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medRxivGenetic & Genomic MedicinePreprint

Clinical Validation of Optical Genome Mapping for the Detection of Structural Variations in Hematological Malignancies

Andy Wing Chun PangiD, Karena A. Kosco, Nikhil SahajpaliD, Arthi Sridhar, Jen Hauenstein, Benjamin Clifford, Joey C. Estabrook, Alex ChitsazaniD, Trilochan Sahoo, M. Anwar IqbaliD, Ravindra B KolheiD, Gordana RacaiD, Alex R. HastieiD, Alka ChaubeyiD

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Abstract

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Standard-of-care (SOC) methods such as karyotyping and fluorescence in situ hybridization (FISH), employed globally for the past three decades have significant limitations in the resolution or the number of recurrent aberrations that can be simultaneously assessed, respectively. Next-generation sequencing (NGS) based technologies are now widely used to detect clinically significant sequence variants but are limited in their ability to accurately detect SVs. Optical genome mapping (OGM) is an emerging technology enabling the genome-wide detection of all classes of SVs at a significantly higher resolution than karyotyping and FISH. OGM neither requires cultured cells nor amplification of DNA and hence addresses the limitations of culture and amplification biases. This study reports the clinical validation of OGM as a laboratory developed test (LDT), according to CLIA guidelines, for genome-wide SV detection in different hematological malignancies. In total, 68 cases with hematological malignancies (of various subtypes), 27 controls and two cancer cell lines were used for this study. Ultra-high molecular weight DNA was extracted from the samples, fluorescently labeled, and run on the Bionano Genomics Saphyr system. A total of 207 datasets, including replicates, were generated and 100% could be analyzed successfully. Sample data were then analyzed using either disease specific or pan-cancer specific BED files to prioritize calls that are known to be diagnostically or prognostically relevant. Accuracy, precision, PPV and NPV were all 100% against standard of care results. Sensitivity, specificity, and reproducibility were 100%, 100% and 96%, respectively. Following the validation, 11 cases were run and analyzed using OGM at three additional sites. OGM found more clinically relevant SVs compared to SOC testing due to its ability to detect all classes of SVs at much higher resolution. The results of this validation study demonstrate OGMs superiority over traditional SOC methods for the detection of SVs for the accurate diagnosis of various hematological malignancies.

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