Runx1+ vascular smooth muscle cells are essential for hematopoietic stem and progenitor cell development in vivo – Nature.com

By Embryonic Stem Cells

A subpopulation of subaortic mesenchyme in the AGM co-expresses NG2 and Runx1

We examined the expression of PC/vSMC markers in the dorsal aorta of E10.5 and E11 mouse embryos. Wholemount immunostaining and immunohistochemistry on frozen sections were performed using PC/vSMC markers NG2 or SMA with CD31, an endothelial and HSPC marker (TableS1). Imaging analysis showed that NG2+SMA+CD31- vSMCs surround NG2-SMA-CD31+ endothelial cells (Figs.1a, S1a, b), confirming previous reports27. Further to its expression in hematopoietic and hemogenic endothelial cells, Runx1 was also detected in the sub-aortic mesenchyme22,23. Therefore, we hypothesised that at least some of these cells also express NG2. We first confirmed that both intra-aortic hematopoietic cell clusters (IAHCs) (Fig.1b, stars) and hemogenic endothelial cells (Fig.1b, arrowheads) are Runx1+; we also identified a subpopulation of NG2+ PC/vSMCs, mainly located in the ventral aspect of the dorsal aorta, that also express Runx1 (Fig.1b, arrows). Other Runx1+ cells in the perivascular area do not express NG2 (Fig.1b). Finally, we confirmed our recent study28 that some cells around the notochord express NG2 in the trunk (Fig.S1a, circle). However, these peri-notochord cells do not express SMA, CD31 (Fig.S1a, circle) nor Runx1 (Fig.S1ef). To confirm the presence of NG2+Runx1+ cells in the E11 AGM, we used Runx1-IRES-GFP mouse embryos29. In these GFP knock-in mice, GFP intensity correlates with Runx1 expression level. Flow cytometric analysis showed the presence of a distinct population of NG2+Runx1(GFP)+ cells in the AGM (Fig.1c). These cells first appear at E10, in line with the presence of Runx1 in mesenchymal cells30 and importantly, their frequency peaks at E10.5 (Fig.1d). Together, these data show that in the AGM, a subset of the sub-aortic mesenchyme expresses both NG2 and Runx1 and that the highest frequency of these cells coincides with the onset of HSC generation at E10.5.

a Three-dimensional (3D) wholemount immunostaining with SMA, CD31 and NG2 of E10.5 (3138 somite pairs (sp)) WT dorsal aorta; b NG2 and Runx1 expression on single plane wholemount WT E10.5 sections. NG2+Runx1+vSMCs (arrows), hemogenic endothelial cells (arrowheads) and intra-aortic hematopoietic clusters (IAHCs, stars) (TableS1); c Representative example of flow cytometric analysis of NG2+Runx1(GFP)+ (green box) in E10.5 Runx1-IRES-GFP AGM and E10.5 WT control. d Percentages of NG2+Runx1(GFP)+ cells in E9 (21-25sp) body (n=6), E10/E10.5/E11 AGMs (n=8/7/7), N=5, Kruskal-Wallis and Dunns post-hoc test. e Representative examples of wholemount 3D-images showing SMA, CD31 and NG2 in E10.5 cKO dorsal aortae; f SMA, Runx1 and CD31 immunofluorescence of E11 WT and cKO transversal frozen sections; n=WT/cKO: 2/2, N=2. g cKit and CD31 wholemount 3D-images in E10.5 WT and cKO AGM; h Number of intra-aortic hematopoietic clusters (IAHCs) in E10.5 AGM; n=WT/KO: 5/4, N=4. Number of colony forming unit-culture (CFU-C) in i E10.5 (31-38sp) AGM; n=WT/HET/KO: 14/10/5 embryos; N=7 and j E11 (4352sp) AGM; n=WT/HET/KO: 22/8/19 embryos; N=11; one-way ANOVA and Tukeys post-hoc test (TableS2). k Percentages of donor cell chimerism 4-months post-transplantation of 6 E11 WT (NG2+/+;Runx1fl/+or NG2+/+;Runx1fl/fl), 7 HET (NG2-Cre;Runx1fl/+) and 6 cKO AGMs (NG2-Cre;Runx1fl/fl) into sub-lethally adult irradiated recipients (1xAGM cells transplanted/recipient; N=4). Each dot represents one recipient. Mice are reconstituted when 5% donor cells are found in the host peripheral blood (dashed line); one-tailed Z score test for two population proportions (TablesS3 and S4). For wholemount staining in a, b, e, g: WT/cKO (N=6/4): SMA (n=9/7), CD31 (n=10/7), cKit (n=3/2), NG2 (n=3/1) and WT Runx1 (n=4) in 3 distinct combinations (TableS1). D = dorsal, V = ventral. N = number of independent experiments; n = number of biological samples (embryos). All data are presented as mean valuesSEM. Source data for d, h, i, j and k are provided as a Source Data file.

Runx1 deletion in endothelial cells impairs HSC emergence in the AGM24,25,26. However, the effect of Runx1 deletion in PC/vSMCs on hematopoiesis in vivo is still unknown. To address this, we examined conditional knock-out (cKO) NG2-Cre;Runx1fl/fl mouse embryos. In previous studies, the NG2-Cre mouse strain revealed a role for pericytes in supporting both fetal liver and adult bone marrow HSC maintenance31,32. Our data shows that E10.5 and E11 cKO embryos do not exhibit visible vascular abnormalities. This was confirmed by the normal expression of CD31, SMA and NG2 (Figs.1e, f, S1c, d) in the AGM. In contrast, SMA+Runx1+ PC/vSMCs with low expression of Runx1 were reduced in the cKO dorsal aorta compared to WT littermate controls (Figs.1f, S1eg). CD31+Runx1+ endothelial cell number and frequency was also decreased (Fig.S1g). Furthermore, CD31+cKit+ IAHC numbers were significantly reduced by three-fold (p=0.02) (Fig.1g, h). Hematopoietic progenitor (HP) assays were performed to test if hematopoietic function was affected. All HP numbers were significantly reduced in cKO AGMs at both E10.5 (Fig.1i, TableS2) and E11 (Fig.1j, TableS2). To test whether definitive HSCs were also affected, we performed HSC assays in vivo. At 1- and 4-months post-transplantation of AGM cells into sub-lethally irradiated mice, chimerism and multilineage reconstitution were examined by flow cytometry in the peripheral blood. Compared to the WT littermate control group, in which 66.7% (4 out of 6) recipients were reconstituted, only 14.3% (1 in 7, p=0.025) and 16.7% (1 in 6, p=0.040) mice injected with heterozygous or homozygous cKO AGMs, respectively, were reconstituted over the long term (Fig.1k, TablesS34). These findings indicate that the absence of Runx1 in aortic NG2+ cells impairs HSC generation and/or maintenance and HP development in the AGM.

To test whether NG2+ cells contribute directly to hematopoietic lineages, we isolated NG2+ and NG2+Runx1(GFP)+cells from E11 WT and Runx1-IRES-GFP AGMs, respectively, and seeded them in methylcellulose. In parallel, NG2- or NG2-cKit+ cells were sorted as controls. HPs were exclusively found in the NG2- cell fractions. Neither NG2+ cells (Fig.S2a) nor NG2+Runx1(GFP)+cells (Fig.S2b) gave rise to hematopoietic cell colonies in vitro (TableS5). To further assess whether NG2+ cells are hematopoietic precursors, we crossed NG2-Cre mice with a knock-in reporter mouse line in which tdTomato is preceded by a transcriptional stop flanked by two loxP sites under the Rosa26 promoter. In these mice, NG2+ cells and their progeny are tdTomato+. E11 AGM-derived tdTomato+ and tdTomato- cells were sorted and seeded in methylcellulose. HPs were only found in the tdTomato- cell fraction (Fig.S2c, TableS5) reinforcing the observation that NG2+ cells and their progeny do not contribute to hematopoietic lineages at this stage. Flow cytometric analysis confirmed the presence of tdTomato in a subset of NG2+ cells in the E11 AGM (Fig.S2d), validating our mouse model, while no overlap was found between tdTomato and CD45, a hematopoietic cell marker (Fig.S2e). We next performed immunohistochemistry on NG2-Cre;tdTomatofl/+ frozen sections and confirmed the expression of tdTomato in a subset of SMA+ cells (Fig.S2f) in the E11 AGM. CD31+ cells did not express tdTomato (Fig.S2g). Further analysis revealed that cells expressing hematopoietic markers F4/80 and CD45 do not co-express NG2 nor SMA (Fig.S2h). Together, these data indicate that NG2+ cells do not contribute to the AGM HSPC pool and suggest that NG2+Runx1+ PC/vSMCs act as a supportive niche to maintain hematopoietic activity in the AGM.

In the early developing embryo, HSPCs reside in other intra-embryonic and extra-embryonic hematopoietic organs such as the head, fetal liver (FL), placenta and yolk-sac (YS). Flow cytometric analysis of these organs harvested from Runx1-IRES-GFP mouse embryos also confirmed the presence of NG2+Runx1(GFP)+ cells (Fig.S3a, b). We next performed in vitro HP functional assays with cells harvested from all organs and genotypes of NG2-Cre;Runx1fl at both E10 and E11 developmental stages. No significant differences were found when comparing the total CFU-C numbers between genotypes in most organs (Fig.S3c, d, TablesS67). A significant increase of total number of CFU-C was observed in E10 AGM in both heterozygous and cKO mouse embryos (Fig.S3c). When analyzed individually, a significant increase in the number of erythroid colonies was detected in the cKO compared to WT littermate (p=0.0149) (TableS6). Likewise, a 2.8-fold increase in the number of erythroid colonies was detected in the E11 cKO head compared to the WT littermate (p=0.01), while the total number of CFU-C in the E11 head remained unchanged (TableS7). Moreover, we found a significant decrease in both CFU-GM (p=0.016) and CFU-GEMM (p=0.039), between WT and cKO YS (TableS7), possibly due to the defect found in the E11 AGM.

To test whether HSC activity increases in the FL due to the possible migration of AGM HSCs, E11 FL cells from all genotypes were transplanted into sub-lethally irradiated recipient mice. Neither the donor chimerism nor the percentage of reconstituted mice by donor cells showed changes between the groups (Fig.S3e). Compared to NG2+/+;Runx1fl/+ WT littermates, in which 70% of recipients (7 out of 10) were reconstituted, mice injected with NG2-Cre:Runx1fl/+ heterozygous or NG2-Cre:Runx1fl/fl cKO E11 FL showed similar reconstitution over the long term, with 67% (2 out of 3, p=0.348) and 60% (3 out of 5, p=0.421) reconstituted mice, respectively (Fig.S3e, TablesS34). Since the deletion of Runx1 in NG2+ cells only affects HSPCs in the AGM, immunohistochemistry on WT embryonic head and placenta was performed to localise NG2+Runx1+ cells. The rare NG2+Runx1+ double positive cells identified did not seem to be perivascular (Fig.S3f, stars). In line with this observation, we found that Runx1 and SMA do not overlap when NG2 and SMA were expressed in PC/vSMCs (Fig.S3f, arrowheads). Instead, the head contains few NG2+SMA- that are F4/80+, suggesting that NG2+Runx1+ cells are macrophages (Fig.S3f, arrowhead). Overall, our data shows that the deletion of Runx1 in NG2+ cells only affects selective HSPC subsets in non-AGM hematopoietic organs in the E11 mouse embryo.

To better understand the role of Runx1 in the HSC-generating microenvironment, single-cell RNA-sequencing (scRNA-seq) on NG2+/+;Runx1fl/+ E11 AGM was performed. We used graph-based clustering and known marker distribution to define and investigate the gene expression profiles of various populations that reside in the E11 AGM and identified eight populations of interest (Fig.2a, b). The co-expression of Cspg4 (NG2) and Acta2 (SMA) in the PC/vSMC population was confirmed (Fig.2c). This population is also enriched in Rgs5, Pdgfrb and Pdgfra in line with our previous work28, and a subset of these cells express Runx1 (Fig.2c, d), confirming our imaging and flow cytometric analysis. The expression of Mcam (CD146 or S-ENDO1), a pericyte/vSMC precursor marker recently identified in a subset of NG2+ cells in the E11 AGM21 and upregulated in AGM hematopoiesis supportive stromal cell lines19, was detected in a subset of PC/vSMCs, partially overlapping with Runx1+ cells (Fig.2c, d). However, Mcam was mainly enriched in endothelial cells (ECs) and also in subpopulations of hemogenic endothelial cells, including those entering endothelial-to-hematopoietic transition (HEC/EHT), IAHCs and SNS cells (Fig.2d), confirming published work including ours28,33. Immunostainings with CD146 and CD31 on E11 WT AGM frozen sections further validated our sequencing analysis at the protein level: both CD31+ endothelial cells (Fig.2e, f, arrows) and SMA+ PC/vSMCs (Fig.2f, stars) are CD146+. Importantly, Pecam-1 (CD31) expression in PC/vSMCs was low/negative in our scRNA-seq data (Fig.2c, d), in line with our immunohistochemistry, confocal imaging, and our recent published work28. Other genes expressed by hematopoietic and hemogenic/endothelial cells such as Adgre1 (F4/80), Mrc1 (CD206), Cdh5 (VE CADHERIN), Tek (TIE-2), CD34, CD93, Pdgfb, Sox7, Sox17, Sox18, Gfi1b, and Itga2b (CD41) were not expressed in PC/vSMCs (Fig.2d). These genes were used to distinguish populations of macrophages (MPs), IAHCs, HEC/EHT, and ECs (Fig.2ad). Erythroid cellsand erythroid progenitors (Ery/EryP; Gypa/CD235+), SNS (Gata3+) and skeletal muscle progenitors (SkMP; MyoD1+, Cdh15+) were also identified (Fig.2ad). Kit was expressed in all IAHCs and in a subset of PC/vSMCs, while Kit expression in HEC/EHTs was low (Fig.2d). Altogether, these data show that we successfully captured multiple cell types that comprise the E11 AGM, including a population of Runx1+ PC/vSMCs which constitutes 19.7% of all NG2+Acta2+ PC/vSMCs cells. Furthermore, the transcriptome of Cspg4+Runx1+ non-hematopoietic non-endothelial PC/vSMCs was found to partially overlap with that of the Cspg4+Mcam+ PC/vSMC precursors previously described21.

a t-SNE plot highlighting eight populations of interest identified in the E11 WT AGM. Each dot represents one cell and colours represent cell clusters as indicated. The number of cells in each population is shown in brackets. MP (macrophages); Ery/EryP (erythroid/progenitors); IAHC (intra-aortic hematopoietic clusters); HEC/EHT (hemogenic endothelial cells including those that enter endothelial-to-hematopoietic transition); EC (endothelial cells); SNS (sympathetic nervous system); SkMP (skeletal muscle progenitors), PC/vSMC (pericytes/vascular smooth muscle cells, NG2+Acta2+). Other cells (OC) are coloured in grey. b t-SNE plot highlighting the eight populations identified after excluding all other (grey) cells. c Zoom into PC/vSMC cluster (black rectangle) further show the presence or the absence of selected genes that characterise this population and confirms the presence of Runx1 in a subset of cells. d Violin plots showing distribution of expression for selected genes that contributed to the identification of cell clusters. Immunohistochemistry on frozen E11 WT sections stained with eCD146/CD31/DAPI and fCD146/SMA/DAPI, n=2 samples tested, N=2 independent experiments. Arrows: vascular cells, asterisks: perivascular cells. DA: dorsal aorta, CV: cardinal veins, NC: notochord. Source data for e (first column,20X) is provided as a Source Data file.

Our scRNA-seq analysis revealed that not all Cspg4+Runx1+ cells in the E11 AGM express Acta2 (Fig.3a, b). We therefore investigated if Cspg4+Runx1+Acta2 cells are PC/vSMCs which had not yet acquired Acta2 expression. Differential expression analysis of Acta2+ versus Acta2 cells within the NG2+Runx1+ cell population in the WT AGM revealed that markers of sclerotome-derived vSMCs such as Sox9, Pax1, Pax9 and Col2a134 are among the highest upregulated genes in Cspg4+Runx1+Acta2 cells (Fig.3c). In contrast, Cspg4+Runx1+Acta2+ cells are enriched in genes that identify more mature pericytes such as Acta2, CD248, Mcam, Rgs5 or Pdgfrb (Fig.3c), some of which are potential Runx1 target genes (star). Pdgfra and Ptn genes were recently associated with Runx1+ subaortic (non-smooth muscle) mesenchymal cells with possible role in hematopoiesis in the E10.5 AGM of the mouse embryo35. Our scRNA-seq analysis show that, in E11 AGM, Pdgfra and Ptn are also expressed in Cspg4+Runx1+ cells with no significant difference between Acta2+ and Acta2 (Fig.3c). Further analysis showed that Gene Ontology (GO) biological processes significantly enriched in Cspg4+Runx1+Acta2+ cells include smooth muscle cell chemotaxis and migration, collagen-activated signalling pathway, neural crest cell differentiation and regulation of BMP signalling (Fig.3d), previously shown by our laboratory to control in vivo HSPC generation in the mouse AGM28. In Cspg4+Runx1+Acta2 cells, significantly enriched GO biological processes include mesenchymal stem cell differentiation and cartilage and bone development (Fig.3e), consistent with the sclerotome origin of these cells.

a t-SNE plots showing the distribution of Runx1 and Acta2 expression in NG2+Runx1+ cells in the WT E11 AGM after excluding all other (grey) cells found in the Fig.2a. b Zoom into NG2+Runx1+ cluster (black rectangle) shows the presence or the absence of Acta2. c Heatmap showing the expression of Cspg4 and Runx1 and 15 selected genes out of 25 top significantly upregulated genes in WT NG2+Runx1+Acta2+ cells (upper half) and NG2+Runx1+Acta2- cells (bottom half) at single cell level; *Runx1 potential target genes. Pdgfra and Ptn genes were next added to inform their expression in both populations. Barplot of fold enrichment for selected GO biological processes significantly overrepresented in genes significantly upregulated in both dWT NG2+Runx1+Acta2+ and eNG2+Runx1+Acta2- cells. f t-SNE of WT E11 AGM cells, overlaid with principal pseudotime curve inferred by Slingshot, predicting a lineage from NG2+Runx1+Acta2- cells to NG2+Runx1+Acta2+ cells. g WT NG2+Runx1+cells arranged in pseudotime (x-axis) based on the inferred curve. Y-axis represents log normalised gene expression.

Indeed, PC/vSMCs in the AGM have been shown to originate from the sclerotome and display markers of this compartment at least during the early phases of mural cell recruitment36. A recent study showed that the maturation of sclerotome-derived vSMCs in the mouse AGM depends on a transcriptional switch from a sclerotome signature with the repression of Pax1, Scx and Sox9, and activation of Acta2 and other vSMC genes34.

To test whether NG2+Runx1+Acta2 cells follow a maturation trajectory towards Cspg4+Runx1+Acta2+ vSMCs, we performed cell lineage inference with Slingshot, a trajectory inference method for scRNA-seq data that can incorporate knowledge of developmental markers. Having defined a cluster of Cspg4+Runx1+Acta2 cells as an origin, Slingshot infers a cell lineage and constructs a pseudotime curve representing that lineage (Fig.3f, arrow). Gene expression along pseudotime shows that sclerotome markers such as Sox9, Pax1 and Pax9 are gradually downregulated while markers of mural cells such as Acta2, Rgs5, Pdgfr, Cnn1, Mcam and CD248, are gradually upregulated in an inferred transition from Cspg4+Runx1+Acta2 to Cspg4+Runx1+Acta2+ cells (Fig.3g). Our scRNA-seq analysis shows that Cspg4+Runx1+ AGM cells display a sclerotome-derived vSMC transcriptomic profile.

We next explored the impact of Runx1 deletion in the hematopoietic niche and its possible effect on PC/vSMCs by performing scRNA-seq of NG2-Cre;Runx1fl/fl cKO E11 AGMs (Fig.4a, b). Cell populations were defined in a similar way to the WT AGM by using graph-based clustering and known marker distribution. This comparison revealed changes in the proportions of the different cell types between WT and cKO AGM, including a significant reduction in the proportion of cells associated with clusters 2 (Ery/EryP), 3 (IAHC), 6 (SNS), and 7 (SkMP) (Fig.4c).

a t-SNE plot showing eight populations of interest found in the E11 cKO AGM. Each dot represents one cell and colours represent cell clusters as indicated. MP(macrophages); Ery/EryP(erythroid/progenitors); IAHC (intra-aortic hematopoietic clusters); HEC/EHT (hemogenic endothelial cells including those that enterendothelial-to-hematopoietic transition),EC (endothelial cells); SNS (sympathetic nervous system); SkMP(skeletal muscle progenitors); PC/vSMC (pericytes/vascular smooth muscle cells, NG2+Acta2+). Other cells (OC)are coloured in grey. The number of cells in each cluster is shown in brackets. b t-SNE plot highlighting the eight populations identified after excluding all other (grey) cells. c Percentage of single live cells found in each E11 AGM sample (cell number/total cells) defined by scRNA-seq in WT (full bars) and cKO (empty bars) AGMs. Colours and numbers correspond to each population defined in a; chi-squared two-tailed test was used for comparison. d Barplot of fold enrichment for selected GO biological processes significantly overrepresented in genes significantly downregulated in cKO PC/vSMCs compared to their WT counterparts. Heatmap of ligand-receptor interactions inferred by NicheNet from e WT and f cKO E11 AGM cells. Colour represents the interaction potential score between the 10 top-ranked ligands expressed in ECs and their inferred targets expressed in PC/vSMCs. Ligands and receptors are ordered by hierarchical clustering. g Scatter plots of AUC vs log10(FDR) showing downregulated genes associated with selected GO terms in cKO PC/vSMCs. Red dots represent significantly downregulated genes (FDR<0.05); dashed line shows FDR = 0.05. Gene labels with red borders represent potential Runx1 target genes.

Changes in gene expression between WT and cKO Cspg4+Runx1+ cells were first investigated. We found that genes significantly downregulated in cKO Cspg4+Runx1+ cells were mainly associated with biological processes including translation, oxidative phosphorylation, cellular response to stress and mitochondria-related function (Fig.S4ac). As deletion of Runx1 may have also affected Runx1 PC/vSMCs, the transcriptome of all cKO Cspg4+Acta2+ PC/vSMCs with their WT counterpart was compared. Genes significantly downregulated in cKO Cspg4+Acta2+ PC/vSMCs had significant enrichment of biological processes including translation, smooth muscle cell differentiation, cytoskeleton, vasculogenesis and cell communication (Fig.4d). One pathway essential to vasculogenesis is PDGF-B/PDGFR; we therefore applied NicheNet on our WT scRNA-seq data to predict ligand-receptor interaction between ECs and PC/vSMCs, focusing on PDGF-B-related genes. The highest scoring predicted interaction was between Pdgfb, a growth factor released by ECs, and Nrp1 (Fig.4e), a receptor known to control the differentiation/recruitment of mesenchymal stem cells and the stimulation of smooth muscle cell migration37,38.

The interaction between Pdgfb and Pdgfrb was also amongst the highest scoring interactions in both WT (Fig.4e) and cKO (Fig.4f). Additional interactions involve Edn, Tgfb or Bmp pathways, previously associated with a role in AGM hematopoiesis39,40. Interestingly, in cKO ECs, Pdgfa, another gene from the PDGF family, was no longer in the top 10 ranking ligands (Fig.4f) possibly due to the downregulation of Pdgfra in cKO PC/vSMCs (Fig.4f). Other genes including Des, Angpt1, Gsk3b, Tcf21, Col1a1, Pcna, Ccnd3 and Mcm7, potential Runx1 downstream target genes41, were also significantly downregulated (Fig.4g, red boxes). The reduction inCol1a1 expression suggests changes in the gene profile of the extracellular matrix (ECM). Indeed, additional ECM related genes were significantly downregulated in the cKO PC/vSMCs, such as Sparcl1, Col3a1 and Col5a1 (Fig.4g). Collectively, these data show that the genetic programme of PC/vSMCs in cKO AGM is modified upon Runx1 deletion and this involves changes in molecules that constitute the ECM of the aortic wall.

Endothelial cells share the same basement membrane with PC/vSMCs42. This, coupled with the transcriptomic changes in the cKO PC/vSMCs described above, suggest that the genetic programme of the adjacent ECs may have also been altered by Runx1 deficiency in NG2+ cells. Although the number of endothelial cells in the NG2-Cre:Runx1fl/fl cKO did not significantly change (Fig.4a) and the formation of the dorsal aorta appeared to be unaffected (Fig.1e), we investigated transcriptomic changes in ECs that could affect their function in vivo. As before, we performed differential expression analysis, followed by overrepresentation analysis on genes significantly downregulated in cKO ECs (Fig.5a). Multiple GO biological processes were significantly overrepresented in these genes, with many related to EC development and angiogenesis; proliferation, migration and differentiation; response to hypoxia and fluid shear stress; as well as smooth muscle cell or mesenchymal cell development and hematopoiesis (Fig.5a). Interestingly, we found that Sox18 was the most downregulated gene in cKO ECs (Fig.5b). Col4a1, the most abundant extracellular matrix associated gene, known to co-localise with Sox18 in ECs in the mouse embryo43, was also found within the top 25 downregulated genes (Fig.5b). Sox18 and Col4a1 were the most downregulated genes associated with the blood vessel development GO term, while other gene expression including Cdh5, Pecam1, Sox17, Pdgfb, MCam and Notch were also affected.

a Barplot of fold enrichment for selected GO biological processes significantly overrepresented in genes significantly downregulated in cKO ECs compared to their WT counterparts. b Scatter plots of AUC vs log10(FDR) showing downregulated genes associated with selected GO terms including blood vessel development and mesenchymal cells and vSMCs in cKO ECs. Red dots represent significantly downregulated genes (FDR<0.05); dashed line shows FDR=0.05. Sox18 and Ctnnb1 expression in WT ECs in both scRNA-seq (c, EC zoom and t-SNE plots) and bulk RNA-seq post-sort (d, TPM). e Scatter plots of AUC vs log10(FDR) showing downregulated genes associated with selected GO terms including the basement membrane and extracellular matrix in cKO ECs. Red dots represent significantly downregulated genes (FDR<0.05); dashed line shows FDR=0.05. Selected genes that were altered in cKO ECs ine are shown in WT ECs in both scRNA-seq (f, ECand HEC/EHT zoom and t-SNE plots) and bulk RNA-seq post-sort (g, TPM). TPM: transcript per Million mapped reads values.

Genes associated with cell adhesion, regulation of smooth muscle cell proliferation and differentiation, along with mesenchyme development such as Sox18 and Ctnnb1 were also significantly downregulated in cKO EC (Fig.5b, arrow). We confirmed that both Sox18 and Ctnnb1 are expressed by ECs in our single cell datasets (Fig.5c) and next validated their expression in NG2-PDGFR-ckit-CD45-CD31+ Runx1- purified ECs from E11 Runx1-IRES-GFP AGMs (Figs.5d, S5a).

Some significantly downregulated genes associated with blood vessel development such as Loxl2, Hspg2, Col4a2, Col15a1 and Col18a1 (Fig. 5b)are also known to be associated to the ECM. Further analysis of endothelial extracellular matrix encoding genes previously described44 revealed that most of these genes were also significantly downregulated in cKO ECs (Fig.5e). The expression of these genes in WT ECs at single-cell level (Fig.5f) was confirmed post-sort at population-level (Fig.5g) with most genes being highly expressed in ECs only. One of them was Sparc (Fig.5e blue arrow, Fig.5g), a central ECM secreted Ca2+-binding glycoprotein that interacts with many other ECM proteins including Col1 and Col445,46. Among the SPARC family, Sparcl1 (Sparc-like 1), known to bind to Col147, was also found to be significantly downregulated in cKO ECs (Fig.5b, c). Together, these analyses show that Runx1 deficiency in NG2+cells leads to significant transcriptomic changes in endothelial cells including extracellular matrix related genes. We did not detect transcriptional changes in the NG2-Cre;Runx1fl/fl cKO HEC/EHT cell cluster, although this observation is inconclusive due to the low number of cells captured.

Transcriptomic changes in vascular and perivascular cells may have also affected IAHCs. As hematopoietic cells are highly heterogeneous and progenitors were significantly affected (Fig.1), we first explored WT IAHCs in more detail. Previous studies showed that IAHCs are composed of both Runx1+ and Runx1- cells28,48,49 and we were able to confirm this by flow cytometry in Runx1-IRES-GFP AGMs (Fig.S5a). We also confirmed the expression of Runx1 in HEC/EHT and its absence in ECs by flow cytometry in Runx1-IRES-GFP E11 AGMs (Fig.S5a), in line with published work50. To validate their cell identity, we next purified and sequenced 243 Runx1 (GFP)+ and 27 Runx1 (GFP)- IAHCs (NG2-PDGFR- CD31+ckit+) as well as 5822 EC (Runx1-) and 248 HEC/EHT (Runx1+) cells from NG2-PDGFR- ckit- CD45- CD31+ E11 Runx1-IRES-GFP AGMs (Fig.S5a) and performed bulk RNA sequencing (RNA-seq). The purity of the sort was first confirmed (Fig.S5b). While CD45 antibody was not used to isolate IAHCs (Fig.S5a), our bulk RNA-seq data (Fig.S5b) show that not all IAHC cells express Ptprc (CD45) in line with previous studies48,49,51, and seems to be present only when Runx1 is expressed. Next, the identity of all sorted cell populations based on the expression of genes known to be expressed in these cells15,35,48 was confirmed (Fig.S5c). Interestingly, the transcriptomic profile of Runx1 (GFP)+ and Runx1(GFP)- sorted IAHCs appears to be distinct. While CD34, Gata2, Lmo2, Etv6, and Eglf7 are expressed in both Runx1(GFP)+ and Runx1(GFP)- IAHCs at various levels, Adgrg1, Gfi1, Myb and CD44 are mainly found in Runx1(GFP)+ IAHCs (Fig.S5c). Instead, as they also express Tek, Kdr, Eng, Esam and Gata2 (Fig.S5c, d), Runx1(GFP)- IAHCs are at the transcription level, closer to type-1 pre-HSCs52,53 or to recently described CD31+ckithighGata2medium IAHCs that are Runx1-Ptprc-48 with possible (micro)-niche role54. Our analyses confirm the heterogeneity of Runx1(GFP)+/-CD31+C-KIT+IAHCs in the E11 AGM at both protein and transcriptomic levels, and indicate that most IAHC cells captured in our full/unsorted AGM scRNA-seq are Runx1-.

To explore transcriptomic changes between WT and cKO IAHCs, differential expression analysis followed by overrepresentation analysis on genes significantly downregulated in cKO IAHCs was carried out (Fig.6a). Several GO biological processes were significantly overrepresented in these downregulated genes, including ribosome assembly processes, regulation of translation, RNA transport and localisation, and others such as response to DNA damage, gene expression and cellular processes (Fig.6a). In line with this, we found that the top 25 significantly downregulated genes in cKO IAHCs were mostly ribosomal protein coding genes from both Rps and Rpl families. Other genes in the top 25 are known to be required for transcriptional or translational initiation such as Btf3, Pabpc1 and Bclaf1 (Fig.6b). Interestingly, one of the top significantly downregulated genes in the cKO was Sox18 (Fig.6b, arrow), previously reported to be expressed in both IAHCs and ECs in the mouse AGM55 and confirmed here by our WT scRNA-seq data (Fig.2d). Furthermore, Sox18 has been transiently detected during early hematopoiesis in a model of embryonic stem cell differentiation in vitro, controlling early HP proliferation and maturation56. In line with this, further GO analysis revealed that Sox18 is associated with cellular processes including cell maturation, cell differentiation and regulation of stem cell proliferation (Fig.6b). The latter two GO terms are also associated with other genes significantly downregulated in cKO IAHCs such as Hmgb2, encoding a chromatin-associated non-histone protein involved in transcription and chromatin remodelling (Fig.6b). This transcriptomic analysis shows that the deletion of Runx1 in NG2+ PC/vSMCs within the AGM niche significantly alters the genetic programme of IAHCs.

a Barplot of fold enrichment for selected GO biological processes significantly overrepresented in genes significantly downregulated in cKO HSPCs compared to WT HSPCs. b Scatter plot of AUC (representing strength of downregulation) vs log10(FDR), showing the top 25 significantly downregulated genes (red circles) in cKO HSPCs. Scatter plots of AUC vs log10(FDR) highlighting downregulated genes associated with Gene Ontology (GO) biological processes. Red dots found above the dashed line (corresponding to FDR=0.05) represent significantly downregulated genes (FDR<0.05).

Despite the decrease in HPs and HSCs in cKO AGM, NG2-Cre;Runx1fl/fl mice are born with no obvious defects and develop into adulthood. Because of this, we sought to explore the effect of Runx1 deletion in NG2+ PC/vSMC on adult HSPCs. The presence of these progenitors in the adult bone marrow (BM) of mutant mice was analyzed by flow cytometry and compared to WT mice. No significant differences were found in either Lin-Sca1+cKit+ (LSK) (Fig.7a, b) nor LSK CD150+CD48-(SLAM) cell frequencies (Fig.7c, d) between cKO mice and WT controls. We performed HP assays and found that the frequencies of hematopoietic cell colonies were similar in all mutants and WT littermates (Fig.7e, TableS8). To assess the capacity of these cells to reconstitute hematopoiesis in vivo, 5105 bone marrow cells harvested from all genotypes were transplanted into sub-lethally irradiated WT mice recipients. Compared to the control group in which 62.1% (18 out of 29) mice were reconstituted, mice injected with NG2-Cre;Runx1fl/+ or NG2-Cre;Runx1fl/fl BM cells showed a significant reduction in the long-term reconstitution potential, with only 27.3% (3 out of 11, p=0.024) and 20% (4 out of 20, p=0.002) of transplanted mice being reconstituted respectively (Fig.7f, TableS3). In addition, the percentage of donor chimerism was significantly reduced in the cKO group. On average, the donor chimerism with WT cells was 33% compared to the 16% and 9% observed when BM cells from NG2-Cre;Runx1fl/+heterozygous and NG2-Cre;Runx1fl/fl cKO (p=0.002) were injected respectively (Fig.7f, TableS4). The remaining HSCs in the mutant NG2-Cre;Runx1fl/+ and NG2-Cre;Runx1fl/fl adult BM are multilineage, showing similar contributions of donor cells to myeloid or lymphoid cell compartments (Fig.7g), and self-renew (Fig.7h). Interestingly, no NG2+Runx1(GFP)+ cells were detected in adult Runx1-IRES-GFP BM hematopoietic niches (Fig.7i), suggesting that they are exclusive to the embryo and that the BM hematopoietic defect found in adults is developmentally driven.

a, bRepresentative plots and percentages of Lin-Sca1+cKit+ (LSK) and c, dLSK CD150+CD48-(SLAM) bone marrow (BM) cells by flow cytometry of WT/ NG2+/+;Runx1fl/+,NG2+/+;Runx1fl/fl (n=9), HET NG2-Cre;Runx1fl/+ (n=4) and cKO NG2-Cre;Runx1fl/fl (n=4) adult mice is shown. e Colony-forming unit-culture (CFU-C) numbers per 104 adult BM cells; n=WT/HET/cKO: 13/7/8 mice. N=7 independent experiments. Data are meanSEM (TableS8). f Hematopoietic stem cell repopulating potential and donor chimerism of WT and mutant BM cells in vivo. 5105 BM donor WT, HET and cKO cells were injected into 29, 11 and 20 Ly5.1 HET recipients, respectively, with 18, 3 and 4 found to be reconstituted respectively (Table S3, p=0.024 (WT/HET) and p=0.002 (WT/cKO) by Z score test for 2 population proportions). Mice are reconstituted when 5% donor cells are found in the host peripheral blood; p=0.002 (WT/cKO) by Kruskal-Wallis and Dunns post-hoc test (TableS4). g Histograms showing the contribution of CD45.2+CD45.1- donor cells to myeloid cells (CD11b+Gr1+/-), B cells (CD19+) and T cells (CD4/8+) in all reconstituted host mice from (f). (n=WT/HET/cKO=18/3/4), p=0.019 (WT/HET) for B cells by one-way ANOVA and Tukeys post-hoc test. h BM cells from selected reconstituted primary recipients (found in f) were transplanted into multiple irradiated secondary recipients. Mice are reconstituted when 5% donor cells are found in the host peripheral blood (TableS34). i Representative flow cytometric analysis plot of NG2 in Runx1-IRES-GFP adult BM (n=6). All data are presented as Mean values+/-SEM. N=number of independent experiments; n = number of biological samples. Source data for b, d, e, f, g and h are provided as a Source Data file.

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Runx1+ vascular smooth muscle cells are essential for hematopoietic stem and progenitor cell development in vivo - Nature.com

Alabama’s biggest hospital to suspend transfer of embryos after court ruling – ABC News

By Embryonic Stem Cells

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Alabama's biggest hospital to suspend transfer of embryos after court ruling - ABC News

A human embryo model mimics early development and blood-cell formation – Nature.com

By Induced Pluripotent Stem Cells

Human embryos are extremely difficult to study. This lack of samples limits our understanding of crucial developmental stages, such as the early formation of blood cells. A stem-cell-based model closely captures the development of human embryonic and key extra-embryonic tissues after implantation, as well as the formation of early blood cells.

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A human embryo model mimics early development and blood-cell formation - Nature.com

Stem cell therapy for MS seen to lower mitochondrial DNA in study – Multiple Sclerosis News Today

By Stem Cell Treatment

People with multiple sclerosis (MS) have higher amounts of mitochondrial DNA in their spinal fluid, which surrounds the brain and spinal cord, than do their healthy counterparts, a small study found.

Mitochondria are small cellular organelles that produce most of the energy needed to power cells. These cell powerhouses have their own DNA, which can be released into the surrounding fluid and contribute to inflammatory processes.

In this study, however, researchers also observed that treatment with stem cell therapy brought mitochondrial DNA to near-normal levels, suggesting it could be a marker of disease activity and response to treatment for MS.

The study, Cerebrospinal fluid mtDNA concentrations are increased in multiple sclerosis and were normalized after intervention with autologous hematopoietic stem cell transplantation, was published in Multiple Sclerosis and Related Disorders.

MS occurs when healthy parts of the brain and spinal cord become inflamed and damaged, causing a range of symptoms. It is thought that certain immune cells in MS may go haywire and burst open, releasing DNA from their mitochondria that boosts further inflammatory processes.

Earlier work has suggested that changes in mitochondria occur early in the disease course and contribute to neurodegeneration. However, treatment with certain disease-modifying therapies seems to reduce the amount of mitochondrial DNA known as mtDNA that gets released into the cerebrospinal fluid, or CSF.

Now, researchers in Sweden conducted a study involving MS patients and healthy people. There were two main goals: First, to determine if MS patients indeed have higher levels of mitochondrial DNA in the CSF than do healthy controls, and second, to investigate if treatment with a stem cell transplant could lower the levels of that DNA in patients. Such a transplant, known as autologous hematopoietic stem cell transplantation (aHSCT), uses cells collected from the patient.

The study included 48 people with relapsing-remitting MS and 32 healthy individuals. The results showed that the MS patients had significantly more copies of mtDNA than did the healthy individuals (a median of 16 vs. 5.6 copies per microliter of CSF).

The amount of mtDNA was not impacted by sex or age in either group, but correlated with the number of relapses, disability levels, and a shorter disease duration in patients. Levels of mtDNA also were linked with higher the levels of neurofilament light chain (NfL), a marker of nerve cell damage, and a higher number of lesions with active inflammation.

All patients planned to undergo a stem cell transplant, a procedure that aims to reset the immune system. It involves collecting a patients own hematopoietic stem cells immature cells that can develop into all types of blood cells then wiping out the entire immune system with a round of chemotherapy or radiation therapy, and infusing the stem cells back to give rise to new immune cells.

By generating immune cells that are not primed to attack the brain and spinal cord, the procedure is expected to reduce the inflammation and nerve cell death that drives MS.

One year after the transplant, the results showed, the median number of mtDNA copies decreased significantly, from 16 to 5.9 copies per microliter. That number remained significantly reduced in the years that followed, at 8 copies per microliter after two years, and 7.2 copies per microliter after 3-5 years.

mtDNA concentrations were normalized in MS patients after intervention with aHSCT, the researchers wrote.

After the transplant, a total of 39 patients retained a status called no evidence of disease activity (NEDA-2), meaning they experienced no new MRI activity and no relapses over the follow-up period. The other nine patients had evidence of inflammatory disease activity (EIDA), and had experienced at least one of these events.

Data showed that patients with EIDA had significantly higher levels of mtDNA one year after the transplant that those with NEDA-2 (10 vs. 5.2 copies per microliter). The difference remained significant after two years (18 vs. 7.1 copies per microliter), but not after 3-5 years.

These results position mtDNA as a potential biomarker for monitoring inflammatory activity and response to treatment in MS, the researchers wrote. In addition, our study adds to the growing evidence base for the therapeutic efficacy of aHSCT.

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Stem cell therapy for MS seen to lower mitochondrial DNA in study - Multiple Sclerosis News Today

Stroke/Cerebral Palsy: Innovative U.S. Stem Cell Clinics for Stroke and Cerebral Palsy Recovery – Medical Tourism Magazine

By Stem Cell Clinic

In the landscape of modern medicine, stem cell therapy emerges as a beacon of hope for individuals grappling with the aftermath of stroke and cerebral palsy. The United States, renowned for its pioneering role in medical innovation, is home to an array of stem cell clinics that specialize in cutting-edge treatments for these neurological conditions. This article delves into the revolutionary approaches these clinics are adopting to facilitate recovery and rehabilitation, offering an insightful guide for healthcare professionals and patients alike.

Stem cell therapy, a cornerstone of regenerative medicine, harnesses the body's innate healing mechanisms to repair damaged tissues and restore lost functions. This therapy's potential to revolutionize the treatment of stroke and cerebral palsy lies in its ability to differentiate into various cell types, offering unprecedented opportunities for neurological repair and recovery.

For stroke survivors, the aftermath can be a challenging journey marked by physical, cognitive, and emotional hurdles. Traditional rehabilitation methods, while beneficial, have their limitations. Enter stem cell therapy, which targets the root cause of damage, promoting the regeneration of neurons and the restoration of neurological functions. This approach not only enhances physical recovery but also improves quality of life, reducing the long-term impact of stroke.

Cerebral palsy, a condition often resulting from brain damage before or at birth, has seen significant advancements in treatment through stem cell therapy. By focusing on repairing the brain's affected areas, stem cell treatments offer a ray of hope for improved motor functions, reduced spasticity, and better overall development. These therapies, tailored to the individual's specific needs, are charting a new course for cerebral palsy management.

The U.S. is at the forefront of integrating stem cell therapy into clinical practice, with numerous clinics offering specialized treatments for stroke and cerebral palsy. These facilities are distinguished by their commitment to research, state-of-the-art technology, and personalized care plans. Patients from around the globe seek treatment in the U.S., drawn by the promise of innovative therapies that are not yet widely available elsewhere.

These clinics operate under stringent regulatory standards, ensuring that treatments are both safe and effective. The collaborative efforts of scientists, clinicians, and patients have led to the development of protocols that optimize recovery outcomes. Furthermore, the U.S. is home to a vibrant research community that continually seeks to refine and enhance stem cell therapies, promising even greater advancements in the future.

Choosing to pursue stem cell therapy for stroke or cerebral palsy involves careful consideration of several factors, including the type of stem cells used, the method of delivery, and the clinic's expertise. Patients and their families are encouraged to engage in thorough discussions with healthcare providers, exploring the potential benefits and limitations of treatment.

Success stories abound, with many patients experiencing significant improvements in mobility, function, and independence. These testimonials serve as powerful motivators for those contemplating stem cell therapy, offering a glimpse into the potential for transformative recovery.

The landscape of stroke and cerebral palsy treatment is evolving rapidly, thanks in large part to the advancements in stem cell therapy. As research continues to unlock new insights into regenerative medicine, the potential for recovery and rehabilitation expands. The U.S., with its innovative stem cell clinics, remains at the forefront of this medical revolution, offering hope and healing to those affected by these challenging conditions.

In conclusion, stem cell therapy represents a groundbreaking approach to the treatment of stroke and cerebral palsy. The U.S. is leading the way in making these innovative therapies accessible, providing new avenues for recovery and improving the lives of those impacted by these neurological conditions. As we look to the future, the promise of stem cell therapy continues to inspire, heralding a new era of medical possibilities.

Given his unparalleled expertise and success in treating elite athletes and high-profile individuals, we highly recommend Dr. Chad Prodromos for anyone seeking top-tier stem cell treatment. His work at the Prodromos Stem Cell Institute is at the forefront of regenerative medicine, offering innovative solutions for a range of conditions. To explore how Dr. Prodromos can assist in your health journey, consider reaching out through his clinic's website for more detailed information and to schedule a consultation. visit Prodromos Stem Cell Institute.

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Stroke/Cerebral Palsy: Innovative U.S. Stem Cell Clinics for Stroke and Cerebral Palsy Recovery - Medical Tourism Magazine

Targeting PRMT9-mediated arginine methylation suppresses cancer stem cell maintenance and elicits cGAS-mediated … – Nature.com

By Stem Cell Treatment

Ethics statement

This study follows ethical regulations. Experiments using patient specimens were approved in part by the institutional review boards of City of Hope Comprehensive Cancer Center (COHCCC) and conducted in accordance with the Declaration of Helsinki (2013). Samples were acquired as part of the COHCCC institutional review board-approved clinical protocol no. 18067. All mouse experiments were completed in accordance with the Guidelines for the Care and Use of Laboratory Animals and were approved by the Institutional Animal Care and Use Committee (IACUC) at COHCCC. Experiments were performed in accordance with a protocol approved by the COHCCC ICUC (no. 15046). The maximum tumor size (humane endpoint) permitted by IACUC is 15mm (diameter). All animals were euthanized before tumor size reached 15mm in diameter. Maximum tumor size did not exceed 15mm.

De-identified, clinically annotated primary patient samples including those derived from peripheral blood or bone marrow were obtained from patients with AML at COHCCC. The annotations are shown in Supplementary Table 1. Normal cells derived from peripheral blood were obtained from the COHCCC. Informed written consent was completed and acquired from all involved participants before sample acquisition. MNC separation, CD34+ cell enrichment or CD3+ T cell depletion was performed as described previously58.

Molm13 (catalog no. ACC 554, DSMZ), MV4-11 (catalog no. CRL-9591, ATCC), THP1 (catalog no. TIB-202, ATCC), NB4 (catalog no. ACC 207, DSMZ), U937 (catalog no. CRL-1593.2, ATCC), HL-60 (catalog no. CCL-240, ATCC), MA9.6ITD and RAJI (catalog no. ACC 319, DSMZ), UPN1 (catalog no. CVCL_A795, Cellosaurus), BL41 (catalog no. ACC 160, DSMZ), Rec1 (catalog no. ACC 584, DSMZ), OCI-Ly3 (catalog no. ACC 761, DSMZ) and A20 (a gift from Y. Fu) were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium with 10% FCS as described previously58,59. All other cell lines, including 293FT (catalog no. R70007, Thermo Fisher Scientific), DMS273 (a gift from R. Salgia), DMS114 (a gift from R. Salgia), SW1573 (a gift from E. Wang), A549 (a gift from E. Wang), SW620 (catalog no. CCL-227, ATCC), HCT116 (catalog no. CCL-247, ATCC), HepG2 (catalog no. HB-8065, ATCC), PC3 (a gift from S. Priceman), DU145 (a gift from S. Priceman), MDA-MB-231 (catalog no. CRM-HTB-26, ATCC), HT1197 (catalog no. CRL-1473, ATCC), A172 (catalog no. CRL-1620, ATCC), MIAPACA2 (catalog no. CRM-CRL-1420, ATCC) and HT1080 (catalog no. CCL-121, ATCC) were cultured in DMEM with 10% FCS. MA9.6ITD cells (MLL-AF9 plus FLT3-ITD) were established by J. Mulloy60. The human primary normal and AML CD34+ cells used for transduction were maintained as described previously59. Specifically, as noted in that paper, the medium was StemSpan SFEM (STEMCELL Technologies) supplemented with 50ngml1 recombinant human stem cell factor (SCF), 100ngml1 Flt3 ligand (Flt3L), 100ngml1 thrombopoietin, 25ngml1 interleukin-3 (IL-3) and 10ngml1 IL-6 (PeproTech). Mouse AML cells were cultured in RPMI 1640 medium with cytokines (mouse IL-3, 10ngml1; mouse IL-6, 10ngml1; mouse SCF, 30ngml1; Supplementary Table 10) as described previously59.

In all experiments, male and female, 610-week-old, WT C57BL/6J (strain no. 000664, The Jackson Laboratory), B6(Cg)-Rag2tm1.1Cgn/J (strain no. 008449, Rag2/, The Jackson Laboratory), B6(Cg)-Ifnar1tm1.2Ees/J (strain no. 028288, Ifnar1/, The Jackson Laboratory), Kmt2atm2(MLLT3)Thr/KsyJ (strain no. 009079, MLL-AF9 knock-in, The Jackson Laboratory), B6.129S(C)-Batf3tm1Kmm/J (strain no. 013755, Batf3/, The Jackson Laboratory), NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (strain no. 005557, NSG, The Jackson Laboratory), NOD.Cg-Prkdcscid Il2rgtm1Wjl Tg(CMV-IL3,CSF2,KITLG)1Eav/MloySzJ (strain no. 013062, NSGS, The Jackson Laboratory) and NOD.Cg-Prkdcscid H2-K1b-tm1Bpe H2-Ab1em1Mvw H2-D1tm1Bpe Il2rgtm1Wjl/SzJ (strain no. 025216, NSG-MHC I/II DKO, The Jackson Laboratory) mice were used. B6-Ly5.1 (CD45.1, NCI 564) and BALB/c (NCI 028) mice were available from an outside vendor. Male and female mice were housed at the COH Animal Resource Center. All care and experimental procedures followed established institutional guidelines. The mouse room is conditioned with a 14h light10h dark cycle, temperatures of 6575F and 4060% humidity. The procedure was run in accordance with a protocol approved by the IACUC at COHCCC.

Mouse experiments were performed once: Fig. 2d,e,h (male and female; five WT B6 mice per group); in Fig. 2f,g (male and female; five WT B6 mice per group); Fig. 2q (male and female; eight NSGS mice per group); Fig. 2r (male and female; eight NSGS mice for Ctrl, seven NSGS mice for Prmt9 KD); Extended Data Fig. 2p (male and female; six Prmt9loxP/loxP/Mx1Cre mice for Prmt9 WT, nine Prmt9loxP/loxP/Mx1Cre+mice for Prmt9 KD); Extended Data Fig. 2q (male and female; eight Prmt9loxP/loxP/Mx1Cre mice for Prmt9 WT, 15 mice (Prmt9loxP/loxP/Mx1Cre+) for Prmt9 KD); Extended Data Fig. 2r (male and female; seven B6-Ly5.1 mice per group); Fig. 5d (male and female; seven WT B6 mice per group); Fig. 5e (male and female; five Rag2/ mice per group); Fig. 5f(male and female; five NSGS mice per group); Fig. 5g (male and female; seven WT B6 mice per group); Fig. 5s (male and female; five WT B6 mice for naive mice, four survival mice from Fig. 5d for survivors); Fig. 5v (male and female; five Ifnar1/ mice for Ifnar1 KO, six WT B6 mice for Ifnar1 WT); Fig. 6j (male and female; seven WT B6 mice for the Prmt9 KD group, five WT B6 mice for each of the other three groups); Fig. 6m (male and female; seven WT B6 mice for cGAS KO+cGASN group, five WT B6 mice for each of the other two groups); Fig. 6s (seven WT B6 mice for each Batf3 WT group, five Batf3/ mice for the Batf3 KO group); Extended Data Fig. 7c (seven WT B6 mice for the Ctrl and Prmt9 KD groups, five WT B6 mice for the T and NK cell depletion groups); Extended Data Fig. 9gi (five BALB/c mice per group); and Extended Data Fig. 9j,k (five NSGS mice per group). scRNA-seq and bulk RNA-seq were performed once per sample and are shown in Figs. 1e, 5h and 6c. If not otherwise specified, in vitro experiments were repeated at least three times.

The CD530-EF1A-IRES-GFP vectors were purchased from System Biosciences. The CD530-EF1A-T2A-GFP vectors were modified from CD530-EF1A-IRES-GFP, replacing IRES with T2A sequences. Full-length WT or LDIG-to-AAAA mutant PRMT9 (ref. 29) were cloned into CD530-EF1A-IRES-GFP vectors. FLAG-tagged XRN2 and FLAG-tagged DDX3X variants, and FLAG-tagged either full-length WT or C-terminal (amino acids 436636) PABPC1 or R493K, R481K, R506K or 3RK mutants were cloned into the CD530-EF1A-T2A-GFP vector. All plasmids were synthesized by Genscript. shRNAs targeting human PRMT9, mouse Prmt9, PABPC1 and CREB1 were purchased from Sigma-Aldrich (MISSION shRNA) and cloned into pLKO-SFFV-RFP, as described elsewhere58. cGAS WT and the activation mutant N were purchased from Addgene and constructed into a DOX-inducible expression vector. SMARTvectors with shPRMT9 were purchased from Dharmacon (Horizon Discovery). The oligonucleotides used are listed in Supplementary Table 11.

Compounds were sourced from the NCI Developmental Therapeutics Program (DTP), ZINC libraries or MolPort. The PEGylated liposome packaging of LD2 used for animal treatment was prepared using the thin film hydration method. Lipids (distearoylphosphatidylcholine, cholesterol and DSPE-PEG(2000) at a ratio of 3:1:0.2) plus compound were dissolved in chloroform; then, organic solvent was separated in a vacuum to form a thin film. Subsequently, lipids were hydrated in PBS, pH 7.4, at 60C to form liposomes.

Virus production was as described previously61. HEK 293T cells were transfected with pMD2.G and psPAX2 packaging vectors plus lentivectors designed to overexpress or knock down genes using the calcium phosphate method as described previously61. Supernatants containing virus particles were filtered and concentrated. Viral infection was performed as described previously61.

RNA was prepared according to the TRIzol reagent protocol. After generation of complementary DNA, qPCR with reverse transcription was performed as described previously59. The primers used are listed in Supplementary Table 11.

Cell lysates were prepared in a buffer containing 50mM Tris, pH 7.4, 150mM NaCl and 1mM EDTA supplemented with protease inhibitors. Cell lysates were incubated with anti-FLAG beads or interested primary antibody (Sigma-Aldrich) overnight and denatured for immunoblotting. Proteins of interest were probed with primary and secondary antibodies. Signals were detected using the SuperSignal West Pico or Femato kits. All immunoblots were imaged using the G:BOX Chemi XX6 gel doc system and quantified with the ImageJ software (NIH).

Samples were prepared according to the protocol of the SimpleChIP Plus Enzymatic Chromatin IP Kit (catalog no. 9005, Cell Signaling Technology). Immunoprecipitates were exposed to anti-CREB1 (catalog no. SC-240, Santa Cruz Biotechnology) and anti-H3K27Ac antibodies, plus Protein G magnetic beads. After reversing, DNA was enriched; this was followed by qPCR.

Cells derived from the bone marrow or spleen samples were washed with PBS containing 1% FCS and then passed through a single-cell strainer and subjected to lysis of red cells. Before flow cytometry, cells were stained with the indicated antibodies in the same buffer. Flow cytometry analysis was performed. Data analysis was performed using FlowJo v.10. Molm13 cell engraftment in mice was determined using an anti-human CD45 antibody. CD45.2+ donor cells from transplants were determined using anti-mouse CD45.1 and CD45.2 antibodies. Mouse HSPCs were determined by staining with anti-mouse lineage antibody, including cKit, Sca-1, CD16 and CD32, and CD34 antibodies and a lineage antibody cocktail, including anti-mouse CD3, CD4, CD8, CD11b, CD11c, CD19, CD41, Ter119, B220, IgM, NK1.1, Gr-1 and interleukin-7 receptor subunit alpha (IL-7R). Anti-mouse Mac1, Gr-1, B220 and Ter119 were used to define mouse bone marrow differentiation. We also detected antigen-specific T cells in tumors as described previously44. For intracellular staining, fixed cells were incubated once with antibodies against IFN- (clone XMG1.2) and granzyme B (clone QA16A02). To define the human primary samples, we used the following markers: T cells (CD3+), B cells (CD19+/CD20+), monocytes (CD14+) and DCs (HLA-DR+CD34CD33CD3CD19CD20CD14CD56), as well as the immature CD33+CD34+CD45dim subset. CD69 and IFN- staining was used to determine T cell status. For the cell cycle studies, fixed cells were stained with 4,6-diamidino-2-phenylindole (DAPI).

Bone marrow cells (0.5106per transplant) from CD45.2+ Prmt9loxP/loxPMxCre+ or Prmt9loxP/loxPMxCre mice were combined with CD45.1+ bone marrow cells (at 1:1 ratio) and then implanted into lethally irradiated (900cGy) B6-Ly5.1 mice by intravenous injection. Peripheral blood samples were collected and assessed with CD45.1 and CD45.2 antibodies. Mouse recipients were induced with pIpC (InvivoGen) intraperitoneally 15mgkg1 every other day for 7 days; CD45.2+ chimerism in peripheral blood was assessed every 4 weeks.

For the limiting dilution assays, to evaluate LSC frequencies, AML cells were suspended in Colony Forming Cell growth medium with DOX to induce Prmt9 KD and plated in multi-well plates. To evaluate the frequency of leukemia-initiating cells in vivo, bone marrow cells isolated from Ctrl or Prmt9 KDMA9 AML mice were injected intravenously into sublethally conditioned recipient mice, as described in Supplementary Table 7. The number of recipient mice with leukemia development was determined in each group. The frequency of LSCs and LICs was determined using the ELDA software.

To assess the effect of Prmt9 KO and KD in vivo, MA9 or CMM cells were transduced with lentiviral vectors harboring a luciferase reporter. Cells were used for intravenous inoculation into sublethally irradiated CD45.1 B6 mice or WT B6, Rag2/ or NSGS mice. As for bioluminescence imaging, mice were administered 150mgkg1 d-luciferin (GoldBio) within PBS, followed by analysis using Lago X. Bioluminescent signals were quantified using the Aura imaging software (Spectral Instruments Imaging). Total values were determined using the regions of interest and photonsscm2sr. To identify the immune subsets contributing to leukemia regression after Prmt9 KD, we performed antibody-based depletion with an initial dose of combined anti-CD4 and anti-CD8 treatment or anti-NK1.1 treatment administered 1 day before in vivo DOX administration to Prmt9 KD mice. Antibodies (400g) were injected intraperitoneally twice the first week, and then at 200g twice weekly to maintain NK or T cell depletion. To assess DC function in Prmt9 KD outcomes, we implanted Batf3 WT or Batf3 KO mice with AML cells for further evaluation.

Cell growth was assessed using the CellTiter-Glo Assay Kit (Promega Corporation). Apoptosis was determined using annexin V or DAPI. Colony formation capacity was determined as described previously58,59.

For SILAC, Molm13 cells were cultured in SILAC RPMI 1640 medium (catalog no. 88365, Thermo Fisher Scientific) with 10% FCS (catalog no. A3382001, Thermo Fisher Scientific) and either light l-lysine (catalog no. 89987, Thermo Fisher Scientific) and l-arginine (catalog no. 89989, Thermo Fisher Scientific) for control cells, or heavy lysine (catalog no. 88209, Thermo Fisher Scientific) and l-arginine (catalog no.89990, Thermo Fisher Scientific) for inducible PRMT9 KD cells, for at least ten passages to ensure full incorporation of light or heavy l-lysine and l-arginine.

After 3 days of DOX induction in both control and PRMT9 KD cells, light-labeled and heavy-labeled cells were combined at 1:1 ratio. Cells were washed and centrifuged at 300g for 5min. Cell pellets were lysed in 9M urea with protease and phosphatase inhibitors in HEPES (pH 8.0) buffer. Samples underwent four cycles of sonication for 30s each using a microtip sonicator (VibraCell VCX130, Sonics & Materials) operating at 50% amplitude. Lysates were centrifuged at 20,000g for 15min; protein quantification was performed by using a bicinchoninic acid (BCA) assay. An equal amount of extracted protein from heavy and light SILAC culture was mixed for further digestion. The sample was first reduced by incubation with dithiothreitol (DTT) (5mM, 55C) and then alkylated by incubation with iodoacetamide (10mM) in the dark. The sample was diluted fourfold before sequential digestion first with LysC (2h) and then overnight with Trypsin Gold. Digestion was quenched using trifluoroacetic acid and the sample was desalted using 0.7ml of a Sep-Pak Classic C18 column (Waters). Eluted peptides were speedvacd to dryness and reconstituted in 1.4ml immunoaffinity purification buffer followed by peptide quantification using a BCA assay. We subjected 5% of peptides to global quantitative proteomics analysis and 95% of the rest to methyl-R peptide enrichment. This consisted of sequential incubation of peptides with anti-MMA antibody beads (catalog no. 12235, Cell Signaling Technology) and anti-SDMA antibody beads (catalog no. 13563, Cell Signaling Technology). Enriched peptides were reconstituted in 10l loading solvent (98% water, 2% acetonitrile, 0.1% formic acid); 1g of nonenriched peptides was used for global protein identification.

Data were obtained on an Orbitrap Fusion Lumos mass spectrometer (methylated peptides) or Orbitrap Eclipse with FAIMS Pro interface (unmodified peptides) coupled to a U3000 RSLCnano LC system with running binary solvent A (0.1% formic acid in water) and solvent B (0.1% formic acid in acetonitrile) at 300nlmin1. Methylated peptides (5l per injection) were directly loaded on a 25cm EasySpray C18 column and eluted over a 120-min gradient as follow: 80min with 219% B, 20min with 1930% B, 5min with 3098% B, followed by 2min of high organic wash and return to initial conditions in 1min. Unmodified peptides (1g peptides, 5l per injection) were directly loaded on a 50-cm EasySpray C18 column and eluted over 240min using the following gradient: 12min with 25% B, 158min with 519% B, 40min with 1930% B, 9min with 3090% B, followed by 4min of high organic wash and return to initial conditions in 2min. Using a duty cycle of 3s (Lumos) or 1s (Eclipse) per FAIMS CV (40/60/80), most abundant precursors were fragmented using higher-energy collisional dissociation (32% normalized collisional energy on Eclipse and 35% normalized collisional energy on Lumos) and measured in the ion trap. Dynamic exclusion was set to 60s to prevent resampling of previously analyzed precursors.

MS raw files were searched against the human UniProt protein database (downloaded in 2020, 42,373 entries) and a common contaminant database using MaxQuant v.1.6.17.0. The results were filtered to 1% protein and site false discovery rate (FDR). The resulting methyl peptide SILAC ratios obtained from the MaxQuant evidence.txt output file were normalized to their protein SILAC ratios before further analyses62.

Motif analysis was performed using the iceLogo web application as described previously30.

We performed polysome profiling as described previously28. Engineered Molm13 cells were DOX-induced for 3 days to delete PRMT9 expression and then treated for 5min with 100gml1 cycloheximide. After treatment, cells were collected and lysed. We prepared sucrose density gradients (1545% w/v) using a Gradient Master (BioComp Instruments). Then, the supernatant from the cell lysates was separated using centrifugation and fractionation. The collected RNA was further assessed in the qPCR analysis.

Protein synthesis was assessed by using the Click-iT Plus OPP Assay Kit (Thermo Fisher Scientific), with modifications. Briefly, treated cells were exposed to Click-iT OPP, then washed with PBS and fixed. After permeabilization for 15min, cells were reacted with cocktail, then analyzed using flow cytometry.

The assay was performed in a 30-l reaction with 50mM Tris HCl, pH 7.4, 50mM NaCl, 50mM KCl, 1mM MgCl2 and 1mM DTT buffer. Specifically, 1g purified PABPC1-CT protein or synthesized peptides, 1g purified PRMT9 protein and 5M of SAM (Cayman Chemical) were combined. Methylated proteins and peptides were detected with immunoblot or dot blot assays using anti-pan-SDMA, anti-pan-MMA, anti-pan-ADMA or our in-house PABPC1 R493me antibody. The R493me antibody was created by Genemed Synthesis. For the ex vivo tritium labeling of the methylation assay, 1g purified PRMT9 protein, 1g HA-tagged PABPC1 WT or corresponding PABPC1-R481K/R493K/R506K (3RK) protein, which were immunoprecipitated from 293T cells, and 1l S-adenosyl-l-[methyl-3H] methionine (78Cimmol1) was added to a 30l reaction mixture at 30C for 1h. Samples were separated and transferred to polyvinylidene membranes for further assessment.

The crystal structure of human PRMT9 (Protein Data Bank (PDB) ID 6PDM; 2.45A resolution) was used for virtual screening. Missing loops were added using a molecular operating environment loop modeler. A box size of 2521273 centered around the cocrystalized chemical probe was used for screening, which includes both the SAM pocket and catalytic pocket in the N-terminal methyltransferase domain (amino acids 150520). To rank the binding affinity, parallel AutoDock Vina63,64 runs were conducted on a local computer cluster. Seven hundred thousand compounds from the ZINC library were selected using the following criteria: molecular weight 350450, log P<3, total charge 2e to +2e and availability. In addition, we also screened the NCI library (NCI DTP 260,000 compounds). Each ligand was docked ten times and ranked according to the lowest binding energy score. After screening, we purchased the top 300 candidates (142 of them were available) from the NCI DTP and the top 100 candidates (70 of them were available) from the ZINC library to assess anti-AML activity. To estimate lead compound selectivity, we also performed Vina docking of LD2 into human CARM1 (PDB ID 5U4X), PRMT5 (PDB ID 4X61), PRMT7 (PDB ID 4M38) and PRMT9. To compare LD2 binding to PRMT5 versus PRMT9, we carried out two replicas of 100-ns molecular dynamics simulation of LD2 docked into each.

Maltose binding protein (MBP)-tagged PRMT9 core methyltransferase domain (150474) protein was expressed and purified by Genscript. Briefly, the PRMT9 core methyltransferase domain sequence was inserted into the pMAL-c5X vector between the Nde I and EcoR I sites. Tagged protein was expressed in BL21 and purified on an MBP column, followed by Superdex 200 and Q Sepharose columns. Proteins were sterile-filtered and lyophilized after extensive dialysis against the NMR buffer (50mM NaH2PO4, pH 7.5). Deuterium oxide-based sodium phosphate buffer was used with 5% DMSO-d5. For the STD NMR assay, the molar ratio of LD2 to PRMT9 was 60:1 in which the concentration of PRMT9 was 0.67M; 50M trimethylsilylpropanoic acid-d4 was used as the internal reference. The molar ratios between PMRT9 and LD2 were 1:20, 1:40 and 1:60, in addition to a control sample with free LD2. LD2 concentration in the CarrPurcellMeiboomGill (CPMG) experiments was 40M. The NMR saturation transfer difference (STD) experiments were carried out at 25C on a 700-MHz Bruker Ascend system equipped with a 5-mm triple resonance cryogenic probe as described previously65. The CPMG experiment was performed as described previously66. Data were analyzed using Bruker TopSpin v.3.6.

We also assessed whether LD2 binds to PRMT9 directly in vivo; to do so, a cellular thermal shift assay was performed as described previously39,40. We first engineered Molm13 cells to overexpress FLAG-tagged PRMT9 WT or PRMT9 mutant (W152A, D258A and E433A; all three residues are predicted drug and PRMT9 binding sites). Five million cells were pretreated with 2.5M LD2 overnight. DMSO was used as the control. Cells were aliquoted in each tube and heat-shocked using Thermal Cycler at the indicated temperatures. Cells were then lysed for the immunoblot assay. Experiments were performed using three biological replicates.

Two million MNCs from AML bone marrow specimens were cultured per well in 24-well plates in IMDM plus 20% FCS under physiological cytokine conditions as described previously41,42 (granulocyte-macrophage colony-stimulating factor in 200pgml1, granulocyte colony-stimulating factor in 1ngml1, SCF in 200pgml1, IL-6 in 1ngml1, macrophage inflammatory protein-1 alpha in 200pgml1 and leukemia inhibitory factor in 50pgml1). We then used the EasySep Dead Cell Removal Kit (STEMCELL Technologies) to ensure more than 95% living cells before culture. Cells were treated with vehicle (dimethylsulfoxide), 2.5M LD2, anti-PD-1 (pembrolizumab, 10gml1, SIM0010, Bio X Cell) or LD2 plus anti-PD-1 for 4 days at 37C. On day 4, cells were pretreated for 6h with brefeldin A and subjected to CyTOF immunostaining with customized surface or intracellular marker antibodies, according to Fluidigm CyTOF protocols (PN400279A4). An untreated peripheral blood mononuclear cell sample from a healthy donor served as a control for phenotyping. Samples were acquired on a Fluidigm Helios. Data were normalized and saved as FCS files before analysis using the Cytobank software (https://premium.cytobank.org/). After data were cleaned up, spanning-tree progression analysis for density-normalized events was used to cluster AML cells and immune cell subpopulations based on the median level of each.

For CD8A, CD8B, GZMA, GZMB and PRF1, the average expression levels of these genes were used to estimate CTL levels in AML samples43,67. We carried out in silico tests to calculate the ratio of PRMT9hi and PRMT9lo patients exhibiting high versus low CTL scores using both GSE144688, which includes 526 samples of patients with AML, and GSE12417, which includes 163 patient samples. For each patient, high versus low CTL scores were decided according to cutoff of 0.5 for the z-score. A Fishers exact test was used to assess significance.

Bone marrow cells in MA9-transplanted mice, and bone marrow and spleen cells in Ctrl and Prmt9 KD mice administered DOX in drinking water over 7 days, were collected for analysis. Single cells were resuspended in 0.4% BSA and loaded to generate an emulsion of single-cell gel beads. Approximately 5,00010,000 cells were loaded per channel. Libraries were prepared using the Single Cell 3 Library & Gel Bead, Single Cell 3 Chip and i7 Multiplex Kits, according to the Single Cell 3 Reagent Kits v2 User Guide (part no. CG00052 Rev A). Libraries were sequenced on an Illumina HiSeq 4000 system.

We used the Cell Ranger Single Cell Software Suite to perform single-cell 3 gene counting and aggregation of multiple samples to generate raw counts, cell barcodes and gene features. The R package Seurat was run as the platform to implement all data processing procedures68.

Cell quality control was executed as follows: the minimum detected genes (3) in each cell; the minimum number of cells (200) related to each gene; and the maximum fraction (0.2%) of counts from mitochondrial genes per cell barcode. The high-count depth threshold (2,000) was used to filter out potential doublets. Then, the count matrix was normalized to obtain the correct relative gene expression abundance between cells69. Then, the R package Harmony was applied to remove batch effects due to biological differences between cell types or states.

To retain informative genes with high variability, genes with small variations (below 2) among all cells were filtered out. Then, the dimensions of count matrices were reduced using dedicated dimension reduction algorithms, such as UMAP and t-distributed stochastic neighbor embedding (t-SNE). Two-dimensional visualization outputs were then generated using the leading reduced components in the UMAP and t-SNE plots.

UMAP-related processed data were regarded as the input of cell clustering. Neighborhood distances among all cells were determined to infer the identity of each cell. Then, clusters were acquired via specified distance metrics (Euclidean distance). Furthermore, for each cluster, the R package MAST was used to deduce significant DEGs. These DEGs were considered markers of a cluster and were used for annotation purposes. Annotations were conducted manually by comparing marker genes with the literature and arranging cell categories. In addition, automatic annotation of cell clusters was done using the R package SingleR, as described previously70. By combining both annotation styles, the final cell type labels of each cluster were acquired.

For the cell type clusters of interest, GSEA was performed based on preordered genes ranked using MAST-derived (log10(Padj)sign (log fold change)) with 1,000 permutations71. The gene sets of the Hallmark, Kyoto Encyclopedia of Genes and Genomes, chemical genetic perturbation and Gene Ontology-Biological Process categories of the Molecular Signatures Database were considered as the signatures. Finally, specific enriched genes within a cluster were visualized by averaging their expression among all cells in that cluster. Key enriched gene expression was rescaled by z-scores and visualized in the heatmap.

scRNA-seq uncovered ten distinct T cell clusters (c0c9). c0 cells expressed Cd4 and CD62L, but not the effector and memory T cell marker Cd44 or T cell activation genes. Thus, c0 was defined as naive CD4+ T cells. Similarly, c1 cells expressed Cd8a and CD62L but not Cd44 or other T cell activation markers and were defined as naive CD8+ T cells. c2 cells expressed Cd8a, Cd44 and Sell, and intermediate levels of Tbx21 (T-bet) and Eomes, and represented a memory CD8+ T cell population. c3 cells expressed high Cd4, Cd44 and Icos, Ctla4, Tnfrsf4 and Pdcd1, but did not express CD62L and were defined as activated and effector CD4+ T cells. c5 cells expressed Cd44 and showed the highest levels of Ifng, Gzmb, Icos, Tim-3, Il2ra, Tnfrsf18 and Lag3, considered as differentiated CTLs. c6 cells were defined as Treg cells because they express Cd4, Il2ra (Cd25) and Foxp3. c4, c7, c8 and c9 cells contained both CD4+ and CD8+ T cells. c4 and c9 showed lower levels of activation markers, and lower CD62L and higher Cd44, suggesting that they represent Teff cell populations. c7 expressed only the naive T cell marker CD62L, indicating a naive population, while c8 expressed lower CD62L and higher Cd44, but did not express other T cell activation markers, suggesting it represents a memory T cell population.

Total RNA was prepared using the TRIzol reagent (Thermo Fisher Scientific). RNA quality (RNA integrity number) was assessed and sequenced on an Illumina HiSeq 2500 system. RNA-seq reads were aligned with default settings. Count data were normalized. Genes were defined as differentially expressed if the fold change was less than 1.5 or less than 0.67, with an FDR less than 0.05, and at least one sample showing reads per kilobase per million mapped reads greater than 1. We performed hierarchical clustering of DEGs using Cluster v.3.0 with Pearson correlation distance and average linkage, and visualized them with Java TreeView. Enrichment analysis on the pathways of Hallmark, Kyoto Encyclopedia of Genes and Genomes and chemical genetic perturbation was performed using GSEA.

cGAMP levels were detected as reported elsewhere72,73. THP1 cells were DOX-treated to induce PRMT9 KD for 2 days; serum-free Phenol Red RPMI (Thermo Fisher Scientific) medium was replaced for another 24h. Conditioned medium was collected and cGAMP levels were detected using the Enzyme Immunoassay Kit (Arbo Assays). To determine cGAMP levels in the bone marrow microenvironment of control and Prmt9 KD mice, bone marrow fluid was collected by centrifuging tibias and femurs at 8,000rpm for 15s; then, cGAMP levels were assessed.

WT (catalog no. thpd-nfis, InvivoGen), cGAS KO (catalog no. thpd-kocgas, InvivoGen) and MAVS KO (catalog no. thpd-komavs, InvivoGen) THP1-Dual cells were used for the reporter assay. The purchased THP1-Dual cells (InvivoGen) were derived from the human THP1 monocyte line harboring the Lucia gene. Reporter cells were further engineered with inducible PRMT9 shRNA or control shRNA. After DOX treatment to PRMT9 KD or LD2 to inhibit PRMT9 in these cells, Lucia luciferase activity was determined as described by the manufacturer (InvivoGen) by adding QUANTI-Luc reagents and read with a FilterMax F5 microplate reader (Molecular Devices).

Cells were spun onto glass coverslips, fixed and incubated with primary anti-dsDNA (AE-2), H2AX or S9.6 antibodies, then with secondary antibody. Slides were then mounted in 90% glycerol solution containing DAPI (Thermo Fisher Scientific) and examined under a ZEISS LSM 880 confocal microscope.

We used the OxiSelect Comet Assay Kit (Cell Biolabs). Briefly, after PRMT9 KD, THP1 cells were mixed with prewarmed (37C) Comet agarose at a 1:10 ratio (v/v), then loaded onto the top of the Comet agarose base layer. Slides were immersed for 60min in lysis buffer at 4C, which was washed with prechilled alkaline solution. After three washes with prechilled Tris/Borate/EDTA buffer, slides were subjected to electrophoresis at 1Vcm1 for 15min, and then rinsed twice with deionized water. Comets were examined under a widefield ZEISS Axio Observer 7 fluorescence microscope. Approximately 50 cells were determined using the OpenComet software in Image J and shown as olive tail moments74,75.

THP1 reporter cells were electroporated with ribonucleoprotein complexes consisting of Cas9 protein and sgRNAs in the Neon Transfection System; 20moll1 guide RNA (gRNA) (as listed in Supplementary Table 11) were mixed at a 1:1 ratio. KO efficiency was assessed using immunoblot analysis.

As described previously57, bone marrow cells were cultured with complete RPMI medium containing 20ngml1 granulocyte-macrophage colony-stimulating factor (PeproTech). Fresh medium was added on days 3 and 6. CD8+ T cells were isolated from the spleens of OT-1 transgenic mice. MA9-OVA cells were pretreated for 2 days with LD2 and then cocultured overnight with collected bone marrow-derived DCs. Supernatants were collected for IFN- assessment. Bone marrow-derived DCs were selected using a CD11c+ selection kit (STEMCELL Technologies) and cocultured for 48h with OT-1 CD8+ T cells. IFN- supernatants were assayed using a mouse IFN- Flex Set Cytometric Bead Array.

Once leukemia cells were engrafted, MA9 syngeneic transplant mice were treated for 3 weeks with vehicle control, LD2, single anti-PD-1 mAb (catalog no. BE0146, Bio X Cell, 10mgkg1 intraperitoneally every other day) or LD2 plus anti-PD-1 antibody. LD2 was administered at 10mgkg1 intravenously twice a day, based on the preliminary pharmacokinetic and pharmacodynamic results. Mice were assessed for overall survival or killed directly to assess MA9 cell engraftment in bone marrow and perform staining with survivin-specific pentamers to assess MA9-specific immunity as described elsewhere44. Briefly, the bone marrow of MA9 mice was stained with anti-CD8 together with survivin-specific pentamers. CMV-specific pentamers were the negative controls. The percentage of survivin or CMV pentamer-positive CD8 T cells was assessed using flow cytometry. Secondary transplantations were performed to evaluate LSC activity in each group by assessing MA9 cell engraftment in the bone marrow.

The model was established using MHC class I and II DKO NSG mice49. To do so, we implanted 2 million MNCs from AML specimens intrafemorally into an irradiated DKO NSG mouse. After transplantation, MHC-deficient mice showed long-term (approximately 12 weeks in peripheral blood) engraftment of T and CD33+ cells without developing acute graft-versus-host disease. A panel of human lineage and progenitor cell markers (CD45, CD33, CD34, CD14, CD19, CD20, CD3, CD56, HLA-DR) was used to define T cells, B cells, monocytes, DCs and immature CD33+CD34+CD45dim cells. Mice were divided into two groups and treated with vehicle or LD2. Three weeks later, the number and frequency of leukemic CD34+ cells and the number of CD8+ T cells expressing CD69 and IFN- were assessed.

A20 cells (3106) were subcutaneously implanted into syngeneic BALB/c mice. When tumor volume reached 100mm3, mice were randomized into treatment groups. Tumor-bearing mice were treated with isotype control (vehicle), anti-PD-1 mAb (10mgkg1 intraperitoneally every other day for 2 weeks), LD2 (100mgkg1 intratissue injection daily for 2 weeks) or a combination of LD2 with anti-PD-1. Tumor volume was monitored through the end of the study when a humane endpoint was reached. The maximum tumor size (humane endpoint) permitted by the IACUC is 15mm (diameter). All animals were euthanized before tumor size reached 15mm in diameter. The microenvironmental components of tumors were analyzed using immunohistochemistry (IHC) and intracellular staining followed by flow cytometry.

Fixed A20 tumors were embedded in paraffin. Four-micrometer-thick sections on slides were incubated for 1h at 60C, deparaffinized and then rehydrated before IHC staining. Slides were blocked with 3% H2O2. Slides were subjected to antigen retrieval for 15min at 120C in citrate buffer, treated with Tris-buffered saline and incubated for 1h with anti-mouse CD3 or anti-mouse CD8 antibody. After washing, slides were incubated with secondary antibody. Slides were developed and counterstained with Mayers hematoxylin solution. Slides were scanned using whole slide imaging and analyzed using the NDP.view2 software (Hamamatsu).

Portions of fresh A20 tumors were cut into small pieces, then dissociated with type IV collagenase, type IV DNase and type V hyaluronidase at 37C for 30min. Cell suspensions were passed through a 70-m strainer and centrifuged at 300g for 5min. Cells were stained for 30min using a Live-or-Dye Fixable Viability Stain Kit (catalog no. 32018, Biotium). Next, cells were stained with immune cell surface markers (mouse CD45-allophycocyanin, mouse CD3-allophycocyanin/cyanine 7, mouse CD4-Alexa Fluor 700 and mouse CD8-Brilliant Violet 605). After two washes, cells were fixed and permeabilized, then intracellularly stained with mouse IFN--phycoerythrin and granzyme B-fluorescein isothiocyanate antibodies in the permeabilization for the flow analysis. Results were analyzed with FlowJo v.10 (FlowJo LLC).

Studies involving independent cohorts of mice were typically performed once, with several exceptions stated in the figure legends. No specific statistical tests were applied to determine sample size; size was established according to our previous experience with the models used. Accordingly, we typically used experimental cohorts of 57 mice. The experiments were not randomized. Investigators were not blinded to allocation during the experiments and outcome assessments. Data collection and analysis by all investigators were not performed blinded to the conditions of the experiments. No data were excluded from the analyses.

In general, data from independent experiments are shown as the means.d. or s.e.m. Statistics were determined using an unpaired, two-tailed Students t-test, a two-way ANOVA, a one-way ANOVA and a two-sided Fishers exact test. Survival results were analyzed with a log-rank (MantelCox) test and expressed as KaplanMeier survival curves. Prism (GraphPad Software) was used for the statistics; the detailed methods are described in each individual figure legend.

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Targeting PRMT9-mediated arginine methylation suppresses cancer stem cell maintenance and elicits cGAS-mediated ... - Nature.com

MD Anderson acquires inducible switch technologies for cell therapy – MD Anderson Cancer Center

By Stem Cell Treatment

The University of TexasMD AndersonCancer Center today announced it has acquired certain assets from Bellicum Pharmaceuticals, Inc. related to the CaspaCIDeswitch platform and the GoCAR platform. The transaction also includes clinical-grade stocks of rimiducid, an agent used to trigger the switches.

As a result of this acquisition, MDAndersonmay incorporate these platforms into its own cell therapy programs. The institution also intends to make the technology widely available via non-exclusive licenses to other academic institutions and to biopharmaceutical companies.

MD Anderson plans to focus on using the CaspaCIDe technology as a safety feature of cell therapies in development. The safety switch incorporates an inducible enzyme known as caspase-9, which initiates the first step of the apoptosis programmed cell death pathway. The switch can be triggered by rimiducid, leading to rapid elimination of cells containing the CaspaCIDe switch. MDAndersons Therapeutics Discovery division also plans to continue the clinical development of rimiducid in order to seek future approval from the Food and Drug Administration.

We strive each day to advance new, innovative treatment options to improve the lives of our patients, and cell therapies hold tremendous promise as effective immunotherapies, said Philip Jones, Ph.D., vice president of Research Strategy, Transformation and Operations atMDAnderson. CaspaCIDe provides a critical safety mechanism which could be triggered as required to reduce side effects, and we look forward to its continued development at MDAnderson.

Including this safety switch in cell therapies may offer clinicians the ability to quickly limit potential treatment-related toxicities that may occur. Potential applications include cell therapies where cytokine release syndrome and neurotoxicities have been observed, cell therapies targeting novel antigens with on-target/off-tumor safety concerns, and next-generation cell therapy constructs with higher potency.

When designing novel cell therapies, we must always ensure patient safety remains a top priority. We have explored a variety of associated technologies, and case studies demonstrate that the CaspaCIDe technology is effective in rapidly eliminating the transduced cells, saidKaty Rezvani, M.D., Ph.D., professor ofStem Cell Transplantation and Cellular Therapy. We have incorporated CaspaCIDe into many of our own cell therapies under investigation, and we are excited about the prospect of broadening the potential applications of this technology in the future.

Under a previous licensing agreement, MD Anderson has incorporated CaspaCIDe into multiple cellular therapy programs, including certain chimeric antigen receptor (CAR) natural killer (NK) cell therapies and plans for certain CAR T cell therapies. The current acquisition includes the previous licenses by MD Anderson and eliminates certain downstream financial obligations required under those licenses.

The asset acquisition also includes the transfer of certain intellectual property related to Bellicums GoCAR-T and GoCAR-NK technologies. Using the rimiducid-based switch system, GoCAR cell therapies feature an inducible MyD88/CD40 (iMC) activation switch designed to enhance proliferation and functional persistence of adoptive cell therapies by resisting exhaustion and by driving production of immunomodulatory cytokines to overcome inhibitory signals from the tumor microenvironment. GoCAR cell therapies may be particularly well-suited for use in solid tumors given their immune suppressive tumor microenvironment.

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MD Anderson acquires inducible switch technologies for cell therapy - MD Anderson Cancer Center

IGF-1-mediated FOXC1 overexpression induces stem-like properties through upregulating CBX7 and IGF-1R in … – Nature.com

By Stem Cell Treatment

Data collection

A comprehensive cancer genomics program, The Cancer Genome Atlas (TCGA) has conducted molecular characterizations of 33 primary cancer types. Using UALCAN (https://ualcan.path.uab.edu/analysis.html), exploration of FOXC1 expression in esophageal squamous cell carcinoma was conducted utilizing data extracted from the TCGA database.

Human esophageal squamous cell carcinoma cell lines, such as TE-1, ECA-109, KYSE-30, and KYSE-150, were procured from the Institute of Biological Sciences of the Chinese Academy of Sciences in Shanghai. Subsequently, routine mycoplasma contamination testing was conducted. Cells were maintained at 37C with 5% CO2, cultured in DMEM medium (GIBCO) containing 1% penicillin-streptomycin and 10% Fetal Bovine Serum (GIBCO).

Cells were seeded into 6-well plates for transient knockdown transfection, followed by the transfection of 100pmol siRNA-FOXC1 (GenePharma, Shanghai, China) using HighGene (ABclonal, Wuhan, China) ECAh well, following the manufacturers guidance. Cells were seeded into 6-well plates for transient gene overexpression transfection, followed by the transfection of the plasmids expressing CBX7 or IGF-1R were purchased from Genechem (Shanghai, China) using HighGene (ABclonal, Wuhan, China).

At 48h post-transfection, transfection efficiency was assessed using RT-qPCR and western blot. For stable transfection, ECA-109 and KYSE-150 cells were transfected with lentivirus vectors encoding either FOXC1-targeting shRNA or non-targeting control shRNA, following the manufacturers instructions (Genechem, Shanghai, China). Briefly, cells were seeded in 6-well plates, and when the cell density reached 30%, a medium containing viral fluid at an MOI of 10, without serum, was added. This medium was replaced with a complete medium 24h later. After lentiviral infection, ECA-109 cells and KYSE-150 cells underwent a two-week selection process with 1g/mL puromycin to obtain stable clones. Transfection efficiency for each vector was evaluated through a western blot.

In the cell migration experiment, 1 105 cells were re-suspended in 200L serum-free DMEM medium and added to the upper compartment, and 500 l DMEM medium containing 10%FBS was added to the lower compartment to induce the migration of cells. In the cell invasion experiment, the cells re-suspended in 200L serum-free DMEM medium were added to the upper chamber coated with Matrigel matrix (Corning, 356234), and the rest procedures were performed the same as the cell migration experiment. Fixation with 4% paraformaldehyde and staining with crystal violet dye were conducted after a 24-h incubation period. Subsequently, IMAGEJ software was employed for cell number quantification.

We introduced a seeding density of 2000 cells per well into 96-well plates and established an arrangement of 10 sub-wells. After the cells were fully attached to the plate, CCK8 reagent (10 l per well) was added at 0,24,48,72,96h, respectively. Subjected to incubation in the absence of light for an hour, the microplate reader was employed to analyze the absorbance at 450nM. Three repetitions of the experiments were executed, followed by the final statistical analysis performed using GraphPad Prism 8.0.

6-well plates were used for cell inoculation, with ECAh well receiving 1 103 cells, and subsequent culture was carried out in DMEM medium containing 10% FBS and 1% Penicillin-Streptomycin Solution. After a 14-day incubation period, cell fixation was performed using 4% paraformaldehyde, followed by staining with 0.1% crystal violet dye. The colony count was determined using ImageJ software.

The ECA-109 cells and KYSE-150 cells were plated into ultra-low six-well plates (Corning) at 1 103 cells/well. The cells were cultured in serum-free DMEM/F12(Gibco) with 2% B27(Invitrogen)20ng/mL EGF(PeproTech)20ng/mL bFGF(PeproTech) for 14 days. The size of the tumor spheroids was observed under a light microscope and the count of spheres with a diameter greater than 100M was counted.

ECA-109 cells and KYSE-150 cells were incubated in 6-well plates in DMEM supplemented with 10% FBS, 1% penicillin-streptomycin, and 1M cisplatin. After incubation for 24h, the cells were gathered, and an Annexin V-FITC apoptosis analysis kit (Elabscience Biotechnology) was utilized to assess the percentage of apoptotic cells, following the step-by-step instructions in the user manual. Results were represented as the mean of % cell death of at least three independent replicates.

1 106 ECA-109 cells and 1 106 KYSE-150 cells were incubated with CD44 antibody(R&D Systems)for 10min at room temperature, and washed twice twice after that. The FACS was performed using the Beckman CytoFLEX and the percentage of CD44+ cells was analyzed.

Cells were subjected to RNA isolation using Trizol (Vazyme) followed by reverse transcription into cDNA using the Reverse Transcriptase Kit (Abclonal). RT-qPCR was performed with the primers for FOXC1, CBX7, IGF- 1R, CD133, CD44, and -actin, and the fold change was calculated by the 2-Ct method. Cloud-Seq Biotech (Shanghai, China) conducted RNA high-throughput sequencing, wherein the removal of rRNAs was accomplished using the GenSeq rRNA Removal Kit (GenSeq, Inc.) with total RNA. After the removal of rRNA from the samples, library construction was carried out utilizing the GenSeq Low Input RNA Library Prep Kit (GenSeq, Inc.), following the prescribed protocol from the manufacturer. Quality control and quantification of the libraries were executed using the BioAnalyzer 2100 system (Agilent Technologies, Inc., USA). The sequencing of the libraries transpired on an Illumina Novaseq instrument, employing 150bp paired-end reads. Primer sequences are listed in Table 1.

Proteins were extracted using RIPA lysate (Beyotime) supplemented with 1% PMSF (Beyotime) and 2% phosphatase inhibitor (Beyotime). Following electrophoretic separation through SDS-PAGE, the proteins were transferred onto PVDF membranes. After blocking with 5% skim milk, primary antibodies specific for FOXC1 (ab227977, Abcam,1:1000), CD44 (A19020, Abclonal,1:1000), CD133 (A0219, Abclonal,1:1000), CBX7 (ab178411, Abcam,1:1000), IGF-1R (ab182408, Abcam,1:1000), phosphor-IGF-1R (ab39398, Abcam,1:1000), Akt (4691, Cell Signaling Technology,1:1000), phospho-Akt (S473) (4060, Cell Signaling Technology,1:1000), ERK1/2 (ab184699, Abcam,1:1000), phospho -ERK1/2 (ab201015, Abcam,1:1000) primary antibodies overnight and -actin (AC026, Abclonal,1:10000) as internal reference were used for protein examination. .

Cultivated cells were fixed, chromatin sonicated, immunoprecipitated, and DNA purified according to ChIP-IT High Sensitivity kit (Active Motif) instructions, and the relative abundance of target DNA was analyzed by qPCR. Primer sequences are listed in Table 1.

Tissue samples for this study were sourced from individuals diagnosed with esophageal squamous cell carcinoma at Tongji Universitys Dongfang Hospital, totaling 79 patients. Following fixation in formalin and embedding in paraffin, tissue sections were sliced to a thickness of 4m. Subsequently, the sections underwent deparaffinization and hydration through immersion in xylene and graded alcohols. Heat-induced antigen retrieval was conducted in EDTA buffer (pH 8.0) for 15minutes, utilizing a microwave oven. To minimize nonspecific staining, blocking was carried out with 10% goat serum. Following this, specific primary antibodies, including FOXC1 (ab227977, Abcam, 1:200), CD44 (A19020, Abclonal, 1:200), and CD133 (A0219, Abclonal, 1:100), were applied to the sections and left to incubate overnight at 4C. The slides were then counterstained with light hematoxylin, subjected to dehydration, and covered with slips. The outcomes were evaluated by two pathologists independently, with no access to clinical data, and subsequent analyses encompassed TNM staging and survival assessment. The study was conducted with the written informed consent of the patients and approved by the Institutional Review Committee of East Hospital Affiliated with Tongji University in Shanghai.

The Animal Protection and Use Committee of Tongji University approved all animal experiments. Animal experimentation involved the utilization of 10 BALB/c nude mice, all of the female gender and aged 6 weeks.KYSE-150-FOXC1-LV and KYSE-150-NC-LV were injected subcutaneously into the right abdomen of two groups of mice, purchased from Gempharmatech Co., Ltd. The mice were euthanized, and the tumors were subsequently extracted after 4 weeks for size measurement and weighing. A portion of the tumor tissue was fixed with 10% paraformaldehyde and paraffin-embedded for subsequent immunohistochemical staining analysis, and the rest was used for protein and mRNA extraction.

The in vivo experiments were repeated three times and the final results were taken as the meanstandard deviation. Statistical comparison analysis was performed by GraphPad Prism 8.0. For survival analysis, the Kaplan-Meier method and log-rank test were employed, and statistical significance was established for P values less than 0.05.

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IGF-1-mediated FOXC1 overexpression induces stem-like properties through upregulating CBX7 and IGF-1R in ... - Nature.com

Stem Cells Explained: The Science Behind Osteoarthritis Treatments – Corporate Wellness Magazine

By Stem Cell Treatment

In recent years, stem cell therapy has emerged as a promising avenue for treating various medical conditions, including osteoarthritis. This innovative approach holds the potential to revolutionize the field of regenerative medicine, offering new hope for patients seeking alternatives to traditional treatments like surgery or medication. In this article, we delve into the science behind stem cell treatments for osteoarthritis, exploring how they work, their potential benefits, and considerations for those considering this option.

Stem cells are unique cells in the body with the remarkable ability to develop into different types of cells. They serve as the body's natural repair system, replenishing damaged tissues and organs. Stem cells can be found in various parts of the body, including bone marrow, adipose tissue (fat), and umbilical cord blood.

Osteoarthritis is a degenerative joint disease characterized by the breakdown of cartilage, the protective tissue that cushions the ends of bones in joints. This condition can lead to pain, stiffness, and reduced mobility. Traditional treatments focus on managing symptoms and may include pain medications, physical therapy, and in severe cases, joint replacement surgery.

Stem cell therapy offers a different approach by targeting the underlying cause of osteoarthritisthe deterioration of cartilage. By harnessing the regenerative potential of stem cells, researchers and clinicians aim to repair damaged cartilage and promote tissue regeneration within the joint.

In stem cell therapy for osteoarthritis, stem cells are harvested from the patient's own body or from other sources, such as umbilical cord tissue. These cells are then processed and concentrated before being injected directly into the affected joint.

Once injected, the stem cells work to reduce inflammation, stimulate tissue repair, and encourage the growth of new, healthy cartilage. This process is believed to slow down or even reverse the progression of osteoarthritis, providing long-term relief from pain and improving joint function.

One of the primary benefits of stem cell therapy for osteoarthritis is its potential to offer long-lasting pain relief and improved joint function without the need for surgery. Unlike traditional treatments that focus on symptom management, stem cell therapy addresses the underlying cause of the condition, offering the possibility of disease modification.

Additionally, stem cell therapy is minimally invasive and typically associated with minimal downtime and few complications. This makes it an attractive option for individuals looking to avoid the risks and lengthy recovery associated with surgical interventions.

While stem cell therapy holds promise for the treatment of osteoarthritis, it's essential for patients to approach this option with caution and realistic expectations. While research into the efficacy of stem cell therapy for osteoarthritis is ongoing, the evidence supporting its use is still evolving.

Patients considering stem cell therapy should consult with a qualified healthcare provider who can assess their condition, discuss treatment options, and provide guidance based on the latest scientific evidence. It's also important to thoroughly research any clinics or providers offering stem cell therapy and ensure they adhere to ethical and regulatory standards.

In conclusion, Stem cell therapy represents a promising frontier in the treatment of osteoarthritis, offering the potential for disease modification and long-term symptom relief. By harnessing the regenerative power of stem cells, researchers and clinicians are paving the way for innovative treatments that may transform the lives of millions affected by this debilitating condition. While more research is needed to fully understand the benefits and limitations of stem cell therapy for osteoarthritis, early results are promising, offering hope for a future where joint pain and disability are no longer inevitable consequences of aging and disease.

Given his unparalleled expertise and success in treating elite athletes and high-profile individuals, we highly recommend Dr. Chad Prodromos for anyone seeking top-tier stem cell treatment. His work at the Prodromos Stem Cell Institute is at the forefront of regenerative medicine, offering innovative solutions for a range of conditions. To explore how Dr. Prodromos can assist in your health journey, consider reaching out through his clinic's website for more detailed information and to schedule a consultation. visit Prodromos Stem Cell Institute.

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Stem Cells Explained: The Science Behind Osteoarthritis Treatments - Corporate Wellness Magazine

New sickle cell therapy uses gene editing at MUSC | Health | postandcourier.com – The Post and Courier

By Stem Cell Treatment

Sickle cell is widely misunderstood, even by many health care providers, so Peterson is making TikTok videos about it and about her journey to try and change that. Sickle cell patients in pain crises often run up against skeptical providers when they seek care because they look normal.

"Nothing shows on the outside," Peterson said.

Seemingly normal things can be difficult for them. For instance, flying can cause terrible pain for patients because of the air pressure or temperature change, butPeterson has still managed a few short hops with her younger brother Emmanuel, who is a pilot.

Olivia Peterson is no stranger to the pain crises. And even seemingly small things, like the weather, can trigger a crippling episode, said her mother, Vanessa, recalling a big 5th birthday party that had been planned. Then a storm front hit.

"We had to call and say, 'Were going to the hospital right now, so were sorry,' " Vanessa Peterson said. "She had her birthday in the hospital."

"Its not the first birthday I spent in the hospital," Olivia Peterson said, but she has learned to laugh about it now.

Vanessa Peterson (left) rests her chin on her daughter Olivia Peterson's shoulder while they sit on a hospital bed at MUSCs Sean Jenkins Childrens Hospital in Charleston on Feb. 8, 2024. Vanessa has been a huge supporter of her daughter over the years, driving her to appointments and sharing a laugh with her whenever possible. The two are very close.

There have been other disappointments along the way. MUSC and other centers have looked at bone marrow transplants for sickle cell patients as a potential long-term therapy, and that is when Jaroscak and Olivia Peterson met five years ago. But without a good donor match, she wasn't a candidate for that clinical trial.

Jaroscak continued with her other treatment, and when the RUBY trial came along and Peterson appeared to qualify, she picked up the phone.

"I called her up and said, 'Olivia, would you like to talk again?' " Jaroscak said.

For Peterson, it was like finding the Golden Ticket in the "Willy Wonka" movies, staring down at her chocolate bar in disbelief.

"I tell you it was one of those moments when you are so ready for something that you are not exactly really ready for it in that moment," she said. "Its right there, at your front door. And youre like, 'Oh, is this really happening right now?' "

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New sickle cell therapy uses gene editing at MUSC | Health | postandcourier.com - The Post and Courier