bioRxivCancer BiologyPreprint
Single cell mutational profiling delineates clonal trajectories in myeloid malignancies
L. A. Miles, R. L. Bowman, T. R. Merlinsky, I. S. Csete, A. Ooi, R. Durruthy-Durruthy, M. Bowman, C. Famulare, M. A. Patel, P. Mendez, C. Ainali, M. Manivannan, S. Sahu, A. D. Goldberg, K. Bolton, A. ZEHIR, R. Rampal, M. P. Carroll, S. E. Meyer, A. D. Viny, R. L. Levine
Abstract
Myeloid malignancies, including acute myeloid leukemia (AML), arise from the proliferation and expansion of hematopoietic stem and progenitor cells which acquire somatic mutations. Bulk molecular profiling studies on patient samples have suggested that somatic mutations are obtained in a step-wise fashion, where mutant genes with high variant allele frequencies (VAFs) are proposed to occur early in disease development and mutations with lower VAFs are thought to be acquired later in disease progression1-3. Although bulk sequencing informs leukemia biology and prognostication, it cannot distinguish which mutations occur in the same clone(s), accurately measure clonal complexity and clone size, or offer definitive evidence of mutational order. To elucidate the clonal framework of myeloid malignancies, we performed single cell mutational profiling on 146 samples from 123 patients. We found AML is most commonly comprised of a small number of dominant clones, which in many cases harbor co-occurring mutations in epigenetic regulators. Conversely, mutations in signaling genes often occur more than once in distinct subclones consistent with increasing clonal diversity. We also used these data to map the clonal trajectory of each patient and found that specific mutation combinations (FLT3-ITD + NPM1c) synergize to promote clonal expansion and dominance. We combined cell surface protein expression with single cell mutational analysis to map somatic genotype and clonal architecture with immunophenotype. Our studies of clonal architecture at a single cell level provide novel insights into the pathogenesis of myeloid transformation and how clonal complexity contributes to disease progression.
- organism: human
- assay: whole-exome sequencing
- research focus: clustering
- research focus: trajectory inference
- research focus: differential expression
- research focus: cell type annotation
- approach: experimental assay
- approach: statistical model
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