Development of a "reverse capture" autoantibody microarray for studies of antigen-autoantibody profiling

Acquisition of useful sero-diagnostic autoantibodies using the same patients'sera and tumor tissues

Cancer tissues are comprised of various components including tumor cells and the surrounding tumor stroma, which consists of the extracellular matrix and inflammatory cells. Since the tumor stroma plays critical roles in tumor development, investigation of the tumor stroma in addition to tumor cells is important to identify useful tumor-associated markers. To discover novel and useful sero-diagnostic markers, a comparative study of tumor-associated autoantibodies (AAbs) in sera from lung adenocarcinoma (AC) patients was investigated by two-dimensional immunoblotting with AC cell lines or each autologous AC tissues. Autoantigens identified from tissue and cell line samples comprised 58 (45 antigens) and 53 spots (41 antigens), respectively. Thirty-six proteins including Transforming growth factor-beta-induced protein ig-h3 (BIGH3) and Hyaluronan and proteoglycan link protein 1 (HAPLN1) were detected only from tissues, 32 proteins only from cell lines, and 9 proteins from both. BIGH3 and HAPLN1 expressions were confirmed in the tumor stroma, but not in AC cell lines by immunostaining and immunoblotting. These data suggest that autologous tumor tissue and serum are important to coincidently detect AAbs derived from the tumor stroma in addition to tumor cells.

Development of a method that eliminates false-positive results due to nerve growth factor interference in the assessment of fulranumab immunogenicity

Fulranumab, a human IgG2 monoclonal antibody that neutralizes nerve growth factor (NGF), is currently in development for the treatment of pain. Our initial immunogenicity test method was found to be prone to NGF interference, leading to a high apparent incidence of anti-drug antibody (ADA) in phase 1 studies. The ADA immunoassay comprised a homogeneous bridging electrochemiluminescence (ECL) format with biotin and ruthenium-labeled fulranumab bound together ("bridged") by ADA in test samples for detection. In this assay, NGF produced a false-positive signal due to its ability to bridge fulranumab molecules. Thus, we developed a specificity assay to eliminate the NGF false-positive results. We encountered the challenge of eliminating drug interference as well as drug target interference, and discovered that the acid-dissociation-based pretreatment of samples used for mitigating drug interference dramatically increased drug target interference. Several strategies were investigated to eliminate the NGF interference; yet only one strategy specifically removed NGF and produced true fulranumab-specific ADA results by using competitive inhibition with fulranumab and utilizing an alternative NGF binding antibody to eliminate NGF interference. Using this new method, we confirmed that the high apparent anti-fulranumab antibody incidence (>60%) in clinical study samples was in fact due to fulranumab-bound NGF released during the acid-dissociation step of the ADA testing method. We conclude that our revised method accurately identifies anti-fulranumab antibodies by incorporating steps to eliminate fulranumab and NGF interference. We advise that acid-dissociation pretreatment must not be universally applied to improve ADA assays without investigating its bioanalytical risks versus benefits.

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.

Serologic autoantibodies as diagnostic cancer biomarkers--a review

Current diagnostic techniques used for the early detection of cancers are successful but subject to detection bias. A recent focus lies in the development of more accurate diagnostic tools. An increase in serologic autoantibody levels has been shown to precede the development of cancer disease symptoms. Therefore, autoantibody levels in patient blood serum have been proposed as diagnostic biomarkers for early-stage diagnosis of cancers. Their clinical application has, however, been hindered by low sensitivity, specificity, and low predictive value scores. These scores have been shown to improve when panels of multiple diagnostic autoantibody biomarkers are used. A five-marker biomarker panel has been shown to increase the sensitivity of prostate cancer diagnosis to 95% as compared with 12.2% for prostate-specific antigen alone. New potential biomarker panels were also discovered for lung, colon, and stomach cancer diagnosis with sensitivity of 76%, 65.4%, and 50.8%, respectively. Studies in breast and liver cancer, however, seem to favor single markers, namely α-2-HS-glycoprotein and des-γ-carboxyprothrombin with sensitivities of 79% and 89% for the early detection of the cancers. The aim of this review is to discuss the relevance of autoantibodies in cancer diagnosis and to outline the current methodologies used in the detection of autoantibodies. The review concludes with a discussion of the autoantibodies currently used in the diagnosis of cancers of the prostate, breast, lung, colon, stomach, and liver. A discussion of the potential future use of autoantibodies as diagnostic cancer biomarkers is also included in this review.

Early lung cancer diagnosis by biosensors

Lung cancer causes an extreme threat to human health, and the mortality rate due to lung cancer has not decreased during the last decade. Prognosis or early diagnosis could help reduce the mortality rate. If microRNA and tumor-associated antigens (TAAs), as well as the corresponding autoantibodies, can be detected prior to clinical diagnosis, such high sensitivity of biosensors makes the early diagnosis and prognosis of cancer realizable. This review provides an overview of tumor-associated biomarker identifying methods and the biosensor technology available today. Laboratorial researches utilizing biosensors for early lung cancer diagnosis will be highlighted.

Tumor-associated autoantibodies as diagnostic and prognostic biomarkers

In the process of tumorigenesis, normal cells are remodeled to cancer cells and protein expression patterns are changed to those of tumor cells. A newly formed tumor microenvironment elicits the immune system and, as a result, a humoral immune response takes place. Although the tumor antigens are undetectable in sera at the early stage of tumorigenesis, the nature of an antibody amplification response to antigens makes tumor-associated autoantibodies as promising early biomarkers in cancer diagnosis. Moreover, the recent development of proteomic techniques that make neo-epitopes of tumor-associated autoantigens discovered concomitantly has opened a new area of ‘immuno-proteomics’, which presents tumor-associated autoantibody signatures and confers information to redefine the process of tumorigenesis. In this article, the strategies recently used to identify and validate serum autoantibodies are outlined and tumor-associated antigens suggested until now as diagnostic/prognostic biomarkers in various tumor types are reviewed. Also, the meaning of autoantibody signatures and their clinical utility in personalized medicine are discussed. [BMB Reports 2012; 45(12): 677-685]

The role of proteomics in prostate cancer research: biomarker discovery and validation

PURPOSE

Prostate Cancer (PCa) represents the second most frequent type of tumor in men worldwide. Incidence increases with patient age and represents the most important risk factor. PCa is mostly characterized by indolence, however in a small percentage of cases (3%) the disease progresses to a metastatic state. To date, the most important issue concerning PCa research is the difficulty in distinguishing indolent from aggressive disease. This problem frequently results in low-grade PCa patient overtreatment and, in parallel; an effective treatment for distant and aggressive disease is not yet available.

RESULT

Proteomics represents a promising approach for the discovery of new biomarkers able to improve the management of PCa patients. Markers more specific and sensitive than PSA are needed for PCa diagnosis, prognosis and response to treatment. Moreover, proteomics could represent an important tool to identify new molecular targets for PCa tailored therapy. Several possible PCa biomarkers sources, each with advantages and limitations, are under investigation, including tissues, urine, serum, plasma and prostatic fluids. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PCa detection, stratification and treatment. Nevertheless, many putative biomarkers are still far from being applied in clinical practice.

CONCLUSIONS

This review aims to discuss the recent advances in PCa proteomics, emphasizing biomarker discovery and their application to clinical utility for diagnosis and patient stratification.

Preliminary study of thyroid and colon cancers-associated antigens and their cognate autoantibodies as potential cancer biomarkers

BACKGROUND

Autoantibodies, which are produced against tumor-associated antigens, are potential tumor markers and attract a growing interest for cancer detection, differential diagnostics and prognosis.

OBJECTIVE

To evaluate the diagnostic significance of 40 antigens identified by immunoscreening of cDNA libraries from thyroid and colon cancers by allogenic screening with different tumor types patients' sera.

METHOD

Plaque-spot serological assay.

RESULTS

Increased frequency of antibody response in sera of cancer patients compared with that of healthy donors was shown toward 14 antigens, 8 of which (CG016, BTN3A3, FKBP4, XRCC4, TSGA2, ACTR1A, FXYD3 and CTSH) have revealed exclusively cancer-related serological profile.

CONCLUSION

Allogenic screening of 40 SEREX-antigens with sera from cancer patients and healthy donors allowed us to reveal 14 antigens with potential diagnostic significance. These antigens and their cognate autoantibodies could be considered as valuable targets for further analysis as potential cancer biomarkers.

Antibody microarrays: analysis of cystic fibrosis

Cystic fibrosis (CF) is the most common autosomal recessive disease in the USA and Europe, whose life-limiting phenotype is manifest on epithelial cells throughout the body. The principal cause of morbidity and mortality is a massively proinflammatory condition in the lung. The mutation responsible for most cases of CF is [ΔF508]CFTR. However, the penetrance of the disease is quite variable, and adverse events leading to hospitalization cannot be easily predicted. Thus, there is a strong need for prognostic endpoints that might serve to identify impending clinical problems long before they happen. Our approach has been to search for proteomic signatures in easily accessed biological fluids that might identify the molecular basis for adverse events. We describe here a workflow that begins with patient-derived bronchial brush biopsies and progresses to analysis of serum and plasma from patients on antibody microarrays.

Autoantibody signatures as biomarkers to distinguish prostate cancer from benign prostatic hyperplasia in patients with increased serum prostate specific antigen

BACKGROUND

Serum prostate specific antigen (PSA) concentrations lack the specificity to differentiate prostate cancer from benign prostate hyperplasia (BPH), resulting in unnecessary biopsies. We identified 5 autoantibody signatures to specific cancer targets which might be able to differentiate prostate cancer from BPH in patients with increased serum PSA.

METHODS

To identify autoantibody signatures as biomarkers, a native antigen reverse capture microarray platform was used. Briefly, well-characterized monoclonal antibodies were arrayed onto nanoparticle slides to capture native antigens from prostate cancer cells. Prostate cancer patient serum samples (n=41) and BPH patient samples (collected starting at the time of initial diagnosis) with a mean follow-up of 6.56 y without the diagnosis of cancer (n=39) were obtained. One hundred micrograms of IgGs were purified and labeled with a Cy3 dye and incubated on the arrays. The arrays were scanned for fluorescence and the intensity was quantified. Receiver operating characteristic curves were produced and the area under the curve (AUC) was determined.

RESULTS

Using our microarray platform, we identified autoantibody signatures capable of distinguishing between prostate cancer and BPH. The top 5 autoantibody signatures were TARDBP, TLN1, PARK7, LEDGF/PSIP1, and CALD1. Combining these signatures resulted in an AUC of 0.95 (sensitivity of 95% at 80% specificity) compared to AUC of 0.5 for serum concentration PSA (sensitivity of 12.2% at 80% specificity).

CONCLUSION

Our preliminary results showed that we were able to identify specific autoantibody signatures that can differentiate prostate cancer from BPH, and may result in the reduction of unnecessary biopsies in patients with increased serum PSA.

Usage of cancer associated autoantibodies in the detection of disease

Efforts toward deciphering the complexity of the tumor specific proteome by profiling immune responses generated against tumor associated antigens (TAAs) holds great promise for predicting the presence of cancer long before the development of clinical symptoms. The immune system is capable of sensing aberrant expression of certain cellular components involved in tumorigenesis and the resultant autoantibody response provides insights to the targets that are responsible for eliciting immunogenicity to these cellular components. Analysis of the cancer-specific humoral immune response has led to panels of biomarkers that are specific and sensitive biomarkers of disease. Using multianalyte-based in vitro analytical discovery platforms which can be easily adapted into clinical diagnostic screening tests, body fluids such as serum, plasma saliva, or urine can be interrogated to detect autoantibodies against natural or recombinant antigens, which may possess etiologic significance to cancer. Non-invasive screening tests exhibiting high specificity and sensitivity to detect early stage cancer in the heterogeneous population of cancer patients potentially have the greatest impact in decreasing mortality rates. Overall, this review summarizes different experimental approaches in the development of diagnostic screening tests for the early detection of cancer and their implementation in the development of clinical multianalyte biomarker assays.

Exploring the immunoproteome for ovarian cancer biomarker discovery

Most scientific efforts towards early detection of ovarian cancer are commonly focused on the discovery of tumour-associated antigens (TAA). Autologous antibodies against TAA, however, may serve as more sensitive diagnostic markers. They circulate in the blood before TAA and are usually more abundant than the TAAs themselves as a result of amplification through the humoral immune response. Accumulating evidence also suggests that a humoral response already exists during malignant transformation when aberrant gene expression is translated into premalignant cellular changes. This article reviews the current knowledge about autoantibodies against TAA in ovarian cancer and presents current immunoproteomic approaches for their detection.

Sequencing and quantifying IgG fragments and antigen-binding regions by mass spectrometry

In cancer and autoimmune diseases, immunoglobulins with a specific molecular signature that could potentially be used as diagnostic or prognostic markers are released into body fluids. An immunomics approach based on this phenomenon relies on the ability to identify the specific amino acid sequences of the complementarity-determining regions (CDR) of these immunoglobulins, which in turn depends on the level of accuracy, resolution, and sensitivity that can be achieved by advanced mass spectrometry. Reproducible isolation and sequencing of antibody fragments (e.g., Fab) by high-resolution mass spectrometry (MS) from seven healthy donors revealed 43 217 MS signals: 225 could be associated with CDR1 peptides, 513 with CDR2 peptides, and 19 with CDR3 peptides. Seventeen percent of the 43 217 MS signals did not overlap between the seven donors. The Fab isolation method used is reproducible and fast, with a high yield. It provides only one Fab sample fraction for subsequent characterization by high-resolution MS. In 17% and 4% of these seven healthy donors, qualitative (presence/absence) and quantitative (intensity) differences in Fab fragments could be demonstrated, respectively. From these results, we conclude that the identification of a CDR signature as biomarker for autoimmune diseases and cancer without prior knowledge of the antigen is feasible.

Anti-CDC25B autoantibody predicts poor prognosis in patients with advanced esophageal squamous cell carcinoma

Background

The oncogene CDC25B phosphatase plays an important role in cancer cell growth. We have recently reported that patients with esophageal squamous cell carcinoma (ESCC) have significantly higher serum levels of CDC25B autoantibodies (CDC25B-Abs) than both healthy individuals and patients with other types of cancer; however, the potential diagnostic or prognostic significance of CDC25B-Abs is not clear. The aim of this study is to evaluate the clinical significance of serum CDC25B-Abs in patients with ESCC.

Methods

CDC25B autoantibodies were measured in sera from both 134 patients with primary ESCC and 134 healthy controls using a reverse capture enzyme-linked immunosorbent assay (ELISA) in which anti-CDC25B antibodies bound CDC25B antigen purified from Eca-109 ESCC tumor cells. The clinicopathologic significance of CDC25B serum autoantibodies was compared to that of the tumor markers carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC-Ag) and cytokeratin 19 fragment antigen 21-1(CYFRA21-1).

Results

Higher levels of CDC25B autoantibodies were present in sera from patients with ESCC (A₄₅₀ = 0.917, SD = 0.473) than in sera from healthy control subjects (A₄₅₀ = 0.378, SD = 0.262, P < 0.001). The area under the receiver operating characteristic (ROC) curve for CDC25B-Abs was 0.870 (95% CI: 0.835-0.920). The sensitivity and specificity of CDC25B-Abs for detection of ESCC were 56.7% and 91.0%, respectively, when CDC25-Abs-positive samples were defined as those with an A₄₅₀ greater than the cut-off value of 0.725. Relatively few patients tested positive for the tumor markers CEA, SCC-Ag and CYFRA21-1 (13.4%, 17.2%, and 32.1%, respectively). A significantly higher number of patients with ESCC tested positive for a combination of CEA, SCC, CYFRA21-1 and CDC25B-Abs (64.2%) than for a combination of CEA, SCC-Ag and CYFRA21-1 (41.0%, P < 0.001). The concentration of CDC25B autoantibodies in serum was significantly correlated with tumor stage (P < 0.001). Although examination of the total patient pool showed no obvious relationship between CDC25B autoantibodies and overall survival, in the subgroup of patients with stage III-IV tumors, the cumulative five-year survival rate of CDC25B-seropositive patients was 6.7%, while that of CDC25B-seronegative patients was 43.4% (P = 0.001, log-rank). In the N1 subgroup, the cumulative five-year survival rate of CDC25B-seropositive patients was 13.6%, while that of CDC25B-seronegative patients was 54.5% (P = 0.040, log-rank).

Conclusions

Detection of serum CDC25B-Abs is superior to detection of the tumor markers CEA, SCC-Ag and CYFRA21-1 for diagnosis of ESCC, and CDC25B-Abs are a potential prognostic serological marker for advanced ESCC.

Serum and tissue profiling in bladder cancer combining protein and tissue arrays

Aiming at identifying biomarkers for bladder cancer, the serum proteome was explored in a pilot study through a profiling approach using protein arrays. Supervised analyses identified a panel 171 immunogenic proteins differentially expressed between patients with bladder cancer (n = 12) and controls without the disease (n = 10). The microanatomical expression patterns of novel immunogenic proteins, especially dynamin and clusterin, were found significantly associated with histopathologic variables and overall survival, as confirmed by immunohistochemistry using an independent series of bladder tumors contained in tissue microarrays (n = 289). Thus, the protein arrays approach has identified a panel of immunogenic candidates that may potentially play a role as diagnostic biomarkers, especially for muscle invasive disease. Moreover, the protein expression patterns of dynamin and clusterin in bladder tumors were shown to adjunct for histopathologic staging and clinical outcome prognosis.

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer

Mucinous epithelial ovarian cancers are clinically and morphologically distinct from the other histopathologic subtypes of ovarian cancer. Unlike other ovarian subtypes, epidemiologic studies have indicated that tobacco exposure is a significant risk factor for developing mucinous ovarian cancer. Detection of autoantibody reactivity is useful in biomarker discovery and for explaining the role of important pathophysiologic pathways in disease. In order to study if there are specific antibody biomarkers in the plasma samples of mucinous ovarian cancer patients, we have initiated a screen by employing a 'reverse capture antibody microarray' platform that uses native host antigens derived from mucinous ovarian tissues as 'baits' for the capture of differentially labelled patient and control autoantibodies. Thirty-five autoantibodies that were significantly elevated in the cancer plasma samples compared with healthy controls, and six autoantibodies that segregated smoking and non-smoking patients were identified. Functional annotation of the antibody targets has identified nine target antigens involved in integrin and Wnt signalling pathways. Immunohistochemistry of archived ovarian specimens showed significant overexpression of eight of the nine target antigens in mucinous ovarian tumour tissues, suggesting that plasma autoantibodies from mucinous ovarian cancer patients might have heightened reactivities with epitopes presented by these overexpressed antigens. Autoantibody profiling may have an unexpected utility in uncovering key signalling pathways that are dysregulated in the system of interest.

Cell-free-based protein microarray technology using agarose/DNA microplate

Protein microarray is considered to be one of the key analytical tools for high-throughput protein function analysis. We found that Arabidopsis HY5 protein functions as a novel DNA-binding tag (DBtag), and DBtagged proteins are immobilized and purified on a newly designed agarose/DNA microplate. In this chapter, we demonstrate a protocol for making the DBtag-based protein microarray and will provide protocols for two applications using the microarray: (1) detection of autophosphorylation activity of DBtagged human protein kinases and inhibition of their activity by staurosporine, and (2) detection of a protein-protein interaction between the DBtagged UBE2N and UBE2v1.

Identifying autoantibody signatures in cancer: a promising challenge

Biomarkers that show high sensitivity and specificity are needed for the early diagnosis and prognosis of cancer. An immune response to cancer is elicited in humans, as demonstrated, in part, by the identification of autoantibodies against a number of tumor-associated antigen (TAAs) in sera from patients with different types of cancer. Identification of TAAs and their cognate autoantibodies is a promising strategy for the discovery of relevant biomarkers. During the past few years, three proteomic approaches, including serological identification of antigens by recombinant expression cloning (SEREX), serological proteome analysis (SERPA) and, more recently, protein microarrays, have been the dominant strategies used to identify TAAs and their cognate autoantibodies. In this review, we aim to describe the advantages, drawbacks and recent improvements of these approaches for the study of humoral responses. Finally, we discuss the definition of autoantibody signatures to improve sensitivity for the development of clinically relevant tests.

A systematic review of humoral immune responses against tumor antigens

This review summarizes studies on humoral immune responses against tumor-associated antigens (TAAs) with a focus on antibody frequencies and the potential diagnostic, prognostic, and etiologic relevance of antibodies against TAAs. We performed a systematic literature search in Medline and identified 3,619 articles on humoral immune responses and TAAs. In 145 studies, meeting the inclusion criteria, humoral immune responses in cancer patients have been analyzed against over 100 different TAAs. The most frequently analyzed antigens were p53, MUC1, NY-ESO-1, c-myc, survivin, p62, cyclin B1, and Her2/neu. Antibodies against these TAAs were detected in 0-69% (median 14%) of analyzed tumor patients. Antibody frequencies were generally very low in healthy individuals, with the exception of few TAAs, especially MUC1. For several TAAs, including p53, Her2/neu, and NY-ESO-1, higher antibody frequencies were reported when tumors expressed the respective TAA. Antibodies against MUC1 were associated with a favorable prognosis while antibodies against p53 were associated with poor disease outcome. These data suggest different functional roles of endogenous antibodies against TAAs. Although data on prediagnostic antibody levels are scarce and antibody frequencies for most TAAs are at levels precluding use in diagnostic assays for cancer early detection, there is some promising data on achieving higher sensitivity for cancer detection using panels of TAAs.

Humoral response to cancer as a tool for biomarker discovery

There is an important need to find relevant biomarkers that show high sensitivity and specificity for early diagnosis and prognosis of cancer. An immune response to cancer is elicited in humans, as demonstrated in part by the identification of autoantibodies against a number of tumor-associated antigens in sera from patients with different types of cancer. Identification of tumor-associated antigens and their cognate autoantibodies is a promising strategy for the discovery of relevant biomarkers. During the past few years, proteomic approaches, including SEREX, SERPA and, more recently, protein microarrays, have been the dominant strategies used to identify tumor-associated antigens and their cognate autoantibodies. In this review, we aim to describe advantages, drawbacks, and recent improvements of these approaches for the study of humoral responses.

Assessing specificity for immunogenicity assays

Developing sensitive and specific bioanalytical assays for measuring the immunogenicity of biological therapeutics has become an integral component of the drug-development process. The strategy for measuring these immune responses involves performing sensitive screening assays that are capable of detecting low levels of both low- and high-affinity antibodies. However, having sensitive assays inherently results in a certain rate of false-positivity. Hence, developing steps to determine specificity in these assays is important to confirm the presence of antidrug antibodies. The specificity assays are defined by the ability of an assay to score a positive result if the serum sample contains an antibody that can bind and/or neutralize the therapeutic protein. Here, we discuss the methodologies for determining specificity in the bioanalytical assays used for measuring antidrug antibodies. These methods will provide investigators and regulators with guidelines to develop and review assays to measure antidrug antibodies, which can specifically interfere with the actions of the drug and/or influence the safety profile of the therapeutic proteins.

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.

Pattern of serum autoantibodies allows accurate distinction between a tumor and pathologies of the same organ

PURPOSE

Recent studies impressively showed the diagnostic potential of seroreactivity patterns for different tumor types, offering the prospect for low-cost screening of numerous tumor types simultaneously. One of the major challenges toward this goal is to prove that seroreactivity profiles do not only allow for identifying a tumor but also allow for distinguishing tumors from other pathologies of the same organ.

EXPERIMENTAL DESIGN

We chose glioma as a model system and tested 325 sera (88 glioma, 95 intracranial tumors, 60 other brain pathologies, and 82 healthy controls) for seroreactivity on a panel of 35 antigens.

RESULTS

We were able to discriminate between glioma and all other sera with cross-validated specificity of 86.1%, sensitivity of 85.2%, and accuracy of 85.8%. We obtained comparably good results for the separation of glioma versus nontumor brain pathologies and glioma versus other intracranial tumors.

CONCLUSION

Our study provides first evidence that seroreactivity patterns allow for an accurate discrimination between a tumor and pathologies of the same organ even between different tumor types of the same organ.

Proteomics-based identification of autoantibody against CDC25B as a novel serum marker in esophageal squamous cell carcinoma

This study was aimed to identify tumor proteins that elicit a humoral response in patients with esophageal squamous cell carcinoma (ESCC). Autologous sera of 15 newly diagnosed patients with ESCC and age- and gender-matched 15 healthy controls were analyzed individually for antibody-based reactivity against proteins from 15 homogenized ESCC tissue mixture resolved by two-dimensional PAGE. One protein spot, which reacted with sera from ESCC patients but not with those from controls, was identified to be CDC25B by mass spectrometry and Western blotting. High expression of CDC25B was detected in ESCC cell lines and primary tumor tissues, but not in normal esophageal tissues. In addition, CDC25B expression was significantly higher in tumor tissue of patients with sera positive CDC25B-Abs than that of patients without CDC25B-Abs. Finally, anti-CDC25B antibodies were readily detectable in sera from 45 of 124 (36.29%) patients with ESCC, 13 of 150 (8.67%) patients with other types of cancer and 0 of 102 (0%) of healthy individuals. Thus, CDC25B autoantibodies may have clinical utility in ESCC screening and diagnosis.

The "reverse capture" autoantibody microarray : an innovative approach to profiling the autoantibody response to tissue-derived native antigens

Recently, we reported the development and use of a "reverse capture" antibody microarray for the purpose of investigating antigen-autoantibody profiling. This platform was developed to allow researchers to characterize and compare the autoantibody profiles of normal and diseased patients. Our "reverse capture" protocol is based on the dual-antibody sandwich immunoassay of enzyme-linked immunosorbent assay (ELISA), and we have previously reported its use to detect autoimmunity to epitopes found on native antigens derived from tumor cell lines. In this protocol, we used ovarian cancer as a model system to adapt the "reverse capture" procedure for use with native antigens derived from frozen tissue samples. The use of this platform in studies of autoimmunity is valuable because it allows for the detection of autoantibody reactivity with epitopes found on the post-translational modifications (PTMs) of native antigens, a feature not present with other protein array platforms. In the first step in the "reverse capture" process, tissue-derived native antigens are immobilized onto the 500 monoclonal antibodies that are spotted in duplicate on the array surface. Using the captured antigens as "baits," we then incubate the array with labeled IgG from test and control samples, and perform a two-slide dye-swap to account for any dye effects. Here, we present a detailed description of the "reverse capture" autoantibody microarray for use with tissue-derived native antigens.

Immunoregulomics : a serum autoantibody-based platform for transcription factor profiling

Gene expression is regulated by a group of proteins known as transcription factors (TFs). By binding to specific DNA cis-elements, each TF contributes a different functional role in gene expression. Panomics has developed a TranSignal TF-TF Interaction Array, which enables the user to determine TF complexes of interest with multiple other TFs. The process works by immunoprecipitating cis-elements bound to native cell nuclear extract TFs using specific antibodies to the TFs, and hybridizing the corresponding cis-elements to a membrane array spotted with different consensus sequences. In this protocol, we adapt this technology to characterize and compare autoantibody reactivity to TFs between patients with and without disease. Using Panomics combination DNA/protein arrays with over 300 different cis-elements spotted on the membrane, we can monitor the differences in autoimmune-targeted regulatory TFs, a process we termed immunoregulomics. This method allows for a qualitative analysis of the interactions with some quantifiable data. The findings can then be verified with the use of gel-shift experiments. Autoantibodies; interactome microarrays; transcription factors.

A comprehensive approach toward novel serum biomarkers for benign prostatic hyperplasia: the MPSA Consortium

PURPOSE

Clinical benign prostatic hyperplasia is primarily diagnosed based on a diverse array of progressive lower urinary tract symptoms and is likely distinct from histological benign prostatic hyperplasia, which is detected by the presence of nonmalignant proliferation of prostate cells but may or may not be associated with symptoms. Pharmacological management of lower urinary tract symptoms has emerged as an effective initial treatment for clinical benign prostatic hyperplasia due to the introduction of new drug therapies shown to be effective in recent large clinical trials. Despite advances in symptom management and research into disease pathology, diagnostic strategies for the prediction of benign prostatic hyperplasia progression and response to drug modalities are lacking, and questions remain as to the molecular differences underlying clinical (symptomatic) vs histological (nonsymptomatic) benign prostatic hyperplasia.

MATERIALS AND METHODS

As part of the Medical Therapy of Prostatic Symptoms (MTOPS) clinical trial, which demonstrated the effectiveness of combination drug therapy in slowing benign prostatic hyperplasia progression, an archive of biological specimens linked to clinical data was collected for future profiling of disease pathology and changes associated with response to drug therapy. The MTOPS Prostatic Samples Analysis (MPSA) Consortium was established to identify and validate molecular markers that may better define benign prostatic hyperplasia related pathologies, identify risk of progression of lower urinary tract symptoms, and predict response to drug therapy using the MTOPS archive. The cooperating MPSA Biomarker Discovery Sites and Pathology Coordinating Center use diverse methodologies and scientific approaches as well as unique expertise to address the goals of the Consortium.

RESULTS

To date the MPSA has identified a number of promising biomarkers as well as other molecular and cellular changes associated with benign prostatic hyperplasia.

CONCLUSIONS

These findings and ongoing Consortium discovery efforts have the potential to provide a greater understanding of the defects underlying disease pathology, and may lead to the development of early and more effective pharmacological treatment strategies for benign prostatic hyperplasia.

Arabidopsis HY5 protein functions as a DNA-binding tag for purification and functional immobilization of proteins on agarose/DNA microplate

Protein microarray is considered to be one of the key analytical tools for high-throughput protein function analysis. Here, we report that the Arabidopsis HY5 functions as a novel DNA-binding tag (DBtag) for proteins. We also demonstrate that the DBtagged proteins could be immobilized and purified on a newly designed agarose/DNA microplate. Furthermore, we show three applications using the microarray: (1) detection of autophosphorylation activity of DBtagged human protein kinases and inhibition of their activity by staurosporine, (2) specific cleavage of DBtagged proteins by a virus protease and caspase 3, and (3) detection of a protein-protein interaction between the DBtagged UBE2N and UBE2v1. Thus, this method may facilitate rapid functional analysis of a wide range of proteins.

Primer: genomic and proteomic tools for the molecular dissection of disease

Completion of the Human Genome Project has been rapidly followed by the emergence of high-throughput technologies that combine automation, miniaturization, and many other strategies and tools to enable systematic surveys of genome composition and gene expression. Of particular relevance to the prevention and management of disease are technologies such as high-throughput DNA genotyping, microarray-based gene-expression profiling, and mass spectrometry-facilitated protein profiling--platforms that collectively support the comprehensive analysis of DNA sequence variants across the genome and the global gene and protein expression changes that distinguish health from disease. Now used extensively in all facets of biomedical investigation, genomic and proteomic tools are already beginning to pinpoint molecular variants that influence risk and outcome in common diseases, and to thereby inform and direct development of novel molecular biomarkers and drug targets. As evidenced by recent advances in DNA sequencing methods, continued improvements in the scope, power, and cost efficiency of genomic and proteomic technologies should ensure their capacity to provide the scale and depth of knowledge required for translating genome sequence information into major medical impact.

Integral protein microarrays for the identification of lung cancer antigens in sera that induce a humoral immune response

The identification of biomarkers (both molecules and profiles) in patient sera offers enormous interest for the diagnosis of cancers. In this context, the detection of antibodies to tumor cell autologous antigens possesses great potential. The humoral immune response represents a form of biological amplification of signals that are otherwise weak because of very low concentrations of antigen, especially in the early stages of cancers. Herein we present the use of integral microarrays spotted with tumor-derived proteins to investigate the antibody repertoire in the sera of lung cancer patients and controls. The use of two-dimensional liquid chromatography allowed us to separate proteins from the lung adenocarcinoma cell line A549 into 1760 fractions, which were printed in duplicate, along with various controls, onto nitrocellulose coated slides. The sensitivity and specificity of the microarrays to detect singular antibodies in fluids were first validated through the recognition of fractions containing a lung marker antigen by antibody probing. Twenty fractions were initially selected as highly reactive against the anti-PGP9.5 antibody, and subsequent mass spectrometry analyses confirmed the identity of PGP9.5 protein in four of them. As a result, the importance of neighboring fractions in microarray detection was revealed due to the spreading of proteins during the separation process. Next, the microarrays were individually incubated with 14 serum samples from patients with lung cancer patients, 14 sera from colon cancer patients, and 14 control sera from normal subjects. The reactivity of the selected fractions was analyzed, and the level of immunoglobulin bound to each fraction by each serum sample was quantified. Eight of the 20 fractions offered p values < 0.01 and were recognized by an average of four reacting patients, whereas no serum from normal individuals was positive for those fractions. Protein microarrays from tumor-derived fractions hold the diagnostic potential of uncovering antigens that induce an immune response in patients with certain types of cancers.

Oncoproteomics of hepatocellular carcinoma: from cancer markers' discovery to functional pathways

Hepatocellular carcinoma (HCC) is a heterogeneous cancer with no promising treatment and remains one of the most prevailing and lethal malignancies in the world. Researchers in many biological areas now routinely identify and characterize protein markers by a mass spectrometry-based proteomic approach, a method that has been commonly used to discover diagnostic biomarkers for cancer detection. The proteomic research platforms span from the classical two-dimensional polyacrylamide gel electrophoresis (2-DE) to the latest Protein Chip or array technology, which are often integrated with the MALDI (matrix-assisted laser-desorption ionization), SELDI (surface-enhanced laser desorption/ionization) or tandem mass spectrometry (MS/MS). New advances on quantitative proteomic analysis (e.g. SILAC, ICAT, and ITRAQ) and multidimensional protein identification technology (MudPIT) have greatly enhanced the capability of proteomic methods to study the expressions, modifications and functions of protein markers. The present article reviews the latest proteomic development and discovery of biomarkers in HCC that may provide insights into the underlying mechanisms of hepatocarcinogenesis and the readiness of biomarkers for clinical uses.

Proteomics in clinical prostate research

The incidence of early prostate cancer (PCa) has increased rapidly in recent years. The majority of newly diagnosed PCa are in early tumor phase. Presently, we do not have adequate biomarkers to assess tumor aggressiveness in individual cases. Consequently, too many patients are given curatively intended treatment. An exploration of the human proteome may provide clinically useful markers. 2-DE has been successfully used for analysis of the protein phenotype using clinical samples. Proteins are separated according to size and charge, gels are compared by image analysis, protein spots of interest are excised, and proteins identified by MS. This method is exploratory and allows protein identification. However, low-abundance proteins are difficult to detect and 2-DE is currently too labor-intensive for routine use. In recent years, nongel based techniques, such as LC-MS, SELDI-MS, and protein arrays have emerged. They require smaller sample sizes and can be more automated than 2-DE. In this review, we describe studies of the protein expression of benign prostatic tissue and PCa, which is likely to serve as the first step in prognostic biomarker discovery. The prostate proteome is still far from a complete mapping which would enhance our understanding of PCa biology.

The 'reverse capture' autoantibody microarray: a native antigen-based platform for autoantibody profiling

We have previously reported the development and the use of a 'reverse capture' autoantibody microarray for studies of antigen-autoantibody profiling. We developed the 'reverse capture' autoantibody microarray to allow the user to characterize and to compare autoantibody profiles. Based on the dual-antibody sandwich immunoassay of ELISA, our 'reverse capture' protocol facilitates the detection of autoimmunity to native host antigens. Our method has the advantage over traditional protein arrays of being able to detect autoimmunity to epitopes found on the post-translational modifications (PTMs) of native antigens. The first step of this method is to immobilize native antigens onto the monoclonal antibodies spotted on the array surface. Using the antigens captured by the microarray as 'baits,' we then incubate the array with differentially labeled IgG from test and control samples, and perform a two-slide dye-swap to normalize for dye effects. In this protocol we present a detailed description of the 'reverse capture' autoantibody microarray, a method that can be completed in 9-10 h over 1-2 d.

Autoantibody microarrays for biomarker discovery

Identification of autoantigens and the detection of autoantibody reactivity are useful in biomarker discovery and for explaining the role of important biochemical pathways in disease. Despite all of their potential advantages, the main challenge to working with autoantibodies is their sensitivity. Nevertheless, proteomics may hold the key to overcoming this limitation by providing the means to multiplex. Clearly, the ability to detect multiple autoantigens using a platform such as a high-density antigen microarray would improve sensitivity and specificity of detection for autoantibody profiling. The aims of this review are to: briefly describe the current status of antigen-autoantibody microarrays; provide examples of their use in biomarker discoveries; address current limitations; and provide examples and strategies to facilitate their implementation in the clinical setting.

Shared immunoproteome for ovarian cancer diagnostics and immunotherapy: potential theranostic approach to cancer

Elimination of cancer through early detection and treatment is the ultimate goal of cancer research and is especially critical for ovarian and other forms of cancer typically diagnosed at very late stages that have very poor response rates. Proteomics has opened new avenues for the discovery of diagnostic and therapeutic targets. Immunoproteomics, which defines the subset of proteins involved in the immune response, holds considerable promise for providing a better understanding of the early-stage immune response to cancer as well as important insights into antigens that may be suitable for immunotherapy. Early administration of immunotherapeutic vaccines can potentially have profound effects on prevention of metastasis and may potentially cure through efficient and complete tumor elimination. We developed a mass-spectrometry-based method to identify novel autoantibody-based serum biomarkers for the early diagnosis of ovarian cancer that uses native tumor-associated proteins immunoprecipitated by autoantibodies from sera obtained from cancer patients and from cancer-free controls to identify autoantibody signatures that occur at high frequency only in cancer patient sera. Interestingly, we identified a subset of more than 50 autoantigens that were also processed and presented by MHC class I molecules on the surfaces of ovarian cancer cells and thus were common to the two immunological processes of humoral and cell-mediated immunity. These shared autoantigens were highly representative of families of proteins with roles in key processes in carcinogenesis and metastasis, such as cell cycle regulation, cell proliferation, apoptosis, tumor suppression, and cell adhesion. Autoantibodies appearing at the early stages of cancer suggest that this detectable immune response to the developing tumor can be exploited as early-stage biomarkers for the development of ovarian cancer diagnostics. Correspondingly, because the T-cell immune response depends on MHC class I processing and presentation of peptides, proteins that go through this pathway are potential candidates for the development of immunotherapeutics designed to activate a T-cell immune response to cancer. To the best of our knowledge, this is the first comprehensive study that identifies and categorizes proteins that are involved in both humoral and cell-mediated immunity against ovarian cancer, and it may have broad implications for the discovery and selection of theranostic molecular targets for cancer therapeutics and diagnostics in general.

Cancer immunomics using autoantibody signatures for biomarker discovery

The increased incidence of autoantibodies in malignancies has been described since the 1970s. Thus the ability to determine molecular fingerprinting of autoantibodies (antibody signatures) may provide useful clinical diagnostic and prognostic information. This review describes the use of several proteomics approaches for the identification of antigens recognized by these autoantibodies. Serological proteome analysis combines separation of tumor cell proteins on two-dimensional gel electrophoresis gels, Western blotting with sera of patients and healthy subjects, and identification of the detected antigens by MS. Alternatively multiple affinity protein profiling combines isolation of the antigens recognized by patient antibodies by two-dimensional immunoaffinity chromatography and identification by MS/MS. The use and limitations of reverse phase protein microarrays for testing patient serum containing autoantibodies are also considered. Lastly the most important difficulty of any proteomically identified autoantibody signature is validation in patient cohorts or clinical samples.

High throughput proteomic strategies for identifying tumour-associated antigens

Tumours elicit an immune response in the host organism and this area has been studied for decades. Initially, tumour-associated antigens were studied by examining a few proteins at a time using techniques such as 1-D SDS-PAGE and sandwich ELISAs. Now, however, with the development of high-throughput strategies, multiple potential antigens in a single experiment could be uncovered. The prevailing view is that these antigens can be used as biosensors for cancers. In addition, some of these antigens may indeed be used as targets for immunotherapy. SEREX, SERPA, and protein microarray technology have been the three dominant strategies employed to identify tumour-associated antigens. In this mini-review, we aim to describe these three techniques and provide their advantages and disadvantages. In addition, we aim to address some of the challenges of cancer immunomics.

Proteomics approaches to urologic diseases

Biomarkers are greatly needed for several urologic diseases, such as interstitial cystitis, the symptomatic and clinical progression of benign prostate hyperplasia, as well as the specific detection of urologic cancers, including prostate and bladder cancer. This review aims to: briefly describe the need for biomarkers in the field and biomarkers that are currently available for clinicians; address the limitations and roadblocks to effective biomarker discovery; and provide examples and strategies for implementing biomarkers in clinical practice and/or drug discovery.