Integrated decoding hematopoiesis and leukemogenesis at single-cell resolution and its clinical implication
Posted 23 Feb 2020
bioRxiv DOI: 10.1101/2020.02.21.960401
Posted 23 Feb 2020
Integrated analyses of hematopoiesis and leukemogenesis could provide new biological and clinical insights1,2. Here we constructed a comprehensive cell atlas using ~100,000 single cell transcriptomes of bone marrow mononuclear cells and its subsets from 5 healthy samples and 11 leukemia samples. Trajectory analysis showed hematopoietic stem cells continuously differentiated through tree-like structure into 7 lineages. Although our single cell analyses showed the major cellular heterogeneity were inter-patients, there were distinct leukemia cell subpopulations within patient. We developed counterpart composite index (CCI) for projecting leukemia cell subpopulation into reference hematopoietic cells, to identify their healthy counterparts that could predict leukemia subtype and clinical outcome. Interestingly, we found the trajectories of leukemogenesis were similar to that of their healthy counterparts, indicating lineage relationship of leukemia cell subpopulations. Single cell analyses of leukemia patient at diagnosis, refractory, remission and relapse vividly presented dynamics of cell population and the underlying genes. Single cell transcriptomic variants analyses showed the relapsed leukemia cells, whose healthy counterparts were closer to the root of hematopoietic tree, were derived from an early minor leukemia cell population. This study not only increased our understanding of hematopoiesis and leukemogenesis, but also provided an approach for leukemia classification and clinical outcome prediction.
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