Abstract 3248: Characterization of multiple myeloma genomes with LinkPrep assay enables detection of somatic variation and SV-driven interactions of the 3D genome

Abstract Multiple myeloma (MM) is characterized by its genomic complexity that includes recurrent driver single nucleotide variation (SNVs) alongside a high burden of structural variation (SV). Complete characterization of somatic variation in a MM genome is dependent on a technology that can accurately and sensitively detect both small and large variants. Here, we demonstrate performance of a novel linked-read approach, called LinkPrep™ technology, for high accuracy detection of both small and large somatic variants in four separate relapse MM genomes.Four MM patient-derived xenografts were profiled with Dovetail® LinkPrep™ kit and sequenced to ∼30X on an Illumina platform. Data was analyzed through the Dovetail Analysis Portal to detect SNVs/Indels (DeepSomatic), CNVs (Purple), and SVs (HiC-breakfinder and proprietary tools). Call sets were compared against other genomics technologies including WGS (80X tumor/ 30X normal), PacBio (15X), and OGM (400X).LinkPrep + Dovetail Analysis Portal returned high quality variant results for the four MM samples. LinkPrep data recalled all pathogenic SNV/Indels detected by 80X WGS (notable pathogenic variants were detected in NRAS, KRAS, TP53). LinkPrep data further detected SVs involving the IGH locus (inversions and translocations) in all four samples. Deeper analysis of one sample (M24) highlights that LinkPrep data detects genetic alterations common in MM including SNV mutations in NRAS and TP53 (both occurring at 100% VAF), IGH rearrangements, chr 1q gain, chr 1p loss of heterozygosity, trisomy of chr 5,7, and 15, and complex rearrangements involving chromosomes 2, 3, 4, 16, and 19. With the exception of a confident subclonal (1% SV-VAF) unbalanced translocation detected by LinkPrep, the remaining LinkPrep large SV calls were validated by other genomics methods. Underscoring the capability of LinkPrep for SV detection, LinkPrep calls at 30X contain >10-100 times more read support for every SV call over other technologies. Using the linked-read feature of LinkPrep data along with CNV segment calls and SV calls provided through the Dovetail Analysis Portal a candidate solution is derived for the complex rearrangement involving chromosomes 2, 3, 4, 16, and 19. This LinkPrep solution, refined down to base pair resolution for every breakpoint, is verified by 400X OGM data. Uniquely, LinkPrep data further enables visualization of the SV-reconstructed 3D genome and reveals neo-loops connecting enhancers with promoters to suggest enhancer hijacking mechanisms associated with the complex rearrangement.Together, these data demonstrate that LinkPrep linked-reads enable improved characterization of somatic variation in highly rearranged genomes, while simultaneously detecting epigenetic states -- all enabled with the accuracy and cost-effectiveness of short read sequencing. Citation Format: Lisa Munding, Nathan Becker, Enze Liu, Alexander Fortuna, Jonathan Torchia, Aneta Mikulasova, J. Zachary Sanborn, Brian Walker. Characterization of multiple myeloma genomes with LinkPrep assay enables detection of somatic variation and SV-driven interactions of the 3D genome [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 3248.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-3248
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 3248: Characterization of multiple myeloma genomes with LinkPrep assay enables detection of somatic variation and SV-driven interactions of the 3D genome

Ethan Liu, Aneta Mikulášová, Alexander Fortuna, Nathan Becker et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract 3248: Characterization of multiple myeloma genomes with LinkPrep assay enables detection of somatic variation and SV-driven interactions of the 3D genome

Ethan Liu, Aneta Mikulášová, Alexander Fortuna, Nathan Becker, Jonathan Torchia, Lisa Munding, Brian Walker, J. Zachary Sanborn
article en

Abstract

Abstract Multiple myeloma (MM) is characterized by its genomic complexity that includes recurrent driver single nucleotide variation (SNVs) alongside a high burden of structural variation (SV). Complete characterization of somatic variation in a MM genome is dependent on a technology that can accurately and sensitively detect both small and large variants. Here, we demonstrate performance of a novel linked-read approach, called LinkPrep™ technology, for high accuracy detection of both small and large somatic variants in four separate relapse MM genomes.Four MM patient-derived xenografts were profiled with Dovetail® LinkPrep™ kit and sequenced to ∼30X on an Illumina platform. Data was analyzed through the Dovetail Analysis Portal to detect SNVs/Indels (DeepSomatic), CNVs (Purple), and SVs (HiC-breakfinder and proprietary tools). Call sets were compared against other genomics technologies including WGS (80X tumor/ 30X normal), PacBio (15X), and OGM (400X).LinkPrep + Dovetail Analysis Portal returned high quality variant results for the four MM samples. LinkPrep data recalled all pathogenic SNV/Indels detected by 80X WGS (notable pathogenic variants were detected in NRAS, KRAS, TP53). LinkPrep data further detected SVs involving the IGH locus (inversions and translocations) in all four samples. Deeper analysis of one sample (M24) highlights that LinkPrep data detects genetic alterations common in MM including SNV mutations in NRAS and TP53 (both occurring at 100% VAF), IGH rearrangements, chr 1q gain, chr 1p loss of heterozygosity, trisomy of chr 5,7, and 15, and complex rearrangements involving chromosomes 2, 3, 4, 16, and 19. With the exception of a confident subclonal (1% SV-VAF) unbalanced translocation detected by LinkPrep, the remaining LinkPrep large SV calls were validated by other genomics methods. Underscoring the capability of LinkPrep for SV detection, LinkPrep calls at 30X contain >10-100 times more read support for every SV call over other technologies. Using the linked-read feature of LinkPrep data along with CNV segment calls and SV calls provided through the Dovetail Analysis Portal a candidate solution is derived for the complex rearrangement involving chromosomes 2, 3, 4, 16, and 19. This LinkPrep solution, refined down to base pair resolution for every breakpoint, is verified by 400X OGM data. Uniquely, LinkPrep data further enables visualization of the SV-reconstructed 3D genome and reveals neo-loops connecting enhancers with promoters to suggest enhancer hijacking mechanisms associated with the complex rearrangement.Together, these data demonstrate that LinkPrep linked-reads enable improved characterization of somatic variation in highly rearranged genomes, while simultaneously detecting epigenetic states -- all enabled with the accuracy and cost-effectiveness of short read sequencing. Citation Format: Lisa Munding, Nathan Becker, Enze Liu, Alexander Fortuna, Jonathan Torchia, Aneta Mikulasova, J. Zachary Sanborn, Brian Walker. Characterization of multiple myeloma genomes with LinkPrep assay enables detection of somatic variation and SV-driven interactions of the 3D genome [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 3248.

Cancer ResearchVol. 86(7_Supplement)
Dovetail Genomics (United States) (US), Sylvester Comprehensive Cancer Center (US), Schauenburg (United Kingdom) (GB)
Openalex Percentile: Top 8%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.