Abstract 4134: A long-read sequencing and phylogenetic framework for improved detection and timing of overlapping and repetitive somatic structural variations

Abstract Despite their accuracy in identifying single nucleotide variants (SNVs), current short-read sequencing technologies struggle to resolve repetitive regions and complex structural variants (SVs), as the reads are simply too short to span such challenging genomic segments. Mapping issues in homologous regions, the high barrier to accurate phasing, and other limitations increasingly point to long-read sequencing as a method to overcome these challenges. Here we develop a computational framework for harmonization and joint analysis of different variant types in the evolutionary context. We particularly focus on structural variants, as they have significant functional consequences and play a large role in driving cancer initiation and progression. As such, we explore the application of long-reads to improve precision breakpoint calling for structural variants in highly repetitive regions, demonstrating their efficacy in resolving complex structural variants. We use this framework to profile 23 subclones of a mouse melanoma cell line, characterized with distinct growth phenotypes and treatment responses. Uniquely, our framework reveals recurrent amplifications of putative driver genes across different lineages caused by independently acquired structural variants, suggesting parallel evolution. In addition, our approach revealed gradual and lineage-specific methylation changes associated with aggressive clonal phenotypes. We show our set of phylogeny-constrained variant calls along with openly released sequencing data can be a valuable resource for the development of new computational methods. Citation Format: Anton Goretsky, Yuelin Liu, Ayse Keskus, Tanveer Ahmad, Chi-Ping Day, Erin K. Molloy, Mikhail Kolmogorov. A long-read sequencing and phylogenetic framework for improved detection and timing of overlapping and repetitive somatic structural variations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4134.

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Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-4134
Primary Topic
Cancer Genomics and Diagnostics
Type
article
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article

Abstract 4134: A long-read sequencing and phylogenetic framework for improved detection and timing of overlapping and repetitive somatic structural variations

Anton Goretsky, Mikhail Kolmogorov, Erin K. Molloy, Yuelin Liu et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract 4134: A long-read sequencing and phylogenetic framework for improved detection and timing of overlapping and repetitive somatic structural variations

Anton Goretsky, Mikhail Kolmogorov, Erin K. Molloy, Yuelin Liu, Chi-Ping Day, Ayse Keskus, Tanveer Ahmad
article en

Abstract

Abstract Despite their accuracy in identifying single nucleotide variants (SNVs), current short-read sequencing technologies struggle to resolve repetitive regions and complex structural variants (SVs), as the reads are simply too short to span such challenging genomic segments. Mapping issues in homologous regions, the high barrier to accurate phasing, and other limitations increasingly point to long-read sequencing as a method to overcome these challenges. Here we develop a computational framework for harmonization and joint analysis of different variant types in the evolutionary context. We particularly focus on structural variants, as they have significant functional consequences and play a large role in driving cancer initiation and progression. As such, we explore the application of long-reads to improve precision breakpoint calling for structural variants in highly repetitive regions, demonstrating their efficacy in resolving complex structural variants. We use this framework to profile 23 subclones of a mouse melanoma cell line, characterized with distinct growth phenotypes and treatment responses. Uniquely, our framework reveals recurrent amplifications of putative driver genes across different lineages caused by independently acquired structural variants, suggesting parallel evolution. In addition, our approach revealed gradual and lineage-specific methylation changes associated with aggressive clonal phenotypes. We show our set of phylogeny-constrained variant calls along with openly released sequencing data can be a valuable resource for the development of new computational methods. Citation Format: Anton Goretsky, Yuelin Liu, Ayse Keskus, Tanveer Ahmad, Chi-Ping Day, Erin K. Molloy, Mikhail Kolmogorov. A long-read sequencing and phylogenetic framework for improved detection and timing of overlapping and repetitive somatic structural variations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4134.

Cancer ResearchVol. 86(7_Supplement)
National Institutes of Health (US), National Cancer Institute (US), University of Maryland, College Park (US)
Openalex Percentile: Top 10%
Cancer Genomics and Diagnostics
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