Cellular and Molecular Life Sciences

, Volume 69, Issue 12, pp 2041–2055 | Cite as

Identification of putative cancer genes through data integration and comparative genomics between plants and humans

  • Mauricio Quimbaya
  • Klaas Vandepoele
  • Eric Raspé
  • Michiel Matthijs
  • Stijn Dhondt
  • Gerrit T. S. Beemster
  • Geert Berx
  • Lieven De VeylderEmail author
Research Article


Coordination of cell division with growth and development is essential for the survival of organisms. Mistakes made during replication of genetic material can result in cell death, growth defects, or cancer. Because of the essential role of the molecular machinery that controls DNA replication and mitosis during development, its high degree of conservation among organisms is not surprising. Mammalian cell cycle genes have orthologues in plants, and vice versa. However, besides the many known and characterized proliferation genes, still undiscovered regulatory genes are expected to exist with conserved functions in plants and humans. Starting from genome-wide Arabidopsis thaliana microarray data, an integrative strategy based on coexpression, functional enrichment analysis, and cis-regulatory element annotation was combined with a comparative genomics approach between plants and humans to detect conserved cell cycle genes involved in DNA replication and/or DNA repair. With this systemic strategy, a set of 339 genes was identified as potentially conserved proliferation genes. Experimental analysis confirmed that 20 out of 40 selected genes had an impact on plant cell proliferation; likewise, an evolutionarily conserved role in cell division was corroborated for two human orthologues. Moreover, association analysis integrating Homo sapiens gene expression data with clinical information revealed that, for 45 genes, altered transcript levels and relapse risk clearly correlated. Our results illustrate how a systematic exploration of the A. thaliana genome can contribute to the experimental identification of new cell cycle regulators that might represent novel oncogenes or/and tumor suppressors.


Arabidopsis thaliana MCF7 Cell cycle Cancer genomics Comparative genomics 



Cyclin-dependent kinase


Endoreduplication index


Frozen Robust Multiarray Analysis


Gene ontology




Pearson correlation coefficient


Positional Weight Matrix


Quantitative polymerase chain reaction


Small interfering RNA



We thank all members of the cell cycle and oncology groups for fruitful discussions and suggestions, the Arabidopsis Biological Research Center for providing the T-DNA insertion lines, and Martine De Cock and Lorena López for help in preparing the manuscript. This work was supported by grants from the Interuniversity Poles of Attraction Programne (IUAP VI/33), initiated by the Belgian State, Science Policy Office, the Research Foundation-Flanders (grant no. G008306), Ghent University (“Geconcerteerde Onderzoeksacties” no.01G013B7), the Stichting tegen Kanker (no. 189-2008), the Association for International Cancer Research (Scotland), the EU-FP6 framework program BRECOSM LSHC-CT-2004-503224, and the EU-FP7 framework program TuMIC 2008-201662. M.Q. is indebted with the VIB international PhD program. K.V. acknowledges the support by Ghent University (Multidisciplinary Research Partnership “Bioinformatics: from nucleotides to networks”) and the Interuniversity Attraction Poles Programme (IUAP P6/25), initiated by the Belgian State, Science Policy Office (BioMaGNet). S.D. is indebted to the Agency for Innovation through Science and Technology for a predoctoral fellowship.

Supplementary material

18_2011_909_MOESM1_ESM.pdf (1.8 mb)
Supplementary material 1 (PDF 1852 kb)
18_2011_909_MOESM2_ESM.docx (26 kb)
Supplementary material 2 (DOCX 26 kb)
18_2011_909_MOESM3_ESM.xls (1.4 mb)
Supplementary material 3 (XLS 1,452 kb)


  1. 1.
    Morgan DO (1997) Cyclin-dependent kinases: engines, clocks, and microprocessors. Annu Rev Cell Dev Biol 13:261–291PubMedCrossRefGoogle Scholar
  2. 2.
    Inze D, De Veylder L (2006) Cell cycle regulation in plant development. Annu Rev Genet 40:77–105PubMedCrossRefGoogle Scholar
  3. 3.
    Srinivas PR, Verma M, Zhao Y, Srivastava S (2002) Proteomics for cancer biomarker discovery. Clin Chem 48:1160–1169PubMedGoogle Scholar
  4. 4.
    Pekarsky Y, Zanesi N, Palamarchuk A, Huebner K, Croce CM (2002) FHIT: from gene discovery to cancer treatment and prevention. Lancet Oncol 3:748–754PubMedCrossRefGoogle Scholar
  5. 5.
    Jones PA, Laird PW (1999) Cancer epigenetics comes of age. Nat Genet 21:163–167PubMedCrossRefGoogle Scholar
  6. 6.
    Marone M, Scambia G, Giannitelli C, Ferrandina G, Masciullo V, Bellacosa A, Benedetti-Panici P, Mancuso S (1998) Analysis of cyclin E and cdk2 in ovarian cancer: gene amplification and RNA overexpression. Int J Cancer 75:34–39PubMedCrossRefGoogle Scholar
  7. 7.
    Scheurle D, DeYoung MP, Binninger DM, Page H, Jahanzeb M, Narayanan R (2000) Cancer gene discovery using digital differential display. Cancer Res 60:4037–4043PubMedGoogle Scholar
  8. 8.
    Argani P, Rosty C, Reiter RE, Wilentz RE, Murugesan SR, Leach SD, Ryu B, Skinner HG, Goggins M, Jaffee EM, Yeo CJ, Cameron JL, Kern SE, Hruban RH (2001) Discovery of new markers of cancer through serial analysis of gene expression: prostate stem cell antigen is overexpressed in pancreatic adenocarcinoma. Cancer Res 61:4320–4324PubMedGoogle Scholar
  9. 9.
    Alizadeh AA, Ross DT, Perou CM, van de Rijn M (2001) Towards a novel classification of human malignancies based on gene expression patterns. J Pathol 195:41–52PubMedCrossRefGoogle Scholar
  10. 10.
    Korkola JE, DeVries S, Fridlyand J, Hwang ES, Estep ALH, Chen Y-Y, Chew KL, Dairkee SH, Jensen RM, Waldman FM (2003) Differentiation of lobular versus ductal breast carcinomas by expression microarray analysis. Cancer Res 63:7167–7175PubMedGoogle Scholar
  11. 11.
    Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, Barrette T, Pandey A, Chinnaiyan AM (2004) Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. Proc Natl Acad Sci USA 101:9309–9314PubMedCrossRefGoogle Scholar
  12. 12.
    Miller LD, Liu ET (2007) Expression genomics in breast cancer research: microarrays at the crossroads of biology and medicine. Breast Cancer Res 9:206PubMedCrossRefGoogle Scholar
  13. 13.
    Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, Clark L, Bayani N, Coppe J-P, Tong F, Speed T, Spellman PT, DeVries S, Lapuk A, Wang NJ, Kuo W-L, Stilwell JL, Pinkel D, Albertson DG, Waldman FM, McCormick F, Dickson RB, Johnson MD, Lippman M, Ethier S, Gazdar A, Gray JW (2006) A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 10:515–527PubMedCrossRefGoogle Scholar
  14. 14.
    Yeager M, Orr N, Hayes RB, Jacobs KB, Kraft P, Wacholder S, Minichiello MJ, Fearnhead P, Yu K, Chatterjee N, Wang Z, Welch R, Staats BJ, Calle EE, Feigelson HS, Thun MJ, Rodriguez C, Albanes D, Virtamo J, Weinstein S, Schumacher FR, Giovannucci E, Willett WC, Cancel-Tassin G, Cussenot O, Valeri A, Andriole GL, Gelmann EP, Tucker M, Gerhard DS, Fraumeni JF Jr, Hoover R, Hunter DJ, Chanock SJ, Thomas G (2007) Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nat Genet 39:645–649PubMedCrossRefGoogle Scholar
  15. 15.
    Easton DF, Pooley KA, Dunning AM, Pharoah PDP, Thompson D, Ballinger DG, Struewing JP, Morrison J, Field H, Luben R, Wareham N, Ahmed S, Healey CS, Bowman R, SEARCH Collaborators, Meyer KB, Haiman CA, Kolonel LK, Henderson BE, Le Marchand L, Brennan P, Sangrajrang S, Gaborieau V, Odefrey F, Shen C-Y, Wu P-E, Wang H-C, Eccles D, Evans DG, Peto J, Fletcher O, Johnson N, Seal S, Stratton MR, Rahman N, Chenevix-Trench G, Bojesen SE, Nordestgaard BG, Axelsson CK, Garcia-Closas M, Brinton L, Chanock S, Lissowska J, Peplonska B, Nevanlinna H, Fagerholm R, Eerola H, Kang D, Yoo K-Y, Noh D-Y, Ahn S-H, Hunter DJ, Hankinson SE, Cox DG, Hall P, Wedren S, Liu J, Low Y-L, Bogdanova N, Schürmann P, Dörk T, Tollenaar RAEM, Jacobi CE, Devilee P, Klijn JGM, Sigurdson AJ, Doody MM, Alexander BH, Zhang J, Cox A, Brock IW, MacPherson G, Reed MWR, Couch FJ, Goode EL, Olson JE, Meijers-Heijboer H, van den Ouweland A, Uitterlinden A, Rivadeneira F, Milne RL, Ribas G, Gonzalez-Neira A, Benitez J, Hopper JL, McCredie M, Southey M, Giles GG, Schroen C, Justenhoven C, Brauch H, Hamann U, Ko Y-D, Spurdle AB, Beesley J, Chen X, kConFab, AOCS Management Group, Mannermaa A, Kosma V-M, Kataja V, Hartikainen J, Day NE, Cox DR, Ponder BAJ (2007) Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447:1087–1093PubMedCrossRefGoogle Scholar
  16. 16.
    Amos CI, Wu X, Broderick P, Gorlov IP, Gu J, Eisen T, Dong Q, Zhang Q, Gu X, Vijayakrishnan J, Sullivan K, Matakidou A, Wang Y, Mills G, Doheny K, Tsai Y–Y, Chen WV, Shete S, Spitz MR, Houlston RS (2008) Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat Genet 40:616–622PubMedCrossRefGoogle Scholar
  17. 17.
    Jemal A, Siegel R, Xu J, Ward E (2010) Cancer statistics, 2010. CA Cancer J Clin 60:277–300PubMedCrossRefGoogle Scholar
  18. 18.
    Stuart JM, Segal E, Koller D, Kim SK (2003) A gene-coexpression network for global discovery of conserved genetic modules. Science 302:249–255PubMedCrossRefGoogle Scholar
  19. 19.
    Ala U, Piro RM, Grassi E, Damasco C, Silengo L, Oti M, Provero P, Di Cunto F (2008) Prediction of human disease genes by human–mouse conserved coexpression analysis. PLoS Comput Biol 4:e1000043PubMedCrossRefGoogle Scholar
  20. 20.
    McGary KL, Park TJ, Woods JO, Cha HJ, Wallingford JB, Marcotte EM (2010) Systematic discovery of nonobvious human disease models through orthologous phenotypes. Proc Natl Acad Sci USA 107:6544–6549PubMedCrossRefGoogle Scholar
  21. 21.
    Jones JDG, Dangl JL (2006) The plant immune system. Nature 444:323–329PubMedCrossRefGoogle Scholar
  22. 22.
    Thresher RJ, Vitaterna MH, Miyamoto Y, Kazantsev A, Hsu DS, Petit C, Selby CP, Dawut L, Smithies O, Takahashi JS, Sancar A (1998) Role of mouse cryptochrome blue-light photoreceptor in circadian photoresponses. Science 282:1490–1494PubMedCrossRefGoogle Scholar
  23. 23.
    Chan SW-L, Henderson IR, Jacobsen SE (2005) Gardening the genome: DNA methylation in Arabidopsis thaliana. Nat Rev Genet 6, 351–360 (Err. Nat Rev Genet 6, 590)Google Scholar
  24. 24.
    Matzke MA, Matzke AJM, Pruss GJ, Vance VB (2001) RNA-based silencing strategies in plants. Curr Opin Genet Dev 11:221–227PubMedCrossRefGoogle Scholar
  25. 25.
    Ma H (1994) GTP-binding proteins in plants: new members of an old family. Plant Mol Biol 26:1611–1636PubMedCrossRefGoogle Scholar
  26. 26.
    Jones AM, Chory J, Dangl JL, Estelle M, Jacobsen SE, Meyerowitz EM, Nordborg M, Weigel D (2008) The impact of Arabidopsis on human health: diversifying our portfolio. Cell 133:939–943PubMedCrossRefGoogle Scholar
  27. 27.
    Evan GI, Vousden KH (2001) Proliferation, cell cycle and apoptosis in cancer. Nature 411:342–348PubMedCrossRefGoogle Scholar
  28. 28.
    Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674PubMedCrossRefGoogle Scholar
  29. 29.
    Goodarzi H, Elemento O, Tavazoie S (2009) Revealing global regulatory perturbations across human cancers. Mol Cell 36:900–911PubMedCrossRefGoogle Scholar
  30. 30.
    Sherr CJ, McCormick F (2002) The RB and p53 pathways in cancer. Cancer Cell 2:103–112PubMedCrossRefGoogle Scholar
  31. 31.
    Nevins JR (2001) The Rb/E2F pathway and cancer. Hum Mol Genet 10:699–703PubMedCrossRefGoogle Scholar
  32. 32.
    Chen H-Z, Tsai S-Y, Leone G (2009) Emerging roles of E2Fs in cancer: an exit from cell cycle control. Nat Rev Cancer 9:785–797PubMedCrossRefGoogle Scholar
  33. 33.
    Jensen LJ, Jensen TS, de Lichtenberg U, Brunak S, Bork P (2006) Co-evolution of transcriptional and post-translational cell-cycle regulation. Nature 443:594–597PubMedGoogle Scholar
  34. 34.
    Craigon DJ, James N, Okyere J, Higgins J, Jotham J, May S (2004) NASCArrays: a repository for microarray data generated by NASC’s transcriptomics service. Nucleic Acids Res 32:D575–D577PubMedCrossRefGoogle Scholar
  35. 35.
    Vandepoele K, Quimbaya M, Casneuf T, De Veylder L, Van de Peer Y (2009) Unraveling transcriptional control in Arabidopsis using cis-regulatory elements and coexpression networks. Plant Physiol 150:535–546PubMedCrossRefGoogle Scholar
  36. 36.
    Poole RL (2007) The TAIR database. Methods Mol Biol 406:179–212PubMedCrossRefGoogle Scholar
  37. 37.
    Carbon S, Ireland A, Mungall CJ, Shu S, Marshall B, Lewis S, Hub AmiGO, Group Web Presence Working (2009) AmiGO: online access to ontology and annotation data. Bioinformatics 25:288–289PubMedCrossRefGoogle Scholar
  38. 38.
    Vandepoele K, Vlieghe K, Florquin K, Hennig L, Beemster GTS, Gruissem W, Van de Peer Y, Inzé D, De Veylder L (2005) Genome-wide identification of potential plant E2F target genes. Plant Physiol 139:316–328PubMedCrossRefGoogle Scholar
  39. 39.
    Thijs G, Marchal K, Lescot M, Rombauts S, De Moor B, Rouzé P, Moreau Y (2002) A Gibbs sampling method to detect overrepresented motifs in the upstream regions of coexpressed genes. J Comput Biol 9:447–464PubMedCrossRefGoogle Scholar
  40. 40.
    Chen F, Mackey AJ, Stoeckert CJ Jr, Roos DS (2006) OrthoMCL–DB: querying a comprehensive multi–species collection of ortholog groups. Nucleic Acids Res 34:D363–D368PubMedCrossRefGoogle Scholar
  41. 41.
    Edgar RC (2004) MUSCLE: a multiple sequence alignment with reduced time and space complexity. BMC Bioinformatics 5:113PubMedCrossRefGoogle Scholar
  42. 42.
    Van de Peer Y, De Wachter R (1994) TREECON for Windows: a software package for the construction and drawing of evolutionary trees for the Microsoft Windows environment. Comput Appl Biosci 10:569–570PubMedGoogle Scholar
  43. 43.
    McCall MN, Bolstad BM, Irizarry RA (2010) Frozen robust multiarray analysis (fRMA). Biostatistics 11:242–253PubMedCrossRefGoogle Scholar
  44. 44.
    De Veylder L, Beeckman T, Beemster GTS, de Almeida Engler J, Ormenese S, Maes S, Naudts M, Van Der Schueren E, Jacqmard A, Engler G, Inzé D (2002) Control of proliferation, endoreduplication and differentiation by the Arabidopsis E2Fa-DPa transcription factor. EMBO J 21:1360–1368PubMedCrossRefGoogle Scholar
  45. 45.
    Boudolf V, Vlieghe K, Beemster GTS, Magyar Z, Torres Acosta JA, Maes S, Van Der Schueren E, Inzé D, De Veylder L (2004) The plant-specific cyclin-dependent kinase CDKB1;1 and transcription factor E2Fa-DPa control the balance of mitotically dividing and endoreduplicating cells in Arabidopsis. Plant Cell 16:2683–2692PubMedCrossRefGoogle Scholar
  46. 46.
    Vlieghe K, Boudolf V, Beemster GTS, Maes S, Magyar Z, Atanassova A, de Almeida Engler J, De Groodt R, Inzé D, De Veylder L (2005) The DP–E2F–like DEL1 gene controls the endocycle in Arabidopsis thaliana. Curr Biol 15:59–63PubMedCrossRefGoogle Scholar
  47. 47.
    Beemster GTS, De Veylder L, Vercruysse S, West G, Rombaut D, Van Hummelen P, Galichet A, Gruissem W, Inzé D, Vuylsteke M (2005) Genome-wide analysis of gene expression profiles associated with cell cycle transitions in growing organs of Arabidopsis. Plant Physiol 138:734–743PubMedCrossRefGoogle Scholar
  48. 48.
    Tsukaya H, Beemster GTS (2006) Genetics, cell cycle and cell expansion in organogenesis in plants. J Plant Res 119:1–4PubMedCrossRefGoogle Scholar
  49. 49.
    Cory AH, Owen TC, Barltrop JA, Cory JG (1991) Use of an aqueous soluble tetrazolium/formazan assay for cell growth assays in culture. Cancer Commun 3:207–212PubMedGoogle Scholar
  50. 50.
    Cao AR, Rabinovich R, Xu M, Xu X, Jin VX, Farnham PJ (2011) Genome-wide analysis of transcription factor E2F1 mutant proteins reveals that N- and C-terminal protein interaction domains do not participate in targeting E2F1 to the human genome. J Biol Chem 286:11985–11996PubMedCrossRefGoogle Scholar
  51. 51.
    Puente XS, Velasco G, Gutierrez-Fernandez A, Bertranpetit J, King MC, Lopez-Otin C (2006) Comparative analysis of cancer genes in the human and chimpanzee genomes. BMC Genomics 7:15PubMedCrossRefGoogle Scholar
  52. 52.
    Sjöblom T, Jones S, Wood LD, Parsons DW, Lin J, Barber TD, Mandelker D, Leary RJ, Ptak J, Silliman N, Szabo S, Buckhaults P, Farrell C, Meeh P, Markowitz SD, Willis J, Dawson D, Willson JKV, Gazdar AF, Hartigan J, Wu L, Liu C, Parmigiani G, Park BH, Bachman KE, Papadopoulos N, Vogelstein B, Kinzler KW, Velculescu VE (2006) The consensus coding sequences of human breast and colorectal cancers. Science 314:268–274PubMedCrossRefGoogle Scholar
  53. 53.
    Chagnon P, Michaud J, Mitchell G, Mercier J, Marion J-F, Drouin E, Rasquin-Weber A, Hudson TJ, Richter A (2002) A missense mutation (R565 W) in Cirhin (FLJ14728) in North American Indian childhood cirrhosis. Am J Hum Genet 71:1443–1449PubMedCrossRefGoogle Scholar
  54. 54.
    Yu B, Mitchell GA, Richter A (2009) Cirhin up-regulates a canonical NF-κB element through strong interaction with Cirip/HIVEP1. Exp Cell Res 315:3086–3098PubMedCrossRefGoogle Scholar
  55. 55.
    Pikarsky E, Porat RM, Stein I, Abramovitch R, Amit S, Kasem S, Gutkovich-Pyest E, Urieli-Shoval S, Galun E, Ben-Neriah Y (2004) NF-KappaB functions as a tumour promoter in inflammation–associated cancer. Nature 431:461–466PubMedCrossRefGoogle Scholar
  56. 56.
    Huber MA, Azoitei N, Baumann B, Grünert S, Sommer A, Pehamberger H, Kraut N, Beug H, Wirth T (2004) NF-κB is essential for epithelial–mesenchymal transition and metastasis in a model of breast cancer progression. J Clin Invest 114:569–581PubMedGoogle Scholar
  57. 57.
    Welburn JPI, Grishchuk EL, Backer CB, Wilson-Kubalek EM, Yates JR III, Cheeseman IM (2009) The human kinetochore Ska1 complex facilitates microtubule depolymerization-coupled motility. Dev Cell 16:374–385PubMedCrossRefGoogle Scholar
  58. 58.
    Reidt W, Wurz R, Wanieck K, Chu HH, Puchta H (2006) A homologue of the breast cancer–associated gene BARD1 is involved in DNA repair in plants. EMBO J 25:4326–4337PubMedCrossRefGoogle Scholar
  59. 59.
    Takahashi N, Lammens T, Boudolf V, Maes S, Yoshizumi T, De Jaeger G, Witters E, Inzé D, De Veylder L (2008) The DNA replication checkpoint aids survival of plants deficient in the novel replisome factor ETG1. EMBO J 27:1840–1851PubMedCrossRefGoogle Scholar
  60. 60.
    Takahashi N, Quimbaya M, Schubert V, Lammens T, Vandepoele K, Schubert I, Matsui M, Inzé D, Berx G, De Veylder L (2010) The MCM-binding protein ETG1 aids sister chromatid cohesion required for postreplicative homologous recombination repair. PLoS Genet 6:e1000817PubMedCrossRefGoogle Scholar
  61. 61.
    Nishiyama A, Frappier L, Méchali M (2011) MCM–BP regulates unloading of the MCM2–7 helicase in late S phase. Genes Dev 25:165–175PubMedCrossRefGoogle Scholar
  62. 62.
    Wu G-j, Sinclair C, Hinson S, Ingle JN, Roche PC, Couch FJ (2001) Structural analysis of the 17q22–23 amplicon identifies several independent targets of amplification in breast cancer cell lines and tumors. Cancer Res 61:4951–4955PubMedGoogle Scholar
  63. 63.
    Lai M-D, Xu J (2007) Ribosomal proteins and colorectal cancer. Curr Genomics 8:43–49PubMedCrossRefGoogle Scholar
  64. 64.
    Macias E, Jin A, Deisenroth C, Bhat K, Mao H, Lindström MS, Zhang Y (2010) An ARF-independent c-MYC-activated tumor suppression pathway mediated by ribosomal protein-Mdm2 Interaction. Cancer Cell 18:231–243PubMedCrossRefGoogle Scholar
  65. 65.
    Leontieva OV, Ionov Y (2009) RNA-binding motif protein 35A is a novel tumor suppressor for colorectal cancer. Cell Cycle 8:490–497PubMedCrossRefGoogle Scholar
  66. 66.
    Warner JR, McIntosh KB (2009) How common are extraribosomal functions of ribosomal proteins? Mol Cell 34:3–11PubMedCrossRefGoogle Scholar
  67. 67.
    Welch PM, Gabal M, Betts DM, Whelan NC, Studer ME (2000) In vitro analysis of antiangiogenic activity of fungi isolated from clinical cases of equine keratomycosis. Vet Ophthalmol 3:145–151PubMedCrossRefGoogle Scholar
  68. 68.
    White DE, Kurpios NA, Zuo D, Hassell JA, Blaess S, Mueller U, Muller WJ (2004) Targeted disruption of β1-integrin in a transgenic mouse model of human breast cancer reveals an essential role in mammary tumor induction. Cancer Cell 6:159–170PubMedCrossRefGoogle Scholar
  69. 69.
    Pearson T, Greiner DL, Shultz LD (2008) Humanized SCID mouse models for biomedical research. Curr Top Microbiol Immunol 324:25–51PubMedCrossRefGoogle Scholar
  70. 70.
    Vucur M, Roderburg C, Bettermann K, Tacke F, Heikenwalder M, Trautwein C, Luedde T (2010) Mouse models of hepatocarcinogenesis: What can we learn for the prevention of human hepatocellular carcinoma? Oncotarget 1:373–378PubMedGoogle Scholar
  71. 71.
    Hartwell LH (1992) Role of yeast in cancer research. Cancer 69:2615–2621PubMedCrossRefGoogle Scholar
  72. 72.
    Rosengard AM, Krutzsch HC, Shearn A, Biggs JR, Barker E, Margulies IMK, King CR, Liotta LA, Steeg PS (1989) Reduced Nm23/Awd protein in tumour metastasis and aberrant Drosophila development. Nature 342:177–180PubMedCrossRefGoogle Scholar
  73. 73.
    Moberg KH, Bell DW, Wahrer DCR, Haber DA, Hariharan IK (2001) Archipelago regulates Cyclin E levels in Drosophila and is mutated in human cancer cell lines. Nature 413:311–316PubMedCrossRefGoogle Scholar
  74. 74.
    Caussinus E, Gonzalez C (2005) Induction of tumor growth by altered stem-cell asymmetric division in Drosophila melanogaster. Nat Genet 37:1125–1129PubMedCrossRefGoogle Scholar

Copyright information

© Springer Basel AG 2012

Authors and Affiliations

  • Mauricio Quimbaya
    • 1
    • 2
    • 3
    • 4
  • Klaas Vandepoele
    • 1
    • 2
  • Eric Raspé
    • 3
    • 4
  • Michiel Matthijs
    • 1
    • 2
  • Stijn Dhondt
    • 1
    • 2
  • Gerrit T. S. Beemster
    • 1
    • 2
    • 5
  • Geert Berx
    • 3
    • 4
  • Lieven De Veylder
    • 1
    • 2
    Email author
  1. 1.Department of Plant Systems BiologyVIBGentBelgium
  2. 2.Department of Plant Biotechnology and BioinformaticsGhent UniversityGentBelgium
  3. 3.Molecular and Cellular Oncology Unit, Department for Molecular Biomedical ResearchVIBGentBelgium
  4. 4.Department of Biomedical Molecular BiologyGhent UniversityGentBelgium
  5. 5.Department of BiologyUniversity of AntwerpAntwerpenBelgium

Personalised recommendations