Eradication of specific donor-dependent variations of mesenchymal stem cells in immunomodulation to enhance therapeutic values

Abstract

Mesenchymal stem cells (MSCs) are one of the most widely clinically trialed stem cells, due to their abilities to differentiate into multiple cell lineages, to secrete regenerative/rejuvenative factors, and to modulate immune functions, among others. In this study, we analyzed human umbilical-cord-derived MSCs from 32 donors and revealed donor-dependent variations in two non-correlated properties, (1) cell proliferation, and (2) immune modulatory functions in vitro and in vivo, which might explain inconsistent clinical efficacies of MSCs. Through unbiased transcriptomic analyses, we discovered that IFN-γ and NF-κB signaling were positively associated with immune modulatory function of MSCs. Activation of these two pathways via IFN-γ and TNF-α treatment eradicated donor-dependent variations. Additional transcriptomic analyses revealed that treatment with these two factors, while having abolished donor-dependent variations in immune modulatory function, did not overall make different donor-derived MSCs the same at whole transcriptomic levels, demonstrating that the cells were still different in many other biological perspectives, and may not perform equally for therapeutic purposes other than immune modulation. Pre-selection or pre-treatment to eradicate MSC variations in a disease-treatment-specific manner would therefore be necessary to ensure clinical efficacies. Together this study provided novel insights into the quality control perspective of using different-donor-derived MSCs to treat inflammation-related clinical conditions and/or autoimmune diseases.

Fig. 1. Donor-dependent variations of huMSC proliferation and immune modulation.

A Three lineage differentiation of huMSCs and expression of cell surface markers. Upper Panel from left to right: MSCs differentiated to adipocytes, chondrocytes, and osteocytes. B BV2-suppression capacity and proliferation capacity of 32 lines of huMSCs. The black bars represent the ratio of BV2 cell mass after 48 h cultured in MSC-CM compared to RPMI-1640 (control medium). The red dots represent the ratio of total huMSC mass at 72 h after inoculation compared to 1 h after inoculation. C correlation between BV2-suppression capacity and huMSC proliferation capacity of 32 huMSC lines. D Boxplot shows BV2-suppression capacity between male (n = 20) and female (n = 20) huMSC lines, eight extra huMSC lines were added to increase the statistical power.

Fig. 2. Donor-dependent variations in immune modulation of huMSCs in LPS-induced neural inflammation animal model in vivo.

A Schematic diagram shows in vivo assessment MSC-CM treatment efficacies in LPS-induced neuroinflammation animal model. Open-field-test was used as the main behavioral readout. Boxplots show ambulatory distance (B) and episodes (C) of the open-field-test of each treatment groups. All data were normalized to the average value of the LPS group. D Boxplot shows inflammatory factors TNF-α mRNA levels in hippocampus of each group. Data were also normalized to the average value of the LPS group, and presented as mean ± SEM, *P < 0.05, **P < 0.01, ****P < 0.0001.

Fig. 3. Transcriptomic analysis of 32 lines of huMSCs revealed functional modules related to BV2-suppression capacity.

A PCA of 32 huMSC lines. B Heatmap shows expression and clustering of genes, expression of which significantly correlated to BV2 inhibition capacity of 32 lines of huMSCs. C GO enrichment analysis of BV2 inhibition correlated genes. IFN-γ, autophagy, and related terms are highlighted in red, which are positively correlated with BV2 inhibition. Candidate genes belonging to each GO term are shown in blue. D GSEA analysis of enriched TFBS targeting gene sets, most of which, except for one, were positively correlated with BV2 inhibition (normalized enrichment score (NES) > 0). E Correlation between gene expression levels of two subunits of NF-κB complex and BV2 inhibition capacity. F Network shows connection between enriched GO terms, TFBS targeting gene sets, and positively correlated genes. Red squares represent GO terms and blue triangles represent TFBS targeting gene sets. The nodes of green balls are genes, which belonging to both corresponding GO terms and TFBS targeting gene sets.

Fig. 4. Two-factor stimulation abolished donor-dependent variations of huMSCs in immune suppression.

A Anti-inflammation genes IDO1, CXCL9 and IL6 were extensively up-regulated in huMSCs by stimulation of TNF-α and IFN-γ (2-factors). B In vitro analysis on BV2 inhibition showed elimination of donor-dependent variations in immune-modulations by two factors. C–E eradication of specific donor-dependent variations of huMSCs regarding treatment efficacies in LPS-induced neuroinflammation model, by open-field-motor scoring and hippocampal TNF-α expression. All data were normalized to LPS group, and were presented as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Fig. 5. Transcriptome analysis of huMSCs before and after 2-factor treatment.

A PCA of all samples including 3 different genetic background and 2 conditions. B Heatmap demonstrating differentially expressed genes (DEGs) between 2 conditions. C GO enrichment analysis of DEGs in B. D Bar-plot demonstrating percentage of proliferating cells before and after 2-factor stimulation based on EdU assay. E Bar-plot shows percentage of cells in each cycle phase before and after cytokine stimulation based on flow cytometry.

Fig. 6. Two transcriptomic data sets (32 huMSC lines and 3 huMSC lines with and without 2-factor stimulation) revealed common genes and pathways.

A Venn diagram shows the overlap between genes up-regulated by 2-factor stimulation and genes positively correlated to BV2 inhibition capacity. B GO enrichment analysis of overlapped 227 genes. C GSVA heatmap shows specific GO-term associated gene sets in 32 huMSCs that positively or negatively correlated with BV2-cell immune suppressive capacity, and their expression levels before and after 2-factor stimulation. Results clearly indicated that interferon and NF-κB pathway associated genes were upregulated upon 2-factor stimulation, whereas genes related to autophagy and protein deacetylation did not correlate well with 2-factor stimulation.