Should IFN-γ, IL-17 and IL-2 be considered predictive biomarkers of acute rejection in liver and kidney transplant? Results of a multicentric study

Millán, Olga; Rafael-Valdivia, L.; Segundo, David San; Boix, Francisco; Castro-Panete, María José; López-Hoyos, Marcos; Muro, Manuel; Valero-Hervás, D.M.; Rimola, Antoni; Navasa, Miguel; Muñoz, Pedro; Miras, M.; Andrés, Amado; Guirado, Lluís; Pascual, Julio; Brunet, Mercè

doi:10.1016/j.clim.2014.07.007

Cited by 60 publications

(42 citation statements)

References 40 publications

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“…40 When the analysis was restricted to CD4 + T cells, the median frequency CD3 + CD4 + producing IL-2 was significantly different between rejectors and nonrejectors only at 15 days posttransplantation. 40 Along the same lines, in a multicenter prospective study 41 of 79 kidney and 63 liver transplant recipients, patients with both liver and kidney disorder with acute rejection showed significantly higher pretransplantation IL-2 production in CD3 + CD8 + CD69 + T cells (cut-off liver: 16.93, sensitivity = 85.71, and specificity = 75; cut-off kidney: 20.05, sensitivity = 46, and specificity = 93.1) but not in CD3 + CD4 + CD69 + T cells. The cut-off values for predicting acute rejection based on the AUC of the ROC curves for % CD3 + CD8 + CD69 + IL-2 + cells in patients with liver and kidney disorder accurately discriminated between rejectors and nonrejectors.…”

Section: Il-2 As a Predictive Biomarker Of Individual Alloreactivity mentioning

confidence: 88%

“…This analysis can be done in 48 hours at a cost of approximately 70€. In our multicenter study, 41 we analyzed cytokine production by flow cytometry using the same SOP and equipment conditions across centers. The median interlaboratory CV was 14.3% (range: 7.3%-24%), and the median intralaboratory CV was 6.7% (range: 5.3%-10.9%).…”

Section: Methods For Ifn-g Measurementmentioning

confidence: 99%

“…40 In line with these findings, the results from a multicenter prospective study in 79 kidney and 63 liver transplant recipients indicate that pre-and post-transplantation analysis of intracellular %CD3 + CD4 + CD69 + IFN-g + and % CD3 + CD8 + CD69 + IFN-g + T cells can help to identify liver and kidney transplant recipients at high risk of acute rejection. 41 Pre-transplantation, those liver and kidney patients who suffer acute rejection first weeks after transplantation showed significantly higher %CD3 + CD4 + CD69 + IFN-g + . The cut-off values based on the AUC of the ROC curves for %CD3 + CD4 + CD69 + IFN-g + (cut-off: 24.07, sensitivity = 71.8, and specificity = 100) and %CD3 + CD8 + CD69 + IFN-g + (cut-off: 40.13, sensitivity = 71.8, and specificity = 100) in patients with liver and kidney disorder (% CD3 + CD4 + CD69 + IFN-g + , cut-off: 28.66, sensitivity = 93.9, and specificity = 100 and %CD3 + CD8 + CD69 + IFN-g + , cutoff: 32.68, sensitivity = 72.7, and specificity = 100) accurately discriminated between rejectors and nonrejectors.…”

Section: Ifn-g As a Predictive Biomarker Of Individual Alloreactivitymentioning

confidence: 99%

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T-Cell Cytokines as Predictive Markers of the Risk of Allograft Rejection

Brunet

López

López-Hoyos

2016

Therapeutic Drug Monitoring

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Over the last decade, several biomarkers and surrogate markers have surfaced as promising predictive markers of risk of rejection in solid organ transplantation. The monitoring of these markers can help to improve graft and recipient care by personalizing immunomodulatory therapies. The complex immune system response against an implanted graft can change during long-term follow-up, and the dynamic balance between effector and regulatory T-cell populations is a crucial factor in antidonor response, risk of rejection, and immunosuppression requirements. Therefore, at any time before and after transplantation, T-effector activity, which is associated with increased production and release of proinflammatory cytokines, can be a surrogate marker of the risk of rejection and need for immunosuppression. In addition, immunosuppressive drugs may have a different effect in each individual patient. The pharmacokinetics and pharmacodynamics of these drugs show high interpatient variability, and pharmacodynamic markers, strongly associated with the specific mechanism of action, can potentially be used to measure individual susceptibility to a specific immunosuppressive agent. The monitoring of a panel of valid biomarkers can improve patient stratification and the selection of immunosuppressive drugs. After transplantation, therapy can be adjusted based on the prediction of rejection episodes (maintained alloreactivity), the prognosis of allograft damage, and the individual's response to the drugs. This review will focus on current data indicating that changes in the T-cell production of the intracellular cytokines interferon-γ and interleukin-2 could be used to predict the risk of rejection and to guide immunosuppressive therapy in transplant recipients.

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Section: Il-2 As a Predictive Biomarker Of Individual Alloreactivity mentioning

confidence: 88%

Section: Methods For Ifn-g Measurementmentioning

confidence: 99%

Section: Ifn-g As a Predictive Biomarker Of Individual Alloreactivitymentioning

confidence: 99%

See 1 more Smart Citation

T-Cell Cytokines as Predictive Markers of the Risk of Allograft Rejection

Brunet

López

López-Hoyos

2016

Therapeutic Drug Monitoring

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“…113 For flow cytometry, a very good example of an effort to standardize a single cell analysis of antigen-specific T-cell cytokine production in such settings as experimental vaccination was published by Maecker et al 114 This approach can be adopted for immune monitoring in transplantation medicine. 90,115 For immune biomarkers in cancer, the Minimal Information about T Cell Assays (MIATA) project was initiated in 2009. 116 Guidelines addressing flow cytometry are also available at the MIATA Web site (http://miataproject.org/).…”

Section: Analytical Methods Harmonization and Standardizationmentioning

confidence: 99%

Analytical Aspects of the Implementation of Biomarkers in Clinical Transplantation

Shipkova

López

Picard

et al. 2016

Therapeutic Drug Monitoring

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In response to the urgent need for new reliable biomarkers to complement the guidance of the immunosuppressive therapy, a huge number of biomarker candidates to be implemented in clinical practice have been introduced to the transplant community. This includes a diverse range of molecules with very different molecular weights, chemical and physical properties, ex vivo stabilities, in vivo kinetic behaviors, and levels of similarity to other molecules, etc. In addition, a large body of different analytical techniques and assay protocols can be used to measure biomarkers. Sometimes, a complex software-based data evaluation is a prerequisite for appropriate interpretation of the results and for their reporting. Although some analytical procedures are of great value for research purposes, they may be too complex for implementation in a clinical setting. Whereas the proof of "fitness for purpose" is appropriate for validation of biomarker assays used in exploratory drug development studies, a higher level of analytical validation must be achieved and eventually advanced analytical performance might be necessary before diagnostic application in transplantation medicine. A high level of consistency of results between laboratories and between methods (if applicable) should be obtained and maintained to make biomarkers effective instruments in support of therapeutic decisions. This overview focuses on preanalytical and analytical aspects to be considered for the implementation of new biomarkers for adjusting immunosuppression in a clinical setting and highlights critical points to be addressed on the way to make them suitable as diagnostic tools. These include but are not limited to appropriate method validation, standardization, education, automation, and commercialization.

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“…Moreover, the higher aTreg frequency before liver transplantation (LT) discriminated among TR as an increased risk of acute rejection in renal TR [6,7], and 2) the intracellular production of IFN-γ and IL-2 cytokine on CD4 and CD8 T-cells as well as IL-17A protein were able to identify liver and kidney patients for high risk of acute rejection at baseline as well as within the first month PT [8].…”

mentioning

confidence: 99%