Correlation of FDG PET/CT, tumor markers and Ki-67 index with EGFR mutation or positive ALK expression in patients with non-small cell lung cancer.

Background: Epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) are the two most common druggable targets in non-small cell lung cancer (NSCLC). To investigate whether the EGFR mutation and ALK rearrangement could be predicted by the combination of FDG avidity, tumor markers and Ki-67 Index.

Methods: A total of 168 newly diagnosed NSCLC patients who had undergone ¹⁸F-FDG PET/CT for staging were enrolled. PET/CT parameters of primary tumors including maximum standardized uptake value (pSUVmax), metabolic tumor volume (pMTV) and total lesion glycolysis (pTLG) were measured. Five serous tumor markers for lung cancer were recorded. Ki-67 labeling index was counted by immunohistochemical staining. EGFR mutation and ALK status were detected by ARMS-PCR and RT-PCR, respectively. Univariate and multivariate analyses were applied to identify the predictors of EGFR mutation and ALK positivity.

Results: EGFR mutation rate was 38.1% (64/168), which were found more frequently in female, ≤60 years old, non-smokers and adenocarcinoma patients, and were not related to lymph node involvements, distant metastases, stage and serum tumor markers. Low pSUVmax, pMTV, pTLG and Ki-67 were significantly associated with EGFR mutation. Logistic regression demonstrated that pSUVmax <6.75 and gender (female) were the independent factors affecting EGFR mutation, and the combination of them had a certain predictive value with the area under the curve of 0.784. ALK positive rate was 6.0% (10/168), all of them were adenocarcinoma patients, which were more common in non-smokers, low serum cytokeratin-19 fragment antigen (CYFRA21-1) and low Ki-67, and were not related to FDG activity. No independent factor for ALK positivity was found on Logistic regression.

Conclusions: Low pSUVmax, rather than tumor markers or Ki-67, was correlated with EGFR mutation independently, which could be integrated with gender (female) to improve the identification for EGFR mutation in NSCLC patients.