Abstract
Aim:
Combined therapy of EGFR TKI and VEGFR TKI may produce a greater therapeutic benefit and overcome EGFR TKI-induced resistance. However, a previous study shows that a combination of EGFR TKI erlotinib (ER) with VEGFR TKI sunitinib (SU) did not improve the overall survival in patients with non-small-cell lung cancer (NSCLC). In this study we examined the anticancer effect of ER, SU and their combination in the treatment of A549 human NSCLC xenograft mice, and conducted PK/PD modeling and simulations to optimize the dose regimen.
Methods:
ER (20, 50 mg·kg−1·d−1) or SU (5, 10, 20 mg·kg−1·d−1) alone, or their combination were administered to BALB/c nude mice bearing A549 tumors for 22 days. The tumor size and body weight were recorded daily. The experimental data were used to develop PK/PD models describing the quantitative relationship between the plasma concentrations and tumor suppression in different dose regimens. The models were further evaluated and validated, and used to predict the efficacy of different combination regimens and to select the optimal regimen.
Results:
The in vivo anticancer efficacy of the combination groups was much stronger than that of either drug administered alone. A PK/PD model was developed with a combination index (φ) of 4.4, revealing a strong synergistic effect between ER and SU. The model simulation predicted the tumor growth in different dosage regimens, and showed that the dose of SU played a decisive role in the combination treatment, and suggested that a lower dose of ER (≤5 mg·kg−1·d−1) and adjusting the dose of SU might yield a better dosage regimen for clinical research.
Conclusion:
The experimental data and modeling confirm synergistic anticancer effect of ER and SU in the treatment of A549 xenograft mice. The optimal dosage regimen determined by the PK/PD modeling and simulation can be used in future preclinical study and provide a reference for clinical application.
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References
Lee CC, Shiao HY, Wang WC, Hsieh HP . Small-molecule EGFR tyrosine kinase inhibitors for the treatment of cancer. Expert Opin Investig Drugs 2014; 23: 1333–48.
Shepherd FA, Rodrigues Pereira J, Ciuleanu T, Tan EH, Hirsh V, Thongprasert S, et al. Erlotinib in previously treated non-small-cell lung cancer. N Engl J Med 2005; 353: 123–32.
Perez-Soler R, Chachoua A, Hammond LA, Rowinsky EK, Huberman M, Karp D, et al. Determinants of tumor response and survival with erlotinib in patients with non-small-cell lung cancer. J Clin Oncol 2004; 22: 3238–47.
Mendel DB, Laird AD, Xin X, Louie SG, Christensen JG, Li G, et al. In vivo antitumor activity of SU11248, a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor and platelet-derived growth factor receptors: determination of a pharmacokinetic/pharmacodynamic relationship. Clin Cancer Res 2003; 9: 327–37.
Abrams TJ, Lee LB, Murray LJ, Pryer NK, Cherrington JM . SU11248 inhibits KIT and platelet-derived growth factor receptor beta in preclinical models of human small cell lung cancer. Mol Cancer Ther 2003; 2: 471–8.
Ferrara N, Gerber HP, LeCouter J . The biology of VEGF and its receptors. Nat Med 2003; 9: 669–76.
Lin L, Bivona TG . Mechanisms of resistance to epidermal growth factor receptor inhibitors and novel therapeutic strategies to overcome resistance in NSCLC patients. Chemother Res Pract 2012; 2012: 817297.
Tortora G, Ciardiello F, Gasparini G . Combined targeting of EGFR-dependent and VEGF-dependent pathways: rationale, preclinical studies and clinical applications. Nat Clin Pract Oncol 2008; 5: 521–30.
Naumov GN, Nilsson MB, Cascone T, Briggs A, Straume O, Akslen LA, et al. Combined vascular endothelial growth factor receptor and epidermal growth factor receptor (EGFR) blockade inhibits tumor growth in xenograft models of EGFR inhibitor resistance. Clin Cancer Res 2009; 15: 3484–94.
Poindessous V, Ouaret D, El Ouadrani K, Battistella A, Megalophonos VF, Kamsu-Kom N, et al. EGFR- and VEGF(R)-targeted small molecules show synergistic activity in colorectal cancer models refractory to combinations of monoclonal antibodies. Clin Cancer Res 2011; 17: 6522–30.
Scagliotti GV, Krzakowski M, Szczesna A, Strausz J, Makhson A, Reck M, et al. Sunitinib plus erlotinib versus placebo plus erlotinib in patients with previously treated advanced non-small-cell lung cancer: a phase III trial. J Clin Oncol 2012; 30: 2070–8.
Suleiman AA, Nogova L, Fuhr U . Modeling NSCLC progression: recent advances and opportunities available. AAPS J 2013; 15: 542–50.
Tham LS, Wang L, Soo RA, Lee SC, Lee HS, Yong WP, et al. A pharmacodynamic model for the time course of tumor shrinkage by gemcitabine + carboplatin in non-small cell lung cancer patients. Clin Cancer Res 2008; 14: 4213–8.
Li M, Li H, Cheng X, Wang X, Li L, Zhou T, et al. Preclinical pharmacokinetic/pharmacodynamic models to predict schedule-dependent interaction between erlotinib and gemcitabine. Pharm Res 2013; 30: 1400–8.
Wang Y, Sung C, Dartois C, Ramchandani R, Booth BP, Rock E, et al. Elucidation of relationship between tumor size and survival in non-small-cell lung cancer patients can aid early decision making in clinical drug development. Clin Pharmacol Ther 2009; 86: 167–74.
Li M, Wu Q, Li H, Ning M, Chen Y, Li L, et al. Sensitive LCMS/ MS method to determine the concentrations of erlotinib and its active metabolite OSI420 in BALB/c nude mice plasma simultaneously and its application to a pharmacokinetic study. J Chin Pharm Sci 2012; 21: 296–303.
Li J, Li J, Wang S, Yuan Y, Su Q, Lu W, et al. Simultaneous determination of sunitinib and its active metabolites N-desethylsunitinib (SU12662) in nude mice plasma by liquid chromatography tandem mass spectrometry and its application to a pharmacokinetic study. J Chin Pharm Sci 2015; 24: 217–24.
Salphati L, Wong H, Belvin M, Bradford D, Edgar KA, Prior WW, et al. Pharmacokinetic-pharmacodynamic modeling of tumor growth inhibition and biomarker modulation by the novel phosphatidylinositol 3-kinase inhibitor GDC-0941. Drug Metab Dispos 2010; 38: 1436–42.
Simeoni M, Magni P, Cammia C, De Nicolao G, Croci V, Pesenti E, et al. Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents. Cancer Res 2004; 64: 1094–101.
Koch G, Walz A, Lahu G, Schropp J . Modeling of tumor growth and anticancer effects of combination therapy. J Pharmacokinet Pharmacodyn 2009; 36: 179–97.
van Erp NP, Gelderblom H, Guchelaar HJ . Clinical pharmacokinetics of tyrosine kinase inhibitors. Cancer Treat Rev 2009; 35: 692–706.
Blumenschein GR Jr, Ciuleanu T, Robert F, Groen HJ, Usari T, Ruiz-Garcia A, et al. Sunitinib plus erlotinib for the treatment of advanced/metastatic non-small-cell lung cancer: a lead-in study. J Thorac Oncol 2012; 7: 1406–16.
Faivre S, Delbaldo C, Vera K, Robert C, Lozahic S, Lassau N, et al. Safety, pharmacokinetic, and antitumor activity of SU11248, a novel oral multitarget tyrosine kinase inhibitor, in patients with cancer. J Clin Oncol 2006; 24: 25–35.
Haznedar JO, Patyna S, Bello CL, Peng GW, Speed W, Yu X, et al. Single- and multiple-dose disposition kinetics of sunitinib malate, a multitargeted receptor tyrosine kinase inhibitor: comparative plasma kinetics in non-clinical species. Cancer Chemother Pharmacol 2009; 64: 691–706.
Jusko WJ . Pharmacodynamics of chemotherapeutic effects: dose-time-response relationships for phase-nonspecific agents. J Pharm Sci 1971; 60: 892–5.
Savic RM, Jonker DM, Kerbusch T, Karlsson MO . Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies. J Pharmacokinet Pharmacodyn 2007; 34: 711–26.
Rocchetti M, Simeoni M, Pesenti E, De Nicolao G, Poggesi I . Predicting the active doses in humans from animal studies: a novel approach in oncology. Eur J Cancer 2007; 43: 1862–8.
Karlsson MO, Anehall T, Friberg LE, Henningsson A, Kloft C, Sandstrom M, et al. Pharmacokinetic/pharmacodynamic modelling in oncological drug development. Basic Clin Pharmacol Toxicol 2005; 96: 206–11.
Acknowledgements
This study was supported by the National Natural Science Foundation of China (Grant No 81473277).
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Supplementary information is available at the Acta Pharmacologica Sinica's website.
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Supplementary Figure S1
Goodness-of-fit plots of PK/PD model in BALB/c nude mice bearing A549 xenograft. (DOC 493 kb)
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Li, Jy., Ren, Yp., Yuan, Y. et al. Preclinical PK/PD model for combined administration of erlotinib and sunitinib in the treatment of A549 human NSCLC xenograft mice. Acta Pharmacol Sin 37, 930–940 (2016). https://doi.org/10.1038/aps.2016.55
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DOI: https://doi.org/10.1038/aps.2016.55
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