Activation of the transcription factor c-Jun in acute cellular and antibody-mediated rejection after kidney transplantation

CCR7 and CD48 as Predicted Targets in Acute Rejection Related to M1 Macrophage after Pediatric Kidney Transplantation

Background

Kidney transplantation (KT) is the best treatment for end-stage renal disease. Although long and short-term survival rates for the graft have improved significantly with the development of immunosuppressants, acute rejection (AR) remains a major risk factor attacking the graft and patients. The innate immune response plays an important role in rejection. Therefore, our objective is to determine the biomarkers of congenital immunity associated with AR after KT and provide support for future research.

Materials and Methods

A differential expression genes (DEGs) analysis was performed based on the dataset GSE174020 from the NCBI gene Expression Synthesis Database (GEO) and then combined with the GSE5099 M1 macrophage-related gene identified in the Molecular Signatures Database. We then identified genes in DEGs associated with M1 macrophages defined as DEM1Gs and performed gene ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) enrichment analysis. Cibersort was used to analyze the immune cell infiltration during AR. At the same time, we used the protein-protein interaction (PPI) network and Cytoscape software to determine the key genes. Dataset, GSE14328 derived from pediatric patients, GSE138043 and GSE9493 derived from adult patients, were used to verify Hub genes. Additional verification was the rat KT model, which was used to perform HE staining, immunohistochemical staining, and Western Blot. Hub genes were searched in the HPA database to confirm their expression. Finally, we construct the interaction network of transcription factor (TF)-Hub genes and miRNA-Hub genes.

Results

Compared to the normal group, 366 genes were upregulated, and 423 genes were downregulated in the AR group. Then, 106 genes related to M1 macrophages were found among these genes. GO and KEGG enrichment analysis showed that these genes are mainly involved in cytokine binding, antigen binding, NK cell-mediated cytotoxicity, activation of immune receptors and immune response, and activation of the inflammatory NF-κB signaling pathway. Two Hub genes, namely CCR7 and CD48, were identified by PPI and Cytoscape analysis. They have been verified in external validation sets, originated from both pediatric patients and adult patients, and animal experiments. In the HPA database, CCR7 and CD48 are mainly expressed in T cells, B cells, macrophages, and tissues where these immune cells are distributed. In addition to immunoinfiltration, CD4+T, CD8+T, NK cells, NKT cells, and monocytes increased significantly in the AR group, which was highly consistent with the results of Hub gene screening. Finally, we predicted that 19 TFs and 32 miRNAs might interact with the Hub gene.

Conclusions

Through a comprehensive bioinformatic analysis, our findings may provide predictive and therapeutic targets for AR after KT.

Coexpression network analysis of human candida infection reveals key modules and hub genes responsible for host-pathogen interactions

Invasive fungal infections are a significant reason for morbidity and mortality among organ transplant recipients. Therefore, it is critical to investigate the host and candida niches to understand the epidemiology of fungal infections in transplantation. Candida albicans is an opportunistic fungal pathogen that causes fatal invasive mucosal infections, particularly in solid organ transplant patients. Therefore, identifying and characterizing these genes would play a vital role in understanding the complex regulation of host-pathogen interactions. Using 32 RNA-sequencing samples of human cells infected with C. albicans, we developed WGCNA coexpression networks and performed DESeq2 differential gene expression analysis to identify the genes that positively correlate with human candida infection. Using hierarchical clustering, we identified 5 distinct modules. We studied the inter- and intramodular gene network properties in the context of sample status traits and identified the highly enriched genes in the correlated modules. We identified 52 genes that were common in the most significant WGCNA turquoise module and differentially expressed genes in human endothelial cells (HUVEC) infection vs. control samples. As a validation step, we identified the differentially expressed genes from the independent Candida-infected human oral keratinocytes (OKF6) samples and validated 30 of the 52 common genes. We then performed the functional enrichment analysis using KEGG and GO. Finally, we performed protein-protein interaction (PPI) analysis using STRING and CytoHubba from 30 validated genes. We identified 8 hub genes (JUN, ATF3, VEGFA, SLC2A1, HK2, PTGS2, PFKFB3, and KLF6) that were enriched in response to hypoxia, angiogenesis, vasculogenesis, hypoxia-induced signaling, cancer, diabetes, and transplant-related disease pathways. The discovery of genes and functional pathways related to the immune system and gene coexpression and differential gene expression analyses may serve as novel diagnostic markers and potential therapeutic targets.

A quadratically regularized functional canonical correlation analysis for identifying the global structure of pleiotropy with NGS data

Investigating the pleiotropic effects of genetic variants can increase statistical power, provide important information to achieve deep understanding of the complex genetic structures of disease, and offer powerful tools for designing effective treatments with fewer side effects. However, the current multiple phenotype association analysis paradigm lacks breadth (number of phenotypes and genetic variants jointly analyzed at the same time) and depth (hierarchical structure of phenotype and genotypes). A key issue for high dimensional pleiotropic analysis is to effectively extract informative internal representation and features from high dimensional genotype and phenotype data. To explore correlation information of genetic variants, effectively reduce data dimensions, and overcome critical barriers in advancing the development of novel statistical methods and computational algorithms for genetic pleiotropic analysis, we proposed a new statistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association analysis which combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CCA). Large-scale simulations show that the QRFCCA has a much higher power than that of the ten competing statistics while retaining the appropriate type 1 errors. To further evaluate performance, the QRFCCA and ten other statistics are applied to the whole genome sequencing dataset from the TwinsUK study. We identify a total of 79 genes with rare variants and 67 genes with common variants significantly associated with the 46 traits using QRFCCA. The results show that the QRFCCA substantially outperforms the ten other statistics.

Anti-donor HLA class I antibodies: pathways to endothelial cell activation and cell-mediated allograft rejection

BACKGROUND

The development of donor-specific human leukocyte antigen (HLA) class I antibodies after organ transplantation is associated with subsequent acute and chronic rejection. The aim of this study was to examine the role of anti-HLA class I antibody in modulating endothelium-leukocyte interaction.

METHODS

Human microvascular endothelial cells (HMEC-1) stimulated with HLA class I antibody (W6/32) or allospecific antibodies from sensitized patients (n=6) were examined for activation of transcription factor CREB by Western blotting. Up-regulation of endothelial adhesion molecules and chemokines was measured by flow cytometry and quantitative polymerase chain reaction, respectively. Leukocyte adhesion was evaluated by chemotaxis and in vitro flow-based assays.

RESULTS

Treatment of HMEC-1 cells with HLA class I antibody resulted in the phosphorylation of CREB in protein kinase A-dependent pathway. Furthermore, there was a significant increase in the expression of cell surface VCAM-1 (Akt-dependent) and ICAM-1 in Akt-dependent and extracellular signal-regulated kinase-dependent manner (P<0.001). Additionally, exposure to W6/32 antibody induced significant expression of interleukin-6, CXCL8, CXCL10, and CCL5. Knockdown of CREB produced a reduction in W6/32-induced CXCL8 expression (P<0.001). Media from W6/32-treated endothelial cells induced a significant monocyte chemotaxis (P<0.001) and flow-based adhesion assay demonstrated an increase in monocyte adhesion to endothelial cells compared with the control group (P<0.001). Importantly, allospecific antibodies from sensitized patients also activated endothelial CREB and significantly up-regulated VCAM-1, ICAM-1, and CXCL8.

CONCLUSION

These findings suggest that donor-specific HLA class I antibodies directly activate endothelial cells leading to an increase in their potential to recruit and bind recipient leukocytes, thereby increasing the potential for allograft inflammation.

MicroRNA-155 regulates T cell proliferation through targeting GSK3β in cardiac allograft rejection in a murine transplantation model

Here we investigated the activity and regulation of miR-155 during cardiac allograft rejection (AR), and to examine the feasibility of using miR-155 as a biomarker of graft status. Expression of miR-155 in graft-infiltrating lymphocytes (GIL), T cells isolated from spleen (TFS), and lymphocytes separated from blood (LFB) was significantly increased during cardiac AR while GSK3β was downregulated in GIL and TFS. Inhibition of miR-155 impaired lymphocyte proliferation and enhanced the expression of GSK3β. Moreover, pharmacological inactivation of GSK3β resulted in rescue of the proliferative capability of T cells pretreated with a miR-155 inhibitor. Luciferase reporter assay confirmed that miR-155 interacted with the 3'-untranslated region (UTR) of GSK3β directly. In particular, the miR-155 in LFB can distinguish recipients with AR from syngeneic controls from POD 3 and later. The present study provides a better understanding of the pathophysiological process underlying cardiac AR progression.

Endothelial chimerism after ABO-incompatible kidney transplantation

BACKGROUND

Endothelial chimerism in transplanted organs can be defined as the presence of recipient-derived endothelial cells in the donor organ. The mechanism of endothelial chimerism is not well understood and remains controversial. The purpose of this study was twofold. First, we investigated the presence of chimerism in renal allografts of ABO-incompatible kidney transplantation recipients. Second, we analyzed the association between chimerism and the clinical course and histopathological changes.

METHODS

We investigated the presence of chimerism in renal allografts of ABO-incompatible kidney transplantation recipients by immunohistochemical detection of blood type A and B antigens and assessed the association between chimerism, the clinical course, and histopathological changes. Among a total of 56 patients (29 blood group A incompatible and 27 blood group B incompatible), 49 cases (28 blood group A incompatible and 21 blood group B incompatible) were enrolled in this study. Blood group antigens were stained using immunohistochemistry.

RESULTS

Twelve of the 49 patients (12/49, 24.5%) exhibited endothelium chimerism in a biopsy sample. Among the 12 patients with endothelium chimerism, 7 patients (7/12, 59%) had acute and chronic active antibody-mediated rejection and 2 patients (2/12, 17%) had severe calcineurin inhibitor toxicity. The graft survival rate in the chimerism group was significantly lower than that in the no-chimerism group ([chimerism vs. no-chimerism] 3 years, 83.3% vs. 97.1%; 5 years, 74.1% vs. 97.1%; 8 years, 46.3% vs. 97.1%; P<0.0001).

CONCLUSIONS

Endothelial chimerism seems to be a hallmark of vigorous immune or nonimmune responses, such as antibody-mediated rejection or calcineurin inhibitor toxicity, and not of the induction of tolerance.

Antibody-mediated allograft rejection: the emerging role of endothelial cell signalling and transcription factors

The presence of antibodies against class I human leukocyte antigens (HLA) can cause the development of chronic allograft rejection. Although endothelial cell activation has been identified as a main effector, the mechanisms mediating this process are not fully understood. Exposure of endothelium to antibodies against HLA antigens induces cell activation which promotes rejection. This activation process can be divided into two phases: an early response in which intracellular signalling proteins and transcription factors are activated, and a later change in protein expression and cell function. In this review, antibody-mediated endothelial signalling and the role of transcription factors in organ transplantation will be described with a particular focus on their potential to mediate some of the graft-damaging effects of anti-HLA class I antibodies.