Abstract 4571: Ultra sensitive detection and quantification of low frequency variants in plasma using nRichDX extraction and PacBio SBB sequencing

Background: The detection and quantification of low frequency circulating tumor DNA (ctDNA) variants in plasma are essential for early cancer diagnosis and monitoring but remain challenging at variant allele frequencies (VAFs) below 1%. This study combines the clinically relevant reference standards to simulate low frequency ctDNA variants with the high sensitivity of the PacBio Onso sequencing system, which utilizes highly accurate sequencing by binding (SBB) chemistry, and nRichDX’s large-volume extraction capabilities. Together, these advancements aim to improve detection accuracy, enhance diagnostic reliability, and facilitate earlier intervention in oncology by overcoming the limitations of low plasma volumes. Methods: Spike in experiments were conducted using SeraCare ctDNA reference v4 material in plasma from healthy patients, with VAFs of 0.1% and 0.01%selected to represent challenging low-frequency levels common in clinical ctDNA detection as well as 0% (wild type control). Experiments were performed with 5 mL and 20 mL plasma volumes, with three replicates per condition. cfDNA was extracted using both nRichDX and Qiagen kits for comparison. Extracted cfDNA underwent library preparation, hybridization capture, library conversion, quality control, equimolar pooling, and sequencing on the Onso platform. Variant calling and data analysis were conducted to assess extraction sensitivity and detection performance at these low VAF levels. Results: The study demonstrated that detecting low frequency variants at 0.1% and 0.01% VAF was challenging in 5 mL plasma samples, regardless of the extraction method, due to the inherent difficulty of capturing such low variant frequencies in smaller volumes. In contrast, the nRichDX system successfully detected these low frequency variants in 20 mL plasma samples, whereas the Qiagen kit showed limited recovery at these levels. Additionally, the nRichDX workflow was more streamlined and efficient compared to Qiagen, further emphasizing the advantages of nRichDX for larger sample volumes and low frequency variant detection. Conclusions: These findings emphasize the critical importance of using larger plasma volumes to detect lower VAFs effectively and increase overall sensitivity in liquid biopsy applications. The nRichDX system’s strong performance with 20 mL samples, combined with its no-transfer process that leaves no targets behind, suggests its potential for improved sensitivity in early cancer detection. Combining the nRichDX system with the increased sequencing accuracy of SBB on the PacBio Onso resulted in maximum recovery for low-frequency variants. This can inform clinical practices to optimize sample volume and extraction methods as well as sequencing performance for accurate identification of low-frequency ctDNA variants. Citation Format: Mayer Saidian, Alex Sockell, Dan Nasko, Ian McLauglin, Jason Saenz, Carlos Hernandez, Andrew Dunnigan, Leila Aghili, Nafiseh Jafari. Ultra sensitive detection and quantification of low frequency variants in plasma using nRichDX extraction and PacBio SBB sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4571.