Literature DB >> 23298863

Pharmacokinetic and pharmacodynamic modeling of hedgehog inhibitor TAK-441 for the inhibition of Gli1 messenger RNA expression and antitumor efficacy in xenografted tumor model mice.

Akifumi Kogame1, Yoshihiko Tagawa, Sachio Shibata, Hideaki Tojo, Maki Miyamoto, Kimio Tohyama, Takahiro Kondo, Shimoga Prakash, Wen Chyi Shyu, Satoru Asahi.   

Abstract

6-Ethyl-N-[1-(hydroxyacetyl)piperidin-4-yl]-1-methyl-4-oxo-5-(2-oxo-2-phenylethyl)-3-(2,2,2-trifluoroethoxy)-4,5-dihydro-1H-pyrrolo[3,2-c]pyridine-2-carboxamide (TAK-441) is a potent, selective hedgehog signaling pathway inhibitor that binds to Smo and is being developed for the treatment of cancer. The objectives of these studies were to explore the possibility of establishing of a link between the pharmacokinetics of TAK-441 and the responses of Gli1 mRNA in tumor-associated stromal or skin cells and the antitumor effect of hedgehog inhibition. To this end, we built pharmacokinetic and pharmacodynamic models that describe the relationship of the concentrations of TAK-441 plasma to the responses of Gli1 mRNA in the tumor (target) and skin (surrogate) and to tumor growth inhibition in mice bearing xenografts of human pancreatic tumors (PAN-04). The responses of Gli1 mRNA and tumor growth were described by an indirect response model and an exponential tumor growth model, respectively. The IC50 values for Gli1 mRNA inhibition in the tumor and skin by TAK-441 were estimated to be 0.0457 and 0.113 μg/ml, respectively. The IC90 value for tumor growth inhibition was estimated to be 0.68 μg/ml. These results suggest that a >83% inhibition of Gli1 mRNA expression in the skin or a >94% inhibition of Gli1 mRNA expression in the tumor would be required to sufficiently inhibit (>90%) hedgehog-related tumor growth in the xenografted model mice. We conclude that Gli1 mRNA expression in the tumor and skin could be a useful biomarker for predicting the antitumor effect of hedgehog inhibitors.

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Year:  2013        PMID: 23298863     DOI: 10.1124/dmd.112.049650

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  10 in total

1.  A pharmacokinetic-pharmacodynamic model predicting tumour growth inhibition after intermittent administration with the mTOR kinase inhibitor AZD8055.

Authors:  James W T Yates; Sarah V Holt; Armelle Logie; Kirsty Payne; Karen Woods; Robert W Wilkinson; Barry R Davies; Sylvie M Guichard
Journal:  Br J Pharmacol       Date:  2017-07-06       Impact factor: 8.739

Review 2.  Safety and Tolerability of Sonic Hedgehog Pathway Inhibitors in Cancer.

Authors:  Richard L Carpenter; Haimanti Ray
Journal:  Drug Saf       Date:  2019-02       Impact factor: 5.606

Review 3.  Personalising pancreas cancer treatment: When tissue is the issue.

Authors:  Katrin M Sjoquist; Venessa T Chin; Lorraine A Chantrill; Chelsie O'Connor; Chris Hemmings; David K Chang; Angela Chou; Marina Pajic; Amber L Johns; Adnan M Nagrial; Andrew V Biankin; Desmond Yip
Journal:  World J Gastroenterol       Date:  2014-06-28       Impact factor: 5.742

Review 4.  Targeting the Sonic Hedgehog Signaling Pathway: Review of Smoothened and GLI Inhibitors.

Authors:  Tadas K Rimkus; Richard L Carpenter; Shadi Qasem; Michael Chan; Hui-Wen Lo
Journal:  Cancers (Basel)       Date:  2016-02-15       Impact factor: 6.639

5.  Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients.

Authors:  Shayna Stein; Rui Zhao; Hiroshi Haeno; Igor Vivanco; Franziska Michor
Journal:  PLoS Comput Biol       Date:  2018-01-02       Impact factor: 4.475

Review 6.  Quantitative translational modeling to facilitate preclinical to clinical efficacy & toxicity translation in oncology.

Authors:  Andy Zx Zhu
Journal:  Future Sci OA       Date:  2018-04-23

Review 7.  Recent Advances in the Clinical Targeting of Hedgehog/GLI Signaling in Cancer.

Authors:  Hao Xie; Brooke D Paradise; Wen Wee Ma; Martin E Fernandez-Zapico
Journal:  Cells       Date:  2019-04-29       Impact factor: 6.600

8.  Developing Exposure/Response Models for Anticancer Drug Treatment: Special Considerations.

Authors:  D R Mould; A-C Walz; T Lave; J P Gibbs; B Frame
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-01-21

9.  Targeting the Epithelial-to-Mesenchymal Transition in Cancer Stem Cells for a Better Clinical Outcome of Glioma.

Authors:  Yu-Bao Lu; Tian-Jiao Sun; Yu-Tong Chen; Zong-Yan Cai; Jia-Yu Zhao; Feng Miao; Yong-Na Yang; Shi-Xin Wang
Journal:  Technol Cancer Res Treat       Date:  2020 Jan-Dec

Review 10.  The Role of Smoothened in Cancer.

Authors:  Kuo-Shyang Jeng; I-Shyan Sheen; Chuen-Miin Leu; Ping-Hui Tseng; Chiung-Fang Chang
Journal:  Int J Mol Sci       Date:  2020-09-18       Impact factor: 5.923

  10 in total

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