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.

There is an increasing demand for optimization-free multiplex assays to rapidly establish comprehensive target panels for cancer monitoring by liquid biopsy. We present the mediator probe (MP) PCR for the quantification of the seven most frequent point mutations and corresponding wild types (KRAS and BRAF) in colorectal carcinoma. Standardized parameters for the digital assay were derived using design of experiments. Without further optimization, the limit of detection (LoD) was determined through spiking experiments with synthetic mutant DNA in human genomic DNA. The limit of blank (LoB) was measured in cfDNA plasma eluates from healthy volunteers. The 2-plex and 4-plex MP ddPCR assays showed a LoB of 0 copies/mL except for 4-plex KRAS G13D (9.82 copies/mL) and 4-plex BRAF V600E (16.29 copies/mL) and allele frequencies of 0.004% ≤ LoD ≤ 0.38% with R2 ≥ 0.98. The quantification of point mutations in patient plasma eluates (18 patients) during follow-up using the 4-plex MP ddPCR showed a comparable performance to the reference assays. The presented multiplex assays need no laborious optimization, as they use the same concentrations and cycling conditions for all targets. This facilitates assay certification, allows a fast and flexible design process, and is thus easily adaptable for individual patient monitoring.

Cell-free DNA (cfDNA) has been investigated in acute graft-versus-host disease (aGvHD) following allogeneic cell transplantation (HSCT). Identifying the tissue of origin of cfDNA in patients with aGvHD is relevant particularly when a biopsy is not feasible. We investigate the cfDNA tissue of origin in patients with aGvHD using methylated gene biomarkers. Patients with liver, colon, or skin aGvHD ( n = 28) were analyzed. Liver- and colon-derived cfDNA was measured using a colon- (SESN3) and liver (PTK2B)-specific methylation marker with digital droplet PCR. A statistically significant difference ( p < 0.001) in PTK2B and SESN3 concentration was observed between patients with colon or liver GvHD and the control group. For SESN3 and PTK2B the area under the curve in the receiver-operating characteristic (ROC) space was 0.952 (95% CI, 0.888–1 p < 0.001) and 0.971 (95% CI, 0.964–1 p < 0.001), respectively. Thresholds to differentiate aGvHD from non-aGvHD in colon were 0 (sensitivity: 0.905; specificity: 0.989) and liver 1.5 (sensitivity: 0.928; specificity: 0.910). Clinical improvement of liver or colon aGvHD resulted in PTK2B and SESN3 reduced concentration. Whereas, in those patients without improvement the PTK2B and SESN3 level remained stable or increased. The PTK2B liver-specific marker and the SESN3 colon-specific marker and their longitudinal analysis might improve aGvHD detection.

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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