Journal of Pharmacokinetics and Pharmacodynamics

, Volume 41, Issue 6, pp 675–691 | Cite as

FLT3 and CDK4/6 inhibitors: Signaling mechanisms and tumor burden in subcutaneous and orthotopic mouse models of acute myeloid leukemia

  • Yaping Zhang
  • Cheng-Pang Hsu
  • Jian-Feng Lu
  • Mita Kuchimanchi
  • Yu-Nien Sun
  • Ji Ma
  • Guifen Xu
  • Yilong Zhang
  • Yang Xu
  • Margaret Weidner
  • Justin Huard
  • David Z. D’Argenio
Original Paper


FLT3ITD subtype acute myeloid leukemia (AML) has a poor prognosis with currently available therapies. A number of small molecule inhibitors of FLT3 and/or CDK4/6 are currently under development. A more complete and quantitative understanding of the mechanisms of action of FLT3 and CDK4/6 inhibitors may better inform the development of current and future compounds that act on one or both of the molecular targets, and thus may lead to improved treatments for AML. In this study, we investigated in both subcutaneous and orthotopic AML mouse models, the mechanisms of action of three FLT3 and/or CDK4/6 inhibitors: AMG925 (Amgen), sorafenib (Bayer and Onyx), and quizartinib (Ambit Biosciences). A composite model was developed to integrate the plasma pharmacokinetics of these three compounds on their respective molecular targets, the coupling between the target pathways, as well as the resulting effects on tumor burden reduction in the subcutaneous xenograft model. A sequential modeling approach was used, wherein model structures and estimated parameters from upstream processes (e.g. PK, cellular signaling) were fixed for modeling subsequent downstream processes (cellular signaling, tumor burden). Pooled data analysis was employed for the plasma PK and cellular signaling modeling, while population modeling was applied to the tumor burden modeling. The resulting model allows the decomposition of the relative contributions of FLT3ITD and CDK4/6 inhibition on downstream signaling and tumor burden. In addition, the action of AMG925 on cellular signaling and tumor burden was further studied in an orthotopic tumor mouse model more closely representing the physiologically relevant environment for AML.


FLT3 inhibitors CDK4/6 inhibitors Acute myeloid leukemia STAT5 Rb Subcutaneous tumor Orthotopic tumor 



We gratefully acknowledge Kathy Keegan for her contribution to mouse tumor studies. We also acknowledge Ruta Phadnis and Tim Carlson for their contribution to pharmacokinetic studies. We appreciate the helpful comments provided by Jordan Fridman at Flexus Biosciences, Inc. This work was supported by Amgen Inc., as well as by Grant NIH/NIBIB P41-EB001978 (DZD).

Conflict of interest

Y. Zhang and D.Z. D’Argenio declare no conflict of interests. J.-F. Lu is an employee of Askgene Pharma, and the remaining authors are employees of Amgen Inc.


  1. 1.
    Gilliland DG, Griffin JD (2002) The roles of FLT3 in hematopoiesis and leukemia. Blood 100(5):1532–1542. doi: 10.1182/blood-2002-02-0492 PubMedCrossRefGoogle Scholar
  2. 2.
    Levis M, Small D (2003) FLT3: ITDoes matter in leukemia. Leukemia 17(9):1738–1752. doi: 10.1038/sj.leu.2403099 PubMedCrossRefGoogle Scholar
  3. 3.
    Nakao M, Yokota S, Iwai T, Kaneko H, Horiike S, Kashima K, Sonoda Y, Fujimoto T, Misawa S (1996) Internal tandem duplication of the flt3 gene found in acute myeloid leukemia. Leukemia 10(12):1911–1918PubMedGoogle Scholar
  4. 4.
    Vardiman JW, Thiele J, Arber DA, Brunning RD, Borowitz MJ, Porwit A, Harris NL, Le Beau MM, Hellstrom-Lindberg E, Tefferi A, Bloomfield CD (2009) The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood 114(5):937–951. doi: 10.1182/blood-2009-03-209262 PubMedCrossRefGoogle Scholar
  5. 5.
    Kiyoi H, Yanada M, Ozekia K (2005) Clinical significance of FLT3 in leukemia. Int J Hematol 82(2):85–92. doi: 10.1532/IJH97.05066 PubMedCrossRefGoogle Scholar
  6. 6.
    Levis M, Small D (2005) FLT3 tyrosine kinase inhibitors. Int J Hematol 82(2):100–107. doi: 10.1532/IJH97.05079 PubMedCrossRefGoogle Scholar
  7. 7.
    Hayakawa F, Towatari M, Kiyoi H, Tanimoto M, Kitamura T, Saito H, Naoe T (2000) Tandem-duplicated Flt3 constitutively activates STAT5 and MAP kinase and introduces autonomous cell growth in IL-3-dependent cell lines. Oncogene 19(5):624–631. doi: 10.1038/sj.onc.1203354 PubMedCrossRefGoogle Scholar
  8. 8.
    Yoshimoto G, Miyamoto T, Jabbarzadeh-Tabrizi S, Iino T, Rocnik JL, Kikushige Y, Mori Y, Shima T, Iwasaki H, Takenaka K, Nagafuji K, Mizuno S, Niiro H, Gilliland GD, Akashi K (2009) FLT3-ITD up-regulates MCL-1 to promote survival of stem cells in acute myeloid leukemia via FLT3-ITD-specific STAT5 activation. Blood 114(24):5034–5043. doi: 10.1182/blood-2008-12-196055 PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Kim KT, Baird K, Ahn JY, Meltzer P, Lilly M, Levis M, Small D (2005) Pim-1 is up-regulated by constitutively activated FLT3 and plays a role in FLT3-mediated cell survival. Blood 105(4):1759–1767. doi: 10.1182/blood-2004-05-2006 PubMedCrossRefGoogle Scholar
  10. 10.
    Dumon S, Santos SC, Debierre-Grockiego F, Gouilleux-Gruart V, Cocault L, Boucheron C, Mollat P, Gisselbrecht S, Gouilleux F (1999) IL-3 dependent regulation of Bcl-xL gene expression by STAT5 in a bone marrow derived cell line. Oncogene 18(29):4191–4199. doi: 10.1038/sj.onc.1202796 PubMedCrossRefGoogle Scholar
  11. 11.
    Weinberg RA (2007) The biology of cancer. Garland Sci, New YorkGoogle Scholar
  12. 12.
    Matsumura I, Kitamura T, Wakao H, Tanaka H, Hashimoto K, Albanese C, Downward J, Pestell RG, Kanakura Y (1999) Transcriptional regulation of the cyclin D1 promoter by STAT5: its involvement in cytokine-dependent growth of hematopoietic cells. The EMBO J 18(5):1367–1377. doi: 10.1093/emboj/18.5.1367 CrossRefGoogle Scholar
  13. 13.
    Wiernik PH (2010) FLT3 inhibitors for the treatment of acute myeloid leukemia. Clin Adv Hematol Oncol 8(6):429-436, 444Google Scholar
  14. 14.
    Grunwald MR, Levis MJ (2013) FLT3 inhibitors for acute myeloid leukemia: a review of their efficacy and mechanisms of resistance. Int J Hematol 97(6):683–694. doi: 10.1007/s12185-013-1334-8 PubMedCrossRefGoogle Scholar
  15. 15.
    Harbour JW, Luo RX, Dei Santi A, Postigo AA, Dean DC (1999) Cdk phosphorylation triggers sequential intramolecular interactions that progressively block Rb functions as cells move through G1. Cell 98(6):859–869PubMedCrossRefGoogle Scholar
  16. 16.
    Lundberg AS, Weinberg RA (1998) Functional inactivation of the retinoblastoma protein requires sequential modification by at least two distinct cyclin-cdk complexes. Mol Cell Biol 18(2):753–761PubMedCentralPubMedGoogle Scholar
  17. 17.
    Meyerson M, Harlow E (1994) Identification of G1 kinase activity for cdk6, a novel cyclin D partner. Mol Cell Biol 14(3):2077–2086PubMedCentralPubMedGoogle Scholar
  18. 18.
    Sherr CJ (1995) D-type cyclins. Trends Biochem Sci 20(5):187–190PubMedCrossRefGoogle Scholar
  19. 19.
    Hall M, Peters G (1996) Genetic alterations of cyclins, cyclin-dependent kinases, and Cdk inhibitors in human cancer. Adv Cancer Res 68:67–108PubMedCrossRefGoogle Scholar
  20. 20.
    Sheppard KE, McArthur GA (2013) The cell-cycle regulator CDK4: an emerging therapeutic target in melanoma. Clin Cancer Res 19(19):5320–5328. doi: 10.1158/1078-0432.CCR-13-0259 PubMedCrossRefGoogle Scholar
  21. 21.
    Wilhelm SM, Carter C, Tang L, Wilkie D, McNabola A, Rong H, Chen C, Zhang X, Vincent P, McHugh M, Cao Y, Shujath J, Gawlak S, Eveleigh D, Rowley B, Liu L, Adnane L, Lynch M, Auclair D, Taylor I, Gedrich R, Voznesensky A, Riedl B, Post LE, Bollag G, Trail PA (2004) BAY 43-9006 exhibits broad spectrum oral antitumor activity and targets the RAF/MEK/ERK pathway and receptor tyrosine kinases involved in tumor progression and angiogenesis. Cancer Res 64(19):7099–7109. doi: 10.1158/0008-5472.CAN-04-1443 PubMedCrossRefGoogle Scholar
  22. 22.
    Zarrinkar PP, Gunawardane RN, Cramer MD, Gardner MF, Brigham D, Belli B, Karaman MW, Pratz KW, Pallares G, Chao Q, Sprankle KG, Patel HK, Levis M, Armstrong RC, James J, Bhagwat SS (2009) AC220 is a uniquely potent and selective inhibitor of FLT3 for the treatment of acute myeloid leukemia (AML). Blood 114(14):2984–2992. doi: 10.1182/blood-2009-05-222034 PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Keegan K, Li C, Li Z, Ma J, Ragains M, Coberly S, Hollenback D, Eksterowicz J, Liang L, Weidner M, Huard JN, Wang X, Alba G, Orf J, Lo MC, Zhao S, Ngo R, Chen A, Liu L, Carlson T, Queva C, McGee LR, Medina JC, Kamb A, Wickramasinghe D, Dai K (2014) Preclinical evaluation of AMG 925, a FLT3/CDK4 dual kinase inhibitor for treating acute myeloid leukemia. Mol Cancer Ther. doi: 10.1158/1535-7163.MCT-13-0858 PubMedGoogle Scholar
  24. 24.
    Cox DM, Zhong F, Du M, Duchoslav E, Sakuma T, McDermott JC (2005) Multiple reaction monitoring as a method for identifying protein posttranslational modifications. J Biomol Tech 16(2):83–90PubMedCentralPubMedGoogle Scholar
  25. 25.
    D’Argenio DZ, Schumitzky A, Wang X (2009) ADAPT 5 user’s guide: pharmacokinetic/pharmacodynamic systems analysis software. Biomedical Simulations Resource, Los AngelesGoogle Scholar
  26. 26.
    Kay BP, Hsu CP, Lu JF, Sun YN, Bai S, Xin Y, D’Argenio DZ (2012) Intracellular-signaling tumor-regression modeling of the pro-apoptotic receptor agonists dulanermin and conatumumab. J Pharmacokinet Pharmacodyn 39(5):577–590. doi: 10.1007/s10928-012-9269-x PubMedCentralPubMedCrossRefGoogle Scholar
  27. 27.
    Harrold JM, Straubinger RM, Mager DE (2012) Combinatorial chemotherapeutic efficacy in non-Hodgkin lymphoma can be predicted by a signaling model of CD20 pharmacodynamics. Cancer Res 72(7):1632–1641. doi: 10.1158/0008-5472.CAN-11-2432 PubMedCentralPubMedCrossRefGoogle Scholar
  28. 28.
    Simeoni M, Magni P, Cammia C, De Nicolao G, Croci V, Pesenti E, Germani M, Poggesi I, Rocchetti M (2004) Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents. Cancer Res 64(3):1094–1101PubMedCrossRefGoogle Scholar
  29. 29.
    Garber K (2006) Realistic rodents? Debate grows over new mouse models of cancer. J Natl Cancer Inst 98(17):1176–1178. doi: 10.1093/jnci/djj381 PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Yaping Zhang
    • 1
  • Cheng-Pang Hsu
    • 2
  • Jian-Feng Lu
    • 3
  • Mita Kuchimanchi
    • 2
  • Yu-Nien Sun
    • 2
  • Ji Ma
    • 2
  • Guifen Xu
    • 2
  • Yilong Zhang
    • 2
  • Yang Xu
    • 2
  • Margaret Weidner
    • 4
  • Justin Huard
    • 4
  • David Z. D’Argenio
    • 1
  1. 1.Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.PKDMAmgenThousand OaksUSA
  3. 3.Askgene PharmaCamarilloUSA
  4. 4.Therapeutic Innovation UnitAmgenSeattleUSA

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