Background:Autologous cell-based therapy using dermal sheath cup (DSC) cells was reported as a new treatment for male and female pattern hair loss. However, the mechanisms underlying its action remain unclear. Objective:We investigated the mechanisms underlying the efficacy of DSC cells in cell-based therapy.
Methods:We conducted multivariate analysis to categorize individuals based on treatment response as responders and non-responders. The differentially expressed genes in DSC cells from the two groups were evaluated using bulk transcriptome, quantitative polymerase chain reaction, and single-cell transcriptome analyses. We performed live cell imaging combined with immunostaining to characterize the DSC subpopulation associated with responders.
Results:We identified nine and three genes as high efficacy (HE) and low efficacy (LE) marker genes, respectively. The HE subpopulations were enriched for cell migration-related genes in single-cell analysis. In contrast, the LE subpopulation was enriched for basement membrane and vasculature-related genes. Moreover, DSC cells in culture were immunocytochemically and morphologically heterogeneous, expressing characteristic factors. Furthermore, live cell imaging showed that DSC cells expressing integrin subunit alpha 6 (ITGA6), an HE subpopulation gene, had markedly higher mobility than those expressing the LE subpopulation genes collagen type IV or CD36.
Conclusions:ITGA6-positive DSC cells, with superior migratory activity, may contribute to cell-based therapy by promoting cell migration into nearby hair follicles.
Keywords:Autologous cell-based therapy; Cell migr; Dermal sheath cup cells; Pattern hair loss.
High migratory activity of dermal sheath cup cells associated with the clinical efficacy of autologous cell-based therapy for pattern hair loss
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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