Longitudinal ultra-sensitive mutation burden sequencing for precise minimal residual disease assessment in AML

Yitian Wu, Shuai Zhang, Ru Feng, Kangming Xiao, Ting Wang, Jiefei Bai, Xiaoyu Zhou, Yuji Wang, Peng Dai (), Hui Liu () and Lucia Ruojia Wu ()
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Yitian Wu: Capital Medical University
Shuai Zhang: Chinese Academy of Medical Sciences
Ru Feng: Chinese Academy of Medical Sciences
Kangming Xiao: Peking University
Ting Wang: Chinese Academy of Medical Sciences
Jiefei Bai: Chinese Academy of Medical Sciences
Xiaoyu Zhou: Capital Medical University
Yuji Wang: Capital Medical University
Peng Dai: Peking University
Hui Liu: Chinese Academy of Medical Sciences
Lucia Ruojia Wu: Capital Medical University

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Relapse is one of the major challenges in clinical treatment of acute myeloid leukemia (AML). Though minimal residual disease (MRD) monitoring plays a crucial role in quantitative assessment of the disease, molecular MRD analysis has been mainly limited to patients diagnosed with gene fusions and NPM1 mutations. Here, we report a longitudinal ultra-sensitive mutation burden (UMB) monitoring strategy for accurate MRD analysis in AML patients regardless of genetic abnormality types. Using a Quantitative Blocker Displacement Amplification (QBDA) sequencing panel with limit of detection below 0.01% variant allele frequency (VAF), a hazard ratio of 14.8 (p

Date: 2024
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DOI: 10.1038/s41467-024-54254-6

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