Literature DB >> 23344784

2-Deoxy-2-[18F]fluoro-D-glucose positron emission tomography demonstrates target inhibition with the potential to predict anti-tumour activity following treatment with the AKT inhibitor AZD5363.

Juliana Maynard1, Sally-Ann Ricketts, Christelle Gendrin, Phillippa Dudley, Barry R Davies.   

Abstract

PURPOSE: The phosphatidyl inositol 3 kinase, AKT and mammalian target of rapamycin are frequently deregulated in human cancer and are among one of the most promising targets for cancer therapy. AZD5363 (AstraZeneca) is an AKT inhibitor in phase 1 clinical trials. Given its utility in assessing glucose metabolism, we investigated the role of 2-Deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) as a biomarker to demonstrate target inhibition and its potential to predict and demonstrate the anti-tumour activity of AZD5363.
METHODS: 18F-FDG PETscans were performed in nude mice in a number of xenograft models (U87-MG glioblastoma, BT474C breast carcinoma and Calu-6 lung). Mice were fasted prior to imaging, and either static or dynamic 18F-FDG PET imaging was performed.
RESULTS: We have shown that 18F-FDG uptake in tumour xenografts was reduced by 39% reduction compared to vehicle after a single dose of AZD5363, demonstrating activation of the AKT pathway after only 4 h of dosing. Multiple doses of AZD5363 showed an anti-tumour volume effect and a reduction in 18F-FDG uptake (28% reduction compared to vehicle), highlighting the potential of 18F-FDG PET as an efficacy biomarker. Furthermore, the degree of inhibition of 18F-FDG uptake corresponded with the sensitivity of the tumour model to AZD5363. The use of dynamic 18F-FDG PET and a two-compartmental analysis identified the mechanism of this change to be due to a change in cellular uptake of 18F-FDG following administration of AZD5363.
CONCLUSIONS: We conclude that 18F-FDG PET is a promising pharmacodynamic biomarker of AKT pathway inhibition, with potential to predict and demonstrate anti-tumour activity. It is a biomarker that may stop ineffective drug schedules, helping to make early stop decisions and identify responding subsets of patients, resulting in improved clinical decision making both during drug development and patient management.

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Year:  2013        PMID: 23344784     DOI: 10.1007/s11307-013-0613-3

Source DB:  PubMed          Journal:  Mol Imaging Biol        ISSN: 1536-1632            Impact factor:   3.488


  33 in total

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