Abstract 5056: Full spectrum of somatic structural variations (SVs) detection in COLO829 with long-read sequencing

Abstract Somatic SVs significantly contribute to cancer development and progression. Characterizing these variations has traditionally been difficult due to the limitations of short-read sequencing technologies and the diverse types and lengths of SVs. The advent of long-read sequencing has enabled a more comprehensive analysis of germline SVs, highlighting its potential applications in cancer genomics. The melanoma cell line COLO829, along with its normal counterpart COLO829BL, is a standard reference for somatic SV detection. Valle-Inclan et al. recently validated 68 somatic SVs combining short-read, long-read, and linked-read sequencing data. However, the sensitivity may be compromised as only a limited number of alignment-based callers were employed, such as NanoSV, Sniffles (for Oxford Nanopore Technologies (ONT)), and pbsv for (PacBio HiFi). As more alignment-based SV callers are being developed, it is crucial to integrate a broader range of tools to construct a comprehensive call set of somatic SVs. Moreover, the performance of assembly-based methods in somatic SV detection within cancer remains largely unexplored. In this study, we aimed to establish a comprehensive spectrum of somatic SVs in the COLO829 melanoma cell line by employing both alignment-based and assembly-based methods with long-read whole-genome sequencing data from PacBio and ONT aligned with Minimap2, SVs were identified and integrated from 7 alignment-based callers: cuteSV, NanoVar, DeBreak, Sniffles2, Svision-Pro, NanoSV, and pbsv. In addition, genome assemblies were constructed via Hifiasm and Verkko, incorporating HiFi reads with Hi-C and ultra-long ONT integration, followed by SV detection using four assembly-based callers: Dipcall, PAV, SVIM-asm, and cuteSV. A dedicated pipeline was developed to identify and filter somatic SVs from germline events, which considers mapping quality, sequencing depth of SV regions and their flanking regions, and 50% reciprocal overlap. Compared to the truth set established by Valle-Inclan et al., we discovered 19 novel somatic SVs, including 10 deletions, 4 insertions, 3 duplications, and 2 inversions. As a comparison, assembly-based methods detected all the deletions, insertions and duplications found by the alignment-based methods. However, it missed 20 inversions and 6 translocations. Our findings highlight the superior sensitivity of alignment-based techniques in somatic SV detection and underscore the complementary nature of assembly-based approaches. This work enhances the benchmark for somatic SV characterization in cancer genomics and confirms the utility of integrated long-read sequencing analyses. Citation Format: Zishan Peng, Zechen Chong. Full spectrum of somatic structural variations (SVs) detection in COLO829 with long-read sequencing [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 5056.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-5056
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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article
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article

Abstract 5056: Full spectrum of somatic structural variations (SVs) detection in COLO829 with long-read sequencing

Zechen Chong, Zhengxiong Peng
Cancer Research
Radiomics and Machine Learning in Medical Imaging
article

Abstract 5056: Full spectrum of somatic structural variations (SVs) detection in COLO829 with long-read sequencing

Zechen Chong, Zhengxiong Peng
article en

Abstract

Abstract Somatic SVs significantly contribute to cancer development and progression. Characterizing these variations has traditionally been difficult due to the limitations of short-read sequencing technologies and the diverse types and lengths of SVs. The advent of long-read sequencing has enabled a more comprehensive analysis of germline SVs, highlighting its potential applications in cancer genomics. The melanoma cell line COLO829, along with its normal counterpart COLO829BL, is a standard reference for somatic SV detection. Valle-Inclan et al. recently validated 68 somatic SVs combining short-read, long-read, and linked-read sequencing data. However, the sensitivity may be compromised as only a limited number of alignment-based callers were employed, such as NanoSV, Sniffles (for Oxford Nanopore Technologies (ONT)), and pbsv for (PacBio HiFi). As more alignment-based SV callers are being developed, it is crucial to integrate a broader range of tools to construct a comprehensive call set of somatic SVs. Moreover, the performance of assembly-based methods in somatic SV detection within cancer remains largely unexplored. In this study, we aimed to establish a comprehensive spectrum of somatic SVs in the COLO829 melanoma cell line by employing both alignment-based and assembly-based methods with long-read whole-genome sequencing data from PacBio and ONT aligned with Minimap2, SVs were identified and integrated from 7 alignment-based callers: cuteSV, NanoVar, DeBreak, Sniffles2, Svision-Pro, NanoSV, and pbsv. In addition, genome assemblies were constructed via Hifiasm and Verkko, incorporating HiFi reads with Hi-C and ultra-long ONT integration, followed by SV detection using four assembly-based callers: Dipcall, PAV, SVIM-asm, and cuteSV. A dedicated pipeline was developed to identify and filter somatic SVs from germline events, which considers mapping quality, sequencing depth of SV regions and their flanking regions, and 50% reciprocal overlap. Compared to the truth set established by Valle-Inclan et al., we discovered 19 novel somatic SVs, including 10 deletions, 4 insertions, 3 duplications, and 2 inversions. As a comparison, assembly-based methods detected all the deletions, insertions and duplications found by the alignment-based methods. However, it missed 20 inversions and 6 translocations. Our findings highlight the superior sensitivity of alignment-based techniques in somatic SV detection and underscore the complementary nature of assembly-based approaches. This work enhances the benchmark for somatic SV characterization in cancer genomics and confirms the utility of integrated long-read sequencing analyses. Citation Format: Zishan Peng, Zechen Chong. Full spectrum of somatic structural variations (SVs) detection in COLO829 with long-read sequencing [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 5056.

Cancer ResearchVol. 85(8_Supplement_1)
University of Alabama at Birmingham (US)
Openalex Percentile: Top 87%
Radiomics and Machine Learning in Medical Imaging
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