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.
This prospective trial aimed to investigate whether tumor‐specific cKIT and PDGFRA mutations can be detected and quantified in circulating tumor (ct)DNA in patients with active GIST, and whether detection indicates disease activity. We included 25 patients with active disease and cKIT or PDGFRA mutations detected in tissue. Mutant ctDNA was detected in the peripheral blood plasma using allele‐specific ligation (L‐)PCR and droplet digital (d)PCR. CtDNA harboring tumor‐specific cKIT or PDGFRA mutations was detected at least once in 16 out of 25 patients using L‐PCR (64%) and in 20 out of 25 patients with dPCR (80%). Using dPCR, the absolute numbers of ctDNA fragments (DNA copies/ml) and the mutant allele frequency (MAF; in percent of wild‐type control) strongly correlated with tumor size expressed as RECIST1.1 sum of diameter (SOD) in mm (ρ = 0.3719 and 0.408, respectively, p < 0.0001) and response status (ρ = 0.3939 and 0.392, respectively, p < 0.0001 and p < 0.001). Specificity of dPCR for detection of progression was 79.2% with a sensitivity of 55.2% and dPCR discriminated CR from active disease with a specificity of 96% and s sensitivity of 44.7%. With L‐PCR, correlations of MAF with tumor size and response status were less prominent. Serial ctDNA measurement reflected individual disease courses over time. Targeted panel sequencing of four patients detected additional driver mutations in all cases and secondary resistance mutations in two cases. Thus, ctDNA indicates disease activity in patients with GIST and should be incorporated as companion biomarker in future prospective trials.
PURPOSE We evaluated circulating tumor DNA (ctDNA) for detecting tumor burden in melanoma and examined whether early changes in the number of ctDNA copies predict response to treatment. PATIENTS AND METHODS We included 12 patients with stage III and 50 patients with stage IV melanoma with BRAF exon 15 or NRAS exon 3 mutations in tumor tissue. We used droplet digital polymerase chain reaction to retrospectively analyze serial plasma samples for mutation-positive ctDNA. RESULTS Matched plasma and serum samples were positive for ctDNA, lactate dehydrogenase, and S100 in 113 (45.8%), 108 (43.7%; not significant), and 58 (23.5%; P < .0001) of 247 samples from 50 patients with stage IV melanoma, and in 17 (63%), eight (29.6%; P = .014), and five (18.5%; P < .0001) of 27 samples from 12 patients with stage III melanoma. The number of mutant ctDNA copies correlated with concentrations of lactate dehydrogenase ( r = 0.50) and S100 ( r = 0.64), tumor volume ( r2 = 0.58), and tumor metabolic activity ( r2 = 0.83). Within 30 days before surgery, initiation of treatment, or change in treatment, ctDNA, LDH, and S100 were positive in 76.8%, 53.6% ( P = .01), and 46.4% ( P < .001) of patients, respectively. In patients with stage III or IV melanoma, early changes in ctDNA within 1 month after initiation of treatment correctly predicted RECIST response categories in 19 of 20 patients. Detectable ctDNA within 30 days after surgery or initiation of systemic treatment predicted inferior progression-free survival in patients with stage III disease ( P = .018). In patients with stage IV disease, 10 or more copies of ctDNA per mL at first follow-up indicated shorter progression-free survival (3.8 v 9 months; hazard ratio, 4.05; 95% CI, 1.56 to 10.53). CONCLUSION ctDNA indicated active tumor and was an adverse prognostic marker for tumor progression. Dynamic changes in ctDNA allowed prediction of response early after initiation of treatment. These data support the use of ctDNA to guide treatment in melanoma.
Background Novel biomarkers and molecular monitoring tools hold potential to improve outcome for patients following resection of pancreatic ductal adenocarcinoma (PDAC). We hypothesized that the combined longitudinal analysis of mutated cell-free plasma KRAS (cfKRASmut) and CA 19–9 during adjuvant treatment and follow-up might more accurately predict disease course than hitherto available parameters. Methods Between 07/2015 and 10/2018, we collected 134 plasma samples from 25 patients after R0/R1-resection of PDAC during adjuvant chemotherapy and post-treatment surveillance at our institution. Highly sensitive discriminatory multi-target ddPCR assays were employed to screen plasma samples for cfKRASmut. cfKRASmut and CA 19–9 dynamics were correlated with recurrence-free survival (RFS) and overall survival (OS). Patients were followed-up until 01/2020. Results Out of 25 enrolled patients, 76% had undergone R0 resection and 48% of resected PDACs were pN0. 17/25 (68%) of patients underwent adjuvant chemotherapy. Median follow-up was 22.0 months, with 19 out of 25 (76%) patients relapsing during study period. Median RFS was 10.0 months, median OS was 22.0 months. Out of clinicopathologic variables, only postoperative CA 19–9 levels and administration of adjuvant chemotherapy correlated with survival endpoints. cfKRASmut. was detected in 12/25 (48%) of patients, and detection of high levels inversely correlated with survival endpoint. Integration of cfKRASmut and CA 19–9 levels outperformed either individual marker. cfKRASmut outperformed CA 19–9 as dynamic marker since increase during adjuvant chemotherapy and follow-up was highly predictive of early relapse and poor OS. Conclusions Integrated analysis of cfKRASmut and CA 19–9 levels is a promising approach for molecular monitoring of patients following resection of PDAC. Larger prospective studies are needed to further develop this approach and dissect each marker’s specific potential.
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.
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