content being viewed by others

Accession codes

Accessions

Gene Expression Omnibus

References

  1. Chen, X. et al. Gene expression patterns in human liver cancers. Mol. Biol. Cell 13, 1929–1939 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Imbeaud, S., Ladeiro, Y. & Zucman-Rossi, J. Identification of novel oncogenes and tumor suppressors in hepatocellular carcinoma. Semin. Liver Dis. 30, 75–86 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Mas, V.R. et al. Genes involved in viral carcinogenesis and tumor initiation in hepatitis C virus–induced hepatocellular carcinoma. Mol. Med. 15, 85–94 (2009).

    Article  CAS  PubMed  Google Scholar 

  4. Roessler, S. et al. A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients. Cancer Res. 70, 10202–10212 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Wurmbach, E. et al. Genome-wide molecular profiles of HCV-induced dysplasia and hepatocellular carcinoma. Hepatology 45, 938–947 (2007).

    Article  CAS  PubMed  Google Scholar 

  6. Herath, N.I., Leggett, B.A. & MacDonald, G.A. Review of genetic and epigenetic alterations in hepatocarcinogenesis. J. Gastroenterol. Hepatol. 21, 15–21 (2006).

    Article  CAS  PubMed  Google Scholar 

  7. Herceg, Z. & Paliwal, A. Epigenetic mechanisms in hepatocellular carcinoma: how environmental factors influence the epigenome. Mutat. Res. 727, 55–61 (2011).

    Article  CAS  PubMed  Google Scholar 

  8. Berger, A.H., Knudson, A.G. & Pandolfi, P.P. A continuum model for tumour suppression. Nature 476, 163–169 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. ENCODE Project Consortium. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  10. Fujimoto, A. et al. Whole-genome sequencing of liver cancers identifies etiological influences on mutation patterns and recurrent mutations in chromatin regulators. Nat. Genet. 44, 760–764 (2012).

    Article  CAS  PubMed  Google Scholar 

  11. Guichard, C. et al. Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma. Nat. Genet. 44, 694–698 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Copeland, N.G. & Jenkins, N.A. Harnessing transposons for cancer gene discovery. Nat. Rev. Cancer 10, 696–706 (2010).

    Article  CAS  PubMed  Google Scholar 

  13. Dupuy, A.J., Akagi, K., Largaespada, D.A., Copeland, N.G. & Jenkins, N.A. Mammalian mutagenesis using a highly mobile somatic Sleeping Beauty transposon system. Nature 436, 221–226 (2005).

    Article  CAS  PubMed  Google Scholar 

  14. Dupuy, A.J. et al. A modified sleeping beauty transposon system that can be used to model a wide variety of human cancers in mice. Cancer Res. 69, 8150–8156 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Rad, R. et al. PiggyBac transposon mutagenesis: a tool for cancer gene discovery in mice. Science 330, 1104–1107 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Yang, J.D. & Roberts, L.R. Hepatocellular carcinoma: a global view. Nat. Rev. Gastroenterol. Hepatol. 7, 448–458 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Keng, V.W. et al. A conditional transposon-based insertional mutagenesis screen for genes associated with mouse hepatocellular carcinoma. Nat. Biotechnol. 27, 264–274 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Chisari, F.V. et al. Molecular pathogenesis of hepatocellular carcinoma in hepatitis B virus transgenic mice. Cell 59, 1145–1156 (1989).

    Article  CAS  PubMed  Google Scholar 

  19. Mann, K.M. et al. Sleeping Beauty mutagenesis reveals cooperating mutations and pathways in pancreatic adenocarcinoma. Proc. Natl. Acad. Sci. USA 109, 5934–5941 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Brett, B.T. et al. Novel molecular and computational methods improve the accuracy of insertion site analysis in Sleeping Beauty–induced tumors. PLoS ONE 6, e24668 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. de Ridder, J., Uren, A., Kool, J., Reinders, M. & Wessels, L. Detecting statistically significant common insertion sites in retroviral insertional mutagenesis screens. PLoS Comput. Biol. 2, e166 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. March, H.N. et al. Insertional mutagenesis identifies multiple networks of cooperating genes driving intestinal tumorigenesis. Nat. Genet. 43, 1202–1209 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Swanton, C. Intratumor heterogeneity: evolution through space and time. Cancer Res. 72, 4875–4882 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Pérez-Mancera, P.A. et al. The deubiquitinase USP9X suppresses pancreatic ductal adenocarcinoma. Nature 486, 266–270 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Solimini, N.L. et al. Recurrent hemizygous deletions in cancers may optimize proliferative potential. Science 337, 104–109 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Whittaker, S., Marais, R. & Zhu, A.X. The role of signaling pathways in the development and treatment of hepatocellular carcinoma. Oncogene 29, 4989–5005 (2010).

    Article  CAS  PubMed  Google Scholar 

  27. Schmidt, V.A., Chiariello, C.S., Capilla, E., Miller, F. & Bahou, W.F. Development of hepatocellular carcinoma in Iqgap2-deficient mice is IQGAP1 dependent. Mol. Cell. Biol. 28, 1489–1502 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Zhang, G., Liu, T. & Wang, Z. Downregulation of MAGI1 associates with poor prognosis of hepatocellular carcinoma. J. Invest. Surg. 25, 93–99 (2012).

    Article  PubMed  Google Scholar 

  29. Horie, Y. et al. Hepatocyte-specific Pten deficiency results in steatohepatitis and hepatocellular carcinomas. J. Clin. Invest. 113, 1774–1783 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lu, L. et al. Hippo signaling is a potent in vivo growth and tumor suppressor pathway in the mammalian liver. Proc. Natl. Acad. Sci. USA 107, 1437–1442 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Zheng, T., Wang, J., Jiang, H. & Liu, L. Hippo signaling in oval cells and hepatocarcinogenesis. Cancer Lett. 302, 91–99 (2011).

    Article  CAS  PubMed  Google Scholar 

  32. Santhekadur, P.K. et al. Multifunction protein staphylococcal nuclease domain containing 1 (SND1) promotes tumor angiogenesis in human hepatocellular carcinoma through novel pathway that involves nuclear factor κB and miR-221. J. Biol. Chem. 287, 13952–13958 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Yoo, B.K. et al. Increased RNA-induced silencing complex (RISC) activity contributes to hepatocellular carcinoma. Hepatology 53, 1538–1548 (2011).

    Article  CAS  PubMed  Google Scholar 

  34. Kojima, K. et al. MicroRNA122 is a key regulator of α-fetoprotein expression and influences the aggressiveness of hepatocellular carcinoma. Nat. Commun. 2, 338 (2011).

    Article  PubMed  CAS  Google Scholar 

  35. Xie, Z. et al. Zinc finger protein ZBTB20 is a key repressor of α-fetoprotein gene transcription in liver. Proc. Natl. Acad. Sci. USA 105, 10859–10864 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Flaim, C.J., Chien, S. & Bhatia, S.N. An extracellular matrix microarray for probing cellular differentiation. Nat. Methods 2, 119–125 (2005).

    Article  CAS  PubMed  Google Scholar 

  37. Watt, A.J. et al. A gene trap integration provides an early in situ marker for hepatic specification of the foregut endoderm. Mech. Dev. 100, 205–215 (2001).

    Article  CAS  PubMed  Google Scholar 

  38. Duns, G. et al. Histone methyltransferase gene SETD2 is a novel tumor suppressor gene in clear cell renal cell carcinoma. Cancer Res. 70, 4287–4291 (2010).

    Article  CAS  PubMed  Google Scholar 

  39. Jackson, R.C., Morris, H.P. & Weber, G. Adenosine deaminase and adenosine kinase in rat hepatomas and kidney tumours. Br. J. Cancer 37, 701–713 (1978).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Nii, A. et al. Significance of dihydropyrimidine dehydrogenase and thymidylate synthase mRNA expressions in hepatocellular carcinoma. Hepatol. Res. 39, 274–281 (2009).

    Article  CAS  PubMed  Google Scholar 

  41. Queener, S.F., Morris, H.P. & Weber, G. Dihydrouracil dehydrogenase activity in normal, differentiating and regnerating liver and in hepatomas. Cancer Res. 31, 1004–1009 (1971).

    CAS  PubMed  Google Scholar 

  42. Cheng, F. et al. Camptothecin-induced downregulation of MLL5 contributes to the activation of tumor suppressor p53. Oncogene 30, 3599–3611 (2011).

    Article  CAS  PubMed  Google Scholar 

  43. Bernard, F. et al. Alterations of NFIA in chronic malignant myeloid diseases. Leukemia 23, 583–585 (2009).

    Article  CAS  PubMed  Google Scholar 

  44. 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, 5539–5543 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Vinciguerra, M. & Foti, M. PTEN at the crossroad of metabolic diseases and cancer in the liver. Ann. Hepatol. 7, 192–199 (2008).

    Article  CAS  PubMed  Google Scholar 

  46. Cohen, P. & Frame, S. The renaissance of GSK3. Nat. Rev. Mol. Cell Biol. 2, 769–776 (2001).

    Article  CAS  PubMed  Google Scholar 

  47. Bjursell, M.K. et al. Adenosine kinase deficiency disrupts the methionine cycle and causes hypermethioninemia, encephalopathy, and abnormal liver function. Am. J. Hum. Genet. 89, 507–515 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Boison, D. et al. Neonatal hepatic steatosis by disruption of the adenosine kinase gene. Proc. Natl. Acad. Sci. USA 99, 6985–6990 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Sutherland, A.P. et al. Zinc finger protein Zbtb20 is essential for postnatal survival and glucose homeostasis. Mol. Cell. Biol. 29, 2804–2815 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Fan, Y. et al. Liver-specific deletion of the growth hormone receptor reveals essential role of growth hormone signaling in hepatic lipid metabolism. J. Biol. Chem. 284, 19937–19944 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Mavalli, M.D. et al. Distinct growth hormone receptor signaling modes regulate skeletal muscle development and insulin sensitivity in mice. J. Clin. Invest. 120, 4007–4020 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. da Rocha, S.T., Edwards, C.A., Ito, M., Ogata, T. & Ferguson-Smith, A.C. Genomic imprinting at the mammalian Dlk1-Dio3 domain. Trends Genet. 24, 306–316 (2008).

    Article  PubMed  CAS  Google Scholar 

  53. Luk, J.M. et al. DLK1–DIO3 genomic imprinted microRNA cluster at 14q32.2 defines a stemlike subtype of hepatocellular carcinoma associated with poor survival. J. Biol. Chem. 286, 30706–30713 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Sung, W.K. et al. Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma. Nat. Genet. 44, 765–769 (2012).

    Article  CAS  PubMed  Google Scholar 

  55. Edgar, B.A. From cell structure to transcription: Hippo forges a new path. Cell 124, 267–273 (2006).

    Article  CAS  PubMed  Google Scholar 

  56. Budhu, A. et al. Integrated metabolite and gene expression profiles identify lipid biomarkers associated with progression of hepatocellular carcinoma and patient outcomes. Gastroenterology 144, 1066–1075 (2013).

    Article  CAS  PubMed  Google Scholar 

  57. Lee, P. et al. In vivo hyperpolarized carbon-13 magnetic resonance spectroscopy reveals increased pyruvate carboxylase flux in an insulin resistant mouse model. Hepatology 57, 515–524 (2013).

    Article  CAS  PubMed  Google Scholar 

  58. DeBerardinis, R.J. & Cheng, T. Q's next: the diverse functions of glutamine in metabolism, cell biology and cancer. Oncogene 29, 313–324 (2010).

    Article  CAS  PubMed  Google Scholar 

  59. Beyoğlu, D. et al. Tissue metabolomics of hepatocellular carcinoma: tumor energy metabolism and the role of transcriptomic classification. Hepatology 58, 229–238 (2013).

    Article  PubMed  CAS  Google Scholar 

  60. Anderson, K. et al. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature 469, 356–361 (2011).

    Article  CAS  PubMed  Google Scholar 

  61. Hou, Y. et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell 148, 873–885 (2012).

    Article  CAS  PubMed  Google Scholar 

  62. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Berquam-Vrieze, K.E. et al. Cell of origin strongly influences genetic selection in a mouse model of T-ALL. Blood 118, 4646–4656 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Gao, H. et al. Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis. Cancer Sci. 100, 782–785 (2009).

    Article  CAS  PubMed  Google Scholar 

  65. Wang, B. et al. Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry. J. Proteome Res. 11, 1217–1227 (2012).

    Article  CAS  PubMed  Google Scholar 

  66. Yang, Y. et al. Metabonomic studies of human hepatocellular carcinoma using high-resolution magic-angle spinning 1H NMR spectroscopy in conjunction with multivariate data analysis. J. Proteome Res. 6, 2605–2614 (2007).

    Article  CAS  PubMed  Google Scholar 

  67. Ward, P.S. & Thompson, C.B. Metabolic reprogramming: a cancer hallmark even Warburg did not anticipate. Cancer Cell 21, 297–308 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Chen, T. et al. Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma. Mol. Cell. Proteomics 10, M110.004945 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Cairns, R.A., Harris, I.S. & Mak, T.W. Regulation of cancer cell metabolism. Nat. Rev. Cancer 11, 85–95 (2011).

    Article  CAS  PubMed  Google Scholar 

  70. Christofk, H.R. et al. The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature 452, 230–233 (2008).

    Article  CAS  PubMed  Google Scholar 

  71. David, C.J., Chen, M., Assanah, M., Canoll, P. & Manley, J.L. HnRNP proteins controlled by c-Myc deregulate pyruvate kinase mRNA splicing in cancer. Nature 463, 364–368 (2010).

    Article  CAS  PubMed  Google Scholar 

  72. DeBerardinis, R.J. et al. Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc. Natl. Acad. Sci. USA 104, 19345–19350 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Wise, D.R. et al. Hypoxia promotes isocitrate dehydrogenase–dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability. Proc. Natl. Acad. Sci. USA 108, 19611–19616 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Vander Heiden, M.G. Targeting cancer metabolism: a therapeutic window opens. Nat. Rev. Drug Discov. 10, 671–684 (2011).

    Article  CAS  PubMed  Google Scholar 

  75. Postic, C. & Magnuson, M.A. DNA excision in liver by an albumin-Cre transgene occurs progressively with age. Genesis 26, 149–150 (2000).

    Article  CAS  PubMed  Google Scholar 

  76. Thoolen, B. et al. Proliferative and nonproliferative lesions of the rat and mouse hepatobiliary system. Toxicol. Pathol. 38, 5S–81S (2010).

    Article  PubMed  Google Scholar 

  77. Morrow, M., Samanta, A., Kioussis, D., Brady, H.J. & Williams, O. TEL-AML1 preleukemic activity requires the DNA binding domain of AML1 and the dimerization and corepressor binding domains of TEL. Oncogene 26, 4404–4414 (2007).

    Article  CAS  PubMed  Google Scholar 

  78. Jee, J. et al. ACT: aggregation and correlation toolbox for analyses of genome tracks. Bioinformatics 27, 1152–1154 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Eppig, J.T. et al. Mouse genome informatics (MGI) resources for pathology and toxicology. Toxicol. Pathol. 35, 456–457 (2007).

    Article  PubMed  Google Scholar 

  80. Kasprzyk, A. BioMart: driving a paradigm change in biological data management. Database (Oxford) 2011, bar049 (2011).

    Article  Google Scholar 

  81. Sayers, E.W. et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 40, D13–D25 (2012).

    Article  CAS  PubMed  Google Scholar 

  82. Chew, V. et al. Chemokine-driven lymphocyte infiltration: an early intratumoural event determining long-term survival in resectable hepatocellular carcinoma. Gut 61, 427–438 (2012).

    Article  CAS  PubMed  Google Scholar 

  83. Spurgeon, S.L., Jones, R.C. & Ramakrishnan, R. High throughput gene expression measurement with real time PCR in a microfluidic dynamic array. PLoS One 3, e1662 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  84. Schmittgen, T.D. & Livak, K.J. Analyzing real-time PCR data by the comparative C(T) method. Nat. Protoc. 3, 1101–1108 (2008).

    Article  CAS  PubMed  Google Scholar 

  85. Huang, W., Sherman, B.T. & Lempicki, R.A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

    Article  CAS  Google Scholar 

  86. Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863–14868 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Schroeder, M.A. et al. Measuring intracellular pH in the heart using hyperpolarized carbon dioxide and bicarbonate: a 13C and 31P magnetic resonance spectroscopy study. Cardiovasc. Res. 86, 82–91 (2010).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We acknowledge K. Reifenberg at Johannes Gutenberg University, Germany, for giving us the HBsAg mouse strain (originated from F. Chisari). We also thank K. Rogers and S. Rogers at the Institute of Molecular and Cell Biology Histopathology core for their necropsy and histotechnology assistance. We thank P. Cheok, N. Lim and D. Chen for their help with mouse breeding and monitoring. This work was supported by the Biomedical Research Council, Agency for Science, Technology and Research, Singapore and the Cancer Prevention Research Institute of Texas (CPRIT). A.G.R. and D.J.A. are supported by the Wellcome Trust and Cancer Research UK. N.A.J. and N.G.C. are both CPRIT Scholars in Cancer Research.

Author information

Author notes

  1. Nancy A Jenkins & Neal G Copeland

    Present address: Present address: The Methodist Hospital Research Institute, Houston, Texas, USA.,

  2. Nancy A Jenkins and Neal G Copeland: These authors contributed equally to this work.

Authors and Affiliations

  1. Institute Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore

    Emilie A Bard-Chapeau, Anh-Tuan Nguyen, Ahmed Sayadi, Belinda Q Chua, Jerrold M Ward, Christopher K Y Chin, Frederic A Bard, Nancy A Jenkins & Neal G Copeland

  2. Experimental Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK

    Alistair G Rust & David J Adams

  3. Clinical Imaging Research Centre, National University of Singapore, Centre for Translation Medicine, Singapore Bioimaging Consortium, Singapore

    Philip Lee & George K Radda

  4. Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore

    Lee-Sun New & Eric Chun Yong Chan

  5. Department of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Johann de Jong & Lodewyk F A Wessels

  6. Singapore Immunology Network (SIgN), A*STAR, Biopolis, Singapore

    Valerie Chew & Jean-Pierre Abastado

  7. National Cancer Centre, Singapore

    Han Chong Toh

  8. Cancer Science Institute of Singapore, National University of Singapore, Singapore

    Touati Benoukraf & Richie Soong

  9. Department of Anatomy and Cell Biology, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA

    Adam J Dupuy

  10. Department of Biochemistry and Molecular Biology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA

    Randy L Johnson

Authors
  1. Emilie A Bard-Chapeau
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anh-Tuan Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alistair G Rust
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmed Sayadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Philip Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Belinda Q Chua
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Lee-Sun New
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Johann de Jong
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jerrold M Ward
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Christopher K Y Chin
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Valerie Chew
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Han Chong Toh
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Jean-Pierre Abastado
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Touati Benoukraf
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Richie Soong
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Frederic A Bard
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Adam J Dupuy
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Randy L Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. George K Radda
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Eric Chun Yong Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Lodewyk F A Wessels
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. David J Adams
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Nancy A Jenkins
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Neal G Copeland
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.A.B.-C. performed the majority of experiments, designed experiments, analyzed data and wrote the manuscript. A.-T.N. performed experiments, analyzed data and wrote the manuscript. A.G.R. and D.J.A. sequenced the samples and processed and analyzed data. A.S., C.K.Y.C., T.B., R.S. and F.A.B. performed computational analyses. B.Q.C. executed experiments. E.C.Y.C. and L.-S.N. performed the metabolomics study. P.L. and G.K.R. carried out in vivo metabolic imaging and metabolic assays. J.M.W. analyzed mouse hepatic pathology. J.-P.A., V.C. and H.C.T. provided and processed human patient samples. A.J.D. helped analyze data, and R.L.J. carried out the liver-SB screen in the Sav1 mutant background. J.d.J. and L.F.A.W. revised statistics and performed analyses. N.G.C. and N.A.J. designed the study, analyzed the data and wrote the manuscript. All authors commented on and edited the final manuscript.

Corresponding author

Correspondence to Neal G Copeland.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–19 (PDF 4223 kb)

Supplementary Table 1

Supplementary Table 1 (XLSX 877 kb)

Supplementary Table 2

Supplementary Table 2 (XLSX 172 kb)

Supplementary Table 3

Supplementary Table 3 (XLSX 172 kb)

Supplementary Table 4

Supplementary Table 4 (XLSX 27 kb)

Supplementary Table 5

Supplementary Table 5 (XLSX 15 kb)

Supplementary Table 6

Supplementary Table 6 (XLSX 467 kb)

Supplementary Table 7

Supplementary Table 7 (XLSX 16 kb)

Supplementary Dataset 1

Supplementary Dataset 1 (TXT 24709 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bard-Chapeau, E., Nguyen, AT., Rust, A. et al. Transposon mutagenesis identifies genes driving hepatocellular carcinoma in a chronic hepatitis B mouse model. Nat Genet 46, 24–32 (2014). https://doi.org/10.1038/ng.2847

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.2847

This article is cited by

Search

Advanced search

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