Integrated Pharmacodynamic Analysis Identifies Two Metabolic Adaption Pathways to Metformin in Breast Cancer

Lord, Simon R. and Cheng, Wei-Chen and Liu, Dan and Gaude, Edoardo and Haider, Syed and Metcalf, Tom and Patel, Neel and Teoh, Eugene J. and Gleeson, Fergus and Bradley, Kevin and Wigfield, Simon and Zois, Christos and McGowan, Daniel R. and Ah-See, Mei-Lin and Thompson, Alastair M. and Sharma, Anand and Bidaut, Luc and Pollak, Michael and Roy, Pankaj G. and Karpe, Fredrik and James, Tim and English, Ruth and Adams, Rosie F. and Campo, Leticia and Ayers, Lisa and Snell, Cameron and Roxanis, Ioannis and Frezza, Christian and Fenwick, John D. and Buffa, Francesca M. and Harris, Adrian L. (2018) Integrated Pharmacodynamic Analysis Identifies Two Metabolic Adaption Pathways to Metformin in Breast Cancer. Cell Metabolism, 28 . pp. 1-10. ISSN 1550-4131

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Abstract

Late-phase clinical trials investigating metformin as a cancer therapy are underway. However, there remains controversy as to the mode of action of metformin in tumors at clinical doses. We conducted a clinical study integrating measurement of markers
of systemic metabolism, dynamic FDG-PET-CT, transcriptomics, and metabolomics at paired time points to profile the bioactivity of metformin in primary breast cancer. We show metformin reduces the levels of mitochondrial metabolites, activates multiple mitochondrial metabolic pathways, and increases 18-FDG flux in tumors. Two tumor groups are identified with distinct metabolic responses, an OXPHOS transcriptional response (OTR) group for which there is an increase in OXPHOS gene transcription and an FDG response group with increased 18-FDG uptake. Increase in proliferation, as measured by a validated proliferation signature, suggested that patients in the OTR group were resistant to metformin treatment. We conclude that mitochondrial response to metformin in primary breast cancer may define anti-tumor effect.

Keywords:Metformin, Breast Cancer, PET, Pharmacodynamic, Metabolic pathway
Subjects:B Subjects allied to Medicine > B100 Anatomy, Physiology and Pathology
C Biological Sciences > C130 Cell Biology
G Mathematical and Computer Sciences > G150 Mathematical Modelling
C Biological Sciences > C100 Biology
B Subjects allied to Medicine > B210 Pharmacology
A Medicine and Dentistry > A300 Clinical Medicine
B Subjects allied to Medicine > B132 Pathobiology
B Subjects allied to Medicine > B800 Medical Technology
Divisions:College of Science > School of Computer Science
ID Code:33695
Deposited On:31 Oct 2018 13:20

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