Human hematopoietic microenvironments

Abstract

Dormancy of hematopoietic stem cells and formation of progenitors are directed by signals that come from the bone marrow microenvironment. Considerable knowledge has been gained on the murine hematopoietic stem cell microenvironment, while less so on the murine progenitor microenvironment and even less so on these microenvironments in humans. Characterization of these microenvironments is decisive for understanding hematopoiesis and finding new treatment modalities against bone marrow malignancies in the clinic. However, it is equally challenging, because hematopoietic stem cells are difficult to detect in the complex bone marrow landscape. In the present study we are characterizing the human hematopoietic stem cell and progenitor microenvironment. We obtained three adjacent bone marrow sections from ten healthy volunteers. One was used to identify a population of CD34+/CD38- “hematopoietic stem cells and multipotent progenitors” and a population of CD34+/CD38+ “progenitors” based on immunofluorescence pattern/intensity and cellular morphology. The other two were immunostained respectively for CD34/CD56 and for CD34/SMA. Using the combined information we performed a non-computer-assisted quantification of nine bone marrow components (adipocytes, megakaryocytes, bone surfaces, four different vessel types (arteries, capillaries, sinusoids and collecting sinuses), other “hematopoietic stem cells and multipotent progenitors” and other “progenitors”) within 30 μm of “hematopoietic stem cells and multipotent progenitors”, “progenitors”, and “random cell profiles”. We show that the microenvironment of the “hematopoietic stem cells and multipotent progenitors” is significantly enriched in sinusoids and megakaryocytes, while the microenvironment of the “progenitors” is significantly enriched in capillaries, other “progenitors”, bone surfaces and arteries.

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“…The development of spatial transcriptomic approaches employing multiplexed immunofluorescence (IF), next‐generation sequencing (NGS), in situ sequencing (ISS) or in situ hybridisation (ISH) strategies have the potential to transform our understanding of the detailed interactions between the cellular and stromal components of the marrow in health and disease. 87 , 88 , 89 , 90 While these techniques are currently unsuitable for routine marrow assessment in MPN, they have the power to identify novel features and targets within the marrow that can be translated into future clinical studies. Complementary advances in AI‐driven image analysis of BMTs have the potential to further transform the field with the provision of an objective, quantitative framework for the evaluation of distinct cellular and stromal features that can be combined into an integrated analysis (Figure 3 ).…”

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“…Clustered logistic regression was used to calculate the odds ratio (OR), ie, the likelihood of a greater or a smaller prevalence of a given factor in one cell population compared with another (ie, at one histological site compared with another) (STATA 17, StataCorp, College Station, TX, USA). ( 27 ) The OR represents the ratio between “the odds of positive versus negative cells in population A” and “the odds of positive versus negative cells in population B.” An OR greater than one means that cell population A has a greater prevalence of positive versus negative cells than population B, and an OR smaller than one means that cell population A has a smaller prevalence of positive versus negative cells than population B. The p value indicates the likelihood that the ratio is statistically significant from one.…”

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