SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples

Area of Science:

• Molecular Biology
• Genomics
• Biotechnology

Background:

• Targeted next-generation sequencing (NGS) of plasma cell-free DNA (cfDNA) enables sensitive detection of low-frequency mutations.
• Duplex sequencing, utilizing unique molecular identifiers (UMIs), is a key technology for accurate variant detection in liquid biopsies.
• High costs associated with current duplex sequencing limit its widespread clinical application.

Purpose of the Study:

• To develop a more cost-effective and efficient duplex sequencing approach.
• To improve the accuracy of low-frequency mutation detection in cfDNA.
• To enhance the clinical utility of liquid biopsies for cancer diagnostics.

Main Methods:

• Developed SinoDuplex, an improved duplex sequencing method using pre-defined barcode adapters.
• Implemented a novel computational algorithm for precise duplex consensus sequence generation.
• Evaluated SinoDuplex performance using reference standards and cfDNA from lung cancer patients.

Main Results:

• SinoDuplex significantly increases the output and cost-effectiveness of duplex sequencing.
• The method demonstrates high sensitivity and specificity for detecting ultra-low allele frequency mutations.
• Successful application in analyzing cfDNA from lung cancer patients.

Conclusions:

• SinoDuplex offers a more accessible and precise approach for low-frequency mutation detection in cfDNA.
• This advancement has the potential to broaden the clinical application of liquid biopsies.
• The SinoDuplex source code is publicly available for further research and development.