Breast cancer stem cell-derived extracellular vesicles transfer ARRDC1-AS1 to promote breast carcinogenesis via a miR-4731-5p/AKT1 axis-dependent mechanism

OBJECTIVES

Deregulation of long non-coding RNAs (lncRNAs) has been frequently reported in breast cancer (BC). This goes to show the importance of understanding its significant contribution towards breast carcinogenesis. In the present study, we clarified a carcinogenic mechanism based on the ARRDC1-AS1 delivered by breast cancer stem cells-derived extracellular vesicles (BCSCs-EVs) in BC.

METHODS

The isolated and well characterized BCSCs-EVs were co-cultured with BC cells. The expression of ARRDC1-AS1, miR-4731-5p, and AKT1 was determined in BC cell lines. BC cells were assayed for their viability, invasion, migration and apoptosis in vitro by CCK-8, Transwell and flow cytometry, as well as tumor growth in vivo after loss- and gain-of function assays. Dual-luciferase reporter gene, RIP and RNA pull-down assays were performed to determine the interactions among ARRDC1-AS1, miR-4731-5p, and AKT1.

RESULTS

Elevation of ARRDC1-AS1 and AKT1 as well as miR-4731-5p downregulation were observed in BC cells. ARRDC1-AS1 was enriched in BCSCs-EVs. Furthermore, EVs containing ARRDC1-AS1 enhanced the BC cell viability, invasion and migration and glutamate concentration. Mechanistically, ARRDC1-AS1 elevated the expression of AKT1 by competitively binding to miR-4731-5p. ARRDC1-AS1-containing EVs were also found to enhance tumor growth in vivo.

CONCLUSION

Collectively, BCSCs-EVs-mediated delivery of ARRDC1-AS1 may promote the malignant phenotypes of BC cells via the miR-4731-5p/AKT1 axis.

FunHoP analysis reveals upregulation of mitochondrial genes in prostate cancer

Mitochondrial activity in cancer cells has been central to cancer research since Otto Warburg first published his thesis on the topic in 1956. Although Warburg proposed that oxidative phosphorylation in the tricarboxylic acid (TCA) cycle was perturbed in cancer, later research has shown that oxidative phosphorylation is activated in most cancers, including prostate cancer (PCa). However, more detailed knowledge on mitochondrial metabolism and metabolic pathways in cancers is still lacking. In this study we expand our previously developed method for analyzing functional homologous proteins (FunHoP), which can provide a more detailed view of metabolic pathways. FunHoP uses results from differential expression analysis of RNA-Seq data to improve pathway analysis. By adding information on subcellular localization based on experimental data and computational predictions we can use FunHoP to differentiate between mitochondrial and non-mitochondrial processes in cancerous and normal prostate cell lines. Our results show that mitochondrial pathways are upregulated in PCa and that splitting metabolic pathways into mitochondrial and non-mitochondrial counterparts using FunHoP adds to the interpretation of the metabolic properties of PCa cells.

nNav1.5 expression is associated with glutamate level in breast cancer cells

Background

Glutamate and voltage-gated sodium channels, both have been the target of intense investigation for its involvement in carcinogenesis and progression of malignant disease. Breast cancer with increased level of glutamate often metastasize to other organs (especially bone), whilst re-expression of ‘neonatal’ Nav1.5, nNav1.5 in breast cancer is known to promote cell invasion in vitro, metastasis in vivo and positive lymph node metastasis in patients.

Methods

In this study, the role of nNav1.5 in regulating glutamate level in human breast cancer cells was examined using pharmacological approach (VGSCs specific blocker, TTX, glutamate release inhibitor, riluzole and siRNA-nNav1.5). Effect of these agents were evaluated based on endogenous and exogenous glutamate concentration using glutamate fluorometric assay, mRNA expression of nNav1.5 using qPCR and finally, invasion using 3D culture assay.

Results

Endogenous and exogenous glutamate levels were significantly higher in aggressive human breast cancer cells, MDA-MB-231 cells compared to less aggressive human breast cancer cells, MCF-7 and non-cancerous human breast epithelial cells, MCF-10A. Treatment with TTX to MDA-MB-231 cells resulted in significant reduction of endogenous and exogenous glutamate levels corresponded with significant suppression of cell invasion. Subsequently, downregulation of nNav1.5 gene was observed in TTX-treated cells.

Conclusions

An interesting link between nNav1.5 expression and glutamate level in aggressive breast cancer cells was detected and requires further investigation.

Predicting biochemical-recurrence-free survival using a three-metabolic-gene risk score model in prostate cancer patients

BACKGROUND

Biochemical recurrence (BCR) after initial treatment, such as radical prostatectomy, is the most frequently adopted prognostic factor for patients who suffer from prostate cancer (PCa). In this study, we aimed to construct a prognostic model consisting of gene expression profiles to predict BCR-free survival.

METHODS

We analyzed 70 metabolic pathways in 152 normal prostate samples and 494 PCa samples from the UCSC Xena dataset (training set) via gene set enrichment analysis (GSEA) to select BCR-related genes and constructed a BCR-related gene risk score (RS) model. We tested the power of our model using Kaplan-Meier (K-M) plots and receiver operator characteristic (ROC) curves. We performed univariate and multivariate analyses of RS using other clinicopathological features and established a nomogram model, which has stronger prediction ability. We used GSE70770 and DFKZ 2018 datasets to validate the results. Finally, we performed differential expression and quantitative real-time polymerase chain reaction analyses of the UCSC data for further verification of the findings.

RESULTS

A total of 194 core enriched genes were obtained through GSEA, among which 16 BCR-related genes were selected and a three-gene RS model based on the expression levels of CA14, LRAT, and MGAT5B was constructed. The outcomes of the K-M plots and ROC curves verified the accuracy of the RS model. We identified the Gleason score, pathologic T stage, and RS model as independent predictors through univariate and multivariate Cox analyses and constructed a nomogram model that presented better predictability than the RS model. The outcomes of the validation set were consistent with those of the training set. Finally, the results of differential expression analyses support the effectiveness of our model.

CONCLUSION

We constructed an RS model based on metabolic genes that could predict the prognosis of PCa patients. The model can be easily used in clinical applications and provide important insights into future research on the underlying mechanism of PCa.

The Autoantibodies against Tumor-Associated Antigens as Potential Blood-Based Biomarkers in Thyroid Neoplasia: Rationales, Opportunities and Challenges

The Autoantibodies targeting Tumor-Associated Antigens (TAA-AAbs) emerge as a result of a variety of tumor-related immunogenic stimuli and may be regarded as the eyewitnesses to the anti-tumor immune response. TAA-AAbs may be readily detected in peripheral blood to unveil the presence of a particular TAA-expressing tumor, and a fair number of TAAs eliciting the tumor-associated autoantibody response have been identified. The potential of TAA-AAbs as tumor biomarkers has been extensively studied in many human malignancies with a major influence on public health; however, tumors of the endocrine system, and, in particular, the well-differentiated follicular cell-derived thyroid neoplasms, remain understudied in this context. This review provides a detailed perspective on and legitimate rationales for the potential use of TAA-AAbs in thyroid neoplasia, with particular reference to the already established diagnostic implications of the TAA-AAbs in human cancer, to the windows for improvement and diagnostic niches in the current workup strategies in nodular thyroid disease and differentiated thyroid cancer that TAA-AAbs may successfully occupy, as well as to the proof-of-concept studies demonstrating the usefulness of TAA-AAbs in thyroid oncology, particularly for the pre-surgical discrimination between tumors of different malignant potential in the context of the indeterminate results of the fine-needle aspiration cytology.

Metabolomics of prostate cancer: Knock-in versus knock-out prostate

Several metabolomics-derived biomarkers of prostate cancer (PC) have been reported with pre-radical prostatectomy (RP) (knock-in PC) conditions; however, uncontested PC biomarkers panel appraisal and investigation of correlative evidence of these measures is lacking through post-RP (knock-out PC). We sought to explore patients' filtered serum-based metabolomics derived signature measures in knock-in PC (n = 90) using nuclear magnetic resonance spectroscopy and multiple rigorous statistical analyses, and to develop the correlative evidence of these measures through knock-out PC (n = 90) follow-up on the 15th and 30th days. The glutamate, citrate and glycine were observed as hallmarks of PC. Observed trends revealed; augmented glutamate level in knock-in PC following a sudden drop and subsequently upside of glutamate at 15th and 30th days of knock-out PC, reduction of citrate in knock-in PC subsequently gradual increase of citrate in knock-out PC, and glycine lessening in knock-in PC following augmentation on 30th day of knock-out PC. This study-based evidence clears the doubts regarding the discovery of metabolomics-derived PC biomarkers.

Antibody profiling of patients with prostate cancer reveals differences in antibody signatures among disease stages

BACKGROUND

Previous studies of prostate cancer autoantibodies have largely focused on diagnostic applications. So far, there have been no reports attempting to more comprehensively profile the landscape of prostate cancer-associated antibodies. Specifically, it is unknown whether the quantity of antibodies or the types of proteins recognized change with disease progression.

METHODS

A peptide microarray spanning the amino acid sequences of the gene products of 1611 prostate cancer-associated genes was synthesized. Serum samples from healthy male volunteers (n=15) and patients with prostate cancer (n=85) were used to probe the array. These samples included patients with various clinical stages of disease: newly diagnosed localized prostate cancer (n=15), castration-sensitive non-metastatic prostate cancer (nmCSPC, n=40), castration-resistant non-metastatic prostate cancer (n=15) and castration-resistant metastatic disease (n=15). The patients with nmCSPC received treatment with either standard androgen deprivation therapy (ADT) or an antitumor DNA vaccine encoding prostatic acid phosphatase. Serial sera samples from these individuals were also used to probe the array, to secondarily determine whether this approach could be used to detect treatment-related changes.

RESULTS

We demonstrated that this peptide array yielded highly reproducible measurements of serum IgG levels. We found that the overall number of antibody responses did not increase with disease burden. However, the composition of recognized proteins shifted with clinical stage of disease. Our analysis revealed that the largest difference was between patients with castration-sensitive and castration-resistant disease. Patients with castration-resistant disease recognized more proteins associated with nucleic acid binding and gene regulation compared with men in other groups. Our longitudinal data showed that treatments can elicit antibodies detectable by this array, and notably vaccine-treated patients developed increased responses to more proteins over the course of treatment than did ADT-treated patients.

CONCLUSIONS

This study represents the largest survey of prostate cancer-associated antibodies to date. We have been able to characterize the classes of proteins recognized by patients and determine how they change with disease burden. Our findings further demonstrate the potential of this platform for measuring antigen spread and studying responses to immunomodulatory therapies.

Nanoscale flow cytometry to distinguish subpopulations of prostate extracellular vesicles in patient plasma

OBJECTIVE

To determine if prostate-derived extracellular vesicles (EVs) present in patient plasma samples are of exocytotic origin (exosomes) or released by the cell membrane (microparticles/microvesicles). Both malignant and normal prostate cells release two types of EVs into the circulation, exosomes, and microparticles/microvesicles which differ in size, origin, and mode of release. Determining what proportion of prostate-derived EVs are of exosomal versus microparticle/microvesicle EV subtype is of potential diagnostic significance.

MATERIALS AND METHODS

Multi-parametric analytical platforms such as nanoscale flow cytometry (nFC) were used to analyze prostate derived extracellular vesicles. Plasmas from prostate cancer (PCa) patient plasmas representing benign prostatic hyperplasia (BPH), low grade prostate cancer (Gleason Score 3 + 3) and high grade prostate cancer (Gleason Score ≥4 + 4) were analyzed for various exosome markers (CD9, CD63, CD81) and a prostate specific tissue marker (prostate specific membrane antigen/PSMA).

RESULTS

By using nanoscale flow cytometry, we determine that prostate derived EVs are primarily of cell membrane origin, microparticles/microvesicles, and not all PSMA expressing EVs co-express exosomal markers such as CD9, CD63, and CD81. CD9 was the most abundant exosomal marker on prostate derived EVs (12-19%). There was no trend observed in terms of more PSMA + CD9 or PSMA + CD63 co-expressing EVs versus increasing grade of prostate cancer.

CONCLUSION

The majority of prostate derived EVs present in plasmas are from the cell membrane as evidenced by their size and most importantly, lack of co-expression of exosomal markers such as CD9/CD63/CD81. In fact, CD81 was not present on any prostate derived EVs in patient plasmas whereas CD9 was present on a minority of prostate derived EVs. The addition of an exosomal marker for detection of prostate-derived EVs does not provide greater clarity in distinguishing EVs released by the prostate.

Evaluation and characterization of anti-RalA autoantibody as a potential serum biomarker in human prostate cancer

Autoantibodies against intracellular tumor-associated antigens (TAAs) are commonly found in human cancers. In this study, we characterized the serum autoantibody response to the RalA, Ras-like GTPase, in patients with prostate cancer (PCa). The autoantibodies were detected by immunofluorescence assay in PCa cell lines, ELISA, and immunoblotting in 339 serum samples from patients with PCa and benign prostatic hyperplasia (BPH), and in normal human sera (NHS). The expression of RalA in prostate tumor tissues was evaluated by immunohistochemistry (IHC) in tumor microarrays. The autoantibody level to RalA (median) in NHS was significantly lower than in PCa (0.053 vs 0.138; P < 0.001) and BPH (0.053 vs 0.132; P < 0.005) groups. The circulating anti-RalA autoantibody could distinguish PCa patients from normal individuals with the area under the receiver operating characteristic (ROC) curve (AUC) performing at 0.861, with sensitivity of 52.9% and specificity of 91.0%. Elevation in serum immunoreactivity was observed in PCa patients after radical prostatectomy. The combined use of both anti-RalA autoantibody and PSA showed a significantly higher discriminatory ability compared with either of those markers alone. RalA protein expression was detected by IHC in 85.3% of tumor tissues from PCa patients, but without significant difference compared to BPH or normal control tissues. Together, our study shows the additional benefits of anti-RalA autoantibody as a potential serological biomarker for PCa, particularly in patients with normal PSA, and further demonstrate the utility of biomarker combinations in the immunodiagnosis of PCa.

Immunoseroproteomic Profiling in African American Men with Prostate Cancer: Evidence for an Autoantibody Response to Glycolysis and Plasminogen-Associated Proteins

African American (AA) men suffer from a disproportionately high incidence and mortality of prostate cancer (PCa) compared with other racial/ethnic groups. Despite these disparities, African American men are underrepresented in clinical trials and in studies on PCa biology and biomarker discovery. We used immunoseroproteomics to profile antitumor autoantibody responses in AA and European American (EA) men with PCa, and explored differences in these responses. This minimally invasive approach detects autoantibodies to tumor-associated antigens that could serve as clinical biomarkers and immunotherapeutic agents. Sera from AA and EA men with PCa were probed by immunoblotting against PC3 cell proteins, with AA sera showing stronger immunoreactivity. Mass spectrometry analysis of immunoreactive protein spots revealed that several AA sera contained autoantibodies to a number of proteins associated with both the glycolysis and plasminogen pathways, particularly to alpha-enolase (ENO1). The proteomic data is deposited in ProteomeXchange with identifier PXD003968. Analysis of sera from 340 racially diverse men by enzyme-linked immunosorbent assays (ELISA) showed higher frequency of anti-ENO1 autoantibodies in PCa sera compared with control sera. We observed differences between AA-PCa and EA-PCa patients in their immunoreactivity against ENO1. Although EA-PCa sera reacted with higher frequency against purified ENO1 in ELISA and recognized by immunoblotting the endogenous cellular ENO1 across a panel of prostate cell lines, AA-PCa sera reacted weakly against this protein by ELISA but recognized it by immunoblotting preferentially in metastatic cell lines. These race-related differences in immunoreactivity to ENO1 could not be accounted by differential autoantibody recognition of phosphoepitopes within this antigen. Proteomic analysis revealed differences in the posttranslational modification profiles of ENO1 variants differentially recognized by AA-PCa and EA-PCa sera. These intriguing results suggest the possibility of race-related differences in the antitumor autoantibody response in PCa, and have implications for defining novel biological determinants of PCa health disparities.

Serum Autoantibodies in Chronic Prostate Inflammation in Prostate Cancer Patients

BACKGROUND

Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens.

METHODS

Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology.

RESULTS

Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076).

CONCLUSIONS

We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation.

Prioritizing candidate disease metabolites based on global functional relationships between metabolites in the context of metabolic pathways

Identification of key metabolites for complex diseases is a challenging task in today's medicine and biology. A special disease is usually caused by the alteration of a series of functional related metabolites having a global influence on the metabolic network. Moreover, the metabolites in the same metabolic pathway are often associated with the same or similar disease. Based on these functional relationships between metabolites in the context of metabolic pathways, we here presented a pathway-based random walk method called PROFANCY for prioritization of candidate disease metabolites. Our strategy not only takes advantage of the global functional relationships between metabolites but also sufficiently exploits the functionally modular nature of metabolic networks. Our approach proved successful in prioritizing known metabolites for 71 diseases with an AUC value of 0.895. We also assessed the performance of PROFANCY on 16 disease classes and found that 4 classes achieved an AUC value over 0.95. To investigate the robustness of the PROFANCY, we repeated all the analyses in two metabolic networks and obtained similar results. Then we applied our approach to Alzheimer's disease (AD) and found that a top ranked candidate was potentially related to AD but had not been reported previously. Furthermore, our method was applicable to prioritize the metabolites from metabolomic profiles of prostate cancer. The PROFANCY could identify prostate cancer related-metabolites that are supported by literatures but not considered to be significantly differential by traditional differential analysis. We also developed a freely accessible web-based and R-based tool at http://bioinfo.hrbmu.edu.cn/PROFANCY.

Post genome-wide association studies functional characterization of prostate cancer risk loci

Background

Over the last decade, genome-wide association studies (GWAS) have discovered many risk associated single nucleotide polymorphisms (SNPs) of prostate cancer (PCa). However, the majority of the associated PCa SNPs, including those in linkage disequilibrium (LD) blocks, are generally not located in protein coding regions. The systematical investigation of the functional roles of these SNPs, especially the non-coding SNPs, becomes very necessary and helpful to the understanding of the molecular mechanism of PCa.

Results

In this work, we proposed a comprehensive framework at network level to integrate the SNP annotation, target gene assignment, gene ontology (GO) classification, pathway enrichment analysis and regulatory network reconstruction to illustrate the molecular functions of PCa associated SNPs. By LD expansion, we first identified 1828 LD SNPs using 49 reported GWAS SNPs as a start. We carefully annotated these 1828 LD SNPs via either UCSC known genes, UCSC regulation elements, or expression Quantitative Trait Loci (eQTL) data. As a result, we found 1154 SNPs were functionally annotated and obtained 205 unique PCa genes for further enrichment analysis. The enriched GO biological processes and pathways were found mainly related to regulation of cell death, apoptosis, cell proliferation, and metabolic process, which have been proved essential to cancer development. We constructed PCa genes specific transcription regulatory networks, finding several important genetic regulators for PCa, such as IGF-1/IGF-2 receptors, SP1, CREB1, and androgen receptor (AR).

Conclusions

A comprehensive framework was proposed for integrative and systematic analysis of PCa SNPs, the analysis can provide essential information for the understanding of the regulatory function of GWAS SNPs in PCa, and will facilitate the discovery of novel candidate biomarkers for diagnosis and prognosis of PCa.

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]

Serum glutamate levels correlate with Gleason score and glutamate blockade decreases proliferation, migration, and invasion and induces apoptosis in prostate cancer cells

PURPOSE

During glutaminolysis, glutamine is catabolized to glutamate and incorporated into citric acid cycle and lipogenesis. Serum glutamate levels were measured in patients with primary prostate cancer or metastatic castrate-resistant prostate cancer (mCRPCa) to establish clinical relevance. The effect of glutamate deprivation or blockade by metabotropic glutamate receptor 1 (GRM1) antagonists was investigated on prostate cancer cells' growth, migration, and invasion to establish biologic relevance.

EXPERIMENTAL DESIGN

Serum glutamate levels were measured in normal men (n = 60) and patients with primary prostate cancer (n = 197) or mCRPCa (n = 109). GRM1 expression in prostatic tissues was examined using immunohistochemistry (IHC). Cell growth, migration, and invasion were determined using cell cytotoxicity and modified Boyden chamber assays, respectively. Apoptosis was detected using immunoblotting against cleaved caspases, PARP, and γ-H2AX.

RESULTS

Univariate and multivariate analyses showed significantly higher serum glutamate levels in Gleason score ≥ 8 than in the Gleason score ≤ 7 and in African Americans than in the Caucasian Americans. African Americans with mCRPCa had significantly higher serum glutamate levels than those with primary prostate cancer or benign prostate. However, in Caucasian Americans, serum glutamate levels were similar in normal research subjects and patients with mCRPC. IHC showed weak or no expression of GRM1 in luminal acinar epithelial cells of normal or hyperplastic glands but high expression in primary or metastatic prostate cancer tissues. Glutamate deprivation or blockade decreased prostate cancer cells' proliferation, migration, and invasion and led to apoptotic cell death.

CONCLUSIONS

Glutamate expression is mechanistically associated with and may provide a biomarker of prostate cancer aggressiveness.

Protein array patterning by diffusive gel stamping

Proteins and small molecules are the effectors of physiological action in biological systems and comprehensive methods are needed to analyze their modifications, expression levels and interactions. Systems-scale characterization of the proteome requires thousands of components in high-complexity samples to be isolated and simultaneously probed. While protein microarrays offer a promising approach to probe systems-scale changes in a high-throughput format, they are limited by the need to individually synthesize tens of thousands of proteins. We present an alternative technique, which we call diffusive gel (DiG) stamping, for patterning a microarray using a cellular lysate enabling rapid visualization of dynamic changes in the proteome as well protein interactions. A major advantage of the method described is that it requires no specialized equipment or in-vitro protein synthesis, making it widely accessible to researchers. The method can be integrated with mass spectrometry, allowing for the discovery of novel protein interactions. Here, we describe and characterize the sensitivity and physical features of DiG-Stamping. We demonstrate the biologic utility of DiG-Stamping by (1) identifying the binding partners of a target protein within a cellular lysate and by (2) visualizing the dynamics of proteins with multiple post-translational modifications.

The current status of cancer biomarker research using tumour-associated antigens for minimal invasive and early cancer diagnostics

Tumour-associated antigens (TAA) can be detected prior to clinical diagnosis and thus would be ideal biomarkers for early detection of cancer using only a few microliters of a patient's serum. In this article we provide a summary of TAA screening and serum-profiling conducted for breast, prostate, lung and colon cancers. Different methodological approaches, including SEREX, SERPA, and phage display for TAA identification and TAA panels are summarised, and a revision of array based techniques is provided. The most promising studies performed on these cancers (performed with 80-400 serum samples, including controls) obtained sensitivities in a range of 44-95% and specificities of 80-100%. From the various studies reviewed, only one performed cross validation (AUC=0.71) in a prostate cancer study. Thus, albeit receiver operation characteristics are very promising, cross validation of most studies is still missing. Additionally, the concerted action of research groups for standardization of serum-TAA testing and cross validation is required. Along with today's technological options, the chances of establishing TAA biomarkers are now higher than ever before. This may also be true for confirmation and validation of already existing data, which is a prerequisite for implementation of TAA biomarkers into clinical diagnostics. This article is part of a Special Issue entitled: Integrated omics.

Serum-autoantibodies for discovery of prostate cancer specific biomarkers

BACKGROUND

The currently used prostate cancer serum marker has a low cancer specificity and improved diagnostics are needed. Here we evaluated whether autoantibodies are present in sera of prostate cancer patients and whether they are useful diagnostic markers for prostate cancer.

METHODS

Sera from 20 prostate cancer patients and 20 healthy controls were incubated on expression clone arrays containing more than 37,000 recombinant human proteins. Functional annotation clustering of the identified autoantigens was performed using the DAVID database. Autoantigens identified in the prostate cancer group were validated on microarrays using sera of 40 prostate cancer patients, 40 patients with elevated PSA levels but prostate cancer negative biopsies (benign disease), and 40 healthy controls.

RESULTS

We detected autoantibodies against 408 different antigens in sera of prostate cancer patients. One hundred seventy-four of these were exclusively detected in the cancer group compared to the healthy control group. Functional annotation clustering revealed an enrichment of RNA-associated, cytoskeleton, and nuclear proteins. The autoantibody panel was validated in serum samples of independent prostate cancer patients. Autoantibody profiles discriminated between prostate cancer patients and benign disease patients with an ROC curve AUC of 0.71. TTLL12, a protein recently described to be over-expressed in prostate cancer, was the highest ranked discrimination autoantigen.

CONCLUSION

A variety of autoantibodies were identified in sera of prostate cancer patients and provide a first step towards autoantibody diagnostics. Serum autoantibodies reflect the disease and represent valuable tools not only for prostate cancer, but also for other diseases affecting the immune response.

Autoantibody signatures: progress and perspectives for early cancer detection

Becoming invasive is a crucial step in cancer development, and the early spread of tumour cells is usually undetected by current imaging technologies. In patients with cancer and no signs of overt metastases, sensitive methods have been developed to identify circulating autoantibodies and their antigen counterparts in several cancers. These technologies are often based on proteomic approaches, and recent advances in protein and antibody microarrays have greatly facilitated the discovery of new antibody biomarkers in sera from cancer patients. Interestingly, in a clinical application setting, combinations of multiple autoantibody reactivities into panel assays have recently been proposed as relevant screening tests and validated in several independent trials. In addition, autoantibody signatures seem to be particularly relevant for early detection of cancer in high-risk cancer patients. In this review, we highlight the concept that immunogenic epitopes associated with the humoural response and key pathogenic pathways elicit serum autoantibodies that can be considered as relevant cancer biomarkers. We outline the proteomic strategies employed to identify and validate their use in clinical practice for cancer screening and diagnosis. We particularly emphasize the clinical utility of autoantibody signatures in several cancers. Finally, we discuss the challenges remaining for clinical validation.

Assessment of the humoral immune response to cancer

One of the deadly hallmarks of cancer is its ability to prosper within the constraints of the host immune system. Recent advances in immunoproteomics and high-throughput technologies have lead to profiling of the antibody repertoire in cancer patients. This in turn has lead to the identification of tumour associated antigens/autoantibodies. Autoantibodies are extremely attractive and promising biomarker entities, however there has been relatively little discussion on how to interpret the humoral immune response. It may be that autoantibody profiles hold the key to ultimately uncovering neoplastic associated pathways and through the process of immunosculpting the tumour may have yielded an immune response in the early stages of malignant tumour development. The aim of this review is to discuss the utility of the autoantibody response that is elicited as a result of malignancy and discuss the advantages and limitations of autoantibody profiling. This article is part of a Special Issue entitled: Translational Proteomics.

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.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Immunogenicity of autoantigens

Background

Autoantibodies against self-antigens have been associated not only with autoimmune diseases, but also with cancer and are even found in healthy individuals. The mechanism causing the autoantibody response remains elusive for the majority of the immunogenic antigens. To deepen the understanding of autoantibody responses, we ask whether natural-occurring, autoimmunity-associated and tumor-associated antigens have structural or biological features related to the immune response. To this end, we have carried out the most comprehensive in-silicio study of different groups of autoantigens including large antigen sets identified by our groups combined with publicly available antigen sets.

Results

We found evidence for an enrichment of genes with a larger exon length increasing the probability of the occurrence of potential immunogenic features such as mutations, SNPs, immunogenic sequence patterns and structural epitopes, or alternative splicing events. While SNPs seem to play a more central role in autoimmunity, somatic mutations seem to be stronger enriched in tumor-associated antigens. In addition, antigens of autoimmune diseases are different from other antigen sets in that they appear preferentially secreted, have frequently an extracellular location, and they are enriched in pathways associated with the immune system. Furthermore, for autoantibodies in general, we found enrichment of sequence-based properties including coiled-coils motifs, ELR motifs, and Zinc finger DNA-binding motifs. Moreover, we found enrichment of proteins binding to proteins or nucleic acids including RNA and enrichment of proteins that are part of ribosome or spliceosome. Both, homologies to proteins of other species and an enrichment of ancient protein domains indicate that immunogenic proteins are evolutionary conserved and that mimicry might play a central role.

Conclusions

Our results provide evidence that proteins which i) are evolutionary conserved, ii) show specific sequence motifs, and iii) are part of cellular structures show an increased likelihood to become autoimmunogenic.

Native antigen fractionation protein microarrays for biomarker discovery

In this protocol, we used the T24 human bladder cancer cell line as a source of native antigens to construct fractionated lysate microarrays. Subsequently, these microarrays were used to compare the autoantibody responses of individuals with interstitial cystitis/painful bladder syndrome (IC/PBS) to those of normal female controls. To accomplish this, T24 cells were lysed under nondenaturing conditions to obtain native antigens. These native antigens were then fractionated in 2D using a PF-2D liquid chromatography; the first dimension separated the proteins by their isoelectric points, and the second separated them according to hydrophobicity. The resulting protein fractions were printed onto nitrocellulose-coated glass slides (PATH slides) to create a set of fractionated lysate microarrays. To compare the autoantibody responses of IC/PBS patients with normal controls, the fractionated lysate arrays were competitively hybridized with fluorescently labeled IgG samples purified from both IC/PBS and control sera. This protocol presents a detailed description of the creation and use of native antigen fractionated lysate microarrays for autoantibody profiling.

Identification of cancer autoantigens in serum: toward diagnostic/prognostic testing?

The development of noninvasive screening tests would represent a major advance in the fight against cancer, as pre-clinical or early diagnosis could be considered the best weapons to reduce cancer mortality. The use of autoantibodies against cancer autoantigens is a promising alternative to fulfill this goal. Recent progress in protein microarray formats and other proteomic strategies has brought extraordinary opportunities to advance the discovery of new cancer autoantigens. These new approaches have allowed identification of autoantibodies with a higher prevalence, simplifying the development of predictor panels with wider coverage. Still, some issues have to be resolved before clinical application of these results. First, technical limitations in the quality and reproducibility of the microarrays and the statistical tools for data analysis have to be resolved. Second, thorough validation of the candidate biomarkers has to be carried out to include not just one particular cancer type but different cancers and other benign, inflammatory pathologies, which may give rise to cross-reactions and loss of the specificity and sensitivity of the predictive assay. The extraordinary sensitivity of the immune system to detect minor alterations in self-proteins might be used to highlight changes in the cancer protein sequence and structure that can be used for personalized therapy, including immunotherapeutic vaccines. The increasing detection of kinase proteins as autoantibody targets points to new molecules with potential therapeutic impact.

Identification of cancer autoantigens in serum: toward diagnostic/prognostic testing?

The development of noninvasive screening tests would represent a major advance in the fight against cancer, as pre-clinical or early diagnosis could be considered the best weapons to reduce cancer mortality. The use of autoantibodies against cancer autoantigens is a promising alternative to fulfill this goal. Recent progress in protein microarray formats and other proteomic strategies has brought extraordinary opportunities to advance the discovery of new cancer autoantigens. These new approaches have allowed identification of autoantibodies with a higher prevalence, simplifying the development of predictor panels with wider coverage. Still, some issues have to be resolved before clinical application of these results. First, technical limitations in the quality and reproducibility of the microarrays and the statistical tools for data analysis have to be resolved. Second, thorough validation of the candidate biomarkers has to be carried out to include not just one particular cancer type but different cancers and other benign, inflammatory pathologies, which may give rise to cross-reactions and loss of the specificity and sensitivity of the predictive assay. The extraordinary sensitivity of the immune system to detect minor alterations in self-proteins might be used to highlight changes in the cancer protein sequence and structure that can be used for personalized therapy, including immunotherapeutic vaccines. The increasing detection of kinase proteins as autoantibody targets points to new molecules with potential therapeutic impact.

Immunoprofiling using NAPPA protein microarrays

Protein microarrays provide an efficient method to immunoprofile patients in an effort to rapidly identify disease immunosignatures. The validity of using autoantibodies in diagnosis has been demonstrated in type 1 diabetes, rheumatoid arthritis, and systemic lupus, and is now being strongly considered in cancer. Several types of protein microarrays exist including antibody and antigen arrays. In this chapter, we describe the immunoprofiling application for one type of antigen array called NAPPA (nucleic acids programmable protein array). We provide a guideline for setting up the screening study and designing protein arrays to maximize the likelihood of obtaining quality data.

Osteopontin is a tumor autoantigen in prostate cancer patients

Anti-tumor antibodies act as biomarkers for the early diagnosis of prostate cancer (PCa). Osteopontin (OPN) is overexpressed in PCa cells and contributes to the progression of the disease. This study aimed to evaluate whether OPN evokes a humoral immune response in PCa patients and whether the reactivity levels of anti-OPN antibodies may be used to better differentiate PCa from benign and healthy donor plasma samples. Plasma samples from biopsy-proven PCa patients (29), benign prostate hyperplasia (BPH) (18) and control healthy donors (HD) (30) were tested by immunoblots using the recombinant human OPN. The frequency of anti-OPN antibodies was significantly higher in PCa (66%) plasma samples as compared to BPH (33%) and HD controls (10%). Anti-OPN antibodies were detected in a high proportion of plasma samples from patients with a Gleason score of less than 6 (57%), prostate-specific antigen levels lower than 10 ng/ml (67%) and pT2 organ-confined disease (70%), suggesting that anti-OPN antibodies may be used as an early serum marker for PCa. To the best of our knowledge, this is the first description of OPN as a tumor autoantigen and one of the most reactive individual autoantigens described thus far. These data support the inclusion of OPN in a multiplex of tumor antigens in order to perform antibody profiling in PCa as well as in other malignancies overexpressing OPN.

Application of proteomic technologies for prostate cancer detection, prognosis, and tailored therapy

Prostate cancer affects 3 in 10 men over the age of 50 years, and, unfortunately, the clinical course of the disease is poorly predicted. At present, there is no means that can distinguish indolent from aggressive/metastatic tumors. Thus, a personalized clinical approach could be helpful in diagnosing clinically relevant disease and guiding appropriate patient therapy. Individualized medicine requires a deep knowledge of the molecular mechanisms underpinning prostate cancer carcinogenesis. Proteomics may be the most powerful way to uncover biomarkers of detection, prognosis, and prediction, as proteins do the work of the cell and represent the majority of the diagnostic markers and drug targets today. Proteomic technologies are rapidly advancing beyond the two-dimensional gel separation techniques of the past to new types of mass spectrometry and protein microarray analyses. Biological fluids and tissue-cell proteomes from men with prostate cancer are being explored to identify diagnostic and prognostic biomarkers and therapeutic targets using these new proteomic approaches. Traditional and novel proteomic technology and their application to prostate cancer studies in translational research will be presented and discussed in this review. Proteomics coupled with powerful nanotechnology-based biomarker discovery approaches may provide a new and exciting opportunity for body fluid-borne biomarker discovery and characterization. While innovative mass spectrometry technology and nanotrap could be applied to improve the discovery and measurement of biomarkers for the early detection of prostate cancer, the use of tissue proteomic tools such as the reverse-phase protein microarray may provide new approaches for personalization of therapies tailored to each tumor's unique pathway activation network.

Glycoprotein analysis using protein microarrays and mass spectrometry

Protein glycosylation plays an important role in a multitude of biological processes such as cell-cell recognition, growth, differentiation, and cell death. It has been shown that specific glycosylation changes are key in disease progression and can have diagnostic value for a variety of disease types such as cancer and inflammation. The complexity of carbohydrate structures and their derivatives makes their study a real challenge. Improving the isolation, separation, and characterization of carbohydrates and their glycoproteins is a subject of increasing scientific interest. With the development of new stationary phases and molecules that have affinity properties for glycoproteins, the isolation and separation of these compounds have advanced significantly. In addition to detection with mass spectrometry, the microarray platform has become an essential tool to characterize glycan structure and to study glycosylation-related biological interactions, by using probes as a means to interrogate the spotted or captured glycosylated molecules on the arrays. Furthermore, the high-throughput and reproducible nature of microarray platforms have been highlighted by its extensive applications in the field of biomarker validation, where a large number of samples must be analyzed multiple times. This review covers a brief survey of the other experimental methodologies that are currently being developed and used to study glycosylation and emphasizes methodologies that involve the use of microarray platforms. This review describes recent advances in several options of microarray platforms used in glycoprotein analysis, including glycoprotein arrays, glycan arrays, lectin arrays, and antibody/lectin arrays. The translational use of these arrays in applications related to characterization of cells and biomarker discovery is also included.

Imaging of branched chain amino acid metabolism in tumors with hyperpolarized 13C ketoisocaproate

Powerful analytical tools are vital for characterizing the complex molecular changes underlying oncogenesis and cancer treatment. This is particularly true, if information is to be collected in vivo by noninvasive approaches. In the recent past, hyperpolarized (13)C magnetic resonance (MR) spectroscopy has been employed to quickly collect detailed spectral information on the chemical fate of tracer molecules in different tissues at high sensitivity. Here, we report a preclinical study showing that alpha-ketoisocaproic acid (KIC) can be used to assess molecular signatures of tumors with hyperpolarized MR spectroscopy. KIC is metabolized to leucine by the enzyme branched chain amino acid transferase (BCAT), which is found upregulated in some tumors. BCAT is a putative marker for metastasis and a target of the proto-oncogene c-myc. Very different fluxes through the BCAT-catalyzed reaction can be detected for murine lymphoma (EL4) and rat mammary adenocarcinoma (R3230AC) tumors in vivo. EL4 tumors show a more than 7-fold higher hyperpolarized (13)C leucine signal relative to the surrounding healthy tissue. In R3230AC tumor on the other hand branched chain amino acid metabolism is not enhanced relative to surrounding tissues. The distinct molecular signatures of branched chain amino acid metabolism in EL4 and R3230AC tumors correlate well with ex vivo assays of BCAT activity.

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.

Quantitative proteomic profiling of prostate cancer reveals a role for miR-128 in prostate cancer

Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of biomarkers of cancer invasion and disease aggressiveness. Although alterations in gene expression have been extensively quantified during neoplastic progression, complementary analyses of proteomic changes have been limited. Here we interrogate the proteomic alterations in a cohort of 15 prostate-derived tissues that included five each from adjacent benign prostate, clinically localized prostate cancer, and metastatic disease from distant sites. The experimental strategy couples isobaric tags for relative and absolute quantitation with multidimensional liquid phase peptide fractionation followed by tandem mass spectrometry. Over 1000 proteins were quantified across the specimens and delineated into clinically localized and metastatic prostate cancer-specific signatures. Included in these class-specific profiles were both proteins that were known to be dysregulated during prostate cancer progression and new ones defined by this study. Enrichment analysis of the prostate cancer-specific proteomic signature, to gain insight into the functional consequences of these alterations, revealed involvement of miR-128-a/b regulation during prostate cancer progression. This finding was validated using real time PCR analysis for microRNA transcript levels in an independent set of 15 clinical specimens. miR-128 levels were elevated in benign prostate epithelial cell lines compared with invasive prostate cancer cells. Knockdown of miR-128 induced invasion in benign prostate epithelial cells, whereas its overexpression attenuated invasion in prostate cancer cells. Taken together, our profiles of the proteomic alterations of prostate cancer progression revealed miR-128 as a potentially important negative regulator of prostate cancer cell invasion.

Influence of beta-galactose-specific mitochondrial lectins from prostate hyperplasic tissue on mitochondrial properties

Galactose-specific lectins (Gal-lectins) were isolated from the mitochondrial fraction of prostate post-operational hyperplasic tissue of two diagnoses: benign prostate hyperplasic tissue with low-grade intraepithelial neoplasia (LGPIN) and benign prostate hyperplasic tissue with atypical adenomatous hyperplasia (AAH). They had similar molecular weight and other properties. Effects of these lectins were investigated in vitro model experiments on bovine liver cells mitochondrial properties. Time-dependent changes: (i) in the amount of H(2)O(2); (ii) redox state of Cu in cytochrome oxidase and (iii) redox state of heme in cytochrome a+a(3) (cyt a+a(3)) of cytochrome c oxidase complex were studied. Gal-lectins from both sources increase the amount of H(2)O(2) and decrease the redox state of Cu in cytochrome oxidase and heme in cyt a+a(3). However the Gal-lectin from tissue with more severed transformation (AAH) expresses significantly more strong and long-lasting influence. These effects are mediated by galactose binding domain of the lectins as are completely abolished by the inclusion of galactose in reaction medium. Accumulation of H(2)O(2) and long-lasting decrease in the redox state of key enzymes of mitochondrial respiration chain could induce defective functioning of these organelles and whole cells. Obtained data point the possible way, which enhances further transformation of prostate tissue by release of Gal-lectins from damaged mitochondria.

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.

New concepts in herpes simplex virus vaccine development: notes from the battlefield

The recent discovery that T cells recognize different sets of herpes simplex virus type 1 and type 2 epitopes from seropositive symptomatic and asymptomatic individuals might lead to a fundamental immunologic advance in vaccine development against herpes infection and diseases. The newly introduced needle-free mucosal (i.e., topical ocular and intravaginal) lipopeptide vaccines provide a novel strategy that might target ocular and genital herpes and possibly provide 'heterologous protection' from HIV-1. Indeed, mucosal self-adjuvanting lipopeptide vaccines are easy to manufacture, simple to characterize, extremely pure, cost-effective, highly immunogenic and safe. In this review, we bring together recent published and unpublished data that illuminates the status of epitope-based herpes vaccine development and present an overview of our recent approach to an 'asymptomatic epitope'-based lipopeptide vaccine.

The fundamental flaws of immunoassays and potential solutions using tandem mass spectrometry

Immunoassays have made it possible to measure dozens of individual proteins and other analytes in human samples for help in establishing the diagnosis and prognosis of disease. In too many cases the results of those measurements are misleading and can lead to unnecessary treatment or missed opportunities for therapeutic interventions. These cases stem from problems inherent to immunoassays performed with human samples, which include a lack of concordance across platforms, autoantibodies, anti-reagent antibodies, and the high-dose hook effect. Tandem mass spectrometry may represent a detection method capable of alleviating many of the flaws inherent to immunoassays. We review our understanding of the problems associated with immunoassays on human specimens and describe methodologies using tandem mass spectrometry that could solve some of those problems. We also provide a critical discussion of the potential pitfalls of novel mass spectrometric approaches in the clinical laboratory.

Cutting edge: permissive MHC class II allele changes the pattern of antitumor immune response resulting in failure of tumor rejection

We studied the growth of transgenic adenocarcinoma of mouse prostate (TRAMP)-C1 tumor cells expressing human prostate-specific Ag (PSA) in HLA-DRB1*1501 (DR2b) transgenic mice. TRAMP-PSA tumors were frequently rejected by HLA-DR2b(-) mice but had increased incidence in HLA-DR2b(+) littermates. The levels of PSA-specific CD8 T cell responses were significantly higher in the HLA-DR2b(-) mice that rejected TRAMP-PSA tumors compared with HLA-DR2b(+) tumor-bearing littermates. In contrast, Ab responses to PSA were strong in HLA-DR2b(+) mice bearing TRAMP-PSA tumors and were virtually undetectable in HLA-DR2b(-) littermates. The analysis of CD4 T cell responses to PSA revealed the presence of several CD4 T cell epitopes in HLA-DR2b(+) mice but failed to identify strong I-A(b)-restricted epitopes in HLA-DR2b(-) mice. Our data demonstrate that the expression of a permissive HLA class II allele can change the pattern of the immune response to a tumor Ag, resulting in the failure of tumor rejection.

Protein arrays as tools for serum autoantibody marker discovery in cancer

Protein array technology has begun to play a significant role in the study of protein-protein interactions and in the identification of antigenic targets of serum autoantibodies in a variety of autoimmune disorders. More recently, this technology has been applied to the identification of autoantibody signatures in cancer. The identification of tumour-associated antigens (TAAs) recognised by the patient's immune response represents an exciting approach to identify novel diagnostic cancer biomarkers and may contribute towards a better understanding of the molecular mechanisms involved. Circulating autoantibodies have not only been used to identify TAAs as diagnostic/prognostic markers and potential therapeutic targets, they also represent excellent biomarkers for the early detection of tumours and potential markers for monitoring the efficacy of treatment. Protein array technology offers the ability to screen the humoral immune response in cancer against thousands of proteins in a high throughput technique, thus readily identifying new panels of TAAs. Such an approach should not only aid in improved diagnostics, but has already contributed to the identification of complex autoantibody signatures that may represent disease subgroups, early diagnostics and facilitated the analysis of vaccine trials.

Emerging Biomarkers for the Diagnosis and Prognosis of Prostate Cancer

Background: Early detection of prostate cancer (CaP), the most prevalent cancer and the second-leading cause of death in men, has proved difficult, and current detection methods are inadequate. Prostate-specific antigen (PSA) testing is a significant advance for early diagnosis of patients with CaP.

Content: PSA is produced almost exclusively in the prostate, and abnormalities of this organ are frequently associated with increased serum concentrations. Because of PSA’s lack of specificity for CaP, however, many patients undergo unnecessary biopsies or treatments for benign or latent tumors, respectively. Thus, a more specific method of CaP detection is required to augment or replace screening with PSA. The focus recently has been on creating cost-effective assays for circulating protein biomarkers in the blood, but because of the heterogeneity of CaP, it has become clear that this effort will be a formidable challenge. Each marker will require proper validation to ensure clinical utility. Although much work has been done on variations of the PSA test (i.e., velocity, density, free vs bound, proisoforms) with limited usefulness, there are many emerging markers at various stages of development that show some promise for CaP diagnosis. These markers include kallikrein-related peptidase 2 (KLK2), early prostate cancer antigen (EPCA), PCA3, hepsin, prostate stem cell antigen, and α-methylacyl-CoA racemase (AMACR). We review biomarkers under investigation for the early diagnosis and management of prostate cancer.

Summary: It is hoped that the use of panels of markers can improve CaP diagnosis and prognosis and help predict the therapeutic response in CaP patients.

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.