Antibody array profiling reveals serum TSP-1 as a marker to distinguish benign from malignant prostatic disease

The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery

Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.

On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances

Prostate cancer (PC) is a leading cause of morbidity and mortality among men worldwide. Molecular biomarkers work in conjunction with existing clinicopathologic tools to help physicians decide who to biopsy, re-biopsy, treat, or re-treat. The past decade has witnessed the commercialization of multiple PC protein biomarkers with improved performance, remarkable progress in proteomic technologies for global discovery and targeted validation of novel protein biomarkers from clinical specimens, and the emergence of novel, promising PC protein biomarkers. In this review, we summarize these advances and discuss the challenges and potential solutions for identifying and validating clinically useful protein biomarkers in PC diagnosis and prognosis. The identification of multi-protein biomarkers with high sensitivity and specificity, as well as their integration with clinicopathologic parameters, imaging, and other molecular biomarkers, bodes well for optimal personalized management of PC patients.

Analytical performance of thrombospondin-1 and cathepsin D immunoassays part of a novel CE-IVD marked test as an aid in the diagnosis of prostate cancer

The Prostate Specific Antigen (PSA) test suffers from low specificity for the diagnosis of Prostate Cancer (PCa). We originally discovered two cancer-related proteins thrombospondin-1 (THBS1) and cathepsin D (CTSD) using a mass-spectrometry-based proteomics approach. The two serum proteins were shown to improve the diagnosis of high-grade PCa. Thus, we developed quantitative ELISAs for the determination of their concentration in human serum. Here we report their analytical performance in terms of limit of detection, specificity, precision, linearity and interferences, which were determined based on CLSI guidelines. Further, we investigated the influence of pre-analytical factors on concentration measurements. For this, blood from 4-6 donors was collected in different tubes and stored at room temperature for different times prior to centrifugation at different centrifugal forces and temperatures. Stability of THBS1 and CTSD under different storage temperatures was also evaluated. Our results show that the assays are specific, linear and sensitive enough to allow measurement of clinical samples. Precision in terms of repeatability and total within-laboratory coefficient of variation (CV) are 5.5% and 8.1% for THBS1 and 4.3% and 7.2% for CTSD, respectively. Relative laboratory-to-laboratory differences were -6.3% for THBS1 and -3% for CTSD. Both THBS1 and CTSD were stable in serum samples, with 80-120% recoveries of concentrations across donors, sample preparation and storage. In conclusion, the ELISAs as part of the novel commercial in vitro diagnostic test Proclarix are suitable for the use in clinical practice. THBS1 and CTSD can be accurately measured for their intended use independent of the lot and laboratory when conditions consistent with routine practice for PSA sampling and storage are used.

Personalization of prostate cancer therapy through phosphoproteomics

Castration-resistant prostate cancer (CRPC) remains incurable despite the approval of several new treatments. Identification of new biomarkers and therapeutic targets to enable personalization of CRPC therapy, with the aim of maximizing therapeutic responses and minimizing toxicity in patients, is urgently needed. Prostate cancer progression and therapeutic resistance are frequently driven by aberrantly activated kinase signalling pathways that are amenable to pharmacological inhibition. Personalized phosphoproteomics, which enables the analysis of signalling networks in individual tumours, is a promising approach to advance personalized therapy by discovering biomarkers of pathway activity and clinically actionable targets. Several technologies for global and targeted phosphoproteomic analysis exist, each with its own strengths and shortcomings. Global discovery phosphoproteomics is predominantly conducted using liquid chromatography-tandem mass spectrometry coupled with data-dependent or data-independent acquisition technologies. Multiplexed targeted phosphoproteomics can be divided into platforms based on mass spectrometry or antibodies, including selected or parallel reaction monitoring and triggered by offset, multiplexed, accurate mass, high-resolution, absolute quantification (known as TOMAHAQ) or forward-phase or reverse-phase protein arrays, respectively. Several obstacles still need to be overcome before the full potential of phosphoproteomics can be realized in routine clinical practice, but a future phosphoproteomics-centric trans-omic profiling approach should enable optimized personalized CRPC management through improved biomarkers and targeted treatments.

Development and clinical testing of individual immunoassays for the quantification of serum glycoproteins to diagnose prostate cancer

Prostate Cancer (PCa) diagnosis is currently hampered by the high false-positive rate of PSA evaluations, which consequently may lead to overtreatment. Non-invasive methods with increased specificity and sensitivity are needed to improve diagnosis of significant PCa. We developed and technically validated four individual immunoassays for cathepsin D (CTSD), intercellular adhesion molecule 1 (ICAM1), olfactomedin 4 (OLFM4), and thrombospondin 1 (THBS1). These glycoproteins, previously identified by mass spectrometry using a Pten mouse model, were measured in clinical serum samples for testing the capability of discriminating PCa positive and negative samples. The development yielded 4 individual immunoassays with inter and intra-variability (CV) <15% and linearity on dilution of the analytes. In serum, ex vivo protein stability (<15% loss of analyte) was achieved for a duration of at least 24 hours at room temperature and 2 days at 4°C. The measurement of 359 serum samples from PCa positive (n = 167) and negative (n = 192) patients with elevated PSA (2-10 ng/ml) revealed a significantly improved accuracy (P <0.001) when two of the glycoproteins (CTSD and THBS1) were combined with %fPSA and age (AUC = 0.8109; P <0.0001; 95% CI = 0.7673-0.8545). Conclusively, the use of CTSD and THBS1 together with commonly used parameters for PCa diagnosis such as %fPSA and age has the potential to improve the diagnosis of PCa.

Inorganic Arsenic-Related Changes in the Stromal Tumor Microenvironment in a Prostate Cancer Cell-Conditioned Media Model

BACKGROUND

The tumor microenvironment plays an important role in the progression of cancer by mediating stromal-epithelial paracrine signaling, which can aberrantly modulate cellular proliferation and tumorigenesis. Exposure to environmental toxicants, such as inorganic arsenic (iAs), has also been implicated in the progression of prostate cancer.

OBJECTIVE

The role of iAs exposure in stromal signaling in the tumor microenvironment has been largely unexplored. Our objective was to elucidate molecular mechanisms of iAs-induced changes to stromal signaling by an enriched prostate tumor microenvironment cell population, adipose-derived mesenchymal stem/stromal cells (ASCs).

RESULTS

ASC-conditioned media (CM) collected after 1 week of iAs exposure increased prostate cancer cell viability, whereas CM from ASCs that received no iAs exposure decreased cell viability. Cytokine array analysis suggested changes to cytokine signaling associated with iAs exposure. Subsequent proteomic analysis suggested a concentration-dependent alteration to the HMOX1/THBS1/TGFβ signaling pathway by iAs. These results were validated by quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) and Western blotting, confirming a concentration-dependent increase in HMOX1 and a decrease in THBS1 expression in ASC following iAs exposure. Subsequently, we used a TGFβ pathway reporter construct to confirm a decrease in stromal TGFβ signaling in ASC following iAs exposure.

CONCLUSIONS

Our results suggest a concentration-dependent alteration of stromal signaling: specifically, attenuation of stromal-mediated TGFβ signaling following exposure to iAs. Our results indicate iAs may enhance prostate cancer cell viability through a previously unreported stromal-based mechanism. These findings indicate that the stroma may mediate the effects of iAs in tumor progression, which may have future therapeutic implications.

CITATION

Shearer JJ, Wold EA, Umbaugh CS, Lichti CF, Nilsson CL, Figueiredo ML. 2016. Inorganic arsenic-related changes in the stromal tumor microenvironment in a prostate cancer cell-conditioned media model. Environ Health Perspect 124:1009-1015; http://dx.doi.org/10.1289/ehp.1510090.

Antibody-Array-Based Proteomic Screening of Serum Markers in Systemic Lupus Erythematosus: A Discovery Study

A discovery study was carried out where serum samples from 22 systemic lupus erythematosus (SLE) patients and matched healthy controls were hybridized to antibody-coated glass slide arrays that interrogated the level of 274 human proteins. On the basis of these screens, 48 proteins were selected for ELISA-based validation in an independent cohort of 28 SLE patients. Whereas AXL, ferritin, and sTNFRII were significantly elevated in patients with active lupus nephritis (LN) relative to SLE patients who were quiescent, other molecules such as OPN, sTNFRI, sTNFRII, IGFBP2, SIGLEC5, FAS, and MMP10 exhibited the capacity to distinguish SLE from healthy controls with ROC AUC exceeding 90%, all with p < 0.001 significance. These serum markers were next tested in a cohort of 45 LN patients, where serum was obtained at the time of renal biopsy. In these patients, sTNFRII exhibited the strongest correlation with eGFR (r = -0.50, p = 0.0014) and serum creatinine (r = 0.57, p = 0.0001), although AXL, FAS, and IGFBP2 also correlated with these clinical measures of renal function. When concurrent renal biopsies from these patients were examined, serum FAS, IGFBP2, and TNFRII showed significant positive correlations with renal pathology activity index, while sTNFRII displayed the highest correlation with concurrently scored renal pathology chronicity index (r = 0.57, p = 0.001). Finally, in a longitudinal cohort of seven SLE patients examined at ∼3 month intervals, AXL, ICAM-1, IGFBP2, SIGLEC5, sTNFRII, and VCAM-1 demonstrated the ability to track with concurrent disease flare, with significant subject to subject variation. In summary, serum proteins have the capacity to identify patients with active nephritis, flares, and renal pathology activity or chronicity changes, although larger longitudinal cohort studies are warranted.

Identification of plasma protein profiles associated with risk groups of prostate cancer patients

PURPOSE

Early detection of prostate cancer (PC) using prostate-specific antigen (PSA) in blood reduces PC-death among unscreened men. However, due to modest specificity of PSA at commonly used cut-offs, there are urgent needs for additional biomarkers contributing enhanced risk classification among men with modestly elevated PSA.

EXPERIMENTAL DESIGN

Recombinant antibody microarrays were applied for protein expression profiling of 80 plasma samples from routine PSA-measurements, a priori divided into four risk groups, based on levels of total and %free PSA.

RESULTS

The results demonstrated that plasma protein profiles could be identified that pin-pointed PC (a malignant biomarker signature) and most importantly that showed moderate to high correlation with biochemically defined PC risk groups. Notably, the data also implied that the risk group with midrange PSA and low %free PSA, a priori known to be heterogeneous, could be further stratified into two subgroups, more resembling the lowest and highest risk groups, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE

In this pilot study, we have shown that plasma protein biomarker signatures, associated with risk groups of PC, could be identified from crude plasma samples using affinity proteomics. This approach could in the longer perspective provide novel opportunities for improved risk classification of PC patients.

High-throughput proteomics using antibody microarrays: an update

Antibody-based microarrays are a rapidly emerging technology that has advanced from the first proof-of-concept studies to demanding serum protein profiling applications during recent years, displaying great promise within disease proteomics. Miniaturized micro- and nanoarrays can be fabricated with an almost infinite number of antibodies carrying the desired specificities. While consuming only minute amounts of reagents, multiplexed and ultrasensitive assays can be performed targeting high- as well as low-abundance analytes in complex nonfractionated proteomes. The microarray images generated can then be converted into protein expression profiles or protein atlases, revealing a detailed composition of the sample. The technology will provide unique opportunities for fields such as disease diagnostics, biomarker discovery, patient stratification, predicting disease recurrence and drug target discovery. This review describes an update of high-throughput proteomics, using antibody-based microarrays, focusing on key technological advances and novel applications that have emerged over the last 3 years.

The application of monoclonal antibodies in cancer diagnosis

Cancer becomes the second leading cause of death in the world. An effective strategy for early diagnosis of the disease is key to reduce the mortality and morbidity. Development of effective monoclonal antibody (mAb)-based assays or diagnostic imaging techniques for detection of antigens and small molecules that are released from cancerous cells will enhance modern diagnostic medicine of cancer significantly. Although mAb technology is still under development, recent advances in preparation of recombinant antigen and antibody engineering techniques have dramatically enhanced the applications of this technology in cancer diagnosis. Compared with other methods, mAb-based assays may provide spatial, temporal, accurate and quantitative measurement for diagnosis of the disease. This review summarizes the progress of the mAb-based assays in the field of molecular diagnosis of cancer.

Relation between serum thrombospondin-2 and cardiovascular mortality in older men screened for abdominal aortic aneurysm

Thrombospondin-1 and -2 (TSP-1 and -2) have been implicated in the regulation of angiogenesis, thrombosis, and inflammation, which are believed to be critical in the pathogenesis of cardiovascular events. The aim of this study was to assess whether serum TSP-1 and TSP-2 concentrations were associated with cardiovascular mortality in older men. A cohort of 992 elderly men was recruited between 2001 and 2004, and blood was collected for assessment of serum TSP-1 and TSP-2 by immunoassay. The men were followed by means of the Western Australia Data Linkage System until July 31, 2009. The association of TSP-1 and TSP-2 with mortality was assessed using Kaplan-Meier estimates and Cox proportional hazard analysis. Serum TSP-2 quartile was strongly positively associated with all-cause and cardiovascular mortality. Men with serum TSP-2 in the first, second, third, and fourth quartiles had a cumulative incidence of cardiovascular mortality of 3.3%, 8.0%, 9.7%, and 12.5% at 5 years, respectively, p = 0.001. Men with serum TSP-2 in the highest quartile had a 3.37-fold (95% confidence interval: 1.53-7.44, p = 0.003) increased risk of cardiovascular mortality after adjusting for other cardiovascular risk factors. Most deaths were secondary to cardiac causes, and serum TSP-2 was also independently associated with cardiac mortality (relative risk: 3.55, 95% confidence interval: 1.54-8.20 for men in the top compared with the lowest quartile). Serum TSP-1 was not associated with cardiovascular mortality. In conclusion, increased serum TSP-2 concentration is independently and significantly associated with the risk of cardiac mortality in older men.

A call for a fresh new look at the plasma proteome

Serum and plasma from which serum is derived represent a substantial challenge for proteomics due to their complexity. A landmark plasma proteome study was initiated a decade ago by the Human Proteome Organization (HUPO) that had as an objective to examine the capabilities of existing technologies. Given the advances in proteomics and the continued interest in the plasma proteome, it would timely reassess the depth and breadth of analysis of plasma that can be achieved with current methodology and instrumentation. A collaborative project to define the plasma proteome and its variation, with a plan to build a plasma proteome database would be timely.

Discovery of cancer biomarkers using antibody arrays

BACKGROUND

The cancer biomarkers field is being enriched by molecular profiling obtained by high-throughput approaches. In the context of other proteomic technologies, targeted antibody arrays are contributing strongly to the identification of protein cancer biomarker candidates.

OBJECTIVE

To describe innovative strategies multiplexing protein measurements of protein extracts of cultured cells, tissue and body fluids using antibody arrays that, combined with appropriate validation approaches, are enabling the discovery of cancer-associated biomarkers.

METHOD

The strategies and cancer biomarker candidates identified using antibody arrays reported so far that may assist in the diagnosis, surveillance and prognosis, and potentially for predictive and therapeutic purposes for patients affected with solid and hematological neoplasias.

RESULTS/CONCLUSION

Owing to their versatility, novel technological and experimental design implementations are broadening the applications of antibody arrays also for biomarker discovery. However, the cancer biomarker candidates delivered so far using this technology are still at an early developmental phase, requiring validation with many specimens focusing on specific clinical end points.

Integrative proteomic profiling of protein activity and interactions using protein arrays

Proteomic studies based on abundance, activity, or interactions have been used to investigate protein functions in normal and pathological processes, but their combinatory approach has not been attempted. We present an integrative proteomic profiling method to measure protein activity and interaction using fluorescence-based protein arrays. We used an on-chip assay to simultaneously monitor the transamidating activity and binding affinity of transglutaminase 2 (TG2) for 16 TG2-related proteins. The results of this assay were compared with confidential scores provided by the STRING database to analyze the functional interactions of TG2 with these proteins. We further created a quantitative activity-interaction map of TG2 with these 16 proteins, categorizing them into seven groups based upon TG2 activity and interaction. This integrative proteomic profiling method can be applied to quantitative validation of previously known protein interactions, and in understanding the functions and regulation of target proteins in biological processes of interest.

Antibody microarrays as tools for biomarker discovery

The cancer biomarkers field is being enriched by molecular profiling obtained by high-throughput approaches. Targeted antibody arrays are strongly contributing to the identification of protein cancer -biomarker candidates and functional proteomic analyses. Due to their versatility, novel technological and experimental design implementations are broadening the applications of antibody arrays. However, the cancer biomarker candidates delivered to date using this technology are still in their early developmental phase, requiring validation with high number of specimens focusing on specific clinical endpoints. Innovative strategies multiplexing protein measurements of protein extracts of cultured cells, tissue and body fluids using antibody arrays combined with appropriate validation approaches are enabling the -discovery of cancer-associated biomarkers. This review describes these strategies and cancer biomarker candidates reported to date that may assist in the diagnosis, surveillance, prognosis, and potentially for predictive and therapeutic purposes for patients affected with solid and hematological neoplasias.

Normalization using a tagged-internal standard assay for analysis of antibody arrays and the evaluation of serological biomarkers for liver disease

For minimizing systemic experimental variation in the analysis of antibody array data, we developed a novel median-centered/IgM-tagged-internal standard (TIS) assay normalization using median-centering and TIS assay-based determination of serum IgM concentrations. We evaluated five normalization methods by analyzing correlation coefficients and coefficients of variation for six serum proteins using human serum samples from normal controls (n=25) and patients with liver cirrhosis (n=25) or hepatocellular carcinoma (HCC; n=29). Median-centered normalization improved correlation coefficients, while IgM-based normalizations improved coefficients of variation. The TIS assay was more efficient, economical, and reproducible for determining IgM concentrations than enzyme-linked immunosorbent assay. Additionally, we normalized antibody array data for six serum proteins using the median-centered/IgM-TIS assay, and evaluated serum biomarkers through distribution analysis of normalized fluorescence intensities and receiver operating characteristic analyses for the diagnosis of liver cirrhosis and HCC. Apolipoprotein A-1 and a combination of alpha-fetoprotein and C-reactive protein were determined to be potential serological biomarkers for liver cirrhosis and HCC, respectively. Thus, median-centered/IgM-TIS assay normalization is a useful approach for analyzing antibody array data and evaluating serological biomarkers for the diagnosis of liver disease or cancers.

Antibody array analysis of labelled proteomes: how should we control specificity?

Researchers who use protein binders in multiplexed assays can be divided into two camps. One believes that arrays with proteome-wide coverage will become a reality once we have developed binders for all proteins. The sceptics claim that detection with immobilized protein binders and sample labelling will not provide the required specificity. In this article, we review the evidence showing that antibody array analysis of labelled samples can provide meaningful data and discuss the issues raised by the sceptics. We argue that direct the evidence for monospecificity has yet to be published. This will require assays designed to resolve the proteins captured by each binder. One option is to combine array measurement with protein separation. We have developed an assay where labelled sample proteins are separated by size exclusion chromatography (SEC) before contact with microsphere-based arrays (Size-MAP; size exclusion chromatography-resolved microsphere-based affinity proteomics). The effect is an 'antibody array Western blot' where reactivity of immobilized binders is resolved against the size of the proteins in the sample. We show that Size-MAP is useful to discriminate monospecific- and polyreactive antibodies and for automatic detection of reacting with the same target. The possibility to test specificity directly in array-based measurement should be useful to select the best binders and to determine whether the DNA microarray for the proteome is a realistic goal or not.

Novel prognostic markers in the serum of patients with castration-resistant prostate cancer derived from quantitative analysis of the pten conditional knockout mouse proteome

BACKGROUND

Metastatic castration-resistant prostate cancer (mCRPC) is associated with a poor outcome. Prognostic information is useful and aids treatment decisions. However, current nomograms based on clinical parameters alone have weak prognostic accuracy. Therefore, the identification of new prognostic serum biomarkers could be useful.

OBJECTIVES

To assess if quantitative analysis of the phosphatase and tensin homolog (Pten) conditional knockout mouse proteome reveals significant prognostic biomarkers in mCRPC and to compare the accuracy of these biomarkers with known prognostic factors.

DESIGN, SETTING, AND PARTICIPANTS

Fifty-seven patients with mCRPC were evaluated retrospectively. Prognostic factors used in clinical nomograms were assessed from the records. New candidate biomarkers in patients' sera were derived using a cancer genetics-guided model we recently described, screening the murine Pten-dependent glycoproteome.

MEASUREMENTS

Quantification in patients' sera was performed by either mass spectrometry-based targeted proteomics or enzyme-linked immunosorbent assays. Prognostic biomarkers for survival were identified based on Kaplan-Meier models. In a second step, random forest analysis was performed to identify a prognostic signature combined from the pooled data of known predictors and newly identified biomarkers.

RESULTS AND LIMITATIONS

With univariate analysis, 13 new significant prognostic factors for survival in the sera of mCRPC patients were found with a Bonferroni-corrected level of significance <5%. Random forest analysis revealed a five-factor predictor (thrombospondin 1; C-reactive protein; poliovirus receptor-related 1; ephrin-A5; and membrane metallo-endopeptidase) with an accuracy of 96% and 94% for 12- and 24-mo survival, respectively. This means that, in our dataset, the error was reduced by 15% compared to using the Halabi et al. nomogram. The retrospective nature of the work and absence of a validating dataset is the major limitation of this work.

CONCLUSIONS

Analysis of the serum proteome in mCRPC patients based on our Pten conditional knockout model, combined with known prognostic factors, potentially improves accuracy of prognostic nomograms. These newly identified markers have to be validated in prospective studies.

Proteomic analysis and discovery using affinity proteomics and mass spectrometry

Antibody-based microarrays are a rapidly evolving affinity-proteomic methodology that recently has shown great promise in clinical applications. The resolution of these proteomic analyses is, however, directly related to the number of data-points, i.e. antibodies, included on the array. Currently, this is a key bottleneck because of limited availability of numerous highly characterized antibodies. Here, we present a conceptually new method, denoted global proteome survey, opening up the possibility to probe any proteome in a species-independent manner while still using a limited set of antibodies. We use context-independent-motif-specific antibodies directed against short amino acid motifs, where each motif is present in up to a few hundred different proteins. First, the digested proteome is exposed to these antibodies, whereby motif-containing peptides are enriched, which then are detected and identified by mass spectrometry. In this study, we profiled extracts from human colon tissue, yeast cells lysate, and mouse liver tissue to demonstrate proof-of-concept.

Toward next generation plasma profiling via heat-induced epitope retrieval and array-based assays

There is a need for high throughput methods for screening patient samples in the quest for potential biomarkers for diagnostics and patient care. Here, we used a combination of undirected target selection, antibody suspension bead arrays, and heat-induced epitope retrieval to allow for protein profiling of human plasma in a novel and systematic manner. Several antibodies were found to reveal altered protein profiles upon epitope retrieval at elevated temperatures with limits of detection improving into lower ng/ml ranges. In a study based on prostate cancer patients, several proteins with differential profiles were discovered and subsequently validated in an independent cohort. For one of the potential biomarkers, the human carnosine dipeptidase 1 protein (CNDP1), the differences were determined to be related to the glycosylation status of the targeted protein. The study shows a path of pursuit for large scale screening of biobank repositories in a flexible and proteome-wide fashion by utilizing heat-induced epitope retrieval and using an antibody suspension bead array format.

Thrombospondin-1 regulates the normal prostate in vivo through angiogenesis and TGF-beta activation

Castration experiments in rodents show that the stromal vasculature is critical to the androgen-mediated prostate growth regulation. However, the role of angiogenesis inhibitors, such as thrombospondin-1 (TSP-1), in this process is unclear. TSP-1 is a multifunctional glycoprotein that can function as a potent angiogenesis inhibitor and an in vivo activator of latent transforming growth factor-beta (TGF-beta) in some tissues. On the basis of these observations, we hypothesized that TSP-1 regulated androgen withdrawal-induced prostate regression and that this process was mediated not only through antiangiogenic activity but also through TGF-beta activation. To test this, we evaluated angiogenic activity in human prostate epithelial and stromal cells treated with androgens and hypoxia in vitro. TSP-1 knockout mice were characterized to investigate the in vivo functions of TSP-1. In vitro, we found that androgens and hypoxia differentially regulated TSP-1 and angiogenic activity. Androgens stimulated normal epithelial cell, but inhibited normal stromal cell, angiogenic activity. Conversely, hypoxia stimulated stromal while inhibiting epithelial activity. Thus, in vivo, net angiogenic activity must reflect cellular interactions. And, we found that media conditioned by epithelial cells grown under normoxic conditions stimulated stromal cell angiogenic activity, and if epithelial cells were grown under hypoxic conditions, stromal activity was further increased. TSP-1 levels, however, were unchanged. In vivo, TSP-1 loss in a mouse model led to prostate epithelial hyperplasia by 3 months of age with only a modest stromal effect. Androgens suppressed TSP-1 as expression increased after castration both in normal mouse prostate and in human prostate cancer tissues. In addition, TSP-1 expression corresponded to increased TGF-beta activation in mouse tissues, specifically in the stromal compartment. These data show a critical role for TSP-1 in prostate epithelial and stromal growth regulation through angiogenic inhibition and activation of latent TGF-beta. Therefore, loss of TSP-1 during tumorigenesis would eliminate two barriers to cancer progression.

Development of high-yield autofluorescent protein microarrays using hybrid cell-free expression with combined Escherichia coli S30 and wheat germ extracts

Background

Protein-based microarray platforms offer considerable promise as high-throughput technologies in proteomics. Particular advantages are provided by self-assembling protein microarrays and much interest centers around analysis of eukaryotic proteins and their molecular interactions. Efficient cell-free protein synthesis is paramount for the production of self-assembling protein microarrays, requiring optimal transcription, translation, and protein folding. The Escherichia coli S30 extract demonstrates high translation rates but lacks the protein-folding efficiency of its eukaryotic counterparts derived from rabbit reticulocyte and wheat germ extract. In comparison to E. coli, eukaryotic extracts, on the other hand, exhibit slower translation rates and poor overall protein yields. A cell-free expression system that synthesizes folded eukaryotic proteins in considerable yields would optimize in vitro translation for protein microarray assembly.

Results

Self-assembling autofluorescent protein microarrays were produced by in situ transcription and translation of chimeric proteins containing a C-terminal Green Fluorescent Protein tag. Proteins were immobilized as array elements using an anti-GFP monoclonal antibody. The amounts of correctly-folded chimeric proteins were quantified by measuring the fluorescence intensity from each array element. During cell-free expression, very little or no fluorescence was observed from GFP-tagged multidomain eukaryotic plant proteins when in vitro translation was performed with E. coli S30 extract. Improvement was seen using wheat germ extract, but fluorescence intensities were still low because of poor protein yields. A hybrid in vitro translation system, combining S30 and wheat germ extracts, produced high levels of correctly-folded proteins for most of the constructs that were tested.

Conclusion

The results are consistent with the hypothesis that the wheat germ extract enhances the protein folding capabilities of the in vitro system by providing eukaryotic ribosomes and chaperones and, at the same time, the E. coli S30 extract, which includes an ATP regeneration system, translates the polypeptides at high rates. This hybrid cell-free expression system allows the facile production of high-yield protein arrays suitable for downstream assays.

Protein-protein interactions and selection: array-based techniques for screening disease-associated biomarkers in predictive/early diagnosis

There has been considerable interest in recent years in the development of miniaturized and parallelized array technology for protein-protein interaction analysis and protein profiling, namely 'protein-detecting microarrays'. Protein-detecting microarrays utilize a wide variety of capture agents (antibodies, fusion proteins, DNA/RNA aptamers, synthetic peptides, carbohydrates, and small molecules) immobilized at high spatial density on a solid surface. Each capture agent binds selectively to its target protein in a complex mixture, such as serum or cell lysate samples. Captured proteins are subsequently detected and quantified in a high-throughput fashion, with minimal sample consumption. Protein-detecting microarrays were first described by MacBeath and Schreiber in 2000, and the number of publications involving this technology is rapidly increasing. Furthermore, the first multiplex immunoassay systems have been cleared by the US Food and Drug Administration, signaling recognition of the usefulness of miniaturized and parallelized array technology for protein detection in predictive/early diagnosis. Although genetic tests still predominate, with further development protein-based diagnosis will become common in clinical use within a few years.

Angiogenesis as a strategic target for prostate cancer therapy

It is becoming increasingly clear that angiogenesis plays a crucial role in prostate cancer (CaP) survival, progression, and metastasis. Tumor angiogenesis is a hallmark of advanced cancers and an attractive treatment target in multiple solid tumors. By understanding the molecular basis of resistance to androgen withdrawal and chemotherapy in CaP, the rational design of targeted therapeutics is possible. This review summarizes the recent advancements that have improved our understanding of the role of angiogenesis in CaP metastasis and the potential therapeutic efficacy of inhibiting angiogenesis in this disease. Current therapeutic options for patients with metastatic hormone-refractory CaP are very limited. Targeting vasculature is a developing area, which shows promise for the control of late stage and recurrent CaP disease and for overcoming drug resistance. We discuss angiogenesis and its postulated mechanisms and focus on the regulation of angiogenesis in CaP progression and the therapeutic beneficial effects associated with targeting of the CaP vasculature to overcome the resistance to current treatments and CaP recurrence.

Cancer biomarkers: are we ready for the prime time?

A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In cancer, a biomarker refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Genetic, epigenetic, proteomic, glycomic, and imaging biomarkers can be used for cancer diagnosis, prognosis and epidemiology. These markers can be assayed in non-invasively collected biofluids. However, few cancer biomarkers are highly sensitive and specific for cancer detection at the present time. Consequently, biomarkers are not yet ready for routine use due to challenges in their clinical validation for early disease detection, diagnosis and monitoring to improve long-term survival of patients.

Validation of serum protein profiles by a dual antibody array approach

In recent years, affinity-based technologies have become important tools for serum profiling to uncover protein expression patterns linked to disease state or therapeutic effects. In this study, we describe a path towards the production of an antibody microarray to allow protein profiling of biotinylated human serum samples with reproducible sensitivity in the picomolar range. With the availability of growing numbers of affinity reagents, protein profiles are to be validated in efficient manners and we describe a cross-platform strategy based on data concordance with a suspension bead array to interrogate the identical set of antibodies with the same cohort of serum samples. Comparative analysis enabled to screen for high-performing antibodies, which were displaying consistent results across the two platforms and targeting known serum components. Moreover, data processing methods such as sample referencing and normalization were evaluated for their effects on inter-platform agreement. Our work suggests that mutual validation of protein expression profiles using alternative microarray platforms holds great potential in becoming an important and valuable component in affinity-based high-throughput proteomic screenings as it allows to narrow down the number of discovered targets prior to orthogonal, uniplexed validation approaches.

Oncoproteomic profiling with antibody microarrays

The incidence of cancer and its associated mortality are increasing globally, indicating an urgent need to develop even more effective and sensitive sets of biomarkers that could help in early diagnosis and consequent intervention. Given that many cellular processes are carried out by proteins, cancer research has recently shifted toward an exploration of the full proteome for such discovery. Among the advanced methodologies that are being developed for analyzing the proteome, antibody microarrays have become a prominent tool for gathering the information required for a better understanding of disease biology, early detection, discrimination of tumors and monitoring of disease progression. Here, we review the technical aspects and challenges in the development and use of antibody microarray assays and examine recently reported applications in oncoproteomics.

Design of high-density antibody microarrays for disease proteomics: key technological issues

Antibody-based microarray is a novel proteomic technology setting a new standard for molecular profiling of non-fractionated complex proteomes. The first generation of antibody microarrays has already demonstrated its potential for generating detailed protein expression profiles, or protein atlases, of human body fluids in health and disease, paving the way for new discoveries within the field of disease proteomics. The process of designing highly miniaturized, high-density and high-performing antibody microarray set-ups have, however, proven to be challenging. In this mini-review we discuss key technological issues that must be addressed in a cross-disciplinary manner before true global proteome analysis can be performed using antibody microarrays.

Antibody-based microarrays

Antibody-based microarrays are a new powerful proteomic technology that can be used to generate rapid and detailed expression profiles of defined sets of protein analytes in complex samples as well as high-resolution portraits of entire proteomes. Miniaturized micro- and nanoarrays can be printed with numerous antibodies carrying the desired specificities. Multiplexed and ultra-sensitive assays, specifically targeting several analytes in a single experiment, can be performed, while consuming only minute amounts of the sample. The array images generated can then be converted into protein expression profiles, or maps, revealing the detailed composition of the sample. This promising proteomic research tool will thus provide unique opportunities for e.g. disease proteomics, biomarker discovery, disease diagnostics, and patient stratification. This review describes the antibody-based microarray technology and applications thereof.

Applications of protein microarrays for biomarker discovery

The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.

Detection of pancreatic cancer using antibody microarray-based serum protein profiling

The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects. Furthermore, a potential protein signature, consisting of 21 protein analytes, could be defined that was shown to be associated with cancer patients having a life expectancy of <12 months. Taken together, the data suggest that antibody microarray analysis of complex proteomes will be a useful tool to define disease associated protein signatures.

Clinical application of antibody microarray in chronic kidney disease: How far to go?

Chronic kidney disease (CKD) that affects about 10% of the adult population has been shown as a worldwide public health problem in recent years. Both basic and clinical investigations have identified complex disease-associated protein networks involved in the pathophysiologic processes of CKD. The traditional single-assay approach and proteomic analysis of those related proteins have given birth to a steadily increasing panel of molecules that may have the potential to serve as biomarkers for CKD. However, both approaches suffered from some shortcomings from a technological point of view. Antibody microarray (AbM) is characterized by high sensitivity, specificity, and quantitative ability for a particular set of known proteins. However, its application in CKD has been very limited so far. The objective of this review, therefore, is to address the potential applications of AbM in studying of CKD. We will briefly discuss the proteins involved in the development of CKD, future directions in which AbM approaches would probably display its potential and also some key issues that need to be considered in application of this novel technique.

Mining the plasma proteome for cancer biomarkers

Systematic searches for plasma proteins that are biological indicators, or biomarkers, for cancer are underway. The difficulties caused by the complexity of biological-fluid proteomes and tissue proteomes (which contribute proteins to plasma) and by the extensive heterogeneity among diseases, subjects and levels of sample procurement are gradually being overcome. This is being achieved through rigorous experimental design and in-depth quantitative studies. The expected outcome is the development of panels of biomarkers that will allow early detection of cancer and prediction of the probable response to therapy. Achieving these objectives requires high-quality specimens with well-matched controls, reagent resources, and an efficient process to confirm discoveries through independent validation studies.

Development and use of a partial Mycobacterium avium subspecies paratuberculosis protein array

As an initial step toward systematically characterizing all antigenic proteins produced by a significant veterinary pathogen, 43 recombinant Mycobacterium avium subspecies paratuberculosis (M. paratuberculosis) expression clones were constructed, cataloged, and stored. NC filters were spotted with purified proteins from each clone along with a whole cell lysate of M. paratuberculosis. Spots on the resulting dot array consisted of hypothetical proteins (13), metabolic proteins (3), cell envelope proteins (7), known antigens (4), and unique proteins with no similarity in public sequence databases (16). Dot blot arrays were used to profile antibody responses in a rabbit and mouse exposed to M. paratuberculosis as well as in cattle showing clinical signs of Johne's disease. The M. paratuberculosis heat shock protein DnaK, encoded by ORF MAP3840 and a membrane protein (MAP2121c), were identified as the most strongly immunoreactive in both the mouse and rabbit hosts, respectively. MAP3155c, which encodes a hypothetical protein, was most strongly immunoreactive in sera from Johne's disease cattle. This study has enabled direct comparisons of antibody reactivity for an entire panel of over 40 proteins and has laid the foundation for future high throughput production and arraying of M. paratuberculosis surface proteins for immune profiling experiments in cattle.

Enhanced detection of autoantibodies on protein microarrays using a modified protein digestion technique

High-throughput studies to determine differential immune (humoral) response to diseases are becoming of increasing interest because the information they provide can help in early diagnosis as well as monitoring of therapeutics. Protein microarrays are a high-throughput and convenient technology that can be applied to the study of the humoral response. Proteins can be arrayed on slides and then probed with serum from different classes of patients to observe differences that may exist among autoantibodies that reflect differences in disease states. However, such studies may be difficult to interpret due to the weak overall signal response of such protein microarrays. We propose that this weak signal response is due to the physical positioning of the disease proteins that renders them sterically hindered from binding partners in the serum. In this study, we hypothesize that reducing the complexity and size of the disease proteins by chemical digestion using cyanogen bromide (CNBr) may enhance the overall signal from the humoral response and facilitate visualization of disease-specific responses in various classes of serum. A modified protein microarray methodology using CNBr digestion is presented here. The new workflow was applied to a set of 10 serum samples from healthy subjects, 10 from patients with chronic pancreatitis and 10 from patients diagnosed with pancreatic cancer and the results were compared to results obtained in the absence of CNBr digestion. CNBr digestion allowed the identification of 10 additional autoantibodies that responded to serum, 5 of which were unique to pancreatitis and cancer sera. This new methodology may increase the sensitivity of microarray studies measuring autoantibodies in serum.

Antibody microarray analysis of directly labelled complex proteomes

In recent years, the antibody microarray technology has made significant progress, going from proof-of-concept designs to established high-performing technology platforms capable of targeting non-fractionated complex proteomes. In these cross-disciplinary efforts, a particular focus has lately been placed on two key technological issues: the sample and data handling. To this end, robust protocols have been designed for direct labelling of whole proteomes compatible with a sensitive fluorescent-based sensing. Tagging of the proteins with biotin in a single-colour approach has, in many cases, proven to be the preferred approach. Furthermore, based on modified approaches, adopted from the DNA microarray field, the first bioinformatic standards for performing the antibody microarray data analysis have emerged, though general standard operating procedure(s) remains to be implemented.