Editorial Feature

Advancing Cancer Diagnosis with Optical Genome Mapping

Optical genome mapping (OGM) is revolutionizing cancer research by enabling the comprehensive detection of structural variations and gene fusions, providing unprecedented insights into cancer biology, and guiding personalized treatment strategies.

Advancing Cancer Diagnosis with Optical Genome Mapping

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What is Optical Genome Mapping?

Optical Genome Mapping (OGM) is a non-sequencing-based technology that enables the high-resolution analysis of large eukaryotic genomes and their structural features. It allows for accurate, genome-wide detection of structural variations (SVs) and copy number variations (CNVs).

Unlike traditional sequencing methods that rely on short DNA fragments, OGM uses ultra-long, high-molecular-weight DNA molecules ranging from 300 kilobases (kb) to several megabases (Mb) in length.

These DNA molecules are labeled with fluorescent dyes at specific sequence motifs, creating a distinctive barcode genome. The labeled DNA molecules are then linearized, imaged using high-resolution fluorescence microscopy to capture unique patterns, and compared to a reference genome by OGM. This enables the identification of SVs and CNVs with precision down to 500 base pairs or higher.1,2

This capability sets OGM apart from other genomic sequencing techniques, which often struggle to resolve large structural variations or variations within repetitive regions, which comprise two-thirds of the human genome. It enables the creation of highly contiguous genomic maps, facilitating the detection of insertions, deletions, inversions, translocations, and other complex rearrangements critical in cancer development.

OGM offers a distinct advantage over next-generation sequencing (NGS) by directly observing structural variations (SVs) instead of inferring them. This approach enables the direct visualization of most large SVs or their breakpoints in the label patterns on individual molecules, providing a clearer understanding of genomic rearrangements.

Additionally, while NGS is limited in assessing variations in and around repetitive sequences, OGM overcomes these constraints, effectively revealing changes contributing to various diseases.3

OGM’s Impact on Cancer Diagnosis

OGM has transformed cancer diagnosis, particularly in hematologic malignancies, by detecting clinically significant SVs with over 95 % concordance according to standard testing. It has unveiled cryptic SVs in MDS cases, impacting risk assessments, and identified additional SVs in AML that could alter clinical management.

OGM's gene-level resolution has enhanced the understanding of cancer genomes, identifying clinically significant molecular subgroups and improving the resolution of breakpoints in myeloid malignancies.

Additionally, OGM has surpassed conventional cytogenetic methods, multiplex-ligation-dependent probe amplification (MLPA), and fluorescence in situ hybridization (FISH) in lymphoid cancers by 20 % in assigning major cytogenetic risk groups.1,4

Case Studies and Current Applications

The impact of OGM on cancer diagnosis is further demonstrated by its applications across various cancer types, providing valuable insights and clinical relevance.

Identification of Somatic Structural Variants in Solid Tumors

A study published in the Journal of Personalized Medicine developed protocols for extracting ultra-high-molecular-weight DNA from solid tumor tissues, enabling the identification of large and complex SVs using OGM.

The researchers successfully extracted high-molecular-weight DNA from small amounts of tumor tissue using a paramagnetic nanobind disc. This allowed them to create detailed genomic maps using OGM, enabling the identification of complex and large (>500 bp) SVs that are often missed by standard next-generation sequencing (NGS) techniques.

The high-quality DNA isolation, high genomic map rates, and effective coverage demonstrated OGM's ability to reliably detect SVs impacting functional and cancer-related genes, making it promising for rapid data turnaround in clinical diagnostic and prognostic applications.5

Revealing the Complex Genetic Landscape of Myeloma

Multiple myeloma (MM) is a plasma cell cancer characterized by a high level of morbidity and a generally incurable nature. Traditionally, FISH has been used to identify genetic abnormalities in MM, but its targeted analysis can be challenging due to its genetic complexity.

A study published in Cancers used OGM to detect clinically significant cytogenetic abnormalities in MM and provide larger pangenomic information. The researchers successfully identified SVs involving MYC and IGH, CNVs including 1p deletion, 17p/TP53 deletion, 1q gain/amplification, and aneuploidy involving gains of odd-numbered chromosomes.

OGM demonstrated a 30 % increase in predictive yield compared to the standard FISH method, showcasing its potential as a replacement for FISH in clinical settings.6

Structural Variations in Breast Cancer

A study published in Frontiers in Bioscience-Landmark explored the landscape of SVs in hereditary breast and ovarian cancer (HBOC) syndrome, particularly in cases with germline BRCA1/2 mutations, using OGM.

The researchers found that samples with higher structural variations heterogeneity (SVhigh) were linked to adverse clinicopathological characteristics, such as higher homologous recombination deficiency scores, Ki-67 expression, and altered signaling pathways.

OGM effectively characterized these complex genetic alterations, including novel gene fusions, suggesting its potential for predicting clinical outcomes and guiding therapeutic strategies.7

Diagnostic Tool for Pediatric Acute Myeloid Leukemia

Pediatric acute myeloid leukemia (AML), the second most common blood cancer in children, exhibits diverse genetic abnormalities, including SVs, aneuploidies, and gene mutations. These genetic changes influence drug responses and help classify patients into risk groups, thereby determining treatment intensity.

Karyotyping and FISH are commonly used for detecting aneuploidies and SVs in pediatric AML, but they are costly, have low resolution, and require cell cultivation and skilled staff.

In a study published in Cancers, researchers evaluated OGM's efficacy in pediatric AML diagnosis compared to standard cytogenetic techniques, focusing on its impact on risk stratification and treatment decisions.

OGM demonstrated significantly higher resolution than traditional methods, identifying new structural variations (SVs) in 70 % of cases, including 32 previously unknown alterations. It also identified potential markers for minimal residual disease (MRD) monitoring, offering a promising avenue for improved treatment response monitoring.

While OGM did not significantly change risk stratification in most cases, it provided valuable supplementary information that could potentially impact therapy decisions.8

Future Prospects and Challenges in OGM

While OGM holds immense potential for advancing cancer diagnosis and personalized medicine, several challenges must be addressed.

One limitation is the requirement for ultra-high-molecular-weight DNA, which precludes the analysis of fixed specimens or DNA isolated using conventional methods. Additionally, OGM is currently a low-throughput technology, and its inability to provide sequence-level data may necessitate complementary sequencing approaches.

The increased detection of cryptic SVs by OGM may also uncover genomic variations of unknown significance, challenging current interpretative capabilities.

As OGM technology evolves, it will be crucial to develop robust analytical pipelines and interpretation databases to support the integration of this high-resolution data into clinical decision-making.4

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References and Further Reading

  1. Garcia-Heras, J. (2021). Optical Genome Mapping: A Revolutionary Tool for “Next Generation Cytogenomics Analysis” with a Broad Range of Diagnostic Applications in Human Diseases. Journal of the Association of Genetic Technologists47(4). https://pubmed.ncbi.nlm.nih.gov/34897113/
  2. Dremsek, P., Schwarz, T., Weil, B., Malashka, A., Laccone, F., Neesen, J. (2021). Optical genome mapping in routine human genetic diagnostics—its advantages and limitations. Genes. doi.org/10.3390/genes12121958
  3. Bionano Genomics. (2024). How Optical Genome Mapping Works. [Online] Bionano Genomics. Available at: https://bionano.com/how-ogm-works/
  4. Annette S. Kim, Adrian M. Dubuc & Samuel Brody. (2024). Optical Genome Mapping: A ‘Tool’ with Significant Potential from Discovery to Diagnostics. [Online]  College of American Pathologists. Available at: https://www.cap.org/member-resources/articles/optical-genome-mapping-a-tool-with-significant-potential-from-discovery-to-diagnostics
  5. Goldrich, DY., et al. (2021). Identification of somatic structural variants in solid tumors by optical genome mapping. Journal of Personalized Medicine. doi.org/10.3390/jpm11020142
  6. Giguère, A., Raymond-Bouchard, I., Collin, V., Claveau, JS., Hébert, J., LeBlanc, R. (2023). Optical Genome Mapping Reveals the Complex Genetic Landscape of Myeloma. Cancers. doi.org/10.3390/cancers15194687
  7. Cheng, Y., et al. (2024). Optical Genome Mapping Reveals the Landscape of Structural Variations and Their Clinical Significance in HBOC-Related Breast Cancer. Frontiers in Bioscience-Landmark doi.org/10.31083/j.fbl2901002
  8. Suttorp, J., et al. (2022). Optical genome mapping as a diagnostic tool in pediatric acute myeloid leukemia. Cancers. doi.org/10.3390/cancers14092058

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Owais Ali

Written by

Owais Ali

NEBOSH certified Mechanical Engineer with 3 years of experience as a technical writer and editor. Owais is interested in occupational health and safety, computer hardware, industrial and mobile robotics. During his academic career, Owais worked on several research projects regarding mobile robots, notably the Autonomous Fire Fighting Mobile Robot. The designed mobile robot could navigate, detect and extinguish fire autonomously. Arduino Uno was used as the microcontroller to control the flame sensors' input and output of the flame extinguisher. Apart from his professional life, Owais is an avid book reader and a huge computer technology enthusiast and likes to keep himself updated regarding developments in the computer industry.

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