Cell-Mediated Immunity (CMI) as the Instrument to Assess the Response Against the Allograft: Present and Future

Monitoring of Serological, Cellular and Genomic Biomarkers in Transplantation, Computational Prediction Models and Role of Cell-Free DNA in Transplant Outcome

The process and evolution of an organ transplant procedure has evolved in terms of the prevention of immunological rejection with the improvement in the determination of immune response genes. These techniques include considering more important genes, more polymorphism detection, more refinement of the response motifs, as well as the analysis of epitopes and eplets, its capacity to fix complement, the PIRCHE algorithm and post-transplant monitoring with promising new biomarkers that surpass the classic serum markers such as creatine and other similar parameters of renal function. Among these new biomarkers, we analyze new serological, urine, cellular, genomic and transcriptomic biomarkers and computational prediction, with particular attention to the analysis of donor free circulating DNA as an optimal marker of kidney damage.

Importance of human leukocyte antigen antibodies and leukocyte antigen/killer-cell immunoglobulin-like receptor genes in liver transplantation

Many mechanisms have been proposed to explain the hypothetical state of hepatic tolerance, which is described by eventual imbalances or deregulation in the balance of cytokines, mediators, effectors, and regulatory cells in the complex milieu of the liver. In this section, we will comment on the importance of donor-specific anti-human leukocyte antigen (HLA) antibodies (DSA) as well as the compatibility and pairings of HLA and killer-cell immunoglobulin-like receptor (KIR) genotypes in the evolution of liver transplantation. Thus, HLA compatibility, viral infections, and HLA-C/KIR combinations have all been linked to liver transplant rejection and survival. There have been reports of increased risk of acute and chronic rejection with ductopenia, faster graft fibrosis, biliary problems, poorer survival, and even de novo autoimmune hepatitis when DSAs are present in the recipient. Higher mean fluorescence intensity (MFI) values of the DSAs and smaller graft size were associated with poorer patient outcomes, implying that high-risk patients with preformed DSAs should be considered for selecting the graft placed and desensitization methods, according to the investigators. Similarly, in a combined kidney-liver transplant, a pretransplant with a visible expression of several DSAs revealed that these antibodies were resistant to treatment. The renal graft was lost owing to antibody-mediated rejection (AMR). The HLA antigens expressed by the transplanted liver graft influenced antibody elimination. Pathologists are increasingly diagnosing AMR in liver transplants, and desensitization therapy has even been employed in situations of AMR, particularly in patients with DSAs in kidney-hepatic transplants and high-class II MFI due to Luminex. In conclusion, after revealing the negative impacts of DSAs with high MFI, pretransplant virtual crossmatch techniques may be appropriate to improve evolution; however, they may extend cold ischemia periods by requiring the donor to be typed.

Into the multi-omics era: Progress of T cells profiling in the context of solid organ transplantation

T cells are the common type of lymphocyte to mediate allograft rejection, remaining long-term allograft survival impeditive. However, the heterogeneity of T cells, in terms of differentiation and activation status, the effector function, and highly diverse T cell receptors (TCRs) have thus precluded us from tracking these T cells and thereby comprehending their fate in recipients due to the limitations of traditional detection approaches. Recently, with the widespread development of single-cell techniques, the identification and characterization of T cells have been performed at single-cell resolution, which has contributed to a deeper comprehension of T cell heterogeneity by relevant detections in a single cell - such as gene expression, DNA methylation, chromatin accessibility, surface proteins, and TCR. Although these approaches can provide valuable insights into an individual cell independently, a comprehensive understanding can be obtained when applied joint analysis. Multi-omics techniques have been implemented in characterizing T cells in health and disease, including transplantation. This review focuses on the thesis, challenges, and advances in these technologies and highlights their application to the study of alloreactive T cells to improve the understanding of T cell heterogeneity in solid organ transplantation.

A high concentration of TGF-β correlates with opportunistic infection in liver and kidney transplantation

Transforming growth factor-β (TGF-β) has been associated with numerous human infections, but its role in the occurrence of opportunistic infection (OI) after solid organ transplantation remains unexplored. This study aimed to assess the utility of the TGF-β following in vitro stimulation of whole peripheral blood (WPB) as a surrogate biomarker of post-transplant OI in a cohort of liver and kidney recipients. Thirty liver and thirty-one kidney transplant recipients were recruited to be prospectively monitored for one-year post-transplantation. Enzyme-linked immunosorbent assay (ELISA) was performed to calculate IFN-γ, IL-17, IL-10 and TGF-β concentration in the supernatant from the activated WPB. Recipients showed higher TGF-β concentrations compared to IFN-γ, IL-17, IL-10 at baseline, although these differences were not significant between INF and NoINF. However, recipients who developed an OI within the first sixth months had a higher concentration of TGF-β than those without OI. A concentration of TGF-β > 363.25 pg/ml in liver and TGF-β > 808.51 pg/ml in kidney recipients were able to stratify patients at high risk of OI with a sensitivity and specificity above 70% in both types of solid organ transplantations. TGF-β could provide valuable information for the management of liver and kidney recipients at risk of post-transplant infection.

PCR Array Technology in Biopsy Samples Identifies Up-Regulated mTOR Pathway Genes as Potential Rejection Biomarkers After Kidney Transplantation

Background: Antibody-mediated rejection (AMR) is the major cause of kidney transplant rejection. The donor-specific human leukocyte antigen (HLA) antibody (DSA) response to a renal allograft is not fully understood yet. mTOR complex has been described in the accommodation or rejection of transplants and integrates responses from a wide variety of signals. The aim of this study was to analyze the expression of the mTOR pathway genes in a large cohort of kidney transplant patients to determine its possible influence on the transplant outcome. Methods: A total of 269 kidney transplant patients monitored for DSA were studied. The patients were divided into two groups, one with recipients that had transplant rejection (+DSA/+AMR) and a second group of recipients without rejection (+DSA/-AMR and -DSA/-AMR, controls). Total RNA was extracted from kidney biopsies and reverse transcribed to cDNA. Human mTOR-PCR array technology was used to determine the expression of 84 mTOR pathway genes. STRING and REVIGO software were used to simulate gene to gene interaction and to assign a molecular function. Results: The studied groups showed a different expression of the mTOR pathway related genes. Recipients that had transplant rejection showed an over-expressed transcript (≥5-fold) of AKT1S1, DDIT4, EIF4E, HRAS, IGF1, INS, IRS1, PIK3CD, PIK3CG, PRKAG3, PRKCB (>12-fold), PRKCG, RPS6KA2, TELO2, ULK1, and VEGFC, compared with patients that did not have rejection. AKT1S1 transcripts were more expressed in +DSA/-AMR biopsies compared with +DSA/+AMR. The main molecular functions of up-regulated gene products were phosphotransferase activity, insulin-like grown factor receptor and ribonucleoside phosphate binding. The group of patients with transplant rejection also showed an under-expressed transcript (≥5-fold) of VEGFA (>15-fold), RPS6, and RHOA compared with the group without rejection. The molecular function of down-regulated gene products such as protein kinase activity and carbohydrate derivative binding proteins was also analyzed. Conclusions: We have found a higher number of over-expressed mTOR pathway genes than under-expressed ones in biopsies from rejected kidney transplants (+DSA/+AMR) with respect to controls. In addition to this, the molecular function of both types of transcripts (over/under expressed) is different. Therefore, further studies are needed to determine if variations in gene expression profiles can act as predictors of graft loss, and a better understanding of the mechanisms of action of the involved proteins would be necessary.

Identification of peripheral CD154+ T cells and HLA-DRB1 as biomarkers of acute cellular rejection in adult liver transplant recipients

Decreasing graft rejection and increasing graft and patient survival are great challenges facing liver transplantation (LT). Different T cell subsets participate in the acute cellular rejection (ACR) of the allograft. Cell-mediated immunity markers of the recipient could help to understand the mechanisms underlying acute rejection. This study aimed to analyse different surface antigens on T cells in a cohort of adult liver patients undergoing LT to determine the influence on ACR using multi-parametric flow cytometry functional assay. Thirty patients were monitored at baseline and during 1 year post-transplant. Two groups were established, with (ACR) and without (NACR) acute cellular rejection. Leukocyte, total lymphocyte, percentages of CD4+ CD154+ and CD8+ CD154+ T cells, human leukocyte antigen (HLA) mismatch between recipient-donor and their relation with ACR as well as the acute rejection frequencies were analysed. T cells were stimulated with concanavalin A (Con-A) and surface antigens were analysed by fluorescence activated cell sorter (FACS) analysis. A high percentage of CD4+ CD154+ T cells (P = 0·001) and a low percentage of CD8+ CD154+ T cells (P = 0·002) at baseline were statistically significant in ACR. A receiver operating characteristic analysis determined the cut-off values capable to stratify patients at high risk of ACR with high sensitivity and specificity for CD4+ CD154+ (P = 0·001) and CD8+ CD154+ T cells (P = 0·002). In logistic regression analysis, CD4+ CD154+ , CD8+ CD154+ and HLA mismatch were confirmed as independent risk factors to ACR. Post-transplant percentages of both T cell subsets were significantly higher in ACR, despite variations compared to pretransplant. These findings support the selection of candidates for LT based on the pretransplant percentages of CD4+ CD154+ and CD8+ CD154+ T cells in parallel with other transplant factors.