A Spatial Transcriptomics Based Label-Free Method for Assessment of Human Stem Cell Distribution and Effects in a Mouse Model of Lung Fibrosis

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 are 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 is achieved by capitalizing on interspecies transcript differences between humans and mice. Furthermore, the method allowed for the examination of molecular changes associated with the spatial distribution of hMSCs. Therefore, this method has the potential to serve as an effective tool for various cell-based therapeutic agents. Utilizing ST and alignment algorithms, the distribution of human mesenchymal stem cells is successfully identified for the first time. Also, this approach incorporates a statistical analysis to reliably manage inaccurately classified RNA transcripts. Furthermore, detailed analyses ensued to identify molecular markers and cell types associated with these cell therapeutic agents. image