Abstract

The standard-of-care (SOC) for genomic testing of myeloid cancers primarily relies on karyotyping and fluorescent in situ hydridization (FISH) (cytogenetic analysis) and targeted gene panels (≤54 genes) that harbor hotspot pathogenic variants (molecular genetic analysis). Both cytogenetic and molecular testing workup is necessary for the identification and detection of large structural variants (SVs) and small variants like single nucleotide variants (SNV) and indels, respectively. Despite this combinatorial approach, ∼50% of myeloid cancer genomes remain cytogenetically normal, and the limited sequencing variant profiles obtained from targeted panels are unable to resolve the genetic etiology of these myeloid tumors. In this study, we evaluated the performance and clinical utility of optical genome mapping (OGM) and a 523-gene next-generation sequencing (NGS) panel for comprehensive genomic profiling of 15 myeloid tumors and compared it to SOC cytogenetic methods (karyotyping and FISH) and a 54-gene NGS panel. OGM and the 523-gene NGS panel were found to have an analytical concordance of 100% with karyotyping, FISH, and the 54-gene panel, respectively. Additionally, OGM better characterized and resolved the structural variants previously reported by karyotyping in five cases, such as identifying the genomic content of marker and ring chromosomes. OGM also identified several additional translocations and eleven copy number variations (CNVs), of which the CNVs were validated/confirmed by the 523-gene panel. The 523-gene panel identified seven additional clinically relevant SNVs (two tier 1A variants and five tier 2C variants, as per the ACMG/AMP guidelines) in four cases. The simultaneous visualization of SVs and small NGS detected sequence variants (SNVs and small indels) from OGM and 523-gene NGS panel, respectively in the NxClinical software v6.1 identified two clinically relevant compound heterozygous events in two samples. This study demonstrates the higher sensitivity, resolution, accuracy, and ability to reveal cryptic and clinically relevant novel variants in myeloid cancers as compared to SOC methodologies. Our cost-effective approach of using OGM and a 523-gene NGS panel for comprehensive genomic profiling of myeloid cancers will not only increase the yield of actionable targets leading to improved clinical outcomes but also help resolve our ongoing conundrum of apparently genomically normal myeloid cancers by providing more answers.

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Abstract

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