Abstract 2316: Automating ctDNA liquid biopsy workflow for mutation testing: From sample extraction to dPCR analysis utilizing the Maxprep™ Liquid Handler, Maxwell® extraction system, and high-plex detection assays

Abstract Liquid biopsies are a minimally-invasive sampling approach to overcome the heterogeneity of tumors and represent a valuable source of circulating tumor DNA (ctDNA) for oncological biomarker analysis. The use of ctDNA as a surrogate for tissue DNA is increasingly popular, and advances in the detection and characterization of ctDNA has enabled liquid biopsy assay integration into clinical utilization. However, an innate challenge with measurement of ctDNA is the requirement for highly sensitive quantitation to reliably detect rare genetic aberrations. Digital PCR has emerged as a powerful technology addressing the needs for next-generation analysis of liquid biopsies samples. Having reliable assays for analysis of key oncology targets help drive adoption of this technology into real-world applications. The exquisite sensitivity of digital PCR requires sample preparation methods that reduce variation, making automation of any manual steps highly desirable. Automation also provides flexibility to scale up as testing volumes increase while simultaneously decreasing overall complexity for the operator. Here we present an automated workflow for ctDNA extraction and analysis using the Maxprep™ Liquid Handler, Maxwell® extraction system (Promega Corporation), and a new, high-throughput digital PCR consumable, the Ruby Chip (Stilla Technologies). This ultra-sensitive detection for liquid biopsy samples was performed using a high-plex dPCR assay. Citation Format: Michael Granitsiotis, Kimberly Gutierrez, Doug Horejsh, Monica Yue. Automating ctDNA liquid biopsy workflow for mutation testing: From sample extraction to dPCR analysis utilizing the Maxprep™ Liquid Handler, Maxwell® extraction system, and high-plex detection assays [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2316.