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Towards a better preclinical cancer model - human immune aging in humanized mice. | LitMetric

Towards a better preclinical cancer model - human immune aging in humanized mice.

Immun Ageing

Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, Proteos, Singapore, 138673, Republic of Singapore.

Published: September 2023

Background: Preclinical models are often used for cancer studies and evaluation of novel therapeutics. The relevance of these models has vastly improved with mice bearing a human immune system, especially in the context of immunotherapy. Nonetheless, cancer is an age-related disease, and studies often overlook the effects of aging. Here we have established a humanized mouse model of human immune aging to investigate the role of this phenomenon on liver tumor dynamics.

Methods: Multiple organs and tissues (blood, thymus, lung, liver, spleen and bone marrow) were harvested from NOD-scid IL2rγ (NIKO) mice reconstituted with human immune cells, over a period of 60 weeks post-birth, for immune profiling. Young and aging immune cells were compared for transcriptomic changes and functional differences. Effect of immune aging was investigated in a liver cancer humanized mouse model.

Results: Focusing on the T cell population, which is central to cancer immunosurveillance and immunotherapy, we showed that the proportion of naïve T cells declined while memory subsets and senescent-like cells increased with age. RNA-sequencing revealed that downregulated genes were related to immune responses and processes, and this was corroborated by reduced cytokine production in aging T cells. Finally, we showed faster liver tumor growth in aging than younger humanized mice, which could be attributed to specific pathways of aging T cell exhaustion.

Conclusion: Our work improves on existing humanized (immune) mouse model and highlights the importance of considering immune aging in liver cancer modeling.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10523735PMC
http://dx.doi.org/10.1186/s12979-023-00374-4DOI Listing

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