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Generation of natural killer and myeloid cells in a 3D artificial marrow organoid system

Schell, B.; Zhao, L. P.; Kergaravat, C.; Lereclus, E.; Kalogeraki, M.; Fenaux, P.; Ades, L.; Toubert, A.; Espeli, M.; Balabanian, k.; Clave, E.; Dulphy, N.; Bisio, V.

2024-01-15 cell biology
10.1101/2024.01.15.575527 bioRxiv
Show abstract

The human bone marrow (BM) microenvironment involves hematopoietic and non-hematopoietic cell subsets organized in a complex architecture. Tremendous efforts have been made to model it in order to analyse normal or pathological hematopoiesis and its stromal counterpart. Herein, we report an original, fully-human in vitro 3D model of the BM microenvironment dedicated to study interactions taking place between mesenchymal stromal cells (MSC) and hematopoietic stem and progenitor cells (HSPC) during the hematopoietic differentiation. This artificial marrow organoid (AMO) model is highly efficient to support NK cell development from the CD34+ HSPC to the terminally differentiated NKG2A-KIR2D+CD57+ NK subset. In addition, myeloid differentiation can also be recapitulated in this model. Moreover, mature NK cell phenotype showed significant differences in the AMO compared to a conventional 2D coculture model for the expression of adhesion molecules and immune checkpoint receptors, thus better reflecting the NK cell behaviour in the BM microenvironment. Lastly, we proved that our model is suitable for evaluating anti-leukemic NK cell function in presence of treatments. Overall, the AMO is a versatile, low cost and simple model able to efficiently recapitulate hematopoiesis and granting better drug response taking into account both immune and non-immune BM microenvironment interactions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=187 HEIGHT=200 SRC="FIGDIR/small/575527v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@f9288corg.highwire.dtl.DTLVardef@1d51c8corg.highwire.dtl.DTLVardef@4563a9org.highwire.dtl.DTLVardef@1920e3c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Published in Scientific Reports (predicted rank #2) · training set

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