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ROBIN: A unified nanopore-based assay integrating intraoperative methylome classification and next-day comprehensive profiling for ultra-rapid tumor diagnosis. | LitMetric

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Article Abstract

Background: Advances in our technological capacity to interrogate CNS tumor biology have led to the ever increasing use of genomic sequencing in diagnostic decision making. Presently, CNS tumors are classified based on their epigenetic signatures, leading to a paradigm shift in diagnostic pathways. Such testing can be performed so rapidly using nanopore sequencing that results can be provided intraoperatively. This information greatly improves the fidelity of smear diagnosis and can help surgeons tailor their approach, balancing the risks of surgery with the likely benefit. Nevertheless, full integrated diagnosis may require subsequent additional assays to detect pathognomonic somatic mutations and structural variants, thereby delaying the time to final diagnosis.

Methods: Here, we present ROBIN, a tool based on PromethION nanopore sequencing technology that can provide both real-time, intraoperative methylome classification and next-day comprehensive molecular profiling within a single assay. ROBIN utilizes 3 methylation classifiers to improve diagnostic performance in the intraoperative setting.

Results: We demonstrate classifier performance on 50 prospective intraoperative cases, achieving a diagnostic turnaround time under 2 hours and generating robust tumor classifications within minutes of sequencing. Furthermore, ROBIN can detect single nucleotide variants, copy number variants, and structural variants in real time, and is able to inform a complete integrated diagnosis within 24 hours. Classifier performance demonstrated concordance with final integrated diagnosis in 90% of prospective cases.

Conclusion: Nanopore sequencing can greatly improve turnaround times for standard-of-care diagnostic testing and is furthermore able to reliably provide clinically actionable intraoperative tumor classification.

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Source
http://dx.doi.org/10.1093/neuonc/noaf103DOI Listing

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