Fig. 3: Inference of mutational history in AML.

a Summary of the clonal evolution patterns. Three of the 55 cases showing branching evolution patterns presented convergent evolution patterns. b–i Inference of mutation phylogeny based on the single-cell DNA seqeuncing (scDNA-seq) data using the SCITE algorithm. Representative cases illustrating distinct patterns of clonal evolution are shown. Each node represents a mutational event, and each circle represents a subclone with cumulative mutational events, which can be traced with a dotted line and solid lines towards the root. The size of the circle is proportional to the clonal population, and the numbers within each circle are the number of cells and the percentage of each clone among the total tumor cells. The 95% credible intervals from the posterior sampling are shown to illustrate the uncertainty in the subclone sizes. The wild-type cells which did not carry any driver mutations are not shown. b, c Linear clonal evolution pattern, in which a subset of cells from the founder clone acquired additional mutations in a stepwise manner. The trunk clone exhibits a forked evolution pattern based on the status of additional mutations. d–i Branching clonal evolution pattern including convergent evolution patterns with molecular alterations in g NPM1-RAS/MAPK-IDH, h chromatin-RUNX1-RAS, and i NPM1-IDH-FLT3/RAS/MAPK pathways. The clonal evolution patterns are characterized by the parallel acquisition of multiple functionally redundant mutations in different cell populations. j, k Inference of the relative timing of loss of heterozygosity (LOH). Zygosity state based on the scDNA-seq data was incorporated into phylogeny reconstruction. Two representative cases with homozygous RUNX1 mutations involving LOH are shown. In both cases, each RUNX1 mutation was initially heterozygous and sequentially developed into homozygous state, without acquiring any additional mutations during LOH events. ADO allele dropout, FPR false-positive rate.