Monitoring of EGFR mutations in circulating tumor DNA of non-small cell lung cancer patients treated with EGFR inhibitors.

PURPOSE: We studied EGFR mutations in circulating tumor DNA (ctDNA) and explored their role in predicting the progression-free survival (PFS) of non-small cell lung cancer (NSCLC) patients treated with erlotinib or gefitinib. METHODS: The L858R, T790M mutations and exon 19 deletions were quantified in plasma using digital droplet polymerase chain reaction (ddPCR). The dynamics of ctDNA mutations over time and relationships with PFS were explored. RESULTS: In total, 249 plasma samples (1-13 per patient) were available from 68 NSCLC patients. The T790M and L858R or exon 19 deletion were found in the ctDNA of 49 and 56% patients, respectively. The median (range) concentration in these samples were 7.3 (5.1-3688.7), 11.7 (5.1-12,393.3) and 27.9 (5.9-2896.7) copies/mL, respectively. Using local polynomial regression, the number of copies of EGFR mutations per mL increased several months prior to progression on standard response evaluation. CONCLUSION: This change was more pronounced for the driver mutations than for the resistance mutations. In conclusion, quantification of EGFR mutations in plasma ctDNA was predictive of treatment outcomes in NSCLC patients. In particular, an increase in driver mutation copy number could predict disease progression.

Performance of four platforms for KRAS mutation detection in plasma cell-free DNA: ddPCR, Idylla, COBAS z480 and BEAMing.

Multiple platforms are commercially available for the detection of circulating cell-free tumour DNA (ctDNA) from liquid biopsies. Since platforms have different input and output variables, deciding what platform to use for a given clinical or research question can be daunting. This study aimed to provide insight in platform selection criteria by comparing four commercial platforms that detect KRAS ctDNA hotspot mutations: Bio-Rad droplet digital PCR (ddPCR), BioCartis Idylla, Roche COBAS z480 and Sysmex BEAMing. Platform sensitivities were determined using plasma samples from metastatic colorectal cancer (mCRC) patients and synthetic reference samples, thereby eliminating variability in amount of plasma analysed and ctDNA isolation methods. The prevalence of KRAS nucleotide alterations was set against platform-specific breadth of target. Platform comparisons revealed that ddPCR and BEAMing detect more KRAS mutations amongst mCRC patients than Idylla and COBAS z480. Maximum sample throughput was highest for ddPCR and COBAS z480. Total annual costs were highest for BEAMing and lowest for Idylla and ddPCR. In conclusion, when selecting a platform for detection of ctDNA hotspot mutations the desired test sensitivity, breadth of target, maximum sample throughput, and total annual costs are critical factors that should be taken into consideration. Based on the results of this study, laboratories will be able to select the optimal platform for their needs.