Mutation order in acute myeloid leukemia identifies uncommon patterns of evolution and illuminates phenotypic heterogeneity.
Matthew SchwedeKatharina JahnJack KuipersLinde A MilesRobert L BowmanTroy RobinsonKen FurudateHidetaka UryuTomoyuki TanakaKumiko ChinoAsiri Saumya EdiriwickremaBrooks A BenardAndrew J GentlesRoss L LevineNiko BeerenwinkelKoichi TakahashiRavindra MajetiPublished in: Leukemia (2024)
Acute myeloid leukemia (AML) has a poor prognosis and a heterogeneous mutation landscape. Although common mutations are well-studied, little research has characterized how the sequence of mutations relates to clinical features. Using published, single-cell DNA sequencing data from three institutions, we compared clonal evolution patterns in AML to patient characteristics, disease phenotype, and outcomes. Mutation trees, which represent the order of select mutations, were created for 207 patients from targeted panel sequencing data using 1 639 162 cells, 823 mutations, and 275 samples. In 224 distinct orderings of mutated genes, mutations related to DNA methylation typically preceded those related to cell signaling, but signaling-first cases did occur, and had higher peripheral cell counts, increased signaling mutation homozygosity, and younger patient age. Serial sample analysis suggested that NPM1 and DNA methylation mutations provide an advantage to signaling mutations in AML. Interestingly, WT1 mutation evolution shared features with signaling mutations, such as WT1-early being proliferative and occurring in younger individuals, trends that remained in multivariable regression. Some mutation orderings had a worse prognosis, but this was mediated by unfavorable mutations, not mutation order. These findings add a dimension to the mutation landscape of AML, identifying uncommon patterns of leukemogenesis and shedding light on heterogeneous phenotypes.
Keyphrases
- single cell
- acute myeloid leukemia
- dna methylation
- poor prognosis
- rna seq
- genome wide
- allogeneic hematopoietic stem cell transplantation
- end stage renal disease
- randomized controlled trial
- long non coding rna
- gene expression
- chronic kidney disease
- peritoneal dialysis
- high throughput
- stem cells
- cell proliferation
- systematic review
- machine learning
- oxidative stress
- cell therapy
- bone marrow
- acute lymphoblastic leukemia
- skeletal muscle
- deep learning
- cell free
- nucleic acid
- endoplasmic reticulum stress
- artificial intelligence