Dataset Information

Preclinical In Vitro and In Vivo Evaluation of [18F]FE@SUPPY for Cancer PET Imaging: Limitations of a Xenograft Model for Colorectal Cancer.

ABSTRACT: Molecular imaging probes such as PET-tracers have the potential to improve the accuracy of tumor characterization by directly visualizing the biochemical situation. Thus, molecular changes can be detected early before morphological manifestation. The A3 adenosine receptor (A3AR) is described to be highly expressed in colon cancer cell lines and human colorectal cancer (CRC), suggesting this receptor as a tumor marker. The aim of this preclinical study was the evaluation of [18F]FE@SUPPY as a PET-tracer for CRC using in vitro imaging and in vivo PET imaging. First, affinity and selectivity of FE@SUPPY and its metabolites were determined, proving the favorable binding profile of FE@SUPPY. The human adenocarcinoma cell line HT-29 was characterized regarding its hA3AR expression and was subsequently chosen as tumor graft. Promising results regarding the potential of [18F]FE@SUPPY as a PET-tracer for CRC imaging were obtained by autoradiography as ?2.3-fold higher accumulation of [18F]FE@SUPPY was found in CRC tissue compared to adjacent healthy colon tissue from the same patient. Nevertheless, first in vivo studies using HT-29 xenografts showed insufficient tumor uptake due to (1) poor conservation of target expression in xenografts and (2) unfavorable pharmacokinetics of [18F]FE@SUPPY in mice. We therefore conclude that HT-29 xenografts are not adequate to visualize hA3ARs using [18F]FE@SUPPY.

SUBMITTER: Balber T

PROVIDER: S-EPMC5830979 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Preclinical In Vitro and In Vivo Evaluation of [18F]FE@SUPPY for Cancer PET Imaging: Limitations of a Xenograft Model for Colorectal Cancer.

Balber T T Singer J J Berroterán-Infante N N Dumanic M M Fetty L L Fazekas-Singer J J Vraka C C Nics L L Bergmann M M Pallitsch K K Spreitzer H H Wadsak W W Hacker M M Jensen-Jarolim E E Viernstein H H Mitterhauser M M

Contrast media & molecular imaging 20180213

Molecular imaging probes such as PET-tracers have the potential to improve the accuracy of tumor characterization by directly visualizing the biochemical situation. Thus, molecular changes can be detected early before morphological manifestation. The A3 adenosine receptor (A3AR) is described to be highly expressed in colon cancer cell lines and human colorectal cancer (CRC), suggesting this receptor as a tumor marker. The aim of this preclinical study was the evaluation of ...[more]

PMID: 29666562

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Project description:BackgroundTo develop and validate a survival model with clinico-biological features and 18F- FDG PET/CT radiomic features via machine learning, and for predicting the prognosis from the primary tumor of colorectal cancer.MethodsA total of 196 pathologically confirmed patients with colorectal cancer (stage I to stage IV) were included. Preoperative clinical factors, serum tumor markers, and PET/CT radiomic features were included for the recurrence-free survival analysis. For the modeling and validation, patients were randomly divided into the training (n = 137) and validation (n = 59) set, while the 78 stage III patients [training (n = 55), and validation (n = 23)] was divided for the further experiment. After selecting features by the log-rank test and variable-hunting methods, random survival forest (RSF) models were built on the training set to analyze the prognostic value of selected features. The performance of models was measured by C-index and was tested on the validation set with bootstrapping. Feature importance and the Pearson correlation were also analyzed.ResultsRadiomics signature (containing four PET/CT features and four clinical factors) achieved the best result for prognostic prediction of 196 patients (C-index 0.780, 95% CI 0.634-0.877). Moreover, four features (including two clinical features and two radiomics features) were selected for prognostic prediction of the 78 stage III patients (C-index was 0.820, 95% CI 0.676-0.900). K-M curves of both models significantly stratified low-risk and high-risk groups (P < 0.0001). Pearson correlation analysis demonstrated that selected radiomics features were correlated with tumor metabolic factors, such as SUVmean, SUVmax.ConclusionThis study presents integrated clinico-biological-radiological models that can accurately predict the prognosis in colorectal cancer using the preoperative 18F-FDG PET/CT radiomics in colorectal cancer. It is of potential value in assisting the management and decision making for precision treatment in colorectal cancer. Trial registration The retrospectively registered study was approved by the Ethics Committee of Fudan University Shanghai Cancer Center (No. 1909207-14-1910) and the data were analyzed anonymously.

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Project description:BackgroundOsteosarcoma is the most common malignant bone tumor in children and young adults that produces aberrant osteoid. The aim of this study was to assess the utility of 2-deoxy-2-[18F-] fluoro-D-glucose ([18F] FDG) and sodium [18F] Fluoride (Na [18F] F) PET scans in orthotopic murine models of osteosarcoma to describe the metabolic pattern of the tumors, to detect and diagnose tumors and to evaluate the efficacy of a new treatment based in oncolytic adenoviruses.MethodsOrthotopic osteosarcoma murine models were created by the injection of 143B and 531MII cell lines. [18F]FDG and Na [18F] F PET scans were performed 30 days (143B) and 90 days (531MII) post-injection. The antitumor effect of two doses (107 and 108 pfu) of the oncolytic adenovirus VCN-01 was evaluated in 531 MII model by [18F] FDG PET studies. [18F] FDG uptake was quantified by SUVmax and Total Lesion Glycolysis (TLG) indexes. For Na [18F] F, the ratio tumor SUVmax/hip SUVmax was calculated. PET findings were confirmed by histopathological techniques.ResultsThe metabolic pattern of tumors was different between both orthotopic models. All tumors showed [18F] FDG uptake, with a sensitivity and specificity of 100%. The [18F] FDG uptake was significantly higher for the 143B model (p < 0.001). Sensitivity for Na [18F] F was around 70% in both models, with a specificity of 100%. 531MII tumors showed a heterogeneous Na [18F] F uptake, significantly higher than 143B tumors (p < 0.01). Importantly, [18F] FDG and Na [18F] F uptake corresponded to highly cellular or osteoid-rich tumors in the histopathological analysis, respectively. [18F] FDG data confirmed that the oncolytic treatment of 531MII tumors produced a significant reduction in growth even with the 107 pfu dose.ConclusionsPET studies demonstrated that the different osteosarcoma xenograft models developed tumors with diverse metabolic patterns that can be described by multitracer PET studies. Since not all tumors produced abundant osteoid, [18F] FDG demonstrated a better sensitivity for tumor detection and was able to quantitatively monitor in vivo response to the oncolytic adenovirus VCN-01.

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Dataset Information

Preclinical In Vitro and In Vivo Evaluation of [18F]FE@SUPPY for Cancer PET Imaging: Limitations of a Xenograft Model for Colorectal Cancer.

Publications

Preclinical <i>In Vitro</i> and <i>In Vivo</i> Evaluation of [<sup>18</sup>F]FE@SUPPY for Cancer PET Imaging: Limitations of a Xenograft Model for Colorectal Cancer.

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