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Biological Significance of 18F-FDG PET/CT Maximum Standard Uptake Value for Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Patients

Authors Wang Y, Han R, Wang Q, Zheng J, Lin C, Lu C, Li L, Chen H, Jin R, He Y

Received 22 October 2020

Accepted for publication 31 December 2020

Published 3 February 2021 Volume 2021:14 Pages 347—356

DOI https://doi.org/10.2147/IJGM.S287506

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Scott Fraser


Yubo Wang,1,* Rui Han,1,* Qiushi Wang,2 Jie Zheng,1 Caiyu Lin,1 Conghua Lu,1 Li Li,1 Hengyi Chen,1 Rongbing Jin,3 Yong He1

1Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People’s Republic of China; 2Department of Pathology, Daping Hospital, Army Medical University, Chongqing, People’s Republic of China; 3Department of Nuclear Medicine, Daping Hospital, Army Medical University, Chongqing, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Yong He
Department of Respiratory Medicine, Daping Hospital, Army Medical University, 10# Changjiangzhilu Daping, Yuzhong District, Chongqing, 400042, People’s Republic of China
Tel +86-2368757791
Fax +86-2368700970
Email heyong@tmmu.edu.cn
Rongbing Jin
Department of Nuclear Medicine, Daping Hospital, Army Medical University, 10# Changjiangzhilu Daping, Yuzhong District, Chongqing, 400042, People’s Republic of China
Tel +86-2368757641
Email jinrb99@126.com

Purpose: To investigate the potential of maximum standardized uptake value (SUVmax) in predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients.
Methods: Clinical data of 311 NSCLC patients who had undergone both EGFR mutation test and 18F-FDG PET/CT scans between January 2013 and December 2017 at our hospital were retrospectively analyzed. Patients were sub-grouped by their origin of SUVmax. Univariate and multivariate analyses were performed to investigate the association between clinical factors and EGFR mutations. Receiver operating characteristic curve (ROC) analysis was performed to confirm the predictive value of clinical factors. In vitro experiments were performed to confirm the correlation between EGFR mutations and glycolysis.
Results: EGFR-mutant patients had higher SUVmax than the wild-type patients in both primary tumors and metastases. In the multivariate analysis, SUVmax, gender and histopathologic type were determined as independent predictors of EGFR mutation status for patients whose SUVmax were obtained from the primary tumors; while for patients whose SUVmax were obtained from the metastases, SUVmax, smoking status and histopathologic type were regarded as independent predictors. ROC analysis showed that SUVmax of the primary tumors (cut off > 10.92), not of the metastases, has better predictive value than other clinical factors in predicting EGFR mutation status. The predict performance was improved after combined SUVmax with other independent predictors. In addition, our in vitro experiments demonstrated that lung cancer cells with EGFR mutations have higher aerobic glycolysis level than wild-type cells.
Conclusion: SUVmax of the primary tumors has the potential to serve as a biomarker to predict EGFR mutation status in NSCLC patients.

Keywords: non-small cell lung cancer, epidermal growth factor receptor, SUVmax, receiver operating characteristic curve

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