Abstract 6257: Genome wide, high-throughput, high-resolution structural variation detection at low variant allele fraction for oncology samples

Abstract

Abstract Structural variation detection remains an elusive undertaking. For decades, G-banded karyotyping has remained the standard practice for nearly all hematological malignancy samples. Cancers are diseases of the genome and structural variants (SVs) are a hallmark of nearly all cancers, are often drivers of oncogenicity, and can sometimes be targeted for treatment, as highlighted by the discovery of the Philadelphia chromosome and later the development of targeted kinase inhibitors. One of the most important limitations of karyotyping, its requirement for cells to divide in culture, has prevented its application for most solid tumors and therefore, there is considerably less understanding of the impact of SVs in solid tumors. Optical genome mapping is a technique that is revolutionizing cytogenomics and unlocking the understanding of SVs in the genome at a level never seen before. It not only can detect nearly all variants that a karyotype can, but it can provide 10,000x higher resolution and does not require cell culture. Because of this, it is being adopted for oncology studies across hematological malignancies and solid tumors. This study demonstrates the performance of a new high throughput Stratys instrument for generation of optical genome map data at extraordinarily high coverage depth. With this instrument, 12 samples can be loaded at once, each loaded onto its own cartridge and the instrument can collect 400x genome coverage for each of these samples in 24 hours. The instrument has random access to the cartridges so that completed samples can be swapped out to facilitate optimal instrument run efficiency. To date, this system has been demonstrated to run 60 samples in a week, each at 400x coverage. Data from the instrument can be processed by Bionano Access™ and VIA™ software to call SVs, copy number variants (CNVs), regions of loss of heterozygosity (LOH), on a genome wide basis, and to classify those variants automatically according to guidelines such as the National Comprehensive Cancer Network (NCCN), World Health Organization (WHO), and National Health Services (NHS, United Kingdom). This new high throughput system with advanced bioinformatic data analysis has the potential to further transform structural variation analysis in cancer research. Citation Format: Alex R. Hastie, Pat Lynch. Genome wide, high-throughput, high-resolution structural variation detection at low variant allele fraction for oncology samples [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 6257.