Approaches to HIS mouse model optimization
Some HIS (Human Immune System) mouse models demonstrate enhanced human myeloid cell development, achieved through various genetic strategies to express human cytokines in different combinations and at varying levels. However, these models only partially replicate human immune responses in vivo, and significant advancements are still needed to achieve full immunological humanization. For instance, current myeloid-enhanced mouse models often experience a reduced lifespan post-humanization, accompanied by severe anemia. This is linked to non-physiological, persistently high cytokine levels during the terminal stages of humanization, which over-activate human macrophages. Ideally, cytokine expression should be optimized to physiological levels or minimized once the human immune system is established.
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Additionally, human T cells in HIS mice lack human HLA education, and lymph node development remains suboptimal. Notably, no existing HIS mouse models exhibit germinal centers in secondary lymphoid tissues, which limits memory B cell development and restricts the efficacy of antigen-specific antibodies and cellular responses. In hu-PBL (human peripheral blood leukocyte) models, graft-versus-host disease (GvHD) typically develops within four weeks after human PBMC (peripheral blood mononuclear cell) infusion. While B2M (beta-2 microglobulin) knockout NSG/NOG mice can delay GvHD onset, they exhibit constitutively high levels of circulating human interferon-gamma. Furthermore, B2M deletion disrupts the neonatal Fc receptor (FcRn), reducing the stability of circulating antibodies and complicating pharmacokinetic/pharmacodynamic (PK/PD) studies of antibody-based immunotherapies.
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To address these limitations, more comprehensive genetic modifications are essential for the future optimization of HIS mouse models. Promising strategies for improving these models are discussed below.
Considerations for upgrading HIS mouse models
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Prospective approaches to achieve complete immunological humanization
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