Development of Highly Sensitive Digital Droplet PCR for Detection of cKIT Mutations in Circulating Free DNA That Mediate Resistance to TKI Treatment for Gastrointestinal Stromal Tumor (GIST).

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.

Early assessment of circulating tumor DNA after curative-intent resection predicts tumor recurrence in early-stage and locally advanced non-small-cell lung cancer.

Circulating tumor DNA (ctDNA) has demonstrated great potential as a noninvasive biomarker to assess minimal residual disease (MRD) and profile tumor genotypes in patients with non-small-cell lung cancer (NSCLC). However, little is known about its dynamics during and after tumor resection, or its potential for predicting clinical outcomes. Here, we applied a targeted-capture high-throughput sequencing approach to profile ctDNA at various disease milestones and assessed its predictive value in patients with early-stage and locally advanced NSCLC. We prospectively enrolled 33 consecutive patients with stage IA to IIIB NSCLC undergoing curative-intent tumor resection (median follow-up: 26.2 months). From 21 patients, we serially collected 96 plasma samples before surgery, during surgery, 1-2 weeks postsurgery, and during follow-up. Deep next-generation sequencing using unique molecular identifiers was performed to identify and quantify tumor-specific mutations in ctDNA. Twelve patients (57%) had detectable mutations in ctDNA before tumor resection. Both ctDNA detection rates and ctDNA concentrations were significantly higher in plasma obtained during surgery compared with presurgical specimens (57% versus 19% ctDNA detection rate, and 12.47 versus 6.64 ng·mL-1 , respectively). Four patients (19%) remained ctDNA-positive at 1-2 weeks after surgery, with all of them (100%) experiencing disease progression at later time points. In contrast, only 4 out of 12 ctDNA-negative patients (33%) after surgery experienced relapse during follow-up. Positive ctDNA in early postoperative plasma samples was associated with shorter progression-free survival (P = 0.013) and overall survival (P = 0.004). Our findings suggest that, in early-stage and locally advanced NSCLC, intraoperative plasma sampling results in high ctDNA detection rates and that ctDNA positivity early after resection identifies patients at risk for relapse.

Personalized Treatment Selection and Disease Monitoring Using Circulating Tumor DNA Profiling in Real-World Cancer Patient Management.

BACKGROUND: Circulating tumor DNA (ctDNA) in the blood plasma of cancer patients is an emerging biomarker used across oncology, facilitating noninvasive disease monitoring and genetic profiling at various disease milestones. Digital droplet PCR (ddPCR) technologies have demonstrated high sensitivity and specificity for robust ctDNA detection at relatively low costs. Yet, their value for ctDNA-based management of a broad population of cancer patients beyond clinical trials remains elusive. METHODS: We developed mutation-specific ddPCR assays that were optimized for their use in real-world cancer management, covering 12 genetic aberrations in common cancer genes, such as EGFR, BRAF, KIT, KRAS, and NRAS. We assessed the limit of detection (LOD) and the limit of blank (LOB) for each assay and validated their performance for ctDNA detection using matched tumor sequencing. RESULTS: We applied our custom ddPCR assays to 352 plasma samples from 96 patients with solid tumors. Mutation detection in plasma was highly concordant with tumor sequencing, demonstrating high sensitivity and specificity across all assays. In 20 cases, radiographic cancer progression was mirrored by an increase of ctDNA concentrations or the occurrence of novel mutations in plasma. Moreover, ctDNA profiling at diagnosis and during disease progression reflected personalized treatment selection through the identification of actionable gene targets in 20 cases. CONCLUSION: Collectively, our work highlights the potential of ctDNA assessment by sensitive ddPCR for accurate disease monitoring, robust identification of resistance mutations, and upfront treatment selection in patients with solid tumors. We envision an increasing future role for ctDNA profiling within personalized cancer management in daily clinical routine.