Purpose: No study has investigated the precise perioperative dynamic changes in circulating tumor DNA (ctDNA) in any patients with early-stage cancer. This study (DYNAMIC) investigated perioperative dynamic changes in ctDNA and determined the appropriate detection time of ctDNA-based surveillance for surgical patients with lung cancer.Experimental Design: Consecutive patients who underwent curative-intent lung resections were enrolled prospectively (NCT02965391). Plasma samples were obtained at multiple prespecified time points including before surgery (time A), during surgery after tumor resection (time B-time D), and after surgery (time P1-time P3). Next-generation sequencing-based detection platform was performed to calculate the plasma mutation allele frequency. The primary endpoint was ctDNA half-life after radical tumor resection.Results: Thirty-six patients showed detectable mutations in time A. The plasma ctDNA concentration showed a rapid decreasing trend after radical tumor resection, with the average mutant allele fraction at times A, B, C, and D being 2.72%, 2.11%, 1.14%, and 0.17%, respectively. The median ctDNA half-life was 35.0 minutes. Patients with minimal residual disease (MRD) detection had a significant slower ctDNA half-life than those with negative MRD (103.2 minutes vs. 29.7 minutes, P ¼ 0.001). The recurrence-free survival of patients with detectable and undetectable ctDNA concentrations at time P1 was 528 days and 543 days, respectively (P ¼ 0.657), whereas at time P2 was 278 days and 637 days, respectively (P ¼ 0.002).Conclusions: ctDNA decays rapidly after radical tumor resection. The ctDNA detection on the third day after R0 resection can be used as the baseline value for postoperative lung cancer surveillance.
Asthma is characterized by airway inflammation, mucus overproduction, airway hyperreactivity, and peribronchial fibrosis. Intelectin has been shown to be increased in airway epithelium of asthmatics. However, the role of intelectin in the pathogenesis of asthma is unknown. Airway epithelial cells can secrete chemokines such as monocyte chemotactic protein (MCP)-1 and -3 that play crucial roles in asthmatic airway inflammation. We hypothesized that intelectin plays a role in allergic airway inflammation by regulating chemokine expression. In a mouse allergic asthma model, we found that mRNA expression of intelectin-2 as well as MCP-1 and -3 in mouse lung was increased very early (within 2 h) after allergen challenge. Expression of intelectin protein was localized to mucous cells in airway epithelium. Treatment of MLE12 mouse lung epithelial cells with interleukin IL-13, a critical mediator of allergic airway disease, induced expression of intelectin-1 and -2 as well as MCP-1 and -3. When IL-13-induced intelectin-1 and -2 expression was inhibited by RNA interference, IL-13-induced extracellular signal-regulated kinase 1/2 phosphorylation and MCP-1 and -3 production by MLE12 cells was inhibited. Furthermore, inhibition of intelectin expression by airway transfection with shRNA targeting intelectin-1 and -2 attenuated allergen-induced airway inflammation. We conclude that intelectin, a molecule expressed by airway epithelial cells and upregulated in asthma, is required for IL-13-induced MCP-1 and -3 production in mouse lung epithelial cells and contributes to allergic airway inflammation.
Cell-free DNA (cfDNA) fragmentation patterns contain important molecular information linked to tissues of origin. We explored the possibility of using fragmentation patterns to predict cytosine-phosphate-guanine (CpG) methylation of cfDNA, obviating the use of bisulfite treatment and associated risks of DNA degradation. This study investigated the cfDNA cleavage profile surrounding a CpG (i.e., within an 11-nucleotide [nt] window) to analyze cfDNA methylation. The cfDNA cleavage proportion across positions within the window appeared nonrandom and exhibited correlation with methylation status. The mean cleavage proportion was ∼twofold higher at the cytosine of methylated CpGs than unmethylated ones in healthy controls. In contrast, the mean cleavage proportion rapidly decreased at the 1-nt position immediately preceding methylated CpGs. Such differential cleavages resulted in a characteristic change in relative presentations of CGN and NCG motifs at 5′ ends, where N represented any nucleotide. CGN/NCG motif ratios were correlated with methylation levels at tissue-specific methylated CpGs (e.g., placenta or liver) (Pearson’s absolute r > 0.86). cfDNA cleavage profiles were thus informative for cfDNA methylation and tissue-of-origin analyses. Using CG-containing end motifs, we achieved an area under a receiver operating characteristic curve (AUC) of 0.98 in differentiating patients with and without hepatocellular carcinoma and enhanced the positive predictive value of nasopharyngeal carcinoma screening (from 19.6 to 26.8%). Furthermore, we elucidated the feasibility of using cfDNA cleavage patterns to deduce CpG methylation at single CpG resolution using a deep learning algorithm and achieved an AUC of 0.93. FRAGmentomics-based Methylation Analysis (FRAGMA) presents many possibilities for noninvasive prenatal, cancer, and organ transplantation assessment.
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