Abstract 5896: Tissue naive comprehensive methylation profiling enhances the identification of ctDNA in lung cancer
Abstract Liquid biopsy of circulating tumor DNA (ctDNA) in plasma has shown to have great clinical value by offering real-time insights into disease progression and response to treatment. Mutation focused cell-free DNA (cfDNA) analysis is limited by low ctDNA levels and is restricted by mutation frequency. DNA methylation is a key epigenetic mechanism for regulating gene expression, gene silencing, and genomic imprinting. In the process of tumorigenesis, aberrant methylation patterns, such as CpG island hypermethylation in promoters of tumor suppressor genes play crucial roles. Tracking the methylation patterns in differential DNA methylation regions (DMRs) in cfDNA can be used to monitor biological changes such as tumor progression or treatment response. Here we developed a novel, multi-omics platform that leverages both genetic and epigenetic information from plasma cfDNA. This platform allows simultaneous extraction of genetic information (mutations, sequence variants) and epigenetic modifications (DNA methylation patterns) at the single-DNA-molecule level. To explore the methylation profiling potential of this platform, we conducted a study using a targeted high-depth sequencing approach on procured plasma cfDNA samples from individuals with lung cancer (n=34) and healthy controls (n=78). Along with the data generation, a robust bioinformatics pipeline was designed and implemented for the analysis, including raw sequence alignment, quality control (QC), methylation status assignment, and cancer associated methylation assessments. The platform demonstrated high sensitivity and specificity in detecting cancer-derived cfDNA in this independent sample set. Overall, approximately 29000 of the DMRs (representing >90% of the designed panel), exhibited aberrant methylation in patient samples. For each individual sample, an integrated methylation score was calculated to quantify the cancerous and non-cancerous cfDNA sources based on methylation profiles. This methylation score effectively stratified samples by both cancer presence and disease stage. The overall detection rate (sensitivity) for this sample set was 0.88 at a specificity of 0.91, with sensitivity of 0.66 in stage I (n=5) and 0.92 in stage II/III (n=29). Notably, this assay maintained high sensitivity for (4/6) samples with low ctDNA levels or minimal mutation burden, as evidenced by a circulating tumor fraction (cTF) below 1e-5, identified by variant allele frequency (VAF).In summary, this assay represents a powerful tool for sensitive and specific ctDNA detection. Citation Format: Yu Sun, Nafisa Bulsara, Qin Tang, Becky Wang, Neil Peterman, Varahenage Namali Perera, Brian Giacopelli, James Yu, Jason Close, Peter George, Andy Eang, Ashley Linares, Alex Robertson, Nicole Lambert, Yexun Wang. Tissue naive comprehensive methylation profiling enhances the identification of ctDNA in lung cancer [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 5896.
Authors
- Nafisa Bulsara
- Vern Perera (ORCID: https://orcid.org/0000-0003-1298-0555)
- Alex Robertson (ORCID: https://orcid.org/0000-0002-0713-5165)
- Nicole Lambert
- Yexun Wang (ORCID: https://orcid.org/0000-0003-0362-1892)
- Jason Close
- Peter Myles George (ORCID: https://orcid.org/0000-0003-1316-4891)
- Hung‐Chun Yu (ORCID: https://orcid.org/0000-0002-4980-8508)
- Yuling Sun (ORCID: https://orcid.org/0000-0001-5289-4673)
- Neil Peterman
- Brian Giacopelli (ORCID: https://orcid.org/0000-0001-9846-3473)
- B. Wang
- Qin Tang (ORCID: https://orcid.org/0000-0001-8902-5316)
- Andy Eang
Institutions
- Foundation Medicine (United States)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-5896
- Primary Topic
- RNA modifications and cancer
- Type
- article
- Field-Weighted Citation Impact
- 0.00