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. 2021 Mar 22;5(4):508-516.
doi: 10.1002/jgh3.12530. eCollection 2021 Apr.

Digital next-generation sequencing of cell-free DNA for pancreatic cancer

Affiliations

Digital next-generation sequencing of cell-free DNA for pancreatic cancer

Shinichi Takano et al. JGH Open. .

Abstract

Background and aim: The clinical applicability of digital next-generation sequencing (dNGS), which eliminates polymerase chain reaction (PCR) and sequencing error-derived noise by using molecular barcodes (MBs), has not been fully evaluated. We evaluated the utility of dNGS of cell-free DNA (cfDNA) in liquid biopsies obtained from patients with pancreatic cancer.

Methods: Fifty-eight patients with pancreatic cancer undergoing endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) were included. Samples were subjected to sequencing of 50 cancer-related genes using next-generation sequencing (NGS). The results were used as reference gene alterations. NGS of cfDNA from plasma was performed for patients with a mutant allele frequency (MAF) >1% and an absolute mutant number > 10 copies/plasma mL in KRAS or GNAS by digital PCR. Sequence readings with and without MBs were compared with reference to EUS-FNA-derived gene alterations.

Results: The concordance rate between dNGS of cfDNA and EUS-FNA-derived gene alterations was higher with than without MBs (p = 0.039), and MAF cut-off values in dNGS could be decreased to 0.2%. dNGS using MBs eliminated PCR and sequencing error by 74% and 68% for TP53 and all genes, respectively. Overall, dNGS detected mutations in KRAS (45%) and TP53 (26%) and copy number alterations in CCND2, CCND3, CDK4, FGFR1, and MYC, which are targets of molecular-targeted drugs.

Conclusions: dNGS of cfDNA using MBs is useful for accurate detection of gene alterations even with low levels of MAFs. These results may be used to inform the development of diagnostics and therapeutics that can improve the prognosis of pancreatic cancer.

Keywords: cell‐free DNA; liquid biopsy; next‐generation sequencing; pancreatic ductal carcinoma.

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Figures

Figure 1
Figure 1
Flow chart of this study. (a) Selection of patients and samples in this study. (b) A schema describing digital next‐generation sequencing (dNGS) using molecular barcodes (MBs). (c) The flow of the NGS analyses.
Figure 2
Figure 2
Mutations detected in tissue samples and cell‐free DNA obtained by liquid biopsy by DNA‐based analyses with and without molecular barcodes (MB). The panel provides a summary of mutations detected in tissue samples and cfDNA. The boxes in the middle panel represent detected mutations in each case, in which a circle, an upper left triangle, and a lower right triangle represent mutations in tissue, cfDNA with MB, and cfDNA without MB, respectively. Blue and yellow triangles represent cfDNA‐derived mutations that matched or did not match tissue‐derived mutations. The light green triangle in KRAS was a cfDNA mutation, which matched a tissue mutation, although its mutant allele frequency (MAF) was lower than the cut‐off value. The left side of the panel displays the gene symbols, and the frequencies of mutation in each gene are shown in the right side of the panel. The upper side of the panel shows the clinical stages of each case and cases of multiple sampling (gray case), in which multiple cfDNA samples were obtained at different times. cfDNA, cell‐free DNA; EUS‐FNA, endoscopic ultrasound‐guided fine‐needle aspiration; MB, analyses using molecular barcodes.
Figure 3
Figure 3
Mutant allele frequencies (MAFs) and numbers of detected mutations of cell‐free DNA (cfDNA) analyzed by with and without molecular barcodes (MBs). (a) The cut‐off value of (MAFs) in the cfDNA‐derived mutation that matched with the tissue‐derived mutation was evaluated by receiver operating characteristics (ROC) curve analysis. The area under the curve was 0.89 and 0.84 (p = 0.039) in analyses with and without MB, respectively. formula image, With MB; formula image, without MB. (b) MAF plots of detected mutations in cfDNA by next‐generation sequencing (NGS) analyses with and without MB. Matches and mismatches with mutations detected in tissue samples are shown in blue and orange dots, respectively. Cut‐off values for matched mutations (i.e. same mutations in cfDNA and tissue samples) were determined by ROC curve analysis to be 0.2% and 0.5% by dNGS and ordinary NGS, respectively. The sensitivity and specificity for matched mutations were 83.3% and 93.3% by dNGS, respectively, and 73.9% and 92.9% by ordinary NGS, respectively. formula image, Match; formula image, mismatch. (c) The proportion of concomitant cfDNA with tissue mutations in KRAS, TP53, and all assayed genes. The number of mutations detected in tissue samples are shown in the left in each graph, and cfDNA mutations matching with those identified in tissue samples are shown in bar plots. Tissue‐matched and ‐mismatched cfDNA mutations are shown as blue and yellow bars, respectively, whereas tissue‐matched mutations with a lower MAF than the cut‐off value are shown as light green bars. formula image, Mismatch; formula image, match < cutoff; formula image, match or tissue. MAF, mutant allele frequency; MB, dNGS analysis with molecular barcodes; cfDNA, cell‐free DNA.
Figure 4
Figure 4
Clinical course of a representative case during systemic chemotherapy. Changes in tumor marker CA19‐9 levels and mutant allele frequency (MAF) are shown as dotted and solid line graphs, respectively, and representative computed tomography images are displayed in the upper panel. In this case, liquid biopsies were obtained three times during the clinical course from which copy number alterations (CNAs) of cell‐free DNA together with gene mutations were analyzed. The right panels show CNAs in MYC and CCND2 as dot plots, in which dots elevated from the center line correspond with amplified genes (arrows).

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