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Metabolomic changes of the multi (-AGC-) kinase inhibitor AT13148 in cells, mice and patients are associated with NOS regulation.
Pal, Akos; Asad, Yasmin; Ruddle, Ruth; Henley, Alan T; Swales, Karen; Decordova, Shaun; Eccles, Suzanne A; Collins, Ian; Garrett, Michelle D; De Bono, Johann; Banerji, Udai; Raynaud, Florence I.
Afiliación
  • Pal A; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Asad Y; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Ruddle R; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Henley AT; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Swales K; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Decordova S; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Eccles SA; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Collins I; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Garrett MD; School of Biosciences, University of Kent, Canterbury, UK.
  • De Bono J; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
  • Banerji U; Drug Development Unit, The Royal Marsden NHS Foundation Trust, Sutton, UK.
  • Raynaud FI; Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
Metabolomics ; 16(4): 50, 2020 04 13.
Article en En | MEDLINE | ID: mdl-32285223
ABSTRACT

INTRODUCTION:

To generate biomarkers of target engagement or predictive response for multi-target drugs is challenging. One such compound is the multi-AGC kinase inhibitor AT13148. Metabolic signatures of selective signal transduction inhibitors identified in preclinical models have previously been confirmed in early clinical studies. This study explores whether metabolic signatures could be used as biomarkers for the multi-AGC kinase inhibitor AT13148.

OBJECTIVES:

To identify metabolomic changes of biomarkers of multi-AGC kinase inhibitor AT13148 in cells, xenograft / mouse models and in patients in a Phase I clinical study.

METHODS:

HILIC LC-MS/MS methods and Biocrates AbsoluteIDQ™ p180 kit were used for targeted metabolomics; followed by multivariate data analysis in SIMCA and statistical analysis in Graphpad. Metaboanalyst and String were used for network analysis.

RESULTS:

BT474 and PC3 cells treated with AT13148 affected metabolites which are in a gene protein metabolite network associated with Nitric oxide synthases (NOS). In mice bearing the human tumour xenografts BT474 and PC3, AT13148 treatment did not produce a common robust tumour specific metabolite change. However, AT13148 treatment of non-tumour bearing mice revealed 45 metabolites that were different from non-treated mice. These changes were also observed in patients at doses where biomarker modulation was observed. Further network analysis of these metabolites indicated enrichment for genes associated with the NOS pathway. The impact of AT13148 on the metabolite changes and the involvement of NOS-AT13148- Asymmetric dimethylarginine (ADMA) interaction were consistent with hypotension observed in patients in higher dose cohorts (160-300 mg).

CONCLUSION:

AT13148 affects metabolites associated with NOS in cells, mice and patients which is consistent with the clinical dose-limiting hypotension.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Pirazoles / 2-Hidroxifenetilamina / Óxido Nítrico Sintasa / Inhibidores de Proteínas Quinasas / Metabolómica / Antineoplásicos Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Metabolomics Año: 2020 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Pirazoles / 2-Hidroxifenetilamina / Óxido Nítrico Sintasa / Inhibidores de Proteínas Quinasas / Metabolómica / Antineoplásicos Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Metabolomics Año: 2020 Tipo del documento: Article