Revealing Key Structural Variants in Hematological Malignancies

hematologic malignancies A revolution in cytogenomics driven by Optical Genome Mapping. key structural variants in Cytogenetics has a problem. Cytogeneticists are stuck in a cycle where—despite knowing that key pathogenic genomic variants must be present in hematological malignancy samples—they lack proper tools with the power to see many of them. Hematological malignancies are a major driver of cancer mortality and morbidity,1,2 and cytogenomic analysis is essential to understand the pathology of each case. The task, however, can be daunting, as finding key variants within a hematological malignancy is challenging. This challenge arises largely because the variants are undetectable with many common cytogenomic approaches.3,4 Traditionally, researchers in cytogenomics mix and match multiple methods, including karyotyping (KT), fluorescence in situ hybridization (FISH), and even microarrays. Together, this widely accepted cytogenomic standard slows cytogenecists down and reduces their discovery power. It’s clear that current technologies and workflows underperform when it comes to empowering researchers to move forward. Problems in the cytogenetic lab lead to problems in the clinic. Advances in genetic analysis can lead to a better understanding of disease etiology. However, without the right tools and workflows for studying structural and numerical variants, I fear that progress will likely be limited. Cytogeneticists deserve to have solutions that meet modern technological capabilities. The field is ready to move forward—to finally reveal critical variants that can drive progress in healthcare. At Bionano, our goal is to transform the way the world sees the genome in order to assist researchers as they lead the charge in the cytogenomic revolution and breathe fresh life into this critical field. Over the following pages, I hope it will become clear that the field is ready for a new paradigm and that optical genome mapping (OGM) provides the advancement that the cytogenomics field has long awaited. Together, with the skill and knowledge of cytogeneticists and our novel solutions, researchers can finally answer critical questions in biology and medicine and one day be a part of elevating the health of humans worldwise. The State of the Field Forward from Bionano President and Chief Executive Officer, Erik Holmlin, Ph.D. For Research Use Only. Not For Use In Diagnostic Procedures. 3 Table of Contents Section 1: Understanding Hematological Malignancies ...............................................................................................4 What are Hematological Malignancies?........................................................................................................................................................4 Main Types of Hematological Malignancies...............................................................................................................................................4 Section 2: Structural Variants and Hematological Malignancies............................................................................6 Cytogenomic Understanding is Key in Hematological Malignancies...............................................................................6 Structural Variants .............................................................................................................................................................................................................6 The Power of Hematological Malignancy Profiles ................................................................................................................................7 Guidelines for the Study of Hematological Malignancies.............................................................................................................7 Challenges in Profiling Pathogenic Structural Variants in Hematological Malignancies...............................8 Section 3: Limitations of Current Methods for Assessing Hematological Structural Variants..............9 Standard Methods Leave Significant Gaps.................................................................................................................................................9 Classical Methods for Identifying Structural Variants......................................................................................................................9 Alternative Structural Variant Approaches.................................................................................................................................................10 Technological Limitations Have Negative Consequences............................................................................................................11 Section 4: Optical Genome Mapping as a Transformative Solution.....................................................................12 What is OGM?.........................................................................................................................................................................................................................12 How Does OGM Work?....................................................................................................................................................................................................12 The Advantages of OGM..............................................................................................................................................................................................15 Operational Benefits of OGM...................................................................................................................................................................15 Clinical Research Benefits of OGM......................................................................................................................................................16 OGM Enhances SV Detection....................................................................................................................................................................21 OGM is the Next Revolution of Cytogenomics........................................................................................................................................26 Meet the Saphyr System, the Solution for Adding OGM to Your Research......................................................27 Transforming the Future of Cytogenomics with OGM.................................................................................................28 References................................................................................................................................................................................................29 For Research Use Only. Not For Use In Diagnostic Procedures. For Research Use Only. Not For Use In Diagnostic Procedures. 4 UNDERSTANDING HEMATOLOGICAL MALIGNANCIES What are Hematological Malignancies? Hematological malignancies are a complex and diverse set of cancers with origins in blood-forming cells. These devastating diseases have high mortality and morbidity rates,1,2 but understanding the genomic etiology of the disease can significantly improve outcomes. The key is to identify the underlying genomic abnormalities unique to each patient. SECTION 1: Main Types of Hematological Malignancies Hematopoietic stem cells • Chronic myeloid leukemia (CML) • Myeloproliferative neoplasms (MPNs) Myelofibrosis (MF) Polycythemia vera (PV) Essential thrombocythemia (ET) • Chronic myelomonocytic leukemia (CMML) and juvenile myelomonocytic leukemia (JMML) Myeloid precursors • Mylodysplastic syndromes (MDS) • Acute myeloid leukemia (AML) Various myeloid precursors or blast cells • Acute lymphoblastic leukemia (ALL) Lymphoid precursors Various lymphoid precursors or blast cells Lymphocytes B lymphocytes T lymphocytes Natural killer cells • Chronic lymphocytic leukemia (CLL) • B-cell non-Hodgkin lymphoma • Hairy cell leukemia • Hodgkin lymphoma • T-cell non-Hodgkin lymphoma • T-cell large granular lymphocytic (LGL) leukemia • NK-cell non-Hodgkin lymphoma • NK-cell large granular lymphocytic (LGL) leukemia • Myeloma Mature myeloid cells Plasma cells Figure 1. Adapted from the Leukemia Lymphoma Society.5 Hematological malignancies can arise from a variety of different stem and progenitor cells. A deeper understanding of the genetic etiology of hematological malignancies could lead to better personalized care and improved outcomes. For Research Use Only. Not For Use In Diagnostic Procedures. 5 A Significant Unmet Need Remains Despite significant research, there remains a significant gap in understanding hematological malignancies. 50% of tested samples fail to yield a meaningful result due to the low resolution of classical testing approaches.6-9 Clearly, more work is required to understand the genomic etiology of these diseases. Figure 2. Hematological malignancies are associated with a range of symptoms and treatment options. Global Symptoms Treatments Loss of appetite Chemotherapy Persistent fatigue Radiation Easy bruising or bleeding Stem cell transplants Weight loss Cell and immune therapies Weakness Targeted therapies The Realities of Hematological Malignancies Section 1 Summary: New tools and solutions are needed to advance clinical research of hematological malignancies, with the hope that a better understanding of the underlying genomic causes of a disease could, in the future, lead to more personalized treatment options and inform the development of new therapeutics. SECTION 1: UNDERSTANDING HEMATOLOGICAL MALIGNANCIES For Research Use Only. Not For Use In Diagnostic Procedures. 6 Structural Variants Structural variants (SVs) are large chromosomal aberrations that affect the order, orientation, quantity, and chromosomal location of functional elements of the genome, including genes, regulatory elements, and reading frames. While there is no definitive consensus on the minimum size of an SV, it is generally accepted that SVs range from approximately 1,000 base pairs (bp) to a full chromosome. In contrast to single nucleotide variants (SNVs), which refer to single base variants, SVs are larger and can encompass a wide range of structural changes, including copy number alterations.10 SVs can disrupt gene function and contribute to the onset of cancers and many other diseases.11,12 SVs are highly prevalent across hematological malignancies, including conditions like multiple myeloma (MM), chronic lymphocytic leukemia (CLL), and non-Hodgkin lymphoma (NHL).13 Hematological malignancies have an exceptionally high prevalence in pediatric populations. 13,14 STRUCTURAL VARIANTS AND HEMATOLOGICAL MALIGNANCIES Cytogenomic Understanding is Key in Hematological Malignancies Cytogenomics is essential for understanding the pathology and progression of hematological malignancies. However, many cytogenomic profiling approaches have inherent limitations that may miss actionable insights or make workflows cumbersome. Adding to this challenge is the massive quantity of cases that require genetic analysis and the rapid pace at which medical society guidelines change to include novel biomarkers. Here, we describe the current methodologies for cytogenomic profiling, including optical genome mapping (OGM), an innovative workflow that is revolutionizing the hematological malignancy profiling landscape. Throughout this eBook, we detail the advantages of OGM through real-world experiences supported by peer-reviewed publications. SECTION 2: “Structural variants are a very important type of variation in the human genome. And potentially they have been underestimated both in prevalence and in amount that they may explain disease cases.” Alexander Hoischen, Ph.D. Associate Professor, Genomic Technologies & Immuno-Genomics Radboud University Medical Center, Departments of Human Genetics and Internal Medicine For Research Use Only. Not For Use In Diagnostic Procedures. 7 The Power of Hematological Malignancy Profiles Structural and copy number variants are hallmarks of hematological malignancies, and biomedical research is an essential step toward understanding the pathology and progression of these conditions. Research that provides a deeper understanding of the profile of hematological malignancies may: • Result in an increase in the number of disease samples with meaningful findings • Provide faster time to genomic insights • Increase the accuracy of sample risk stratification analysis • Lead to advancements in healthcare Figure 3. Structural and copy number variants play a prominent role in hematological malignancies, and their detection is essential for furthering hematological research.15-17 Guidelines for the Study of Hematological Malignancies To perform cutting-edge hematological research, understanding up-to-date clinical guidelines, such as those issued by the National Comprehensive Cancer Network (NCCN) and the World Health Organization (WHO), is imperative. Societal guidelines often recommend testing for multiple structural variants in each hematological malignancy and subtype.18-20 These guidelines provide an important roadmap to assess the cancer case’s risk of progression and likely response to therapy, including targeted therapy. However, these guidelines change rapidly, making it difficult for methodologies to maintain pace with current standards. In particular, adapting biomarkers is challenging and expensive for traditional, probe-based approaches, such as FISH.18-20 Therefore, leading techniques in biomedical research must maintain flexibility to quickly adapt to changing clinical guidelines. Cytogenetic Testing is Essential in Hematological Malignancies • A major cause of hematological malignancies is the presence of chromosomal aberrations.15 • The detection of chromosomal aberrations yields insights into tumor pathogenesis.15 • In childhood and adolescent AML, chromosomal aberrations are often the only genome variants detected.16 • There are over 250 known recurrent chromosomal aberrations in hematological malignancies.17 Translocation Inversion Inseiion Repeat Duplicate Deletion SECTION 2: STRUCTURAL VARIANTS AND HEMATOLOGICAL MALIGNANCIES For Research Use Only. Not For Use In Diagnostic Procedures. 8 Challenges in Profiling Pathogenic Structural Variants in Hematological Malignancies Identifying chromosomal abnormalities within a hematological malignancy remains a complex undertaking.3,4 As outlined in the key research publications throughout this eBook, it can be challenging to reveal the large variety of structural and copy number variants present in hematological samples—from simple SVs, such as deletions, duplications, translocations, inversions, and aneusomies, to complex chromothripsis. In addition to their varying degrees of complexity, variants can span a wide spectrum of sizes (from hundreds to millions of base pairs) and allele fractions. It is imperative to have a comprehensive profile of all SV classes within a given sample to identify actionable insights and discover new impactful biomarkers rapidly. Thus, it is desirable for detection methods to handle a wide assortment of chromosomal presentations to provide accurate and valuable insights. Section 2 Summary: • Structural variants are prevalent across hematological malignancies. • Correctly identifying these variants is essential to modern hematological research. • Identifying variants is challenging with current approaches due to their inherent variety and complexity. Figure 4. There are a wide variety of structural variants, all of which need to be detected. Aneusomy Translocations Complex Rearrangements Interstitial Variants Copy Neutral Loss of Heterozygosity Inseiion Deletion Duplication Inversion Chromothripsis Chromoplexy Ring Chromosome SECTION 2: STRUCTURAL VARIANTS AND HEMATOLOGICAL MALIGNANCIES For Research Use Only. Not For Use In Diagnostic Procedures. 9 Standard Methods Leave Significant Gaps As discussed, identifying structural and copy number variants in hematological malignancies is essential. However, many of the standard methods in the cytogeneticist toolbox, such as karyotyping, FISH, and microarrays, have inherent limitations that can impede the identification of critical variants. Table 1. Overview and key limitations for various standard SV detection methods.6-9 Methodology Description Key Limitations Microscopic examination of the size, shape, and number of chromosomes that produces a genome-wide snapshot of gross genetic changes. Resolution: low resolution (5-20Mbp); many aberrations cannot be resolved visually Bias: vulnerable to culture and technician selection bias Complexity & Subjectivity: cumbersome workflow requires cell culture and expertly trained cytogeneticists Fluorescent probes hybridize with specific DNA sequences, allowing for visualization of targeted DNA regions. Not Scalable: only one aberration is investigated at a time Bias: requires a predetermined set of probes at predefined breakpoints and will miss any untargeted chromosomal alternations Comparative genomic hybridization and SNV microarrays that detect copy number gains and losses. Limited Scope: only CNVs detected, without structural context; unable to detect balanced rearrangements Accuracy: challenges resolving repeat-rich and duplicated regions along with single-copy gains Inconsistent: variable performance based on array platform and parameter optimization SECTION 3: LIMITATIONS OF CURRENT METHODS FOR ASSESSING HEMATOLOGICAL STRUCTURAL VARIANTS Multiple studies report that 50% of hematological malignancy samples fail to yield meaningful results.6-9 “The results of the study demonstrate that we are grossly under-evaluating the degree of genomic aberrations.”21 Rashmi Kanagal-Shamanna, MD Associate Professor, Department of Hematopathology The University of Texas MD Anderson Cancer Center Classical Methods for Identifying Structural Variants Karyotyping22–24 Microarrays26 Fluorescence In Situ Hybridization (FISH)25 50% Negative For Research Use Only. Not For Use In Diagnostic Procedures. 10 LIMITATIONS OF CURRENT METHODS FOR ASSESSING HEMATOLOGICAL STRUCTURAL VARIANTS Alternative Structural Variant Approaches Next-Generation Sequencing (NGS) NGS is a great approach for identifying small specific modifications, such as point mutations, but these techniques often fail to capture larger chromosomal abnormalities. NGS Methods for Profiling Structural Variants: • Whole genome sequencing27 • Targeted genomics panels28 Common Limitations of NGS Approaches29: • Expensive and technically challenging • Requires manual computational analysis and interpretation • May miss large-scale structural variations such as inversions, copy number alterations, and translocations • Targeted panels are biased and only assess a limited, predetermined region of the genome Figure 5. Current classical methods leave a critical gap in the detection of large-scale and often pathogenic SVs. • A genome-wide approach able to detect all classes of structural variants • High sensitivity for variants present at low fractions in complex samples Structural Variants (SVs) InDels SNVs Resolution Whole Chromosome 5 Mbp 500 kbp 50 kbp 5 kbp 500 bp 1 bp FISH (targeted) ARRAY (gains and losses only) KARYOTYPING OGM SEQUENCING What Hematopathology Researchers Need in a Detection Method A robust and efficient protocol with short turn-around-time • A simple and consolidated process for reporting variants SECTION 3: For Research Use Only. Not For Use In Diagnostic Procedures. 11 Technological Limitations Have Negative Consequences Current approaches limit the research community’s ability to accurately and efficiently characterize SVs, leading to poor overall detection rates.29 Combining multiple approaches is a workaround cytogeneticists use to compensate for the limitations of individual methods. However, this approach (Figure 6) results in complex and cumbersome workflows, which still often miss key variants, as detailed in the case studies highlighted in future sections across this eBook. “The primary reason that a lot of the structural variation has not been able to be detected in the past really comes from the limited resolution of the standard of care technologies.” Brynn Levy, MSc (Med), Ph.D., FACMG Professor, Department of Pathology and Cell Biology Columbia University Medical Center Figure 6. The limitations of current methodologies result in inefficient and inaccurate workflows that require time, money, and specialized expertise.29 Section 3 Summary: • Current approaches require complex integration of multiple techniques, resulting in costly, slow workflows. Even then, many variants are missed or unresolved due to limited resolution and bias. • Ultimately, these shortcomings present missed opportunities to further hematological research and find actionable insights.29 • A new approach to structural variant detection is required in hematology to find more actionable insights and modernize workflows. Typical turnaround time: up to 21 days Leukemias (AML, ALL, CML, CLL, etc.) Other Hematologic Neoplasms (MDS, MPN, Myelofibrosis, etc.) Lymphomas (NHL, HL, DBCL, etc.) Myelomas (MM, PCM) Repoi Repoi Repoi Repoi Interpretation Cell culture Karyotype Cell separation FISH FISH FISH FISH FISH FISH DNA extraction Microarray PCR SECTION 3: LIMITATIONS OF CURRENT METHODS FOR ASSESSING HEMATOLOGICAL STRUCTURAL VARIANTS For Research Use Only. Not For Use In Diagnostic Procedures. 12 What is OGM? Optical Genome Mapping (OGM) is a powerful new workflow for studying structural and copy number variants that the hematological malignancy research community needs to modernize. OGM combines high-resolution imaging with advanced analytical analysis to provide genome-wide coverage of structural and copy number variants.30 This paradigm-shifting technique uses ultra-high molecular weight DNA, single molecule imaging, nanotechnology, plus advanced computational analysis to detect all classes of structural and copy number variants in a single, unbiased, and highly efficient assay.31–33 OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION How Does OGM Work? OGM is a workflow that combines several steps to facilitate visualization and analysis. At a high level, OGM begins by purifying ultra-high molecular DNA to maintain native long-range structure. Then DNA is labeled with fluorophores that bind a motif repeatedly found throughout the genome and linearized in nanochannel arrays. Advanced analytical software uses the fluorescent signals to resolve high-resolution genomic structures from the resulting digitized optical data. Figure 7. OGM is a next-generation workflow that improves the detection of structural and copy number variants. Because OGM spans the full genome, this method is an unbiased and efficient approach to profile actionable structural variants. SECTION 4: Optical Genome Mapping: Transforming the Way Cytogenetics See the Genome • Spans the full genome • Combines high resolution with digital analysis • Unbiased workflow that can detect all classes of SV along with numerical variants, including: • Aneuploidy • Deletion • Duplication • Amplification • Inversion • Translocation • Loss of heterozygosity • Complex rearrangements “I feel OGM is a perfect technology to bridge the gap between the traditional cytogenetic technologies to identify structure variants and the molecular technologies to identify aberrations at [the] single base pair level.” Rashmi Kanagal-Shamanna, MD Associate Professor, Department of Hematopathology The University of Texas MD Anderson Cancer Center For Research Use Only. Not For Use In Diagnostic Procedures. 13 Unlike other methods that require extensive cell culture, OGM is compatible with a variety of primary cell and tissue types, including: • Blood • Bone marrow aspirate • Cultured cells • Tissue • Tumor Sample Prep Genome Mapping Data Analysis Ultra-high molecular weight isolation and labeling with Prep Kits Sample loaded on the Bionano Saphyr® Chip DNA molecules linearization and imaging in the Saphyr® Instrument From raw data to final repoi, through Bionano SolveTM, AccessTM, and VIATM Soƒware Final Repoi Leukemias (AML, ALL, CML, CLL, etc.) Other Hematologic Neoplasms (MDS, MPN, Mylelofibrosis, etc.) Lymphomas (NHL, HL, DBCL, etc.) Myelomas (MM, PCM) Total processing time: 3-5 days OGM Workflow Figure 8. The OGM workflow efficiently and accurately resolves all SV types across samples. Learn more about how OGM works SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 14 OGM Karyotyping FISH CMA NGS Resolution for Structural Variant Detection Min. SV size: 5kb (>500bp for germline variants) >5 to 10 Mbp >100 to 200 kbp >50 to 100 kbp 1 to ~500bp (short-read) 1bp to ~10kb (long-read) Detection Bias Unbiased Unbiased Single, targeted probe Design bias Sequence bias Average Turn-AroundTime <1 week 1-2 weeks 3-5 days <1 week Variable Subjectivity of Analysis Unbiased Technician bias Technician bias Unbiased Analysis pipeline bias OGM Performance Capabilities OGM provides high-resolution for structural variant detection across hematological malignancies. Table 3. High-resolution and sensitivity of OGM across hematological malignancies.34 Cancer Analysis Application Data Collected 1.5 Tbp Raw Coverage Tier 400x Effective Coverage ≥300x Variant Allele Fraction ≥5% Resolution by variant type at >90% sensitivity Insertions ≥5 kbp Deletions ≥7 kbp Duplications ≥150 kbp Translocations ≥70 kbp Inversions ≥70 kbp Table 2. OGM is an improvement over alternative methods. SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 15 The Advantages of OGM OGM is already transforming the hematological malignancy landscape by streamlining workflows, uncovering novel, actionable variants, and resolving previously unclear pathologies where other technologies were unable to do so. Operational Benefits of OGM OGM radically simplifies the cytogenomic process. Instead of integrating multiple complex, subjective, and technically challenging tests, researchers can use a single OGM assay and achieve greater efficiency. Consolidating methods provides many operational benefits for users, such as: • Reduced hands-on time • Faster time to actionable results • Cost savings associated with running fewer assays • Simplified operations and training “I think the core benefit of OGM is that it combines three technologies in one. So it offers the opportunity to replace Karyotype, FISH and microarrays all in one assay. So as such, our workflow in the laboratory may become much more standardized and easy.” Alexander Hoischen, Ph.D. Associate Professor, Genomic, Technologies and Immuno-Genomics Radboud University Medical Center, Departments of Human Genetics and Internal Medicine OGM has other operational benefits, including compatibility with multiple sample types, an inherently unbiased workflow, and reduced overall complexity. OGM is an approachable method that can provide a robust, easy-to-use solution for every lab member. Figure 9. OGM consolidates multiple complex workflows into one approachable assay. Karyotyping Microarray FISH OGM SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 16 Clinical Research Benefits of OGM OGM goes beyond simply consolidating workflows to aid operational logistics. In fact, OGM shows great potential for enhancing clinical research by aiding in the detection of structural and copy number variants beyond those identified with alternative methods.21,35 There is a preponderance of evidence supporting the ability of OGM to match alternative methods.36 In addition to OGM’s high concordance with leading detection practices, evidence also suggests OGM is capable of detecting structural and copy number variants that these methods routinely fail to detect.21,35-39 Unlike alternative methods, which are often limited in their ability (Table 1), OGM can reliably resolve all classes of structural and copy number variants, including complex SVs. “30% of previously unsolved cases for B-ALL, which previously underwent karyotype + FISH + microarray + NGS, were solved using OGM.” Gordana Raca, MD, Ph.D., FACMG40 Director of Clinical Cytogenomics, Center for Personalized Medicine Department of Pathology and Lab Medicine Children’s Hospital Los Angeles Professor, Clinical Pathology Keck School of Medicine at the University of Southern California Figure 10. The advantages of OGM workflows have direct implications for laboratory operations. OGM Advantage Operational Advantage Compatibility with multiple sample types Simpler, consolidated workflow, leading to multiple efficiencies One method for all structural and numerical variant classes Unbiased, whole-genome, high-resolution digital analysis, powered by complete data analysis software Saved time and less subjectivity Single workflow and consolidated technology Simpler training SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION 17 This ability to identify pathogenic and actionable structural and copy number variants can be traced back to the same features that provide extensive operational benefits — its unbiased, whole-genome, modern approach. The power of OGM has the potential for paradigm-shifting clinical implications for the future of hematological malignancies. Clinical research using OGM may lead to solutions that help solve unresolved cases across hematological malignancies, improve risk stratification, and ultimately result in better patient outcomes. Figure 11. The advantages of OGM workflows have direct implications for clinical research. OGM Advantage Clinical Research Advantage Robust, reliable, and accurate structural and copy number variant detection High concordance with classical methods Unbiased screening across the entire genome Detection of novel variants Higher resolution and sensitivity More actionable insights Greater sample stratification capabilities More accurate stratification and prognostic risk assessment 100% “With OGM we are changing subjectivity to objectivity in going from a visual microscope-based karyotype to a high-resolution digital output.” Adam C. Smith, Ph.D., FCCMG, FACMG, erCLG SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. For Research Use Only. Not For Use In Diagnostic Procedures. 18 Figure 12. OGM encompasses many of the benefits of classical cytogenetic methods with the additional ability to detect variants missed by other methods. OGM Shows High Concordance with Other Methods Studies have shown that OGM has high concordance with traditional methods such as karyotyping and FISH.21,35-39 Additionally, OGM has the resolution to identify large-scale structural and copy number variants that NGS approaches struggle to recognize.21,35 Taken together, these characteristics position OGM as a premier solution to identifying all SV classes with accuracy and efficiency. Provides the ability to detect what is in classical cytogenetics while expanding detection to reveal incremental pathogenic findings with high resolution. Optical Genome Mapping Classical Cytogenetic Approaches BLOOD ADVANCES OGM not only matches classical technologies but has the power to uncover additional relevant variants in 13% of cases. Optical Genome Mapping in Acute Myeloid Leukemia: A Multicenter Evaluation37 OGM was 100% concordant with standard methods when evaluating a cohort of 100 acute myeloid leukemia (AML) cases. In 13% of cases, OGM identified additional and often actionable pathogenic findings. KEY PUBLICATION 1 SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION 19 Figure 13. Adapted from Sahajpal et al., 2022.41 OGM provided high concordance with traditional methods. OGM Resulted In: accuracy specificity sensitivity 99.2% 100% 98.7% JOURNAL OF MOLECULAR DIAGNOSTICS OGM represents a viable alternative to classical methods, providing high concordance and improved pathogenic insights. Clinical Validation and Diagnostic Utility of Optical Genome Mapping for Enhanced Cytogenomic Analysis of Hematological Neoplasms.41 An analysis of 69 well-characterized, unique samples with OGM resulted in high concordance with 99.2% accuracy, 100% specificity, and 98.7% sensitivity, compared to classical methods. OGM analysis also identified several SVs that other approaches missed. KEY PUBLICATION 2 Plus incremental pathogenic SV findings. SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. For Research Use Only. Not For Use In Diagnostic Procedures. 20 Cohort Size Clinical Referral Number of Abnormalities Included (Classical Methods) Concordance with Cytogenetic Results University of Oulo42 18 CLL 16 100% Multi-site AML Consortium37 100 AML 190 98.4% Augusta, Emory41 69 CLL, AML, MDS, MM, lymphoma, PCM, CML, ET and others 164 99% M.D. Anderson21 101 MDS 194 99% CHU Amiens43 10 B and T ALL 78 97% Johns Hopkins University44 5 Leukemia/Lymphoma and Solid Tumors 30 100% University Hospital Olomouc45 11 Multiple myeloma 172 98% Radbound University36 48 AML, MDS, CML, CLL, ALL, MM, MPN, T-PLL, LYBM 112 100% Table 4. Numerous studies validate OGM’s excellent concordance with other approaches. 8 7 6 5 4 3 2 1 SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 21 OGM Enhances SV Detection Many studies suggest that OGM finds structural and copy number variants that were missed by other approaches and frequently identifies novel SVs.21,35 Figure 14. When OGM is used, novel pathogenic SV findings are often detected. KEY PUBLICATION 3 LEUKEMIA OGM can improve the identification of pathogenic variants. High-Resolution Structural Variant Profiling of Myelodysplastic Syndromes by Optical Genome Mapping Uncovers Cryptic Aberrations of Prognostic and Therapeutic Significance.21 OGM detected 383 significant, recurrent, and novel SVs — nearly twice as many SVs as chromosome banding analysis (CBA). Of the 383 clinically significant aberrations, more than half were cryptic to CBA. (Figure 15, below). OGM led to incremental pathogenic findings in: of samples 34% Yang et al., 2022 13% Levy et al., 2023 of samples Balducci et al., 2022 of samples 33-54% SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 22 OGM detected twice as many SVs as traditional methods Yang et al., 2022 Figure 16. When OGM is used, novel SV findings are often detected, compared to traditional methods. OGM led to overall 31% more SVs detected, compared to KT and FISH Gerding et al., 2022 Figure 15. Adapted from Yang et al., 2022.21 Comparison between the results of conventional cytogenetics, specifically chromosomal banding analysis (CBA) and optical genome mapping (OGM). OGM detected nearly twice as many SVs as CBA. Conventional cytogenetics Optical genome mapping 1 2 3 4 6 7 8 5 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X Y 1 2 3 4 6 7 8 5 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X Y SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 23 OGM Has the Ability to Better Resolve Complex Karyotypes Cytogenetic methods such as FISH and karyotyping struggle to resolve many complex SVs, such as novel fusions and chromothripsis and fail to compensate for inherent genome complexity.46 These limitations leave critical actionable SVs undiscovered. OGM, with its genome-wide approach and digital precision, can confidently and consistently profile challenging SVs.37 “OGM reveals more of what matters: more clinically relevant SVs, leading to higher success rates and resolution of unsolved cases.” Laïla El-Khattabi, MD Hôpitaux de Paris (AP-HP)-Université de Paris KEY PUBLICATION 4 THE AMERICAN JOURNAL OF HUMAN GENETICS OGM resulted in a more complete assessment than other single assays and has the potential to replace classical cytogenetic approaches and rapidly map novel leukemic drivers. Next-Generation Cytogenetics: Comprehensive Assessment of 52 Hematological Malignancy Genomes by Optical Genome Mapping.36 Samples from 52 individuals with hematological malignancies were processed. OGM detected 19 novel gene fusions and revealed higher complexity than previously recognized. SCIENTIFIC REPORTS OGM has the potential to resolve complex genomic architectures in hematological malignancies. Whole-Genome Optical Mapping of Bone-Marrow Myeloma Cells Reveals Association of Extramedullary Multiple Myeloma with Chromosome 1 Abnormalities.45 This study used OGM to refine large intrachromosomal rearrangements on chromosome 1 and associate them with extramedullary progression. KEY PUBLICATION 5 SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 24 Figure 17. Optical genome mapping can resolve many classes of structural variants, including complex variants such as complex rearrangements and abnormal ploidies. KEY PUBLICATION 6 CANCERS OGM is a powerful approach to characterize complex karyotypes with improved resolution. TP53 Abnormalities are Underlying the Poor Outcome Associated with Chromothripsis in Chronic Lymphocytic Leukemia Patients with Complex Karyotype.46 OGM was used to study the genomic complexity of chronic lymphocytic leukemia patients with chromothripsis. OGM characterized these complex karyotypes and improved the resolution of chromothripsis. Complex Rearrangements Multiple clustered fusions within and between chromosome 15 and 17, with copy number losses and focal amplifications Abnormal Ploidy Copy neutral loss of heterozygosity, in multiple chromosomes with baseline CN Copy number gain and aneusomy; multiple chromosomes with CN=4 SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION OGM Has the Potential to Improve Risk Stratification As demonstrated in many published studies, OGM exceeds the current detection standard for hematological malignancies. Improved detection has the potential to provide profound implications in the future for improving risk stratification.21,35,37,38 25 “The more data we can get, the more informed decisions we can make, and optical genome mapping provides an amount of data that isn’t available through other techniques.” Ravindra Kolhe, MD, Ph.D., FCAP Professor and Interim Chair, Pathology Associate Dean, Translational Research Associate Director, Genomics, Georgia Cancer Center Leon Henri Charbonnier Endowed Chair of Pathology Medical College of Georgia KEY PUBLICATION 7 AMERICAN JOURNAL OF HEMATOLOGY OGM increased the detection rate and cytogenetic resolution and may provide better sample stratification and inform more accurate understanding. Optimizing the Diagnostic Workflow for Acute Lymphoblastic Leukemia by Optical Genome Mapping.47 Here, the authors analyzed 41 acute lymphoblastic leukemia cases and found that OGM identified all recurrent copy number alternations and structural variants, and for 8% of samples, OGM findings resulted in a change in ELN or R-IPSS score. SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. For Research Use Only. Not For Use In Diagnostic Procedures. 26 Section 4 Summary: • OGM is a completely new approach for studying structural and copy number variants that combines high-resolution imaging with advanced analysis. • OGM provides operational and clinical research advantages, such as efficient and cost-effective workflows, genome-wide coverage, and detection of all classes of structural and copy-number variants. • OGM is highly concordant with classical methods while enhancing variant detection. OGM is the Next Revolution in Cytogenomics OGM meets the current standards of cytogenomics while filling the gaps left by traditional methods. Unlike approaches such as karyotyping and FISH, OGM provides an objective, high-resolution view of the genome. OGM also provides the structural resolution required to identify structural and copy number variants often missed by NGS. As cytogenomics continues to move forward, the capabilities and advantages of OGM stand out as a powerful solution for researchers. Figure 18. The advantages of OGM for hematological cytogenomic profiling. OGM Improves Cytogenomic Profiling Reduced Complexity of Workflows • Cost savings associated with fewer testing methods and assays • Reduction of turn around time • Removal of subjective, biased methods from analysis Improved Performance Compared to Classical Methods • High concordance with classical cytogenetic methods • Better characterization and resolution of SVs • Discovery of novel SVs SECTION 4: OPTICAL GENOME MAPPING AS A TRANSFORMATIVE SOLUTION For Research Use Only. Not For Use In Diagnostic Procedures. 27 Meet the Saphyr® System, the Solution for Adding OGM to Your Research Bionano’s OGM workflow allows researchers to go from sample-to-answer in as few as 3 to 5 days. Streamline time to results and achieve comprehensive cytogenomic data efficiently with the Saphyr system from Bionano. The Saphyr system brings cytogenomics into the modern age with genome-wide coverage and digital precision. Bionano’s Saphyr system provides researchers with an end-to-end solution at their fingertips. Teams can seamlessly generate and analyze data with an intuitive and optimized workflow. Speak to a specialist to learn more about OGM and how it can fit into your lab. Simple Preparation (SP and DLS reagent kits) OGM Data Generation (the Saphyr instrument) Data Analysis and Interpretation (Access, Solve, and Via software) 1–3 days 2–3 days For Research Use Only. Not For Use In Diagnostic Procedures. 28 Transforming the Future of Cytogenomics with OGM The future of cytogenomics is bright with Bionano. Researchers can consolidate their process from cumbersome, multi-method integrations into a seamless, end-to-end OGM workflow. The straightforward OGM approach empowers teams to optimize their time, creating efficiencies where other methods create challenges. Not only does OGM simplify workflows for teams, but it also increases genomic insights. OGM has repeatedly demonstrated its ability to exceed standard methods. It is no wonder OGM bridges the gaps left by other approaches — OGM is an objective, unbiased, whole-genome method with digital precision. With OGM in their toolkit, researchers will find new structural and copy-number variants with a lower cost and operational burden. “The things we can do using this technology, the discoveries, the identification of biomarkers, prognostication, improving therapy, identifying targets, [they’re] endless. The potential is endless, and I’m super excited to work with this in the future.” Rashmi Kanagal-Shamanna, MD Associate Professor, Department of Hematopathology The University of Texas MD Anderson Cancer Center For Research Use Only. Not For Use In Diagnostic Procedures. 29 References 1. World Cancer Research Fund International. Worldwide Cancer Data. Accessed July 24, 2023. https://www.wcrf.org/ cancer-trends/worldwide-cancer-data/ 2. National Cancer Insitute. Surveillance, Epidemiology, and End Results Program. Accessed July 24, 2023. https:// seer.cancer.gov/ 3. Pang AW, MacDonald JR, Pinto D, et al. Towards a comprehensive structural variation map of an individual human genome. Genome Biol. 2010;11(5):R52. doi:10.1186/gb-2010-11-5-r52 4. Prakash G, Kaur A, Malhotra P, et al. Current role of genetics in hematologic malignancies. Indian J Hematol Blood Transfus. 2016;32(1):18-31. doi:10.1007/s12288-015-0584-4 5. Leukemia & Lymphoma Society. Where do Blood Cancers Develop? October 2019. Accessed October 12, 2023. https://www.lls.org/sites/default/files/National/USA/Pdf/Publications/PS104_CancerOriginsChart_2019final.pdf 6. Tsui SP, Ip HW, Saw NY, et al. Redefining prognostication of de novo cytogenetically normal acute myeloid leukemia in young adults. Blood Cancer J. 2020;10(10):104. doi:10.1038/s41408-020-00373-4 7. Nimer SD. Is it important to decipher the heterogeneity of “normal karyotype AML”? Best Pract Res Clin Haematol. 2008;21(1):43-52. doi:10.1016/j.beha.2007.11.010 8. Walker A, Marcucci G. Molecular prognostic factors in cytogenetically normal acute myeloid leukemia. Expert Rev Hematol. 2012;5(5):547-558. doi:10.1586/ehm.12.45 9. Seo GH, Lee H, Lee J, et al. Diagnostic performance of automated, streamlined, daily updated exome analysis in patients with neurodevelopmental delay. Mol Med. 2022;28(1):38. doi:10.1186/s10020-022-00464-x 10. National Center for Biotechnology Information. Overview of Structural Variation. January 21, 2022. Accessed June 8, 2023. https://www.ncbi.nlm.nih.gov/dbvar/content/overview/#:~:text=Structural%20variation%20(SV)%20is%20generally, copy%20number%20variants%20(CNVs). 11. Weischenfeldt J, Symmons O, Spitz F, Korbel JO. Phenotypic impact of genomic structural variation: insights from and for human disease. Nat Rev Genet. 2013;14(2):125-138. doi:10.1038/nrg3373 12. Beroukhim R, Mermel CH, Porter D, et al. The landscape of somatic copy-number alteration across human cancers. Nature. 2010;463(7283):899-905. doi:10.1038/nature08822 13. Tietsche de Moraes Hungria V, Chiattone C, Pavlovsky M, et al. Epidemiology of Hematologic Malignancies in Real-World Settings: Findings From the Hemato-Oncology Latin America Observational Registry Study. J Glob Oncol. 2019;5:1-19. doi:10.1200/JGO.19.00025 14. Leukemia & Lymphoma Society. CHILDHOOD AND ADOLESCENT BLOOD CANCER FACTS AND STATISTICS. Accessed June 8, 2023. https://www.lls.org/facts-and-statistics/childhood-and-adolescent-blood-cancer-facts-and-statistics 15. Schütte J, Reusch J, Khandanpour C, Eisfeld C. Structural variants as a basis for targeted therapies in hematological malignancies. Front Oncol. 2019;9:839. doi:10.3389/fonc.2019.00839 16. Tarlock K, Zhong S, He Y, et al. Distinct age-associated molecular profiles in acute myeloid leukemia defined by comprehensive clinical genomic profiling. Oncotarget. 2018;9(41):26417-26430. doi:10.18632/oncotarget.25443 17. Fukuhara S, Oshikawa-Kumade Y, Kogure Y, et al. Feasibility and clinical utility of comprehensive genomic profiling of hematological malignancies. Cancer Sci. 2022;113(8):2763-2777. doi:10.1111/cas.15427 18. Arber DA, Orazi A, Hasserjian RP, et al. International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data. Blood. 2022;140(11):1200-1228. doi:10.1182/blood.2022015850 For Research Use Only. Not For Use In Diagnostic Procedures. 30 References 19. Döhner H, Wei AH, Appelbaum FR, et al. Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. Blood. 2022;140(12):1345-1377. doi:10.1182/blood.2022016867 20. Khoury JD, Solary E, Abla O, et al. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms. Leukemia. 2022;36(7):1703-1719. doi:10.1038/s41375-022-01613-1 21. Yang H, Garcia-Manero G, Sasaki K, et al. High-resolution structural variant profiling of myelodysplastic syndromes by optical genome mapping uncovers cryptic aberrations of prognostic and therapeutic significance. Leukemia. 2022;36(9): 2306-2316. doi:10.1038/s41375-022-01652-8 22. O’Connor C. Karyotyping. Nature Education. 2008. Accessed June 8, 2023. https://www.nature.com/scitable/topicpage/ karyotyping-for-chromosomal-abnormalities-298/ 23. Cooley LD, Morton CC, Sanger WG, Saxe DF, Mikhail FM. Section E6.5-6.8 of the ACMG technical standards and guidelines: chromosome studies of lymph node and solid tumor-acquired chromosomal abnormalities. Genet Med. 2016;18(6):643-648. doi:10.1038/gim.2016.51 24. Wan TSK. Cancer cytogenetics: methodology revisited. Ann Lab Med. 2014;34(6):413-425. doi:10.3343/alm.2014.34.6.413 25. O’Connor C. Fluorescence In Situ Hybridization (FISH). Nature Education. 2008. Accessed June 7, 2023. https://www.nature. com/scitable/topicpage/fluorescence-in-situ-hybridization-fish-327/ 26. Alkan C, Coe BP, Eichler EE. Genome structural variation discovery and genotyping. Nat Rev Genet. 2011;12(5):363-376. doi:10.1038/nrg2958 27. Wheeler MM, Stilp AM, Rao S, et al. Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program. Nat Commun. 2022;13(1):7592. doi:10.1038/s41467-022-35354-7 28. Singhal D, Hahn CN, Feurstein S, et al. Targeted gene panels identify a high frequency of pathogenic germline variants in patients diagnosed with a hematological malignancy and at least one other independent cancer. Leukemia. 2021;35(11):3245-3256. doi:10.1038/s41375-021-01246-w 29. Akkari YMN, Baughn LB, Dubuc AM, et al. Guiding the global evolution of cytogenetic testing for hematologic malignancies. Blood. 2022;139(15):2273-2284. doi:10.1182/blood.2021014309 30. Barseghyan H, Tang W, Wang RT, et al. Next-generation mapping: a novel approach for detection of pathogenic structural variants with a potential utility in clinical diagnosis. Genome Med. 2017;9(1):90. doi:10.1186/s13073-017-0479-0 31. Zhang S, Pei Z, Lei C, et al. Detection of cryptic balanced chromosomal rearrangements using high-resolution optical genome mapping. J Med Genet. 2023;60(3):274-284. doi:10.1136/jmedgenet-2022-108553 32. Sahajpal NS, Barseghyan H, Kolhe R, Hastie A, Chaubey A. Optical Genome Mapping as a Next-Generation Cytogenomic Tool for Detection of Structural and Copy Number Variations for Prenatal Genomic Analyses. Genes (Basel). 2021;12(3). doi:10.3390/genes12030398 33. Mantere T, Neveling K, Pebrel-Richard C, et al. Optical genome mapping enables constitutional chromosomal aberration detection. Am J Hum Genet. 2021;108(8):1409-1422. doi:10.1016/j.ajhg.2021.05.012 34. Bionano Genomics. Bionano Solve Theory of Operation: Structural Variant Calling. Accessed September 25, 2023. https:// bionanogenomics.com/wp-content/uploads/2018/04/30110-Bionano-Solve-Theory-of-Operation-Structural-Variant- Calling.pdf 35. Balducci E, Kaltenbach S, Villarese P, et al. Optical genome mapping refines cytogenetic diagnostics, prognostic stratification and provides new molecular insights in adult MDS/AML patients. Blood Cancer J. 2022;12(9):126. doi:10.1038/ s41408-022-00718-1 For Research Use Only. Not For Use In Diagnostic Procedures. 31 References 36. Neveling K, Mantere T, Vermeulen S, et al. Next-generation cytogenetics: Comprehensive assessment of 52 hematological malignancy genomes by optical genome mapping. Am J Hum Genet. 2021;108(8):1423-1435. doi:10.1016/j.ajhg.2021.06.001 37. Levy B, Baughn LB, Akkari Y, et al. Optical genome mapping in acute myeloid leukemia: a multicenter evaluation. Blood Adv. 2023;7(7):1297-1307. doi:10.1182/bloodadvances.2022007583 38. Gerding WM, Tembrink M, Nilius-Eliliwi V, et al. Optical genome mapping reveals additional prognostic information compared to conventional cytogenetics in AML/MDS patients. Int J Cancer. 2022;150(12):1998-2011. doi:10.1002/ijc.33942 39. Puiggros A, Ramos-Campoy S, Kamaso J, et al. Optical genome mapping: A promising new tool to assess genomic complexity in chronic lymphocytic leukemia (CLL). Cancers (Basel). 2022;14(14). doi:10.3390/cancers14143376 40. Raca G, Kovach AE, Doan A, et al. 10. Capture-based transcriptome sequencing (RNA-Seq) and optical genome mapping (OGM) enhance detection of newly described molecular subtypes of pediatric B-lymphoblastic leukemia (B-ALL). Cancer Genet. 2022;264-265:4. doi:10.1016/j.cancergen.2022.05.013 41. Sahajpal NS, Mondal AK, Tvrdik T, et al. Clinical validation and diagnostic utility of optical genome mapping for enhanced cytogenomic analysis of hematological neoplasms. J Mol Diagn. 2022;24(12):1279-1291. doi:10.1016/j.jmoldx.2022.09.009 42. Valkama A, Vorimo S, Kumpula TA, et al. Optical Genome Mapping as an Alternative to FISH-Based Cytogenetic Assessment in Chronic Lymphocytic Leukemia. Cancers (Basel). 2023;15(4). doi:10.3390/cancers15041294 43. Lestringant V, Duployez N, Penther D, et al. Optical genome mapping, a promising alternative to gold standard cytogenetic approaches in a series of acute lymphoblastic leukemias. Genes Chromosomes Cancer. 2021;60(10):657-667. doi:10.1002/gcc.22971 44. Stinnett V, Jiang L, Haley L, et al. 7. Adoption of optical genome mapping in clinical cancer cytogenetic laboratory: A stepwise approach. Cancer Genet. 2022;260-261:3. doi:10.1016/j.cancergen.2021.05.021 45. Kriegova E, Fillerova R, Minarik J, et al. Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities. Sci Rep. 2021;11(1):14671. doi:10.1038/s41598-021- 93835-z 46. Ramos-Campoy S, Puiggros A, Kamaso J, et al. TP53 Abnormalities Are Underlying the Poor Outcome Associated with Chromothripsis in Chronic Lymphocytic Leukemia Patients with Complex Karyotype. Cancers (Basel). 2022;14(15). doi:10.3390/cancers14153715 47. Rack K, De Bie J, Ameye G, et al. Optimizing the diagnostic workflow for acute lymphoblastic leukemia by optical genome mapping. Am J Hematol. 2022;97(5):548-561. doi:10.1002/ajh.26487 Sciwheel inserting bibliography. For Research Use Only. Not For Use In Diagnostic Procedures. © 2023 Bionano Genomics, Inc. All Rights Reserved. For Research Use Only. Not For Use In Diagnostic Procedures. Reveal key structural variants with OGM Speak to a specialist about the high-resolution you need to maximize detection of critical pathogenic abberations. https://bionano.com/hematological-malignancies/