bioRxivCancer BiologyPreprint
iPSC-Derived Microglia-like Cells Exhibit Protocol-Dependent Transcriptomic Features and Robust Phagocytosis of Glioma Cells
Maya N. WalkeriD, Hui Tang, Caylee Silvers, Sasha Roth, Deanna Marie TiekiD, Bo HuiD, Shi‐Yuan ChengiD, Xiao SongiD
Abstract
Microglia are the brain-resident macrophages and key regulators of the brain tumor microenvironment. Although induced pluripotent stem cell-derived microglia (iMG) provide a valuable model for studying human microglial, systematic comparisons of differentiation protocols are limited, and their utility for modeling microglia-tumor cell interactions remains underexplored. Here, we analyzed 54 public RNA-seq datasets representing 22 iMG differentiation protocols, including embryoid body (EB)-based, two-dimensional (2D), transcription factor-induced, and coculture-based approaches. Most iMG closely resembled primary human microglia, although substantial protocol-dependent differences were observed. iMG generated using EB-based protocols showed higher TMEM119 expression, whereas those generated using 2D-based protocols showed higher P2RY12 expression. A widely adopted EB-based protocol showed the highest phagocytosis gene signature. Using this protocol, we generated iMG that efficiently phagocytosed patient-derived glioma stem-like cells and upregulated inflammatory and immunoregulatory genes following phagocytosis. These findings provide a transcriptomic benchmark for current iMG models and support their use in investigating microglia-glioma interactions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/739939v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@893ebforg.highwire.dtl.DTLVardef@769c08org.highwire.dtl.DTLVardef@fe06ccorg.highwire.dtl.DTLVardef@1705d70_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: experimental assay
- approach: statistical model
- Citations
- 0
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