Loss of hematopoietic progenitors heterogeneity is an adverse prognostic factor in lower-risk myelodysplastic neoplasms.

Myelodysplastic neoplasms (MDS) are characterized by clonal evolution starting from the compartment of hematopoietic stem and progenitors cells (HSPCs), leading in some cases to leukemic transformation. We hypothesized that deciphering the diversity of the HSPCs compartment may allow for the early detection of an emergent sub-clone that drives disease progression. Deep analysis of HSPCs repartition by multiparametric flow cytometry revealed a strong disorder of the hematopoietic branching system in most patients at diagnosis with different phenotypic signatures closely related to specific MDS features. In two independent cohorts of 131 and 584 MDS, the HSPCs heterogeneity quantified through entropy calculation was decreased in 47% and 46% of cases, reflecting a more advanced state of the disease with deeper cytopenias, higher IPSS-R risk and accumulation of somatic mutations. We demonstrated that patients with lower-risk MDS and low CD34 + CD38+HSPCs entropy had an adverse outcome and that this parameter is as an independent predictive biomarker for progression free survival, leukemia free survival and overall survival. Analysis of HSPCs repartition at diagnosis represents therefore a very powerful tool to identify lower-risk MDS patients with a worse outcome and valuable for clinical decision-making, which could be fully integrated in the MDS diagnostic workflow.

Hematopoietic differentiation is characterized by a transient peak of entropy at a single-cell level.

BACKGROUND: Mature blood cells arise from hematopoietic stem cells in the bone marrow by a process of differentiation along one of several different lineage trajectories. This is often represented as a series of discrete steps of increasing progenitor cell commitment to a given lineage, but as for differentiation in general, whether the process is instructive or stochastic remains controversial. Here, we examine this question by analyzing single-cell transcriptomic data from human bone marrow cells, assessing cell-to-cell variability along the trajectories of hematopoietic differentiation into four different types of mature blood cells. The instructive model predicts that cells will be following the same sequence of instructions and that there will be minimal variability of gene expression between them throughout the process, while the stochastic model predicts a role for cell-to-cell variability when lineage commitments are being made. RESULTS: Applying Shannon entropy to measure cell-to-cell variability among human hematopoietic bone marrow cells at the same stage of differentiation, we observed a transient peak of gene expression variability occurring at characteristic points in all hematopoietic differentiation pathways. Strikingly, the genes whose cell-to-cell variation of expression fluctuated the most over the course of a given differentiation trajectory are pathway-specific genes, whereas genes which showed the greatest variation of mean expression are common to all pathways. Finally, we showed that the level of cell-to-cell variation is increased in the most immature compartment of hematopoiesis in myelodysplastic syndromes. CONCLUSIONS: These data suggest that human hematopoietic differentiation could be better conceptualized as a dynamical stochastic process with a transient stage of cellular indetermination, and strongly support the stochastic view of differentiation. They also highlight the need to consider the role of stochastic gene expression in complex physiological processes and pathologies such as cancers, paving the way for possible noise-based therapies through epigenetic regulation.