Evidence map›Paper›PMID 28039488›Full record

ArticleOncotarget2017

uPAR-targeted optical near-infrared (NIR) fluorescence imaging and PET for image-guided surgery in head and neck cancer: proof-of-concept in orthotopic xenograft model.

Anders Christensen, Karina Juhl, Morten Persson, Birgitte Wittenborg Charabi, Jann Mortensen, Katalin Kiss, Giedrius Lelkaitis, Niclas Rubek, Christian von Buchwald, Andreas Kjær

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 56 citations in OpenAlex.

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  2. Fluorescent Molecular Imaging Can Improve Intraoperative Sentinel Margin Detection in Oral Squamous Cell Carcinoma.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022
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  12. A phase I study of a PARP1-targeted topical fluorophore for the detection of oral cancer.European journal of nuclear medicine and molecular imaging · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Anders ChristensenDepartment of Otolaryngology, Head & Neck Surgery and Audiology, Rigshospitalet, Copenhagen University Hospital, Denmark.
Karina JuhlDepartment of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Denmark.
Morten PerssonDepartment of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Denmark.
Birgitte Wittenborg CharabiDepartment of Otolaryngology, Head & Neck Surgery and Audiology, Rigshospitalet, Copenhagen University Hospital, Denmark.
Jann MortensenDepartment of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Denmark.
Katalin KissDepartment of Pathology, Rigshospitalet, Copenhagen University Hospital, Denmark.
Giedrius LelkaitisDepartment of Pathology, Rigshospitalet, Copenhagen University Hospital, Denmark.
Niclas RubekDepartment of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Denmark.
Christian von BuchwaldDepartment of Otolaryngology, Head & Neck Surgery and Audiology, Rigshospitalet, Copenhagen University Hospital, Denmark.
Andreas KjærDepartment of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Denmark.
Rigshospitalet · DKCopenhagen University Hospital · DKUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeUrokinase-like Plasminogen Activator Receptor (uPAR) is overexpressed in a variety of carcinoma types, and therefore represents an attractive imaging target. The aim of this study was to assess the feasibility of two uPAR-targeted probes for PET and fluorescence tumor imaging in a human xenograft tongue cancer model. EXPERIMENTAL DESIGN AND

resultsTumor growth of tongue cancer was monitored by bioluminescence imaging (BLI) and MRI. Either ICG-Glu-Glu-AE105 (fluorescent agent) or 64Cu-DOTA-AE105 (PET agent) was injected systemically, and fluorescence imaging or PET/CT imaging was performed. Tissue was collected for micro-fluorescence imaging and histology. A clear fluorescent signal was detected in the primary tumor with a mean in vivo tumor-to-background ratio of 2.5. Real-time fluorescence-guided tumor resection was possible, and sub-millimeter tumor deposits could be localized. Histological analysis showed co-localization of the fluorescent signal, uPAR expression and tumor deposits. In addition, the feasibility of uPAR-guided robotic cancer surgery was demonstrated. Also, uPAR-PET imaging showed a clear and localized signal in the tongue tumors.

conclusionsThis study demonstrated the feasibility of combining two uPAR-targeted probes in a preclinical head and neck cancer model. The PET modality provided preoperative non-invasive tumor imaging and the optical modality allowed for real-time fluorescence-guided tumor detection and resection. Clinical translation of this platform seems promising.

Indexed as

Xenograft Model Antitumor AssaysAnimalsCarcinoma, Squamous CellCell Line, TumorFeasibility StudiesFemaleFluorescent DyesHead and Neck NeoplasmsHumansMagnetic Resonance ImagingMice, Inbred StrainsMice, NudeOptical ImagingPositron Emission Tomography Computed TomographyReceptors, Urokinase Plasminogen ActivatorReproducibility of ResultsFluorescent DyesReceptors, Urokinase Plasminogen Activatorhead and neck cancerimage-guided surgeryPETtumor margin assessmentuPAR

Identifiers

PMID28039488
PMCPMC5362495
OpenAlexW2563841765

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.