Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates

Identification of metabolism-related key genes as potential biomarkers for pathogenesis of immune thrombocytopenia

Immune thrombocytopenia (ITP), an acquired autoimmune disease, is characterized by immune-mediated platelet destruction. A biomarker is a biological entity that contributes to disease pathogenesis and reflects disease activity. Metabolic alterations are reported to be associated with the occurrence of various diseases. As metabolic biomarkers for ITP have not been identified. This study aimed to identify metabolism-related differentially expressed genes as potential biomarkers for pathogenesis of ITP using bioinformatic analyses.The microarray expression data of the peripheral blood mononuclear cells were downloaded from the Gene Expression Omnibus database (GSE112278 download link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112278 ). Key module genes were intersected with metabolism-related genes to obtain the metabolism-related key candidate genes. The hub genes were screened based on the degree function in the coytoscape sofware. The key ITP-related genes were subjected to functional enrichment analysis. Immune infiltration analysis was performed using a single-sample gene set enrichment analysis algorithm to evaluate the differential infiltration levels of immune cell types between ITP patient and control. Molecular subtypes were identified based on the expression of hub genes. The expression of hub genes in the ITP patients was validated using quantitative real-time polymerase chain reaction analysis. This study identified five hub genes (ADH4, CYP7A1, CYP1A2, CYP8B1, and NR1H4), which were be associated with the pathogenesis of ITP, and two molecular subtypes of ITP. Among these hub genes, CYP7A1 and CYP8B1 involved in cholesterol metabolism,were further verified in clinical samples.

Application of Mass Cytometry Platforms to Solid Organ Transplantation

Transplantation serves as the cornerstone of treatment for patients with end-stage organ disease. The prevalence of complications, such as allograft rejection, infection, and malignancies, underscores the need to dissect the complex interactions of the immune system at the single-cell level. In this review, we discuss studies using mass cytometry or cytometry by time-of-flight, a cutting-edge technology enabling the characterization of immune populations and cell-to-cell interactions in granular detail. We review the application of mass cytometry in human and experimental animal studies in the context of transplantation, uncovering invaluable contributions of the tool to understanding rejection and other transplant-related complications. We discuss recent innovations that have the potential to streamline and standardize mass cytometry workflows for application to multisite clinical trials. Additionally, we introduce imaging mass cytometry, a technique that couples the power of mass cytometry with spatial context, thereby mapping cellular interactions within tissue microenvironments. The synergistic integration of mass cytometry and imaging mass cytometry data with other omics data sets and high-dimensional data platforms to further define immune dynamics is discussed. In conclusion, mass cytometry technologies, when integrated with other tools and data, shed light on the intricate landscape of the immune response in transplantation. This approach holds significant potential for enhancing patient outcomes by advancing our understanding and facilitating the development of new diagnostics and therapeutics.

IgM marks persistent IgG anti-human leukocyte antigen antibodies in highly sensitized heart transplant patients

BACKGROUND

Sensitization to human leukocyte antigens (HLA) is a persistent problem in heart transplant (HT) candidates. We sought to characterize the anti-HLA antibody and circulating B cell repertoire in a cohort of highly sensitized HT candidates.

METHODS

We assessed immunoglobulin G (IgG) and immunoglobulin M (IgM) anti-HLA antibodies using Luminex single antigen bead assays in a cohort of 11 highly sensitized (HS; calculated panel reactive antibody ≥ 90%) and 3 mildly sensitized (MS) candidates. We also performed B cell receptor repertoire sequencing (BCRseq) in HS candidates and 33 non-candidate controls. HLA antibody strength was measured by mean fluorescence intensity (MFI).

RESULTS

We found that IgM anti-HLA antibodies were present in all HS candidates, but with a lower breadth and strength as compared to IgG. When anti-HLA IgG specificities intersected with IgM, binding strength was higher. In contrast, there were IgM but no intersecting IgG specificities for the MS group. In four candidates in the HS group, IgG anti-HLA antibodies decreased in both breadth and strength after HT, but the decrease in strength was smaller if the IgG possessed a specificity that intersected with pre-transplant IgM. BCRseq revealed larger B cell clonotypes in HS candidates but similar diversity as compared to controls.

CONCLUSIONS

IgM marks IgG anti-HLA antibodies with higher strength before HT and persistence after HT. The presence of IgM intersecting IgG for an anti-HLA specificity may be a useful approach to determine which donor HLA should be avoided for a sensitized candidate.

The Value of Single-cell Technologies in Solid Organ Transplantation Studies

Single-cell technologies open up new opportunities to explore the behavior of cells at the individual level. For solid organ transplantation, single-cell technologies can provide in-depth insights into the underlying mechanisms of the immunological processes involved in alloimmune responses after transplantation by investigating the role of individual cells in tolerance and rejection. Here, we review the value of single-cell technologies, including cytometry by time-of-flight and single-cell RNA sequencing, in the context of solid organ transplantation research. Various applications of single-cell technologies are addressed, such as the characterization and identification of immune cell subsets involved in rejection or tolerance. In addition, we explore the opportunities for analyzing specific alloreactive T- or B-cell clones by linking phenotype data to T- or B-cell receptor data, and for distinguishing donor- from recipient-derived immune cells. Moreover, we discuss the use of single-cell technologies in biomarker identification and risk stratification, as well as the remaining challenges. Together, this review highlights that single-cell approaches contribute to a better understanding of underlying immunological mechanisms of rejection and tolerance, thereby potentially accelerating the development of new or improved therapies to avoid allograft rejection.

Full spectrum flow cytometry and mass cytometry: A 32-marker panel comparison

High-dimensional single-cell data has become an important tool in unraveling the complexity of the immune system and its involvement in homeostasis and a large array of pathologies. As technological tools are developed, researchers are adopting them to answer increasingly complex biological questions. Up until recently, mass cytometry (MC) has been the main technology employed in cytometric assays requiring more than 29 markers. Recently, however, with the introduction of full spectrum flow cytometry (FSFC), it has become possible to break the fluorescence barrier and go beyond 29 fluorescent parameters. In this study, in collaboration with the Stanford Human Immune Monitoring Center (HIMC), we compared five patient samples using an established immune panel developed by the HIMC using their MC platform. Using split samples and the same antibody panel, we were able to demonstrate highly comparable results between the two technologies using multiple data analysis approaches. We report here a direct comparison of two technology platforms (MC and FSFC) using a 32-marker flow cytometric immune monitoring panel that can identify all the previously described and anticipated immune subpopulations defined by this panel.

The promise of machine learning applications in solid organ transplantation

Solid-organ transplantation is a life-saving treatment for end-stage organ disease in highly selected patients. Alongside the tremendous progress in the last several decades, new challenges have emerged. The growing disparity between organ demand and supply requires optimal patient/donor selection and matching. Improvements in long-term graft and patient survival require data-driven diagnosis and management of post-transplant complications. The growing abundance of clinical, genetic, radiologic, and metabolic data in transplantation has led to increasing interest in applying machine-learning (ML) tools that can uncover hidden patterns in large datasets. ML algorithms have been applied in predictive modeling of waitlist mortality, donor–recipient matching, survival prediction, post-transplant complications diagnosis, and prediction, aiming to optimize immunosuppression and management. In this review, we provide insight into the various applications of ML in transplant medicine, why these were used to evaluate a specific clinical question, and the potential of ML to transform the care of transplant recipients. 36 articles were selected after a comprehensive search of the following databases: Ovid MEDLINE; Ovid MEDLINE Epub Ahead of Print and In-Process & Other Non-Indexed Citations; Ovid Embase; Cochrane Database of Systematic Reviews (Ovid); and Cochrane Central Register of Controlled Trials (Ovid). In summary, these studies showed that ML techniques hold great potential to improve the outcome of transplant recipients. Future work is required to improve the interpretability of these algorithms, ensure generalizability through larger-scale external validation, and establishment of infrastructure to permit clinical integration.

Progress and applications of mass cytometry in sketching immune landscapes

Recently emerged mass cytometry (cytometry by time-of-flight [CyTOF]) technology permits the identification and quantification of inherently diverse cellular systems, and the simultaneous measurement of functional attributes at the single-cell resolution. By virtue of its multiplex ability with limited need for compensation, CyTOF has led a critical role in immunological research fields. Here, we present an overview of CyTOF, including the introduction of CyTOF principle and advantages that make it a standalone tool in deciphering immune mysteries. We then discuss the functional assays, introduce the bioinformatics to interpret the data yield via CyTOF, and depict the emerging clinical and research applications of CyTOF technology in sketching immune landscape in a wide variety of diseases.

Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 1-Overview of Knowledge Discovery Techniques in Artificial Intelligence

Aim

To perform a systematic review on the application of artificial intelligence (AI) based knowledge discovery techniques in pharmacoepidemiology.

Study Eligibility Criteria

Clinical trials, meta-analyses, narrative/systematic review, and observational studies using (or mentioning articles using) artificial intelligence techniques were eligible. Articles without a full text available in the English language were excluded.

Data Sources

Articles recorded from 1950/01/01 to 2019/05/06 in Ovid MEDLINE were screened.

Participants

Studies including humans (real or simulated) exposed to a drug.

Results

In total, 72 original articles and 5 reviews were identified via Ovid MEDLINE. Twenty different knowledge discovery methods were identified, mainly from the area of machine learning (66/72; 91.7%). Classification/regression (44/72; 61.1%), classification/regression + model optimization (13/72; 18.0%), and classification/regression + features selection (12/72; 16.7%) were the three most frequent tasks in reviewed literature that machine learning methods has been applied to solve. The top three used techniques were artificial neural networks, random forest, and support vector machines models.

Conclusions

The use of knowledge discovery techniques of artificial intelligence techniques has increased exponentially over the years covering numerous sub-topics of pharmacoepidemiology.

Systematic Review Registration

Systematic review registration number in PROSPERO: CRD42019136552.

Regulatory T cells in solid organ transplantation

The induction of graft tolerance remains the holy grail of transplantation. This is important as chronic allograft dysfunction and the side effects of immunosuppression regimens place a major burden on the lives of transplant patients and their healthcare systems. This has mandated the need to understand the immunobiology of graft rejection and identify novel therapeutics. Regulatory T (Treg) cells play an important role in modulating pro‐inflammatory microenvironments and maintaining tissue homeostasis. However, there are fundamental unanswered questions regarding Treg cell immunobiology. These cells are a heterogeneous entity with functionally diverse roles. Moreover, the adoption of novel deeper immunophenotyping and genomic sequencing technologies has identified this phenotype and function to be more complex than expected. Hence, a comprehensive understanding of Treg cell heterogeneity is needed to safely and effectively exploit their therapeutic potential. From a clinical perspective, the recent decade has seen different clinical teams commence and complete first‐in‐man clinical trials utilising Treg cells as an adoptive cellular therapy. In this review, we discuss these trials from a translational perspective with an important focus on safety. Finally, we identify crucial knowledge gaps for future study.

Phenotypic and Transcriptomic Lymphocytes Changes in Allograft Recipients After Intravenous Immunoglobulin Therapy in Kidney Transplant Recipients

High dose intravenous immunoglobulin (IVIG) are widely used after kidney transplantation and its biological effect on T and B cell phenotype in the context of maintenance immunosuppression was not documented yet. We designed a monocentric prospective cohort study of kidney allograft recipients with anti-HLA donor specific antibodies (DSA) without acute rejection on screening biopsies treated with prophylactic high-dose IVIG (2 g/kg) monthly for 2 months. Any previous treatment with Rituximab was an exclusion criterion. We performed an extensive analysis of phenotypic and transcriptomic T and B lymphocytes changes and serum cytokines after treatment (day 60). Twelve kidney transplant recipients who completed at least two courses of high-dose IVIG (2 g/kg) were included in a median time of 45 (12–132) months after transplant. Anti-HLA DSA characteristics were similar before and after treatment. At D60, PBMC population distribution was similar to the day before the first infusion. CD8⁺ CD45RA⁺ T cells and naïve B-cells (Bm2⁺) decreased (P = 0.03 and P = 0.012, respectively) whereas Bm1 (mature B-cells) increased (P = 0.004). RORγt serum mRNA transcription factor and CD3 serum mRNA increased 60 days after IVIG (P = 0.02 for both). Among the 25 cytokines tested, only IL-18 serum concentration significantly decreased at D60 (P = 0.03). In conclusion, high dose IVIG induced limited B cell and T cell phenotype modifications that could lead to anti-HLA DSA decrease. However, no clinical effect has been isolated and the real benefit of prophylactic use of IVIG after kidney transplantation merits to be questioned.

Using the Immunophenotype to Predict Response to Biologic Drugs in Rheumatoid Arthritis

Tumour necrosis factor (TNF)-α is a key mediator of inflammation in rheumatoid arthritis, and its discovery led to the development of highly successful anti-TNF therapy. Subsequently, other biologic drugs targeting immune pathways, namely interleukin-6 blockade, B cell depletion, and T cell co-stimulation blockade, have been developed. Not all patients respond to a biologic drug, leading to a knowledge gap between biologic therapies available and the confident prediction of response. So far, genetic studies have failed to uncover clinically informative biomarkers to predict response. Given that the targets of biologics are immune pathways, immunological study has become all the more pertinent. Furthermore, advances in single-cell technology have enabled the characterization of many leucocyte subsets. Studying the blood immunophenotype may therefore, define biomarker profiles relevant to each individual patient's disease and treatment outcome. This review summarises our current understanding of how immune biomarkers might be able to predict treatment response to biologic drugs.

Circulating B Cells With Memory and Antibody-Secreting Phenotypes Are Detectable in Pediatric Kidney Transplant Recipients Before the Development of Antibody-Mediated Rejection

Development of anti-human leukocyte antigen donor-specific antibodies (DSAs) is associated with antibody-mediated rejection (AMR) and reduced allograft survival in kidney transplant recipients. Whether changes in circulating lymphocytes anticipate DSA or AMR development is unclear.

METHODS

We used time-of-flight mass cytometry to analyze prospectively collected peripheral blood mononuclear cells (PBMC) from pediatric kidney transplant recipients who developed DSA (DSA-positive recipients [DSAPOS], n = 10). PBMC were obtained at 2 months posttransplant, 3 months before DSA development, and at DSA detection. PBMC collected at the same time points posttransplant from recipients who did not develop DSA (DSA-negative recipients [DSANEG], n = 11) were used as controls.

RESULTS

DSAPOS and DSANEG recipients had similar baseline characteristics and comparable frequencies of total B and T cells. Within DSAPOS recipients, there was no difference in DSA levels (mean fluorescence intensity [MFI]: 13 687 ± 4159 vs 11 375 ± 1894 in DSAPOSAMR-positive recipients (AMRPOS) vs DSAPOSAMR-negative recipients (AMRNEG), respectively; P = 0.630), C1q binding (5 DSAPOSAMRPOS [100%] vs 4 DSAPOSAMRNEG [80%]; P = 1.000), or C3d binding (3 DSAPOSAMRPOS [60%] vs 1 DSAPOSAMRNEG [20%]; P = 0.520) between patients who developed AMR and those who did not. However, DSAPOS patients who developed AMR (n = 5; 18.0 ± 3.6 mo post-DSA detection) had increased B cells with antibody-secreting (IgD-CD27+CD38+; P = 0.002) and memory (IgD-CD27+CD38-; P = 0.003) phenotypes compared with DSANEG and DSAPOSAMRNEG recipients at DSA detection.

CONCLUSIONS

Despite the small sample size, our comprehensive phenotypic analyses show that circulating B cells with memory and antibody-secreting phenotypes are present at DSA onset, >1 year before biopsy-proven AMR in pediatric kidney transplant recipients.

Pretransplant transcriptomic signature in peripheral blood predicts early acute rejection

Commonly available clinical parameters fail to predict early acute cellular rejection (EAR, occurring within 6 months after transplant), a major risk factor for graft loss after kidney transplantation. We performed whole-blood RNA sequencing at the time of transplant in 235 kidney transplant recipients enrolled in a prospective cohort study (Genomics of Chronic Allograft Rejection [GoCAR]) and evaluated the relationship of pretransplant transcriptomic profiles with EAR. EAR was associated with downregulation of NK and CD8+ T cell gene signatures in pretransplant blood. We identified a 23-gene set that predicted EAR in the discovery (n = 81, and AUC = 0.80) and validation (n = 74, and AUC = 0.74) sets. Exclusion of recipients with 5 or 6 HLA donor mismatches increased the AUC to 0.89. The risk score derived from the gene set was also significantly associated with acute cellular rejection after 6 months, antibody-mediated rejection and/or de novo donor-specific antibodies, and graft loss in a cohort of 154 patients, combining the validation set and additional GoCAR patients with surveillance biopsies between 6 and 24 months (n = 80) posttransplant. This 23-gene set is a potentially important new tool for determination of the recipient's immunological risk before kidney transplantation, and facilitation of an individualized approach to immunosuppressive therapy.

Current status of alloimmunity

PURPOSE OF REVIEW

The present review aims to highlight the major recent advances in transplantation with regards to basic, translational, and clinical research.

RECENT FINDINGS

We describe new concepts in understanding allorecognition and allospecificity of T cells, and discuss current challenges in targeting memory T cells, including the limitation of rodent disease models. From a clinical perspective, we highlight the advances in molecular biopsy characterization, which have expanded our knowledge of potential drivers of injury and may provide better parameters for patient risk stratification. We also highlight the dual role of innate immunity in both stimulating and regulating adaptive immunity, as well as novel insights into environmental exposures that may affect immune regulation, such as high-salt diet. Finally, we discuss advances in understanding humoral response and novel technologies, such as chimeric antigen receptors-engineered T cells, microparticle-based drug delivery, and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated protein 9 (Cas9) gene editing, that may provide intriguing and promising approaches to restrain alloimmunity.

SUMMARY

Current advances in our understanding of the basic mechanisms of alloimmunity and their potential translation to clinical applications will permit the development of novel diagnostic and therapeutic strategies to improve long-term graft survival.

Applying Mass Cytometry to the Analysis of Lymphoid Populations in Transplantation

Single-cell flow cytometric techniques have been indispensable to improving our understanding of the phenotype and function of immune cell subsets that are important in both rejection and tolerance after transplant. Mass cytometry, or cytometry by time of flight, is a single-cell-based platform that utilizes antibodies conjugated to rare heavy metal ions for analysis of cellular proteins by a time-of-flight mass spectrometer. This new technology allows for the evaluation of >40 simultaneous cellular parameters in a single sample because the limitation of spectral overlap, seen in conventional flow cytometry, is eliminated. In this review, we discuss the current state of mass cytometry, describe the advantages and disadvantages compared with multiparameter flow cytometry, introduce novel methods of high-dimensional data analysis and visualization, and review some recent studies using mass cytometry to profile the immune systems of healthy people and transplant recipients.

Immunotherapy biomarkers 2016: overcoming the barriers

This report summarizes the symposium, 'Immunotherapy Biomarkers 2016: Overcoming the Barriers', which was held on April 1, 2016 at the National Institutes of Health in Bethesda, Maryland. The symposium, cosponsored by the Society for Immunotherapy of Cancer (SITC) and the National Cancer Institute (NCI), focused on emerging immunotherapy biomarkers, new technologies, current hurdles to further progress, and recommendations for advancing the field of biomarker development.

B cell repertoires in HLA-sensitized kidney transplant candidates undergoing desensitization therapy

Background

Kidney transplantation is the most effective treatment for end-stage renal disease. Sensitization refers to pre-existing antibodies against human leukocyte antigen (HLA) protein and remains a major barrier to successful transplantation. Despite implementation of desensitization strategies, many candidates fail to respond. Our objective was to determine whether measuring B cell repertoires could differentiate candidates that respond to desensitization therapy.

Methods

We developed an assay based on high-throughput DNA sequencing of the variable domain of the heavy chain of immunoglobulin genes to measure changes in B cell repertoires in 19 highly HLA-sensitized kidney transplant candidates undergoing desensitization and 7 controls with low to moderate HLA sensitization levels. Responders to desensitization had a decrease of 5% points or greater in cumulated calculated panel reactive antibody (cPRA) levels, and non-responders had no decrease in cPRA.

Results

Dominant B cell clones were not observed in highly sensitized candidates, suggesting that the B cells responsible for sensitization are either not present in peripheral blood or present at comparable levels to other circulating B cells. Candidates that responded to desensitization therapy had pre-treatment repertoires composed of a larger fraction of class-switched (IgG and IgA) isotypes compared to non-responding candidates. After B cell depleting therapy, the proportion of switched isotypes increased and the mutation frequencies of the remaining non-switched isotypes (IgM and IgD) increased in both responders and non-responders, perhaps representing a shift in the repertoire towards memory B cells or plasmablasts. Conversely, after transplantation, non-switched isotypes with fewer mutations increased, suggesting a shift in the repertoire towards naïve B cells.

Conclusions

Relative abundance of different B cell isotypes is strongly perturbed by desensitization therapy and transplantation, potentially reflecting changes in the relative abundance of memory and naïve B cell compartments. Candidates that responded to therapy experienced similar changes to those that did not respond. Further studies are required to understand differences between these two groups of highly sensitized kidney transplant candidates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-017-1118-7) contains supplementary material, which is available to authorized users.