On Day 2 of the Bionano Symposium 2023, experts from around the world shared exciting work where the use of optical genome mapping (OGM) was expanded, from hematological malignancies to multiple types of solid tumors, such as breast cancer, sarcoma, melanoma, and neuroendocrine liver metastasis. Today’s presenters showed how OGM has potential to replace traditional cytogenetic methods, and at the same time complement NGS methods, to unlock a broader spectrum of genetic variants, generate a more complete cancer genome profile, and discover new actionable biomarkers.
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On the second day of presentations, we learned how OGM is being used as a highly effective tool for analyzing tumor samples, not only detecting the same SVs that would be seen with traditional methods, but also unveiling new pathogenic findings, including in samples for which many other assays have been used without positive results.
Dr. Ravindra Kolhe, from the Georgia Cancer Center and Medical College of Georgia, presented a novel workflow for assessing hematological malignancy samples, that replaces a targeted NGS panel, karyotyping and FISH, with OGM and a comprehensive NGS gene panel. The new algorithm leads to an increase in pathogenic findings, while also enabling faster turnaround time, higher resolution, better characterization of samples, and cost-efficiencies, as compared to the traditional workflow.
In presentations from, Jef Baelen, from KU Leuven, and Dr. Juan Diaz Martin, from Sevilla, Spain, the use of OGM as a key cytogenetic tool in sarcoma samples was evaluated. Multiple examples of different sarcoma samples analyzed with the technique demonstrated its performance to characterize, with high-resolution, multiple types of structural variants. Interestingly, in the Leuven study, when results from OGM copy-number changes profiles were compared to results from methylation microarrays, there was a perfect match of regions where CNV was present, and methylation signals were altered. Researchers plan to complete the analysis of OGM as a clinical research tool and implement it in parallel while utilizing OGM for poorly characterized sarcomas.
Dr. Kolhe shared how analyzing OGM and SNV data in VIA software allows for the integration of NGS and OGM, which enables the “true visualization and confirmation” of compound events, through presentation of different examples. The benefits of such visualization are to seamlessly detect and map small variants, copy number changes, and structural variants, in a single visualization platform, and analyze sample cases in which different types of variants are affecting the same gene or genomic regions.
Dr. Marcin Imielinski, from NYU, presented the use of genome graphs as an approach to integrate short-read NGS data with OGM. The combined analysis enables through analysis of complex structural variants events, such as chromothripsis and chromoplexy. As part of this presentation, he provided exciting data from a preliminary analysis of OGM genome graphs from acral melanoma samples.
In addition, Dr. Daniel Ackerman, from University of Pennsylvania, presented multiple new simple and complex pathogenic structural variant discoveries, in neuroendocrine liver metastasis, enabled by OGM analysis. He also discussed the next steps in the study, which will encompass the combination of OGM with NGS datasets.
Dr. Sandra Vanhuele, from Institute Curie, shared how OGM provides a high-resolution technique to comprehensively detect structural variants across the genome, generating very through characterization of genomic scars, and estimates of HRD scores, properly differentiating Homologous recombination deficient (HRD) from proficient (HRP) samples.
The use of OGM was also discussed as an effective quality control check, to screen off-target events in CAR-T cell lines. Dr. Rashmi Kanagal-Shamanna, from MD Anderson Cancer Center, presented promising findings from a proof-of-concept study, in which 3 cell line samples, from the same donor (two of them genetically modified), were compared against each other.
Presentation No. 1
Ravindra Kolhe, MD, PhD, FCAP | Professor and Interim Chair of Pathology | Associate Dean for Translational Research | Associate Director for Genomics, Georgia Cancer Center | Leon Henri Charbonnier Endowed Chair of Pathology, Medical College of Georgia
In another solid tumor presentation, Dr. Kolhe highlighted that the typical standard-of-care for myeloid cancers relies on a combined approach of karyotyping, FISH, and targeted gene panels for hotspot pathogenetic variants. However, one of the major challenges of this combined approach is that many myeloid cancer genomes remain cytogenetically normal due to the resolution of these technologies, leading to gaps in accurate characterization of a sample.
To address this, Dr. Kolhe presented a novel algorithm that replaces karyotyping and FISH with OGM and a comprehensive gene panel for improved resolution in variant detection for myeloid malignancies. This algorithm has been validated in a published study in the Journal of Molecular Diagnostics and PLOS One.
Dr. Kolhe reported that the performance of this novel algorithm using the Bionano Saphyr® system was “absolutely great” and found it to be a fit for clinical research use. He also discussed that analyzing OGM and SNV data in VIA software allows for the integration of NGS and OGM for “true visualization and confirmation” of compound events. The proposed algorithm provides a shorter turnaround time and higher resolution in an extremely cost-effective approach compared to targeting NGS panel, karyotyping, FISH as well as WGS NGS.
Presentation No. 2
Rashmi Kanagal-Shamanna, MD | Associate Professor, Dept. of Hematopathology and Director, Molecular Diagnostic Laboratory – Microarray – The University of Texas MD Anderson Cancer Center
Dr. Kanagal-Shamanna discussed the use of OGM as a key tool to characterize SVs in myeloid dysplastic syndromes (MDS). She presented data from a study showing how OGM analysis of MDS samples compared to conventional karyotyping—OGM identified more than twice the number of structural aberrations in over a third of the samples, and novel findings led to redefinition of risk-levels on these samples.
She also highlighted the need to integrate NGS and OGM data for complete characterization, and how using these technologies to complement one another shows great promise in clinical research studies with immunotherapies in MDS.
Dr. Kanagal-Shamanna also presented research results on the ability of OGM to objectively map the clonal evolution of individual aberrations and track clones in response to therapies. She also discussed the potential of CAR-T cell treatment, noting it is only effective in 40-50% of cases and at a high treatment cost. As proof of principle, Dr. Kanagal-Shamanna—with data analysis provided by Bionano—assessed OGM potential as a quality control process step in the generation of CAR-T cells. The results from the primary findings showed that OGM could potentially serve as an effective quality control check, through proper characterization of the structural variant profiles of samples, and assessment of off-target events, post gene editing procedures.
Presentation No. 3
Marcin Imieliński MD, PhD | Core Member | New York Genome Center
Dr. Imieliński discussed the importance of identifying complex SVs and copy number variations (CNVs) in cancer, as they are often associated with each other. He presented a new visualization tool, called Pan Genome Viewer (PGV), which combines data from JaBbA—a genome graph inference from WGS that enables pattern recognition—with OGM to identify these complex SVs.
One specific example discussed was the identification of tyfonas, a complex SV found in acral melanoma, which could be a potential biomarker for immunotherapy. This project aimed to perform detailed mapping of these types of SVs and CV aberrations using WGS NGS and OGM. Visualizing, interpreting, and integrating complex SVs from data obtained by jointly analyzed SR WGS and OGM is a challenge. The visualization tools Bionano has developed significantly aid in this analysis.
Dr. Imieliński highlighted the importance of genome graph-based analysis using tools like PGV, which allows for better classification of complex SVs and CNVs.
Presentation No. 4
Juan Díaz-Martín, PhD | Research Associate | Instituto de Biomedicina de Sevilla, IBiS-HUVR
Dr. Díaz-Martín discussed the need for prognostic biomarkers in sarcomas to stratify patients by identifying SVs in t-sarcomas and non-t-sarcomas—and how OGM can be used to identify and differentiate tumor types.
The study discussed using OGM to detect fusions in Ewing sarcomas and “Ewing-like” sarcomas, using 20 samples to highlight the application of OGM in identifying structural variants in a clinical research context. Pathogenomic translations analyzed with OGM showed similar results to SNP arrays for copy number alterations for CNAs.
Presentation No. 5
Daniel Ackerman | Research Assistant Professor | University of Pennsylvania
Daniel discussed the use of OGM as a tool for identifying SVs in neuroendocrine tumors (NETs). The presentation highlighted the challenges in diagnosis and therapy selection for NETs, the current limitations of the grading system, and the lack of predictive biomarkers.
The study used OGM to identify SVs in a sample cohort with NETs and identified alterations at known tumor suppressors. Daniel shared plans for future studies to expand the sample cohort and analyze samples using OGM alongside NGS and potentially correlating genomic features with clinical outcomes, progression of disease, and overall survival.
Presentation No. 6
Sandra Vanhuele | Bioinformatician | Institut Curie, Inserm U830
Sandra discussed the results of a comparison study between OGM and WGS in triple negative breast cancer (TNBC). The study found that OGM was able to detect translocations that were missed by WGS, and that WGS was unable to efficiently detect SVs in low tumor content samples, while OGM was able to detect these SVs even at low VAF.
Sandra also highlighted the potential of OGM in differentiating homologous recombination deficiency (HRD) and homologous recombination proficient (HRP) in TNBC. The study concluded that HRD features were readily detectable even in low tumor content samples using OGM, which has potential in differentiating HRD and HRP TNBC.
Presentation No. 7
Jef Baelen | PhD Student | KU Leuven
Baelen discussed the challenges of analyzing sarcomas, a diverse group of cancers with over 50 subtypes to date, of which 10% are poorly characterized. Current methods, such as karyotyping and FISH, are costly, labor-intensive, and have limitations in detecting structural variations.
Baelen presented an optimized protocol for using OGM for sarcoma tissue, which was found to match results from methylation microarray. Baelen discussed the potential to validate OGM as a replacement for standard cytogenetic techniques in clinical research applications and implement it for poorly characterized sarcomas.
Learn more about unlocking true comprehensive detection of chromosomal aberrations in solid tumor samples, to maximize actionable pathogenic variant findings, with OGM.
Register now to join us live this week and view recorded sessions after 1/26/23 on the Bionano Symposium 2023 virtual event platform.