A pharmacokinetic-pharmacodynamic model for the MET tyrosine kinase inhibitor, savolitinib, to explore target inhibition requirements for anti-tumour activity.
MET receptor TK inhibitor
mouse tumour models
pharmacokinetic-pharmacodynamic model
savolitinib
target inhibition
Journal
British journal of pharmacology
ISSN: 1476-5381
Titre abrégé: Br J Pharmacol
Pays: England
ID NLM: 7502536
Informations de publication
Date de publication:
02 2021
02 2021
Historique:
received:
24
02
2020
revised:
05
10
2020
accepted:
20
10
2020
pubmed:
31
10
2020
medline:
22
6
2021
entrez:
30
10
2020
Statut:
ppublish
Résumé
Savolitinib (AZD6094, HMPL-504, volitinib) is an oral, potent, and highly MET receptor TK inhibitor. This series of studies aimed to develop a pharmacokinetic-pharmacodynamic (PK/PD) model to link inhibition of MET phosphorylation (pMET) by savolitinib with anti-tumour activity. Cell line-derived xenograft (CDX) experiments using human lung cancer (EBC-1) and gastric cancer (MKN-45) cells were conducted in athymic nude mice using a variety of doses and schedules of savolitinib. Tumour pMET changes and growth inhibition were calculated after 28 days. Population PK/PD techniques were used to construct a PK/PD model for savolitinib. Savolitinib showed dose- and dose frequency-dependent anti-tumour activity in the CDX models, with more frequent, lower dosing schedules (e.g., twice daily) being more effective than intermittent, higher dosing schedules (e.g., 4 days on/3 days off or 2 days on/5 days off). There was a clear exposure-response relationship, with maximal suppression of pMET of >90%. Data from additional CDX and patient-derived xenograft (PDX) models overlapped, allowing calculation of a single EC High and persistent levels of MET inhibition by savolitinib were needed for optimal monotherapy anti-tumour activity in preclinical models. The modelling framework developed here can be used to translate tumour growth inhibition from the mouse to human and thus guide choice of clinical dose and schedule.
Sections du résumé
BACKGROUND AND PURPOSE
Savolitinib (AZD6094, HMPL-504, volitinib) is an oral, potent, and highly MET receptor TK inhibitor. This series of studies aimed to develop a pharmacokinetic-pharmacodynamic (PK/PD) model to link inhibition of MET phosphorylation (pMET) by savolitinib with anti-tumour activity.
EXPERIMENTAL APPROACH
Cell line-derived xenograft (CDX) experiments using human lung cancer (EBC-1) and gastric cancer (MKN-45) cells were conducted in athymic nude mice using a variety of doses and schedules of savolitinib. Tumour pMET changes and growth inhibition were calculated after 28 days. Population PK/PD techniques were used to construct a PK/PD model for savolitinib.
KEY RESULTS
Savolitinib showed dose- and dose frequency-dependent anti-tumour activity in the CDX models, with more frequent, lower dosing schedules (e.g., twice daily) being more effective than intermittent, higher dosing schedules (e.g., 4 days on/3 days off or 2 days on/5 days off). There was a clear exposure-response relationship, with maximal suppression of pMET of >90%. Data from additional CDX and patient-derived xenograft (PDX) models overlapped, allowing calculation of a single EC
CONCLUSION AND IMPLICATIONS
High and persistent levels of MET inhibition by savolitinib were needed for optimal monotherapy anti-tumour activity in preclinical models. The modelling framework developed here can be used to translate tumour growth inhibition from the mouse to human and thus guide choice of clinical dose and schedule.
Substances chimiques
Antineoplastic Agents
0
Protein Kinase Inhibitors
0
Pyrazines
0
Triazines
0
1-(1-(imidazo(1,2-a)pyridin-6-yl)ethyl)-6-(1-methyl-1H-pyrazol-4-yl)-1H-(1,2,3)triazolo(4,5-b)pyrazine
2A2DA6857R
Proto-Oncogene Proteins c-met
EC 2.7.10.1
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
600-613Subventions
Organisme : AstraZeneca
Informations de copyright
© 2020 The British Pharmacological Society.
Références
Ahn, M.-J., Cantarini, M., Frewer, P., Hawkins, G., Peters, J. A., Howarth, P., … Oxnard, G. (2019). SAVANNAH: Phase II trial of osimertinib plus savolitinib in EGFR-mutant, MET-driven advanced NSCLC, following prior osimertinib (Poster P1.01-134). Paper presented at the IASLC 2019 World Conference on Lung Cancer (WCLC), Barcelona, Spain, 7-10 September 2019.
Albiges, L., Guegan, J., Le Formal, A., Verkarre, V., Rioux-Leclercq, N., Sibony, M., … Escudier, B. (2014). MET is a potential target across all papillary renal cell carcinomas: Result from a large molecular study of pRCC with CGH array and matching gene expression array. Clinical Cancer Research, 20(13), 3411-3421. https://doi.org/10.1158/1078-0432.Ccr-13-2173
Alexander, S. P. H., Fabbro, D., Kelly, E., Mathie, A., Peters, J. A., Veale, E. L., … Davies, J. A. (2019). The Concise Guide to PHARMACOLOGY 2019/20: Catalytic receptors. British Journal of Pharmacology, 176(Suppl 1), S247-s296. https://doi.org/10.1111/bph.14751
Arcila, M. E., Oxnard, G. R., Nafa, K., Riely, G. J., Solomon, S. B., Zakowski, M. F., … Ladanyi, M. (2011). Rebiopsy of lung cancer patients with acquired resistance to EGFR inhibitors and enhanced detection of the T790M mutation using a locked nucleic acid-based assay. Clinical Cancer Research, 17(5), 1169-1180. https://doi.org/10.1158/1078-0432.CCR-10-2277
Awad, M. M., Oxnard, G. R., Jackman, D. M., Savukoski, D. O., Hall, D., Shivdasani, P., … Sholl, L. M. (2016). MET exon 14 mutations in non-small-cell lung cancer are associated with advanced age and stage-dependent MET genomic amplification and c-Met overexpression. Journal of Clinical Oncology, 34(7), 721-730. https://doi.org/10.1200/jco.2015.63.4600
Bean, J., Brennan, C., Shih, J. Y., Riely, G., Viale, A., Wang, L., … Pao, W. (2007). MET amplification occurs with or without T790M mutations in EGFR mutant lung tumors with acquired resistance to gefitinib or erlotinib. Proceedings of the National Academy of Sciences of the United States of America, 104(52), 20932-20937. https://doi.org/10.1073/pnas.0710370104
Bladt, F., Faden, B., Friese-Hamim, M., Knuehl, C., Wilm, C., Fittschen, C., … Blaukat, A. (2013). EMD 1214063 and EMD 1204831 constitute a new class of potent and highly selective c-Met inhibitors. Clinical Cancer Research, 19(11), 2941-2951. https://doi.org/10.1158/1078-0432.CCR-12-3247
Bueno, L., de Alwis, D. P., Pitou, C., Yingling, J., Lahn, M., Glatt, S., & Trocóniz, I. F. (2008). Semi-mechanistic modelling of the tumour growth inhibitory effects of LY2157299, a new type I receptor TGF-β kinase antagonist, in mice. European Journal of Cancer, 44(1), 142-150. https://doi.org/10.1016/j.ejca.2007.10.008
Choueiri, T. K., Jakacki, R., Ghiorghiu, D., Haddad, V., Kohlmann, A., Frigault, M. M., & Ottesen, L. (2017). Abstract 924TiP. Savolitinib versus sunitinib in patients with MET-driven, unresectable and locally advanced or metastatic papillary renal cell carcinoma: SAVOIR, a randomised, phase III trial. Annals of Oncology, 28(suppl_5), v328. https://doi.org/10.1093/annonc/mdx371.078
Cui, Y., Dai, G., Ren, Y., Zhou, F., Fan, S., Sai, Y., … Su, W. (2011). Abstract 3612. A novel and selective c-Met inhibitor against subcutaneous xenograft and othotopic brain tumor models. Cancer Research, 71(8 Supplement), 3612-3612. https://doi.org/10.1158/1538-7445.Am2011-3612
Engelman, J. A., Zejnullahu, K., Mitsudomi, T., Song, Y., Hyland, C., Park, J. O., … Janne, P. A. (2007). MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science, 316(5827), 1039-1043. https://doi.org/10.1126/science.1141478
Falchook, G. S., Hong, D. S., Amin, H. M., Fu, S., Piha-Paul, S. A., Janku, F., … Kurzrock, R. (2014). Abstract 450PD. First-in-human phase I trial assessing the highly selective c-Met inhibitor MSC2156119J (EMD 1214063) in patients with advanced solid tumors. Annals of Oncology, 25(Suppl 4), iv149. https://doi.org/10.1093/annonc/mdu331.10
Frampton, G. M., Ali, S. M., Rosenzweig, M., Chmielecki, J., Lu, X., Bauer, T. M., … Miller, V. A. (2015). Activation of MET via diverse exon 14 splicing alterations occurs in multiple tumor types and confers clinical sensitivity to MET inhibitors. Cancer Discovery, 5(8), 850-859. https://doi.org/10.1158/2159-8290.Cd-15-0285
Gan, H. K., Millward, M., Hua, Y., Qi, C., Sai, Y., Su, W., … Lickliter, J. D. (2019). First-in-human phase I study of the selective MET inhibitor, savolitinib, in patients with advanced solid tumors: Safety, pharmacokinetics, and antitumor activity. Clinical Cancer Research, 25, 4924-4932. https://doi.org/10.1158/1078-0432.Ccr-18-1189
Gavine, P. R., Ren, Y., Han, L., Lv, J., Fan, S., Zhang, W., … Wang, Q. M. (2015). Volitinib, a potent and highly selective c-Met inhibitor, effectively blocks c-Met signaling and growth in c-MET amplified gastric cancer patient-derived tumor xenograft models. Molecular Oncology, 9(1), 323-333. https://doi.org/10.1016/j.molonc.2014.08.015
Gu, Y., Sai, Y., Wang, J., Xia, S., Wang, G., Zhao, Y., … Su, W. (2013). Abstract 3371. Preclinical disposition and pharmacokinetics of volitinib, a novel selective cMet inhibitor. Cancer Research, 73(8 Supplement), 3371. https://doi.org/10.1158/1538-7445.AM2013-3371
Gu, Y., Sai, Y., Wang, J., Yu, M., Wang, G., Zhang, L., … Su, W. (2019). Preclinical pharmacokinetics, disposition, and translational pharmacokinetic/pharmacodynamic modeling of savolitinib, a novel selective cMet inhibitor. European Journal of Pharmaceutical Sciences, 136, 104938. https://doi.org/10.1016/j.ejps.2019.05.016
Henry, R. E., Barry, E. R., Castriotta, L., Ladd, B., Markovets, A., Beran, G., … Schuller, A. G. (2016). Acquired savolitinib resistance in non-small cell lung cancer arises via multiple mechanisms that converge on MET-independent mTOR and MYC activation. Oncotarget, 7(36), 57651-57670. https://doi.org/10.18632/oncotarget.10859
Jia, H., Dai, G., Weng, J., Zhang, Z., Wang, Q., Zhou, F., … Su, W. (2014). Discovery of (S)-1-(1-(imidazo[1,2-a]pyridin-6-yl)ethyl)-6-(1-methyl-1H-pyrazol-4-yl)-1H-[1,2, 3]triazolo[4,5-b]pyrazine (volitinib) as a highly potent and selective mesenchymal-epithelial transition factor (c-Met) inhibitor in clinical development for treatment of cancer. Journal of Medicinal Chemistry, 57(18), 7577-7589. https://doi.org/10.1021/jm500510f
Jones, R. D., Grondine, M., Borodovsky, A., Martin, M. S., DuPont, M., D'Cruz, C., … Ahmed, G. F. (2018). Abstract 4263: A semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) model of savolitinib (AZD6094/HMPL-504), a novel MET inhibitor, to explore extent and duration of target inhibition required for optimal efficacy in the EBC-1 mouse xenograft model. Cancer Research, 78(13 Supplement), 4263-4263. https://doi.org/10.1158/1538-7445.Am2018-4263
Kay, K., Dolcy, K., Bies, R., & Shah, D. K. (2019). Estimation of solid tumor doubling times from progression-free survival plots using a novel statistical approach. The AAPS Journal, 21(2), 27. https://doi.org/10.1208/s12248-019-0302-5
Lee, J. Y., Kim, M.-S., Kim, E. H., Chung, N., & Jeong, Y. K. (2016). Retrospective growth kinetics and radiosensitivity analysis of various human xenograft models. Laboratory Animal Research, 32(4), 187-193. https://doi.org/10.5625/lar.2016.32.4.187
Lilley, E., Stanford, S. C., Kendall, D. E., Alexander, S. P., Cirino, G., Docherty, J. R., … Ahluwalia, A. (2020). ARRIVE 2.0 and the British Journal of Pharmacology: Updated guidance for 2020. British Journal of Pharmacology, 177, (16), 3611-3616. https://doi.org/10.1111/bph.15178
Lindbom, L., Pihlgren, P., & Jonsson, E. N. (2005). PsN-toolkit-A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Computer Methods and Programs in Biomedicine, 79(3), 241-257. https://doi.org/10.1016/j.cmpb.2005.04.005
Matsumoto, K., & Nakamura, T. (1996). Emerging multipotent aspects of hepatocyte growth factor. Journal of Biochemistry, 119(4), 591-600. https://doi.org/10.1093/oxfordjournals.jbchem.a021283
Norton, L., & Simon, R. (1977). Tumor size, sensitivity to therapy, and design of treatment schedules. Cancer Treatment Reports, 61(7), 1307-1317.
Olivero, M., Valente, G., Bardelli, A., Longati, P., Ferrero, N., Cracco, C., … Di Renzo, M. F. (1999). Novel mutation in the ATP-binding site of the MET oncogene tyrosine kinase in a HPRCC family. International Journal of Cancer, 82(5), 640-643. https://doi.org/10.1002/(sici)1097-0215(19990827)82:5<640::aid-ijc4>3.0.co;2-6
Oxnard, G. R., Cantarini, M., Frewer, P., Hawkins, G., Peters, J., Howarth, P., … Ahn, M.-J. (2019). SAVANNAH: A Phase II trial of osimertinib plus savolitinib for patients (pts) with EGFR-mutant, MET-driven (MET+), locally advanced or metastatic non-small cell lung cancer (NSCLC), following disease progression on osimertinib. Journal of Clinical Oncology, 37(15_suppl), TPS9119. https://doi.org/10.1200/JCO.2019.37.15_suppl.TPS9119
Parra-Guillen, Z. P., Mangas-Sanjuan, V., Garcia-Cremades, M., Troconiz, I. F., Mo, G., Pitou, C., … Wallin, J. E. (2018). Systematic modeling and design evaluation of unperturbed tumor dynamics in xenografts. Journal of Pharmacology and Experimental Therapeutics, 366(1), 96-104. https://doi.org/10.1124/jpet.118.248286
Percie du Sert, N., Hurst, V., Ahluwalia, A., Alam, S., Avey, M. T., Baker, M., … Würbel, H. (2020). The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLoS Biology, 18(7), e3000410. https://doi.org/10.1371/journal.pbio.3000410
Raghav, K., Bailey, A. M., Loree, J. M., Kopetz, S., Holla, V., Yap, T. A., … Hong, D. (2018). Untying the gordion knot of targeting MET in cancer. Cancer Treatment Reviews, 66, 95-103. https://doi.org/10.1016/j.ctrv.2018.04.008
Schuler, M., Berardi, R., Lim, W. T., de Jonge, M., Bauer, T. M., Azaro, A., … Kim, T. M. (2020). Molecular correlates of response to capmatinib in advanced non-small-cell lung cancer: Clinical and biomarker results from a phase I trial. Annals of Oncology, 31, 789-797. https://doi.org/10.1016/j.annonc.2020.03.293
Schuller, A. G., Barry, E. R., Jones, R. D., Henry, R. E., Frigault, M. M., Beran, G., … D'Cruz, C. M. (2015). The MET inhibitor AZD6094 (savolitinib, HMPL-504) induces regression in papillary renal cell carcinoma patient-derived xenograft models. Clinical Cancer Research, 21(12), 2811-2819. https://doi.org/10.1158/1078-0432.Ccr-14-2685
Sequist, L. V., Han, J.-Y., Ahn, M.-J., Cho, B. C., Yu, H., Kim, S.-W., … Oxnard, G. (2020). Osimertinib plus savolitinib in patients with EGFR mutation-positive, MET-amplified, non-small-cell lung cancer after progression on EGFR tyrosine kinase inhibitors: Interim results from a multicentre, open-label, phase 1b study. The Lancet Oncology, 21(3), 373-386. https://doi.org/10.1016/S1470-2045(19)30785-5
Sequist, L. V., Waltman, B. A., Dias-Santagata, D., Digumarthy, S., Turke, A. B., Fidias, P., … Cosper, A. K. (2011). Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Science Translational Medicine, 3(75), 75ra26. https://doi.org/10.1126/scitranslmed.3002003
Simeoni, M., Magni, P., Cammia, C., De Nicolao, G., Croci, V., Pesenti, E., … Rocchetti, M. (2004). Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents. Cancer Research, 64(3), 1094-1101. https://doi.org/10.1158/0008-5472.can-03-2524
Soman, N. R., Correa, P., Ruiz, B. A., & Wogan, G. N. (1991). The TPR-MET oncogenic rearrangement is present and expressed in human gastric carcinoma and precursor lesions. Proceedings of the National Academy of Sciences of the United States of America, 88(11), 4892-4896. https://doi.org/10.1073/pnas.88.11.4892
Xiong, W., El Bawab, S., Bladt, F., Meyring, M., Klevesath, M., Falchook, G., … Girard, P. (2015). Abstract 4510. Model-based phase II dose selection of c-Met inhibitor MSC2156119J. Cancer Research, 75(15 Supplement), 4510. https://doi.org/10.1158/1538-7445.AM2015-4510
Yamazaki, S. (2013). Translational pharmacokinetic-pharmacodynamic modeling from nonclinical to clinical development: A case study of anticancer drug, crizotinib. The AAPS Journal, 15(2), 354-366. https://doi.org/10.1208/s12248-012-9436-4
Yamazaki, S., Skaptason, J., Romero, D., Lee, J. H., Zou, H. Y., Christensen, J. G., … Koudriakova, T. (2008). Pharmacokinetic-pharmacodynamic modeling of biomarker response and tumor growth inhibition to an orally available cMet kinase inhibitor in human tumor xenograft mouse models. Drug Metabolism and Disposition, 36(7), 1267-1274. https://doi.org/10.1124/dmd.107.019711
Yates, J. W. T., Ashton, S., Cross, D., Mellor, M. J., Powell, S. J., & Ballard, P. (2016). Irreversible inhibition of EGFR: Modeling the combined pharmacokinetic-pharmacodynamic relationship of osimertinib and its active metabolite AZ5104. Molecular Cancer Therapeutics, 15(10), 2378-2387. https://doi.org/10.1158/1535-7163.MCT-16-0142
Yu, H., Ahn, M.-J., Kim, S.-W., Cho, B. C., Sequist, L., Orlov, S., … Han, J.-Y. (2019). Abstract CT032. TATTON Phase Ib expansion cohort: Osimertinib plus savolitinib for patients (pts) with EGFR-mutant, MET-amplified NSCLC after progression on prior first/second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI). Cancer Research, 79(13 Supplement), 3612-3612. https://doi.org/10.1158/1538-7445.SABCS18-CT032