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Erschienen in:
01.11.2014 | Original Article
Role of [18F]FDG PET in prediction of KRAS and EGFR mutation status in patients with advanced non-small-cell lung cancer
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 11/2014
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Purpose
The tumour molecular profile predicts the activity of epidermal growth factor receptor (EGFR) inhibitors in non-small-cell lung cancer (NSCLC). However, tissue availability and tumour heterogeneity limit its assessment. We evaluated whether [18F]FDG PET might help predict KRAS and EFGR mutation status in NSCLC.
Methods
Between January 2005 and October 2011, 340 NSCLC patients were tested for KRAS and EGFR mutation status. We identified patients with stage III and IV disease who had undergone [18F]FDG PET/CT scanning for initial staging. SUVpeak, SUVmax and SUVmean of the single hottest tumour lesions were calculated, and their association with KRAS and EGFR mutation status was assessed. A receiver operator characteristic (ROC) curve analysis and a multivariate analysis (including SUVmean, gender, age and AJCC stage) were performed to identify the potential value of [18F]FDG PET/CT for predicting KRAS mutation.
Results
From 102 patients staged using [18F]FDG PET/CT, 28 (27 %) had KRAS mutation (KRAS+), 22 (22 %) had EGFR mutation (EGFR+) and 52 (51 %) had wild-type KRAS and EGFR profiles (WT). KRAS+ patients showed significantly higher [18F]FDG uptake than EGFR+ and WT patients (SUVmean 9.5, 5.7 and 6.6, respectively; p < 0.001). No significant differences were observed in [18F]FDG uptake between EGFR+ patients and WT patients. ROC curve analysis for KRAS mutation status discrimination yielded an area under the curve of 0.740 for SUVmean (p < 0.001). The multivariate analysis showed a sensitivity and specificity of 78.6 % and 62.2 %, respectively, and the AUC was 0.773.
Conclusion
NSCLC patients with tumours harbouring KRAS mutations showed significantly higher [18F]FDG uptake than WT patients, as assessed in terms of SUVpeak, SUVmax and SUVmean. A multivariate model based on age, gender, AJCC stage and SUVmean might be used as a predictive marker of KRAS mutation status in patients with stage III or IV NSCLC.