Next-Generation Sequencing for Measurable Residual Disease Detection in Acute Myeloid Leukemia: From Concept to Clinical Application

Juan C. Gomez-Gelvez, MD
Section Head, Molecular Hematopathology — Henry Ford Health System

Measurable residual disease (MRD) represents the small number of leukemic cells that persist after treatment—undetectable by morphology yet clinically decisive. MRD status is now recognized as one of the strongest predictive and prognostic biomarkers in acute myeloid leukemia, influencing relapse risk, survival, and post-remission management.

In this on-demand session, Dr. Gomez-Gelvez walks through the principles, practicalities, and clinical impact of using NGS to detect MRD with high sensitivity.

What You’ll Learn

Why MRD matters in AML
Its role as a predictor of relapse, marker of treatment response, and surrogate endpoint in clinical trials.
How NGS compares to existing modalities
Insights into ELN recommendations, and sensitivity comparisons with flow cytometry and other molecular methods.
Building a reliable NGS-MRD workflow
Key considerations for assay design, including:
– Optimal sampling time points
– Marker selection and deamination-filtering criteria
– Pre-analytic and analytic validation requirements
Early findings from a 33-gene NGS panel analysis
Demonstrating achievable sensitivity down to 0.01% (10⁻⁴) and highlighting its broad applicability across AML patient profiles.

Key Takeaways

NGS-based MRD assays deliver high sensitivity, even in patients lacking recurrent fusions or PCR-amenable mutations.
MRD positivity by NGS is strongly associated with higher relapse risk and worse survival.
Standardization across sampling, assay parameters, and reporting is critical for clinical implementation.
As evidence grows, NGS-MRD is poised to become central in risk stratification, post-remission therapy decisions, and clinical trial endpoints.

Why Watch?

If you’re advancing AML diagnostics or shaping MRD strategies, this session provides clear, practical guidance from clinical concept through real-world application.

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