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Characterization of an Orthotopic Colorectal Cancer Mouse Model and Its Feasibility for Accurate Quantification in Positron Emission Tomography

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Abstract

Purpose

Quantification in positron emission tomography (PET) imaging of an orthotopic mouse model of colorectal cancer (CRC) is challenging due to difficult tumor delineation. We aimed to establish a reproducible delineation approach, evaluate its feasibility for reliable PET quantification and compare its added translational value with its subcutaneous counterpart.

Procedures

A subcutaneous Colo205-luc2 tumor fragment harvested from a donor mouse was transplanted onto the caecum of nude mice, with (n = 10) or without (n = 10) the addition of an X-ray detectable thread. Animals underwent 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET imaging, complemented with X-ray computed tomography (CT) and magnetic resonance imaging (MRI, 7T). Animals without a thread underwent additional contrast enhanced (Exitron) CT imaging. Tumors were delineated on the MRI, μPET image or contrast enhanced μCT images and correlations between in vivo and ex vivo [18F]FDG tumor uptake as well as between image-derived and caliper-measured tumor volume were evaluated. Finally, cancer hallmarks were assessed immunohistochemically for the characterization of both models.

Results

Our results showed the strongest correlation between both in vivo and ex vivo uptake (r = 0.84, p < 0.0001) and image-derived and caliper-measured tumor volume (r = 0.96, p < 0.0001) when the tumor was delineated on the MR image. Orthotopic tumors displayed an abundance of stroma, higher levels of proliferation (p = 0.0007), apoptosis (p = 0.02), and necrosis (p < 0.0001), a higher number of blood vessels (p < 0.0001); yet lower tumor hypoxia (p < 0.0001) as compared with subcutaneous tumors.

Conclusions

This orthotopic mouse model proved to be a promising tool for the investigation of CRC through preclinical imaging studies provided the availability of anatomical MR images for accurate tumor delineation. Furthermore, the tumor microenvironment of the orthotopic tumor resembled more that of human CRC, increasing its likelihood to advance translational nuclear imaging studies of CRC.

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Acknowledgements

The authors thank Philippe Joye and Caroline Berghmans of the Molecular Imaging Center Antwerp as well as Johan Van Audekerke of the Bio-Imaging Lab for their valuable technical assistance. This work was funded by the University of Antwerp through a Bijzonder Onderzoeksfond for S.R. (BOF27327) and the iMinds ICON project FIAT (functional image analysis of tumors) for J.V., M.V. and R.H. Si.S and C.V. are supported by the Innovative Medicines Initiative Joint Undertaking (www.imi.europa.eu) under grant agreement number 115151, resources of which are composed of financial contribution from the European Union’s Seventh Framework Program (FP7/2007-2013) and EFPIA companies’ in-kind contribution.

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Authors and Affiliations

  1. Molecular Imaging Center Antwerp (MICA), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium

    Sara Rapic, Christel Vangestel, Jeroen Verhaeghe, Tim Van den Wyngaert, Steven Staelens & Sigrid Stroobants

  2. Department of Nuclear Medicine, Antwerp University Hospital, Wilrijkstraat 10, 2650, Edegem, Belgium

    Christel Vangestel, Tim Van den Wyngaert & Sigrid Stroobants

  3. Bio-Imaging Lab (BIL), Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium

    Rukun Hinz & Marleen Verhoye

  4. Department of Pathological Anatomy, Antwerp University Hospital, Wilrijkstraat 10, 2650, Edegem, Belgium

    Patrick Pauwels

  5. Center for Oncological Research (CORE), Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium

    Patrick Pauwels

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  1. Sara Rapic
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Correspondence to Sigrid Stroobants.

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Rapic, S., Vangestel, C., Verhaeghe, J. et al. Characterization of an Orthotopic Colorectal Cancer Mouse Model and Its Feasibility for Accurate Quantification in Positron Emission Tomography. Mol Imaging Biol 19, 762–771 (2017). https://doi.org/10.1007/s11307-017-1051-4

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