At Fluxion, we’re passionate about delivering cell-based and cell-free solutions that facilitate the transformation of research discoveries into new ways to diagnose and treat patients. By characterizing molecular and cellular mechanisms of disease, Fluxion’s platforms help bridge the translational medicine gap, enabling rapid advances in disease research, drug discovery, and the development of diagnostic tests.
Liquid biopsies aim to identify clinically actionable information from cell-free DNA (cfDNA) and circulating tumor cells (CTCs), among other biomarkers. Such assays are economical with respect to solid biopsies, and they afford a non-invasive way of screening for disease and monitoring progression over time. However, analyzing data from liquid biopsies requires overcoming a number of technological and analytical hurdles imposed by the characteristically small amount of starting material.
Here, we describe the application of the ERASE-Seq (Elimination of Recurrent Artifacts and Stochastic Errors) sequencing and analysis pipeline to cfDNA isolated from peripheral blood obtained from 348 lung cancer patients. ERASE-Seq leverages Molecular Amplification Pools (MAPs) and a background-aware error-identification approach to confidently identify low-frequency variants from cfDNA datasets using amplicon panels without unique molecular identifiers (UMIs, or molecular barcodes). To assess performance, we compare results to droplet digital PCR (ddPCR), and orthogonal approach commonly used to identify low-frequency variation.
We find that ERASE-Seq has excellent sensitivity (98.5%) and specificity (98.9%) when compared to ddPCR in clinical samples. We identify a number of actionable results, including canonical EGFR mutations that confer sensitivity to tyrosine kinase inhibitors. In 13% of cases, we identify mutations not found by ddPCR due to a larger target space and greater sensitivity for indels. We identify actionable mutations in the absence of tissue data (96) and cases where resistance variants are emerging upon progression (5%). Furthermore, we are able to classify mutations traditionally associated with clonal hematopoiesis (CH) with high confidence, which are known to become more prevalent with age and are associated with the development of blood cancers.
We demonstrate the clinical utility of the ERASE-Seq approach in accurately detecting actionable mutations from cfDNA samples from lung cancer patients. Additionally, we identify low-frequency CH-associated mutations that could be associated with the onset of future cancers, providing promising results for ERASE-Seq's utility in future diagnostic assay development.