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Optimization of Early Response Monitoring and Prediction of Cancer Antiangiogenesis Therapy via Noninvasive PET Molecular Imaging Strategies of Multifactorial Bioparameters.

ABSTRACT: Objective: Antiangiogenesis therapy (AAT) has provided substantial benefits regarding improved outcomes and survival for suitable patients in clinical settings. Therefore, the early definition of therapeutic effects is urgently needed to guide cancer AAT. We aimed to optimize the early response monitoring and prediction of AAT efficacy, as indicated by the multi-targeted anti-angiogenic drug sunitinib in U87MG tumors, using noninvasive positron emission computed tomography (PET) molecular imaging strategies of multifactorial bioparameters. Methods: U87MG tumor mice were treated via intragastric injections of sunitinib (80 mg/kg) or vehicle for 7 consecutive days. Longitudinal MicroPET/CT scans with ¹⁸F-FDG, ¹⁸F-FMISO, ¹⁸F-ML-10 and ¹⁸F-Alfatide II were acquired to quantitatively measure metabolism, hypoxia, apoptosis and angiogenesis on days 0, 1, 3, 7 and 13 following therapy initiation. Tumor tissues from a dedicated group of mice were collected for immunohistochemical (IHC) analysis of key biomarkers (Glut-1, CA-IX, TUNEL, ?_??₃ and CD31) at the time points of PET imaging. The tumor sizes and mouse weights were measured throughout the study. The tumor uptake (ID%/g_max), the ratios of the tumor/muscle (T/M) for each probe, and the tumor growth ratios (TGR) were calculated and used for statistical analyses of the differences and correlations. Results: Sunitinib successfully inhibited U87MG tumor growth with significant differences in the tumor size from day 9 after sunitinib treatment compared with the control group (P < 0.01). The uptakes of ¹⁸F-FMISO (reduced hypoxia), ¹⁸F-ML-10 (increased apoptosis) and ¹⁸F-Alfatide II (decreased angiogenesis) in the tumor lesions significantly changed during the early stage (days 1 to 3) of sunitinib treatment; however, the uptake of ¹⁸F-FDG (increased glucose metabolism) was significantly different during the late stage. The PET imaging data of each probe were all confirmed via ex vivo IHC of the relevant biomarkers. Notably, the PET imaging of ¹⁸F-Alfatide II and ¹⁸F-FMISO was significantly correlated (all P < 0.05) with TGR, whereas the imaging of ¹⁸F-FDG and ¹⁸F-ML-10 was not significantly correlated with TGR. Conclusion: Based on the tumor uptake of the PET probes and their correlations with MVD and TGR, ¹⁸F-Alfatide II PET may not only monitor the early response but also precisely predict the therapeutic efficacy of the multi-targeted, anti-angiogenic drug sunitinib in U87MG tumors. In conclusion, it is feasible to optimize the early response monitoring and efficacy prediction of cancer AAT using noninvasive PET molecular imaging strategies of multifactorial bioparameters, such as angiogenesis imaging with ¹⁸F-Alfatide II, which represents an RGD-based probe.

SUBMITTER: Bao X

PROVIDER: S-EPMC5039682 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Optimization of Early Response Monitoring and Prediction of Cancer Antiangiogenesis Therapy via Noninvasive PET Molecular Imaging Strategies of Multifactorial Bioparameters.

Bao Xiao X Wang Ming-Wei MW Luo Jian-Min JM Wang Si-Yang SY Zhang Yong-Ping YP Zhang Ying-Jian YJ

Theranostics 20160910 12

<b>Objective</b>: Antiangiogenesis therapy (AAT) has provided substantial benefits regarding improved outcomes and survival for suitable patients in clinical settings. Therefore, the early definition of therapeutic effects is urgently needed to guide cancer AAT. We aimed to optimize the early response monitoring and prediction of AAT efficacy, as indicated by the multi-targeted anti-angiogenic drug sunitinib in U87MG tumors, using noninvasive positron emission computed tomography (PET) molecular ...[more]

PMID: 27698942

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Project description:Microfluidic technologies provide an attractive platform for the synthesis of radiolabeled compounds. Visualization of radioisotopes on chip is critical for synthesis optimization and technological development. With Cerenkov imaging, beta particle emitting isotopes can be localized with a sensitive CCD camera. In order for Cerenkov imaging to also serve as a quantitative tool, it is necessary to understand how material properties relevant to Cerenkov emission, namely, index of refraction and beta particle stopping power, affect Cerenkov light output. In this report, we investigate the fundamental physical characteristics of Cerenkov photon yield at different stages of [(18)F]FDG synthesis on the electrowetting on dielectric (EWOD) microfluidic platform. We also demonstrate how Cerenkov imaging has enabled synthesis optimization. Geant4, a Monte Carlo program applied extensively in high energy physics, is used to simulate Cerenkov photon yield from (18)F beta particles traversing materials of interest during [(18)F]FDG synthesis on chip. Our simulations show that the majority (approximately two-thirds) of the (18)F beta particle energy available to produce Cerenkov photons is deposited on the glass plates of the EWOD chip. This result suggests the possibility of using a single calibration factor to convert Cerenkov signal to radioactivity, independent of droplet composition. We validate our simulations with a controlled measurement examining varying ratios of [(18)O]H2O, dimethyl sulfoxide (DMSO), and acetonitrile (MeCN), and find a consistent calibration independent of solvent composition. However, the calibration factor may underestimate the radioactivity in actual synthesis due to discoloration of the droplet during certain steps of probe synthesis. In addition to the attractive quantitative potential of Cerenkov imaging, this imaging strategy provides indispensable qualitative data to guide synthesis optimization. We are able to use this imaging technique to optimize the mixing protocol as well as identify and correct for loss of radioactivity due to the migration of radioactive vapor outside of the EWOD heater, enabling an overall increase in the crude radiochemical yield from 50 ± 3% (n = 3) to 72 ± 13% (n = 5).

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Dataset Information

Optimization of Early Response Monitoring and Prediction of Cancer Antiangiogenesis Therapy via Noninvasive PET Molecular Imaging Strategies of Multifactorial Bioparameters.

Publications

Optimization of Early Response Monitoring and Prediction of Cancer Antiangiogenesis Therapy via Noninvasive PET Molecular Imaging Strategies of Multifactorial Bioparameters.

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