Dataset Information

The Use of a Non-Conventional Long-Lived Gallium Radioisotope ⁶⁶Ga Improves Imaging Contrast of EGFR Expression in Malignant Tumours Using DFO-ZEGFR:2377 Affibody Molecule.

ABSTRACT: Epidermal growth factor receptor (EGFR) is overexpressed in many malignancies. EGFR-targeted therapy extends survival of patients with disseminated cancers. Radionuclide molecular imaging of EGFR expression would make EGFR-directed treatment more personalized and therefore more efficient. A previous study demonstrated that affibody molecule [⁶⁸Ga]Ga-DFO-ZEGFR:2377 permits specific positron-emission tomography (PET) imaging of EGFR expression in xenografts at 3 h after injection. We anticipated that imaging at 24 h after injection would provide higher contrast, but this is prevented by the short half-life of ⁶⁸Ga (67.6 min). Here, we therefore tested the hypothesis that the use of the non-conventional long-lived positron emitter ⁶⁶Ga (T_1/2 = 9.49 h, ?⁺ = 56.5%) would permit imaging with higher contrast. ⁶⁶Ga was produced by the ⁶⁶Zn(p,n)⁶⁶Ga nuclear reaction and DFO-ZEGFR:2377 was efficiently labelled with ⁶⁶Ga with preserved binding specificity in vitro and in vivo. At 24 h after injection, [⁶⁶Ga]Ga-DFO-ZEGFR:2377 provided 3.9-fold higher tumor-to-blood ratio and 2.3-fold higher tumor-to-liver ratio than [⁶⁸Ga]Ga-DFO-ZEGFR:2377 at 3 h after injection. At the same time point, [⁶⁶Ga]Ga-DFO-ZEGFR:2377 provided 1.8-fold higher tumor-to-blood ratio, 3-fold higher tumor-to-liver ratio, 1.9-fold higher tumor-to-muscle ratio and 2.3-fold higher tumor-to-bone ratio than [⁸⁹Zr]Zr-DFO-ZEGFR:2377. Biodistribution data were confirmed by whole body PET combined with magnetic resonance imaging (PET/MRI). The use of the positron emitter ⁶⁶Ga for labelling of DFO-ZEGFR:2377 permits PET imaging of EGFR expression at 24 h after injection and improves imaging contrast.

SUBMITTER: Oroujeni M

PROVIDER: S-EPMC7926986 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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The Use of a Non-Conventional Long-Lived Gallium Radioisotope <sup>66</sup>Ga Improves Imaging Contrast of EGFR Expression in Malignant Tumours Using DFO-ZEGFR:2377 Affibody Molecule.

Oroujeni Maryam M Xu Tianqi T Gagnon Katherine K Rinne Sara S SS Weis Jan J Garousi Javad J Andersson Ken G KG Löfblom John J Orlova Anna A Tolmachev Vladimir V

Pharmaceutics 20210223 2

Epidermal growth factor receptor (EGFR) is overexpressed in many malignancies. EGFR-targeted therapy extends survival of patients with disseminated cancers. Radionuclide molecular imaging of EGFR expression would make EGFR-directed treatment more personalized and therefore more efficient. A previous study demonstrated that affibody molecule [<sup>68</sup>Ga]Ga-DFO-ZEGFR:2377 permits specific positron-emission tomography (PET) imaging of EGFR expression in xenografts at 3 h after injection. We an ...[more]

PMID: 33672373

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Project description:ObjectiveTo evaluate if a deep learning model can be used to characterise breast cancers on contrast-enhanced spectral mammography (CESM).MethodsThis retrospective mono-centric study included biopsy-proven invasive cancers with an enhancement on CESM. CESM images include low-energy images (LE) comparable to digital mammography and dual-energy subtracted images (DES) showing tumour angiogenesis. For each lesion, histologic type, tumour grade, estrogen receptor (ER) status, progesterone receptor (PR) status, HER-2 status, Ki-67 proliferation index, and the size of the invasive tumour were retrieved. The deep learning model used was a CheXNet-based model fine-tuned on CESM dataset. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated for the different models: images by images and then by majority voting combining all the incidences for one tumour.ResultsIn total, 447 invasive breast cancers detected on CESM with pathological evidence, in 389 patients, which represented 2460 images analysed, were included. Concerning the ER, the deep learning model on the DES images had an AUC of 0.83 with the image-by-image analysis and of 0.85 for the majority voting. For the triple-negative analysis, a high AUC was observable for all models, in particularity for the model on LE images with an AUC of 0.90 for the image-by-image analysis and 0.91 for the majority voting. The AUC for the other histoprognostic factors was lower.ConclusionDeep learning analysis on CESM has the potential to determine histoprognostic tumours makers, notably estrogen receptor status, and triple-negative receptor status.Key points• A deep learning model developed for chest radiography was adapted by fine-tuning to be used on contrast-enhanced spectral mammography. • The adapted models allowed to determine for invasive breast cancers the status of estrogen receptors and triple-negative receptors. • Such models applied to contrast-enhanced spectral mammography could provide rapid prognostic and predictive information.

Project description:UnlabelledEpidermal growth factor receptor (EGFR) is often overexpressed in a variety of human cancers, and its expression is associated with poor prognosis for many cancer types. However, an accurate technique to noninvasively image EGFR expression in vivo is not available in the clinical setting. In this research, an Affibody analog, anti-EGFR Ac-Cys-Z(EGFR:1907), was successfully site-specifically (18)F-labeled for PET of EGFR expression.MethodsThe prosthetic group N-[2-(4-(18)F-fluorobenzamido) ethyl] maleimide ((18)F-FBEM) was conjugated to Ac-Cys-Z(EGFR:1907) under mild conditions (pH 7) to produce the probe (18)F-FBEM-Cys-Z(EGFR:1907). The binding affinity and specificity tests of (18)F-FBEM-Cys-Z(EGFR:1907) to EGFR were conducted using A431 cancer cells. Small-animal PET and biodistribution studies were conducted on various mice tumor xenograft models with EGFR overexpression (6 types) after injection of approximately 2.0 MBq of (18)F-FBEM-Cys-Z(EGFR:1907) with or without coinjection of unlabeled Ac-Cys-Z(EGFR:1907) for up to 3 h after injection. A correlation study between (18)F-FBEM-Cys-Z(EGFR:1907) small- animal PET quantification and ex vivo Western blot analysis of tumor EGFR expression was conducted in those 6 types of tumor models.Results(18)F-FBEM-Cys-Z(EGFR:1907) binds to EGFR with low nanomolar affinity (37 nM) in A431 cells. (18)F-FBEM-Cys-Z(EGFR:1907) rapidly accumulated in the tumor and cleared from most of the normal organs except the liver and kidneys at 3 h after injection, allowing excellent tumor-to-normal tissue contrast to be obtained. In the A431 tumor xenograft model, coinjection of the PET probe with 45 μg of Ac-Cys-Z(EGFR:1907) was able to improve the tumor uptake (3.9 vs. 8.1 percentage of the injected radioactive dose per gram of tissue, at 3 h after injection) and tumor imaging contrast, whereas coinjection with 500 μg of Ac-Cys-Z(EGFR:1907) successfully blocked the tumor uptake significantly (8.1 vs. 1.0 percentage of the injected radioactive dose per gram of tissue, at 3 h after injection, 88% inhibition, P < 0.05). Moderate correlation was found between the tumor tracer uptake at 3 h after injection quantified by PET and EGFR expression levels measured by Western blot assay (P = 0.007, R = 0.59).Conclusion(18)F-FBEM-Cys-Z(EGFR:1907) is a novel protein scaffold-based PET probe for imaging EGFR overexpression of tumors, and its ability to differentiate tumors with high and low EGFR expression in vivo holds promise for future clinical translation.

Dataset Information

The Use of a Non-Conventional Long-Lived Gallium Radioisotope ⁶⁶Ga Improves Imaging Contrast of EGFR Expression in Malignant Tumours Using DFO-ZEGFR:2377 Affibody Molecule.

Publications

The Use of a Non-Conventional Long-Lived Gallium Radioisotope <sup>66</sup>Ga Improves Imaging Contrast of EGFR Expression in Malignant Tumours Using DFO-ZEGFR:2377 Affibody Molecule.

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Dataset Information

The Use of a Non-Conventional Long-Lived Gallium Radioisotope 66Ga Improves Imaging Contrast of EGFR Expression in Malignant Tumours Using DFO-ZEGFR:2377 Affibody Molecule.

Publications

The Use of a Non-Conventional Long-Lived Gallium Radioisotope <sup>66</sup>Ga Improves Imaging Contrast of EGFR Expression in Malignant Tumours Using DFO-ZEGFR:2377 Affibody Molecule.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

The Use of a Non-Conventional Long-Lived Gallium Radioisotope ⁶⁶Ga Improves Imaging Contrast of EGFR Expression in Malignant Tumours Using DFO-ZEGFR:2377 Affibody Molecule.