Abstract
Cytogenetic analysis for hematological malignancies most often includes karyotyping, fluorescence in situ hybridization, and rarely, chromosomal microarray (CMA). While considered the gold standard, karyotyping and FISH have significant limitations in resolution of structural variants (SVs). CMA has a much higher resolution, but cannot detect balanced SVs, and is less commonly used in the hematologic oncology setting. Optical genome mapping (OGM) can detect all classes of SVs at high resolution (duplications, deletions, inversions, insertions, translocations), and as such, detects many copy number variants (CNVs) and SVs that have not been previously described. Although these novel SVs will help better describe genetic contributions to disease, analysis, interpretation and curation can take considerable time. A streamlined workflow has been developed for use with Bionano VIA™ software for a comprehensive analysis of relevant SVs in a hematological malignancy genome. First, by employing disease-specific decision trees for variants published in guidelines for those conditions, the software automatically flags Tier 1A variants detected according to ACMG/AMP/CGC criteria. Second, the overall genome complexity is assessed by observing chromosomal abnormalities detected by OGM. Large events (>5Mb) are counted, and complex genomes are assigned if there are more than 3 or 5 events, depending on the cancer type. Third, calls are further refined by filtering on a pan-cancer specific list to capture those variants that are then manually classified as Tier 1B or 2 by the analyst. The Bionano VIA software allows case-specific and disease subtype-specific information to be added to various sections within the software, such as the Knowledgebase, Event Table, and Sample Info fields to facilitate autopopulation of reportable data and interpretations into a formatted report template. Bionano VIA software can also accommodate multiple platforms simultaneously (e.g., NGS panels) to provide users with a comprehensive view of genomic aberrations relevant to hematological malignancies. This workflow is intended to streamline analysis and automate reporting of oncology samples, which can be extremely complex and often require extensive research.
Citation Format: Benjamin Clifford, Jen Hauenstien, Andy Wing Chun Pang, Rachel D. Burnside, Neil Miller, Alex Hastie, Alka Chaubey. Streamlined workflow for analyzing and reporting hematological malignancies in Bionano VIATM software [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2227.