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Epstein-Barr virus (EBV) is associated with hematologic and solid tumors. We utilized a hybridization capture-based next-generation sequencing (NGS) platform targeting 400 genes associated with hematological malignancies to detect and quantify nontargeted viral-derived EBV reads that aligned to the EBV reference contig (NC_007605). We evaluated 5234 samples from 3636 unique patients with hematological neoplasms and found that 100 samples (1.9%) in 93 unique patients had ≥6 EBV reads (range, 6 to 32,325; mean, 827.5; median, 54). Most (n = 73, 73%) represented known EBV-associated conditions, and the most common was post-transplant lymphoproliferative disorders (n = 21, 29%). Documented EBV viremia was found in 4 of 27 samples with a moderate quantity of EBV reads and conditions not known to be EBV associated, whereas suspected viremia or low-level activation was likely in the remaining 23 samples. A good correlation (Spearman r = 0.8; 95% CI, 0.74-0.85) was found between EBV reads by NGS and systematic semiquantitative EBV-encoded RNA in situ hybridization in 162 available samples, particularly at greater EBV involvement. An optimal threshold for significant morphologic EBV involvement was found to be ≥10 reads by the receiver operating characteristic analysis (area under the curve, 0.990; 95% CI, 0.9974%-1.000%). Thus, in addition to mutational analysis, hybrid-capture-based NGS panels can detect and quantitate off-target EBV-derived viral DNA, which correlates well with morphology. Copyright © 2022 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Citation

Kseniya Petrova-Drus, Andrés E Quesada, Anita S Bowman, Ryan Ptashkin, Jinjuan Yao, Maria E Arcila, Caleb Ho, Christine Moung, Jennifer Regalado, Ryma Benayed, Jamal K Benhamida, Pallavi K Galera, Ahmet Dogan, Chad Vanderbilt. Quantitative Off-Target Detection of Epstein-Barr Virus-Derived DNA in Routine Molecular Profiling of Hematopoietic Neoplasms by Panel-Based Hybrid-Capture Next-Generation Sequencing. The Journal of molecular diagnostics : JMD. 2022 Jan;24(1):69-78

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PMID: 34801704

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