Identification of a protein signature in renal allograft rejection

Proteomic analysis investigating kidney transplantation outcomes- a scoping review

BACKGROUND

Kidney transplantation is the optimal treatment option for most patients with end-stage kidney disease given the significantly lower morbidity and mortality rates compared to remaining on dialysis. Rejection and graft failure remain common in transplant recipients with limited improvement in long-term transplant outcomes despite therapeutic advances. There is an unmet need in the development of non-invasive biomarkers that specifically monitor graft function and predict transplant pathologies that affect outcomes. Despite the potential of proteomic investigatory approaches, up to now, no candidate biomarkers of sufficient sensitivity or specificity have translated into clinical use. The aim of this review was to collate and summarise protein findings and protein pathways implicated in the literature to date, and potentially flag putative biomarkers worth validating in independent patient cohorts.

METHODS

This review followed the Joanna Briggs' Institute Methodology for a scoping review. MedlineALL, Embase, Web of Science Core Collection, Scopus and Google Scholar databases were searched from inception until December 2022. Abstract and full text review were undertaken independently by two reviewers. Data was collated using a pre-designed data extraction tool.

RESULTS

One hundred one articles met the inclusion criteria. The majority were single-centre retrospective studies of small sample size. Mass spectrometry was the most used technique to evaluate differentially expressed proteins between diagnostic groups and studies identified various candidate biomarkers such as immune or structural proteins.

DISCUSSION

Putative immune or structural protein candidate biomarkers have been identified using proteomic techniques in multiple sample types including urine, serum and fluid used to perfuse donor kidneys. The most consistent findings implicated proteins associated with tubular dysfunction and immunological regulatory pathways such as leukocyte trafficking. However, clinical translation and adoption of candidate biomarkers is limited, and these will require comprehensive evaluation in larger prospective, multicentre trials.

Rejection markers in kidney transplantation: do new technologies help children?

Recent insights in allorecognition and graft rejection mechanisms revealed a more complex picture than originally considered, involving multiple pathways of both adaptive and innate immune response, supplied by efficient inflammatory synergies. Current pillars of transplant monitoring are serum creatinine, proteinuria, and drug blood levels, which are considered as traditional markers, due to consolidated experience, low cost, and widespread availability. The most diffuse immunological biomarkers are donor-specific antibodies, which are included in routine post-transplant monitoring in many centers, although with some reproducibility issues and interpretation difficulties. Confirmed abnormalities in these traditional biomarkers raise the suspicion for rejection and guide the indication for graft biopsy, which is still considered the gold standard for rejection monitoring. Rapidly evolving new "omic" technologies have led to the identification of several novel biomarkers, which may change the landscape of transplant monitoring should their potential be confirmed. Among them, urinary chemokines and measurement of cell-free DNA of donor origin are perhaps the most promising. However, at the moment, these approaches remain highly expensive and cost-prohibitive in most settings, with limited clinical applicability; approachable costs upon technology investments would speed their integration. In addition, transcriptomics, metabolomics, proteomics, and the study of blood and urinary extracellular vesicles have the potential for early identification of subclinical rejection with high sensitivity and specificity, good reproducibility, and for gaining predictive value in an affordable cost setting. In the near future, information derived from these new biomarkers is expected to integrate traditional tools in routine use, allowing identification of rejection prior to clinical manifestations and timely therapeutic intervention. This review will discuss traditional, novel, and invasive and non-invasive biomarkers, underlining their strengths, limitations, and present or future applications in children.

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.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

Artificial neural network and bioavailability of the immunosuppression drug

PURPOSE OF REVIEW

The success of organ transplant is determined by number of demographic, clinical, immunological and genetic variables. Artificial intelligence tools, such as artificial neural networks (ANNs) or classification and regression trees (CART) can handle multiple independent variables and predict the dependent variables by deducing the complex nonlinear relationships between variables.

RECENT FINDINGS

In the last two decades, several researchers employed these tools to identify donor-recipient matching pairs, to optimize immunosuppressant doses, to predict allograft survival and to minimize adverse drug reactions. These models showed better performance characteristics than the empirical dosing strategies in terms of sensitivity, specificity, overall accuracy, or area under the curve of receiver-operating characteristic curves. The performance of the models was dependent directly on the input variables. Recent studies identified protein biomarkers and pharmacogenetic determinants of immunosuppressants as additional variables that increase the precision in prediction. Accessibility of medical records, proper follow-up of transplant cases, deep understanding of pharmacokinetic and pharmacodynamic pathways of immunosuppressant drugs coupled with genomic and proteomic markers are essential in developing an effective artificial intelligence platform for transplantation.

SUMMARY

Artificial intelligence has a greater clinical utility both in pretransplantation and posttransplantation periods to get favourable clinical outcomes, thus ensuring successful graft survival.

Computational advances of tumor marker selection and sample classification in cancer proteomics

Cancer proteomics has become a powerful technique for characterizing the protein markers driving transformation of malignancy, tracing proteome variation triggered by therapeutics, and discovering the novel targets and drugs for the treatment of oncologic diseases. To facilitate cancer diagnosis/prognosis and accelerate drug target discovery, a variety of methods for tumor marker identification and sample classification have been developed and successfully applied to cancer proteomic studies. This review article describes the most recent advances in those various approaches together with their current applications in cancer-related studies. Firstly, a number of popular feature selection methods are overviewed with objective evaluation on their advantages and disadvantages. Secondly, these methods are grouped into three major classes based on their underlying algorithms. Finally, a variety of sample separation algorithms are discussed. This review provides a comprehensive overview of the advances on tumor maker identification and patients/samples/tissues separations, which could be guidance to the researches in cancer proteomics.

Novel non-invasive biomarkers diagnostic of acute rejection in renal transplant recipients: A systematic review

BACKGROUND AND OBJECTIVES

Acute rejection is a significant complication detrimental to kidney transplant function. Current accepted means of diagnosis is percutaneous renal biopsy, a costly and invasive procedure. There is an urgent need to detect and validate non-invasive biomarkers capable of replacing the biopsy.

DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS

Comprehensive literature searches of Medline, EMBASE and Cochrane Central Register of Controlled Trials databases were performed. Eligible studies were included as per inclusion criteria and assessed for quality using the GRADE quality of evidence tool. Outcomes evaluated included biomarker diagnostic performance, number of patients/samples, mean age and gender ratio, immunosuppression regime, in addition to clinical applications of the biomarker(s) tested. PRISMA guidelines were followed. Where possible, statistical analysis of comparative performance data was performed.

RESULTS

23 studies were included in this review, including 19 adult, 3 paediatric and 1 mixed studies. A total of 2858 participants and 50 candidate non-invasive tests were identified. Sensitivity, specificity and area under the curve performance values ranged 36%-100%, 30%-100% and 0.55-0.98, respectively.

CONCLUSIONS

Although larger, more robust multi-centre validation studies are needed before non-invasive biomarkers can replace the biopsy, numerous candidate tests have demonstrated significant promise for various facets of postoperative management. Suggested uses include: ruling out patients with a low risk of acute rejection to avoid the need for biopsy, non-invasive testing where the biopsy is contraindicated and a prompt diagnosis is needed, and integration into a serial blood monitoring protocol in conjunction with serum creatinine.

Analytical Aspects of the Implementation of Biomarkers in Clinical Transplantation

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.

A LASSO Method to Identify Protein Signature Predicting Post-transplant Renal Graft Survival

Identifying novel biomarkers to predict renal graft survival is important in post-transplant clinical practice. Serum creatinine, currently the most popular surrogate biomarker, offers limited information of the underlying allograft profiles. It is known to perform unsatisfactorily to predict renal function. In this paper, we apply a LASSO machine-learning algorithm in the Cox proportional hazards model to identify promising proteins that are associated with the hazard of allograft loss after renal transplantation, motivated by a clinical pilot study that collected 47 patients receiving renal transplants at the University of Michigan Hospital. We assess the association of 17 proteins previously identified by Cibrik et al. [5] with allograft rejection in our regularized Cox regression analysis, where the LASSO variable selection method is applied to select important proteins that predict the hazard of allograft loss. We also develop a post-selection inference to further investigate the statistical significance of the proteins on the hazard of allograft loss, and conclude that two proteins KIM-1 and VEGF-R2 are important protein markers for risk prediction.

Non-invasive approaches in the diagnosis of acute rejection in kidney transplant recipients, part II: omics analyses of urine and blood samples

Kidney transplantation (KTx) represents the best available treatment for patients with end-stage renal disease. Still, the full benefits of KTx are undermined by acute rejection (AR). The diagnosis of AR ultimately relies on transplant needle biopsy. However, such an invasive procedure is associated with a significant risk of complications and is limited by sampling error and interobserver variability. In the present review, we summarize the current literature about non-invasive approaches for the diagnosis of AR in kidney transplant recipients (KTRs), including in vivo imaging, gene-expression profiling and omics analyses of blood and urine samples. Most imaging techniques, such as contrast-enhanced ultrasound and magnetic resonance, exploit the fact that blood flow is significantly lowered in case of AR-induced inflammation. In addition, AR-associated recruitment of activated leucocytes may be detectable by 18F-fluorodeoxyglucose positron emission tomography. In parallel, urine biomarkers, including CXCL9/CXCL10 or a three-gene signature of CD3ε, CXCL10 and 18S RNA levels, have been identified. None of these approaches has yet been adopted in the clinical follow-up of KTRs, but standardization of analysis procedures may help assess reproducibility and comparative diagnostic yield in large, prospective, multicentre trials.

Proteomics for rejection diagnosis in renal transplant patients: Where are we now?

Rejection is one of the key factors that determine the long-term allograft function and survival in renal transplant patients. Reliable and timely diagnosis is important to treat rejection as early as possible. Allograft biopsies are not suitable for continuous monitoring of rejection. Thus, there is an unmet need for non-invasive methods to diagnose acute and chronic rejection. Proteomics in urine and blood samples has been explored for this purpose in 29 studies conducted since 2003. This review describes the different proteomic approaches and summarizes the results from the studies that examined proteomics for the rejection diagnoses. The potential limitations and open questions in establishing proteomic markers for rejection are discussed, including ongoing trials and future challenges to this topic.

Proteomics in transplantation

Proteomics and biochemical profiling have emerged as exciting and powerful tools in clinical biomarker research. In the field of transplantation, proteomics aims not only at developing noninvasive means for immune monitoring but also to gain mechanistic insights into the pathophysiology of the alloimmune response and hence defining new therapeutic targets. This chapter provides an overview of proteomic biomarker-driven approaches and its underlying concepts and discusses the advantages, clinical implications, challenges, and limitations of this novel modality as it relates to solid organ transplantation.