Background: Mutations in cKIT or PDGFRA are found in up to 90% of patients with gastrointestinal stromal tumors (GISTs). Previously, we described the design, validation, and clinical performance of a digital droplet (dd)PCR assay panel for the detection of imatinib-sensitive cKIT and PDFGRA mutations in circulating tumor (ct)DNA. In this study, we developed and validated a set of ddPCR assays for the detection of cKIT mutations mediating resistance to cKIT kinase inhibitors in ctDNA. In addition, we cross-validated these assays using next generation sequencing (NGS). Methods: We designed and validated five new ddPCR assays to cover the most frequent cKIT mutations mediating imatinib resistance in GISTs. For the most abundant imatinib-resistance-mediating mutations in exon 17, a drop-off, probe-based assay was designed. Dilution series (of decreasing mutant (MUT) allele frequency spiked into wildtype DNA) were conducted to determine the limit of detection (LoD). Empty controls, single wildtype controls, and samples from healthy individuals were tested to assess specificity and limit of blank (LoB). For clinical validation, we measured cKIT mutations in three patients and validated results using NGS. Results: Technical validation demonstrated good analytical sensitivity, with a LoD ranging between 0.006% and 0.16% and a LoB ranging from 2.5 to 6.7 MUT fragments/mL. When the ddPCR assays were applied to three patients, the abundance of ctDNA in serial plasma samples reflected the individual disease course, detected disease activity, and indicated resistance mutations before imaging indicated progression. Digital droplet PCR showed good correlation to NGS for individual mutations, with a higher sensitivity of detection. Conclusions: This set of ddPCR assays, together with our previous set of cKIT and PDGFRA mutations assays, allows for dynamic monitoring of cKIT and PDGFRA mutations during treatment. Together with NGS, the GIST ddPCR panel will complement imaging of GISTs for early response evaluation and early detection of relapse, and thus it might facilitate personalized decision-making.
Research Areas and Centers
- Research Area: Luebeck Integrated Oncology Network (LION)
- Centers: University Cancer Center Schleswig-Holstein (UCCSH)