December 2012 Clinical Laboratory News: Volume 38, Number 12

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December 2012: Volume 38, Number 12


The Case for Biomarkers in Solid Organ Transplantation
When Will Clinically Valuable Tests be Ready?

By Genna Rollins

Since the advent of kidney transplantation in the mid-1950s as a high-risk research procedure, solid organ transplants have become an effective life-saving therapy for patients with established organ failure. An estimated 30,000 patients in the U.S. receive new organs each year, and in the case of kidney transplants—the most common type with the best outcomes—the 1-year patient survival rate is above 90%, and the acute rejection rate less than 20%. Yet transplant surgeons and researchers bemoan the negative statistics simmering just beneath the surface of this otherwise medical success story. About half of transplanted kidneys fail within 10 years, and patients with failed transplants of all types make up a sizable presence on the waiting list for new organs, a vexing challenge given that the number of people in need of organs far exceeds the supply, with more than 100,000 currently on the transplant waiting list. Experts in the field say validated biomarkers are essential to improving long-term patient and graft outcomes.

“Solid organ transplantation is a life-saving intervention across the board, particularly in patients with organ failure where there is no legitimate rescue therapy like hemodialysis. That includes liver, heart, and lung recipients. The surgical techniques, immunosuppressant therapy, and care of patients have improved dramatically in the past 20 years, to the point where we expect most people to survive to five years afterwards where they generally wouldn’t be alive without a transplant,” explained Josh Levitsky, MD, MS, an associate professor of medicine and surgery at the Northwestern University Feinberg School of Medicine in Chicago. “We’re doing very well in terms of keeping people alive and keeping their organs functioning. The issue is, we really haven’t dealt with long-term problems where we see this progression of graft loss over the years and complications from immunotherapy. Biomarkers would really help diagnose or predict these complications at the earliest stages.”

A chorus of experts echoed Levitsky’s view of how vital clinically validated biomarkers will be in changing long-term transplant outcomes. Minnie Sarwal, MD, PhD, a leading transplant researcher whose lab focuses on the molecular and immunologic basis of transplant dysfunction, noted the “urgent” clinical need to develop appropriate biomarkers. “Improved monitoring of transplant of solid organs is, in fact, one of the next crucial steps required to increase both patient and allograph survival,” she said. Sarwal is a professor of pediatrics, immunology, and surgery at Stanford University in Palo Alto, Calif.

The Need for Biomarkers

Biomarkers matter in transplantation because of the imprecision of current methods to identify both acute and chronic rejection, predict the risk of infection and patient prognosis, and manage the potent but life-saving immunosuppressant therapy required for every transplant patient.

Daniel Salomon, MD, explained the long-standing challenge in identifying rejection of transplanted organs, either through invasive biopsies or imperfect blood-based markers, both of which detect problems well into the disease process. “Diagnosis of events in the course of a transplant patient’s life after the transplant hasn’t changed in 30 years. In the case of kidneys, we measure serial serum creatinine, and we’ve grappled with various calculations that arguably refine things a little. But the fact remains that the patient loses about 50 percent of kidney function before we see a rise in this analyte, yet we use a rise in serum creatinine as essentially our primary trigger for initiating any further diagnostics,” he said. “The same is true with biopsies—50 percent or more of the transplanted organ typically is injured before we see decline in function. So in all these transplants—heart, liver, kidney—we’ve found when you biopsy patients who have normal function, you’ll find rejection. All this subclinical rejection was already predicted by the fact that you have to destroy 50 percent of the organ before you see a decline in function. That’s why an early diagnostic for rejection is a pressing medical need in transplantation.” Salomon is professor and program medical director for the Scripps Research Institute’s Center for Organ Transplantation in La Jolla, Calif.

Transplant surgeons also dream of a day when life-long immunosuppressive therapy can be individualized and minimized for each patient. Therapeutic drug monitoring of potent calcineurin inhibitors like cyclosporine and tacrolimus is the standard of care in all transplants, and has boosted graft and patient survival rates. But immunosuppressive therapy still is too blunt an instrument, according to Manikkam Suthanthiran, MD. “Imagine treating a hypertensive patient, for example, by writing a prescription for enalapril based on their weight alone. That’s what we’re doing in transplant. Everybody gets 0.2 mg/kg of tacrolimus, as an example. But we need to personalize this, to titrate the immunosuppressive drugs. If the patient is in a safe zone of immunosuppression the drug level can be reduced. It’s clear that not all patients require the same dosage or level of drug therapy.” Suthanthiran is Stanton Griffis distinguished professor of medicine and a professor of biochemistry and surgery at Cornell Medical College in New York City. In addition, he is the founding chairman of transplantation medicine and chief of nephrology and hypertension at The New York Presbyterian-Weill Cornell Medical Center.

Too Little or Too Much

Michael Oellerich, MD, FRCPath, elaborated on the fine line transplant specialists walk between over- and under-immunosuppression of patients. “There are limitations to therapeutic drug monitoring. It’s very useful to prevent and predict toxicity but less efficient to predict efficacy. This is a problem at a time now when most transplant centers have minimization protocols to lower immunosuppressive therapy, but not so much that the patient develops donor-specific antibodies that damage the donor organ. Almost tolerance is what we’re striving for, but indiscriminately lowering immunosuppression is very dangerous and will not take us anywhere,” he said. “On the other hand, there are important side-effects from over-suppressing patients, including nephrotoxicity, cancer, and cardiovascular and infectious diseases. These secondary complications are now probably more important than acute rejection, which is relatively well under control. So it’s clear that the long-term optimization of the graft depends on optimization of the immunosuppression regimens.” Oellerich is Lower Saxony Distinguished Professor of Clinical Chemistry at Georg-August-University in Göttingen, Germany.

Achieving the paradigm Suthanthiran and Oellerich envision depends on identifying biomarkers that predict how patients will respond to immunosuppressive therapy. This will enable clinicians to establish personalized regimens from the moment of transplantation, rather than fiddling with standard dosages after the fact and in response to clinical changes that only manifest after the rejection process is well underway.

Aside from the positive impact on individual patients, better graft outcomes would have important practical implications for the transplant field, according to Christoph Olbricht, MD, medical director of the clinic for kidney and hypertension diseases at Klinikum Stuttgart in Stuttgart, Germany. “The major problem in most countries is we don’t have enough organs, so we’re always looking for ways to improve long-term outcomes. Some recipients live with good organ function for 20 years, and that should be the standard. I’m convinced we’ll only achieve this with biomarkers. There is no other way,” he said. A look at the transplant statistics demonstrates where the most pressing needs lie (See Table, below).

Transplants by the Number
Number of Transplants Performed in 2009
Kidney Liver Heart Lung Pancreas Intestine
17,682 6,320 2,241 1,690 1,233 180
1-year Survival Rate in 2008
Kidney Liver Heart Lung Pancreas Intestine
Deceased Donor Living
Donor
92 96.5 84.9 88.6 83.1 75.4 72.2
5-year Survival Rate in 2004
70 82.5 67.1 73.1 51.6 48.3 50.5
Rate of Cumulative Incidence of
First-reported Acute Rejection at 3 Years
16.6 14.2 21.9 45.3 49.8 27.2 53.5
Source: Organ Procurement and Transplantation Network and Scientific Registry of Transplant Recipients 2010 Annual Data Report.

Vigorous Efforts, Slow Progress

If the need for better transplant-related biomarkers is so obvious, why isn’t the field further along? It certainly is not for lack of effort. According to one report, there have been upwards of 15,000 studies involving biomarkers in transplantation. Despite this formidable research enterprise, however, so far just two new biomarkers of importance in post-transplant management have crossed the U.S. Food and Drug Administration (FDA) clearance milestone, Immunknow, and AlloMap. The former is a functional immune assay manufactured by Cylex that measures the increase in intracellular adenosine-triphosphate after T-lymphocyte activation. AlloMap is a gene expression test produced by XDx that predicts the absence of acute allograft rejection in heart transplantation. According to experts, neither test has been widely adopted.

Many transplant centers have implemented routine pre-transplant testing of donors and recipients for serum anti-human leukocyte antigen (HLA), based on emerging evidence linking this analyte to significantly worse kidney transplant outcomes. However, this too appears to be an incomplete measure, as even a total donor-recipient match doesn’t seem to fully capture the risk of rejection.

Dealing with Confounders

That so few biomarkers have made the journey from investigational status to regulatory approval and clinical relevancy reflects the complex and incompletely understood mechanisms behind progressive loss of graft function, as well as more mundane but no less daunting validation challenges.

Sarwal cited several confounders in biomarker discovery that have proven challenging for the field. “Treatment choices can introduce bias in certain populations, and this can skew biomarker discovery and the initial discovery set of samples such that when the biomarker is used in a validation set it doesn’t perform as well,” she observed. “The second issue is the problem of not having a true gold standard for classification of different etiologies of graft dysfunction. The biopsy remains our best gold standard, but we know it’s fraught with the issues of sampling bias and bias in readout, with different readouts from different pathologists.” She also pointed to experimental confounders that have contributed to findings not being replicated across studies, such as different sample storage and handling protocols and how data sets generated in different labs on different platforms can be normalized.

The transplant community through collaboration already has responded to issues like inconsistencies in sample handling and storage, data analytics, and small study populations that limit the statistical power and reproducibility of findings. Levitsky, Salomon, and Suthanthiran all are participating in Clinical Trials in Organ Transplantation (CTOT), a cooperative research program funded by the National Institutes of Health aimed at conducting clinical and mechanistic studies that will lead to improved transplant outcomes. Other similar initiatives are underway in Canada—Biomarkers in Transplantation—and in Europe, Reprogramming the Immune System for Establishment of Tolerance. Oellerich’s lab also is involved in multicenter studies in Germany.

Clearing Performance Hurdles

As the hunt for clinically relevant transplant-related biomarkers proceeds, Oellerich emphasized that candidate analytes face high performance hurdles. “It is very important for whatever biomarkers we establish that they must be practical. That means it must be possible preferably to have results on the same day for a reasonable cost. If the test is too complicated, if you have to flip around live cells, for example, or if you have to wait a couple of days for results, transplant physicians won’t be able to react very well. Transplantation already is so complex that this is not practical,” he said. “For this reason, I think it is probably more important in a reliable way to show the clinicians the right direction rather than having the most sophisticated panel that nobody can pay for.”

Salomon also noted the disconnect between cutting-edge technologies being used to source candidate biomarkers and more established methods available in CLIA-certified labs where these tests will be performed in real-world practice. “We’re doing discovery on these newer technologies like deep mRNA sequencing, picking the top five genes and moving them back to older technologies like PCR because diagnostic labs are very comfortable in that space,” he said. “We’re going to see a break with the past in diagnostics soon. Yet that will take another parallel evolution in technology to match what we’re doing right now in discovery with biomarkers.”

The Research Pipeline

Salomon’s lab is using many of the most sophisticated technologies to look for integrated genomic and immunologic signatures in donors and recipients that will predict the best course of post-transplantation treatment. As part of a COTC-sponsored study, Scripps researchers are prospectively monitoring panels of blood, urine, and serum markers in 300 kidney and 300 liver recipients.

Levitsky’s team is exploring both proteomics and genomics. “We’re looking at mRNA arrays and protein panels to see what genes are expressed and translated into proteins that are signs of immune responses, kidney disease, viral infections or other complications,” he explained. Suthanthiran was a pioneer in analyzing mRNA in the urine of kidney recipients, and that continues to be the focus of his research efforts.

Among other lines of investigation, Oellerich was intrigued by a report published in 2011 that rocked the transplant world. This study found that higher levels of cell-free donor DNA circulating in the blood of heart transplant recipients were associated with rejection (PNAS 2011;108:6229–34). “This was so convincing for me that we started about a year ago, in collaboration with Ekkehard Schütz, MD, at Chronix Biomedical, to also establish such methods and we have now in development a test with which we can determine 0.2 percent of one person’s DNA against a second person’s DNA. We will follow this donor-recipient ratio in multicenter studies we’re setting up in transplant patients and see whether this is a useful early marker,” he said.

Candidate Biomarkers in Transplant Monitoring
 
Organ
 
Sample Type
 
Biomarker
Value
Diagnostic
Predictive
Kidney
Urine
 
 
 
 
 
 
 
 
 
 
 
 
Perforin mRNA
X
X
GB mRNA
X
X
CD103 mRNA
X
 
PI-9
X
X
Granulysin mRNA
X
X
IP-10 mRNA
X
 
CSCR3 mRNA
X
 
FOXP3 mRNA
X
 
FasL mRNA
X
 
Urine IP-10 Protein
 
X
TIM-3 mRNA
X
 
IFN-γ mRNA
X
 
NKG2D mRNA
X
X
Kidney
Blood
 
 
 
 
 
 
GB, perforin,
FasL mRNA
X
X
CD40L mRNA
X
 
IL-4, -5, -6, IFN-γ
X
 
HLA-DRA mRNA
X
 
TNF-α mRNA
X
 
IL-8 mRNA
X
 
 
 
Serum
AT1R-AA
X
X
Liver
Blood
 
 
TLR
 
X
C3 gene
 
X
CXCR, CSCL-10, CSCL9
X
X
Lung
Blood
 
 
TLR
X
X
C3 gene
 
X
CXCR, CSCL-10, CSCL9
X
X
Heart
Blood
 
CXCR, CSCL-10, CSCL9
X
X
TIRC7 mRNA
X
 
Serum
Novel non-HLA antigen, PECAM1
X
X
Urine
KIM-1, CTGF
X
 

AT1R-AA, agonistic antibodies against angiotensin type II receptor 1; CD40L, CD40 Ligand; Chemokines, CXCR, CSCL-10, CSCL9; CSCR3, Chemokine receptor CSCR3; CTGF, connective tissue growth factors; FasL, Fas Ligand; FOXP3, Fork-head box transcription factor; GB, Granzyme B; HLA-DRA, Human HLA class II histocompatibility antigen DR alpha; IFN, interferon; IL, interleukin; IP-10, Interferon-inducible Protein-10; KIM-1, Kidney injury molecule 1; NKG2D, natural-killer group 2, member D; PECAM1, platelet endothelial cell adhesion molecule 1; PI-9, Serine Proteinase Inhibitor-9; TIM-3, T-cell immunoglobulin mucin-3; TIRC7, T-cell immune response cDNA7; TLR, Toll-like receptor

Adapted from: Genome Medicine 2011;3:37; Transplantation 2008; 86:192–9; Transplantation 2011;92:1–9.

 
 

A plethora of urine, serum, and blood markers have been proposed for diagnostic and/or prognostic value in different solid organ transplants (see Table, above). Which of these, either individually or as a panel, will rise to prominence is quite an open question. “Are any of them better? Nobody knows, because none have been validated in any prospective noisy real clinical practice study so that one could benchmark anything. What needs to happen first is we go through a period where there are multiple tests involving plasma, blood, proteomics, and gene expression. We need to get them out and validated, and then each has to stand on its own,” explained Salomon. “Then we ask two questions: is one hands down better than the other? Or are they complimentary?”

While experts remain uncertain about which transplant-related biomarkers will demonstrate the most value or in what timeframe any will be ready for clinical use, they were unanimous in believing such tests are coming soon to practice.

For Further Information

  • Anglicheau D, Suthranthiran M. Noninvasive prediction of organ graft rejection and outcome using gene expression patterns. Transplantation 2008;86:192–9.
  • Heidt S, San Segundo D, Shankar S, et al. Peripheral blood sampling for the detection of allograft rejection: Biomarker identification and validation. Transplantation 2011;92:1–9.
  • Roedder S, Vitalone M, Khatri P, et al. Biomarkers in solid organ transplantation: Establishing personalized transplantation medicine. Genome Medicine 2011;3:37.
  • Cravedi P, Heeger PS. Immunologic monitoring in transplantation revisited. Curr Opin Organ Transplant 2012; 17:26–32.
  • Brandhorst G, Oellerich M. Individually tailored immunosuppression: Is there a role for biomarkers? Clin Chem 2011; 57:376–81.
  • Hernandez-Fuentes MP, Lechler RI. A ‘biomarker signature’ for tolerance in transplantation. Nat Rev Nephrol 2010;6:606–13.
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