Abstract LB249: Multi-omics cancer risk assessment of Barrett’s esophagus with DNA methylation sequencing from endoscopic brush samples

Abstract Introduction: Barrett’s esophagus (BE) confers increased cancer risk. Endoscopic surveillance is recommended to distinguish non-dysplastic BE (NDBE), low grade dysplasia (LGD), high grade dysplasia (HGD), or adenocarcinoma (EAC) for endoscopic intervention. However, this paradigm is limited by sampling error, leading to missed/interval EAC. Herein, we aimed to classify these samples more accurately by performing whole genome methylation sequencing (WGMS) and utilizing multiple genomic features on endoscopic brush samples. Materials and methods: Endoscopic brush samples from patients with NDBE (n=18), HGD (18), EAC (18), and normal controls (18) were collected and underwent WGMS (discovery dataset). Sequence reads were processed through internal pipeline to extract CpG methylation and read level methylation ratio (alpha value). Copy number aberration (CNA) detection was performed using both CNVkit and ichorCNA. Differential methylated regions (DMRs) were identified through comparing EAC/HGD with NDBE and normal samples. Targeted methylation sequencing for selected DMRs and shallow WGMS were performed on EAC (41), HGD (26), LGD (23), NDBE (42), and normal controls (37) as validation. Ratio of the reads with alpha value0. 6 for each DMR was used for further analysis. Detected CNA segments were summarized into chromosome arm loss or gain (aneuploidy score or AS representing the number of chromosome arms gained or lost in a sample) and trimmed median absolute deviation (tMAD). Classification models were developed using the discovery set and the best performing one was applied to the validation dataset. Results: Genome-wide DNA methylation largely segregated different groups of samples as diagnosed; however, some unexpected group crossings were observed. Top 200 DMRs were identified between EAC/HGD and NDBE and normal samples. CNA changes were widespread in EAC, very common in HGD but rare in NDBE (17/18 EACs, 14/18 HGDs, 5/18 NDBEs with AS0). With tMAD 0. 015, 16/18 EACs, 8/18 HGDs but none of 18 NDBEs passed the threshold. EAC or HGD samples without detectable CNAs had very low “tumor” fraction as determined by methylation-based cell type deconvolution or ichorCNA. Similar results were found in the validation dataset. A multi-omics (AS, tMAD, estimated tumor fraction, and DMR methylation) model could predict EAC, HGD, or NDBE with 0. 81 accuracy through cross validation (10X) and 0. 73 in the independent dataset. This increased to 0. 98 and 0. 90 in separating high risk EAC/HGD from NDBE, respectively. Conclusion: Multi-omics data obtained from single WGMS allow for a comprehensive analysis of BE samples with varying dysplasia levels. Using classification modeling, these characteristics can be effectively used to accurately identify and distinguish between EAC and HGD from NDBE, suggesting their utility as adjuncts to endoscopic surveillance biopsies. Citation Format: Zhifu Sun, Caroline L. Matchett, Seth W. Slettedahl, William R. Taylor, Panwen Wang, Calise Berger, Caryn E. Anderson, Melissa A. Passe, Ramona Lansing, Collin E. Chalmers, Patrick H. Foote, Jeanette E. Eckel Passow, Doug W. Mahoney, John B. Kisiel, Prasad G. Iyer. Multi-omics cancer risk assessment of Barrett’s esophagus with DNA methylation sequencing from endoscopic brush samples abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (7Suppl): Abstract nr LB249.