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Periodic Report Summary 2 - BIOMARGIN (Biomarkers of renal graft injuries in kidney allograft recipients)

Project Context and Objectives:
For patients with end-stage renal disease, transplantation has become the preferred treatment, providing better survival than prolonged dialysis, in both adults and children. In renal allograft recipients, graft survival at one year post-transplantation has improved to more than 95%. However, at 10 years, it is only approximately 65-70%, with no major improvement with regards to the previous decade. Also, although acute rejection (AR) is a major risk factor for the development of chronic allograft nephropathy leading to graft loss, decreases in the incidence of AR in recent years have not translated into improved long-term outcomes. Both immune mechanisms (Tcell mediated and antibody-mediated rejection, de novo or recurrent glomerular disease, etc.) and nonimmune mechanisms (nephrotoxicity of calcineurin inhibitors, accelerated aging, epithelial mesenchymal transition, etc.) contribute to the progression of chronic histological damage and scarring of renal allografts. These injury processes jeopardize graft function and long-term graft survival. As only a subset of patients develop chronic injury and because at present physicians do not have the ability to reverse chronic fibrotic kidney damage, it is essential that the transplant community develops reliable and noninvasive approaches to predict which patients are most likely to develop graft failure, so that appropriate interventions can be instituted before this becomes clinically apparent.

The practical objectives of BIOMARGIN are to:
• Discover, select and validate: (1) blood and/or urine biomarkers, at different omics levels, of renal allograft lesions, with good diagnostic performance as compared to biopsy histological analysis (‘Gold standard’); (2) mechanism-based classifiers of graft lesions, including intra-graft mRNA or miRNA as well as lipid, peptide and protein localization within the graft, to help histological interpretation of the biopsy; and (3) early biomarkers of chronic graft dysfunction and ultimately graft loss, less invasive than graft biopsy and with improved predictive values of longterm outcome.
• Provide clinicians with tools (analytical techniques, interpretation algorithms, a dedicated website) to obtain such information in a timely manner, and promote these innovations towards scientific societies and patient associations.
• Set-up a research environment for further biomarker research in transplantation.
The BIOMARGIN consortium employs an innovative strategy tackling several complementary –omics and mass spectrometry imaging approaches. The biomarker candidates will be selected and integrated using molecular biology, computational biology, statistics and disease progression models.

Project Results:
The objectives of the first 18-months period were mainly to:
(1) Collect, distribute and analyze triplets of blood, urine and kidney biopsy samples from ca. 120 renal transplant patients, with normal biopsy, or histological signs of T-cell mediated rejection (TCMR), Antibody-mediated rejection (AbMR) or Interstitial Fibrosis/Tubular Atrophy (IFTA).
(2) Write the protocol, patient information and consent forms of the BIOMARGIN European Cohort Study (BECS), translate them into the different languages of the Partners’ member state, submit them to the national authorities and national/regional/local ethics committee (as appropriate) and obtain the signatures of the transplant centers members of the consortium to participate in this study.

The plan was to select banked urine, blood and biopsy samples collected as usual practice in the 4 Biobanks participating in the project (APHP Necker #3, KU Leuven #6, MHH #9 and CHU Limoges #13). However, when reviewing the results of the first exchange of test samples for the purpose of quality control, an unexpected disparity of sample collection and preparation conditions was discovered, resulting in a risk for the reliability of analytical results. Then, after a long discussion among the consortium, a SOP was written to harmonize sample collection, preparation and storage. As a consequence, sample collection started late leading to an overall delay of 10 months which has impacted all the work-packages.

In parallel, all the activities planned by CARDINAL SYSTEMS #10 for the clinical trial 3xBIOS2 were finalized:
- Regulatory and ethical application of the case-control & trans-sectional and cohort studies
- Central reading of the first set of preselected biopsy slides
- Anonymization and shipment of the first set of samples from the 4 biobanks to the 8 labs involved
- Development of an electronic Clinical Research File (eCRF)
- Preselection and final selection (after central reading by expert pathologists) of 134 sample triplets (urine, blood, biopsy core) collected in the standardized conditions
- Quality monitoring of the samples and of the clinical research files
- Sample shipment to the 8 laboratories on May 13, 2014

The analytical tasks performed for step 1 of 3xBIOS² study (“training set”) for biomarker discovery are as follows:
- Urine protein and creatinine concentrations were measured in all samples by INSERM #1a
- Untargeted microRNA profiling in blood was completed by INSERM #1c.
- The extracted RNA samples were subsequently sent by INSERM #1c to KU Leuven #6 and mRNA expression analysis is on-going
- Untargeted analyses of microRNA in urine: 119 samples underwent microarray analysis by INSERM #1b (11 were disqualified, as they did not meet the QC criteria). All raw data and QC reports were sent to CEA #4 for statistical analysis
- Untargeted analyses of mRNA in 120 urine samples by INSERM #1c are still on-going (10 samples disqualified after quality check)
- Untargeted analyses of peptides in urine was successfully performed in all samples except one by MOSAIQUES DIAGNOSTICS Gmbh #8 using CE-MS, and in 48 samples by INSERM #1a using MALDI-TOF/TOF. The rest of the analyses, as well as all analyses by NanoLC-ESI-HRMS by VITO #7, are on-going.
- Untargeted analyses of proteins in urine: half of the proteomic analyses were performed by INSERM #1a, using NanoLC and MALDI-TOF/TOF.
- Untargeted analyses of lipids in urine: after method comparison, optimization and validation, UNIVERSITE PARIS DESCARTES #11 analyzed all samples and detected, annotated using an on-line database, and semi-quantified many lipids of different categories in a large range of concentrations.
- Untargeted analyses of metabolic biomarkers in plasma and urine: 3 different GCMS methods were developed. The development of scripts for MS data preprocessing is on-going. Due to missing the initial time-slot, analyses have been postponed to Nov. and Dec. 2014.
- Untargeted analysis of mRNA and miRNA gene expression in biopsy samples: KU Leuven #6 extracted 131 biopsy samples and evaluated RNA quality and concentration. mRNA of 118 good-quality samples was amplified and hybridized onto microarrays. Microarray gene expression profiles were then calculated and normalized. At month 18, the extracted RNA samples were subsequently sent for miRNA expression analysis to APHP Necker #3.
- Mass-spectrometry imaging of renal allograft biopsies: specialized staff training was delivered and reproducible and efficient methods developed and validated, for sample preparation and analysis by MALDI-TOF (lipids, proteins) and TOF-SIMS (lipids).

Data integration and disease prediction modelling:
• The "Prototype “2BIO-DB” biomarker database for data and metadata collection" was built by CEA #4 and sent to INSERM #1a at M12. The database is currently being filled with 120 miRNA biomarkers from the literature by APHP Necker #3. Proteins and mRNAs will follow shortly. In parallel, the database is currently being implemented as an online resource by INSERM #1a. 2BIO-DB will now be appended up to M48 with the new biomarkers discovered during the project.
• A genetic data mining algorithm was applied on a dataset previously published by MOSAIQUES DIAGNOSTICS GMBH #8. At M17, CEA #4 received the first Biomargin datasets, of miRNA and peptidomics in urine. Preliminary univariate and multivariate analyses of both datasets have been performed.
Longitudinal evaluation of the diagnostic and prognostic performance of selected biomarkers:
• The Biomargin ambispective European Cohort Study (BECS) protocol was discussed with, and agreed upon, by all the clinical Partners and presented at the Consortium annual meeting in March 2014 to have a feedback from the other Partners and the Advisory Board. In parallel were written information and consent forms for adult patients, for parents/legal guardians of children and for the children, of different age groups, themselves. Each form was translated into the languages of the clinical Partners, who further corrected them.
• Finally, the protocol and associated consent and information forms were submitted for regulatory approval in France, Germany and Belgium between May and August 2014.
• The enrolment of patients in the BECS study will start after regulatory approvals. However, BECS includes a retrospective part for patients with samples already banked as part of usual clinical care. The pre-screening since month 6 of BIOMARGIN identified approx. 50 such patients who can already be included as soon as approvals are obtained.
• The Clinical Research File for BECS study was finalized in July 2014. The electronic CRF is planned to be released in October 2014.

The Objectives of the 2nd part of the project were mainly to:
6. Collect, distribute and analyze a second and third sets of triplets of blood, urine and kidney biopsy samples, corresponding to steps 2 and 3 of 3×BIOS2.
7. Obtain regulatory approval for the BIOMARGIN European Cohort Study (BECS), enroll 450 adult and 50 pediatric patients and collect urine and blood samples at predefined times post-transplantation, as well as prior to any graft biopsy (together with a biopsy core for biomarker analysis).
8. Measure the expression of mRNA, miRNA, peptides, proteins, lipids and metabolites of the “extended list” in blood (mRNA, miRNA and metabolites), urine (all) and biopsy (mRNA, miRNA, lipids and proteins) of the selection set (step 2) and trans-sectional set (step 3) of the 3×BIOS2 study
9. Set up of quantitative, validated reference techniques for the determination of the candidate biomarkers in the relevant matrices.
10. Propose an extended list of biomarker candidates through pathway analysis; validated methodology and corresponding software tools for biomarker consolidation; predictive models using a restrictive list of biomarkers and clinical covariates

Description of the work performed and main results:
(1) Clinical transfer logistics and management: step 2 followed the same case-control design as step 1, where samples were collected from ca. 120 renal transplant patients, with normal biopsy, or histological signs of T-cell mediated rejection (TCMR), Antibody-mediated rejection (AbMR) or Interstitial Fibrosis/Tubular Atrophy (IFTA). Step 3 is a trans-sectional study where the first consecutive 450 triplets of samples accrued to the consortium’s biobanks after a predefined starting date must be analyzed. All the activities planned by CARDINAL SYSTEMS #10 for the clinical trial 3xBIOS2 were finalized:
• Regulatory and ethical application of the case-control & trans-sectional and cohort studies
• Central reading of the second and third sets of biopsy slides
• Anonymization and shipment of the second and third sets of samples from the 4 biobanks to the 8 labs involved
• Development of an electronic Clinical Research File (eCRF) for the steps 2 and 3 of 3xBIOS2
• Preselection and final selection (after central reading by expert pathologists) of 138 sample triplets (urine, blood, biopsy core) collected in the standardized conditions at step 2 of 3xBIOS2
• Shipment of 458 unselected sample triplets (urine, blood, biopsy core) collected in the standardized conditions at step 3 of 3xBIOS2 (with central reading by expert pathologists in parallel)
• Quality monitoring of the samples and of the clinical research files
• Sample shipment to the 8 laboratories on months 26-27 for step 2 samples and on months 33-35 for step 3 samples
(2) Longitudinal evaluation of the diagnostic and prognostic performance of selected biomarkers:
• BECS regulatory approval was obtained in France, Germany and Belgium between 6 June 2013 and 30 Aug 2013.
• At the end of this second study period, 574 adult patients, but only 15 pediatric patients had been enrolled. Enrolment of children will be pursued, as well sample and clinical data collection in all patients over the third study period.
(3) The analytical tasks performed for step 2 of 3xBIOS² study (“selection set”) for biomarker discovery are as follows:
• Urine protein and creatinine concentrations were measured in all samples by INSERM #1a
• mRNA and microRNA profiling of blood samples : After arrival of step 2 samples on month 26-27, partner #1c extracted the 138 Paxgene® blood tubes selected, verified RNA quality and concentration nanodrop technology and an Agilent 2100 BioAnalyzer. All samples were ready on Month 36 for the quantification of blood mRNA and miRNA biomarker candidates from the extensive list defined in WP7. However, the final assessment of miRNA and mRNA biomarker candidates (extensive list) in samples from the Selection set is only scheduled for Month 40. 458 Paxgene® tubes from the trans-sectional study (step 3) were sent to partner #1c between Month 33 and Month 35. RNAs were purified and their quality was assessed as described on Month 37. Aliquots of RNA samples from both Step2 and Step3 were sent to Partner #6 on Month 37.
• mRNA and microRNA profiling of urine samples: similarly on month 26-27, 138 urine samples were received by partner #1b and 135 by Part #1c; miRNAs and mRNA extraction was competed by Month 28, respectively. miRNAs and mRNAs will be quantified by Month 40. 456 urine samples from the cross-sectional study (step 3) were received by Partner #1c between Month 33 and Month 35. RNA purification of these samples was ongoing on Month 36.
• Untargeted analyses of peptides in urine: Since the evaluation of statistical data of the Training Set (phase I of Biomargin sample analysis) was lagging behind and in order to avoid postponing analysis of the independent Selection Set (phase II of Biomargin sample analysis), it was decided by all WP4 partners at the beginning of the second reporting period that Part 1a (INSERM Limoges) and 7 (VITO) use also untargeted shotgun peptidomics/proteomics instead of switching to their targeted MRM techniques. All partners of WP4 therefore used the full data sets of the Selection Set samples to validate the peptide and protein marker candidates included in the extensive list of phase I that was previously submitted to the EC as Del. 4.1. Untargeted analysis of the Selection Set was accomplished by all WP4 partners and proteomic data sent to partner 4 (CEA) for their data integration and disease prediction modelling steps in WP7. Moreover, each WP4 partner started its own evaluation to identify the most valid peptide/protein biomarkers indicative of the different biopsy-defined renal allograft injuries.
• Untargeted analyses of lipids in urine: because step 2 samples were received before the statistical results of step 1, it was decided like in other WPs, to perform a second untargeted lipidomics analysis on this second series of samples. LC-MS analyses of the 137 urinary extracts were performed in one batch. The complete set of data files was sent to partners 4 (WP7) for statistical analysis on month 33.
• Untargeted analyses of metabolic biomarkers in plasma and urine was performed on urine and plasma samples from the extended list (Step 2) using both gas- and liquid- chromatography mass spectrometry (GCMS and LCMS) by partner 12. Standard operating procedures were used for metabolite extraction, MS analyses and data processing. Separate extraction methods were developed for plasma and urine. All data processing was performed using in-house mass spectral libraries and custom scripts. Multivariate data analyses were performed. The most distinctive metabolic differences were found using GCMS, therefore it was decided that GCMS should be used to analyse plasma and urine samples from the extended list. The result for Urine showed no clear Biomarker candidates, however, for plasma a number of pathways were identified that need further support from the proteomics studies. After validation using proteomics, developing targeted methods for a number of specified biomarker candidates related to the identified pathways will be performed.
• messenger RNA and microRNA profiling of biopsy samples: Allprotect® samples from the Selection set (step 2) were sent to partner #6 on Month 26-27. After arrival of the samples, partner #6 extracted all Allprotect® tubes that were selected for phase 2 of the program (N=137). After extraction, RNA quality and concentration were evaluated using nanodrop technology. All samples were ready on Month 36 for the quantification of biopsy mRNA and miRNA biomarker candidates from the extensive list defined in WP7. The assessment of miRNA and mRNA biomarker candidates (extensive list) in samples from the Selection set is scheduled for Month 40. The 319 Allprotect® samples from the trans-sectional study (Step3) were received by partner #6 between months 33 and 35. RNAs were purified and their quality was assessed as described. Aliquots of RNA samples from Step2 and Step3 will be sent to Partner #1c on Month 37.
• Mass-spectrometry imaging of renal allograft biopsies: During this second reporting period, 10 human kidney biopsies (one control sample, two normal transplant kidneys and 7 rejection samples) were evaluated using ToF-SIMS (Time of Flight-Secondary Ion Mass Spectrometry) and MALDI-TOF/TOF (Matrix Assisted Laser Desorption Ionization- Time of Flight) in parallel. The first provides the localization of elements and lipids, and the second of lipids, peptides and proteins. The data were submitted on Month 36 as Deliverables 6.4 and 6.5, some of which show interesting preliminary findings.

(4) Data integration and disease prediction modelling: Period 2 was mainly devoted to the following tasks: biomarker consolidation and extended list of biomarkers and statistical data integration and restricted list of biomarkers. CEA (Part 4) received the step 1 datasets between July 2014 (M17) and February 2015 (M24) and then performed statistical analyses using the first version of the pipeline mainly developed during the first phase of the project. The first results presented during the annual meeting in Hannover (March 2015) and the discussion with the clinicians showed that it would be better to take into account a mixed phenotype definition of the samples for the statistical analysis, instead of the “diagnosis category” since a proportion of samples exhibited mixed phenotypes. Therefore, a second version of the pipeline was developed and the statistical results for each dataset presented during the statistical analysis Workshop held in Paris in October 2015. Since then, Part 4 has received eight step2 datasets, the statistical analysis were carried out with the same pipeline and comparisons were made between the relevant variables of step1 and step2 in order to generate a restricted list of biomarkers. The statistical analysis on the remaining datasets will be carried out as soon as CEA will receive the datasets from the partners.

Potential Impact:
The final goal is to provide renal transplant clinicians with innovative biomarkers enabling closer, more accurate, more predictive and/or less invasive monitoring of renal transplant patients than serum creatinine or graft biopsies. Such currently unavailable biomarkers will likely improve patient care and will have several positive impacts.
- Diagnostic tools:
The whole purpose of BIOMARGIN is to develop new biomarkers that will enable a closer monitoring of the graft in order to detect acute or chronic injuries earlier, which will translate into a more rapid intervention and hopefully better long-term outcome.
- Improve treatment outcome for transplanted patient:
Early and specific diagnosis of immunological or non-immunological allograft injuries is a major prerequisite for a successful intervention. The earlier therapy can be started, the greater the chances are to stop, or even reverse, the injury process and prevent irreversible scarring of the renal tissue. Based on this, we expect to better conserve renal tissue and function, thus prolonging allograft survival, which is currently limited to approximately 12 years on average. This is particularly important for pediatric patients, who are expected to need several transplantations during their lifetime to avoid prolonged dependence on dialysis.
- Better understanding of the mode of action of existing or potential treatments:
So far, the pathophysiology of progressive loss of allograft function has been poorly understood. There are only a few clearly defined allograft injuries, such as acute T-cell mediated rejection and acute/chronic antibody-mediated rejection, but the underlying causes of graft loss appear to be much more diverse. The use of different ‘omics’ technologies in BIOMARGIN holds the promise of delineating specific molecules and pathways in these processes, of immunological or non-immunological origin, which can serve to define therapeutic targets.
Moreover, biomarkers may bring a new understanding of drug effects on the renal intra-cellular pathways and on biomarker levels that should help transplant clinicians select the best therapeutic option in a given situation and monitor its effects, using biomarkers. In addition, by unravelling signalling pathways involved in graft lesions such as fibrosis, BIOMARGIN should also open new paths for therapeutic interventions.
- Impact on graft outcome, patient survival and quality of life:
Owing to closer monitoring of the graft and faster reaction regarding the adaptation of individual patient treatment, the rates of renal graft function deterioration and of graft loss should be reduced. At the present time, the therapeutic arsenal does not allow for the reversal of chronic antibody-mediated rejection or allograft fibrosis, for instance. This is the reason why biomarkers with a strong predictive value would be important, as the most efficient therapeutic measures nowadays are preventive in nature. The general condition of the patients will improve, resulting in a better quality of life for both the patient and his/her entourage. Also, prolonged graft survival should translate into prolonged patient survival, as patients on dialysis have a shorter life expectancy than transplanted patients. Less kidney allograft recipients will come back on the waiting list for kidney transplantation each year, and consequently this will increase the total number of patients being transplanted and shorten the time patients spend on the waiting list, which in turn will also increase their life expectancy, as recently demonstrated.
In Europe, 50,000 to 100,000 patients have end-stage renal failure. Compared to dialysis treatment, for most patients kidney transplantation is better suited to regain health, quality of life, and the ability to pursue an individual and self-sufficient lifestyle. Approximately 18,000 kidney transplantations are performed annually in Europe. However, this figure is far exceeded by the number of patients on the waiting list for renal transplantation. Improving the success rate of transplantation by prolonging the allograft survival would contribute to have less second or third renal transplantations, hence more new patients transplanted, instead of being dependent on dialysis.
- Socio-Economical Impact:
The BIOMARGIN non-invasive biomarkers will reduce the need for, and the costs related to, graft biopsies. Extended graft survival will also result in less patients returning to dialysis, the cost of which is clearly much higher than the cost of transplant patient medical care, especially years after transplantation. Also, shortening the time patients spend on a waiting list is cost saving. Finally, patients with a functioning graft are much more likely to be able work and to earn their living.
A second important economic impact expected is for the European industry, especially the SME sector, through the commercialization of key-in-hand techniques for biomarker analyses and interpretation.
Finally, the involvement of patient associations (through the external advisory board and active communication actions planned) will help spread the results of this research quicker and to a wider community.

List of Websites:
www.biomargin.eu

Related information

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INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM)
France
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