How to Read a Next-Generation Sequencing Report for AML and MDS—What Hematologists Need to Know

Acute myeloid leukemia (AML) and myelodysplastic neoplasms (MDS) are clonal hematopoietic malignancies in which next-generation sequencing (NGS) has become integral for diagnosis, classification, risk stratification, and measurable residual dis-ease (MRD) monitoring. Traditional cytogenetic and PCR-based assays remain useful, but targeted NGS panels now represent the standard of care, providing rapid and sen-sitive detection of recurrent gene mutations, structural variants, and gene fusions. Whole-genome, whole-exome, RNA sequencing, and long-read platforms expand the spectrum of detectable alterations, though targeted panels remain most practical for routine diagnostics. Bioinformatic pipelines and quality metrics—including read length, sequencing depth, and coverage—are critical for accurate variant calling, with validation often required for variants of uncertain significance or those near detection thresholds. NGS is now embedded in diagnostic frameworks, including the WHO 2022 and ICC classifications, which incorporate recurrently mutated genes such as TP53, ASXL1, RUNX1, and FLT3. These data inform prognostic models, with ELN-2022 defining ad-verse-risk AML subgroups for patients treated with intensive chemotherapy, ELN-2024 AML patients treated with less-intensive therapies, and the IPSS-M refining MDS risk categories by integrating mutational data. NGS also enables MRD monitor-ing, with gene panels and PCR-NGS hybrid approaches (e.g., for FLT3-ITD) showing increasing clinical utility, though standardization is still lacking. Furthermore, diag-nostic NGS frequently uncovers germline predisposition syndromes (e.g., DDX41, GATA2), with significant implications for treatment decisions and donor selection in transplantation. We discuss advantages, limitations, and future perspectives of NGS in clinical hema-tology, with the aim of providing a practical guide for clinicians navigating the grow-ing complexity of molecular data in daily practice.