Proteomic profiling of renal allograft rejection in serum using magnetic bead-based sample fractionation and MALDI-TOF MS. Clin Exp Med. 2010;10:259-268. [PMID: 20376689 DOI: 10.1007/s10238-010-0094-5]

Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection

Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.

Silencing circ-USP1 protects the renal tubular from kidney injury induced by hypoxia via modulating miR-194-5p/DNMT3A axis in acute renal allografts

Recent studies indicate that circular RNAs are involved in dysregulation of kidney injury. Nevertheless, the underlying mechanisms remain largely unclear. Therefore, this study sought to investigate the role of circ-USP1 in the pathogenesis of early renal allografts. Thirty-two male C57BL/6J mice aged between 6 and 8 weeks were divided into the sham and allograft groups. Thereafter, the association between miR-194-5p, circ-USP1 and DNMT3A was confirmed using a combination of bioinformatics and the luciferase reporter gene assay. Additionally, the expression of circ-USP1, miR-194-5p and DNMT3A mRNA was detected through qPCR. Afterwards, the Western blot assay was performed to examine the expression of DNMT3A protein. Finally, the TUNEL assay was conducted to determine the rate of apoptosis in DNMT3A cells. The expression of circ-USP1 increased, while that of miR-194-5p decreased in renal allografts. Additionally, silencing circ-USP1 reduced kidney injuries caused by renal allografts in mice. Moreover, miR-194-5p was a target for circ-USP1, and DNMT3A was a target of miR-194-5p. Finally, it was shown that silencing circ-USP1 reduced DNMT3A expression in the kidney of mice that received renal allografts. Circ-USP1 functions as a competing endogenous RNA for miR-194-5p. This occurs in order to regulate DNMT3A expression in kidney injury induced by hypoxia in acute renal allografts.

Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome

Hypertensive disorders of pregnancy (HDP) is the most common and widely known as serious complication of pregnancy. As this syndrome is a major leading cause of maternal, fetal, and neonatal morbidity/mortality worldwide, many studies have sought to identify candidate molecules as potential disease biomarkers (DBMs) for use in clinical examinations. Accumulating evidence over the past 2 decades that the many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. This review provides the potential utility of peptidomic analysis for monitoring for pathophysiological status in HDP, and presents an overview of current status of peptide quantification technology. Especially, the technical limitations of the methods used for DBM discovery in the blood are discussed.

Novel urinary exosomal biomarkers of acute T cell-mediated rejection in kidney transplant recipients: A cross-sectional study

BACKGROUND

Acute rejection is hazardous to graft survival in kidney transplant recipients (KTRs). We aimed to identify novel biomarkers for early diagnosis of acute T cell-mediated rejection (TCMR) in urinary exosomes of KTRs.

METHODS

Among 458 graft biopsies enrolled in a cross-sectional multicenter study, 22 patients with stable graft function (STA) who had not shown pathologic abnormality and 25 patients who diagnosed biopsy-proven TCMR were analyzed. We performed proteomic analysis using nano-ultra performance liquid chromatography-tandem mass spectrometry (nano-UPLC-MS/MS) to identify candidate biomarkers for early TCMR diagnosis on urinary exosomes. We confirmed the protein levels of each candidate biomarker by western blot analysis.

RESULTS

A total of 169 urinary exosome proteins were identified by nano-UPLC-MS/MS. Forty-six proteins showed increased expression in STA patients, while 17 proteins were increased in TCMR patients. Among them, we selected five proteins as candidate biomarkers for early diagnosis of TCMR according to significance, degree of quantity variance, and information from the ExoCarta database. We confirmed the proteomic expression levels of five candidate biomarkers by western blot analysis in each patient. Of all candidate biomarkers, tetraspanin-1 and hemopexin were significantly higher in TCMR patients (STA:TCMR ratio = 1:1.8, P = 0.009, and 1:3.5, P = 0.046, respectively).

CONCLUSIONS

Tetraspanin-1 and hemopexin were detected in KTR urine and could act as potential diagnostic proteins for TCMR.

Metabolomics Study for Identification of Potential Biomarkers of Long-term Survival in Kidney Transplantation Recipients

BACKGROUND

The recent progress and appropriate use of immunosuppressive drugs have considerably improved the short-term survival in kidney transplantation recipients (KTRs). The development of new strategies to improve long-term survival outcome after kidney transplantation is also becoming important. Although current diagnosis of allograft dysfunction relies on serum creatinine concentration and biopsy, they are nonspecific indicators of allograft function. Therefore, noninvasive, sensitive, and specific biomarkers for the prediction of long-term survival are needed. The aim of this study was to discover potential biomarkers for long-term survival in KTRs through the use of liquid chromatography-tandem mass spectrometry.

METHODS

We used the metabolic approach to explore the change of metabolites in the serum of KTRs. Twenty-four KTRs with long-term good survival (LGS) and 10 KTRs with chronic antibody-mediated rejection (CAMR) were included in this study. After quantile normalization with chromatographic data, multivariate statistical analysis was performed. We attempted to analyze metabolic profiling with LGS and CAMR groups.

RESULTS

The orthogonal partial least-squares discriminant analysis score plot showed a separation between 2 groups in the principal component. In the corresponding loading plot, 344 metabolites responsible for the separation observed in the score plot were identified (variable influence on projection ≥1.0). We then selected 54 metabolites to compare mass with charge by searching a web database, and 11 compounds were identified.

CONCLUSIONS

We found metabolites in serum that differ in LGS and CAMR groups. Further studies are needed to figure out potential metabolomic biomarkers to predict long-term survival in KTRs.

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.

The application of fuzzy statistics and linear discriminant analysis as criteria for optimizing the preparation of plasma for matrix-assisted laser desorption/ionization mass spectrometry peptide profiling

An alternative bioinformatics approach based on fuzzy theory statistics and linear discriminant analysis is proposed for the interpretation of MALDI MS spectra in peptide profiling. When applied, the methodology enables the establishment of a reproducible plasma preparation protocol appropriate for the evaluation of small data sets. The samples were collected from pregnant women affected by gestational diabetes mellitus (GDM), n=18 and control group, n=13. The following pre-treatment sets were tested: pipette tips with C18 stationary phase (ZipTip, Millipore and Omix, Agilent) and magnetic bead-based weak cation exchange chromatography kit (MB WCX, Bruker Daltonics). The spectra were recorded using a MALDI TOF mass spectrometer (UltrafleXtreme, Bruker Daltonics) for a mass range of m/z from 1000 to 10,000. The significant features were selected using the wrapper selection method, and two classification systems were tested: discriminant analysis (DA) and fuzzy inference system (FIS). ClinProTools software was employed to compare the usefulness of the proposed methodology. The study showed that the optimum results for MS spectra were obtained after the use of the ZipTip as pre-treatment method in plasma preparation. Chemometric analysis allowed the differentiation of the GDM group from the control with a high degree of accuracy: 0.7333 (DA) and 0.8065 (FIS).

Biomarker Characterization by MALDI-TOF/MS

Mass spectrometric techniques frequently used in clinical diagnosis, such as gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, ambient ionization mass spectrometry, and matrix-assisted laser desorption ionization/time-of-flight mass spectrometry (MALDI-TOF/MS), are discussed. Due to its ability to rapidly detect large biomolecules in trace amounts, MALDI-TOF/MS is an ideal tool for characterizing disease biomarkers in biologic samples. Clinical applications of MS for the identification and characterization of microorganisms, DNA fragments, tissues, and biofluids are introduced. Approaches for using MALDI-TOF/MS to detect various disease biomarkers including peptides, proteins, and lipids in biological fluids are further discussed. Finally, various sample pretreatment methods which improve the detection efficiency of disease biomarkers are introduced.

Utility of serum peptidome patterns of esophageal squamous cell carcinoma patients for comprehensive treatment

Esophageal cancer (EC) is one of the most common malignant tumors, and the incidence of esophageal squamous cell carcinoma (ESCC) is highest in China. Early diagnosis and effective monitoring are keys to comprehensive treatment and discovering tumor metastases and recurrence in time. The aim of this study was to confirm serum peptidome pattern utility for diagnosis of ESCC, and assessment of operation success, postoperative chemotherapy results, tumor metastasis and recurrence. Serum samples were collected from 61 patients treated with surgery and chemotherapy and 20 healthy individuals. Spectral data generated with weak cationic-exchanger magnetic beads (WCX-MB) and MALDI-TOF MS by a support vector machine (SVM), were used to construct diagnostic models and system training as potential biomarkers. A pattern consisting of 11 protein peaks, separated ESCC (m/z 650.75), operated (m/z 676.61, 786.1, 786.58), postoperative chemotherapy (m/z 622.77, 650.66, 676.46) and tumor metastasis and recurrence (m/z 622.63, 650.56, 690.77, 676.12) from the healthy individuals with a sensitivity of 100.0% and a specificity of 100.0%. These results suggested that MALDI- TOF MS combined with MB separation yields significantly higher sensitivity and specificity for the detection of serum protein in patients with EC patients treated with surgery and chemotherapy.

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.

Proteomics and metabolomics in renal transplantation-quo vadis?

The improvement of long-term transplant organ and patient survival remains a critical challenge following kidney transplantation. Proteomics and biochemical profiling (metabolomics) may allow for the detection of early changes in cell signal transduction regulation and biochemistry with high sensitivity and specificity. Hence, these analytical strategies hold the promise to detect and monitor disease processes and drug effects before histopathological and pathophysiological changes occur. In addition, they will identify enriched populations and enable individualized drug therapy. However, proteomics and metabolomics have not yet lived up to such high expectations. Renal transplant patients are highly complex, making it difficult to establish cause-effect relationships between surrogate markers and disease processes. Appropriate study design, adequate sample handling, storage and processing, quality and reproducibility of bioanalytical multi-analyte assays, data analysis and interpretation, mechanistic verification, and clinical qualification (=establishment of sensitivity and specificity in adequately powered prospective clinical trials) are important factors for the success of molecular marker discovery and development in renal transplantation. However, a newly developed and appropriately qualified molecular marker can only be successful if it is realistic that it can be implemented in a clinical setting. The development of combinatorial markers with supporting software tools is an attractive goal.

Redox proteomics in study of kidney-associated hypertension: new insights to old diseases

SIGNIFICANCE

The kidney helps to maintain low blood pressure in the human body, and impaired kidney function is a common attribute of aging that is often associated with high blood pressure (hypertension). Kidney-related pathologies are important contributors (either directly or indirectly) to overall human mortality. In comparison with other organs, kidney has an unusually wide range of oxidative status, ranging from the well-perfused cortex to near-anoxic medulla.

RECENT ADVANCES

Oxidative stress has been implicated in many kidney pathologies, especially chronic kidney disease, and there is considerable research interest in oxidative stress biomarkers for earlier prediction of disease onset. Proteomics approaches have been taken to study of human kidney tissue, serum/plasma, urine, and animal models of hypertension.

CRITICAL ISSUES

Redox proteomics, in which oxidative post-translational modifications can be identified in protein targets of oxidative or nitrosative stress, has not been very extensively pursued in this set of pathologies.

FUTURE DIRECTIONS

Proteomics studies of kidney and related tissues have relevance to chronic kidney disease, and redox proteomics, in particular, represents an under-exploited toolkit for identification of novel biomarkers in this commonly occurring pathology.

Analysis of the differentially expressed low molecular weight peptides in human serum via an N-terminal isotope labeling technique combining nano-liquid chromatography/matrix-assisted laser desorption/ionization mass spectrometry

RATIONALE

Peptidomics analysis of human serum is challenging due to the low abundance of serum peptides and interference from the complex matrix. This study analyzed the differentially expressed (DE) low molecular weight peptides in human serum integrating a DMPITC-based N-terminal isotope labeling technique with nano-liquid chromatography and matrix-assisted laser desorption/ionization mass spectrometry (nano-LC/MALDI-MS).

METHODS

The workflow introduced a [d(6)]-4,6-dimethoxypyrimidine-2-isothiocyanate (DMPITC)-labeled mixture of aliquots from test samples as the internal standard. The spiked [d(0)]-DMPITC-labeled samples were separated by nano-LC then spotted on the MALDI target. Both quantitative and qualitative studies for serum peptides were achieved based on the isotope-labeled peaks.

RESULTS

The DMPITC labeling technique combined with nano-LC/MALDI-MS not only minimized the errors in peptide quantitation, but also allowed convenient recognition of the labeled peptides due to the 6 Da mass difference. The data showed that the entire research procedure as well as the subsequent data analysis method were effective, reproducible, and sensitive for the analysis of DE serum peptides.

CONCLUSIONS

This study successfully established a research model for DE serum peptides using DMPITC-based N-terminal isotope labeling and nano-LC/MALDI-MS. Application of the DMPITC-based N-terminal labeling technique is expected to provide a promising tool for the investigation of peptides in vivo, especially for the analysis of DE peptides under different biological conditions.

Magnetic beads-based biological mass spectrometry technology for diagnosis of esophageal carcinoma

AIM: To detect specific protein biomarkers for esophageal cancer by comparing serum proteomic spectra between patients with esophageal cancer and healthy individuals.

METHODS: Serum samples were collected from 63 patients with esophageal cancer and 62 healthy individuals, and randomized into model construction group and validation group. WCX kit and matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF-MS) technology were used to detect serum samples from patients with esophageal cancer and healthy individuals. Flex Analysis software was used to analyze protein peaks for significant difference. Mass spectrometry data obtained were analyzed using ClinPro Tools software. The model was then built using ClinproTools2.2 software and evaluated in a blind test for reliability.

RESULTS: Twenty-four differentially expressed proteins in serum were screened by comparing serum protemic spectra between esophageal cancer patients and healthy individuals, including 12 up-regulated proteins and 9 down-regulated ones. Three proteins (654.74, 1 451.48 and 1 866.67 Dr) were obtained for developing a ClinProt model which was able to classify esophageal cancer patients and healthy individuals with a sensitivity of 93.75% (30/32) and a specificity of 90.00% (27/30). In a double blind validation, the ClinProt model yielded a sensitivity of 93.55% (29/31) and a specificity of 90.32% (28/31).

CONCLUSION: MALDI-TOF-MS combined with WCX kit technology allows directly screening differentially expressed serum protein in esophageal cancer, and these protein markers can be used for diagnosis of early esophageal cancer.

Serum peptidome patterns of colorectal cancer based on magnetic bead separation and MALDI-TOF mass spectrometry analysis

Background. Colorectal cancer (CRC) is one of the most common cancers in the world, identification of biomarkers for early detection of CRC represents a relevant target. The present study aims to determine serum peptidome patterns for CRC diagnosis. Methods. The present work focused on serum proteomic analysis of 32 health volunteers and 38 CRC by ClinProt Kit combined with mass spectrometry. This approach allowed the construction of a peptide patterns able to differentiate the studied populations. An independent group of serum (including 33 health volunteers, 34 CRC, 16 colorectal adenoma, 36 esophageal carcinoma, and 31 gastric carcinoma samples) was used to verify the diagnostic and differential diagnostic capability of the peptidome patterns blindly. An immunoassay method was used to determine serum CEA of CRC and controls. Results. A quick classifier algorithm was used to construct the peptidome patterns for identification of CRC from controls. Two of the identified peaks at m/z 741 and 7772 were used to construct peptidome patterns, achieving an accuracy close to 100% (>CEA, P < 0.05). Furthermore, the peptidome patterns could differentiate validation group with high accuracy. Conclusions. These results suggest that the ClinProt Kit combined with mass spectrometry yields significantly higher accuracy for the diagnosis and differential diagnosis of CRC.

Diagnosis of colorectal cancer by MALDI-TOF-MS combined with WCX magnetic beads

AIM: To explore the difference in serum proteomic spectra between patients with colorectal cancer and healthy individuals, and to identify the specific protein biomarkers.

METHODS: Serum samples collected from 67 colorectal cancer patients and 66 healthy individuals were randomized into model construction group and validation group. Magnetic beads-based weak cation exchange (MB-WCX) kit and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) were used to profile serum proteome. Flex analysis software was used to analyze protein peaks for significant difference. A diagnostic model was then built using ClinproTools2.2software and evaluated blindly for reliability.

RESULTS: Thirty-three differentially expressed proteins in serum were screened between colorectal cancer patients and healthy individuals, including 25 up-regulated proteins and 8 down-regulated ones. Five proteins (759, 3316, 4645, 4248, and 2645 Dr) were used for building a ClinProt model which was able to classify colorectal cancer patients and healthy individuals with a sensitivity of 94.12% (32/34) and a specificity of 96.97% (32/33). A double blind validation test showed that the ClinProt model yielded a sensitivity of 93.94 (31/33) and a specificity of 96.97% (32/33).

CONCLUSION: Combination of MALDI-TOF-MS with WCX kit allows to directly screen proteins differentially expressed in the serum of patients with colorectal cancer, and these proteins can be used to diagnose early-stage colorectal cancer.

Serum peptidome patterns for early screening of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in the world. Early diagnosis is critical for guiding the therapeutic management of ESCC. The present study aims to determine serum peptidome patterns for diagnosing ESCC. To identify novel peptidome patterns for diagnosing ESCC, sera from 31 healthy volunteers and 32 ESCC patients were subjected to a comparative proteomic analysis using a ClinProt™ Kit combined with mass spectrometry (MS). This approach enables the determination of peptidome patterns that can differentiate between ESCC sera and sera from healthy volunteers. For further validation, the diagnostic and differential diagnostic capabilities of the peptidome patterns were verified blindly by using an independent group of sera, consisting of sera from 31 ESCC patients, 33 healthy volunteers, 38 colorectal patients, and 36 gastric cancer patients. A Quick Classifier Algorithm was used to construct the peptidome patterns for the identification of ESCC from the control samples. Five of the identified peaks at mass to charge ratios 759, 786, 1,866, 3,316, and 6,634 were used to construct the peptidome patterns with almost 100% accuracy. Furthermore, the peptidome patterns could also differentiate the validation group with high accuracy. These results suggest that the ClinProt™ Kit combined with MS achieves significantly high accuracy for ESCC diagnosis and differential diagnosis.

Serum peptidome patterns of breast cancer based on magnetic bead separation and mass spectrometry analysis

Background

Breast cancer is one of the most common cancers in the world, and the identification of biomarkers for the early detection of breast cancer is a relevant target. The present study aims to determine serum peptidome patterns for screening of breast cancer.

Methods

The present work focused on the serum proteomic analysis of 36 healthy volunteers and 37 breast cancer patients using a ClinProt Kit combined with mass spectrometry (MS). This approach allows the determination of peptidome patterns that are able to differentiate the studied populations. An independent group of sera (36 healthy volunteers and 37 breast cancer patients) was used to verify the diagnostic capabilities of the peptidome patterns blindly. An immunoassay method was used to determine the serum mucin 1 (CA15-3) of validation group samples.

Results

Support Vector Machine (SVM) Algorithm was used to construct the peptidome patterns for the identification of breast cancer from the healthy volunteers. Three of the identified peaks at m/z 698, 720 and 1866 were used to construct the peptidome patterns with 91.78% accuracy. Furthermore, the peptidome patterns could differentiate the validation group achieving a sensitivity of 91.89% (34/37) and a specitivity of 91.67% (33/36) (> CA 15–3, P < 0.05).

Conclusions

These results suggest that the ClinProt Kit combined with MS shows great potentiality for the diagnosis of breast cancer.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1501556838687844

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.

Mass spectrometry-based proteomics in biomedical research: emerging technologies and future strategies

In recent years, the technology and methods widely available for mass spectrometry (MS)-based proteomics have increased in power and potential, allowing the study of protein-level processes occurring in biological systems. Although these methods remain an active area of research, established techniques are already helping answer biological questions. Here, this recent evolution of MS-based proteomics and its applications are reviewed, including standard methods for protein and peptide separation, biochemical fractionation, quantitation, targeted MS approaches such as selected reaction monitoring, data analysis and bioinformatics. Recent research in many of these areas reveals that proteomics has moved beyond simply cataloguing proteins in biological systems and is finally living up to its initial potential – as an essential tool to aid related disciplines, notably health research. From here, there is great potential for MS-based proteomics to move beyond basic research, into clinical research and diagnostics.