Wnt/β-catenin signaling mediates the abnormal osteogenic and adipogenic capabilities of bone marrow mesenchymal stem cells from chronic graft-versus-host disease patients

Nestin+ Mesenchymal Stromal Cells Fibrotic Transition Mediated by CD169+ Macrophages in Bone Marrow Chronic Graft-versus-Host Disease

Chronic graft-versus-host disease (cGVHD) involves multiple organs, but little is known about bone marrow (BM) alterations caused by cGVHD. In mice and humans, we found that cGVHD is associated with BM fibrosis resulting in T cell infiltration, IgG deposition, and hematopoietic dysfunction. Macrophages and Nestin+ mesenchymal stromal cells (MSCs) participated in the process of BM fibrosis during BM cGVHD development. BM macrophage numbers were significantly increased in mice and humans with BM fibrosis associated with cGVHD. Amplified macrophages produced TGF-β1, which recruited Nestin+ MSCs forming clusters, and Nestin+ MSCs later differentiated into fibroblasts, a process mediated by increased TGF-β/Smad signaling. TLR4/MyD88-mediated activation of endoplasmic reticulum (ER) stress in macrophages is associated with fibrosis by increasing Nestin+ MSC migration and differentiation into fibroblasts. Depletion of macrophages by clodronate-containing liposomes and inhibition of ER stress by 4-phenylbutyric acid reversed BM fibrosis by inhibiting fibroblast differentiation. These studies provide insights into the pathogenesis of BM fibrosis during cGVHD development.

Validated graft-specific biomarkers identify patients at risk for chronic graft-versus-host disease and death

BACKGROUNDChronic graft-versus-host disease (cGVHD) is a serious complication of allogeneic hematopoietic cell transplantation (HCT). More accurate information regarding the risk of developing cGVHD is required. Bone marrow (BM) grafts contribute to lower cGVHD, which creates a dispute over whether risk biomarker scores should be used for peripheral blood (PB) and BM.METHODSDay 90 plasma proteomics from PB and BM recipients developing cGVHD revealed 5 risk markers that were added to 8 previous cGVHD markers to screen 982 HCT samples of 2 multicenter Blood and Marrow Transplant Clinical Trials Network (BMTCTN) cohorts. Each marker was tested for its association with cause-specific hazard ratios (HRs) of cGVHD using Cox-proportional-hazards models. We paired these clinical studies with biomarker measurements in a mouse model of cGVHD.RESULTSSpearman correlations between DKK3 and MMP3 were significant in both cohorts. In BMTCTN 0201 multivariate analyses, PB recipients with 1-log increase in CXCL9 and DKK3 were 1.3 times (95% CI: 1.1-1.4, P = 0.001) and 1.9 times (95%CI: 1.1-3.2, P = 0.019) and BM recipients with 1-log increase in CXCL10 and MMP3 were 1.3 times (95%CI: 1.0-1.6, P = 0.018 and P = 0.023) more likely to develop cGVHD. In BMTCTN 1202, PB patients with high CXCL9 and MMP3 were 1.1 times (95%CI: 1.0-1.2, P = 0.037) and 1.2 times (95%CI: 1.0-1.3, P = 0.009) more likely to develop cGVHD. PB patients with high biomarkers had increased likelihood to develop cGVHD in both cohorts (22%-32% versus 8%-12%, P = 0.002 and P < 0.001, respectively). Mice showed elevated circulating biomarkers before the signs of cGVHD.CONCLUSIONBiomarker levels at 3 months after HCT identify patients at risk for cGVHD occurrence.FUNDINGNIH grants R01CA168814, R21HL139934, P01CA158505, T32AI007313, and R01CA264921.

Screening for genes, miRNAs and transcription factors of adipogenic differentiation and dedifferentiation of mesenchymal stem cells

BACKGROUND

The purpose of present study was to reveal the molecular mechanisms responsible for both adipogenic differentiation and dedifferentiation of mesenchymal stem cells (MSCs).

METHODS

Microarray data GSE36923 were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between adipogenically differentiated cells vs undifferentiated bone marrow-derived MSCs, adipogenically differentiated cells vs dedifferentiated cells samples at day 7 and adipogenically differentiated cells vs dedifferentiated cells samples at day 35 were screened, and overlapped DEGs across the three groups were analyzed. The underlying functions of the upregulated and downregulated DEGs were investigated by Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis. The protein-protein interaction network was constructed, and hub genes were obtained subsequently. Hub genes were verified with GSE113253 dataset, and then miRNA-gene network and TF-gene network were constructed.

RESULTS

A total of 284 upregulated DEGs and 376 downregulated DEGs overlapped across the three groups. PPAR signaling pathway, AMPK signaling pathway, insulin signaling pathway, carbon metabolism, pyruvate metabolism, fatty acid metabolism, regulation of lipolysis in adipocytes, biosynthesis of amino acids, citrate cycle (TCA cycle) and 2-Oxocarboxylic acid metabolism were the top 10 pathways involving in the upregulated DEGs, and graft-versus-host disease, allograft rejection, viral myocarditis, cell adhesion molecules, phagosome, type I diabetes mellitus, antigen processing and presentation, autoimmune thyroid disease, intestinal immune network for IgA production and rheumatoid arthritis were the top 10 pathways in downregulated DEGs. After validation, the 8 hub genes were IL6, PPARG, CCL2, FASN, CEBPA, ADIPOQ, FABP4 and LIPE. Ten key miRNAs were hsa-mir-27a-3p, hsa-mir-182-5p, hsa-mir-7-5p, hsa-mir-16-5p, hsa-mir-1-3p, hsa-mir-155-5p, hsa-mir-21-3p, hsa-mir-34a-5p, hsa-mir-27a-5p and hsa-mir-30c-5p, and 10 key TFs were TFDP1, GTF2A2, ZNF584, NRF1, ZNF512, NFRKB, CEBPG, KLF16, GLIS2 and MXD4.

CONCLUSION

Our study constructed miRNA-gene network and TF-gene network involved in both adipogenic differentiation and dedifferentiation of MSCs, contributing to enhancing the efficiency of MSCs transplantation in soft tissue defect repair and developing more potent remedies for adipogenesis-related skeletal disorders.