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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., ctDNA profiling in plasma revealed higher levels and detection rates of ctDNA during tumor resection as compared to pretreatment time points in patients with early‐stage or locally advanced NSCLC. Moreover, patients testing positive for ctDNA immediately after tumor resection had worse clinical outcomes than patients with undetectable ctDNA. Our research highlights the role of ctDNA assessment for guiding treatment in patients with respectable NSCLC.

PURPOSE Clinical outcomes of patients with CNS lymphomas (CNSLs) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure is challenging. Furthermore, CNSL diagnosis often remains unconfirmed because of contraindications for invasive stereotactic biopsies. Therefore, improved biomarkers are needed to better stratify patients into risk groups, predict treatment response, and noninvasively identify CNSL. PATIENTS AND METHODS We explored the value of circulating tumor DNA (ctDNA) for early outcome prediction, measurable residual disease monitoring, and surgery-free CNSL identification by applying ultrasensitive targeted next-generation sequencing to a total of 306 tumor, plasma, and CSF specimens from 136 patients with brain cancers, including 92 patients with CNSL. RESULTS Before therapy, ctDNA was detectable in 78% of plasma and 100% of CSF samples. Patients with positive ctDNA in pretreatment plasma had significantly shorter progression-free survival (PFS, P < .0001, log-rank test) and overall survival (OS, P = .0001, log-rank test). In multivariate analyses including established clinical and radiographic risk factors, pretreatment plasma ctDNA concentrations were independently prognostic of clinical outcomes (PFS HR, 1.4; 95% CI, 1.0 to 1.9; P = .03; OS HR, 1.6; 95% CI, 1.1 to 2.2; P = .006). Moreover, measurable residual disease detection by plasma ctDNA monitoring during treatment identified patients with particularly poor prognosis following curative-intent immunochemotherapy (PFS, P = .0002; OS, P = .004, log-rank test). Finally, we developed a proof-of-principle machine learning approach for biopsy-free CNSL identification from ctDNA, showing sensitivities of 59% (CSF) and 25% (plasma) with high positive predictive value. CONCLUSION We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings highlight the role of ctDNA as a noninvasive biomarker and its potential value for personalized risk stratification and treatment guidance in patients with CNSL. [Media: see text]

Proteases are known to promote or impair breast cancer progression and metastasis. However, while a small number of the 588 human and 672 murine protease genes have been extensively studied, others were neglected. For an unbiased functional analysis of all genome-encoded proteases, i.e., the degradome, in breast cancer cell growth, we applied an inducible RNA interference library for protease-focused genetic screens. Importantly, these functional screens were performed in two phenotypically different murine breast cancer cell lines, including one stem cell-like cell line that showed phenotypic plasticity under changed nutrient and oxygen availability. Our unbiased genetic screens identified 252 protease genes involved in breast cancer cell growth that were further restricted to 100 hits by a selection process. Many of those hits were supported by literature, but some proteases were novel in their functional link to breast cancer. Interestingly, we discovered that the environmental conditions influence the degree of breast cancer cell dependency on certain proteases. For example, breast cancer stem cell-like cells were less susceptible to depletion of several mitochondrial proteases in hypoxic conditions. From the 100 hits, nine proteases were functionally validated in murine breast cancer cell lines using individual knockdown constructs, highlighting the high reliability of our screens. Specifically, we focused on mitochondrial processing peptidase (MPP) subunits alpha (Pmpca) and beta (Pmpcb) and discovered that MPP depletion led to a disadvantage in cell growth, which was linked to mitochondrial dysfunction.

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.