Association between cigarette smoking history, metabolic phenotypes, and EGFR mutation status in patients with non-small cell lung cancer

Background: Cigarette smoking exerts a significant impact on metabolic phenotypes and epidermal growth factor receptor (EGFR) mutation status; however, their correlation remains insufficiently established. Therefore, the aim of this study was to investigate the association between cigarette smoking history, metabolic phenotypes, and EGFR mutation status in patients with non-small cell lung cancer (NSCLC).

Methods: We retrospectively analyzed 198 consecutive patients with NSCLC who underwent ¹⁸F-fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) before treatment and were tested for EGFR mutation status between September 2019 and March 2022. Metabolic phenotypes, including the maximum standardized uptake value (SUVmax) of the primary tumors (pSUVmax), metastatic lymph nodes (nSUVmax), and distant metastases (mSUVmax) were assessed. Patients were classified into never-smokers and smokers based on detailed smoking history. The correlations between smoking status, metabolic parameters, and EGFR mutation status were evaluated in patients with NSCLC.

Results: We observed EGFR mutations in 73 (60.3%) of 121 never-smokers and 18 (23.4%) of 77 smokers (P<0.001). EGFR-mutant NSCLC had a lower pSUVmax than that of EGFR wild-type (WT; 8.9±4.5 vs. 12.7±6.9, P<0.001). Smokers had a higher pSUVmax than never-smokers (12.5±6.4 vs. 9.9±5.9, P=0.004). With the increase of cumulative smoking dose, the pSUVmax increased significantly (r=0.198, P=0.005). There was no significant difference between nSUVmax and mSUVmax in patients with or without EGFR mutation and smoking history. Cumulative smoking dose, pSUVmax, and their combination predicted EGFR mutation status with areas under the receiver operating characteristic (ROC) curves (AUCs) 0.688, 0.673, and 0.753, respectively.

Conclusions: Our findings indicate that cigarette smoking may be one of the triggers for increased pSUVmax and decreased EGFR mutations, further suggesting that EGFR mutations are associated with low pSUVmax, which may guide clinicians in risk stratification and treatment strategy selection for patients with NSCLC.