Abstract 4895: Optical genome mapping analysis across multiple solid tumor types in Bionano VIATM software

Abstract

Abstract Solid tumors can show highly complex somatic structural and copy number variants (CNVs) of multiple classes. These variants can reveal mechanisms behind carcinogenesis, including the amplification of oncogenes, deletion or inactivation of tumor suppressor genes, and fusions to create new oncogenes. High degrees of heterogeneity within solid tumors can complicate analysis. Optical Genome Mapping (OGM) is a comprehensive technology which combines the resolution of molecular-level data with the scale of cytogenomic analysis. ≈5-15mg sections of freshly frozen tumor are homogenized in buffer to release ultra-high molecular weight DNA. Long fragments are then labeled at a regular 6mer, then linearized and imaged with native long-range structure (≥150kbp) preserved. In silico molecules are assembled into maps and aligned to a reference genome to detect structural variants with sensitivity to ≥5% allele fraction. Bionano VIATM software provides tools for visualization and interpretation of structural variants detected with OGM. VIA also provides CNV calling and detection of Absence of Heterozygosity (AOH) and allelic imbalance using SNP-FASST3, a segmentation algorithm for detecting mosaic events in OGM and other types of data. VIA calculates a B-Allele frequency (BAF) distribution from OGM data and adds a genome-wide BAF track to the applications suite, enabling calling of allelic imbalance events such as AOH. Visualized together, the overlay of structural variant information on copy number data provides context for chromosome fusions underlying copy number change. Additionally, balanced fusions are revealed consistently in cases where the impact is copy neutral. To demonstrate the utility of integrative analysis of structural, copy number, and allelic imbalance variants in solid tumor datasets, we processed a pilot set of six diverse solid tumors through Bionano software. Brain, breast, kidney, lung, ovarian, and prostate tumor data which had undergone previous analysis in Bionano Solve 3.7 were freshly analyzed in Solve 3.8 and VIA 7.0. In the lung tumor dataset there are clear allelic imbalance segments spanning most of chromosome 4 with no concomitant copy number change. In VIA, these segments can be merged on examination, converted to AOH calls, and further specified to reflect mosaic copy neutral loss of heterozygosity (CN-LOH). In the complex kidney tumor dataset, it is difficult to resolve ploidy state based on copy number data alone. This ambiguity is resolvable with VIA, by leveraging the copy number and BAF-based allelic imbalance distributions and recentering probes to a manually defined diploid region. The comprehensive OGM data approach facilitated by VIA can streamline analysis in challenging solid tumor datasets. Structural variant visualization, CNV detection and AOH detection are available in VIA 7.0. Citation Format: Samer I. Al-Saffar, Benjamin Clifford, Aliz Raksi, Alex Hastie, Neil Miller, Alka Chaubey. Optical genome mapping analysis across multiple solid tumor types in Bionano VIATM software [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 4895.