A spatial transcriptomics based Label-free Method for Assessment of Human Stem Cell Distribution and Effects in a Mouse Model of Lung Fibrosis
收藏NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE253378
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Recently, cell therapy has emerged as a promising treatment option for various disorders. Given the intricate mechanisms of action (MOA) and heterogenous distribution in target tissues inherent to cell therapy, it is necessary to develop more sophisticated, unbiased approaches to evaluate the distribution of administered cells and the molecular changes at a microscopic level. This study introduces a label-free approach for assessing the tissue distribution of administered human mesenchymal stem cells (hMSCs) and their MOA, leveraging spatially resolved transcriptomics (ST) analysis. The hMSCs were introduced into a mouse model with lung fibrosis, followed by the manipulation of ST to visualize the spatial distribution of hMSCs within the tissue. This was achieved by capitalizing on interspecies transcript differences between human and mouse. Furthermore, the method allowed for the examination of molecular changes associated with the spatial distribution of hMSCs. Therefore, our method has the potential to serve as an effective tool for various cell-based therapeutic agents. We administered human mesenchymal stem cells (hMSC) in a mouse model of lung fibrosis and presented a method for evaluating both the tissue-level distribution of the administered stem cells and their effect on treated tissue by using Visium Spatial Transcriptomics.
创建时间:
2024-08-01



