Abstract 4566: A methylation-based, tissue-independent blood test for recurrence monitoring and treatment assessment
Authors: Jiayue Xu, Xingyu Yang, Qiancheng You, Jing Su, Zeliang Deng, Xinyue Kang, Guangyou Li, Si Zhang, Bingsi Li
Journal: Cancer Research (2025)

Abstract Background: Circulating tumor DNA (ctDNA) has emerged as a promising biomarker of minimal residual disease (MRD) detection and therapy response assessment. However, the low tumor burden in early-stage cancer and interference from non-tumor variants (e.g. clonal hematopoiesis) often necessitate tumor tissue to achieve the desired sensitivity and specificity. This requirement can limit the clinical application, particularly in situations where tissue biopsy is challenging or rapid turnaround times are critical. We previously validated an tissue-free assay (OverC) that combines a novel methylation sequencing method and machine learning for sensitive detection of low-frequency ctDNA in multiple cancer types. Here we describe the expansion of this assay for recurrence monitoring and treatment assessment. Methods: DNA extracted from 139 formalin-fixed paraffin-embedded tumor/normal tissues and 249 plasma samples subjected to whole-genome methylation sequencing (5-30X depth) for single-molecule pattern recognition. The targeted methylation panel of the refined version, known as OverC Monitor, covered 70, 546 CpGs (∼1.0 Mb), representing promoters, introns and other epigenetic regulatory elements. The classifier was developed with a larger THUNDER training set and independently validated with 506 pre-treatment plasma samples from patients with cancer and age-matched non-cancer controls. A positive call is made upon the identification of a cancer signal exceeding a locked threshold. In addition, a quantitative measure of tumor allele fraction (TAF) was developed and reported for each sample to assess its prognostic and monitoring potential. Results: The assay performance was tested using plasma samples from 104 patients with lung cancer (LC), 48 colorectal cancer (CRC) and 74 liver cancer (HCC) and 280 age-comparable non-cancer donors. For LC, the sensitivity was 69.2% (Stage I: 30.3%, Stage II: 60.0%, Stage III: 86.7%, Stage IV: 91.7%) at a specificity of 98.6%. The sensitivity for CRC was 81.3% (Stage I: 41.7%, Stage II: 90.0%, Stage III: 95.0%, Stage IV: 100%) at a specificity of 98.9%. For HCC, the sensitivity reached 95.9% (Stage I: 89.5%, Stage II: 100.0%, Stage III: 95.0%, Stage IV: 100.0%) at a specificity of 98.9%. Further validation with larger cohorts and additional tumor types is underway, and updated data will be presented as it becomes available. Conclusions: By leveraging cancer-derived methylation signatures and machine learning, we have developed and validated a highly sensitive assay (OverC Monitor) for detecting trace amounts of ctDNA in blood. This innovative, tissue-free approach has demonstrated performance on par with cutting-edge tissue-dependent mutation tracking methods for certain cancer types, highlighting its potential for broader clinical use in recurrence monitoring and treatment efficacy assessment. Citation Format: Jiayue Xu, Xingyu Yang, Qiancheng You, Jing Su, Zeliang Deng, Xinyue Kang, Guangyou Li, Si Zhang, Bingsi Li. A methylation-based, tissue-independent blood test for recurrence monitoring and treatment assessment [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 4566.