Radiosynthesis, Biological Evaluation, and Preclinical Study of a 68Ga-Labeled Cyclic RGD Peptide as an Early Diagnostic Agent for Overexpressed α v β 3 Integrin Receptors in Non-Small-Cell Lung Cancer.
Nazanin PiroozniaKhosrou AbdiDavood BeikiFarshad EmamiSeyed Shahriar ArabOmid SabzevariZahra Pakdin-PariziParham GeramifarPublished in: Contrast media & molecular imaging (2020)
The α v β 3 integrin receptors have high expression on proliferating growing tumor cells of different origins including non-small-cell lung cancer. RGD-containing peptides target the extracellular domain of integrin receptors. This specific targeting makes these short sequences a suitable nominee for theranostic application. DOTA-E(cRGDfK)2 was radiolabeled with 68Ga efficiently. The in vivo and in vitro stability was examined in different buffer systems. Metabolic stability was assessed in mice urine. In vitro specific binding, cellular uptake, and internalization were determined. The tumor-targeting potential of [68Ga]Ga-DOTA-E(cRGDfK)2 in a lung cancer mouse model was studied. Besides, the very early diagnostic potential of the 68Ga-labeled RGD peptide was evaluated. The acquisition and reconstruction of the PET-CT image data were also carried out. Radiochemical and radionuclide purity for [68Ga]Ga-DOTA-E(cRGDfK)2 was >%98 and >%99, respectively. Radiotracer showed high in vivo, in vitro, and metabolic stability which was determined by ITLC. The dissociation constant (K d) of [68Ga]Ga-DOTA-E(cRGDfK)2 was 15.28 nM. On average, more than 95% of the radioactivity was specific binding (internalized + surface-bound) to A549 cells. Biodistribution data showed that radiolabeled peptides were accumulated significantly in A549 tumor and excreted rapidly by the renal system. Tumor uptake peaks were at 1-hour postinjection for [68Ga]Ga-DOTA-E(cRGDfK)2. The tumor was clearly visualized in all images. [68Ga]Ga-DOTA-E(cRGDfK)2 can be used as a peptide-based imaging agent allowing very early detection of different cancers overexpressing α v β 3 integrin receptors and can be a potential candidate in clinical peptide-based imaging for lung cancer.
Keyphrases
- pet ct
- positron emission tomography
- mouse model
- pet imaging
- type diabetes
- deep learning
- machine learning
- computed tomography
- risk assessment
- photodynamic therapy
- blood pressure
- cancer therapy
- cell migration
- electronic health record
- induced apoptosis
- mesenchymal stem cells
- big data
- climate change
- drug delivery
- endoplasmic reticulum stress