Molecular counting enables accurate and precise quantification of methylated ctDNA for tumor-naive cancer therapy response monitoring

Abstract Personalized cancer treatment can significantly extend survival and improve quality of life for many patients, but accurate and real-time therapy response monitoring remains challenging. To overcome logistical and technical challenges associated with therapy response monitoring via imaging...

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Main Authors: Patrick Peiyong Ye, Robb Viens, Katherine E Shelburne, Sydne Scot Langpap, Xavier S Bower, Jonathan Jiahui Shi, Wen Zhou, Jan Christian Wignall, Joyce Jiawei Zhu, Brian D. Woodward, Hatim Husain, David S. Tsao, Oguzhan Atay
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-90013-3
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Summary:Abstract Personalized cancer treatment can significantly extend survival and improve quality of life for many patients, but accurate and real-time therapy response monitoring remains challenging. To overcome logistical and technical challenges associated with therapy response monitoring via imaging scans or assays that track the variant allele fraction (VAF) of somatic mutations in circulating tumor DNA (ctDNA), we developed a tumor-naive liquid biopsy assay that leverages Quantitative Counting Template (QCT) technology to accurately and precisely quantify methylated ctDNA (Northstar Response™). The assay achieves < 10% coefficient of variation at 1% tumor fraction, which is 2 × lower than tumor-naive, targeted-panel approaches using VAF. The assay accurately distinguishes 0.25% absolute changes in contrived tumor fraction (AUC > 0.94) and performs well in 12 solid tumor types. Finally, in a small cohort of patients with lung, colorectal, or pancreatic cancer, the assay detected changes in ctDNA methylation that correlate with clinical outcomes. With its precise quantification of ctDNA methylation, Northstar Response is a novel tool for therapy response monitoring with the potential to inform clinical decision making for cancer treatment.
ISSN:2045-2322