A framework for the clinical implementation of optical genome mapping in hematologic malignancies.

Optical Genome Mapping (OGM) is rapidly emerging as an exciting cytogenomic technology both for research and clinical purposes. In the last 2 years alone, multiple studies have demonstrated that OGM not only matches the diagnostic scope of conventional standard of care cytogenomic clinical testing but it also adds significant new information in certain cases. Since OGM consolidates the diagnostic benefits of multiple costly and laborious tests (e.g., karyotyping, fluorescence in situ hybridization, and chromosomal microarrays) in a single cost-effective assay, many clinical laboratories have started to consider utilizing OGM. In 2021, an international working group of early adopters of OGM who are experienced with routine clinical cytogenomic testing in patients with hematological neoplasms formed a consortium (International Consortium for OGM in Hematologic Malignancies, henceforth "the Consortium") to create a consensus framework for implementation of OGM in a clinical setting. The focus of the Consortium is to provide guidance for laboratories implementing OGM in three specific areas: validation, quality control and analysis and interpretation of variants. Since OGM is a complex technology with many variables, we felt that by consolidating our collective experience, we could provide a practical and useful tool for uniform implementation of OGM in hematologic malignancies with the ultimate goal of achieving globally accepted standards.

Detection of Genomic Structural Variations Associated with Drug Sensitivity and Resistance in Acute Leukemia.

Acute leukemia is a particularly problematic collection of hematological cancers, and, while somewhat rare, the survival rate of patients is typically abysmal without bone marrow transplantation. Furthermore, traditional chemotherapies used as standard-of-care for patients cause significant side effects. Understanding the evolution of leukemia to identify novel targets and, therefore, drug treatment regimens is a significant medical need. Genomic rearrangements and other structural variations (SVs) have long been known to be causative and pathogenic in multiple types of cancer, including leukemia. These SVs may be involved in cancer initiation, progression, clonal evolution, and drug resistance, and a better understanding of SVs from individual patients may help guide therapeutic options. Here, we show the utilization of optical genome mapping (OGM) to detect known and novel SVs in the samples of patients with leukemia. Importantly, this technology provides an unprecedented level of granularity and quantitation unavailable to other current techniques and allows for the unbiased detection of novel SVs, which may be relevant to disease pathogenesis and/or drug resistance. Coupled with the chemosensitivities of these samples to FDA-approved oncology drugs, we show how an impartial integrative analysis of these diverse datasets can be used to associate the detected genomic rearrangements with multiple drug sensitivity profiles. Indeed, an insertion in the gene MUSK is shown to be associated with increased sensitivity to the clinically relevant agent Idarubicin, while partial tandem duplication events in the KMT2A gene are related to the efficacy of another frontline treatment, Cytarabine.

Comparative Benchmarking of Optical Genome Mapping and Chromosomal Microarray Reveals High Technological Concordance in CNV Identification and Additional Structural Variant Refinement.

The recommended practice for individuals suspected of a genetic etiology for disorders including unexplained developmental delay/intellectual disability (DD/ID), autism spectrum disorders (ASD), and multiple congenital anomalies (MCA) involves a genetic testing workflow including chromosomal microarray (CMA), Fragile-X testing, karyotype analysis, and/or sequencing-based gene panels. Since genomic imbalances are often found to be causative, CMA is recommended as first tier testing for many indications. Optical genome mapping (OGM) is an emerging next generation cytogenomic technique that can detect not only copy number variants (CNVs), triploidy and absence of heterozygosity (AOH) like CMA, but can also define the location of duplications, and detect other structural variants (SVs), including balanced rearrangements and repeat expansions/contractions. This study compares OGM to CMA for clinically reported genomic variants, some of these samples also have structural characterization by fluorescence in situ hybridization (FISH). OGM was performed on IRB approved, de-identified specimens from 55 individuals with genomic abnormalities previously identified by CMA (61 clinically reported abnormalities). SVs identified by OGM were filtered by a control database to remove polymorphic variants and against an established gene list to prioritize clinically relevant findings before comparing with CMA and FISH results. OGM results showed 100% concordance with CMA findings for pathogenic variants and 98% concordant for all pathogenic/likely pathogenic/variants of uncertain significance (VUS), while also providing additional insight into the genomic structure of abnormalities that CMA was unable to provide. OGM demonstrates equivalent performance to CMA for CNV and AOH detection, enhanced by its ability to determine the structure of the genome. This work adds to an increasing body of evidence on the analytical validity and ability to detect clinically relevant abnormalities identified by CMA. Moreover, OGM identifies translocations, structures of duplications and complex CNVs intractable by CMA, yielding additional clinical utility.

Analytic Validation of Optical Genome Mapping in Hematological Malignancies.

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), which have been employed globally for the past three decades, have significant limitations in terms of resolution and 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 requires neither cultured cells nor amplification of DNA, addressing the limitations of culture and amplification biases. This study reports the clinical validation of OGM as a laboratory-developed test (LDT) according to stringent regulatory (CAP/CLIA) guidelines for genome-wide SV detection in different hematological malignancies. In total, 60 cases with hematological malignancies (of various subtypes), 18 controls, and 2 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 Saphyr system. A total of 215 datasets, Inc.luding replicates, were generated, and 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. Sensitivity, specificity, and reproducibility were 100%, 100%, and 96%, respectively. Following the validation, 14 cases and 10 controls were run and analyzed using OGM at three outside laboratories showing reproducibility of 96.4%. OGM found more clinically relevant SVs compared to SOC testing due to its ability to detect all classes of SVs at higher resolution. The results of this validation study demonstrate the superiority of OGM over traditional SOC methods for the detection of SVs for the accurate diagnosis of various hematological malignancies.

Characterization of the G protein-coupled receptor family SREB across fish evolution.

The SREB (Super-conserved Receptors Expressed in Brain) family of G protein-coupled receptors is highly conserved across vertebrates and consists of three members: SREB1 (orphan receptor GPR27), SREB2 (GPR85), and SREB3 (GPR173). Ligands for these receptors are largely unknown or only recently identified, and functions for all three are still beginning to be understood, including roles in glucose homeostasis, neurogenesis, and hypothalamic control of reproduction. In addition to the brain, all three are expressed in gonads, but relatively few studies have focused on this, especially in non-mammalian models or in an integrated approach across the entire receptor family. The purpose of this study was to more fully characterize sreb genes in fish, using comparative genomics and gonadal expression analyses in five diverse ray-finned (Actinopterygii) species across evolution. Several unique characteristics were identified in fish, including: (1) a novel, fourth euteleost-specific gene (sreb3b or gpr173b) that likely emerged from a copy of sreb3 in a separate event after the teleost whole genome duplication, (2) sreb3a gene loss in Order Cyprinodontiformes, and (3) expression differences between a gar species and teleosts. Overall, gonadal patterns suggested an important role for all sreb genes in teleost testicular development, while gar were characterized by greater ovarian expression that may reflect similar roles to mammals. The novel sreb3b gene was also characterized by several unique features, including divergent but highly conserved amino acid positions, and elevated brain expression in puffer (Dichotomyctere nigroviridis) that more closely matched sreb2, not sreb3a. These results demonstrate that SREBs may differ among vertebrates in genomic structure and function, and more research is needed to better understand these roles in fish.

Identification of Somatic Structural Variants in Solid Tumors by Optical Genome Mapping.

Genomic structural variants comprise a significant fraction of somatic mutations driving cancer onset and progression. However, such variants are not readily revealed by standard next-generation sequencing. Optical genome mapping (OGM) surpasses short-read sequencing in detecting large (>500 bp) and complex structural variants (SVs) but requires isolation of ultra-high-molecular-weight DNA from the tissue of interest. We have successfully applied a protocol involving a paramagnetic nanobind disc to a wide range of solid tumors. Using as little as 6.5 mg of input tumor tissue, we show successful extraction of high-molecular-weight genomic DNA that provides a high genomic map rate and effective coverage by optical mapping. We demonstrate the system's utility in identifying somatic SVs affecting functional and cancer-related genes for each sample. Duplicate/triplicate analysis of select samples shows intra-sample reliability but also intra-sample heterogeneity. We also demonstrate that simply filtering SVs based on a GRCh38 human control database provides high positive and negative predictive values for true somatic variants. Our results indicate that the solid tissue DNA extraction protocol, OGM and SV analysis can be applied to a wide variety of solid tumors to capture SVs across the entire genome with functional importance in cancer prognosis and treatment.

Accelerating medical research using the swift workflow system.

Both medical research and clinical practice are starting to involve large quantities of data and to require large-scale computation, as a result of the digitization of many areas of medicine. For example, in brain research - the domain that we consider here - a single research study may require the repeated processing, using computationally demanding and complex applications, of thousands of files corresponding to hundreds of functional MRI studies. Execution efficiency demands the use of parallel or distributed computing, but few medical researchers have the time or expertise to write the necessary parallel programs. The Swift system addresses these concerns. A simple scripting language, SwiftScript, provides for the concise high-level specification of workflows that invoke various application programs on potentially large quantities of data. The Swift engine provides for the efficient execution of these workflows on sequential computers, parallel computers, and/or distributed grids that federate the computing resources of many sites. Last but not least, the Swift provenance catalog keeps track of all actions performed, addressing vital bookkeeping functions that so often cause difficulties in large computations. To illustrate the use of Swift for medical research, we describe its use for the analysis of functional MRI data as part of a research project examining the neurological mechanisms of recovery from aphasia after stroke. We show how SwiftScript is used to encode an application workflow, and present performance results that demonstrate our ability to achieve significant speedups on both a local parallel computing cluster and multiple parallel clusters at distributed sites.