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Utilizing Monocarboxylate Transporter 1-Mediated Blood-Brain Barrier Penetration for Glioblastoma Positron Emission Tomography Imaging with 6-[18F]Fluoronicotinic Acid

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Abstract

Glioblastoma is the most malignant brain tumor in adults, and its prognosis remains dismal. The blood–brain barrier impedes the effectiveness of many drugs, which are otherwise effective for cancer treatment. Monocarboxylate transporter 1 (MCT1) is expressed on endothelial and glioblastoma cells. Our approach aims to leverage MCT1 to transport theranostic agents across the blood–brain barrier. In this context, we present herein the application of fluorine-18-labeled nicotinic acid (denoted as [18F]FNA) for glioblastoma imaging using positron emission tomography (PET). An intracranial mouse model of human glioblastoma was prepared by using patient-derived BT12 cells. PET imaging, ex vivo biodistribution, brain tissue autoradiography, and tumor and tissue uptake kinetic analyses were performed. Additionally, the ligand–target interaction was studied using in silico modeling. The xenografted glioblastomas were distinctly visualized in all 18 mice with a mean standardized uptake value of 0.92 ± 0.11 and tumor-to-brain ratio of 1.66 ± 0.17. The tumor uptake of intravenously administered [18F]FNA decreased by 76% on average when MCT1 was inhibited, whereas preadministration of 60 mg/kg niacin significantly enhanced [18F]FNA tumor uptake. The G protein-coupled receptor GPR109A is a high-affinity receptor for niacin (nicotinic acid). In silico simulations indicated that both niacin and fluorinated nicotinic acid (FNA) interact with the GPR109A receptor in a similar manner. In the presence of a GPR109A inhibitor in in vivo experiments, the tumor residence of [18F]FNA was extended. [18F]FNA has demonstrated its potential for PET imaging in a clinically relevant orthotopic glioblastoma model, and MCT1 plays a crucial role in [18F]FNA transport. The results pave the way for the development of niacin-derived theranostics for glioblastoma care.
Original languageEnglish
Pages (from-to)4819-4830
Number of pages12
JournalMolecular Pharmaceutics
Volume22
Issue number8
DOIs
Publication statusPublished - 4 Aug 2025
MoE publication typeA1 Journal article-refereed

Funding

We thank the research support from the Finnish Cancer Foundation, Sigrid Jusélius Foundation, Finnish Cultural Foundation, Research Council of Finland (#368560, #350117), Turku University Foundation, and State Research Funding of Turku University Hospital (#11009), and Tampere Tuberculosis Foundation. This research was partially supported by the Research Council of Finland’s Flagship InFLAMES, and funding decision numbers were 337531, 337530, 359346, and 357910. The Histology facility at the University of Turku performed the H&E staining. Digitization of tissue staining was performed using a 3DHISTECH Pannoramic 250 FLASH II slide scanner at the Genome Biology Unit, which is supported by HiLIFE, the Faculty of Medicine at the University of Helsinki, and Biocenter Finland. The authors thank Aake Honkaniemi, Jesse Ponkamo, David Ekwe, and Nelson Nwaenie from Turku PET Centre for technical assistance in animal PET imaging, and the Carimas image analysis software development team at the Turku PET Centre. We also thank the bioinformatics (J. V. Lehtonen) and structural biology (FINStruct) infrastructure support from Biocenter Finland and CSC IT Center for Science for the computational infrastructure support at the Structural Bioinformatics Laboratory, Åbo Akademi University. The Histology facility at the University of Turku performed the H&E staining. Digitization of tissue staining was performed using a 3DHISTECH Pannoramic 250 FLASH II slide scanner at the Genome Biology Unit, which is supported by HiLIFE, the Faculty of Medicine at the University of Helsinki, and Biocenter Finland. The authors thank Aake Honkaniemi, Jesse Ponkamo, David Ekwe, and Nelson Nwaenie from Turku PET Centre for technical assistance in animal PET imaging, and the Carimas image analysis software development team at the Turku PET Centre. We also thank the bioinformatics (J. V. Lehtonen) and structural biology (FINStruct) infrastructure support from Biocenter Finland and CSC IT Center for Science for the computational infrastructure support at the Structural Bioinformatics Laboratory, Åbo Akademi University.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • G protein-coupledreceptor GPR109A
  • Fluorine-18
  • Glioblastoma
  • Monocarboxylate transporter 1
  • Niacin
  • Nicotinic acid

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