A novel magnetic bead-based cfDNA extraction method for advanced ctDNA marker discovery and methylation profiling.
Abstract
3051 Background: Cell-free DNA (cfDNA) extraction and circulating tumor DNA (ctDNA) enrichment are critical for liquid biopsy-based cancer diagnostics. However, the QIAamp Circulating Nucleic Acid Kit (QIA), despite its widespread use, has limitations, including a labor-intensive manual workflow and suboptimal performance in ctDNA marker enrichment and contaminant removal, potentially affecting downstream methylation analyses. To overcome these limitations, we developed a novel, automatable magnetic bead-based cfDNA extraction method to improve ctDNA enrichment and biomarker discovery. Methods: The optimized extraction protocol incorporates refinements in pre-treatment, lysis, and binding steps to enhance cfDNA purity and ctDNA enrichment. Plasma samples from 8 lung adenocarcinoma (LUAD) patients, 10 healthy donors, and five simulated plasma samples spiked with varying proportions of fragmented genomic DNA from H838 (cancer) and NA12878 (healthy) cells were processed using both our optimized assay and the QIA kit. Results: The optimized method achieved cfDNA yields comparable to the QIA kit in LUAD and healthy samples but exhibited significantly higher extraction yields in simulated samples (39.91 ng vs. 31.17 ng, p < 0.05). Digital PCR demonstrated superior enrichment of 136 bp and 400 bp cfDNA fragments, while library preparation showed a 1-fold and 1.46-fold increase in pre-library yield and a 16.55% and 6.45% increase in mapped ratios for LUAD and healthy donors, respectively. These results demonstrate that our method achieves superior cfDNA enrichment efficiency compared to QIA, making it better suited for NGS-based workflows. Library complexity rose from 24.07% to 31.24% in LUAD samples and from 29.71% to 35.04% in healthy donors, with coverage depth of target regions improving by 56.13% and 22.88%, respectively. This enabled the detection of more CpG sites at equivalent sequencing depths. Simulated sample analysis confirmed that our optimized method better preserved methylation accuracy, achieving higher consistency between extracted and unextracted DNA. Furthermore, the optimized method identified significantly more cancer-specific haplotypes across 1,517 LUAD markers, improving ctDNA detection sensitivity, particularly in low tumor burden samples. Conclusions: Our automatable magnetic bead-based cfDNA extraction method outperforms QIA in library quality, complexity, and methylation accuracy while enabling enhanced ctDNA enrichment and biomarker detection. This approach provides a robust and scalable solution for advancing liquid biopsy-based cancer diagnostics. Technique Protocol Throughput Handling time per run (min) Cost ($) Beta bias with unextracted DNA Unmethylated marker counts median Methylated marker counts median QIAamp (QIA) Vacuum-column Manual 24 180~240 25 0.01319 382 526 Our assay Magnetic bead Automatic 24 30 1 0.00365 590 734
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (13)
Zhuoran Jiang
Shanghai Xiaohe Medical Laboratory Co., Ltd., Shanghai, China
Feng Xu
Faculty of Pharmaceutical Sciences
Yuting Liu
Congchong Wei
Shanghai Xiaohe Medical Laboratory Co., Ltd., Shanghai, China
Yanzhan Yang
Shanghai Xiaohe Medical Laboratory Co. Ltd., Shanghai, Select a state..., China
Ying Xin
The Hong Kong Polytechnic University Shenzhen Research Institute
Guo Chen
Key Laboratory of Materials Physics
Shiqing Chen
Marketing and Medicine, Shanghai Xiaohe Medical Laboratory Co. Ltd., Shanghai, Select a state., China
Baoliang Zhu
Shanghai Xiaohe Medical Laboratory Co. Ltd., Shanghai, China
Xueguang Sun
Shanghai Xiaohe Medical Laboratory Co., Ltd., Shanghai, China
Xiaohui Wu
Key Laboratory of Functional Polymer Materials of Ministry of Education, Institute of Polymer Chemistry, State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for New Organic Matter, Haihe Laboratory of Sustainable Chemical Transformations, College of Chemistry
Qiang Guo
Hefei Li