Genomic analysis of renal allograft dysfunction using cDNA microarrays

Surfing the Big Data Wave: Omics Data Challenges in Transplantation

In both research and care, patients, caregivers, and researchers are facing a leap forward in the quantity of data that are available for analysis and interpretation, marking the daunting "big data era." In the biomedical field, this quantitative shift refers mostly to the -omics that permit measuring and analyzing biological features of the same type as a whole. Omics studies have greatly impacted transplantation research and highlighted their potential to better understand transplant outcomes. Some studies have emphasized the contribution of omics in developing personalized therapies to avoid graft loss. However, integrating omics data remains challenging in terms of analytical processes. These data come from multiple sources. Consequently, they may contain biases and systematic errors that can be mistaken for relevant biological information. Normalization methods and batch effects have been developed to tackle issues related to data quality and homogeneity. In addition, imputation methods handle data missingness. Importantly, the transplantation field represents a unique analytical context as the biological statistical unit is the donor-recipient pair, which brings additional complexity to the omics analyses. Strategies such as combined risk scores between 2 genomes taking into account genetic ancestry are emerging to better understand graft mechanisms and refine biological interpretations. The future omics will be based on integrative biology, considering the analysis of the system as a whole and no longer the study of a single characteristic. In this review, we summarize omics studies advances in transplantation and address the most challenging analytical issues regarding these approaches.

Comparison of Tolerated and Rejected Islet Grafts: A Gene Expression Study

Recently we showed that donor-specific tolerance to MHC-matched islet allografts in diabetic NOD mice could be induced by simultaneous islet and bone marrow transplantation. Mononuclear cell infiltration surrounding the islets was also found in tolerated grafts. In this study, we compared gene expression in the tolerated and rejected islet grafts by using Affymetrix Murine U74A oligonucleotide arrays. To confirm the results of microarray analysis, we performed real-time PCR and RNase protection assay on selected genes. Of over 12,000 genes studied, 57 genes were expressed at consistently higher levels in tolerated islet grafts, and 524 genes in rejected islet grafts. Genes from a variety of functional clusters were found to be different between rejected and tolerated grafts. In the rejected islet grafts, a number of T-cell surface markers and of cytotoxicity-related genes were highly expressed. Also in the rejected grafts, a number of cytokines and chemokines and their receptors were highly expressed. The differential expression of selected genes found by microarray analysis was also confirmed by real-time PCR and RNase protection assay. Our results indicated that gene microarray analysis can help us to detect gene expression differences representative of the biologic mechanisms of tolerance and rejection.

Advances of genomic science and systems biology in renal transplantation: a review

The diagnosis of rejection in kidney transplant patients is based on histologic classification of a graft biopsy. The current “gold standard” is the Banff 97 criteria; however, there are several limitations in classifying rejection based on biopsy samples. First, a biopsy involves an invasive procedure. Second, there is significant variance among blinded pathologists in the interpretation of a biopsy. And third, there is also variance between the histology and the molecular profiles of a biopsy. To increase the positive predictive value of classifiers of rejection, a Banff committee is developing criteria that integrate histologic and molecular data into a unified classifier that could diagnose and prognose rejection. To develop the most appropriate molecular criteria, there have been studies by multiple groups applying omics technologies in attempts to identify biomarkers of rejection. In this review, we discuss studies using genome-wide data sets of the transcriptome and proteome to investigate acute rejection, chronic allograft dysfunction, and tolerance. We also discuss studies which focus on genetic biomarkers in urine and peripheral blood, which will provide clinicians with minimally invasive methods for monitoring transplant patients. We also discuss emerging technologies, including whole-exome sequencing and RNA-Seq and new bioinformatic and systems biology approaches, which should increase the ability to develop both biomarkers and mechanistic understanding of the rejection process.

Transcriptome changes of chronic tubulointerstitial damage in early kidney transplantation

BACKGROUND

Tubulointerstitial damage (TID) is a key feature of chronic kidney transplant failure; however, the associated gene expression changes are poorly defined.

METHODS

This pilot study used RNA from 59 protocol kidney transplant biopsies at implantation, 1, 3, and 12 months (n=18 patients), processed into cDNA and hybridized to 8K human cDNA microarrays. Gene expression was correlated with graft histology categorized by the Banff schema.

RESULTS

Gene and pathway expression were differentially activated according to the time after transplantation. Immune pathway activity peaked at 1 month, fibrotic expression at 3 months, wound healing-remodelling and cell proliferation-repair processes were activated between 3 and 12 months, whereas macrophage-related gene expression occurred late by 12 months. Forty percent of genes and 50% pathways initially activated persisted to 3 months. Biopsies with TID displayed 262 differentially expressed genes (P<0.001, B>2 compared with implantation), dominated by upregulated fibrogenic and immune-related genes reflecting unique immune (10% to 15% of genes) and fibrotic (15% vs. 4% in normal) pathway activation. Profibrotic genes were expressed before interstitial fibrosis was observed by sequential microscopic analysis. Kidneys progressing to TID by 3 months demonstrated 30 unique genes (B>1, P<0.05) versus nonprogressors with 95 genes (B>1, P<0.009). Fourteen of these progressor genes also occurred in the top decile from an independent validation set.

CONCLUSIONS

Allografts display predictable immune and fibrotic gene expression profiles, with patterns of expression gradually varying by time after transplantation. The pathology reflects differential activation of intrinsic pathways. Gene expression predated histologic damage, suggesting its possible use in early diagnostic testing.

Designer genes: Filling the gap in transplantation

Accelerated evolution of the field of functional genomics has been greatly facilitated by high-throughput microarray-based gene function studies, relating to the parallel and serial expression measurements of genomes. Microarray experimentation is being applied for the study of basic research questions, drug target discovery, pharmacology, toxicogenomics, target selectivity, disease biomarker determination, development of prognostic tests, and disease subclass determination. This article will review the current applications of microarray technology in the field of organ transplantation and discuss the potential impact of this technology on transplantation medicine.

Enhanced granulysin mRNA expression in urinary sediment in early and delayed acute renal allograft rejection

BACKGROUND

Acute rejection (aRx) has a major impact on the long-term outcome of renal allografts, and its diagnosis is contingent on the invasive procedure of allograft biopsy. New immunosuppressive protocols have reduced the incidence but have not abolished this problem. Moreover, aRx is now more frequently seen several weeks after transplantation in outpatients. A noninvasive diagnostic test for predicting aRx could improve the management and outcome. The recently described measurement of urinary mRNA expression offers a new noninvasive approach.

METHODS

In this study, the authors monitored the urinary mRNA expression (221 specimens from 26 patients) of various immune molecules by real-time reverse-transcriptase polymerase chain reaction for up to 3 months after kidney transplantation. Most of the patients received anti-interleukin (IL)-2 receptor monoclonal antibody induction and tacrolimus-based maintenance immunosuppression, which resulted in a low incidence of aRx. To verify the "rejection" markers, an additional nine samples of patients with aRx were analyzed.

RESULTS

Granulysin mRNA increase (vs. 95% confidence interval of 159 urine samples from nonrejecting patients) was detected during 11 of 14 aRx episodes, and follow-up studies showed its predictive value for delayed aRx episodes, even weeks before enhanced serum creatinine was observed. Granulysin induction was associated with enhanced regulated on activation normal T-cell expressed and secreted (RANTES) mRNA expression in 8 of 11 samples. Other cytotoxic effector molecules (granzyme B, perforin, FasL), cytokines (tumor necrosis factor-alpha, RANTES, IL-2, IL-10, interferon-gamma, transforming growth factor-beta), CD3, and CCR1 showed less specificity and sensitivity.

CONCLUSIONS

The authors' data illustrate that the noninvasive kinetic mRNA expression measurement of defined markers in urinary cells of renal allograft recipients allows the early noninvasive detection of ongoing aRx.

Quiescent phenotype of tumor-specific CD8+ T cells following immunization

In a human melanoma model of tumor antigen (TA)-based immunization, we tested the functional status of TA-specific CD8+ cytotoxic T lymphocytes. A "quiescent" phenotype lacking direct ex vivo cytotoxic and proliferative potential was identified that was further characterized by comparing its transcriptional profile to that of TA-specific T cells sensitized in vitro by exposure to the same TA and the T-cell growth factor interleukin 2 (IL-2). Quiescent circulating tumor-specific CD8+ T cells were deficient in expression of genes associated with T-cell activation, proliferation, and effector function. This quiescent status may explain the observed lack of correlation between the presence of circulating immunization-induced lymphocytes and tumor regression. In addition, the activation of TA-specific T cells by in vitro antigen recall and IL-2 suggests that a complete effector phenotype might be reinstated in vivo to fulfill the potential of anticancer vaccine protocols.

Arraying the orchestration of allograft pathology

Microarrays, or gene chips, are exciting investigative tools for analyzing expression changes across thousands of genes in concert in tissues and cells of interest. Despite the relatively recent application of microarrays to transplant research, they hold great promise for unraveling the staging of rejection, stratifying patients towards more individualized treatment regimes, and discovering noninvasive biomarkers for monitoring of intragraft events. Bioinformatics tools are being developed to sift through the large data sets generated as "genomic fingerprints" of the underlying biologic pathways. Gene clustering and class prediction tools allow discovery of diagnostic and prognostic molecular signatures of health and disease. Oligonucleotide-based microarrays also have utility in genotyping polymorphic markers. This report reviews the current literature of microarray use in transplantation research, compares currently available array platforms, and discusses future application of this technology to clinical organ transplantation.

Clinical applications of DNA microarray analysis

Microarray technology provides a revolutionary macro-genetic and bioinformatic-rich platform for understanding human diseases. DNA microarrays facilitate the study of complex diseases, enabling several observations simultaneously that can become foundations for newer hypotheses-shifting us towards a non-reductionist approach to biological phenomenon. This appears of particular value for scientific and clinical dissection of tumor pathologies. Despite the tremendous potential presented by microarray technology for the investigation of disease, concrete insights and advances that translate to the clinical setting are only recently beginning to be tapped. Here, we discuss specific examples of how microarray technology is being integrated into our ever-evolving approach to clinical disease. We focus on molecular strategies for (a) disease classification, (b) disease outcome, and (c) disease mechanisms.

Active-specific immunization against melanoma: Is the problem at the receiving end?

The recent progress in tumor immunology is a striking example of the successful application of modern biotechnology to understand the complex phenomenon of immune-mediated cancer rejection. Tumor antigens were identified and successfully utilized in active immunization trials to induce tumor antigen-specific T cells. This achievement has left, however, clinicians and researchers perplexed by the paradoxical observation that immunization-induced T cells can recognize tumor cells in standard assays but cannot induce tumor regression. A closer look at T cell physiology and tumor biology suggests that this observation is not so surprising. Here, we argue that successful immunization is one of several steps required for tumor clearance while more needs to be understood about how T cells localize and are effective within a tumor microenvironment impervious to the execution of their effector function.

ECM homeostasis in renal diseases: a genomic approach

Chronic renal disease is in general histologically accompanied by a vast amount of scar tissue, ie glomerulosclerosis and interstitial fibrosis. Scarring results from excessive accumulation of extracellular matrix (ECM) components, a process driven by a plethora of cytokines and growth factors. Studies in experimental renal disease which target these regulators using gene therapy limit or prevent the development of scarring. This review focuses specifically on the role of transforming growth factor-beta, platelet-derived growth factor, connective tissue growth factor, hepatocyte growth factor, and epidermal growth factor. The results obtained in animal models hold promise for molecular intervention strategies in human renal disease. Microarray technology allows large-scale gene expression profiling in kidney tissue to identify common molecular pathways in a step towards discovery of new drug targets. Molecular techniques are expected to be used for diagnostic and prognostic purposes in nephrological practice to supplement renal biopsy. Several studies already show that molecular techniques might be of use in routine diagnostic practice. Improvement of diagnosis and prediction of outcome in renal patients might lead to more efficient and earlier therapeutic intervention.

Heightened peripheral blood lymphocyte CD69 expression is neither sensitive nor specific as a noninvasive diagnostic test for renal allograft rejection

It has been reported that acute allograft rejection is associated with heightened expression of the peripheral blood lymphocyte (PBL) early activation marker CD69 and that this may serve as a potential biomarker of rejection. This study sought to determine whether PBL CD69 expression correlates with both acute clinical and subclinical renal allograft rejection as well as clinically inapparent cytomegalovirus (CMV) infection. Flow cytometric determination of PBL CD69 expression was performed at the time of clinical and protocol biopsies (n = 131) in 45 renal transplant recipients. Nineteen patients also underwent weekly monitoring of PBL CD69 expression for the initial 15 wk after transplantation. Simultaneous screening for CMV viremia was performed with a semiquantitative PCR assay. No differences were seen in either CD4+ or CD8+ lymphocyte CD69 expression between the biopsy diagnoses. CMV viremia however, independent of rejection, was associated with greater CD69 expression on CD8+ lymphocytes (17.8 +/- 10.4% versus 9.6 +/- 4.8%; P < 0.0001) but not CD4+ lymphocytes. No individuals experienced clinical CMV disease. Weekly monitoring of PBL CD69 expression did not change coincident with the diagnosis of rejection; however, CMV viremia coincided with a substantial rise in the proportion of CD8+69+ lymphocytes in a number of individuals. Thus, PBL CD69 expression is neither sensitive nor specific for the noninvasive diagnosis of renal allograft rejection. Furthermore, clinically inapparent CMV viremia is associated with heightened expression of this activation marker on CD8+ lymphocytes. This latter finding suggests that clinically inapparent CMV viremia may be a potential confounder for biomarkers of rejection that examine peripheral blood lymphocytes.

Gene-expression profiling of the response of peripheral blood mononuclear cells and melanoma metastases to systemic IL-2 administration

BACKGROUND

Interleukin-2 (IL-2) has direct pluripotent effects on cells with immune and inflammatory function. Which of these effects has a critical role in mediating tumor regression remains enigmatic. In this study, we compared early changes in transcriptional profiles of circulating mononuclear cells with those occurring within the microenvironment of melanoma metastases following systemic IL-2 administration.

RESULTS

The results suggest that the immediate effects of IL-2 administration on the tumor microenvironment is transcriptional activation of genes predominantly associated with monocyte cell function; minimal effects were noted on migration, activation and proliferation of T cells. However, production of chemokines and markers of adhesion and migration within few hours of IL-2 administration may be responsible for a secondary recruitment of immune cells to the tumor site later.

CONCLUSIONS

Our results suggest that IL-2 induces inflammation at tumor sites with three predominant secondary effects: activation of antigen-presenting monocytes; massive production of chemoattractants that may recruit other immune cells to the tumor (including MIG and PARC, which are specific for T cells); and activation of cytolytic mechanisms in monocytes (calgranulin, grancalcin) and NK cells (NKG5, NK4).