Monitoring pembrolizumab response in patients with metastatic non-small cell lung cancer using circulating tumour DNA and circulating tumour cells.

Background: Liquid biopsy, in the form of cell-free-DNA (cfDNA), circulating-tumour-DNA (ctDNA), and circulating tumour cells (CTCs) can be used to monitor the efficacy of systemic therapy. We investigated the predictive value of these markers in patients with advanced non-small cell lung cancer (aNSCLC) treated with pembrolizumab within a prospective phase-II maintenance study of pembrolizumab post-platinum-doublet-chemotherapy (NCT02705820).

Methods: Plasma-derived cfDNA was evaluated in 125 patients' plasma samples at baseline (t0), after 3 weeks (t1), 6 weeks (t2) and 9 weeks (t3) from 46 individuals and analysed by next-generation sequencing to identify and quantify somatic mutations. CTCs were detected in peripheral blood mononuclear cells and characterised according to programme death-ligand 1 (PD-L1) and Ki67.

Results: Patients presenting cfDNA increase at t2 had shorter progression-free survival (PFS; 2.05 vs. 6.1 months, P=0.04) and overall survival (OS; 8.35 vs. 20.0 months, P=0.004) than those with decreased cfDNA. Somatic mutations were found in 58.14% of patients in TP53, EGFR, KRAS, ALK, PI3KCA and MAP2K1 genes. Patients with >50% decrease or clearance in ctDNA from baseline to early treatment had 3.34 times lower risk for progression and improved survival outcomes (P=0.03). A high Ki67 CTC-index negatively affected PFS [hazard ratio (HR) =10.13, P=0.03] and OS (HR =6.1, P=0.01). Combining ctDNA dynamics and Ki67 was superior to any single marker in identifying patients with disease progression, with a sensitivity of 88.2% at t0 and 70% at t2 and a false-positive rate of 30.4% at t0 and 11.1% at t2.

Conclusions: Monitoring ctDNA mutation dynamics during early treatment could serve as a promising real-time predictor of response. Moreover, combining ctDNA-dynamics with Ki67 provides enhanced predictive accuracy for progression, supporting the importance of more holistic multifactorial analyses in the prediction of immunotherapy response in aNSCLC.