The use of single-cell RNA sequencing and spatial transcriptomics has recently challenged and refined concepts in the field of wound healing by enabling detailed characterisation of cellular heterogeneity while providing spatial context. Previously used separately, these methods are now increasingly applied together due to the advent of newer platforms, enabling delineation of discrete subpopulations of cutaneous cells, including epidermal basal stem cells, fibroblasts, neutrophils, macrophages, and T cells. Detailed transcriptional profiling of these subpopulations has revealed upregulation of either pro-regenerative or pro-fibrotic pathways. For example, fibroblast heterogeneity significantly influences wound healing outcomes, with Lef1+ and Trps1+ fibroblasts promoting regeneration through Wnt and Hedgehog pathway activation, whereas fibroblasts isolated from scars show upregulation of genes that promote excessive fibroblast activation, such as the YAP mechanotransduction pathway. Despite these insights, clinical translation can be challenging due to platform variability, computational demands, and biological heterogeneity inherent to models of wound healing. Ultimately, integration of multiomic data and public databases such as the Human Skin Atlas is necessary to increase biomarker reliability and mechanistic clarity. As these technologies become more accessible and standardised, they hold great potential for personalised wound care management by enabling molecular risk stratification and targeted therapeutic interventions. This literature review aimed to elucidate the latest advancements in gene expression analysis, with particular focus on the use of scRNA-seq and ST in the context of wound healing. The goal is to summarise previous efforts that contribute to the understanding of the cellular mechanisms of wound healing and reflect on how these insights could influence future therapeutic development.
Bergman et al. (Fri,) studied this question.