Abstract 3675: An integrated approach for simultaneous detection of genomic and epigenetic alterations in blood-based ctDNA analysis

Abstract Cancer harbors abnormalities in the genome and the epigenome, and both can serve as biomarkers to facilitate its detection. We developed an integrated multi-omic approach to identify genomic and methylation alterations simultaneously from blood-based circulating tumor DNA (ctDNA) analysis. In contrast to traditional methods of separated lab workflows for each signal modality, our lab workflow generates both genomic and methylation sequencing libraries from the same input sample. During the workflow, a cytosine conversion-resistant analog of the original cell-free DNA (cfDNA) molecule is synthesized such that its genomic sequence is preserved. Following cytosine conversion of the original cfDNA and its analog in a single reaction, methylation and genomic libraries are respectively derived. A new signal modality identification design is used for separation of genomic and methylation libraries during data processing. Our strategy has the benefit of reducing operational complexity while maximizing ctDNA capture efficiency from small quantities of analyte. Our results show that the multi-omic library is efficiently synthesized (52.8% of genomic reads and 47.2% methylation reads after parsing signal modality identifier), and that the genomic library is effectively protected from cytosine conversion (99.98% protection efficiency). Filtered conversion efficiency exceeds 99.9% in CH (where H corresponds to A, T or C) context from the methylation library, supporting high signal integrity in the methylation workflow. Genomic variant calling detected known cancer variants in FFPE tissue and plasma samples (>96% variants in FFPE tissue samples from stage II and III cancers). In a small clinical cohort study, the methylation signal modality detected 40% of stage I, 95% of stage II and 87% of stage III lung cancer plasma samples at 100% specificity without requiring matching tissue. Taken together, our integrated multi-omic approach provides a versatile tool for combined sensitivity and actionability in blood-based ctDNA detection. Citation Format: Qin Tang, Becky Wong, Varahenage Namali Perera, Yu Sun, Nafisa Bulsara, Brian Giacopelli, James Yu, Jason Close, Peter George, Andy Eang, Ashley Linares, Andrew S. Lee, Neil Peterman, Alex Robertson, Nicole Lambert, Yexun Wang. An integrated approach for simultaneous detection of genomic and epigenetic alterations in blood-based ctDNA analysis [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 3675.