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Cancer Res. 2010 Nov 15;70(22):9022-30. doi: 10.1158/0008-5472.CAN-10-1338. Epub 2010 Nov 9.

PET imaging of tumor neovascularization in a transgenic mouse model with a novel 64Cu-DOTA-knottin peptide.

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  • 1Molecular Imaging Program at Stanford, Department of Radiology, Division of Oncology, Stanford University, Stanford, California 94305-5427, USA.

Abstract

Due to the high mortality of lung cancer, there is a critical need to develop diagnostic procedures enabling early detection of the disease while at a curable stage. Targeted molecular imaging builds on the positive attributes of positron emission tomography/computed tomography (PET/CT) to allow for a noninvasive detection and characterization of smaller lung nodules, thus increasing the chances of positive treatment outcome. In this study, we investigate the ability to characterize lung tumors that spontaneously arise in a transgenic mouse model. The tumors are first identified with small animal CT followed by characterization with the use of small animal PET with a novel 64Cu-1,4,7,10-tetra-azacylododecane-N,N',N'',N'''-tetraacetic acid (DOTA)-knottin peptide that targets integrins upregulated during angiogenesis on the tumor associated neovasculature. The imaging results obtained with the knottin peptide are compared with standard 18F-fluorodeoxyglucose (FDG) PET small animal imaging. Lung nodules as small as 3 mm in diameter were successfully identified in the transgenic mice by small animal CT, and both 64Cu-DOTA-knottin 2.5F and FDG were able to differentiate lung nodules from the surrounding tissues. Uptake and retention of the 64Cu-DOTA-knottin 2.5F tracer in the lung tumors combined with a low background in the thorax resulted in a statistically higher tumor to background (normal lung) ratio compared with FDG (6.01±0.61 versus 4.36±0.68; P<0.05). Ex vivo biodistribution showed 64Cu-DOTA-knottin 2.5F to have a fast renal clearance combined with low nonspecific accumulation in the thorax. Collectively, these results show 64Cu-DOTA-knottin 2.5F to be a promising candidate for clinical translation for earlier detection and improved characterization of lung cancer.

Copyright © 2010 AACR.

PMID:
21062977
[PubMed - indexed for MEDLINE]
PMCID:
PMC3057960
Free PMC Article
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