ERASE-Seq: A Novel NGS Statistical Approach Outperforms Barcodes and Enables Precise Detection of Somatic Variants in cfDNA

Cristian Ionescu-Zanetti (1), Nicholas Kamps-Hughes (1), Hong Yin (2)
1-Fluxion Biosciences, Alameda, CA 2-Lousiana State University Health Science Center, Shreveport, LA

Abstract

Liquid biopsy assays have shown great promise as a precision medicine approach to therapy selection and patient monitoring, but significant sensitivity and specificity improvements are still needed. To address this we introduce ERASE-Seq (Elimination of Recurrent Artifacts and Stochastic Errors), a method for accurate and sensitive detection of ultra-low frequency DNA variants. ERASE-Seq differs from previous methods by creating a variant event matrix (Fig 1) that includes multiple sample runs and control data. A robust statistical framework is applied at each position in the sequence, providing a 10 to 100-fold reduction in false positive rates compared to published molecular barcoding methods.

ERASE-Seq was tested using spiked human DNA mixtures with clinically realistic DNA input amounts to detect alterations between 0.05% and 1%, the range commonly found in liquid biopsy samples. Alterations were detected with greater than 90% sensitivity and a false positve rate below 0.3 calls per 10,000 possible alterations. The approach represents a significant performance improvement with respect to molecular barcoding methods and does not require changing molecular reagents. Clinical study results using the Spotlight 59 Oncology Panel with the ERASE-Seq approach show consistent performance.

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ERASE poster - LSU_thumb.png