66. Optical genome mapping workflow for Somatic Abnormality detection in Multiple Solid Tumor types

Aly Abdelkareem

Benjamin Clifford

Dr. Ben Clifford is a genomics scientist with interests in physical genome mapping, evolution, and technology. In his Bionano Scientific and Clinical Affairs role, he serves as a strategic and technical liaison for laboratories developing their operations around optical genome mapping (OGM). These strategic projects seek to evaluate and validate applications in structural and copy number variation, and elucidate underlying biology in cancer and pre- and post- natal constitutional disorders.

He joined Bionano in 2016 in a direct support role, as a field application scientist conducting sample-thru-analysis technical trainings for new users of the Saphyr System. Prior to joining Bionano, Ben completed his Ph.D. from the University of Notre Dame, USA, researching the genomics of evolution and speciation.


Benjamin Clifforda, Andy Wing Chun Pangb, Mark Oldakowskia, Alka Chaubeya, Alex Hastiea

aBionano Genomics, San Diego, CA, USA; bBionano Genomics, Toronto, Ontario, CA

Solid tumors are often characterized by a high degree of complex somatic structural variants of multiple classes, especially rearrangements and copy number variants. Characterizing this genomic complexity is crucial for understanding the biology behind carcinogenesis but is challenging as a result of limitations of current genomic technology classes: cytogenic (low resolution) and molecular (poor sensitivity for structural variation). Accurate assessment of genomic structural variation is important because some tumors acquire growths advantage by amplifying or creating oncogenes by fusing otherwise non-pathogenic genes and by deleting/inactivating tumor suppressor genes.

Fusions are generally detected through targeted assays like NGS panels, PCR and FISH, or through karyotyping. However, high-resolution genome-wide approaches to detect fusions are needed. Optical Genome Mapping (OGM) is able fill this gap, providing high resolution (~3kbp breakpoint precision) and ability to span repetitive and complicated genomic regions.

Here we demonstrate a simple OGM workflow for the analysis of tumor biopsies, applying it to varying types (bladder, brain, breast, colon, kidney, liver, lung, ovary, prostate, tongue, thyroid). High-molecular weight DNA is isolated from snap-frozen tissue from 6.5-18 mg biopsies, then processed for OGM. The resulting analyses produced variants annotated and filtered within Bionano Access? software to enrich for somatic variants by filtering against a control database (?1% presence) and for those that overlap with gene(s). Based on this analysis, we have identified rearrangements and CNVs involving oncogenes and tumor suppressors (ERBB2, CDKN2A, NF1; many others) as well as numerous novel fusions in our comprehensive characterization of these complex genomes.