Abstract 2264: Identifying and analyzing independent clonal populations in single Barrett’s esophagus biopsies

Abstract

Abstract Barrett’s esophagus (BE) is a non-obligate precursor of esophageal adenocarcinoma (EAC), often measuring multiple centimeters in length and characterized by columnar epithelium replacing normal squamous epithelium in the distal esophagus. Early studies in BE suggested that all cells within a patient’s Barrett’s segment are progenies of a single founder cell. However, in recent years this previously accepted model of BE as a monoclonal disease has been retired in favor of a multiclonal model with new evidence suggesting that a patient’s Barrett’s segment can be composed of multiple independent clones with independent founder cells. Nonetheless, single BE samples are still routinely assumed to be monoclonal, leading to independent sets of genomic aberrations erroneously being analyzed as a single set in the case of multiclonal samples. Here, we utilize a previously generated whole-genome sequenced BE dataset and repurpose an established pipeline for detecting subclonal populations to identify BE samples that are comprised of multiple independent clones. Additionally, we present a novel approach for validating multiclonality from sequencing data by phasing pair-end sequencing reads using germline variants. We demonstrate that 20/80 patients have at least one multiclonal sample and that the independent clones contained in these single biopsies can have drastically different genomic profiles. Further, we speculate that these multiclonal samples capture a snapshot of clonal competition and evolution within BE. These findings highlight the importance of accounting for multiclonality when studying BE and provide the first systematic analysis of multiclonal BE samples. Citation Format: Mariya Kazachkova, Phoebe He, Ludmil B. Alexandrov. Identifying and analyzing independent clonal populations in single Barrett’s esophagus biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2264.