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Human primary liver cancer–derived organoid cultures for disease modeling and drug screening

Abstract

Human liver cancer research currently lacks in vitro models that can faithfully recapitulate the pathophysiology of the original tumor. We recently described a novel, near-physiological organoid culture system, wherein primary human healthy liver cells form long-term expanding organoids that retain liver tissue function and genetic stability. Here we extend this culture system to the propagation of primary liver cancer (PLC) organoids from three of the most common PLC subtypes: hepatocellular carcinoma (HCC), cholangiocarcinoma (CC) and combined HCC/CC (CHC) tumors. PLC-derived organoid cultures preserve the histological architecture, gene expression and genomic landscape of the original tumor, allowing for discrimination between different tumor tissues and subtypes, even after long-term expansion in culture in the same medium conditions. Xenograft studies demonstrate that the tumorogenic potential, histological features and metastatic properties of PLC-derived organoids are preserved in vivo. PLC-derived organoids are amenable for biomarker identification and drug-screening testing and led to the identification of the ERK inhibitor SCH772984 as a potential therapeutic agent for primary liver cancer. We thus demonstrate the wide-ranging biomedical utilities of PLC-derived organoid models in furthering the understanding of liver cancer biology and in developing personalized-medicine approaches for the disease.

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Figure 1: Patient-derived primary liver cancer organoid cultures expand long-term in vitro while maintaining the histological architecture of the tumor subtype from which they were derived.
Figure 2: Immunohistochemistry analyses reveal that the PLC tumoroids retain expression patterns of the distinct subtype of the original tissue from which they were derived, even after long-term expansion in culture.
Figure 3: Tumoroids recapitulate the expression profiles of the specific tissue of origin.
Figure 4: Tumoroids preserve the genetic alterations from the original tumor.
Figure 5: In vivo growth and metastatic potential of PLC tumoroids.
Figure 6: PLC tumoroid lines as a platform for drug screening and validation of actionable therapeutic targets.

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References

  1. Bosch, F.X., Ribes, J., Díaz, M. & Cléries, R. Primary liver cancer: worldwide incidence and trends. Gastroenterology 127 (Suppl. 1), S5–S16 (2004).

    Article  PubMed  Google Scholar 

  2. Bridgewater, J. et al. Guidelines for the diagnosis and management of intrahepatic cholangiocarcinoma. J. Hepatol. 60, 1268–1289 (2014).

    Article  PubMed  Google Scholar 

  3. Hirohashi, S. et al. Tumours of the Liver and Intrahepatic Bile Ducts. in World Health Organization Classification of Tumours (eds. Stanley R. Hamilton, M.D. & Lauri A. Aaltonen, M.D., Ph.D.) (IARCPress, 69372 Lyon, France, 2000).

  4. Lee, S.D. et al. Clinicopathological features and prognosis of combined hepatocellular carcinoma and cholangiocarcinoma after surgery. Hepatobiliary Pancreat. Dis. Int. 13, 594–601 (2014).

    Article  CAS  PubMed  Google Scholar 

  5. International Consensus Group for Hepatocellular NeoplasiaThe International Consensus Group for Hepatocellular Neoplasia. Pathologic diagnosis of early hepatocellular carcinoma: a report of the international consensus group for hepatocellular neoplasia. Hepatology 49, 658–664 (2009).

  6. Marquardt, J.U. & Andersen, J.B. Liver cancer oncogenomics: opportunities and dilemmas for clinical applications. Hepat. Oncol. 2, 79–93 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Wang, A.-Q. et al. Combined hepatocellular cholangiocarcinoma: Controversies to be addressed. World J. Gastroenterol. 22, 4459–4465 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sharma, S.V., Haber, D.A. & Settleman, J. Cell line-based platforms to evaluate the therapeutic efficacy of candidate anticancer agents. Nat. Rev. Cancer 10, 241–253 (2010).

    Article  CAS  PubMed  Google Scholar 

  9. De Minicis, S. et al. Liver carcinogenesis: rodent models of hepatocarcinoma and cholangiocarcinoma. Dig. Liver Dis. 45, 450–459 (2013).

    Article  CAS  PubMed  Google Scholar 

  10. Oikawa, T. et al. Model of fibrolamellar hepatocellular carcinomas reveals striking enrichment in cancer stem cells. Nat. Commun. 6, 8070 (2015).

    Article  CAS  PubMed  Google Scholar 

  11. Shamir, E.R. & Ewald, A.J. Three-dimensional organotypic culture: experimental models of mammalian biology and disease. Nat. Rev. Mol. Cell Biol. 15, 647–664 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ku, J.L. et al. Establishment and characterisation of six human biliary tract cancer cell lines. Br. J. Cancer 87, 187–193 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Cavalloni, G. et al. Establishment and characterization of a human intrahepatic cholangiocarcinoma cell line derived from an Italian patient. Tumour Biol. 37, 4041–4052 (2016).

    Article  CAS  PubMed  Google Scholar 

  14. Huch, M. & Koo, B.-K. Modeling mouse and human development using organoid cultures. Development 142, 3113–3125 (2015).

    Article  CAS  PubMed  Google Scholar 

  15. Hindley, C.J., Cordero-Espinoza, L. & Huch, M. Organoids from adult liver and pancreas: stem cell biology and biomedical utility. Dev. Biol. 420, 251–261 (2016).

    Article  CAS  PubMed  Google Scholar 

  16. Crespo, M. et al. Colonic organoids derived from human induced pluripotent stem cells for modeling colorectal cancer and drug testing. Nat. Med. 23, 878–884 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Li, X. et al. Oncogenic transformation of diverse gastrointestinal tissues in primary organoid culture. Nat. Med. 20, 769–777 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Sato, T. et al. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett's epithelium. Gastroenterology 141, 1762–1772 (2011).

    Article  CAS  PubMed  Google Scholar 

  19. van de Wetering, M. et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161, 933–945 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Boj, S.F. et al. Organoid models of human and mouse ductal pancreatic cancer. Cell 160, 324–338 (2015).

    Article  CAS  PubMed  Google Scholar 

  21. Gao, D. et al. Organoid cultures derived from patients with advanced prostate cancer. Cell 159, 176–187 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Huch, M. et al. Unlimited in vitro expansion of adult bi-potent pancreas progenitors through the Lgr5/R-spondin axis. EMBO J. 32, 2708–2721 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Huch, M. et al. In vitro expansion of single Lgr5+ liver stem cells induced by Wnt-driven regeneration. Nature 494, 247–250 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Huch, M. et al. Long-term culture of genome-stable bipotent stem cells from adult human liver. Cell 160, 299–312 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Broutier, L. et al. Culture and establishment of self-renewing human and mouse adult liver and pancreas 3D organoids and their genetic manipulation. Nat. Protoc. 11, 1724–1743 (2016).

    Article  CAS  PubMed  Google Scholar 

  26. Brunt, E.M.P.V., Sempoux, C. & Theise, N.D. Biphenotypic (hepatobiliary) primary liver carcinomas: the work in progress. Hepat. Oncol. 2, 18 (2015).

    Google Scholar 

  27. Zhang, F. et al. Combined hepatocellular cholangiocarcinoma originating from hepatic progenitor cells: immunohistochemical and double-fluorescence immunostaining evidence. Histopathology 52, 224–232 (2008).

    Article  CAS  PubMed  Google Scholar 

  28. Zhao, Y.-J., Ju, Q. & Li, G.-C. Tumor markers for hepatocellular carcinoma. Mol. Clin. Oncol. 1, 593–598 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Ohguchi, S. et al. Expression of α-fetoprotein and albumin genes in human hepatocellular carcinomas: limitations in the application of the genes for targeting human hepatocellular carcinoma in gene therapy. Hepatology 27, 599–607 (1998).

    Article  CAS  PubMed  Google Scholar 

  30. Yakaboski, E., Jares, A. & Ma, Y. Stem cell gene SALL4 in aggressive hepatocellular carcinoma: a cancer stem cell-specific target? Hepatology 60, 419–421 (2014).

    Article  CAS  PubMed  Google Scholar 

  31. Yong, K.J. et al. Oncofetal gene SALL4 in aggressive hepatocellular carcinoma. N. Engl. J. Med. 368, 2266–2276 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Moeini, A. et al. Mixed hepatocellular cholangiocarcinoma tumors: Cholangiolocellular carcinoma is a distinct molecular entity. J. Hepatol. 66, 952–961 (2017).

    Article  CAS  PubMed  Google Scholar 

  33. Shibata, T. & Aburatani, H. Exploration of liver cancer genomes. Nat. Rev. Gastroenterol. Hepatol. 11, 340–349 (2014).

    Article  CAS  PubMed  Google Scholar 

  34. Woo, H.G. et al. Identification of a cholangiocarcinoma-like gene expression trait in hepatocellular carcinoma. Cancer Res. 70, 3034–3041 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Kalinich, M. et al. An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma. Proc. Natl. Acad. Sci. USA 114, 1123–1128 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kamlua, S. et al. A novel TFF2 splice variant (EX2TFF2) correlates with longer overall survival time in cholangiocarcinoma. Oncol. Rep. 27, 1207–1212 (2012).

    Article  CAS  PubMed  Google Scholar 

  37. Banales, J.M. et al. Expert consensus document: Cholangiocarcinoma: current knowledge and future perspectives consensus statement from the European Network for the Study of Cholangiocarcinoma (ENS-CCA). Nat. Rev. Gastroenterol. Hepatol. 13, 261–280 (2016).

    Article  PubMed  Google Scholar 

  38. Kraiklang, R. et al. A novel predictive equation for potential diagnosis of cholangiocarcinoma. PLoS One 9, e89337 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Andersen, J.B. et al. Genomic and genetic characterization of cholangiocarcinoma identifies therapeutic targets for tyrosine kinase inhibitors. Gastroenterology 142, 1021–1031.e15 (2012).

    Article  CAS  PubMed  Google Scholar 

  40. Hsieh, S.Y. et al. Stathmin1 overexpression associated with polyploidy, tumor-cell invasion, early recurrence, and poor prognosis in human hepatoma. Mol. Carcinog. 49, 476–487 (2010).

    Article  CAS  PubMed  Google Scholar 

  41. Blokzijl, F. et al. Tissue-specific mutation accumulation in human adult stem cells during life. Nature 538, 260–264 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Zou, S. et al. Mutational landscape of intrahepatic cholangiocarcinoma. Nat. Commun. 5, 5696 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. Totoki, Y. et al. High-resolution characterization of a hepatocellular carcinoma genome. Nat. Genet. 43, 464–469 (2011).

    Article  CAS  PubMed  Google Scholar 

  44. Li, M.M. et al. Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. J. Mol. Diagn. 19, 4–23 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Schulze, K. et al. Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets. Nat. Genet. 47, 505–511 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Borlak, J., Meier, T., Halter, R., Spanel, R. & Spanel-Borowski, K. Epidermal growth factor-induced hepatocellular carcinoma: gene expression profiles in precursor lesions, early stage and solitary tumours. Oncogene 24, 1809–1819 (2005).

    Article  CAS  PubMed  Google Scholar 

  47. Jiao, Y. et al. Exome sequencing identifies frequent inactivating mutations in BAP1, ARID1A and PBRM1 in intrahepatic cholangiocarcinomas. Nat. Genet. 45, 1470–1473 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Li, M. et al. Inactivating mutations of the chromatin remodeling gene ARID2 in hepatocellular carcinoma. Nat. Genet. 43, 828–829 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lee, Y.T. & Geer, D.A. Primary liver cancer: pattern of metastasis. J. Surg. Oncol. 36, 26–31 (1987).

    Article  CAS  PubMed  Google Scholar 

  50. Francies, H.E., Barthorpe, A., McLaren-Douglas, A., Barendt, W.J. & Garnett, M.J. Drug sensitivity assays of human cancer organoid cultures. In: Methods in Molecular Biology (Humana Press, 2016).

  51. Morris, E.J. et al. Discovery of a novel ERK inhibitor with activity in models of acquired resistance to BRAF and MEK inhibitors. Cancer Discov. 3, 742–750 (2013).

    Article  CAS  PubMed  Google Scholar 

  52. Iorio, F. et al. A Landscape of Pharmacogenomic Interactions in Cancer. Cell 166, 740–754 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Drexler, H.G. et al. p53 alterations in human leukemia-lymphoma cell lines: in vitroartifact or prerequisite for cell immortalization? Leukemia 14, 198–206 (2000).

    Article  CAS  PubMed  Google Scholar 

  54. Frisch, S.M., Schaller, M. & Cieply, B. Mechanisms that link the oncogenic epithelial-mesenchymal transition to suppression of anoikis. J. Cell Sci. 126, 21–29 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Gu, Q. et al. Genomic characterization of a large panel of patient-derived hepatocellular carcinoma xenograft tumor models for preclinical development. Oncotarget 6, 20160–20176 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Hidalgo, M. et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov. 4, 998–1013 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Trapnell, C., Pachter, L. & Salzberg, S.L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Liao, Y., Smyth, G.K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    Article  CAS  PubMed  Google Scholar 

  59. Love, M.I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. The UniProt Consortium. UniProt: the universal protein knowledgebase. Nucleic Acids Res. 45, D158–D169 (2017).

  62. Fang, H. & Gough, J. The 'dnet' approach promotes emerging research on cancer patient survival. Genome Med. 6, 64 (2014).

    PubMed  PubMed Central  Google Scholar 

  63. Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Koboldt, D.C. et al. VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics 25, 2283–2285 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6, 80–92 (2012).

    Article  CAS  Google Scholar 

  67. Sherry, S.T. et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 29, 308–311 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Forbes, S.A. et al. COSMIC: exploring the world's knowledge of somatic mutations in human cancer. Nucleic Acids Res. 43, D805–D811 (2015).

    Article  CAS  PubMed  Google Scholar 

  70. Sim, N.L. et al. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res. 40, W452–W457 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Galili, T. dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics 31, 3718–3720 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Colaprico, A. et al. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucleic Acids Res. 44, e71 (2016).

    Article  PubMed  CAS  Google Scholar 

  73. Vis, D.J. et al. Multilevel models improve precision and speed of IC50 estimates. Pharmacogenomics 17, 691–700 (2016).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

M.H. is a Wellcome Trust Sir Henry Dale Fellow and is jointly funded by the Wellcome Trust and the Royal Society (104151/Z/14/Z). L.B. is supported by an EMBO Postdoctoral Fellowship (EMBO ALTF 794-2014) and Marie-Curie Postdoctoral Fellowship (grant no. 656193_H2020-MSCA-IF-2014). G.M. was supported by a Marie Curie Initial Training Network (Marie Curie ITN WntsApp 608180) and a H2020 LSMF4LIFE grant (ECH2020-668350). This work was funded by an NC3Rs International prize, a Beit Prize, a Cambridge Cancer Center-pump priming award (CRUK-RG83267) and, partially, by a NC3Rs project grant (NC/R001162/1), all of them awarded to M.H. Work at the L.J.W.v.d.L lab was funded by the research program InnoSysTox (project number 114027003), by the Netherlands Organisation for Health Research and Development (ZonMw), and part of the research program financed by the Dutch Digestive Foundation (MLDS-Diagnostics project number D16-26). Work in the M.J.G. lab is funded by the Wellcome Trust (102696), Stand Up To Cancer (SU2C-AACRDT1213) and Cancer Research UK (C44943/A22536). We thank C. Pacini (Wellcome Trust–Cancer Research UK Gurdon Institute) for help with the clustering analysis of the HCC and CC TCGA cohorts and the samples used in this study. We also thank C. Olpe and N. Hircq (Wellcome Trust–Cancer Research UK Gurdon Institute) for help in the early phases of the project, C. Hindley (Wellcome Trust–Cancer Research UK Gurdon Institute) for editorial assistance, the Gurdon Institute facilities for help with imaging and animal care, S. Moss, K. Harnish (Wellcome Trust–Cancer Research UK Gurdon Institute), M. Paramor and J. Martinez (Wellcome Trust–Medical Research Council Stem Cell Institute) for assistance with sequencing analysis and A. Jah (Cambridge University Hospitals NHS Trust) and J. de Jonge (Erasmus Rotterdam Center) for facilitating the recruitment of patients. Finally, M.H. would like to thank B. Hogan (University of North Carolina—Chapel Hill) and M. Zernicka-Goetz (University of Cambridge) for helpful discussions and critical comments.

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Authors

Contributions

L.B. designed and performed experiments and interpreted results. G.M. performed experiments and interpreted results. R.A.-B. and O.S. performed experiments. L.M.G., C.R.B., G.E.A. and S.D. performed bioinformatic analyses. S.E.D. performed the histopathology diagnosis. M.M.A.V., M.P.G., R.L., J.N.M.I.J., S.J.W, R.K.P., N.G. and K.S.P. provided patient material and interpreted clinical data. K.S.P. performed the kidney-capsule transplants. H.E.F. and M.J.G. performed the drug screening, interpreted the results and wrote the drug screening section of the manuscript. M.H. conceived and designed the project, designed and performed experiments and interpreted results. M.H. and L.B. wrote the manuscript. All authors commented on the manuscript.

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Correspondence to Meritxell Huch.

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Supplementary information

Supplementary Figures & Table

Supplementary Figures 1–8 & Supplementary Table 1 (PDF 45208 kb)

Life Sciences Reporting Summary (PDF 170 kb)

Supplementary Dataset 1

RNAseq data analysis (XLSX 9351 kb)

Supplementary Dataset 2

Tumoroids GSEA data (XLSX 722 kb)

Supplementary Dataset 3

Tissues GSEA data (XLSX 625 kb)

Supplementary Dataset 4

WES analysis (XLSX 332 kb)

Supplementary Dataset 5

Drug screening (XLSX 80 kb)

Supplementary Dataset 6

List of antibodies, kits, and primers used (XLSX 46 kb)

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Broutier, L., Mastrogiovanni, G., Verstegen, M. et al. Human primary liver cancer–derived organoid cultures for disease modeling and drug screening. Nat Med 23, 1424–1435 (2017). https://doi.org/10.1038/nm.4438

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