Single cell sequencing in acute myeloid leukemia: Linking genotype to functional phenotype for precision risk...

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy characterized by clonal expansion of myeloid precursor cells. The pathologic evaluation of AML integrates multiple levels of characterization, including morphology of cells circulating in peripheral blood and bone marrow, identification of blast lineage by immunohistochemistry and flow cytometry immunophenotyping, and genetic studies including karyotype, fluorescence in-situ hybridization, and next generation sequencing (NGS). NGS analysis is utilized routinely to define the mutational landscape of AML, which informs risk stratification and choice of therapy. However, the current methods of immunophenotypic classification in clinical practice use a relatively small number of surface markers to coarsely determine hematopoietic lineage, and bulk sequencing approaches are largely unable to accurately capture clonal complexity, resolve mutational order, and distinguish residual leukemia from clonal hematopoiesis. Single-cell sequencing techniques have transformed our understanding of normal and malignant hematopoiesis by moving beyond the classical hematopoietic hierarchy to define transitional cell states, thereby unraveling clonal complexity with unprecedented resolution. Single-cell multi-omic approaches that span genomics, transcriptomics, proteomics, epigenomics, and metabolomics have the potential to unravel the vast disease heterogeneity in AML, address the discordance between genetic subtypes and functional phenotypes, and improve risk stratification. The latest frontier, spatial single-cell techniques apply these multi-omic approaches to study cells in situ, offering new insights into the bone marrow microenvironment. Here, we review how single cell sequencing technologies have been utilized to study AML throughout the course of disease, including initial diagnosis, assessment of measurable residual disease in remission, and clonal evolution at relapse, and we look ahead to future applications that may impact clinical practice.