Clinical Utility of Optical Genome Mapping for Improved Cytogenomic Analysis of Gliomas
Biomedicines, ISSN: 2227-9059, Vol: 12, Issue: 8
2024
- 13Captures
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Most Recent Blog
Biomedicines, Vol. 12, Pages 1659: Clinical Utility of Optical Genome Mapping for Improved Cytogenomic Analysis of Gliomas
Biomedicines, Vol. 12, Pages 1659: Clinical Utility of Optical Genome Mapping for Improved Cytogenomic Analysis of Gliomas Biomedicines doi: 10.3390/biomedicines12081659 Authors: Harmanpreet Singh Nikhil S.
Most Recent News
Augusta University Researcher Publishes New Data on Gliomas (Clinical Utility of Optical Genome Mapping for Improved Cytogenomic Analysis of Gliomas)
2024 AUG 14 (NewsRx) -- By a News Reporter-Staff News Editor at Clinical Oncology Daily -- Fresh data on gliomas are presented in a new
Article Description
A glioma is a solid brain tumor which originates in the brain or brain stem area. The diagnosis of gliomas based on standard-of-care (SOC) techniques includes karyotyping, fluorescence in situ hybridization (FISH), and chromosomal microarray (CMA), for detecting the pathogenic variants and chromosomal abnormalities. But these techniques do not reveal the complete picture of genetic complexity, thus requiring an alternative technology for better characterization of these tumors. The present study aimed to evaluate the clinical performance and feasibility of using optical genome mapping (OGM) for chromosomal characterization of gliomas. Herein, we evaluated 10 cases of gliomas that were previously characterized by CMA. OGM analysis showed concordance with the results of CMA in identifying the characterized Structural Variants (SVs) in these cases. More notably, it also revealed additional clinically relevant aberrations, demonstrating a higher resolution and sensitivity. These clinically relevant SVs included cryptic translocation, and SVs which are beyond the detection capabilities of CMA. Our analysis highlights the unique capability of OGM to detect all classes of SVs within a single assay, thereby unveiling clinically significant data with a shorter turnaround time. Adopting this diagnostic tool as a standard of care for solid tumors like gliomas shows potential for improving therapeutic management, potentially leading to more personalized and timely interventions for patients.
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