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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.

Certain cancer treatments, such as the poly (ADP-ribos) polymerase (PARP) inhibitors, have been shown to be effective in killing cancer cells exhibiting genome instability signatures indicative of homologous recombination deficiency (HRD). Hence, these signatures are used as biomarkers to inform treatment decisions and prognosis. There are three measurements of HRD signatures commonly employed: loss of heterozygosity (HRD-LOH), telomeric allelic imbalance (TAI) and large-scale state transition (LST). It has been shown that combining all three scores can better determine the HRD phenotype, leading to a higher clinical impact. Yet current HRD signature tests, used to estimate HRD, have low negative predictive value, and one possible reason is that current genomic technologies lack sensitivity to capture the full extent of somatic genomic rearrangements. Here, optical genome mapping (OGM) was used to detect large structural variants (SVs) and calculate a HRD score. OGM captures high molecular weight DNA to call SVs by aligning these molecules to the public reference genome. OGM can comprehensively detect insertions and deletions >5kbp, inversions, interchromosomal translocations, plus large interstitial copy number variation (CNV) and aneusomies. Subsequently, an automated script was developed to compute the HRD score, which is the summation of the three HRD signatures: HRD-LOH, the number of regions with a loss >15 Mbp but shorter than the whole chromosome; TAI, the number of regions of gain and loss >10Mbp that extend to a subtelomere but do not cross the centromere; and LST, the number of chromosomal breakpoints whose SV size >10Mb but not the whole chromosome. We applied this script on 20 samples of solid tumors and myeloid neoplasms, and the automated scores are concordant with expertly curated scores, confirming the validity of the calculation. We believe that OGM data combined with this automated analysis of HRD signatures is much more sensitive and accurate for detection of HRD signatures and that this will enable more precise prediction of drug response for multiple tumor types. Citation Format: Andy Wing Chun Pang, Kelsea Chang, Nikhil Sahajpal, Daniel Saul, Ravindra Kolhe, Alka Chaubey, Alex Hastie. Application of optical genome mapping to identify samples with homologous recombination deficiency [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 6539.

Cell lines have revolutionized scientific research as they are employed as primary tools in both basic and clinical research. Cell lines are extensively used to understand disease mechanisms, drug responses, drug metabolism, drug cytotoxicity, antibody production, vaccine development, gene function, generation of artificial tissues, synthesis of biological compounds, and develop transgenic preclinical models. However, the cells acquire additional genetic aberrations from the time the cell lines are established that might significantly impact the research for which the cell line is being used. The current methods to assess structural variants and copy number variants are limited in resolution (Karyotype), targeted (FISH), cannot detect balanced SVs (CMA), and cannot detect SVs in repetitive regions of the genome (NGS). Optical genome mapping (OGM) is an emerging next-generation cytogenenomics technology that can detect SVs including CNVs and complex rearrangements, using Saphyr platform that images ultra-long DNA molecules labelled at unique 6 base-pair motifs that span the entire genome, enabling genome-wide coverage and the ability to detect large SVs throughout the genome. In this study, we analyzed eight different cell lines that included seven cell lines of syndromes such as Fragile X (n=2), FSHD (n=2), DMD1 (n=1), Prader Willi (n=1), deafness (n=1), and one cell line for a transgenic mouse model. We have additionally analyzed 104 lymphoblast cell lines from the 1000 genomes project which do not have known clinical features. Briefly, ultra-high molecular weight DNA (150kb to >1Mb) was isolated from cultured cells using ~1.5 million cells as per manufacturer’s protocol, uniformly labeled at a specific 6-base sequence motif, and loaded into a cartridge, where the molecules were electrophoretically linearized and imaged multiple times using the Bionano Genomics Saphyr® platform. Using the captured images, a de novo genome map indicating the positions of the labels was constructed and compared to a reference genome to detect structural differences in the 2 maps. Chromosomal aberrations were detected by comparing optical maps to a reference and control dataset, and a coverage-based CNV calling was performed. In the present study, all eight cell lines were characterized with the concordance of reported genetic aberration in the syndromic cell lines. However, in the transgenic mouse cell line, several additional clinically pathogenic variants were detected in addition to the know variation. The study demonstrates the strength of OGM technology for detecting SVs and CNVs and its utility in the chromosomal characterization of cell lines that might significantly contribute towards accurate and reproducible research in a particular phenotype. Citation Format: Nikhil S. Sahajpal, Ashis K. Mondal, Alex Hastie, Alka Chaubey, Ravindra Kolhe. Utility of optical genome mapping for the chromosomal characterization of cell lines used in preclinical and clinical research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2933.

Guidelines from WHO, NCCN and others, for the genetic analysis of hematological malignancies included structural variation analysis. Traditionally, this has relied on a combination of three cytogenetic technologies for structural variation analysis: karyotyping, FISH, and microarray, are used to detect copy number variants, translocations, inversions. Next generation sequencing is also applied for mutation analysis but has not been successful for structural variation analysis. These traditional methods have many very manual aspects and require extensive expertise. Optical genome mapping (OGM) consolidates assays into a single laboratory assay in which the output provides the visualization of structural and copy number variants at one time. OGM is able to comprehensively detect structural variations genome wide down to 5% variant allele fraction for CNVs, inversions, and translocations from blood and bone marrow aspirates making it an attractive choice for hematologic malignancy genomic analysis. Preanalytical and analytical steps require approximately 4-5 days from sample to processed data with structural variation calls. Dynamic filtering in the user interface can be configured to remove most polymorphic variants and prioritize relevant variants. In addition, the OGM graphical user interface software, Bionano Access 1.7, allows for the user to assign classification/relevance to the variants for each case. For example, an ALL sample with t(9;22), deletion of CDKN2A, and whole chromosome gains of 4,6, and 10 can be easily visualized with the Circos plot and, then, can be further examined and annotated as needed. A second analyst can repeat the process blind to the first analysis and a supervisor can adjudicate the classifications. A variety of cases with hallmark abnormalities from various leukemias will be presented with the filtering and prioritization workflow used to derive them. This comprehensive technology allows for a quicker, more reliable output than traditional cytogenetic approaches. Citation Format: Jennifer Hauenstein, Andy Pang, Alka Chaubey, Alex Hastie. Optical genome mapping workflow for identification and annotation of variants in hematological diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2931.