The proteogenomic path towards biomarker discovery

Elucidating the nexus between onco-immunology and kidney transplantation: An insight from precision medicine perspective

The interplay of onco-immunology and kidney transplantation heralds a transformative era in medical science. This integration, while promising, presents significant challenges. Chief among these is the dichotomy of immunosuppression-boosting immunity against malignancies while suppressing it for graft survival. Additionally, limited clinical data on novel therapies, genetic variations influencing responses, economic concerns, and the narrow therapeutic window for post-transplant malignancies necessitate strategic addressal. Conversely, opportunities abound, including personalized immune monitoring, targeted therapies, minimized immunosuppression, and improved patient quality of life. Emphasizing collaborative research and interdisciplinary cooperation, the merging of these fields offers the potential for enhanced graft survival and reduced post-transplant malignancy risks. As we harness modern technology and promote patient-centric care, the vision for the future of kidney transplantation becomes increasingly hopeful, paving the way for more personalized and effective treatments. The article aims to elucidate the critical challenge of balancing immunosuppression to simultaneously combat malignancies and ensure graft survival. It addresses the scarcity of clinical data on novel therapies, the impact of genetic variations on treatment responses, and the economic and therapeutic concerns in managing post-transplant malignancies. Furthermore, it explores the opportunities precision medicine offers, such as personalized immune monitoring, targeted therapies, and reduced immunosuppression, which could significantly improve patient outcomes. Highlighting the importance of collaborative research and interdisciplinary efforts, the article seeks to demonstrate the potential for enhanced graft survival and reduced post-transplant malignancy risks. By leveraging modern technology and prioritizing patient-centric care, it envisions a future where kidney transplantation is more personalized and effective, offering hope for advancements in this field.

Peptidomics and proteogenomics: background, challenges and future needs

INTRODUCTION

With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development.

AREAS COVERED

Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date.

EXPERT OPINION

This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

Big Data Proteogenomics lies at the intersection of high-throughput Mass Spectrometry (MS) based proteomics and Next Generation Sequencing based genomics. The combined and integrated analysis of these two high-throughput technologies can help discover novel proteins using genomic, and transcriptomic data. Due to the biological significance of integrated analysis, the recent past has seen an influx of proteogenomic tools that perform various tasks, including mapping proteins to the genomic data, searching experimental MS spectra against a six-frame translation genome database, and automating the process of annotating genome sequences. To date, most of such tools have not focused on scalability issues that are inherent in proteogenomic data analysis where the size of the database is much larger than a typical protein database. These state-of-the-art tools can take more than half a month to process a small-scale dataset of one million spectra against a genome of 3 GB. In this article, we provide an up-to-date review of tools that can analyze proteogenomic datasets, providing a critical analysis of the techniques' relative merits and potential pitfalls. We also point out potential bottlenecks and recommendations that can be incorporated in the future design of these workflows to ensure scalability with the increasing size of proteogenomic data. Lastly, we make a case of how high-performance computing (HPC) solutions may be the best bet to ensure the scalability of future big data proteogenomic data analysis.

Current Challenges and Implications of Proteogenomic Approaches in Prostate Cancer

In the recent past, next-generation sequencing (NGS) approaches have heralded the omics era. With NGS data burgeoning, there arose a need to disseminate the omic data better. Proteogenomics has been vividly used for characterising the functions of candidate genes and is applied in ascertaining various diseased phenotypes, including cancers. However, not much is known about the role and application of proteogenomics, especially Prostate Cancer (PCa). In this review, we outline the need for proteogenomic approaches, their applications and their role in PCa.

Targeted Urine Metabolomics for Monitoring Renal Allograft Injury and Immunosuppression in Pediatric Patients

Despite new advancements in surgical tools and therapies, exposure to immunosuppressive drugs related to non-immune and immune injuries can cause slow deterioration and premature failure of organ transplants. Diagnosis of these injuries by non-invasive urine monitoring would be a significant clinical advancement for patient management, especially in pediatric cohorts. We investigated the metabolomic profiles of biopsy matched urine samples from 310 unique kidney transplant recipients using gas chromatography-mass spectrometry (GC-MS). Focused metabolite panels were identified that could detect biopsy confirmed acute rejection with 92.9% sensitivity and 96.3% specificity (11 metabolites) and could differentiate BK viral nephritis (BKVN) from acute rejection with 88.9% sensitivity and 94.8% specificity (4 metabolites). Overall, targeted metabolomic analyses of biopsy-matched urine samples enabled the generation of refined metabolite panels that non-invasively detect graft injury phenotypes with high confidence. These urine biomarkers can be rapidly assessed for non-invasive diagnosis of specific transplant injuries, opening the window for precision transplant medicine.

Next-Generation Sequencing and MALDI Mass Spectrometry in the Study of Multiresistant Processed Meat Vancomycin-Resistant Enterococci (VRE)

Vancomycin-resistant enterococci (VRE), due to their intrinsic resistance to various commonly used antibiotics and their malleable genome, make the treatment of infections caused by these bacteria less effective. The aims of this work were to characterize isolates of Enterococcus spp. that originated from processed meat, through phenotypic and genotypic techniques, as well as to detect putative antibiotic resistance biomarkers. The 19 VRE identified had high resistance to teicoplanin (89%), tetracycline (94%), and erythromycin (84%) and a low resistance to kanamycin (11%), gentamicin (11%), and streptomycin (5%). Based on a Next-Generation Sequencing NGS technique, most isolates were vanA-positive. The most prevalent resistance genes detected were erm(B) and aac(6')-Ii, conferring resistance to the classes of macrolides and aminoglycosides, respectively. MALDI-TOF mass spectrometry (MS) analysis detected an exclusive peak of the Enterococcus genus at m/z (mass-to-charge-ratio) 4428 ± 3, and a peak at m/z 6048 ± 1 allowed us to distinguish Enterococcus faecium from the other species. Several statistically significant protein masses associated with resistance were detected, such as peaks at m/z 6358.27 and m/z 13237.3 in ciprofloxacin resistance isolates. These results reinforce the relevance of the combined and complementary NGS and MALDI-TOF MS techniques for bacterial characterization.

Putative Protein Biomarkers of Escherichia coli Antibiotic Multiresistance Identified by MALDI Mass Spectrometry

The commensal bacteria Escherichia coli causes several intestinal and extra-intestinal diseases, since it has virulence factors that interfere in important cellular processes. These bacteria also have a great capacity to spread the resistance genes, sometimes to phylogenetically distant bacteria, which poses an additional threat to public health worldwide. Here, we aimed to use the analytical potential of MALDI-TOF mass spectrometry (MS) to characterize E. coli isolates and identify proteins associated closely with antibiotic resistance. Thirty strains of extended-spectrum beta-lactamase producing E. coli were sampled from various animals. The phenotypes of antibiotic resistance were determined according to Clinical and Laboratory Standards Institute (CLSI) methods, and they showed that all bacterial isolates were multi-resistant to trimethoprim-sulfamethoxazole, tetracycline, and ampicillin. To identify peptides characteristic of resistance to particular antibiotics, each strain was grown in the presence or absence of the different antibiotics, and then proteins were extracted from the cells. The protein fingerprints of the samples were determined by MALDI-TOF MS in linear mode over a mass range of 2 to 20 kDa. The spectra obtained were compared by using the ClinProTools bioinformatics software, using three machine learning classification algorithms. A putative species biomarker was also detected at a peak m/z of 4528.00.

Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization

The clinical sampling of urine is noninvasive and unrestricted, whereby huge volumes can be easily obtained. This makes urine a valuable resource for the diagnoses of diseases. Urinary and renal proteomics have resulted in considerable progress in kidney-based disease diagnosis through biomarker discovery and treatment. This review summarizes the bioinformatics tools available for this area of proteomics and the milestones reached using these tools in clinical research. The scant research publications and the even more limited bioinformatic tool options available for urinary and renal proteomics are highlighted in this review. The need for more attention and input from bioinformaticians is highlighted, so that progressive achievements and releases can be made. With just a handful of existing tools for renal and urinary proteomic research available, this review identifies a gap worth targeting by protein chemists and bioinformaticians. The probable causes for the lack of enthusiasm in this area are also speculated upon in this review. This is the first review that consolidates the bioinformatics applications specifically for renal and urinary proteomics.

Optimizing Detection of Kidney Transplant Injury by Assessment of Donor-Derived Cell-Free DNA via Massively Multiplex PCR

Standard noninvasive methods for detecting renal allograft rejection and injury have poor sensitivity and specificity. Plasma donor-derived cell-free DNA (dd-cfDNA) has been reported to accurately detect allograft rejection and injury in transplant recipients and shown to discriminate rejection from stable organ function in kidney transplant recipients. This study used a novel single nucleotide polymorphism (SNP)-based massively multiplexed PCR (mmPCR) methodology to measure dd-cfDNA in various types of renal transplant recipients for the detection of allograft rejection/injury without prior knowledge of donor genotypes. A total of 300 plasma samples (217 biopsy-matched: 38 with active rejection (AR), 72 borderline rejection (BL), 82 with stable allografts (STA), and 25 with other injury (OI)) were collected from 193 unique renal transplant patients; dd- cfDNA was processed by mmPCR targeting 13,392 SNPs. Median dd-cfDNA was significantly higher in samples with biopsy-proven AR (2.3%) versus BL (0.6%), OI (0.7%), and STA (0.4%) (p < 0.0001 all comparisons). The SNP-based dd-cfDNA assay discriminated active from non-rejection status with an area under the curve (AUC) of 0.87, 88.7% sensitivity (95% CI, 77.7⁻99.8%) and 72.6% specificity (95% CI, 65.4⁻79.8%) at a prespecified cutoff (>1% dd-cfDNA). Of 13 patients with AR findings at a routine protocol biopsy six-months post transplantation, 12 (92%) were detected positive by dd-cfDNA. This SNP-based dd-cfDNA assay detected allograft rejection with superior performance compared with the current standard of care. These data support the feasibility of using this assay to detect disease prior to renal failure and optimize patient management in the case of allograft injury.

Characterisation of the circulating acellular proteome of healthy sheep using LC-MS/MS-based proteomics analysis of serum

BACKGROUND

Unlike humans, there is currently no publicly available reference mass spectrometry-based circulating acellular proteome data for sheep, limiting the analysis and interpretation of a range of physiological changes and disease states. The objective of this study was to develop a robust and comprehensive method to characterise the circulating acellular proteome in ovine serum.

METHODS

Serum samples from healthy sheep were subjected to shotgun proteomic analysis using nano liquid chromatography nano electrospray ionisation tandem mass spectrometry (nanoLC-nanoESI-MS/MS) on a quadrupole time-of-flight instrument (TripleTOF® 5600+, SCIEX). Proteins were identified using ProteinPilot™ (SCIEX) and Mascot (Matrix Science) software based on a minimum of two unmodified highly scoring unique peptides per protein at a false discovery rate (FDR) of 1% software by searching a subset of the Universal Protein Resource Knowledgebase (UniProtKB) database (http://www.uniprot.org). PeptideShaker (CompOmics, VIB-UGent) searches were used to validate protein identifications from ProteinPilot™ and Mascot.

RESULTS

ProteinPilot™ and Mascot identified 245 and 379 protein groups (IDs), respectively, and PeptideShaker validated 133 protein IDs from the entire dataset. Since Mascot software is considered the industry standard and identified the most proteins, these were analysed using the Protein ANalysis THrough Evolutionary Relationships (PANTHER) classification tool revealing the association of 349 genes with 127 protein pathway hits. These data are available via ProteomeXchange with identifier PXD004989.

CONCLUSIONS

These results demonstrated for the first time the feasibility of characterising the ovine circulating acellular proteome using nanoLC-nanoESI-MS/MS. This peptide spectral data contributes to a protein library that can be used to identify a wide range of proteins in ovine serum.

Biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics: a systematic review

Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry‐based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta‐analyses guidelines. Twenty‐five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice.

Mining the human urine proteome for monitoring renal transplant injury

The human urinary proteome provides an assessment of kidney injury with specific biomarkers for different kidney injury phenotypes. In an effort to fully map and decipher changes in the urine proteome and peptidome after kidney transplantation, renal allograft biopsy matched urine samples were collected from 396 kidney transplant recipients. Centralized and blinded histology data from paired graft biopsies was used to classify urine samples into diagnostic categories of acute rejection, chronic allograft nephropathy, BK virus nephritis, and stable graft. A total of 245 urine samples were analyzed by liquid chromatography-mass spectrometry using isobaric Tags for Relative and Absolute Quantitation (iTRAQ) reagents. From a group of over 900 proteins identified in transplant injury, a set of 131 peptides were assessed by selected reaction monitoring for their significance in accurately segregating organ injury causation and pathology in an independent cohort of 151 urine samples. Ultimately, a minimal set of 35 proteins were identified for their ability to segregate the 3 major transplant injury clinical groups, comprising the final panel of 11 urinary peptides for acute rejection (93% area under the curve [AUC]), 12 urinary peptides for chronic allograft nephropathy (99% AUC), and 12 urinary peptides for BK virus nephritis (83% AUC). Thus, urinary proteome discovery and targeted validation can identify urine protein panels for rapid and noninvasive differentiation of different causes of kidney transplant injury, without the requirement of an invasive biopsy.

High-dose immunosuppressant alters the immunological status of New Zealand white rabbits following skin transplantation

The aim of this study was to investigate the effect of an immunosuppressant on the immunological status of New Zealand white rabbits after skin grafting, and to evaluate a method for monitoring the immunological status of subjects with skin transplants. The rabbits were randomly divided into allograft rejection, autograft tolerance, nontransplant, allograft low-dose immunosuppressant and allograft high-dose immunosuppressant groups. The rabbits in the low- and high-dose immunosuppressant groups were treated with cyclosporine A intravenously 8 h prior to skin transplantation and once daily following transplantation at doses of 2 and 25 mg/kg, respectively. At 12 days after skin transplantation, the spleens of donor (female) rabbits and recipient (male) rabbits were harvested for the preparation of single-cell suspensions. The splenocytes from recipient and donor rabbits were labeled with 0.3 or 6 µM carboxy fluorescein diacetate succinimidyl ester, respectively, and a mixed cell suspension was prepared. The final preparation was intravenously injected into recipient New Zealand white rabbits. The ratio of the two fluorescently labeled cell populations in the peripheral blood was measured using flow cytometry at 1, 2, 4 and 8 h after the injection, and the cell death rate was calculated. Histological analysis was also performed on samples collected at the time of splenectomy. The cell death rates of the allograft rejection and low-dose immunosuppressant groups reached their highest levels 8 h after the injection of spleen cell suspension. Allogeneic spleen cells from donor male rabbits were almost completely removed within 8 h of injection. The cell death rate increased slowly in the nontransplant, autograft and high-dose immunosuppressant groups without specificity. This study provides a specific method for the in vivo monitoring of the immunological status of patients after skin grafting. This method can quickly and accurately detect the immunological status of recipients following the injection of a mixed splenocyte suspension, thereby indicating the strength of immune rejection by the immune systems of the recipients.

Computational Models for Transplant Biomarker Discovery

Translational medicine offers a rich promise for improved diagnostics and drug discovery for biomedical research in the field of transplantation, where continued unmet diagnostic and therapeutic needs persist. Current advent of genomics and proteomics profiling called "omics" provides new resources to develop novel biomarkers for clinical routine. Establishing such a marker system heavily depends on appropriate applications of computational algorithms and software, which are basically based on mathematical theories and models. Understanding these theories would help to apply appropriate algorithms to ensure biomarker systems successful. Here, we review the key advances in theories and mathematical models relevant to transplant biomarker developments. Advantages and limitations inherent inside these models are discussed. The principles of key -computational approaches for selecting efficiently the best subset of biomarkers from high--dimensional omics data are highlighted. Prediction models are also introduced, and the integration of multi-microarray data is also discussed. Appreciating these key advances would help to accelerate the development of clinically reliable biomarker systems.

Molecular monitoring of alloimmune-mediated injury in kidney transplant patients

PURPOSE OF REVIEW

Rapid progress in molecular technology has allowed development of numerous molecular tools to help the clinician to evaluate graft status in kidney transplant patients. This review highlights recent findings, describing the use of molecular approaches to monitor, diagnose, and predict alloimmune-mediated injury in kidney grafts.

RECENT FINDINGS

Both previously identified and newly discovered molecular markers of immune injury have been studied and validated in large multicenter studies. Recent data indicate that measuring specific gene transcripts in noninvasive samples, such as urine or peripheral blood, can identify the occurrence of acute rejection and differentiate this immune-mediated injury from other causes of graft dysfunction. Serial monitoring of urine in stable renal transplant patients may detect the onset of rejection before development of graft dysfunction. Moreover, combining gene expression analysis with conventional histopathologic assessment of grafts can enhance the accuracy of diagnosis and may also help predict graft outcomes.

SUMMARY

Measuring specific gene transcription in noninvasive clinical samples has the potential to become an important and standard tool to monitor alloimmune-mediated injury in kidney transplant recipients. Prospective studies are ongoing to validate these findings for use of these approaches in clinical settings.

Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

Background

The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic. Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature of transcriptional and translation regulatory mechanisms and the disparities between genomic and proteomic data from the same samples. In this study, we have examined tumor antigens as potential biomarkers for breast cancer using genomics and proteomics data from previously reported laser capture microdissected ER+ tumor samples.

Results

We applied proteogenomic analyses to study the genetic aberrations of 32 tumor antigens determined in the proteomic data. We found that tumor antigens that are aberrantly expressed at the genetic level and expressed at the protein level, are likely involved in perturbing pathways directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found to be perturbed.

Conclusion

Tumor antigens are a group of proteins recognized by the cells of the immune system. Specifically, they are recognized in tumor cells where they are present in larger than usual amounts, or are physiochemically altered to a degree at which they no longer resemble native human proteins. This proteogenomic analysis of 32 tumor antigens suggests that tumor antigens have the potential to be highly specific biomarkers for different cancers.

Recipients with in utero induction of tolerance upregulated MHC class I in the engrafted donor skin

The alterations in MHC class I expression play a crucial step in immune evasion of cancer or virus-infected cells. This study aimed to examine whether tolerized grafts modified MHC class I expression. FVB/N mice were rendered tolerant of C57BL/6 alloantigens by in utero transplantation of C57BL/6 marrows. Postnatally, engrafted donor skins and leukocytes were examined for their MHC expression by quantitative real-time PCR and flow cytometry. Engrafted donor skins upregulated their MHC class I related gene transcripts after short-term (1~2 weeks) or long-term (>1 month) engraftment. This biological phenomenon was simultaneously associated with upregulation of TAP1 gene transcripts, suggesting an important role of TAP1 in the regulation of MHC class I pathway. The surface MHC class I molecules of H-2K^b in engrafted donor leukocytes consistently showed overexpression. Conclusively, the induction of allograft tolerance involved biological modifications of donor transplants. The overexpression of MHC class I within engrafted transplants of tolerant mice might be used as the tolerance biomarkers for identifying a state of graft tolerance.

Laser ionization mass spectrometry in oral squamous cell carcinoma

Biomarker research in oral squamous cell carcinoma (OSCC) aims for screening/early diagnosis and in predicting its recurrence, metastasis and overall prognosis. This article reviews the current molecular perspectives and diagnosis of oral cancer with proteomics using matrix-assisted laser desorption ionization (MALDI) and surface-enhanced laser desorption ionization (SELDI) mass spectrometry (MS). This method shows higher sensitivity, accuracy, reproducibility and ability to handle complex tissues and biological fluid samples. However, the data interpretation tools of contemporary mass spectrometry still warrant further improvement. Based on the data available with laser-based mass spectrometry, biomarkers of OSCC are classified as (i) diagnosis and prognosis, (ii) secretory, (iii) recurrence and metastasis, and (iv) drug targets. Majority of these biomarkers are involved in cell homeostasis and are either physiologic responders or enzymes. Therefore, proteins directly related to tumorigenesis have more diagnostic value. Salivary secretory markers are another group that offers a favourable and easy strategy for non-invasive screening and early diagnosis in oral cancer. Key molecular inter-related pathways in oral carcinogenesis are also intensely researched with software analysis to facilitate targeted drug therapeutics. The review suggested the need for incorporating 'multiple MS or tandem approaches' and focusing on a 'group of biomarkers' instead of single protein entities, for making early diagnosis and treatment for oral cancer a reality.

Elucidating novel serum biomarkers associated with pulmonary tuberculosis treatment

In an unbiased approach to biomarker discovery, we applied a highly multiplexed proteomic technology (SOMAscan, SomaLogic, Inc, Boulder, CO) to understand changes in proteins from paired serum samples at enrollment and after 8 weeks of TB treatment from 39 patients with pulmonary TB from Kampala, Uganda enrolled in the Center for Disease Control and Prevention's Tuberculosis Trials Consortium (TBTC) Study 29. This work represents the first large-scale proteomic analysis employing modified DNA aptamers in a study of active tuberculosis (TB). We identified multiple proteins that exhibit significant expression differences during the intensive phase of TB therapy. There was enrichment for proteins in conserved networks of biological processes and function including antimicrobial defense, tissue healing and remodeling, acute phase response, pattern recognition, protease/anti-proteases, complement and coagulation cascade, apoptosis, immunity and inflammation pathways. Members of cytokine pathways such as interferon-gamma, while present, were not as highly represented as might have been predicted. The top proteins that changed between baseline and 8 weeks of therapy were TSP4, TIMP-2, SEPR, MRC-2, Antithrombin III, SAA, CRP, NPS-PLA2, LEAP-1, and LBP. The novel proteins elucidated in this work may provide new insights for understanding TB disease, its treatment and subsequent healing processes that occur in response to effective therapy.

Proteome-base biomarkers in diabetes mellitus: progress on biofluids' protein profiling using mass spectrometry

The worldwide number of individuals suffering from diabetes mellitus (DM) has been projected to rise from 171 million in 2000 to 366 million in 2030. Identification of specific biomarkers for prediction and monitoring of DM is needed not only for the adequate screening diagnosis but also to assist the design of interventions to prevent or delay progression of this pathology and its attendant complications. Proteomic methods based on MS hold special promise for the identification of novel biomarkers that might form the foundation for new clinical tests, but to date, their contribution has been somehow unfruitful. Indeed, from more than 300 proteins found differently modulated in body fluids from diabetic patients, approximately 50 were validated with other approaches like ELISA or Western blotting and the clinical trials are being initiated to employ biofluids' proteomics (specifically urinary proteomics) in clinical decision. This review provides an overview of MS-based applications in the identification of potential biomarkers for DM, emphasizing the methodological challenges involved.

Protein and peptide biomarkers in organ transplantation

Organ transplantation is the optimal treatment choice for end-stage organ failure in pediatric patients. The ideal maintenance of a transplanted organ requires efficient monitoring tools and an effective individualized post-transplant treatment plan. Currently available post-transplant monitoring options are not ideal because of their invasiveness or their lack of sensitivity and specificity when providing an accurate assessment of transplant injury. Current research on proteins and peptides, including mass spectrometry-based proteomics, can identify novel surrogate protein and peptide biomarkers that can assist in monitoring the graft in order to correctly assess the status of the transplanted organ. In this article, we have critically reviewed current relevant literature to highlight the importance of protein and peptide biomarkers in the field of pediatric organ transplantation, the status of research findings in the field of protein and peptide biomarkers in different organ transplantation and factors that impact and inhibit the progression of protein biomarker discovery in the field of solid-organ transplantation in pediatrics.

Recent advances in biomarker discovery in solid organ transplant by proteomics

The identification and clinical use of more sensitive and specific biomarkers in the field of solid organ transplantation is an urgent need in medicine. Solid organ transplantation has seen improvements in the short-term survival of transplanted organs due to recent advancements in immunosuppressive therapy. However, the currently available methods of allograft monitoring are not optimal. Recent advancements in assaying methods for biomolecules such as genes, mRNA and proteins have helped to identify surrogate biomarkers that can be used to monitor the transplanted organ. These high-throughput 'omic' methods can help researchers to significantly speed up the identification and the validation steps, which are crucial factors for biomarker discovery efforts. Still, the progress towards identifying more sensitive and specific biomarkers remains a great deal slower than expected. In this article, we have evaluated the current status of biomarker discovery using proteomics tools in different solid organ transplants in recent years. This article summarizes recent reports and current status, along with the hurdles in efficient biomarker discovery of protein biomarkers using proteomics approaches. Finally, we will touch upon personalized medicine as a future direction for better management of transplanted organs, and provide what we think could be a recipe for success in this field.

CXCL10: a candidate biomarker in transplantation

Interferon (IFN) γ-induced protein 10 kDa (IP-10) or C-X-C motif chemokine 10 (CXCL10) is a small cytokine belonging to the CXC chemokine family. This family of signaling molecules is known to control several biological functions and to also play pivotal roles in disease initiation and progression. By binding to its specific cognate receptor CXCR3, CXCL10 critically regulates chemotaxis during several immune-inflammatory processes. In particular, this chemokine controls chemotaxis during the inflammatory response resulting from allograft rejection after transplantation. Interestingly, a strong association has been described between CXCL10 production, immune response and the fate of the graft following allotransplantation. Enhanced CXCL10 production has been observed in recipients of transplants of different organs. This enhanced production likely comes from either the graft or the immune cells and is correlated with an increase in the concentration of circulating CXCL10. Because CXCL10 can be easily measured in the serum and plasma from a patient, the detection and quantitation of circulating CXCL10 could be used to reveal a transplant recipient's immune status. The purpose of this review is to examine the critical role of CXCL10 in the pathogenesis of allograft rejection following organ transplantation. This important role highlights the potential utilization of CXCL10 not only as a therapeutic target but also as a biomarker to predict the severity of rejection, to monitor the inflammatory status of organ recipients and, hopefully, to fine-tune patient therapy in transplantation.

The Rice Proteogenomics Database OryzaPG-DB: Development, Expansion, and New Features

Our recently developed rice proteogenomics database (OryzaPG-DB) is the first sustainable resource for rice shotgun-based proteogenomics, providing information on peptides identified in rice protein digested peptides measured by means of liquid chromatography-tandem mass spectrometry (LC-MS/MS), and mapping of the peptides to their genomic origins and the genomic novelty of each peptide. The sequences of the peptides, proteins, cDNAs and genes, and the gene annotations are available for download in FASTA and GFF3 formats, respectively. Further, an annotated visualization of the gene models, corresponding peptides, and genomic novelty is available for each gene, and MS/MS spectra are available for each peptide. In this article, we discuss the utilization of OryzaPG-DB and report on its development, recent content expansions, and newly added features in the current version (OryzaPG-DB v1.1).

Biomarkers: the future

The future application of biomarkers in critical illness will be to select and guide therapy. Specific biomarkers could identify a pathophysiologic perturbation or noxious mediator to counteract or the need to replete a deficient protective protein. Functional genomics could identify patients at risk for illness or at risk for a poor outcome in critical illness. Genetic expression studies could help differentiate patients with sepsis from those with noninfectious inflammation and could also help to monitor illnesses over time. Expressional and functional proteomics could lead to the identification of new biomarkers and organ-specific therapies.

Integrated proteomic and transcriptomic investigation of the acetaminophen toxicity in liver microfluidic biochip

Microfluidic bioartificial organs allow the reproduction of in vivo-like properties such as cell culture in a 3D dynamical micro environment. In this work, we established a method and a protocol for performing a toxicogenomic analysis of HepG2/C3A cultivated in a microfluidic biochip. Transcriptomic and proteomic analyses have shown the induction of the NRF2 pathway and the related drug metabolism pathways when the HepG2/C3A cells were cultivated in the biochip. The induction of those pathways in the biochip enhanced the metabolism of the N-acetyl-p-aminophenol drug (acetaminophen-APAP) when compared to Petri cultures. Thus, we observed 50% growth inhibition of cell proliferation at 1 mM in the biochip, which appeared similar to human plasmatic toxic concentrations reported at 2 mM. The metabolic signature of APAP toxicity in the biochip showed similar biomarkers as those reported in vivo, such as the calcium homeostasis, lipid metabolism and reorganization of the cytoskeleton, at the transcriptome and proteome levels (which was not the case in Petri dishes). These results demonstrate a specific molecular signature for acetaminophen at transcriptomic and proteomic levels closed to situations found in vivo. Interestingly, a common component of the signature of the APAP molecule was identified in Petri and biochip cultures via the perturbations of the DNA replication and cell cycle. These findings provide an important insight into the use of microfluidic biochips as new tools in biomarker research in pharmaceutical drug studies and predictive toxicity investigations.

Identifying biomarkers as diagnostic tools in kidney transplantation

There is a critical need for biomarkers for early diagnosis, treatment response, and surrogate end point and outcome prediction in organ transplantation, leading to a tailored and individualized treatment. Genomic and proteomic platforms have provided multiple promising new biomarkers during the last few years. However, there is still no routine application of any of these markers in clinical transplantation. This article will discuss the existing gap between biomarker discovery and clinical application in the kidney transplant setting. Approaches to implementing biomarker monitoring into clinical practice will also be discussed.

Biomarkers in solid organ transplantation: establishing personalized transplantation medicine

Technological advances in molecular and in silico research have enabled significant progress towards personalized transplantation medicine. It is now possible to conduct comprehensive biomarker development studies of transplant organ pathologies, correlating genomic, transcriptomic and proteomic information from donor and recipient with clinical and histological phenotypes. Translation of these advances to the clinical setting will allow assessment of an individual patient's risk of allograft damage or accommodation. Transplantation biomarkers are needed for active monitoring of immunosuppression, to reduce patient morbidity, and to improve long-term allograft function and life expectancy. Here, we highlight recent pre- and post-transplantation biomarkers of acute and chronic allograft damage or adaptation, focusing on peripheral blood-based methodologies for non-invasive application. We then critically discuss current findings with respect to their future application in routine clinical transplantation medicine. Complement-system-associated SNPs present potential biomarkers that may be used to indicate the baseline risk for allograft damage prior to transplantation. The detection of antibodies against novel, non-HLA, MICA antigens, and the expression of cytokine genes and proteins and cytotoxicity-related genes have been correlated with allograft damage and are potential post-transplantation biomarkers indicating allograft damage at the molecular level, although these do not have clinical relevance yet. Several multi-gene expression-based biomarker panels have been identified that accurately predicted graft accommodation in liver transplant recipients and may be developed into a predictive biomarker assay.

Searching for the noninvasive biomarker holy grail: are urine proteomics the answer?

Recently, biobehavioral nursing scientists have focused their attention on the search for biomarkers or biological signatures to identify patients at risk for various health problems and poor disease outcomes. In response to the national impetus for biomarker discovery, the measurement of biological fluids and tissues has become increasingly sophisticated. Urine proteomics, in particular, may hold great promise for biobehavioral focused nursing scientists for examination of symptom-and syndrome-related research questions. Urine proteins are easily accessible secreted proteins that provide direct and indirect windows into bodily functions. Advances in proteomics and biomarker discovery provide new opportunities to conduct research studies with banked and fresh urine to benefit diagnosis, prognosis, and evaluation of outcomes in various disease populations. This article provides a review of proteomics and a rationale for utilizing urine proteomics in biobehavioral research. It addresses as well some of the challenges involved in data collection and sample preparation.

Profiling the proteome in renal transplantation

Improved monitoring of transplanted solid organs is one of the next crucial steps leading to an increase in both patient and allograft survival. This can be facilitated through one or a set of surrogate biomarker molecules that accurately and precisely indicate the health status of the transplanted organ. Recent developments in the field of high throughput "omic" methods including genomics and proteomics have facilitated robust and comprehensive analysis of genes and proteins. This development has stimulated efforts in the identification of effective and clinically applicable gene and protein biomarkers in solid organ transplantation, including kidney transplantation. Some achievements have been made through proteomics in terms of profiling proteins and identification of potential biomarkers. However, the road to a successful biomarker discovery and its clinical implementation has proved to be challenging, requiring a number of key issues to be addressed. Such issues are: the lack of widely accepted protocols, difficulty in sample processing and transportation and a lack of collaborative efforts to achieve significant sample sizes in clinical studies. In this review using our area of expertise, we describe the current strategies used for proteomic-based biomarker discovery in renal transplantation, discuss inherent issues associated with these efforts and propose better strategies for successful biomarker discovery.

Toward quantitative proteomics of organ substructures: implications for renal physiology

Organs are complex structures that consist of multiple tissues with different levels of gene expression. To achieve comprehensive coverage and accurate quantitation data, organs ideally should be separated into morphologic and/or functional substructures before gene or protein expression analysis. However, because of complex morphology and elaborate isolation protocols, to date this often has been difficult to achieve. Kidneys are organs in which functional and morphologic subdivision is especially important. Each subunit of the kidney, the nephron, consists of more than 10 subsegments with distinct morphologic and functional characteristics. For a full understanding of kidney physiology, global gene and protein expression analyses have to be performed at the level of the nephron subsegments; however, such studies have been extremely rare to date. Here we describe the latest approaches in quantitative high-accuracy mass spectrometry-based proteomics and their application to quantitative proteomics studies of the whole kidney and nephron subsegments, both in human beings and in animal models. We compare these studies with similar studies performed on other organ substructures. We argue that the newest technologies used for preparation, processing, and measurement of small amounts of starting material are finally enabling global and subsegment-specific quantitative measurement of protein levels in the kidney and other organs. These new technologies and approaches are making a decisive impact on our understanding of the (patho)physiological processes at the molecular level.

Proteomic characterization of Her2/neu-overexpressing breast cancer cells

The receptor tyrosine kinase HER2 is an oncogene amplified in invasive breast cancer and its overexpression in mammary epithelial cell lines is a strong determinant of a tumorigenic phenotype. Accordingly, HER2-overexpressing mammary tumors are commonly indicative of a poor prognosis in patients. Several quantitative proteomic studies have employed two-dimensional gel electrophoresis in combination with MS/MS, which provides only limited information about the molecular mechanisms underlying HER2/neu signaling. In the present study, we used a SILAC-based approach to compare the proteomic profile of normal breast epithelial cells with that of Her2/neu-overexpressing mammary epithelial cells, isolated from primary mammary tumors arising in mouse mammary tumor virus-Her2/neu transgenic mice. We identified 23 proteins with relevant annotated functions in breast cancer, showing a substantial differential expression. This included overexpression of creatine kinase, retinol-binding protein 1, thymosin 4 and tumor protein D52, which correlated with the tumorigenic phenotype of Her2-overexpressing cells. The differential expression pattern of two genes, gelsolin and retinol binding protein 1, was further validated in normal and tumor tissues. Finally, an in silico analysis of published cancer microarray data sets revealed a 23-gene signature, which can be used to predict the probability of metastasis-free survival in breast cancer patients.

Differentially expressed RNA from public microarray data identifies serum protein biomarkers for cross-organ transplant rejection and other conditions

Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers.

Protein biomarkers in the blood are urgently needed for the diagnosis of a wide variety of diseases to improve health care. We aim to find a fast and cost-effective strategy to discover diagnostic protein biomarkers. Hundreds of diseases have already been investigated using microarray technology, measuring the mRNA expression of all genes in the disease-damaged tissues. We analyzed biopsy-based microarray data for 41 diseases in the public repository, identified genes with dysregulated mRNA expressions and detectable-protein abundance in the blood, and predicted them as candidate diagnostic protein biomarkers. We found that clinically and preclinically validated diagnostic protein biomarkers were significantly enriched in our predicted protein candidates for 22 diseases. We then measured the concentrations of ten predicted protein biomarkers in the serum samples from 39 renal transplant patients. Three of them were confirmed to be diagnostic of acute rejection after renal transplantation. All three proteins were further confirmed to be diagnostic of acute rejection in 63 cardiac transplant recipients. Our results show that publically available genome-wide gene expression data on disease-damaged tissues can be effectively translated into diagnostic protein biomarkers.

Tumour node metastasis staging of bladder cancer: prognosis versus pitfalls

PURPOSE OF REVIEW

The WHO classification of urothelial cancer in 2004 has made changes based on the insights of molecular genetics, indicating bladder cancer with entities that are genetically stable versus those that are genetically instable. Seen as work in progress, the need of further validation is obvious. Clinical studies based on solid histological diagnosis are as necessary as the definition of more molecular features of bladder cancer.

RECENT FINDINGS

Solid histological diagnosis includes sufficient clinical information and adequate tissue processing. This combined with molecular data will lead to a more clear-cut distinction between benign and malignant and possibly to another change in terminology with higher concordance to other epithelial tumours. Whereas the identification of FGFR3 mutations has led to a better distinction of at least two pathways of urothelial carcinogenesis, additional multiparametric approaches may help improve the still inadequate search for urine and blood markers indicative of bladder cancer and/or its progression. Proteomic profiling, sets of epigenetic markers, and micro RNAs will be given as examples.

SUMMARY

Recent data mainly support the concept of the WHO 2004 classification of bladder cancer. We are optimistic that an even more clear-cut distinction between benign recurring, nonprogressing tumours and more aggressive tumours will enable us to focus and limit chemotherapy.

Update on the clinical pharmacogenomics of organ transplantation

Organ transplantation suffers from a static graft and patient survival rate, and a high incidence of serious adverse drug effects. The pharmacogenomics of organ transplantation has emerged only recently and is complementary to the immunogenetic information that has accumulated over the past decade. Gene polymorphism studies have focused on the genes that interact across the group of immunosuppressants, including ciclosporin, tacrolimus, sirolimus and corticosteroids. The polymorphisms that hold the most potential for use in a drug selection algorithm are in genes CYP3A5, ABCB1, IMPDH1 and IMPDH2, and cytokines and growth factors. Gene-expression arrays have led to gene-expression testing, such as the use of AlloMap((R)) with heart transplant patients. The expanded use of gene-expression assays, proteomics and drug selection algorithms in organ transplantation will progress slowly and may be outpaced by drug test co-development programs for new transplant drugs. In the future, clinical pharmacogenomics will be a routine part of patient care for organ transplant patients.

Deconvoluting the 'omics' for organ transplantation

PURPOSE OF REVIEW

The desire for biomarkers for diagnosis and prognosis of diseases has never been greater. With the availability of genome data and an increased availability of proteome data, the discovery of biomarkers has become increasingly feasible. This article reviews some recent applications of the many evolving 'omic technologies to organ transplantation.

RECENT FINDINGS

With the advancement of many high-throughput 'omic techniques such as genomics, metabolomics, antibiomics, peptidomics, and proteomics, efforts have been made to understand potential mechanisms of specific graft injuries and develop novel biomarkers for acute rejection, chronic rejection, and operational tolerance.

SUMMARY

The translation of potential biomarkers from the laboratory bench to the clinical bedside is not an easy task and will require the concerted effort of the immunologists, molecular biologists, transplantation specialists, geneticists, and experts in bioinformatics. Rigorous prospective validation studies will be needed using large sets of independent patient samples. The appropriate and timely exploitation of evolving 'omic technologies will lay the cornerstone for a new age of translational research for organ transplant monitoring.

The immunological monitoring of kidney and liver transplants in adult and pediatric recipients

Over the last half century, kidney and liver transplantation have been recognized as the treatment of choice for adult and children with end-stage renal or liver failure. Infants present a relative naïve immune system, but they are capable of mounting both cellular and humoral immune responses to the foreign antigens presented by the allograft. Immune monitoring is a way of measuring functional and molecular correlates of immune reactivity which may provide clinically useful information for identifying patients who have an increase risk of acute rejection prior to clinical symptoms or develop transplant tolerance. However, although numerous assays have been shown to predict rejection, to date no assays have been demonstrated to detect or predict transplantation tolerance. This is a summary of the published literature on promising antigen-specific and non-antigen-specific assays used for immunological monitoring in solid organ transplantation. This work also attempts to review their applicability to pediatric transplantation, specifically, pediatric kidney and liver recipients.