Sequencing-Based Measurable Residual Disease Testing in Acute Myeloid Leukemia.

Jennifer M Yoest,Cara Lunn Shirai,Eric J Duncavage

doi:10.3389/fcell.2020.00249

Abstract

Next generation sequencing (NGS) methods have allowed for unprecedented genomic characterization of acute myeloid leukemia (AML) over the last several years. Further advances in NGS-based methods including error correction using unique molecular identifiers (UMIs) have more recently enabled the use of NGS-based measurable residual disease (MRD) detection. This review focuses on the use of NGS-based MRD detection in AML, including basic methodologies and clinical applications.

Highlights

Acute myeloid leukemia (AML) is a heterogeneous group of clonal hematopoietic stem cell malignancies characterized by a block in myeloid differentiation resulting in increased myeloid blasts and rapidly aggressive clinical course (Estey and Dohner, 2006; O’Donnell et al, 2013; Papaemmanuil et al, 2016; Cai and Levine, 2019)
Measurable residual disease (MRD; referred to as minimal residual disease) testing in AML fulfills several unmet clinical needs, including the ability to determine individual risk in AML patients based on mutational clearance after treatment
Despite the potential increase in sensitivity and specificity achieved with duplex error correction, most clinical AML MRD methods rely on single strand unique molecular identifier (UMI)-based error correction, since the coverage required to realize performance gains with duplex UMI error correction across a panel of genes is generally not tenable in the clinical laboratory

Summary

Introduction

Acute myeloid leukemia (AML) is a heterogeneous group of clonal hematopoietic stem cell malignancies characterized by a block in myeloid differentiation resulting in increased myeloid blasts and rapidly aggressive clinical course (Estey and Dohner, 2006; O’Donnell et al, 2013; Papaemmanuil et al, 2016; Cai and Levine, 2019). NGS-based MRD provides a way to monitor most AML patients for molecular MRD by allowing for the detection of multiple gene mutations in a single assay.

Results

Conclusion