Array-based methods for diagnosis and prevention of transplant rejection

Intragraft transcriptome level of CXCL9 as biomarker of acute cellular rejection after liver transplantation

BACKGROUND

Liver transplantation has been a life-saving and well-established treatment for acute liver failure and various end-stage liver diseases. However, acute cellular rejection (ACR) is one of the key factors that determine long-term graft function and survival after liver transplantation, and there are still no specific biomarkers available to monitor the alloimmune response. The aim of the present study was to identify molecular biomarkers for ACR in liver allograft.

METHODS

We analyzed the gene expression profile using an oligonucleotide microarray covering 44,000 human probes in 35 liver biopsy samples after living donor liver transplant, which consisted of 13 samples with ACR (ACR group; moderate/mild, 6/7), 13 samples with other dysfunctions (non-ACR group; recurrent hepatitis C / ischemia/reperfusion injury (IRI)/ nonspecific inflammation / small-for-size syndrome, 5/4/3/1), and 9 samples without liver dysfunction (protocol group). We selected 113 informative genes based on microarray results and adopted the network analysis to visualize key modulators in ACR. We selected 6 modulators (CXCL9, GZMB, CCL19, GBP2, LAIR1, and CDC25A) and confirmed the reproducibility in 23 independent biopsy samples and investigated the response to the rejection treatment in sequential samples.

RESULTS

Network analysis revealed the top three subnetworks, which had NF-κB, MAPK, and IFNG as central hubs. Among selected modulators, intragraft expression levels of CXCL9 mRNA was most upregulated and sensitive to alloimmune status.

CONCLUSION

Intragraft CXCL9 mRNA has a functionally important role in T-cell activation in liver allograft and serves as biomarker for ACR.

Understanding the genetic basis for adverse drug effects: the calcineurin inhibitors

The calcineurin inhibitors-cyclosporine and tacrolimus-are the mainstay of immunosuppressive therapy in solid organ transplantation. These drugs produce severe adverse drug effects (ADEs) such as nephrotoxicity, posttransplantation diabetes mellitus, and hypertension. Accumulated evidence suggests that the development of type 2 diabetes, hypertension, and renal failure may be associated with specific DNA genotypes. In this review, the genes involved with the development of these disease processes are compared with those implicated in calcineurin inhibitor-induced ADEs. The renin-angiotensin system genes, cytokine-encoding genes, and plasminogen activator inhibitor type 1 genes have been implicated in calcineurin inhibitor-induced nephrotoxicity, as well as in development of renal failure. A number of genes are implicated in contributing to diabetes, and these include the vitamin D receptor gene, VDR; hepatocyte nuclear factor genes, HNF; transcription factor 7-like 2 gene, TCF7L2; angiotensin-converting enzyme gene, ACE; cytokines; peroxisome proliferator-activated receptor gamma gene, PPARG; and others. Studies have suggested that the VDR, PPARG, HNF1A, and adenosine 5'-triphosphate-binding cassette ABCC8 (which encodes the sulfonylurea receptor) genes are associated with calcineurin inhibitor-induced diabetes. The genes encoding for the angiotensin-converting enzyme, endothelial constitutive nitric oxide synthase, and cytochrome P450 3A isoenzyme have been involved in the development of hypertension and in calcineurin inhibitor-induced hypertension. The genetic study of disease states can be the stepping stones for thoroughly understanding the genetic basis of ADEs. Gene polymorphisms are implicated in the development of diseases and corresponding disease-like ADEs. The disease-associated genes provide candidate genes for exploring ADEs and may provide genomic biomarkers for assessing the risk for developing severe calcineurin inhibitor-related ADEs as well as for developing preventive strategies.

Detection and differentiation of four poultry diseases using asymmetric reverse transcription polymerase chain reaction in combination with oligonucleotide microarrays

Asymmetric reverse transcription polymerase chain reaction (RT-PCR) and microarrays were combined to distinguish 4 viruses, including Avian influenza virus (AIV), Newcastle disease virus (NDV), Infectious bronchitis virus (IBV), and Infectious bursal disease virus (IBDV), and hemagglutinin (HA) subtypes H5, H7, and H9, and neuraminidase (NA) subtypes N1 and N2 of AIV. The AIV matrix protein (M), and HA and NA genes, IBV nucleoprotein (NP) gene, NDV NP gene, and IBDV A fragment gene were cloned into plasmids. These genes were amplified from these positive recombinant plasmids, which included the inserted target genes by PCR. The PCR products were purified and printed on the amino-modified slides as the probes. RNA was extracted from samples and labeled by asymmetric RT-PCR using a cyanine (Cy)3-labeled primers. The labeled complementary (c)DNA was hybridized to the probes immobilized on the glass slides. After hybridization, the microarrays were scanned, and the hybridization pattern agreed perfectly with the known location of each probe. No cross-hybridization could be detected. Results demonstrated that microarray based on asymmetric RT-PCR is an effective way to distinguish AIV, IBV, NDV, and IBDV simultaneously.

In praise of arrays

Microarray technologies have both fascinated and frustrated the transplant community since their introduction roughly a decade ago. Fascination arose from the possibility offered by the technology to gain a profound insight into the cellular response to immunogenic injury and the potential that this genomic signature would be indicative of the biological mechanism by which that stress was induced. Frustrations have arisen primarily from technical factors such as data variance, the requirement for the application of advanced statistical and mathematical analyses, and difficulties associated with actually recognizing signature gene-expression patterns and discerning mechanisms. To aid the understanding of this powerful tool, its versatility, and how it is dramatically changing the molecular approach to biomedical and clinical research, this teaching review describes the technology and its applications, as well as the limitations and evolution of microarrays, in the field of organ transplantation. Finally, it calls upon the attention of the transplant community to integrate into multidisciplinary teams, to take advantage of this technology and its expanding applications in unraveling the complex injury circuits that currently limit transplant survival.

From molecular diagnostics to personalized testing

Gene-based molecular diagnostics is changing the practice of medicine and will continue to do so for the foreseeable future. The major underlying principle of these diagnostic tests is the use of specific nucleic acid sequences as surrogates; amplification of the surrogate markers enables the detection of pathogens or disease-related gene mutations. Gene targets can be amplified by target-, probe- or signal-based methods. Combined use of nucleic acid amplification and enzyme-linked immunosorbent assay with methods such as immuno-polymerase-chain reaction allows us to detect protein at femtogram (10–15 g) levels. A variety of choices are available for the detection of amplified amplicons with the fluorophore-linked nanoparticles as the most sensitive markers. The unique advantages of using covalently-linked nanoparticles include the detection of single molecules, the ability to enrich molecules of interest with unprecedented detection sensitivity (up to zeptogram levels, 10–21 g) and the flexibility of multiple functionalization. Automation appears to be the current trend for high-volume molecular testing of infectious diseases. Molecular profiling of various diseases using genomic or proteomic approaches opens up a molecule wonderland with promise and emergence of new molecular testing that will likely impact the practice of medicine to a greater degree in the future. The future of molecular-based testing and the journey toward personalized testing will be discussed.