In May 2023, Professor Jun Ma and his team from Harbin Institute of Hematology Oncology published a paper in the Journal of Leukemia & Lymphoma titled “Application of high-throughput next-generation sequencing in diagnosis and treatment of myeloid hematologic malignancies in the era of precision medicine,” introducing the progress of NGS applications in acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPN).
The occurrence of myeloid hematologic malignancies is the result of clonal expansion of hematopoietic stem cells driven by genetic abnormalities. While morphology plays a crucial role in the diagnosis of myeloid hematologic malignancies, next-generation sequencing (NGS) technologies such as targeted NGS, whole exome sequencing (WGS), whole genome sequencing (WES), whole transcriptome sequencing (WTS), and single-cell sequencing enable us to rapidly, accurately, and comprehensively understand genetic aberrations. The genomic characteristics are becoming increasingly important in the accurate diagnosis and classification, risk assessment, treatment plan selection, and treatment efficacy evaluation of myeloid hematologic malignancies. Therefore, research in this field has been a hot topic at the American Society of Hematology (ASH) annual meetings in recent years.
In the context of the application progress of NGS in acute myeloid leukemia (AML), the article compared the proportions of patients classified based on the 2022 World Health Organization 5th edition (WHO 2022) and the 2022 International Consensus Classification (ICC) according to the DGA classification. There was a significant increase in the proportion of patients classified based on DGA, while the proportion based on morphological classification decreased significantly. The variant allele frequency (VAF) values and allelic states of TP53 mutations in AML patients significantly impact their prognosis. The ELN 2022 risk stratification performs better than ELN 2017 in the real world. A comprehensive genomic/immunophenotypic analysis at MRD time points can distinguish between clonal hematopoiesis and leukemia precursor/leukemia clones, significantly enhancing the ability to predict the likelihood of relapse.
In the context of the application progress of NGS in myelodysplastic syndromes (MDS), the MDS classification has added two subtypes defined based on genetic alterations: MDS with SF3B1 mutations in low blast count and MDS with biallelic TP53 mutations (MDS-biTP53).
In the context of the application progress of NGS in myeloproliferative neoplasms (MPN), a study from the Chinese Academy of Medical Sciences, Peking Union Medical College, integrates genetic and clinical information into thrombotic risk stratification. The aim is to enhance the predictive capability of thrombosis in patients with polycythemia vera (PV) and propose risk-adapted treatment strategies based on the new model. Another study from the University Hospital Complex of Santiago de Compostela in Spain employs machine learning methods to construct a prognostic risk prediction model for myelofibrosis (MF), improving the accuracy of disease risk prediction for bone marrow fibrosis (MF).
At the 64th Annual Meeting of the American Society of Hematology in 2022, there were a series of new developments regarding the application of NGS technology in the diagnosis, classification, risk stratification for prognosis, treatment guidance, and detection of minimal residual disease in myeloid hematologic malignancies. The widespread use of high-throughput next-generation sequencing (NGS) and other molecular genetic testing technologies has allowed researchers to gain a deeper understanding of the pathogenesis of hematologic malignancies, particularly myeloid hematologic malignancies. This has become a focal point and hotspot in the precision treatment of hematologic malignancies.
