Clinical implications of circulating cell-free DNA quantification and metabolic tumor burden in advanced non-small cell lung cancer

Abstract

Objectives: This study unravels the significance of cell-free DNA (cfDNA) quantification as a promising measure of the biological behavior/aggressiveness of tumors. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) measured by positron emission tomography/computed tomography scan enable a precise assessment of metabolic tumor burden. However, their clinical implications in identifying patients who need more aggressive treatment in advanced non-small cell lung cancer (NSCLC) are not fully understood. Materials and methods: In the current prospective trial, we analyzed 101 newly diagnosed advanced NSCLC (stage III-IV) patients with measurable baseline MTV, TLG, and cfDNA quantification. The best cut-offs for cfDNA levels, MTV, and TLG to predict progression-free survival and overall survival were determined using X-tile analysis. Results: There were significant positive correlations between cfDNA and MTV (r = 0.488, p < 0.001) and between cfDNA and TLG (r = 0.554, p < 0.001). High-cfDNA levels and high-MTV/TLG negatively correlated with overall survival (OS) (all p < 0.001). Patients with high-MTV showed similar median OS irrespective of their cfDNA levels (low-cfDNA vs. high-cfDNA = 9.2 vs 6.6 months; p > 0.05). However, patients with low-MTV and low-cfDNA levels showed longer OS than those with low-MTV and high-cfDNA levels (low-cfDNA vs. high-cfDNA = 49.3 vs 11.5 months; p < 0.001). The patient group with low-TLG also showed similar trends. The cfDNA level was an independent prognostic factor for OS by Cox-proportional hazard analysis. Conclusion: Although the patients with high metabolic tumor burden had a poor prognosis, regardless of the biological behavior/aggressiveness of the tumor, patients with low metabolic tumor burden and high cfDNA levels showed a poor prognosis. Taken together, this study indicates a stronger prognostic value of baseline cfDNA levels in identifying patients with advanced NSCLC and personalizing their treatment strategies for better survival.