Mass profiling-directed isolation and identification of a stage-specific serologic protein biomarker of advanced prostate cancer

Multiplexed Prostate Cancer Companion Diagnostic Devices

Prostate cancer (PCa) remains one of the most prominent forms of cancer for men. Since the early 1990s, Prostate-Specific Antigen (PSA) has been a commonly recognized PCa-associated protein biomarker. However, PSA testing has been shown to lack in specificity and sensitivity when needed to diagnose, monitor and/or treat PCa patients successfully. One enhancement could include the simultaneous detection of multiple PCa-associated protein biomarkers alongside PSA, also known as multiplexing. If conventional methods such as the enzyme-linked immunosorbent assay (ELISA) are used, multiplexed detection of such protein biomarkers can result in an increase in the required sample volume, in the complexity of the analytical procedures, and in adding to the cost. Using companion diagnostic devices such as biosensors, which can be portable and cost-effective with multiplexing capacities, may address these limitations. This review explores recent research for multiplexed PCa protein biomarker detection using optical and electrochemical biosensor platforms. Some of the novel and potential serum-based PCa protein biomarkers will be discussed in this review. In addition, this review discusses the importance of converting research protocols into multiplex point-of-care testing (xPOCT) devices to be used in near-patient settings, providing a more personalized approach to PCa patients’ diagnostic, surveillance and treatment management.

Monitoring of platelet function parameters and microRNA expression levels in patients with prostate cancer treated with volumetric modulated arc radiotherapy

Radiotherapy (RT) may result in platelet activation and thrombosis development. To the best of our knowledge, the potential effect of volumetric-modulated arc therapy (VMAT), a novel radiotherapy technique, on platelet function and microRNA (miRNA/miR) expression has not been previously investigated. The present study aimed to determine the effect of VMAT on the alterations in platelet function parameters and miRNA expression levels. A total of 25 patients with prostate cancer and 25 healthy subjects were included in the present study. Blood samples were collected from the patient group on the day prior to RT (pre-RT), the day RT was completed (post-RT day 0), and 40 days following the end of therapy (post-RT day 40). Platelet count, mean platelet volume (MPV) value, platelet aggregation, plasma P-selectin, thrombospondin-1, platelet factor 4, plasma miR-223 and miR-126 expression levels were measured. A significant decrease in platelet count in the post-RT day 0 group was measured in comparison with the pre-RT and the post-RT day 40 groups. Pre-RT MPV values were higher than those of the post-RT day 0 and the post-RT day 40 groups. No significant differences were observed in the levels of platelet activation markers or miR-223 and miR-126 expression levels between the RT groups. Although RT may result in a reduction in platelet and MPV counts, the results of the present study indicate that platelet activation markers are not affected by VMAT. Therefore, it is possible that no platelet activation occurs during VMAT, owing to the conformal dose distributions, improved target volume coverage and the sparing of normal tissues from undesired radiation.

The prognostic significance of circulating serum amyloid A and CXC chemokine ligand 4 in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common pediatric bone cancer.  Despite advances in treatment regimens, the survival rate remains 60-70%.  There is an urgent need to identify prognostic biomarkers, so that targeted therapies can be developed to improve the outcome.

PROCEDURE

Our laboratory has previously identified that circulating serum amyloid A (SAA) and CXC chemokine ligand 4 (CXCL4) are upregulated in patients with OS.  In this study, we tested if they could be used as prognostic biomarkers.  We used enzyme-linked immunosorbent assays to measure their concentrations in serum samples (n = 233) and immunohistochemistry to examine their expressions in primary tumors (n = 37).  Prognostic significance of the serum concentrations and tumor expressions of the biomarkers was then evaluated.

RESULTS

Patients with "high SAA" and "low CXCL4" circulating levels at diagnosis significantly correlated with a worse outcome (HR = 1.68, P = 0.014), which was independent of the metastatic status.  These patients also exhibited a significantly higher rate of poor histologic response to chemotherapy.  Furthermore, low tumor expression of CXCL4 correlated with poor survival (HR = 3.57, P = 0.005).

CONCLUSIONS

Our results demonstrate that circulating SAA and CXCL4 may serve as prognostic biomarkers in OS.  Targeting CXCL4 has been reported, suggesting that it may be exploited as a therapeutic target in OS.

Methodology and Applications of Disease Biomarker Identification in Human Serum

Biomarkers are biomolecules that serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Because of the high abundance of albumin and heterogeneity of plasma lipoproteins and glycoproteins, biomarkers are difficult to identify in human serum. Due to the clinical significance the identification of disease biomarkers in serum holds great promise for personalized medicine, especially for disease diagnosis and prognosis. This review summarizes some common and emerging proteomics techniques utilized in the separation of serum samples and identification of disease signatures. The practical application of each protein separation or identification technique is analyzed using specific examples. Biomarkers of cancers of prostate, breast, ovary, and lung in human serum have been reviewed, as well as those of heart disease, arthritis, asthma, and cystic fibrosis. Despite the advancement of technology few biomarkers have been approved by the Food and Drug Administration for disease diagnosis and prognosis due to the complexity of structure and function of protein biomarkers and lack of high sensitivity, specificity, and reproducibility for those putative biomarkers. The combination of different types of technologies and statistical analysis may provide more effective methods to identify and validate new disease biomarkers in blood.

Glycans and glycoproteins as specific biomarkers for cancer

Protein glycosylation and other post-translational modifications are involved in potentially all aspects of human growth and development. Defective glycosylation has adverse effects on human physiological conditions and accompanies many chronic and infectious diseases. Altered glycosylation can occur at the onset and/or during tumor progression. Identifying these changes at early disease stages may aid in making decisions regarding treatments, as early intervention can greatly enhance survival. This review highlights some of the efforts being made to identify N- and O-glycosylation profile shifts in cancer using mass spectrometry. The analysis of single or panels of potential glycoprotein cancer markers are covered. Other emerging technologies such as global glycan release and site-specific glycosylation analysis and quantitation are also discussed. Graphical Abstract Steps involved in the biomarker discovery.

CXCL4 mediates tumor regrowth after chemotherapy by suppression of antitumor immunity

The recurrence of colorectal cancer after chemotherapy is the leading cause of its high mortality. We propose that elucidating the mechanisms of tumor regrowth after chemotherapy in tumor-bearing mice may provide new insights into tumor relapse in cancer patients. We firstly report the identification of a chemokine, CXCL4, that plays an important role in the molecular mechanism of cancer regrowth after chemotherapy. A syngenic transplantation tumor model was established with murine colon cancer CT26 cells and treated with 5-FU. Genome-wide gene expression analysis determined that CXCL4 was transiently upregulated in the tumor model. Systemic overexpression of CXCL4 accelerated cancer growth in vivo, but not in vitro. Conversely, the anti-CXCL4 monoclonal antibody (CXCL4-mab) retarded tumor-regrowth after 5-FU treatment in immune-competent mice, but not nude mice. The CXCL4-mab treatment increased the local expression levels of IFN-γ and Gran-b genes in the tumor-bed, and elevated the function of CTLs against CT26 cells. Thus, the colon cancer cells in responding to the cytotoxic stress of 5-FU produce a high level of CXCL4, which suppresses antitumor immunity to confer the residual cancer cells an advantage for regrowth after chemotherapy. Our findings provide a novel target for developing therapeutics aiming to increase antitumor immunity after chemotherapy.

The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

Plumbagin elicits differential proteomic responses mainly involving cell cycle, apoptosis, autophagy, and epithelial-to-mesenchymal transition pathways in human prostate cancer PC-3 and DU145 cells

Plumbagin (PLB) has exhibited a potent anticancer effect in preclinical studies, but the molecular interactome remains elusive. This study aimed to compare the quantitative proteomic responses to PLB treatment in human prostate cancer PC-3 and DU145 cells using the approach of stable-isotope labeling by amino acids in cell culture (SILAC). The data were finally validated using Western blot assay. First, the bioinformatic analysis predicted that PLB could interact with 78 proteins that were involved in cell proliferation and apoptosis, immunity, and signal transduction. Our quantitative proteomic study using SILAC revealed that there were at least 1,225 and 267 proteins interacting with PLB and there were 341 and 107 signaling pathways and cellular functions potentially regulated by PLB in PC-3 and DU145 cells, respectively. These proteins and pathways played a critical role in the regulation of cell cycle, apoptosis, autophagy, epithelial to mesenchymal transition (EMT), and reactive oxygen species generation. The proteomic study showed substantial differences in response to PLB treatment between PC-3 and DU145 cells. PLB treatment significantly modulated the expression of critical proteins that regulate cell cycle, apoptosis, and EMT signaling pathways in PC-3 cells but not in DU145 cells. Consistently, our Western blotting analysis validated the bioinformatic and proteomic data and confirmed the modulating effects of PLB on important proteins that regulated cell cycle, apoptosis, autophagy, and EMT in PC-3 and DU145 cells. The data from the Western blot assay could not display significant differences between PC-3 and DU145 cells. These findings indicate that PLB elicits different proteomic responses in PC-3 and DU145 cells involving proteins and pathways that regulate cell cycle, apoptosis, autophagy, reactive oxygen species production, and antioxidation/oxidation homeostasis. This is the first systematic study with integrated computational, proteomic, and functional analyses revealing the networks of signaling pathways and differential proteomic responses to PLB treatment in prostate cancer cells. Quantitative proteomic analysis using SILAC represents an efficient and highly sensitive approach to identify the target networks of anticancer drugs like PLB, and the data may be used to discriminate the molecular and clinical subtypes, and to identify new therapeutic targets and biomarkers, for prostate cancer. Further studies are warranted to explore the potential of quantitative proteomic analysis in the identification of new targets and biomarkers for prostate cancer.

Potential serum biomarkers for glioblastoma diagnostic assessed by proteomic approaches

BACKGROUND

The rapid progress of proteomics over the past years has allowed the discovery of a large number of potential biomarker candidates to improve early tumor diagnosis and therapeutic response, thus being further integrated into clinical environment. High grade gliomas represent one of the most aggressive and treatment-resistant types of human brain cancer, with approximately 9-12 months median survival rate for patients with grade IV glioma (glioblastoma). Using state-of-the-art proteomics technologies, we have investigated the proteome profile for glioblastoma patients in order to identify a novel protein biomarker panel that could discriminate glioblastoma patients from controls and increase diagnostic accuracy.

RESULTS

In this study, SELDI-ToF MS technology was used to screen potential protein patterns in glioblastoma patients serum; furthermore, LC-MS/MS technology was applied to identify the candidate biomarkers peaks. Through these proteomic approaches, three proteins S100A8, S100A9 and CXCL4 were selected as putative biomarkers and confirmed by ELISA. Next step was to validate the above mentioned molecules as biomarkers through identification of protein expression by Western blot in tumoral versus peritumoral tissue.

CONCLUSIONS

Proteomic technologies have been used to investigate the protein profile of glioblastoma patients and established several potential diagnostic biomarkers. While it is unlikely for a single biomarker to be highly effective for glioblastoma diagnostic, our data proposed an alternative and efficient approach by using a novel combination of multiple biomarkers.

Molecular diagnosis of prostate cancer: are we up to age?

Prostate cancer (PCa), a highly heterogeneous disease, is the one of the leading cause of morbidity and mortality in the developed countries. Historically used biomarkers such as prostatic acid phosphatase (PAP), serum prostate-specific antigen (PSA), and its precursor have not stood the challenge of sensitivity and specificity. At present, there is need to re-evaluate the approach to diagnose and monitor PCa. To this end, molecular markers that can accurately identify men with PCa at an early stage, and those who would benefit from early therapeutic intervention, are the need of the hour. There has been unprecedented progress in the development of new PCa biomarkers through advancements in proteomics, tissue DNA and protein/RNA microarray, identification of microRNA, isolation of circulating tumor cells, and tumor immunohistochemistry. This review will examine the current status of prostate cancer biomarkers with emphasis on emerging biomarkers by evaluating their diagnostic and prognostic potentials.

MALDI mass spectrometry in prostate cancer biomarker discovery

Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Profiling of antibody production against xenograft-released proteins by protein microarrays discovers prostate cancer markers

This study describes a novel xenograft-based biomarker discovery platform and proves its usefulness in the discovery of serum markers for prostate cancer. By immunizing immuno-competent mice with serum from nude mice bearing prostate cancer xenografts, an antibody response against xenograft-derived antigens was elicited. By probing protein microarrays with serum from immunized mice, several prostate cancer-derived antigens were identified, of which a subset was successfully retrieved in serum from mice bearing prostate cancer xenografts and prevalidated in human serum samples of prostate cancer patients. Among the discovered and validated proteins were the members of the TAM receptor family (TYRO3, AXL, and MERTK), ACY1, and PSMA1. In conclusion, this novel method allows for the identification of low abundant cancer-derived serum proteins, circumventing dynamic range and host-response issues in standard patient cohort proteomics comparisons.

The role of the CXC chemokines platelet factor-4 (CXCL4/PF-4) and its variant (CXCL4L1/PF-4var) in inflammation, angiogenesis and cancer

Chemokines are chemotactic cytokines which recruit leukocytes to inflammatory sites. They also affect tumor development and metastasis by acting as growth factor, by attracting pro- or anti-tumoral leukocytes or by influencing angiogenesis. Platelet factor-4 (CXCL4/PF-4) was the first chemokine shown to inhibit angiogenesis. CXCL4L1/PF-4var, recently isolated from thrombin-stimulated platelets, differing from authentic CXCL4/PF-4 in three carboxy-terminally located amino acids, was found to be more potent than CXCL4/PF-4 in inhibiting angiogenesis and tumor growth. Both glycosaminoglycans (GAG) and CXCR3 are implicated in the activities of the PF-4 variants. This report reviews the current knowledge on the role of CXCL4/PF-4 and CXCL4L1/PF-4var in physiological and pathological processes. In particular, the role of CXCL4/PF-4 in cancer, heparin-induced thrombocytopenia and atherosclerosis is described.

Development of a new magnetic beads-based immunoprecipitation strategy for proteomics analysis

Sample pre-treatment is a critical step for an efficient and reliable analysis and it is highly dependent on the complexity of the matrix. This work shows an example of application of an immunoprecipitation approach using a new magnetic beads-based format, which allows a selective/specific extraction of potential biomarkers from metastatic prostate cancer. Results obtained on the development of this method, and its application for the extraction and pre-concentration of certain biomarkers present in metastatic cell lines of prostate cancer, are presented and discussed. It is concluded that the efficiency of the immunoprecipitation step is clearly compromised by the crosslinking conditions and it is highly dependent on the specificity of selected antibodies. The epoxy magnetic beads used in this work allowed an effective crosslinking of the antibodies contributing to an increased efficiency of the immunoprecipitation step. The optimized conditions for the application of these epoxy magnetic beads for the immunoprecipitation of anti-TUBA3C in metastatic prostate cancer cell line (PC3) are discussed here, as an example of application of the immnuprecipitation approach developed, which resulted in a very efficient tool for a specific extraction and pre-concentration of the targeted protein and, therefore, contributing to the efficiency of further analysis.

Comprehensive identification and modified-site mapping of S-nitrosylated targets in prostate epithelial cells

Background

Although overexpression of nitric oxide synthases (NOSs) has been found associated with prostate diseases, the underlying mechanisms for NOS-related prostatic diseases remain unclear. One proposed mechanism is related to the S-nitrosylation of key regulatory proteins in cell-signaling pathways due to elevated levels of NO in the prostate. Thus, our primary objective was to identify S-nitrosylated targets in an immortalized normal prostate epithelial cell line, NPrEC.

Methodology/Principal Findings

We treated NPrEC with nitroso-cysteine and used the biotin switch technique followed by gel-based separation and mass spectrometry protein identification (using the LTQ-Orbitrap) to discover S-nitrosylated (SNO) proteins in the treated cells. In parallel, we adapted a peptide pull-down methodology to locate the site(s) of S-nitrosylation on the protein SNO targets identified by the first technique. This combined approach identified 116 SNO proteins and determined the sites of modification for 82 of them. Over 60% of these proteins belong to four functional groups: cell structure/cell motility/protein trafficking, protein folding/protein response/protein assembly, mRNA splicing/processing/transcriptional regulation, and metabolism. Western blot analysis validated a subset of targets related to disease development (proliferating cell nuclear antigen, maspin, integrin β4, α-catenin, karyopherin [importin] β1, and elongation factor 1A1). We analyzed the SNO sequences for their primary and secondary structures, solvent accessibility, and three-dimensional structural context. We found that about 80% of the SNO sites that can be mapped into resolved structures are buried, of which approximately half have charged amino acids in their three-dimensional neighborhood, and the other half residing within primarily hydrophobic pockets.

Conclusions/Significance

We here identified 116 potential SNO targets and mapped their putative SNO sites in NPrEC. Elucidation of how this post-translational modification alters the function of these proteins should shed light on the role of NO in prostate pathologies. To our knowledge, this is the first report identifying SNO targets in prostate epithelial cells.

Ribosome-inactivating proteins isolated from dietary bitter melon induce apoptosis and inhibit histone deacetylase-1 selectively in premalignant and malignant prostate cancer cells

Epidemiologic evidence suggests that a diet rich in fruits and vegetables is associated with a reduced risk of prostate cancer (PCa) development. Although several dietary compounds have been tested in preclinical PCa prevention models, no agents have been identified that either prevent the progression of premalignant lesions or treat advanced disease. Momordica charantia, known as bitter melon in English, is a plant that grows in tropical areas worldwide and is both eaten as a vegetable and used for medicinal purposes. We have isolated a protein, designated as MCP30, from bitter melon seeds. The purified fraction was verified by SDS-PAGE and mass spectrometry to contain only 2 highly related single chain Type I ribosome-inactivating proteins (RIPs), alpha-momorcharin and beta-momorcharin. MCP30 induces apoptosis in PIN and PCa cell lines in vitro and suppresses PC-3 growth in vivo with no effect on normal prostate cells. Mechanistically, MCP30 inhibits histone deacetylase-1 (HDAC-1) activity and promotes histone-3 and -4 protein acetylation. Treatment with MCP30 induces PTEN expression in a prostatic intraepithelial neoplasia (PIN) and PCa cell lines resulting in inhibition of Akt phosphorylation. In addition, MCP30 inhibits Wnt signaling activity through reduction of nuclear accumulation of beta-catenin and decreased levels of c-Myc and Cyclin-D1. Our data indicate that MCP30 selectively induces PIN and PCa apoptosis and inhibits HDAC-1 activity. These results suggest that Type I RIPs derived from plants are HDAC inhibitors that can be utilized in the prevention and treatment of prostate cancer.

Serum peptidome profiling revealed platelet factor 4 as a potential discriminating Peptide associated with pancreatic cancer

PURPOSE

Mass spectrometry-based serum peptidome profiling is a promising tool to identify novel disease-associated biomarkers, but is limited by preanalytic factors and the intricacies of complex data processing. Therefore, we investigated whether standardized sample protocols and new bioinformatic tools combined with external data validation improve the validity of peptidome profiling for the discovery of pancreatic cancer-associated serum markers.

EXPERIMENTAL DESIGN

For the discovery study, two sets of sera from patients with pancreatic cancer (n = 40) and healthy controls (n = 40) were obtained from two different clinical centers. For external data validation, we collected an independent set of samples from patients (n = 20) and healthy controls (n = 20). Magnetic beads with different surface functionalities were used for peptidome fractionation followed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). Data evaluation was carried out by comparing two different bioinformatic strategies. Following proteome database search, the matching candidate peptide was verified by MALDI-TOF MS after specific antibody-based immunoaffinity chromatography and independently confirmed by an ELISA assay.

RESULTS

Two significant peaks (m/z 3884; 5959) achieved a sensitivity of 86.3% and a specificity of 97.6% for the discrimination of patients and healthy controls in the external validation set. Adding peak m/z 3884 to conventional clinical tumor markers (CA 19-9 and CEA) improved sensitivity and specificity, as shown by receiver operator characteristics curve analysis (AUROC(combined) = 1.00). Mass spectrometry-based m/z 3884 peak identification and following immunologic quantitation revealed platelet factor 4 as the corresponding peptide.

CONCLUSIONS

MALDI-TOF MS-based serum peptidome profiling allowed the discovery and validation of platelet factor 4 as a new discriminating marker in pancreatic cancer.

Reducing agent-mediated precipitation of high-abundance plasma proteins

Depletion of high-abundance proteins is regarded as a critical sample preparation step for most plasma proteomic analyses and profiling strategies. This report describes a process that rapidly and reproducibly precipitates high-abundance disulfide-rich proteins, including albumin and transferrin, from serum and plasma. A low volume of concentrated reducing agent, viz. dithiothreitol (DTT) or tris(2-carboxyethyl)phosphine (TCEP), was added directly to plasma followed by a brief incubation at ambient temperature. Removal of the precipitate via centrifugation and identification of the protein content revealed an albumin-enriched pellet. Direct analysis of the supernatant by MALDI-TOF-MS afforded peptidome and small protein profiles with enhanced features and minimal ionization of full-length albumin. The reproducible and quantitative nature of the method has been demonstrated by monitoring the plasma levels of an antiangiogenic protein biologic, rKringle5 (rK5). The 10.5-kDa analyte was only reliably detected in plasma after treatment with reducing agent, ionizing linearly from 150 to 1200 fmol (on-target) with a mean CV of 7%. This method distinguishes itself from immunoaffinity resin-based approaches since it can be scaled to large milliliter quantities and it is compatible with plasma from all species tested.

Proneurotensin/neuromedin N secreted from small cell lung carcinoma cell lines as a potential tumor marker

Proteins secreted from specific cancer cells have a high potential for use as tumor markers. We identified secreted proteins produced by 15 different carcinoma cell lines grown in serum-free medium using MS/MS. Proneurotensin/neuromedin N (proNT/NMN) was found in conditioned medium from four of seven small cell lung carcinoma cell lines but not from eight nonsmall cell lung carcinoma cell lines. These results indicate proNT/NMN has potential as a specific tumor marker of small cell lung carcinoma.

Applying proteomic-based biomarker tools for the accurate diagnosis of pancreatic cancer

BACKGROUND

The proteome varies with physiologic and disease states. Few studies have been reported that differentiate the proteome of those with pancreatic cancer.

AIM

To apply proteomic-based technologies to body fluids. To differentiate pancreatic neoplasia from nonneoplastic pancreatic disease.

METHODS

Samples from 50 patients (15 healthy (H), 24 cancer (Ca), 11 chronic pancreatitis (CP)) were prospectively collected and underwent analysis. A high-throughput method, using high-affinity solid lipophilic extraction resins, enriched low molecular weight proteins for extraction with a high-speed 200-Hz matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-MS; Bruker Ultraflex III). Samples underwent software processing with FlexAnalysis, Clinprot, MatLab, and Statistica (baseline, align, and normalize spectra). Nonparametric pairwise statistics, multidimensional scaling, hierarchical analysis, and leave-one-out cross validation completed the analysis. Sensitivity (sn) and specificity (sp) of group comparisons were determined. Two top-down-directed protein identification approaches were combined with MALDI-MS and tandem mass spectrometry to fully characterize the most significant protein biomarker.

RESULTS

Using eight serum features, we differentiated Ca from H (sn 88%, sp 93%), Ca from CP (sn 88%, sp 30%), and Ca from both H and CP combined (sn 88%, sp 66%). In addition, nine features obtained from urine differentiated Ca from both H and CP combined with high efficiency (sn 90%, sp 90%). Interestingly, the plasma samples (considered by the Human Proteome Organization to be the preferred biological fluid) did not show significant differences. Multidimensional scaling indicated that markers from both serum and urine led to a highly effective clinical indicator of each specific disease state.

CONCLUSIONS

The proteomic analysis of noninvasively acquired biological fluids provided a high level of predictability for diagnosing pancreatic cancer. While the proteomic analysis of serum was capable of screening individuals for pancreatic disease (i.e., CP and Ca vs. H), specific urine biomarkers further distinguished malignancy (Ca) from chronic inflammation (CP).

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.

Proteomics for prediction and characterization of response to infliximab in Crohn's disease: a pilot study

OBJECTIVES

Infliximab is the first anti-TNFalpha accepted by the Food and Drug Administration for use in inflammatory bowel disease treatment. Few clinical, biological and genetic factors tend to predict response in Crohn's disease (CD) patient subcategories, none widely predicting response to infliximab.

DESIGN AND METHODS

Twenty CD patients showing clinical response or non response to infliximab were used for serum proteomic profiling on Surface Enhanced Lazer Desorption Ionisation-Time of Flight-Mass Spectrometry (SELDI-TOF-MS), each before and after treatment. Univariate and multivariate data analysis were performed for prediction and characterization of response to infliximab.

RESULTS

We obtained a model of classification predicting response to treatment and selected relevant potential biomarkers, among which platelet aggregation factor 4 (PF4). We quantified PF4, sCD40L and IL-6 by ELISA for correlation studies.

CONCLUSIONS

This first proteomic pilot study on response to infliximab in CD suggests association between platelet metabolism and response to infliximab and requires validation studies on a larger cohort of patients.

Electrophoretic methods for analysis of urinary polypeptides in IgA-associated renal diseases

We evaluated the utility of SDS-PAGE/Western blot and CE coupled with MS (CE-MS) for detection of urinary polypeptide biomarkers of renal disease in patients with IgA-associated glomerulonephritides. In a reference cohort of 402 patients with various renal disorders and 207 healthy controls, we defined CE-MS patterns of renal damage and IgA nephropathy (IgAN). In a blinded analysis of a separate cohort of patients with IgAN (n = 10), Henoch-Schoenlein purpura (HSP) with nephritis (n = 10), and IgA-associated glomerulonephritis due to hepatitis C virus (HCV)-induced cirrhosis (n = 9), and healthy controls (n = 12), we compared SDS-PAGE/Western blot and CE-MS against clinical urinalysis for detection of urinary proteins/polypeptides. Urinalysis indicated proteinuria for 50, 90, and 33% of patients, respectively, and for none of the healthy controls. SDS-PAGE/Western blot showed urinary polypeptides abnormality for 90, 80, and 67% of patients, respectively, and for none of the healthy controls. CE-MS indicated a Renal Damage Pattern in 80, 80, and 100 of patients, respectively, and in 17% of healthy controls, with the more specific IgAN Pattern in 90, 90, and 1%, respectively, and in none of the healthy controls. Based on differences in CE-MS patterns, the disease mechanisms may differ among various IgA-associated glomerulonephritides. These exploratory findings should be evaluated in a prospective study with contemporaneous renal biopsy and urinary testing. If validated, it may be feasible to adapt the CE-MS methodology to develop novel tests to detect renal injury at earlier stages, assess clinical manifestations, and monitor responses to therapy in patients with IgA-associated renal diseases.

Clinical proteomics: discovery of cancer biomarkers using mass spectrometry and bioinformatics approaches--a prostate cancer perspective

Prostate cancer (PCa) is an intractable disease, where diagnosis and clinical prediction of the disease course and response to treatment is compromised by the lack of objective and robust biomarker assays. In late stage metastatic disease, treatment options are limited, although it is recognized that some patients may benefit from immunotherapy and in particular vaccine therapy. However, research into biomarkers that correlate with the clinical outcome of immunotherapy has lagged behind vaccine development. Thus, proteomic tools are increasingly being utilized for the discovery of biomarkers which will allow us to make clinical decisions about patient treatment at an earlier stage and should aid in shortening the development time for vaccines. In this review we will summarize the various proteomic platforms used to investigate new biomarkers in PCa for better patient diagnosis, prognosis, patient stratification, treatment monitoring and clinical surrogate endpoints. We will discuss method limitations and highlight the key areas of research required for understanding the etiology of PCa.

Analyses of intricate kinetics of the serum proteome during and after colon surgery by protein expression time series

Monitoring changes in serum protein expression in response to acute events such as trauma, infection or drug intervention may reveal key proteins of great value in predicting recovery or treatment response. Concerted actions of many proteins are expected. Proteins sharing similar expression changes may function in the same physiological process. As a model we analyzed expression changes in serum of colon cancer patients, before, during, and after laparoscopic colon resection. Eight samples were taken from each of four patients before, during, and up to 5 days after surgery. Total serum and a low molecular weight fraction were analyzed by SELDI-TOF-MS. In total 146 masses were detected. A principal components analysis (PCA) illustrates the temporal variation in the postsurgery proteome. Time series for each mass could be clustered into four distinct groups based on similarity in expression pattern. Two masses of 11.4 and 11.6 kDa, part of a slow response cluster, were identified as forms of the acute phase protein serum amyloid A (SAA). Fourteen more proteins belong to this cluster and may also function in acute phase response. We present an approach to analyze temporal variation in the proteome. This approach may be useful to evaluate surgical, nutritional, and pharmacological interventions.

Proteomics in cancer

Proteomic studies have generated numerous datasets of potential diagnostic, prognostic, and therapeutic significance in human cancer. Two key technologies underpinning these studies in cancer tissue are two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Although surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF)-MS is the mainstay for serum or plasma analysis, other methods including isotope-coded affinity tag technology, reverse-phase protein arrays, and antibody microarrays are emerging as alternative proteomic technologies. Because there is little overlap between studies conducted with these approaches, confirmation of these advanced technologies remains an elusive goal. This problem is further exacerbated by lack of uniform patient inclusion and exclusion criteria, low patient numbers, poor supporting clinical data, absence of standardized sample preparation, and limited analytical reproducibility (in particular of 2D-PAGE). Despite these problems, there is little doubt that the proteomic approach has the potential to identify novel diagnostic biomarkers in cancer. In therapeutic proteomics, the challenge is significant due to the complexity systems under investigation (i.e., cells generate over 10(5) different polypeptides). However, the most significant contribution of therapeutic proteomics research is expected to derive not from single experiments, but from the synthesis and comparison of large datasets obtained under different conditions (e.g., normal, inflammation, cancer) and in different tissues and organs. Thus, standardized processes for storing and retrieving data obtained with different technologies by different research groups will have to be developed. Shifting the emphasis of cancer proteomics from technology development and data generation to careful study design, data organization, formatting, and mining is crucial to answer clinical questions in cancer research.

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.

Genomics and proteomics: emerging technologies in clinical cancer research

Fueled by the complete genomic data acquired from the human genome project and the desperate clinical need of comprehensive analytical tools to study a heterogeneous disease like cancer, genomic and proteomic technologies have evolved rapidly, accelerating the rate and number of discoveries in clinical cancer research. These discoveries include mechanistic understanding of cancer biology as well as the identification of biomarkers supporting early detection, molecular classification of tumors, molecular predictors of metastasis, treatment response, and prognosis. While the technical advances have been significant, clinical researchers and practicing physicians are now confronted with the challenges of understanding technically and statistically complex data sets, translating this complex information to fit clinical contexts and incorporating it into clinical studies. In this review, we will summarize the available technologies and associated bioinformatics, discuss studies that are clinically relevant, and discuss the limitations we are still facing. We will present a framework for future directions of these technologies and how we believe they should be applied in clinical studies.