Litcius/Paper detail

Pretreatment tumor-related leukocytosis misleads positron emission tomography-computed tomography during lymph node staging in gynecological malignancies

Seiji Mabuchi, Naoko Komura, Tomoyuki Sasano, Kotaro Shimura, Eriko Yokoi, Katsumi Kozasa, Hiromasa Kuroda, Ryoko Takahashi, Mahiru Kawano, Yuri Matsumoto, Hiroki Kato, Jun Hatazawa, Tadashi Kimura

2020Nature Communications34 citationsDOIOpen Access PDF

Abstract

The accuracy of fluorine-18-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG-PET/CT) can be influenced by the increased glycolytic activity of inflammatory lesions. Here, using clinical data obtained from gynecological cancer patients, tumor samples and animal models, we investigate the impact of pretreatment tumor-related leukocytosis (TRL) on the diagnostic performance of 18F-FDG-PET/CT in detecting pelvic and paraaortic lymph node metastasis. We demonstrate that pretreatment TRL misleads 18F-FDG-PET/CT during lymph node staging in gynecological malignancies. In the mechanistic investigations, we show that the false-positive 18F-FDG-PET/CT result for detecting nodal metastasis can be reproduced in animal models of TRL-positive cancer bearing G-CSF expressing cervical cancer cells. We also show that increased 18F-FDG uptake in non-metastatic nodes can be explained by the MDSC-mediated premetastatic niche formation in which proinflammatory factors, such as S100A8 or S100A9, are abundantly expressed. Together, our results suggest that the MDSC-mediated premetastatic niche created in the lymph node of TRL-positive patients misleads 18F-FDG-PET/CT for detecting nodal metastasis.

Topics & Concepts

Positron emission tomographyLeukocytosisMedicineLymph nodeMetastasisCancerRadiologyNuclear medicinePathologyInternal medicineS100 Proteins and AnnexinsRadiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and Applications