ProteinChip technology reveals distinctive protein expression profiles in the urine of bladder cancer patients

Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis

In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Perceptron) alongside commonly used methods, such as Deep Learning Convolutional Neural Networks, for the urinary bladder cancer detection. The dataset used for this research consisted of 1997 images of bladder cancer and 986 images of non-cancer tissue. The results of the conducted research showed that using Multi-Layer Perceptron trained and tested with images pre-processed with Laplacian edge detector are achieving AUC value up to 0.99. When different image sizes are compared it can be seen that the best results are achieved if 50×50 and 100×100 images were used.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed.

SIGNIFICANCE

Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases.

Establishment and characterization of a highly immunogenic human renal carcinoma cell line

Renal cell carcinoma (RCC) is the most common kidney cancer, and accounts for ~3% of all adult malignancies. RCC has proven refractory to conventional treatment modalities but appears to be the only histological form that shows any consistent response to immunotherapeutic approaches. The development of a clinically effective vaccine remains a major strategic target for devising active specific immunotherapy in RCC. We aimed to identify a highly immunogenic antigenic format for immunotherapeutic approaches, so as to boost immune responses in RCC patients. We established and cloned an immunogenic cell line, RCC85#21 named Elthem, which was derived from a non-aggressive and non-metastatic clear cell carcinoma. The cell line characterization was performed by genomics (real-time PCR, genome instability), proteomics (two dimensional electrophoresis, mass spectro-metry) and immunological analysis (mixed lymphocytes tumor cell cultures). Real-time PCR confirmed the RCC85#21 cell expression of tumor antigens and cytokine genes. No difference in microsatellite instability (MSI) in RCC85#21 cell line was found as compared to control, loss of heterozygosity was observed in the RCC85#21 clone, but not in the renal cancer cell lines from which it was generated. The image analysis of RCC85#21 by two-dimensional gels showed 700±26 spots and 119 spots were identified by mass spectrometry analysis. RCC85#21 promoted a significant RCC-specific T cells activation by exhibiting a cytotoxic phenotype after mixed lymphocyte and tumor cell cultures. CD8+ T cells isolated from RCC patients displayed an elevated reactivity against RCC85#21 and efficiently lysed the RCC85#21 clone. The RCC85#21 immunogenic cell line will be suitable for immune stimulation. The identification of novel tumor associated antigens will allow the evaluation of the immune response in vitro and, subsequently, in vivo paving the way for new immunotherapeutic strategies in the RCC setting.

Detection of bladder cancer using proteomic profiling of urine sediments

We used protein expression profiles to develop a classification rule for the detection and prognostic assessment of bladder cancer in voided urine samples. Using the Ciphergen PBS II ProteinChip Reader, we analyzed the protein profiles of 18 pairs of samples of bladder tumor and adjacent urothelium tissue, a training set of 85 voided urine samples (32 controls and 53 bladder cancer), and a blinded testing set of 68 voided urine samples (33 controls and 35 bladder cancer). Using t-tests, we identified 473 peaks showing significant differential expression across different categories of paired bladder tumor and adjacent urothelial samples compared to normal urothelium. Then the intensities of those 473 peaks were examined in a training set of voided urine samples. Using this approach, we identified 41 protein peaks that were differentially expressed in both sets of samples. The expression pattern of the 41 protein peaks was used to classify the voided urine samples as malignant or benign. This approach yielded a sensitivity and specificity of 59% and 90%, respectively, on the training set and 80% and 100%, respectively, on the testing set. The proteomic classification rule performed with similar accuracy in low- and high-grade bladder carcinomas. In addition, we used hierarchical clustering with all 473 protein peaks on 65 benign voided urine samples, 88 samples from patients with clinically evident bladder cancer, and 127 samples from patients with a history of bladder cancer to classify the samples into Cluster A or B. The tumors in Cluster B were characterized by clinically aggressive behavior with significantly shorter metastasis-free and disease-specific survival.

Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications

To date, multiple biomarker discovery studies in urine have been conducted. Nevertheless, the rate of progression of these biomarkers to qualification and even more clinical application is extremely low. The scope of this article is to provide an overview of main clinically relevant proteomic findings from urine focusing on kidney diseases, bladder and prostate cancers. In addition, approaches for promoting the use of urine in clinical proteomics including potential means to facilitate the validation of existing promising findings (biomarker candidates identified from previous studies) and to increase the chances for success for the identification of new biomarkers are discussed.

Serum proteomic analysis of hereditary nonpolyposis colorectal cancer

AIM: To identify differentially expressed serum proteins between preoperative patients with hereditary nonpolyposis colorectal cancer (HNPCC) and those with sporadic colorectal cancer to find potential markers for the diagnosis of HNPCC.

METHODS: The composition of serum proteins was detected by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and protein chip assay in 20 preoperative HNPCC patients and 25 patients with sporadic colorectal cancer. Discriminatory serum protein profiles were analyzed with the Biomarker Wizard software and Biomarker Pattern software.

RESULTS: Two proteins (m/z 7 516.68 Da and 4 827.07 Da) were chosen to create a decision classification tree model which could discriminate the two groups of patients. In the test mode, the accuracy, sensitivity, specificity, and positive predictive value of the model for prediction of HNPCC was 86.7%, 72.3%, 95.1% and 92.5%, respectively, while the corresponding values for blinded validation were 75.6%, 100%, 69.8% and 99.2%, respectively.

CONCLUSION: The classification tree model constructed with two differentially expressed proteins identified by SELDI-TOF-MS between HNPCC patients and patients with sporadic colorectal cancer possesses high sensitivity and specificity in the prediction of HNPCC.

Methods for the discovery of low-abundance biomarkers for urinary bladder cancer in biological fluids

For the study of bladder cancer and the identification of respective tumor markers, blood and, in particular, urine constitute suitable sources of biological material, while both harboring their specific challenges for analytics concerning low-abundance biomarkers. Dissolved proteins and nucleic acids as well as cells and cell-bound molecules can be the analytes. In urine, exfoliated bladder tumor cells have to be identified and in blood, circulating tumor cells have to be detected among huge amounts of other cells. For the detection of both low-abundance cells and molecules, their specific enrichment prior to analysis is advantageous or even necessary. Adapted methods for the analysis of proteomes and subproteomes by 2D-gel electrophoresis, multidimensional chromatography and antibody arrays are discussed. Analysis of nucleic acid-based markers exploits the high amplification power of PCR and modified PCR combined with previous (subtransciptomes) or subsequent (microarray) enrichment to sensitively and specifically detect markers. DNA mutations, DNA-methylation status and apoptotic DNA fragments, as well as levels of ribonucleic acids including microRNAs, can be analyzed by means of these methods. Finally, the challenge of identifying circulating tumor cells and assigning them to their original tissue is critically discussed.

Urinary proteomics: ready for prime time in urological cancer diagnostics?

The impact of clinical proteomics on the diagnosis and treatment of urological malignancies is modest in comparison with the high expectations of the past. However, most available studies suffer from flawed clinical designs rather than from technical limitations. This article will briefly introduce the main technological approaches taken, their advantages and disadvantages and will highlight the different challenges associated with urinary proteome analysis. Furthermore, several examples of the successful application of urinary clinical proteomics in the field of prostate and bladder cancer will be introduced. These examples suggest careful validation of novel biomarkers, appropriate study designs using blinded cohorts enrolled from appropriate target populations and the standardization of techniques as key elements required for successful urinary proteomics studies. These prerequisites are essential for turning the old promise of a personalized medicine approach into a new reality to optimize patients’ preventive and therapeutic care.

Urinary proteomics--a tool for biomarker discovery

The strong need for the discovery of novel disease markers together with the development of high-throughput techniques that provide highly sensitive analysis of protein content in tissues and bodily fluids, using proteomics, has opened the completely new chapter in biomarker discovery. The detection of biomarkers based on urinary proteome analysis is rapidly advancing and may provide new tools to improve non-invasive diagnostics, prognostics, and therapy enhancement. As a tool for biomarker discovery, urinary proteomics is especially fruitful in the area of early diagnostics and differentiation of renal damage, and it possesses enormous potential for improving and expanding non-invasive cancer diagnostics. An abundance of urinary proteins could provide a wide variety of biomarkers for the diagnosis and follow-up of many systemic diseases as well. This article reviews the utility of urinary proteomics for biomarker discovery from the perspective of clinical application. Despite huge potential and prompt development of urinary proteomics, many challenges are still in front of us. Research effort and financial investment have to be oriented on providing strategies for exceeding current methodological and technical obstacles in a way to ensure the successful validation and implementation of newly discovered urinary biomarkers. The result is expected to be the development of new non-invasive tests and procedures able to guarantee higher efficiency of patient care and provide needed personalized medical approach.

[Research progress in SELDI-TOF MS and its clinical applications]

Proteinchip profiling is a powerful and innovative proteomic technology for the discovery of biomarkers and the development of diagnostic/prognostic assays. On the basis of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), Ciphergen’s proteinchip system offers a single, unified, and high throughput platform for a multitude of proteomic research applications. Proteins are the major functional components of the cell. The study of proteomics helps to better understand the mechanism of a disease. Remarkable findings in disease biomarkers have shed light on the early diagnosis, monitoring, and prognosis of various diseases, especially for cancer. In this paper, the development and technology of SELDI-TOF MS are introduced. The research progress and encouraging research results in malignancies, infectious diseases, neurological diseases, and diabetes mellitus using SELDI-TOF MS are reviewed. This paper concludes by evaluating the pros and cons, and the future perspectives are also expounded.

Urinary proteomic profiling for diagnostic bladder cancer biomarkers

The ability to detect and monitor bladder cancer in noninvasively obtained urine samples is a major goal. While a number of protein biomarkers have been identified and commercially developed, none have greatly improved the accuracy of sample evaluation over invasive cystoscopy. The ongoing development of high-throughput proteomic profiling technologies will facilitate the identification of molecular signatures that are associated with bladder disease. The appropriate use of these approaches has the potential to provide efficient biomarkers for the early detection and monitoring of recurrent bladder cancer. Identification of disease-associated proteins will also advance our knowledge of tumor biology, which, in turn, will enable development of targeted therapeutics aimed at reducing morbidity from bladder cancer. In this article, we focus on the accumulating proteomic signatures of urine in health and disease, and discuss expected future developments in this field of research.

Combined use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and empirical proteomic ontology knowledge base for identification of serum biomarkers for colorectal cancer

AIM: To determine the feasibility of combined use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and empirical proteomic ontology knowledge base (EPO-KB) for identification of serum biomarkers for colorectal cancer.

METHODS: Serum samples from 169 colorectal cancer patients and 83 age- and gender-matched healthy individuals were analyzed by SELDI-TOF-MS using immobilized metal affinity capture 30 (IMAC30) proteinchip arrays. The resulting SELDI-TOF-MS spectral data were analyzed using the Biomarker WizardTM and Biomarker Patterns™ software to find differential proteins and develop a classification tree for colorectal cancer. The differential proteins were identified by searching the EPO-KB and verified by enzyme-linked immunosorbent assay (ELISA).

RESULTS: A total of 34 mass peaks were identified. Four peaks at mass:charge ratios (m/z) of 2873, 3163, 6121 and 7778 were used to construct the classification tree. The classification tree could effectively distinguish colorectal cancer samples from control samples, achieving a sensitivity and specificity of 91.57% and 90.53% in training mode, and 82.25% and 80.72% in test mode, respectively. Database search revealed that the peak at a m/z of 7778 corresponded to platelet factor 4 (PF4). ELISA detection of PF4 showed that serum PF4 level was significantly higher in colorectal cancer patients than in healthy controls (P < 0.01), with a sensitivity and specificity of 61.1% and 76.9%, respectively.

CONCLUSION: Combined use of SELDI-TOF-MS and EPO-KB is feasible for identification of serum biomarkers for colorectal cancer. PF4 (m/z at 7778) is significantly upregulated in colorectal cancer patients, providing a new biomarker for colorectal cancer.

Molecular markers for detection, surveillance and prognostication of bladder cancer

Many markers for the detection of bladder cancers have been tested and almost all urinary markers reported are better than cytology with regard to sensitivity, but they score lower in specificity. Currently molecular and genetic changes play an important role in the discovery of new molecular markers for detection, prognostication and surveillance. The purpose of this review is to highlight the most important urinary molecular biomarker developments that have been studied and reported recently. In the current review we have summarized the most recent and relevant published reports on molecular urinary markers. The results of this review show that the first generation of urinary markers did not add much to urinary cytology. The current generation of markers is better, but additional clinical trials are needed. Our knowledge of molecular pathways in bladder cancer is growing and new methods of marker development emerge, but the perfect marker is still to be found. Currently, there are not clinically usable molecular markers that can guide us in diagnosis or surveillance, nor guide us in lowering the frequency of urethrocystoscopy in bladder cancer.

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry: serum protein profiling in seminoma patients

PURPOSE

Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS) allows rapid protein profiling of complex biological mixtures. We analyzed testicular germ cell cancer serum samples to differentiate between cancer and controls with a special focus on beta-hCG-negative seminomas.

METHODS

Proteomic spectra were generated by the ProteinChip system and analyzed by the proteomic platform "proteomic.net". For statistical analysis, an artificial intelligence learning algorithm was used.

RESULTS

The classification algorithm correctly identified the pattern in 90.4% of the patients. Decision trees predicted seminomas with 91.5% sensitivity and 89.4% specificity. Seminoma patients with normal beta-hCG serum level were correctly predicted with 80% sensitivity and 70% specificity.

CONCLUSIONS

Our study demonstrates protein profiles of testicular germ cell cancer patients that differ in a highly significant degree from normal controls. Validation of these findings may enable proteomic profiling to become a valuable tool, especially for aftercare.

Quantitative mass spectrometry-based techniques for clinical use: biomarker identification and quantification

The potential for development of personalised medicine through the characterisation of novel biomarkers is an exciting prospect for improved patient care. Recent advances in mass spectrometric (MS) techniques, liquid phase analyte separation and bioinformatic tools for high throughput now mean that this goal may soon become a reality. However, there are challenges to be overcome for the identification and validation of robust biomarkers. Bio-fluids such as plasma and serum are a rich source of protein, many of which may reflect disease status, and due to the ease of sampling and handling, novel blood borne biomarkers are very much sought after. MS-based methods for high throughput protein identification and quantification are now available such that the issues arising from the huge dynamic range of proteins present in plasma may be overcome, allowing deep mining of the blood proteome to reveal novel biomarker signatures for clinical use. In addition, the development of sensitive MS-based methods for biomarker validation may bypass the bottleneck created by the need for generation and usage of reliable antibodies prior to large scale screening. In this review, we discuss the MS-based methods that are available for clinical proteomic analysis and highlight the progress made and future challenges faced in this cutting edge area of research.

Evaluation of urine proteome pattern analysis for its potential to reflect coronary artery atherosclerosis in symptomatic patients

Coronary artery disease (CAD) is a major cause of mortality and morbidity. Noninvasive proteome analysis could guide clinical evaluation and early/preventive treatment. Under routine clinical conditions, urine of 67 patients presenting with symptoms suspicious for CAD were analyzed by capillary electrophoresis directly coupled with mass spectrometry (CE-MS). All patients were subjected to coronary angiography and either assigned to a CAD or non-CAD group. A training set of 29 patients was used to establish CAD and non-CAD-associated proteome patterns of plasma as well as urine. Significant discriminatory power was achieved in urine but not in plasma. Therefore, urine proteomic analysis of further 38 patients was performed in a blinded study. A combination of 17 urinary polypeptides allowed separation of both groups in the test set with a sensitivity of 81%, a specificity of 92%, and an accuracy of 84%. Sequencing of urinary marker peptides identified fragments of collagen alpha1 (I and III), which we furthermore demonstrated to be expressed in atherosclerotic plaques of human aorta. In conclusion, specific CE-MS polypeptide patterns in urine were associated with significant CAD in patients with angina-typical symptoms. These promising findings need to be further evaluated in regard to reliability of a urine-based screening method with the potential of improving the diagnostic approaches for CAD.

Detection of tumours of the urinary tract in voided urine

Patients with non-muscle-invasive bladder cancer are treated by transurethral resection. About 60-70% of these patients will develop recurrences and in 11% of these cases progression to a muscle-invasive tumour occurs. Surveillance of patients by cystoscopy is therefore carried out every 3-4 months in the first 2 years and yearly thereafter. Several biomarkers have been developed that potentially can detect recurrent bladder cancer in voided urine samples and may present an alternative for the invasive cystoscopy procedure. Recently, van Rhijn reviewed the performance of several of these biomarkers regarding detection of recurrent disease in patients under surveillance. In general, sensitivities were much lower when only patients under surveillance were taken into account than when the patient cohorts included patients with primary disease or patients with high-grade tumours. In this article recent new data on those markers that displayed a sensitivity and specificity of at least 70% as mentioned in the review by van Rhijn are reviewed. The literature selected was limited to those papers in which the performance of makers was assayed only on urine samples of patients under surveillance. The markers with sensitivity and specificity over 70% that were selected from the previous study are Lewis X, NMP22, microsatellite analysis (MA), CYFRA 21.1, cytokeratin 20 and the UroVysion fluorescence in situ hybridization (FISH) test. Recent new developments such as the use of FGFR3 mutation analysis and methylation detection are also discussed. In conclusion, tests such as the UroVysion FISH test and MA are able to detect most concomitant recurrences and to predict recurrent disease. In general, lesions that are missed are pTa and low grade. With MA several upper tract recurrences were identified that were missed by cystoscopy. The value of the most promising urine tests needs to be established in longitudinal studies and exclusively on patients under surveillance for recurrent disease. A longitudinal setting allows subsequent urine samples to be tested and this increases sensitivity because a negative test outcome sometimes occurs between positive ones. Stratification of patients according to the genetic status of their primary tumours and smoking habits should be investigated. Decision models should be developed that recommend at which points in time cystoscopy or urine testing should be performed.

Apolipoprotein A-I and platelet factor 4 are biomarkers for infliximab response in rheumatoid arthritis

OBJECTIVES

The use of biologicals such as infliximab has dramatically improved the treatment of rheumatoid arthritis (RA). However, factors predictive of therapeutic response need to be identified. A proteomic study was performed prior to infliximab therapy to identify a panel of candidate protein biomarkers of RA predictive of treatment response.

METHODS

Plasma profiles of 60 patients with RA (28 non-responders (as defined by the American College of Rheumatology 20% improvement criteria (ACR20)) negative and 32 responders (ACR70 positive) to infliximab) were studied by surface enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF MS) technology on two types of arrays, an anion exchange array (SAX2) and a nickel affinity array (IMAC3-Ni). Biomarker characterisation was carried out using classical biochemical methods (purification by ammonium sulfate precipitation or metal affinity chromatography) and identification by matrix assisted laser desorption/ionisation time-of-flight (MALDI-TOF) MS analysis.

RESULTS

Two distinct protein profiles were observed on both arrays and several proteins were differentially expressed in both patient populations. Five proteins at 3.86, 7.77, 7.97, 8.14 and 74.07 kDa were overexpressed in the non-responder group, whereas one at 28 kDa was increased in the responder population (sensitivity>56%, specificity>77.5%). Moreover, combination of several biomarkers improved the sensitivity and specificity of the detection of patient response to over 97%. The 28 kDa protein was characterised as apolipoprotein A-I and the 7.77 kDa biomarker was identified as platelet factor 4.

CONCLUSIONS

Six plasma biomarkers are characterised, enabling the detection of patient response to infliximab with high sensitivity and specificity. Apolipoprotein A-1 was predictive of a good response to infliximab, whereas platelet factor 4 was associated with non-responders.

Discovery and validation of urinary biomarkers for prostate cancer

Only 30% of patients with elevated serum prostate specific antigen (PSA) levels who undergo prostate biopsy are diagnosed with prostate cancer (PCa). Novel methods are needed to reduce the number of unnecessary biopsies. We report on the identification and validation of a panel of 12 novel biomarkers for prostate cancer (PCaP), using CE coupled MS. The biomarkers could be defined by comparing first void urine of 51 men with PCa and 35 with negative prostate biopsy. In contrast, midstream urine samples did not allow the identification of discriminatory molecules, suggesting that prostatic fluids may be the source of the defined biomarkers. Consequently, first void urine samples were tested for sufficient amounts of prostatic fluid, using a prostatic fluid indicative panel ("informative" polypeptide panel; IPP). A combination of IPP and PCaP to predict positive prostate biopsy was evaluated in a blinded prospective study. Two hundred thirteen of 264 samples matched the IPP criterion. PCa was detected with 89% sensitivity, 51% specificity. Including age and percent free PSA to the proteomic signatures resulted in 91% sensitivity, 69% specificity.

Challenges of using mass spectrometry as a bladder cancer biomarker discovery platform

INTRODUCTION

Bladder cancer (BCa) is one of the most prevalent malignancies worldwide, mostly due to its high recurrence rates. In consequence, the necessity of repeated screening for reappearance demonstrates the urgent need for novel biomarkers as alternatives to invasive standard procedures.

METHODS

Proteomic technologies have emerged as powerful platforms for unbiased biomarker discovery and revolutionized the classical "target-driven" analysis of single marker candidates. Although proteome profiling is still far from demonstrating its full potential in clinical diagnosis, first studies clearly denote its significant potential.

CONCLUSIONS

This review provides a discussion of the challenges related to clinical proteomics using mass spectrometry, emphasizing bladder cancer biomarker discovery. An outline of the technological prerequisites for reliable proteome profiling, data mining and interpretation, as well as, reflections on future trends in the field are provided.

Urinary markers in bladder cancer

OBJECTIVES

Many markers for the detection of bladder cancers have been tested. Almost all urinary markers reported are better than cytology with regard to sensitivity, but they score lower in specificity. The purpose of this review is to highlight the most important urinary biomarkers studied and reported recently.

METHODS

Literature on bladder cancer markers has been reviewed regularly in the last few years. In the current review we have tried to summarise the most recent literature of urinary markers.

RESULTS

The results of this review show that the first-generation urinary markers did not add much to urinary cytology. The current generation of markers is promising but larger clinical trails are needed. The future of marker development is bright with new techniques emerging, but the perfect marker is still to be found.

CONCLUSION

Currently, no single marker can yet guide us in surveillance and lower the frequency of urethrocystoscopy.

A better understanding of molecular mechanisms underlying human disease

This review summarises and discusses the degree to which proteomics is contributing to medical care, providing examples and signspots for future directions. Why do genomic approaches provide a limited view of gene expression? Because of the multifactorial nature of many diseases, proteomics enables us to understand the molecular basis of disease, not only at the organism, whole-cell or tissue levels, but also in subcellular structures, protein complexes and biological fluids. The application of proteomics in medicine is expected to have a major impact by providing an integrated view of individual disease processes. This review describes several proteomic platforms and examines the role of proteomics as a tool for clinical biomarker discovery, the identification of prognostic and earlier diagnostic markers, their use in monitoring the effects of drug treatments and eventually find more efficient and safer therapeutics for a wide range of pathologies.

[Identification of biomarkers and therapeutic targets for renal cell cancer using ProteinChip technology]

In order to understand tumour biology in its complexity, it is necessary to investigate the proteomics in addition to the DNA and RNA level. SELDI-TOF-MS represents a new technology allowing a highly sensitive high-throughput analysis to detect specific protein profiles. In renal cancer, it was possible to define specific protein patterns in serum. Several proteins have been identified, i.e. serum amyloid alpha (SAA). Analysis of tumour tissues leads to a better understanding of tumour biology and provides the basis for differential classification and evaluation of prognosis. Investigation of the proteome concerning therapy results opens up the possibility of assessing downstream effects on the one hand and identifying biomarkers for selection of patients and therapy monitoring on the other hand. This review presents the first results for renal cancer.

Discovery and identification of Serum Amyloid A protein elevated in lung cancer serum

Two hundred and eighteen serum samples from 175 lung cancer patients and 43 healthy individuals were analyzed by using Surface Enhaced Laser Desorption/Ionization Time of Flight Mass Spectrome-try (SELDI-TOF-MS). The data analyzed by both Biomarker Wizardtrade mark and Biomarker Patternstrade mark software showed that a protein peak with the molecular weight of 11.6 kDa significantly increased in lung cancer. Meanwhile, the level of this biomarker was progressively increased with the clinical stages of lung cancer. The candidate biomarker was then obtained from tricine one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis by matching the molecular weight with peaks on WCX2 chips and was identified as Serum Amyloid A protein (SAA) by MALDI/MS-MS and database searching. It was further validated in the same serum samples by immunoprecipitation with commercial SAA antibody. To confirm the SAA differential expression in lung cancer patients, the same set of serum samples was measured by ELISA assay. The result showed that at the cutoff point 0.446 (OD value) on the Receiver Operating Characteristic (ROC) curve, SAA could better discriminate lung cancer from healthy individuals with sensitivity of 84.1% and specificity of 80%. These findings demonstrated that SAA could be characterized as a biomarker related to pathological stages of lung cancer.

Contribution of oncoproteomics to cancer biomarker discovery

Oncoproteomics is the study of proteins and their interactions in a cancer cell by proteomic technologies. Proteomic research first came to the fore with the introduction of two-dimensional gel electrophoresis. At the turn of the century, proteomics has been increasingly applied to cancer research with the wide-spread introduction of mass spectrometry and proteinchip. There is an intense interest in applying proteomics to foster an improved understanding of cancer pathogenesis, develop new tumor biomarkers for diagnosis, and early detection using proteomic portrait of samples. Oncoproteomics has the potential to revolutionize clinical practice, including cancer diagnosis and screening based on proteomic platforms as a complement to histopathology, individualized selection of therapeutic combinations that target the entire cancer-specific protein network, real-time assessment of therapeutic efficacy and toxicity, and rational modulation of therapy based on changes in the cancer protein network associated with prognosis and drug resistance. Besides, oncoproteomics is also applied to the discovery of new therapeutic targets and to the study of drug effects. In pace with the successful completion of the Human Genome Project, the wave of proteomics has raised the curtain on the postgenome era. The study of oncoproteomics provides mankind with a better understanding of neoplasia. In this article, the discovery of cancer biomarkers in recent years is reviewed. The challenges ahead and perspectives of oncoproteomics for biomarkers development are also addressed. With a wealth of information that can be applied to a broad spectrum of biomarker research projects, this review serves as a reference for biomarker researchers, scientists working in proteomics and bioinformatics, oncologists, pharmaceutical scientists, biochemists, biologists, and chemists.

Urinary bladder tumor markers

Bladder cancer is amenable to biomarker development because many tumor-associated molecules are secreted in urine. Tumor cells are shed in urine, and, therefore, tests that detect tumor cell-surface markers have also been developed to diagnose bladder cancer and monitor its recurrence. Several bladder tumor markers show higher sensitivity than cytology, but most have lower specificity. In addition to markers that use conventional technologies such as enzyme-linked immunosorbent assay, point-of-care devices, reverse transcriptase polymerase chain reaction, fluorescent in situ hybridization, and immunocytochemistry, proteomic and gene profiling approaches are being used to find new biomarkers to assist in the molecular profiling of bladder cancer. This review describes both new and well-studied bladder tumor markers.

Urinary biomarker profiling in transitional cell carcinoma

Urinary biomarkers or profiles that allow noninvasive detection of recurrent transitional cell carcinoma (TCC) of the bladder are urgently needed. We obtained duplicate proteomic (SELDI) profiles from 227 subjects (118 TCC, 77 healthy controls and 32 controls with benign urological conditions) and used linear mixed effects models to identify peaks that are differentially expressed between TCC and controls and within TCC subgroups. A Random Forest classifier was trained on 130 profiles to develop an algorithm to predict the presence of TCC in a randomly selected initial test set (n = 54) and an independent validation set (n = 43) several months later. Twenty two peaks were differentially expressed between all TCC and controls (p < 10(-7)). However potential confounding effects of age, sex and analytical run were identified. In an age-matched sub-set, 23 peaks were differentially expressed between TCC and combined benign and healthy controls at the 0.005 significance level. Using the Random Forest classifier, TCC was predicted with 71.7% sensitivity and 62.5% specificity in the initial set and with 78.3% sensitivity and 65.0% specificity in the validation set after 6 months, compared with controls. Several peaks of importance were also identified in the linear mixed effects model. We conclude that SELDI profiling of urine samples can identify patients with TCC with comparable sensitivities and specificities to current tumor marker tests. This is the first time that reproducibility has been demonstrated on an independent test set analyzed several months later. Identification of the relevant peaks may facilitate multiplex marker assay development for detection of recurrent disease.

Human body fluid proteome analysis

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.

Discovery of urinary biomarkers

A myriad of proteins and peptides can be identified in normal human urine. These are derived from a variety of sources including glomerular filtration of blood plasma, cell sloughing, apoptosis, proteolytic cleavage of cell surface glycosylphosphatidylinositol-linked proteins, and secretion of exosomes by epithelial cells. Mass spectrometry-based approaches to urinary protein and peptide profiling can, in principle, reveal changes in excretion rates of specific proteins/peptides that can have predictive value in the clinical arena, e.g. in the early diagnosis of disease, in classification of disease with regard to likely therapeutic responses, in assessment of prognosis, and in monitoring response to therapy. These approaches have potential value, not only in diseases of the kidney and urinary tract but also in systemic diseases that are associated with circulating small protein and peptide markers that can pass the glomerular filter. Most large scale biomarker discovery studies reported thus far have used one of two approaches to identify proteins and peptides whose excretion in urine changes in specific disease states: 1) two-dimensional electrophoresis with mass spectrometric and/or immunochemical identification of proteins and 2) top-down mass spectrometric methods (SELDI-TOF-MS and capillary electrophoresis-MS). These studies have been chiefly in the areas of nephrology, urology, and oncology. We review these applications, focusing on two areas of progress, viz. in bladder cancer and in acute rejection of renal transplants. Progress has been limited so far. However, with the advent of powerful LC-MS/MS methods along with methods for quantifying LC-MS/MS output, there is hope for an accelerated discovery and validation of disease biomarkers in urine.

Protein profiling of bladder cancer using the 2D-PAGE and SELDI-TOF-MS technique

Protein profiling is a promising tool for tumor characterization and the detection of tumor markers in bladder cancer. Techniques for 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and surface-enhanced laser desorption/ionization with time-of-flight mass spectrometry (SELDI-TOF-MS) have improved; both were evaluated using bladder tumor tissue. Normal urothelium and pTa G2, pT1 G3, and >or=pT3 G3 tissues were obtained from the operating room and, after macrodissection, subjected to 2D-PAGE and to SELDI-TOF-MS ProteinChip. 2D-PAGE gels expressed significantly different protein patterns for pTa G2 and pT3 G3 tumors. pT1 G3 tumors showed expression profiles similar to those of the invasive tumors, with upregulation of galectin 3, gelsolin, villin 2, moesin, and annexin 6. Similarly, distinct protein peaks were detected for superficial and muscle-invasive urothelial cancers by SELDI-TOF-MS. Six of seven superficial pTa G2 tumors showed an intense peak at 6.7 and 10.1 kD, while invasive carcinomas showed an intense peak near 9.5 kD. No disturbing influence of surrounding tissue on the results was detected. It was shown that both techniques (2D-PAGE and ProteinChip) work well, and especially ProteinChip analysis seems promising for clinical application.