<scp>FDG‐PET SUV</scp>‐max values do not correlate with epidermal growth factor receptor mutation status in lung adenocarcinoma

Putora, Paul Martin; Früh, Martin; Müller, Joachim

doi:10.1111/resp.12083

Cited by 21 publications

(14 citation statements)

References 6 publications

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“…The results revealed that patients who harbored an EGFR mutation exhibited decreased SUV max values, and further studies revealed that the EGFR mutation alters the SUV max partially via the NOX4/ROS/GLUT1 axis. Putora et al, 2013 No association between ADC 28 SUV max 10.7 vs. 9.9 in (34) SUV max and EGFR status EGFR-positive and wild-type, respectively SUV max , maximum standardized uptake value; EGFR, epidermal growth factor receptor; ADC, adenocarcinoma; SCC, squamous cell carcinoma.…”

Section: Discussionmentioning

confidence: 99%

EGFR mutation decreases FDG uptake in non‑small cell lung cancer via the NOX4/ROS/GLUT1 axis

et al. 2018

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[ 18 F]fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)-computed tomography (CT) is a functional imaging modality based on glucose metabolism. The association between the maximum standardized uptake value (SUV max) from 18 F-FDG PET-CT scanning and epidermal growth factor receptor (EGFR) mutation status has, to the best of our knowledge, not previously been fully elucidated, and the potential mechanisms by which EGFR mutations alter FDG uptake are largely unknown. A total of 157 patients who were pathologically diagnosed with non-small cell lung cancer (NSCLC) who underwent EGFR mutation testing and PET-CT pretreatment between June 2015 and October 2017 were retrospectively analyzed. χ 2 and univariate analyses were performed to identify the contributors to EGFR mutation. The receiver operating characteristic (ROC) curve was analyzed, and the area under the curve (AUC) was calculated. Glucose transporter 1 (GLUT1) and NADPH oxidase 4 (NOX4) expression, and reactive oxygen species (ROS) activity were detected in the A549 (wild-type), PC-9 (EGFR mutation-positive, EGFR exon 19del) and NCI-H1975 (EGFR mutation-positive, combined with L858R and T790M substitution) cell lines. A total of 109 patients who met the criteria were enrolled, and 63 of those tested as EGFR mutation-positive. The SUV max values were significantly lower in patients with EGFR mutations (mean, 6.52±0.38) compared with in patients with wild-type EGFR (mean, 9.37±0.31; P<0.001). Using univariate analysis, EGFR mutation status was significantly associated with sex, smoking status, tumor histology and SUV max of the primary tumor. In the multivariate analysis, smoking status (never-smoking), histopathology (adenocarcinoma) and SUV max (≤9.91) were the statistically significant predictors of EGFR mutations. ROC curve analysis identified that the SUV max cutoff point was 9.92, for which the AUC was 0.75 (95% confidence interval, 0.68-0.83). Reverse transcription-polymerase chain reaction indicated that the GLUT1 mRNA decreased in the PC-9 and NCI-H1975 cell lines compared with the A549 cell line (0.82±0.07 and 0.72±0.04 vs. 0.98±0.04, respectively; P<0.05) and decreased ROS activity was observed in the PC-9 cell line. Furthermore, the expression of NOX4 mRNA decreased by 20% in PC-9 (P<0.01) and by 14% (P<0.05) in NCI-H1975 cells. In addition, NOX4 protein expression decreased by 13% in PC-9 and by 16% in NCI-H1975 cells (both P<0.05) compared with the A549 cell line. The SUV max could be considered to effectively predict EGFR mutation status of patients with NSCLC, and the EGFR mutation status may alter FDG uptake partially via the NOX4/ROS/GLUT1 axis.

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Section: Discussionmentioning

confidence: 99%

EGFR mutation decreases FDG uptake in non‑small cell lung cancer via the NOX4/ROS/GLUT1 axis

et al. 2018

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“…Na et al and Huang et al found a significant association between SUVmax and EGFR mutation status, although the trends between the EGFR mutant groups and wild-type groups in the two reports differed [15, 16]. Three other studies found no relationship between SUVmax and EGFR gene mutation status [19, 20, 24]. Data from previous association studies are summarized in Table 4.…”

Section: Discussionmentioning

confidence: 99%

The role of metabolic tumor volume (MTV) measured by [18F] FDG PET/CT in predicting EGFR gene mutation status in non-small cell lung cancer

et al. 2017

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Many noninvasive methods have been explored to determine the mutation status of the epidermal growth factor receptor (EGFR) gene, which is important for individualized treatment of non-small cell lung cancer (NSCLC). We evaluated whether metabolic tumor volume (MTV), a parameter measured by [18F] fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) might help predict EGFR mutation status in NSCLC. Overall, 87 patients who underwent EGFR genotyping and pretreatment PET/CT between January 2013 and September 2016 were reviewed. Clinicopathologic characteristics and metabolic parameters including MTV were evaluated. Univariate and multivariate analyses were used to assess the independent variables that predict mutation status to create prediction models. Forty-one patients (41/87) were identified as having EGFR mutations. The multivariate analysis showed that patients with lower MTV (MTV≤11.0 cm3, p=0.001) who were non-smokers (p=0.037) and had a peripheral tumor location (p=0.033) were more likely to have EGFR mutations. Prediction models using these criteria for EGFR mutation yielded a high AUC (0.805, 95% CI 0.712–0.899), which suggests that the analysis had good discrimination. In conclusion, NSCLC patients with EGFR mutations showed significantly lower MTV than patients with wild-type EGFR. Prediction models based on MTV and clinicopathologic characteristics could provide more information for the identification of EGFR mutations.

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“…Several previous PET quantitative analysis showed correlation of value of SUV max and histopathological features including tumor subtypes, Ki-67 expression, EGFR mutation and Alk rearrangement [19,20]. However, there are also some studies showing negative data to the relationship between SUV max and tumor subtypes or EGFR expression in lung cancer [21].…”

Section: Patientsmentioning

confidence: 98%

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

Choi

Cheon

et al. 2014

Nucl Med Mol Imaging

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Purpose Texture analysis on 18 F-fluorodeoxyglucose positron emission tomography ( 18 F-FDG PET) scan is a relatively new imaging analysis tool to evaluate metabolic heterogeneity. We analyzed the difference in textural characteristics between non-small cell lung carcinoma (NSCLC) subtypes, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). Methods Diagnostic 18 F-FDG PET/computed tomography (CT) scans of 30y patients (median age, 67; range, 42-88) with NSCLC (17 ADC and 13 SqCC) were retrospectively analyzed. Regions of interest were manually determined on selected transverse image containing the highest SUV value in tumors. Texture parameters were extracted by histogrambased algorithms, absolute gradient-based algorithms, runlength matrix-based algorithms, co-occurrence matrix-based algorithms, and autoregressive model-based algorithms. Twenty-four out of hundreds of texture features were selected by three algorithms: Fisher coefficient, minimization of both classification error probability and average correlation, and mutual information. Automated clustering of tumors was based on the most discriminating feature calculated by linear discriminant analysis (LDA). Each tumor subtype was determined by histopathologic examination after biopsy and surgery. Results Fifteen texture features had significant different values between ADC and SqCC. LDA with 24 automateselected texture features accurately clustered between ADC and SqCC with 0.90 linear separability. There was no high correlation between SUV max and texture parameters (|r|≤0.62). Conclusion Each subtype of NSCLC tumor has different metabolic heterogeneity. The results of this study support the potential of textural parameters on FDG PET as an imaging biomarker.

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FDG‐PET SUV‐max values do not correlate with epidermal growth factor receptor mutation status in lung adenocarcinoma

Cited by 21 publications

References 6 publications

EGFR mutation decreases FDG uptake in non‑small cell lung cancer via the NOX4/ROS/GLUT1 axis

EGFR mutation decreases FDG uptake in non‑small cell lung cancer via the NOX4/ROS/GLUT1 axis

The role of metabolic tumor volume (MTV) measured by [18F] FDG PET/CT in predicting EGFR gene mutation status in non-small cell lung cancer

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

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