, Volume 16, Issue 6, pp 619–626 | Cite as

Nonlinear regulation of commitment to apoptosis by simultaneous inhibition of Bcl-2 and XIAP in leukemia and lymphoma cells

  • Joanna SkommerEmail author
  • Somkanya C. Das
  • Arjun Nair
  • Thomas Brittain
  • Subhadip RaychaudhuriEmail author
Original Paper


Apoptosis is a complex pathway regulated by the concerted action of multiple pro- and anti-apoptotic molecules. The intrinsic (mitochondrial) pathway of apoptosis is governed up-stream of mitochondria, by the family of Bcl-2 proteins, and down-stream of mitochondria, by low-probability events, such as apoptosome formation, and by feedback circuits involving caspases and inhibitor of apoptosis proteins (IAPs), such as XIAP. All these regulatory mechanisms ensure that cells only commit to death once a threshold of damage has been reached and the anti-apoptotic reserve of the cell is overcome. As cancer cells are invariably exposed to strong intracellular and extracellular stress stimuli, they are particularly reliant on the expression of anti-apoptotic proteins. Hence, many cancer cells undergo apoptosis when exposed to agents that inhibit anti-apoptotic Bcl-2 molecules, such as BH3 mimetics, while normal cells remain relatively insensitive to single agent treatments with the same class of molecules. Targeting different proteins within the apoptotic network with combinatorial treatment approaches often achieves even greater specificity. This led us to investigate the sensitivity of leukemia and lymphoma cells to a pro-apoptotic action of a BH3 mimetic combined with a small molecule inhibitor of XIAP. Using the computational probabilistic model of the apoptotic pathway, verified by experimental results from human leukemia and lymphoma cell lines, we show that inhibition of XIAP has a non-linear effect on sensitization towards apoptosis induced by the BH3 mimetic HA14-1. This study justifies further ex vivo and animal studies on the potential of the treatment of leukemia and lymphoma with a combination of BH3 mimetics and XIAP inhibitors.


Cancer BH3 mimetic HA14-1 XIAP inhibition Embelin Leukemia Lymphoma Computational modeling Monte Carlo simulation Systems biology of apoptotic network Probabilistic modeling 



We are grateful to Prof. R. Dunbar (SBS, University of Auckland) for providing U937 and peripheral blood mononuclear cells, Prof B. Baguley (UoA) for providing Raji CEM and HL-60 cells, Dr J. Taylor (SBS, UoA) for THP-1α cells, and Dr D. Wlodkowic (Department of Chemistry, UoA) for providing PhiPhiLux-G1D1 reagent.

Supplementary material

10495_2011_593_MOESM1_ESM.doc (60 kb)
Supplementary material 1 (DOC 60 kb)


  1. 1.
    Chonghaile TN, Letai A (2008) Mimicking the BH3 domain to kill cancer cells. Oncogene 27(Suppl 1):S149–S157PubMedCrossRefGoogle Scholar
  2. 2.
    Labi V, Grespi F, Baumgartner F, Villunger A (2008) Targeting the Bcl-2-regulated apoptosis pathway by BH3 mimetics: a breakthrough in anticancer therapy? Cell Death Differ 15:977–987PubMedCrossRefGoogle Scholar
  3. 3.
    Skommer J, Wlodkowic D, Deptala A (2007) Larger than life: mitochondria and the Bcl-2 family. Leuk Res 31:277–286PubMedCrossRefGoogle Scholar
  4. 4.
    Du C, Fang M, Li Y, Li L, Wang X (2000) Smac, a mitochondrial protein that promotes cytochrome c-dependent caspase activation by eliminating IAP inhibition. Cell 102:33–42PubMedCrossRefGoogle Scholar
  5. 5.
    Kohl TM, Hellinger C, Ahmed F, Buske C, Hiddemann W, Bohlander SK, Spiekermann K (2007) BH3 mimetic ABT-737 neutralizes resistance to FLT3 inhibitor treatment mediated by FLT3-independent expression of BCL2 in primary AML blasts. Leukemia 21:1763–1772PubMedCrossRefGoogle Scholar
  6. 6.
    High LM, Szymanska B, Wilczynska-Kalak U, Barber N, O’Brien R, Khaw SL, Vikstrom IB, Roberts AW, Lock RB (2010) The Bcl-2 homology domain 3 mimetic ABT-737 targets the apoptotic machinery in acute lymphoblastic leukemia resulting in synergistic in vitro and in vivo interactions with established drugs. Mol Pharmacol 77:483–494PubMedCrossRefGoogle Scholar
  7. 7.
    Lehár J, Krueger AS, Avery W, Heilbut AM, Johansen LM, Price ER et al (2009) Synergistic drug combinations tend to improve therapeutically relevant selectivity. Nat Biotechnol 27:659–666PubMedCrossRefGoogle Scholar
  8. 8.
    Nikolovska-Coleska Z, Xu L, Hu Z, Tomita Y, Li P, Roller PP et al (2004) Discovery of embelin as a cell-permeable, small-molecular weight inhibitor of XIAP through structure-based computational screening of a traditional herbal medicine three-dimensional structure database. J Med Chem 47:2430–2440PubMedCrossRefGoogle Scholar
  9. 9.
    Skommer J, Brittain T, Raychaudhuri S (2010) Bcl-2 inhibits apoptosis by increasing the time-to-death and intrinsic cell-to-cell variations in the mitochondrial pathway of cell death. Apoptosis 15:1223–1233PubMedCrossRefGoogle Scholar
  10. 10.
    Raychaudhuri S, Willgohs E, Nguyen TN, Khan EM, Goldkorn T (2008) Monte Carlo simulation of cell death signaling predicts large cell-to-cell stochastic fluctuations through the type 2 pathway of apoptosis. Biophys J 95(8):3559–3562PubMedCrossRefGoogle Scholar
  11. 11.
    Goldstein JC, Waterhouse NJ, Juin P, Evan GI, Green DR (2000) The coordinate release of cytochrome c during apoptosis is rapid, complete and kinetically invariant. Nat Cell Biol 2:156–162PubMedCrossRefGoogle Scholar
  12. 12.
    Albeck JG, Burke JM, Spencer SL, Lauffenburger DA, Sorger PK (2008) Modeling a snap-action, variable-delay switch controlling extrinsic cell death. PLoS Biol 6:2831–2852PubMedCrossRefGoogle Scholar
  13. 13.
    Rehm M, Huber HJ, Dussmann H, Prehn JH (2006) Systems analysis of effector caspase activation and its control by X-linked inhibitor of apoptosis protein. EMBO J 25:4338–4349PubMedCrossRefGoogle Scholar
  14. 14.
    Legewie S, Blüthgen N, Herzel H (2006) Mathematical modeling identifies inhibitors of apoptosis as mediators of positive feedback and bistability. PLoS Comput Biol 2:e120PubMedCrossRefGoogle Scholar
  15. 15.
    Tamm I, Kornblau SM, Segall H, Krajewski S, Welsh K, Kitada S, Scudiero DA, Tudor G, Qui YH, Monks A, Andreeff M, Reed JC (2000) Expression and prognostic significance of IAP-family genes in human cancers and myeloid leukemias. Clin Cancer Res 6(5):1796–1803PubMedGoogle Scholar
  16. 16.
    Carter BZ, Milella M, Tsao T, McQueen T, Schober WD, Hu W, Dean NM, Steelman L, McCubrey JA, Andreeff M (2003) Regulation and targeting of antiapoptotic XIAP in acute myeloid leukemia. Leukemia 17(11):2081–2089PubMedCrossRefGoogle Scholar
  17. 17.
    Dressler V, Müller G, Sühnel J (1999) CombiTool—a new computer program for analyzing combination experiments with biologically active agents. Comput Biomed Res 32:145–160PubMedCrossRefGoogle Scholar
  18. 18.
    Jun YW, Sheikholeslami S, Hostetter DR, Tajon C, Craik CS, Alivisatos AP (2009) Continuous imaging of Plasmon rules in live cells reveals early-stage caspase-3 activation at the single-molecule level. Proc Natl Acad Sci USA 106:17735–17740PubMedCrossRefGoogle Scholar
  19. 19.
    Raychaudhuri S (2010) Minimal model of a signaling network elucidates cell-to-cell stochastic variability in apoptosis. PLoS One 5:e11930PubMedCrossRefGoogle Scholar
  20. 20.
    Swierniak A, Kimmel M, Smieja J (2009) Mathematical modeling as a tool for planning anticancer therapy. Eur J Pharmacol 625(1–3):108–121PubMedCrossRefGoogle Scholar
  21. 21.
    Marin-Sanguino A, Gupta SK, Voit EO, Vera J (2011) Biochemical pathway modeling tools for drug target detection in cancer and other complex diseases. Methods Enzymol 487:319–369PubMedCrossRefGoogle Scholar
  22. 22.
    Liso A, Castiglione F, Cappuccio A, Stracci F, Schlenk RF, Amadori S, Thiede C, Schnittger S, Valk PJ, Döhner K, Martelli MF, Schaich M, Krauter J, Ganser A, Martelli MP, Bolli N, Löwenberg B, Haferlach T, Ehninger G, Mandelli F, Döhner H, Michor F, Falini B (2008) A one-mutation mathematical model can explain the age incidence of acute myeloid leukemia with mutated nucleophosmin (NPM1). Haematologica 93(8):1219–1226PubMedCrossRefGoogle Scholar
  23. 23.
    Attolini CS, Cheng YK, Beroukhim R, Getz G, Abdel-Wahab O, Levine RL, Mellinghoff IK, Michor F (2010) A mathematical framework to determine the temporal sequence of somatic genetic events in cancer. Proc Natl Acad Sci USA 107(41):17604–17609PubMedCrossRefGoogle Scholar
  24. 24.
    Foo J, Drummond MW, Clarkson B, Holyoake T, Michor F (2009) Eradication of chronic myeloid leukemia stem cells: a novel mathematical model predicts no therapeutic benefit of adding G-CSF to imatinib. PLoS Comput Biol 5(9):e1000503PubMedCrossRefGoogle Scholar
  25. 25.
    Kronik N, Kogan Y, Elishmereni M, Halevi-Tobias K, Vuk-Pavlović S, Agur Z (2010) Predicting outcomes of prostate cancer immunotherapy by personalized mathematical models. PLoS One 5(12):e15482PubMedCrossRefGoogle Scholar
  26. 26.
    Wang JL, Liu D, Zhang ZJ, Shan S, Han X, Srinivasula SM, Croce CM, Alnemri ES, Huang Z (2000) Structure-based discovery of an organic compound that binds Bcl-2 protein and induces apoptosis of tumor cells. Proc Natl Acad Sci USA 97(13):7124–7129PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.School of Biological SciencesUniversity of AucklandAucklandNew Zealand
  2. 2.Department of Biomedical EngineeringUniversity of CaliforniaDavisUSA

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