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

Abstract

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 18 F-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.

A Review of the Correlation Between Epidermal Growth Factor Receptor Mutation Status and 18F-FDG Metabolic Activity in Non-Small Cell Lung Cancer

“…However, opposite results could be observed that the metabolic activity of 18 F-FDG (e.g., SUV max ) in NSCLC EGFR-mutant patients was significantly higher than that of wild-type patients ( 25 , 52 – 54 ). The expression status of EGFR protein was also evaluated, and higher SUV max was positively correlated with EGFR overexpression ( 59 , 60 ).…”

Identification of EGFR mutation status in male patients with non-small-cell lung cancer: role of 18F-FDG PET/CT and serum tumor markers CYFRA21-1 and SCC-Ag

“…Liu et al showed that MTV were lower in NSCLC patients harboring EGFR mutations than in patients bearing wild-type EGFR [ 39 ]. It was found, however, conversely, that patients with NSCLC harboring EGFR mutations had significantly higher metabolic activity of 18 F-FDG (e.g., SUV max ) as compared to patients with wild-type EGFR [ 40 , 41 ]. Even no significant difference in 18 F-FDG uptake between EGFR mutant and wild-type NSCLC patients has also been reported [ 42 ].…”

Deep Radiotranscriptomics of Non-Small Cell Lung Carcinoma for Assessing Molecular and Histology Subtypes with a Data-Driven Analysis

“…In contrast, the radiotranscriptomics of EGFR did not improve on the current state-of-the-art study of Rizzo et al [ 23 ], which was based solely on semantic CT features. This can also be attributed to the imaging modality, since better and more discriminative features or biomarkers [ 66 ] have been reported in several studies [ 25 , 67 , 68 , 69 ] where the PET/CT radiomic signature with an AUC of 0.805 significantly outperformed the CT only features (AUC 0.667) in EGFR mutation status differentiation. Despite the limited number of patients for machine learning analysis, especially regarding the molecular subtype patient cohorts, the proposed radiotranscriptomic model for KRAS differentiation outperformed the model of Rizzo et al [ 23 ].…”