ArticlebioRxiv : the preprint server for biology2025
Exploring the immune environment of glioblastoma through single-cell RNA sequencing in humanized mouse models.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Glioblastoma (GBM) is the deadliest primary brain tumor in adults, where current therapies fail to meaningfully extend survival. Available animal GBM tumor models, especially therapy-resistant and recurrent ones with unique immunological aspects, are restricted, impeding innovative treatment research. To confront this critical obstacle we established a unique GBM mouse model that utilizes patient-derived xenografts (PDXs) within humanized mice. Methods: We selected two immune-deficient mouse models to facilitate the reconstitution of myeloid lineage cells. After undergoing myeloablation, mice received CD34+ hematopoietic stem progenitor cells derived from human umbilical cord blood for humanization. Upon confirming the reconstitution of human blood cells, mice were xenografted with PDXs resistant to radiation. Tumor profiles and immune cell infiltration were analyzed via flow cytometry, immunohistochemistry, and single-cell RNA sequencing (scRNA-seq). The findings were evaluated against scRNA-seq data from recurrent human GBM. Results: A diverse range of human immune cells, including T, NK, and myeloid lineage cells, infiltrated PDX tumors in humanized mice. Notably, gene expression profiles in these immune cells resembled that of recurrent human GBM. Unlike conventional xenograft models, this model highlighted enhanced tumor diversity, particularly a high fraction of neural progenitor-like cells. Conclusions: Our humanized GBM mouse model displayed an immune cell signature similar to recurrent GBM. This model is a valuable resource for analyzing the tumor immune landscape and assessing new therapies, particularly immunotherapies. By enabling effective evaluation of novel treatments, our model has the potential to significantly advance GBM research.
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