Amyloid-like aggregation of proteins is induced by short amyloidogenic sequence segments within a specific protein sequence resulting in self-assembly into β-sheets. We recently validated a technology platform in which synthetic amyloid peptides ("Pept-ins") containing a specific aggregation-prone region (APR) are used to induce specific functional knockdown of the target protein from which the APR was derived, including bacterial, viral, and mammalian cell proteins. In this work, we investigated if Pept-ins can be used as vector probes for Positron Emission Tomography (PET) imaging of intracellular targets. The radiolabeled Pept-ins [Ga]Ga-NODAGA-PEG-vascin (targeting VEGFR2) and [Ga]Ga-NODAGA-PEG-P2 (targeting ) were evaluated as PET probes. The Pept-in based radiotracers were cross-validated in a murine tumor and muscle infection model, respectively, and were found to combine target specificity with favorable pharmacokinetics. When the amyloidogenicity of the interacting region of the peptide is suppressed by mutation, cellular uptake and accumulation are abolished, highlighting the importance of the specific design of synthetic Pept-ins. The ubiquity of target-specific amyloidogenic sequence segments in natural proteins, the straightforward sequence-based design of the Pept-in probes, and their spontaneous internalization by cells suggest that Pept-ins may constitute a generic platform for PET imaging of intracellular targets.
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http://dx.doi.org/10.1021/acs.bioconjchem.1c00369 | DOI Listing |
Mol Pharm
December 2024
Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.
Fibroblast activation protein inhibitors (FAPIs) labeled with gallium-68 and lutetium-177 show potential for use in the diagnosis and treatment of various cancers expressing FAP. However, Lu-labeled FAPIs often exhibit short tumor retention time, limiting their therapeutic applications. To improve tumor retention, we synthesized three radiolabeled dimeric FAPIs, [F], [Cu], and [Ga].
View Article and Find Full Text PDFFront Med (Lausanne)
December 2024
Department of Physics, Faculty of Science, Minia University, Minia, Egypt.
Front Endocrinol (Lausanne)
December 2024
One Health Research Group, Universidad de las Americas, Quito, Ecuador.
Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors derived from chromaffin cells, with 80-85% originating in the adrenal medulla and 15-20% from extra-adrenal chromaffin tissues (paragangliomas). Approximately 30-40% of PPGLs have a hereditary component, making them one of the most genetically predisposed tumor types. Recent advances in genetic research have classified PPGLs into three molecular clusters: pseudohypoxia-related, kinase-signaling, and -signaling pathway variants.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Background: The aim of this study is to develop deep learning models based on F-fluorodeoxyglucose positron emission tomography/computed tomographic (F-FDG PET/CT) images for predicting individual epidermal growth factor receptor () mutation status in lung adenocarcinoma (LUAD).
Methods: We enrolled 430 patients with non-small-cell lung cancer from two institutions in this study. The advanced Inception V3 model to predict EGFR mutations based on PET/CT images and developed CT, PET, and PET + CT models was used.
Front Oncol
December 2024
Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China.
Objectives: The accurate assessment of lymph node metastasis (LNM) can facilitate clinical decision-making on radiotherapy or radical hysterectomy (RH) in cervical adenocarcinoma (AC)/adenosquamous carcinoma (ASC). This study aims to develop a deep learning radiomics nomogram (DLRN) to preoperatively evaluate LNM in cervical AC/ASC.
Materials And Methods: A total of 652 patients from a multicenter were enrolled and randomly allocated into primary, internal, and external validation cohorts.
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