Modeling microRNA-Transcription Factor Networks in Cancer

Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 774)

Abstract

An increasing number of transcription factors (TFs) and microRNAs (miRNAs) is known to form feedback loops (FBLs) of interactions where a TF positively or negatively regulates the expression of a miRNA, and the miRNA suppresses the translation of the TF messenger RNA. FBLs are potential sources of instability in a gene regulatory network. Positive FBLs can give rise to switching behaviors while negative FBLs can generate periodic oscillations. This chapter presents documented examples of FBLs and their relevance to stem cell renewal and differentiation in gliomas. Feed-forward loops (FFLs) are only discussed briefly because they do not affect network stability unless they are members of cycles. A primer on qualitative network stability analysis is given and then used to demonstrate the network destabilizing role of FBLs. Steps in model formulation and computer simulations are illustrated using the miR-17-92/Myc/E2F network as an example. This example possesses both negative and positive FBLs.

Keywords

Mathematical modeling Feedback loops Feedforward loops miR-17-92 E2F Myc p53 Cancer zone Qualitative network 

Abbreviations

CZ

cancer zone

dTF

differentiation transcription factor module

FFL

feed-forward loop

FBL

feedback loop

PA

apoptosis factors

PC

cell cycle factors

qNET

qualitative network

sTF

stem cell transcription factor module

TF

transcription factor

References

  1. 1.
    Esquela-Kerscher A, Slack FJ (2006) Oncomirs—microRNAs with a role in cancer. Nat Rev Cancer 6:259–269PubMedCrossRefGoogle Scholar
  2. 2.
    Cho WC (2007) OncomiRs: the discovery and progress of microRNAs in cancers. Mol Cancer 6:60PubMedCentralPubMedCrossRefGoogle Scholar
  3. 3.
    Krutovskikh VA, Herceg Z (2010) Oncogenic microRNAs (OncomiRs) as a new class of cancer biomarkers. Bioessays 32:894–904PubMedCrossRefGoogle Scholar
  4. 4.
    Shalgi R, Brosh R, Oren M, Pilpel Y, Rotter V (2009) Coupling transcriptional and post-transcriptional miRNA regulation in the control of cell fate. Aging (Albany NY) 1:762–770Google Scholar
  5. 5.
    Tsang J, Zhu J, van Oudenaarden A (2007) MicroRNA-mediated feedback and feedforward loops are recurrent network motifs in mammals. Mol Cell 26:753–767PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Osella M, Bosia C, Corá D, Caselle M (2011) The role of incoherent microRNA-mediated feedforward loops in noise buffering. PLoS Comput Biol 7:e1001101PubMedCentralPubMedCrossRefGoogle Scholar
  7. 7.
    Herranz H, Cohen SM (2010) MicroRNAs and gene regulatory networks: managing the impact of noise in biological systems. Genes Dev 24:1339–1344PubMedCrossRefGoogle Scholar
  8. 8.
    El Baroudi M, Corà D, Bosia C, Osella M, Caselle M (2011) A curated database of miRNA mediated feed-forward loops involving MYC as master regulator. PLoS One 6:e14742PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Takano S, Yamashita T, Ohneda O (2010) Molecular therapeutic targets for glioma angiogenesis. J Oncol 2010:351908PubMedCentralPubMedGoogle Scholar
  10. 10.
    Alonso MM, Alemany R, Fueyo J, Gomez-Manzano C (2008) E2F1 in gliomas: a paradigm of oncogene addiction. Cancer Lett 263:157–163PubMedCrossRefGoogle Scholar
  11. 11.
    Koul D (2008) PTEN signaling pathways in glioblastoma. Cancer Biol Ther 7:1321–1325PubMedCrossRefGoogle Scholar
  12. 12.
    Le Bechec A, Portales-Casamar E, Vettter G, Moes M, Zindy P-J, Saumet A, Arenillas D, Theillet C, Wasserman W, Lecellier C-H, Friederich E (2011) MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in meta-regulation network model. BMC Bioinform 12:67CrossRefGoogle Scholar
  13. 13.
    Friard O, Re A, Taverna D, Bortoli MD, Cora’ D (2010) CircuitsDB: a database of mixed microRNA/transcription factor feed-forward regulatory circuits in human and mouse. BMC Bioinform 11:435CrossRefGoogle Scholar
  14. 14.
    Gong X, Sun J, Zhao Z (2011) Gene regulation in glioblastoma: a combinatorial analysis of microRNAs and transcription factors. Int J Comput Biol Drug Des 4:111–126PubMedCrossRefGoogle Scholar
  15. 15.
    Dong H, Luo L, Hong S, Siu H, Xiao Y, Jin L, Chen R, Xiong M (2010) Integrated analysis of mutations, miRNA and mRNA expression in glioblastoma. BMC Syst Biol 4:163PubMedCentralPubMedCrossRefGoogle Scholar
  16. 16.
    González-Gómez P, Sánchez P, Mira H (2011) MicroRNAs as regulators of neural stem cell-related pathways in glioblastoma multiforme. Mol Neurobiol 44:235–249PubMedCrossRefGoogle Scholar
  17. 17.
    Godlewski J, Newton HB, Chiocca EA, Lawler SE (2010) MicroRNAs and glioblastoma; the stem cell connection. Cell Death Differ 17:221–228PubMedCrossRefGoogle Scholar
  18. 18.
    Malzkorn B, Wolter M, Liesenberg F, Grzendowski M, Stühler K, Meyer HE, Reifenberger G (2010) Identification and functional characterization of microRNAs involved in the malignant progression of gliomas. Brain Pathol 20:539–550PubMedCrossRefGoogle Scholar
  19. 19.
    Ernst A, Campos B, Meier J, Devens F, Liesenberg F, Wolter M, Reifenberger G, Herold-Mende C, Lichter P, Radlwimmer B (2010) De-repression of CTGF via the miR-17-92 cluster upon differentiation of human glioblastoma spheroid cultures. Oncogene 29:3411–3422PubMedCrossRefGoogle Scholar
  20. 20.
    Lages E, Guttin A, El Atifi M, Ramus C, Ipas H, Dupré I, Rolland D, Salon C, Godfraind C, de Fraipont F, Dhobb M, Pelletier L, Wion D, Gay E, Berger F, Issartel J-P (2011) MicroRNA and target protein patterns reveal physiopathological features of glioma subtypes. PLoS One 6:e20600PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Aguda BD, Kim Y, Piper-Hunter MG, Friedman A, Marsh CB (2008) MicroRNA regulation of a cancer network: consequences of the feedback loops involving miR-17-92, E2F, and Myc. Proc Natl Acad Sci USA 105:19678–19683PubMedCrossRefGoogle Scholar
  22. 22.
    de la Iglesia N, Puram SV, Bonni A (2009) STAT3 regulation of glioblastoma pathogenesis. Curr Mol Med 9:580–590PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Liu Y, Li C, Lin J (2010) STAT3 as a therapeutic target for glioblastoma. Anticancer Agents Med Chem 10:512–519PubMedCrossRefGoogle Scholar
  24. 24.
    Brantley EC, Benveniste EN (2008) Signal transducer and activator of transcription-3: a molecular hub for signaling pathways in gliomas. Mol Cancer Res 6:675–684PubMedCrossRefGoogle Scholar
  25. 25.
    Brock M, Trenkmann M, Gay RE, Michel BA, Gay S, Fischler M, Ulrich S, Speich R, Huber LC (2009) Interleukin-6 modulates the expression of the bone morphogenic protein receptor type II through a novel STAT3-microRNA cluster 17/92 pathway. Circ Res 104:1184–1191PubMedCrossRefGoogle Scholar
  26. 26.
    Foshay KM, Gallicano GI (2009) MiR-17 family miRNAs are expressed during early mammalian development and regulate stem cell differentiation. Dev Biol 326:431–443PubMedCrossRefGoogle Scholar
  27. 27.
    Sachdeva M, Zhu S, Wu F, Wu H, Walia V, Kumar S, Elble R, Watabe K, Mo Y-Y (2009) p53 represses c-Myc through induction of the tumor suppressor miR-145. Proc Natl Acad Sci USA 106:3207–3212PubMedCrossRefGoogle Scholar
  28. 28.
    Aguda BD, Kim Y, Kim HS, Friedman A, Fine HA (2011) Qualitative network modeling of the Myc-p53 control system of cell proliferation and differentiation. Biophys J 101:2082–2091PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    Suh S-S, Yoo JY, Nuovo GJ, Jeon Y-J, Kim S, Lee TJ, Kim T, Bakàcs A, Alder H, Kaur B, Aqeilan RI, Pichiorri F, Croce CM (2012) MicroRNAs/TP53 feedback circuitry in glioblastoma multiforme. Proc Natl Acad Sci USA 109:5316–5321PubMedCrossRefGoogle Scholar
  30. 30.
    Gao F-B (2008) Posttranscriptional control of neuronal development by microRNA networks. Trends Neurosci 31:20–26PubMedCentralPubMedCrossRefGoogle Scholar
  31. 31.
    Silber J, Lim DA, Petritsch C, Persson AI, Maunakea AK, Yu M, Vandenberg SR, Ginzinger DG, James CD, Costello JF, Bergers G, Weiss WA, Alvarez-Buylla A, Hodgson JG (2008) MiR-124 and miR-137 inhibit proliferation of glioblastoma multiforme cells and induce differentiation of brain tumor stem cells. BMC Med 6:14PubMedCentralPubMedCrossRefGoogle Scholar
  32. 32.
    Zhang P, Lathia JD, Flavahan WA, Rich JN, Mattson MP (2009) Squelching glioblastoma stem cells by targeting REST for proteasomal degradation. Trends Neurosci 32:559–565PubMedCentralPubMedCrossRefGoogle Scholar
  33. 33.
    Qu Q, Shi Y (2009) Neural stem cells in the developing and adult brains. J Cell Physiol 221:5–9PubMedCentralPubMedCrossRefGoogle Scholar
  34. 34.
    Park H-J, Kim J-K, Jeon H-M, Oh S-Y, Kim S-H, Nam D-H, Kim H (2010) The neural stem cell fate determinant TLX promotes tumorigenesis and genesis of cells resembling glioma stem cells. Mol Cells 30:403–408PubMedCrossRefGoogle Scholar
  35. 35.
    Hatanpaa KJ, Burma S, Zhao D, Habib AA (2010) Epidermal growth factor receptor in glioma: signal transduction, neuropathology, imaging, and radioresistance. Neoplasia 12:675–684PubMedCentralPubMedGoogle Scholar
  36. 36.
    Papagiannakopoulos T, Friedmann-Morvinski D, Neveu P, Dugas JC, Gill RM, Huillard E, Liu C, Zong H, Rowitch DH, Barres BA, Verma IM, Kosik KS (2012) Pro-neural miR-128 is a glioma tumor suppressor that targets mitogenic kinases. Oncogene 31:1884–1895PubMedCrossRefGoogle Scholar
  37. 37.
    Moore LM, Zhang W (2010) Targeting miR-21 in glioma: a small RNA with big potential. Expert Opin Ther Targets 14:1247–1257PubMedCrossRefGoogle Scholar
  38. 38.
    Fujita S, Ito T, Mizutani T, Minoguchi S, Yamamichi N, Sakurai K, Iba H (2008) miR-21 Gene expression triggered by AP-1 is sustained through a double-negative feedback mechanism. J Mol Biol 378:492–504PubMedCrossRefGoogle Scholar
  39. 39.
    Brun M, Coles JE, Monckton EA, Glubrecht DD, Bisgrove D, Godbout R (2009) Nuclear factor I regulates brain fatty acid-binding protein and glial fibrillary acidic protein gene expression in malignant glioma cell lines. J Mol Biol 391:282–300PubMedCrossRefGoogle Scholar
  40. 40.
    Chang T-C, Wentzel EA, Kent OA, Ramachandran K, Mullendore M, Lee KH, Feldmann G, Yamakuchi M, Ferlito M, Lowenstein CJ, Arking DE, Beer MA, Maitra A, Mendell JT (2007) Transactivation of miR-34a by p53 broadly influences gene ­expression and promotes apoptosis. Mol Cell 26:745–752PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Li Y, Guessous F, Zhang Y, Dipierro C, Kefas B, Johnson E, Marcinkiewicz L, Jiang J, Yang Y, Schmittgen TD, Lopes B, Schiff D, Purow B, Abounader R (2009) MicroRNA-34a inhibits glioblastoma growth by targeting multiple oncogenes. Cancer Res 69:7569–7576PubMedCentralPubMedCrossRefGoogle Scholar
  42. 42.
    Yamakuchi M, Lowenstein CJ (2009) MiR-34, SIRT1 and p53: the feedback loop. Cell Cycle 8:712–715PubMedCrossRefGoogle Scholar
  43. 43.
    Zheng H, Ying H, Yan H, Kimmelman AC, Hiller DJ, Chen A-J, Perry SR, Tonon G, Chu GC, Ding Z, Stommel JM, Dunn KL, Wiedemeyer R, You MJ, Brennan C, Wang YA, Ligon KL, Wong WH, Chin L, DePinho RA (2008) p53 and Pten control neural and glioma stem/progenitor cell renewal and differentiation. Nature 455:1129–1133PubMedCrossRefGoogle Scholar
  44. 44.
    Guessous F, Zhang Y, Kofman A, Catania A, Li Y, Schiff D, Purow B, Abounader R (2010) microRNA-34a is tumor suppressive in brain tumors and glioma stem cells. Cell Cycle 9:1031–1036PubMedCentralPubMedCrossRefGoogle Scholar
  45. 45.
    Chang T-C, Yu D, Lee Y-S, Wentzel EA, Arking DE, West KM, Dang CV, Thomas-Tikhonenko A, Mendell JT (2008) Widespread microRNA repression by Myc contributes to tumorigenesis. Nat Genet 40:43–50PubMedCentralPubMedCrossRefGoogle Scholar
  46. 46.
    Sotillo E, Laver T, Mellert H, Schelter JM, Cleary MA, McMahon S, Thomas-Tikhonenko A (2011) Myc overexpression brings out unexpected antiapoptotic effects of miR-34a. Oncogene 30:2587–2594PubMedCentralPubMedCrossRefGoogle Scholar
  47. 47.
    Zheng H, Ying H, Yan H, Kimmelman AC, Hiller DJ, Chen A-J, Perry SR, Tonon G, Chu GC, Ding Z, Stommel JM, Dunn KL, Wiedemeyer R, You MJ, Brennan C, Wang YA, Ligon KL, Wong WH, Chin L, dePinho RA (2008) Pten and p53 converge on c-Myc to control differentiation, self-renewal, and transformation of normal and neoplastic stem cells in glioblastoma. Cold Spring Harb Symp Quant Biol 73:427–437PubMedCrossRefGoogle Scholar
  48. 48.
    Fang X, Yoon J-G, Li L, Yu W, Shao J, Hua D, Zheng S, Hood L, Goodlett DR, Foltz G, Lin B (2011) The SOX2 response program in glioblastoma multiforme: an integrated ChIP-seq, expression microarray, and microRNA analysis. BMC Genomics 12:11PubMedCentralPubMedCrossRefGoogle Scholar
  49. 49.
    Heng J-CD, Orlov YL, Ng H-H (2010) Transcription factors for the modulation of pluripotency and reprogramming. Cold Spring Harb Symp Quant Biol 75:237–244PubMedCrossRefGoogle Scholar
  50. 50.
    Annovazzi L, Mellai M, Caldera V, Valente G, Schiffer D (2011) SOX2 expression and amplification in gliomas and glioma cell lines. Cancer Genomics Proteomics 8:139–147PubMedGoogle Scholar
  51. 51.
    Lin T, Chao C, Saito S, Mazur SJ, Murphy ME, Appella E, Xu Y (2005) p53 induces differentiation of mouse embryonic stem cells by suppressing Nanog expression. Nat Cell Biol 7:165–171PubMedCrossRefGoogle Scholar
  52. 52.
    Kuijk EW, van Mil A, Brinkhof B, Penning LC, Colenbrander B, Roelen BAJ (2010) PTEN and TRP53 independently suppress Nanog expression in spermatogonial stem cells. Stem Cells Dev 19:979–988PubMedCrossRefGoogle Scholar
  53. 53.
    Brandner S (2010) Nanog, Gli, and p53: a new network of stemness in development and cancer. EMBO J 29:2475–2476PubMedCrossRefGoogle Scholar
  54. 54.
    Moon J-H, Kwon S, Jun EK, Kim A, Whang KY, Kim H, Oh S, Yoon BS, You S (2011) Nanog-induced dedifferentiation of p53-deficient mouse astrocytes into brain cancer stem-like cells. Biochem Biophys Res Commun 412:175–181PubMedGoogle Scholar
  55. 55.
    Gantmacher F (1959) Applications of the theory of matrices. Interscience, New YorkGoogle Scholar
  56. 56.
    Clarke BL (1980) Stability of complex reaction networks. Adv Chem Phys 43:1–213Google Scholar
  57. 57.
    Aguda BD, Tang Y (1999) The kinetic origins of the restriction point in the mammalian cell cycle. Cell Prolif 32:321–335PubMedCrossRefGoogle Scholar
  58. 58.
    Aguda BD, Algar CK (2003) A structural analysis of the qualitative networks regulating the cell cycle and apoptosis. Cell Cycle 2:538–544PubMedCrossRefGoogle Scholar
  59. 59.
    Aguda BD, Goryachev AB (2007) From pathways databases to network models of switching behavior. PLoS Comput Biol 3:1674–1678PubMedGoogle Scholar
  60. 60.
    Yao G, Lee TJ, Mori S, Nevins JR, You L (2008) A bistable Rb-E2F switch underlies the restriction point. Nat Cell Biol 10:476–482PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Neuro-Oncology Branch, Center for Cancer ResearchNational Cancer Institute, National Institutes of HealthBethesdaUSA

Personalised recommendations