Diagnostic markers of ovarian cancer by high-throughput antigen cloning and detection on arrays

p53 autoantibodies as potential detection and prognostic biomarkers in serous ovarian cancer

BACKGROUND

This study examined the value of serum p53 autoantibodies (p53-AAb) as detection and prognostic biomarkers in ovarian cancer.

METHODS

p53-AAb were detected by ELISA in sera obtained preoperatively from women undergoing surgery for a pelvic mass. This group included women subsequently diagnosed with invasive serous ovarian cancer (n = 60), nonserous ovarian cancers (n = 30), and women with benign disease (n = 30). Age-matched controls were selected from the general population (n = 120). Receiver operating characteristic curves were constructed to compare the values of p53-AAb, CA 125, and HE4 as a screening biomarker. Kaplan-Meier curves and Cox proportional hazards modeling were used to assess its prognostic value on survival.

RESULTS

p53-AAb were detected in 25 of 60 (41.7%) of serous cases, 4 of 30 (13.3%) nonserous cases, 3 of 30 (10%) benign disease cases, and 10 of 120 (8.3%) controls (combined P = 0.0002). p53-AAb did not significantly improve the detection of cases [area under the curve (AUC), 0.69] or the discrimination of benign versus malignant disease (AUC, 0.64) compared with CA 125 (AUC, 0.99) or HE4 (AUC, 0.98). In multivariate analysis among cases, p53-AAb correlated only with a family history of breast cancer (P = 0.01). Detectable p53 antibodies in pretreatment sera were correlated with improved overall survival (P = 0.04; hazard ratio, 0.57; 95% confidence interval, 0.33-0.97) in serous ovarian cancer.

CONCLUSIONS

Antibodies to p53 are detected in the sera of 42% of patients with advanced serous ovarian cancer.

IMPACT

Although their utility as a preoperative diagnostic biomarker, beyond CA 125 and HE4, is limited, p53-AAb are prognostic for improved overall survival.

Seromic profiling of ovarian and pancreatic cancer

Autoantibodies, a hallmark of both autoimmunity and cancer, represent an easily accessible surrogate for measuring adaptive immune responses to cancer. Sera can now be assayed for reactivity against thousands of proteins using microarrays, but there is no agreed-upon standard to analyze results. We developed a set of tailored quality control and normalization procedures based on ELISA validation to allow patient comparisons and determination of individual cutoffs for specificity and sensitivity. Sera from 60 patients with pancreatic cancer, 51 patients with ovarian cancer, and 53 age-matched healthy donors were used to assess the binding of IgG antibodies against a panel of >8000 human antigens using protein microarrays and fluorescence detection. The resulting data interpretation led to the definition and ranking of proteins with preferred recognition by the sera from cancer patients in comparison with healthy donors, both by frequency and strength of signal. We found that 202 proteins were preferentially immunogenic in ovarian cancer sera compared to 29 in pancreatic cancer, with few overlaps. Correlates of autoantibody signatures with known tumor expression of corresponding antigens, functional pathways, clinical stage, and outcome were examined. Serological analysis of arrays displaying the complete human proteome (seromics) represents a new era in cancer immunology, opening the way to defining the repertoire of the humoral immune response to cancer.

Colorectal cancer proteomics, molecular characterization and biomarker discovery

Colorectal cancer (CRC) is a widespread disease, whose major genetic changes and mutations have been well characterized in the sporadic form. Much less is known at the protein and proteome level. Still, CRC has been the subject of multiple proteomic studies due to the urgent necessity of finding clinically relevant markers and to elucidate the molecular mechanisms underlying the progression of the disease. These proteomic approaches have been limited by different technical issues, mainly related with sensitivity and reproducibility. However, recent advances in proteomic techniques and MS systems have rekindled the quest for new biomarkers in CRC and an improved molecular characterization. In this review, we will discuss the application of different proteomic approaches to the identification of differentially expressed proteins in CRC. In particular, we will make a critical assessment about the use of 2-D DIGE, MS and protein microarray technologies, in their different formats, to identify up- or downregulated proteins and/or autoantibodies profiles that could be useful for CRC characterization and diagnosis. Despite a wide list of potential biomarkers, it is clear that more scientific efforts and technical advances are still needed to cover the range of low-abundant proteins, which may play a key role in CRC diagnostics and progression.

Genomic and proteomic biomarkers for cancer: a multitude of opportunities

Biomarkers are molecular indicators of a biological status, and as biochemical species can be assayed to evaluate the presence of cancer and therapeutic interventions. Through a variety of mechanisms cancer cells provide the biomarker material for their own detection. Biomarkers may be detectable in the blood, other body fluids, or tissues. The expectation is that the level of an informative biomarker is related to the specific type of disease present in the body. Biomarkers have potential both as diagnostic indicators and monitors of the effectiveness of clinical interventions. Biomarkers are also able to stratify cancer patients to the most appropriate treatment. Effective biomarkers for the early detection of cancer should provide a patient with a better outcome which in turn will translate into more efficient delivery of healthcare. Technologies for the early detection of cancer have resulted in reductions in disease-associated mortalities from cancers that are otherwise deadly if allowed to progress. Such screening technologies have proven that early detection will decrease the morbidity and mortality from cancer. An emerging theme in biomarker research is the expectation that panels of biomarker analytes rather than single markers will be needed to have sufficient sensitivity and specificity for the presymptomatic detection of cancer. Biomarkers may provide prognostic information of disease enabling interventions using targeted therapeutic agents as well as course-corrections in cancer treatment. Novel genomic, proteomic and metabolomic technologies are being used to discover and validate tumor biomarkers individually and in panels.

Characterization of humoral responses of ovarian cancer patients: antibody subclasses and antigenic components

OBJECTIVES

Current antigen-based diagnostic assays for ovarian cancers rely on intravasation of specific aberrantly expressed proteins and their achieving detectable steady-state concentrations, resulting in their inability to truly detect small early lesions. In contrast, tumor antigen immunorecognition is observed following initial transformation events. Our objective was to characterize humoral antitumor responses in terms of IgG subclasses generated and tumor antigens recognized.

METHODS

For patients with benign and malignant ovarian disease, tumor-reactive IgG subclasses were characterized by Western immunoblotting. Antigen recognition patterns were analyzed by 2-dimensional electrophoresis and proteins exhibiting shared or stage-specific recognition were defined by mass spectrometry (MS) sequencing.

RESULTS

Sera from ovarian cancer patients exhibited significantly greater immunoreactivities than either controls or women with benign disease. While late-stage patients recognized more proteins at greater intensity, stage-specific differential recognition patterns were observed in the IgG subclasses, with the greatest recognition appearing in IgG2 subclasses. Immunoreactivity in IgG2 and IgG3 from stage I and II patients appears to be most intense with nuclear antigens >40 kDa, while, in stage III patients, additional immunoreactivity was present in the <40 kDa components. Stage III patients also exhibited similar reaction with membrane antigens <40 kDa. Two-dimensional electrophoresis revealed 32 stage-linked antigenic differences with 11 in early-stage and 21 in late-stage ovarian cancer.

CONCLUSIONS

Owing to the timing and stability of humoral responses, quantitation of IgG subclasses recognizing specific tumor antigens provides superior biomarkers for early cancer identification and allows for differentiation of benign versus malignant ovarian masses and early- and late-stage cancers.

Patient-derived tumor-reactive antibodies as diagnostic markers for ovarian cancer

OBJECTIVE

Most ovarian cancers are diagnosed at advanced stage (67%) and prospects for significant improvement in survival reside in early diagnosis. Our objective was to validate our array assay for the identification of ovarian cancer based on quantitation of tumor-reactive IgG.

METHODS

The diagnostic array utilizes specific exosome-derived antigens to detect reactive IgG in patients' sera. Specific protein targets were isolated by immunoaffinity from exosomes derived from ovarian tumor cell lines. Sera were obtained from age-matched female volunteers, women with benign ovarian disease and with ovarian cancer. Immunoreactivity was also compared between exosomal proteins and their recombinant counterparts.

RESULTS

Sera from ovarian cancer patients exhibited significantly greater immunoreactivities than either normal controls or women with benign disease (both considered negative to all antigens tested). Reactivities with nucleophosmin, cathepsin D, p53, and SSX common antigen for patients with all stages of ovarian cancer were significantly higher than for controls and women with benign ovarian disease. Reactivity with placental type alkaline phosphatase, TAG 72, survivin, NY-ESO-1, GRP78, and Muc16 (CA125) allowed the differentiation between Stage III/IV and early stage ovarian cancer.

CONCLUSIONS

The quantitation of circulating tumor-reactive IgG can be used to identify the presence of ovarian cancer. The analyses of IgG recognition of specific exosomal antigens allows for the differentiation of women with benign ovarian masses from ovarian cancer, as well as distinguishing early and late stage ovarian cancers. Thus, the quantitative assessment of IgG reactive with specific tumor-derived exosomal proteins can be used as diagnostic markers for ovarian cancer.

Autoantibody profiling for cancer detection

Despite substantial progress in the understanding of the pathogenesis of cancer, the development and implementation of strategies for early cancer detection have lagged behind. Harnessing the immune response to tumor antigens is particularly useful for early detection because the immune response occurs early during tumor development and affords signal amplification with the end product, namely reactive immunoglobulins, being released into the circulation allowing easy access through the blood. This article presents recent developments in autoantibody profiling with a focus on proteomic approaches and applications to lung cancer.

Identification of tumor-associated autoantigens for the diagnosis of colorectal cancer in serum using high density protein microarrays

There is a mounting evidence of the existence of autoantibodies associated to cancer progression. Antibodies are the target of choice for serum screening because of their stability and suitability for sensitive immunoassays. By using commercial protein microarrays containing 8000 human proteins, we examined 20 sera from colorectal cancer (CRC) patients and healthy subjects to identify autoantibody patterns and associated antigens. Forty-three proteins were differentially recognized by tumoral and reference sera (p value <0.04) in the protein microarrays. Five immunoreactive antigens, PIM1, MAPKAPK3, STK4, SRC, and FGFR4, showed the highest prevalence in cancer samples, whereas ACVR2B was more abundant in normal sera. Three of them, PIM1, MAPKAPK3, and ACVR2B, were used for further validation. A significant increase in the expression level of these antigens on CRC cell lines and colonic mucosa was confirmed by immunoblotting and immunohistochemistry on tissue microarrays. A diagnostic ELISA based on the combination of MAPKAPK3 and ACVR2B proteins yielded specificity and sensitivity values of 73.9 and 83.3% (area under the curve, 0.85), respectively, for CRC discrimination after using an independent sample set containing 94 sera representative of different stages of progression and control subjects. In summary, these studies confirmed the presence of specific autoantibodies for CRC and revealed new individual markers of disease (PIM1, MAPKAPK3, and ACVR2B) with the potential to diagnose CRC with higher specificity and sensitivity than previously reported serum biomarkers.

Beyond CA125: the coming of age of ovarian cancer biomarkers. Are we there yet?

Ovarian cancer (OC) is the fourth leading cause of cancer deaths among women in the United States, despite its relatively low incidence of 50 per 100,000. Even though advances in therapy have been made, the OC fatality-to-case ratio remains exceedingly high, due to the lack of accurate tools to diagnose early-stage disease when cure is still possible. The most studied marker for OC, CA125, is only expressed by 50-60% of patients with early stage disease. Large efforts have been deployed to identify novel serum markers, yet no single marker has emerged as a serious competitor for CA125. Various groups are investing in combination approaches to increase the diagnostic value of existing markers, but many markers may still lie in under-explored areas of ovarian cancer biology, such as tumor vasculature environment and post-translational modifications (glycomics).

Analysis of gene expression profiles in HeLa cells in response to overexpression or siRNA-mediated depletion of NASP

BACKGROUND

NASP (Nuclear Autoantigenic Sperm Protein) is a linker histone chaperone required for normal cell division. Changes in NASP expression significantly affect cell growth and development; loss of gene function results in embryonic lethality. However, the mechanism by which NASP exerts its effects in the cell cycle is not understood. To understand the pathways and networks that may involve NASP function, we evaluated gene expression in HeLa cells in which NASP was either overexpressed or depleted by siRNA.

METHODS

Total RNA from HeLa cells overexpressing NASP or depleted of NASP by siRNA treatment was converted to cRNA with incorporation of Cy5-CTP (experimental samples), or Cy3-CTP (control samples). The labeled cRNA samples were hybridized to whole human genome microarrays (Agilent Technologies, Wilmington, Delaware, USA). Various gene expression analysis techniques were employed: Significance Analysis of Microarrays (SAM), Expression Analysis Systematic Explorer (EASE), and Ingenuity Pathways Analysis (IPA).

RESULTS

From approximately 36 thousand genes present in a total human genome microarray, we identified a set of 47 up-regulated and 7 down-regulated genes as a result of NASP overexpression. Similarly we identified a set of 56 up-regulated and 71 down-regulated genes as a result of NASP siRNA treatment. Gene ontology, molecular network and canonical pathway analysis of NASP overexpression demonstrated that the most significant changes were in proteins participating in organismal injury, immune response, and cellular growth and cancer pathways (major "hubs": TNF, FOS, EGR1, NFkappaB, IRF7, STAT1, IL6). Depletion of NASP elicited the changed expression of proteins involved in DNA replication, repair and development, followed by reproductive system disease, and cancer and cell cycle pathways (major "hubs": E2F8, TP53, FGF, FSH, FST, hCG, NFkappaB, TRAF6).

CONCLUSION

This study has demonstrated that NASP belongs to a network of genes and gene functions that are critical for cell survival. We have confirmed the previously reported interactions between NASP and HSP90, HSP70, histone H1, histone H3, and TRAF6. Overexpression and depletion of NASP identified overlapping networks that included TNF as a core protein, confirming that both high and low levels of NASP are detrimental to cell cycle progression. Networks with cancer-related functions had the highest significance, however reproductive networks containing follistatin and FSH were also significantly affected, which confirmed NASP's important role in reproductive tissues. This study revealed that, despite some overlap, each response was associated with a unique gene signature and placed NASP in important cell regulatory networks.

Multidimensional degradomics identifies systemic autoantigens and intracellular matrix proteins as novel gelatinase B/MMP-9 substrates

The action radius of matrix metalloproteinases or MMPs is not restricted to massive extracellular matrix (ECM) degradation, it extends to the proteolysis of numerous secreted and membrane-bound proteins. Although many instances exist in which cells disintegrate, often in conjunction with induction of MMPs, the intracellular MMP substrate repertoire or degradome remains relatively unexplored. We started an unbiased exploration of the proteolytic modification of intracellular proteins by MMPs, using gelatinase B/MMP-9 as a model enzyme. To this end, multidimensional degradomics technology was developed by the integration of broadly available biotechniques. In this way, 100-200 MMP-9 candidate substrates were isolated, of which 69 were identified. Integration of these results with the known biological functions of the substrates revealed many novel MMP-9 substrates from the intracellular matrix (ICM), such as actin, tubulin, gelsolin, moesin, ezrin, Arp2/3 complex subunits, filamin B and stathmin. About 2/3 of the identified candidates were autoantigens described in multiple autoimmune conditions and in cancer (e.g. annexin I, nucleolin, citrate synthase, HMGB1, alpha-enolase, histidyl-tRNA synthetase, HSP27, HSC70, HSP90, snRNP D3). These findings led to the insight that MMPs and other proteases may have novel (immuno)regulatory properties by the clearance of toxic and immunogenic burdens of abundant ICM proteins released after extensive necrosis. In line with the extracellular processing of organ-specific autoantigens, proteolysis might also assist in the generation of immunodominant 'neo-epitopes' from systemic autoantigens. The study of proteolysis of ICM molecules, autoantigens, alarmins and other crucial intracellular molecules may result in the discovery of novel roles for proteolytic modification.

EBAG9 inducing hyporesponsiveness of T cells promotes tumor growth and metastasis in 4T1 murine mammary carcinoma

The estrogen receptor-binding fragment-associated gene 9 (EBAG9) has been identified as an estrogen-responsive gene and was recently identified as a tumor-promoting and prognostic factor for renal cell carcinoma. We investigated whether EBAG9 expression was correlated with primary tumor growth and distant tumor metastasis in a murine breast carcinoma model. Knockdown expression of EBAG9 by small interfering RNA significantly suppressed tumor growth and metastasis in vivo in a highly malignant, spontaneously metastasizing 4T1 mouse mammary carcinoma model. 4T1 cells stably overexpressing EBAG9 developed larger and faster tumor growth and lung metastasis compared with parental 4T1 or 4T1 expressing vector alone. Strong specific cytotoxic T lymphocyte activity and enhanced gamma-interferon and interleukin-2 productions were induced in mice that received EBAG9 small interfering RNA therapy. Gene silencing of EBAG9 prolonged the survival of tumor-bearing mice and induced more intensive infiltration of CD8+ T cells in tumor mass. EBAG9 induced apoptosis of T cells, enhanced glycogen synthase kinase 3beta phosphorylation and inhibited gamma-interferon production of T cells when T lymphocytes were cocultured with 4T1 cells overexpressing EBAG9. Furthermore, overexpression of EBAG9 in 4T1 cells was accompanied with enhanced expression of chemokine (C-X-C motif) receptor 4, which might be involved in tumor metastasis. Taken together, our results suggested that EBAG9 promoted primary 4T1 mammary carcinoma growth and distant metastasis, and EBAG9 small interfering RNA exerted overt regression of tumor growth and metastasis. These findings might provide insights into the mechanism through which tumors evade immunosurveillance and provide a strategy for therapeutic intervention of cancer metastases.

Detecting tumor-specific autoantibodies for cancer diagnosis: a technology overview

BACKGROUND

Studies on the autoantibody (humoral immune) response to tumor-associated aberrant cellular components have provided critical information about an individual's disease state. Tumor-specific autoantibodies detected in human serum samples are being studied extensively to determine their utility in developing serological diagnostic assays for cancer. The development of accurate panels of diagnostic markers for cancer detection is now being pursued using new technologies and tailored computational methods capable of analyzing data generated from large-scale biomarker discovery projects.

OBJECTIVE

In this technical overview, current methodologies being applied to the identification and characterization of tumor-specific autoantibodies in cancer patients' sera are reviewed.

METHODS

A variety of research approaches are presented that are now being used or have the potential to evaluate large numbers of patient sera for the presence of tumor-specific autoantibodies. Each approach is discussed regarding its primary attributes (advantages and limitations) that could lead to serological diagnostic assays for the early detection of cancer.

CONCLUSION

Preliminary results in the development of serological diagnostic assays have demonstrated that the basic experimental tools to accomplish this goal exist. In the future, autoantibody patterns against tumor-specific proteins may achieve high specificity and sensitivity for diagnosing disease in screening populations. The development of highly accurate reliable assays is a prerequisite for this technology to be integrated into clinically applicable strategies in patient care.

Identification of tumor-associated antigens by using SEREX in hepatocellular carcinoma

AIM

To identify biomarkers for diagnosis and prognosis of hepatocellular carcinoma (HCC).

METHODS

Screening the HCC cDNA library with HCC patients sera. Isolated proteins were used as antigens to detect antibodies from patients with HCC and control sera.

RESULTS

Eighty-one positive clones were identified. The frequencies of autoantibody against five HCC-associated antigens were higher in HCC than that in chronic hepatitis and normal human sera. The sensitivity and specificity of KRT23, AHSG and FTL antigens combination tests up to 98.2% in joint test and 90.0% in series test separately.

CONCLUSIONS

HCC associate antigens identified from this study supply candidate markers of diagnosis, combined detection and immunotherapy of HCC.

Ribosomal protein S19 interacts with macrophage migration inhibitory factor and attenuates its pro-inflammatory function

Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine that has been implicated in the pathogenesis of inflammatory disorders such as infection, sepsis, and autoimmune disease. MIF exists preformed in cytoplasmic pools and exhibits an intrinsic tautomerase and oxidoreductase activity. MIF levels are elevated in the serum of animals and patients with infection or different inflammatory disorders. To elucidate how MIF actions are controlled, we searched for endogenous MIF-interacting proteins with the potential to interfere with key MIF functions. Using in vivo biotin-tagging and endogenous co-immunoprecipitation, the ribosomal protein S19 (RPS19) was identified as a novel MIF binding partner. Surface plasmon resonance and pulldown experiments with wild type and mutant MIF revealed a direct physical interaction of the two proteins (K(D) = 1.3 x 10(-6) m). As RPS19 is released in inflammatory lesions by apoptotic cells, we explored whether it affects MIF function and inhibits its binding to receptors CD74 and CXCR2. Low doses of RPS19 were found to strongly inhibit MIF-CD74 interaction. Furthermore, RPS19 significantly compromised CXCR2-dependent MIF-triggered adhesion of monocytes to endothelial cells under flow conditions. We, therefore, propose that RPS19 acts as an extracellular negative regulator of MIF.

Profiling the autoantibody repertoire by screening phage-displayed human cDNA libraries

The advent of the serological identification of antigens by procedures such as cDNA cloning and recombinant protein expression has allowed the direct molecular definition of immunogenic proteins. The phage-display technology provides several advantages over conventional immunoscreening procedures based on plasmid or lambda-phage cDNA libraries. So far, attempts to display open reading frames, such as those encoded by cDNA fragments, on filamentous phages have not been very successful. We managed to develop a strategy based on "folding reporters" which allows filtering out open reading frames from DNA and displaying them on filamentous phages in such a way that they are amenable to subsequent selection or screening. Once the cDNA library of interest is created, phage-display technology is used for selection of novel putative antigens; these are then validated by printing isolated protein on microarray and screening with patients' sera.

Discovery of antibody biomarkers using protein microarrays of tumor antigens cloned in high throughput

Development of humoral and cellular immunity against self-cellular proteins in cancer patients is a phenomenal observation. The ability of immune system to sense the presence of the disease and to fight of the disease by generating autoantibodies against tumor antigens makes it a natural biosensor. Several screening technologies have been employed for the identification of tumor-specific antibodies in cancer patients. We have developed a multidimensional approach for the identification of diagnostic antigens that utilizes a combination of high-throughput antigen cloning and protein microarray-based serological detection of complex panels of antigens by exploiting the serum autoantibody repertoire directed toward tumor-associated antigens in cancer patients. Furthermore, validation of these antigens by different bioinformatics and biological approaches will reveal the diagnostic/prognostic utility of these antigens for personalized immunotherapy.

Developing classifiers for the detection of cancer using multi-analytes

The development of a successful classifier from multiple predictors (analytes) is a multistage process complicated typically by the paucity of the data samples when compared to the number of available predictors. Choosing an adequate validation strategy is key for drawing sound conclusions about the usefulness of the classifier. Other important decisions have to be made regarding the type of prediction model to be used and training algorithm, as well as the way in which the markers are selected. This chapter describes the principles of the classifier development and underlines the most common pitfalls. A simulated dataset is used to illustrate the main concepts involved in supervised classification.

Monitoring B cell response to immunoselected phage-displayed peptides by microarrays

Successful adaptation of microarray technology for high-throughput screening of proteins requires a large number of purified recombinant proteins, e.g., antibodies for use as capture molecules. Phage surface display technology has been used for the surface expression of proteins, peptides or cDNA repertoires expressed by tumor cells. It does not require protein purification, as recombinant phages can be spotted on glass slides and used in a high-throughput screening format. Biopanning of phage libraries on patient serum antibodies is expected to enrich for antibody-binding phages for the fabrication of diagnostic and/or prognostic B-cell epitope microarrays. In contrast to other immunological techniques, microarrays can measure the antibody levels against different epitopes in a single test. This chapter highlights the recent advances in phage-based microarray technology to profile humoral immune responses in cancer patients.

Array Biosensor for Toxin Detection: Continued Advances

The following review focuses on progress made in the last five years with the NRL Array Biosensor, a portable instrument for rapid and simultaneous detection of multiple targets. Since 2003, the Array Biosensor has been automated and miniaturized for operation at the point-of-use. The Array Biosensor has also been used to demonstrate (1) quantitative immunoassays against an expanded number of toxins and toxin indicators in food and clinical fluids, and (2) the efficacy of semi-selective molecules as alternative recognition moieties. Blind trials, with unknown samples in a variety of matrices, have demonstrated the versatility, sensitivity, and reliability of the automated system.

Tumor-infiltrating T cells correlate with NY-ESO-1-specific autoantibodies in ovarian cancer

Background

Tumor-infiltrating CD8+ T cells are correlated with prolonged progression-free and overall survival in epithelial ovarian cancer (EOC). A significant fraction of EOC patients mount autoantibody responses to various tumor antigens, however the relationship between autoantibodies and tumor-infiltrating T cells has not been investigated in EOC or any other human cancer. We hypothesized that autoantibody and T cell responses may be correlated in EOC and directed toward the same antigens.

Methodology and Principal Findings

We obtained matched serum and tumor tissue from 35 patients with high-grade serous ovarian cancer. Serum samples were assessed by ELISA for autoantibodies to the common tumor antigen NY-ESO-1. Tumor tissue was examined by immunohistochemistry for expression of NY-ESO-1, various T cell markers (CD3, CD4, CD8, CD25, FoxP3, TIA-1 and Granzyme B) and other immunological markers (CD20, MHC class I and MHC class II). Lymphocytic infiltrates varied widely among tumors and included cells positive for CD3, CD8, TIA-1, CD25, FoxP3 and CD4. Twenty-six percent (9/35) of patients demonstrated serum IgG autoantibodies to NY-ESO-1, which were positively correlated with expression of NY-ESO-1 antigen by tumor cells (r = 0.57, p = 0.0004). Autoantibodies to NY-ESO-1 were associated with increased tumor-infiltrating CD8+, CD4+ and FoxP3+ cells. In an individual HLA-A2+ patient with autoantibodies to NY-ESO-1, CD8+ T cells isolated from solid tumor and ascites were reactive to NY-ESO-1 by IFN-γ ELISPOT and MHC class I pentamer staining.

Conclusion and Significance

We demonstrate that tumor-specific autoantibodies and tumor-infiltrating T cells are correlated in human cancer and can be directed against the same target antigen. This implies that autoantibodies may collaborate with tumor-infiltrating T cells to influence clinical outcomes in EOC. Furthermore, serological screening methods may prove useful for identifying clinically relevant T cell antigens for immunotherapy.

Profiling tumor-associated autoantibodies for the detection of colon cancer

PURPOSE

The purpose of the present study was to screen the autoantibody signature of colon cancers to develop serum markers for colon cancer detection.

EXPERIMENTAL DESIGN

A phage cDNA expression library of colon cancer was built. The library was sequentially screened by a pool of 10 colon cancer sera, goat antihuman IgG, and a pool of two healthy sera to identify phage-expressed antigens recognized by tumor-associated antibodies. The clones picked out by these screening were subjected to a training set with 24 colon cancer sera and 24 healthy sera. The antigen combination, which got the most satisfactory classification, was tested by an independent set of 24 colon cancer sera with equal number of sera from normal donors. The carcinoembryonic antigen (CEA) level of these sera was detected for the additional classification analysis with or without the antigen combination.

RESULTS

A cDNA expression library consisting of 2 x 10(6) primary clones was prepared. After three turns of screening, 24 antigens recognized by tumor-associated antibodies were picked out for serum marker identification. The training set showed that a six-marker combination got the most satisfactory classification in a logistic regression model; leave-one-out validation achieved 91.7% sensitivity and 91.7% specificity. In a testing set with this marker panel, we correctly predicted 85% of the samples. Although according to CEA level alone, we correctly predicted 75% of the samples with 42% of cancer patients misclassified. When CEA was combined with the six markers, the sensitivity and specificity increased to 91.7% and 95.8%, respectively. The six antigen sequences in the phage display system are relatively short peptides. Only two of them showed homology to known protein sequences.

CONCLUSIONS

Autoantibodies against phage-expressed antigens derived from colon cancer tissues could be used as serum markers for the detection of colon cancer.

Tracking humoral responses using self assembling protein microarrays

The humoral immune response is a highly specific and adaptive sensor for changes in the body's protein milieu, which responds to novel structures of both foreign and self antigens. Although Igs represent a major component of human serum and are vital to survival, little is known about the response specificity and determinants that govern the human immunome. Historically, antigen-specific humoral immunity has been investigated using individually produced and purified target proteins, a labor-intensive process that has limited the number of antigens that have been studied. Here, we present the development of methods for applying self-assembling protein microarrays and a related method for producing 96-well formatted macroarrays for monitoring the humoral response at the proteome scale. Using plasmids encoding full-length cDNAs for over 850 human proteins and 1700 pathogen proteins, we demonstrate that these microarrays are highly sensitive, specific, reproducible, and can simultaneously measure immunity to thousands of proteins without a priori protein purification. Using this approach, we demonstrate the detection of humoral immunity to known and novel self-antigens, cancer antigens, autoimmune antigens, as well as pathogen-derived antigens. This represents a powerful and versatile tool for monitoring the immunome in health and disease.

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.

Microarray methods for protein biomarker detection

The application of protein biomarkers as an aid for the detection and treatment of diseases has been subject to intensified interest in recent years. The quantitative assaying of protein biomarkers in easily obtainable biological fluids such as serum and urine offers the opportunity to improve patient care via earlier and more accurate diagnoses in a convenient, non-invasive manner as well as providing a potential route towards more individually targeted treatment. Essential to achieving progress in biomarker technology is the ability to screen large numbers of proteins simultaneously in a single experiment with high sensitivity and selectivity. In this article, we highlight recent progress in the use of microarrays for high-throughput biomarker profiling and discuss some of the challenges associated with these efforts.

Use of a combination of approaches to identify and validate relevant tumor-associated antigens and their corresponding autoantibodies in ovarian cancer patients

PURPOSE

Novel biomarkers are urgently needed to increase the sensitivity of CA125 for the early detection of ovarian cancer. Indeed, it has been shown that as much as 20% of early-stage patients do not express significant levels of this biomarker. Therefore, the possibility of using autoantibodies directed against tumor-associated antigens as putative cancer markers is being more examined. Indeed, many autoantibodies have recently been shown to correlate with cancer patient prognosis or to be suitable for detection of the disease.

EXPERIMENTAL DESIGN

In this study, we have used a new approach involving the use of proteomics, immunology, and ELISA methods to identify relevant autoantibodies in the plasma of ovarian cancer patients. To do so, we developed an innovative technique called two-dimensional differential gel electrophoresis analysis of immunoprecipitated tumor antigens.

RESULTS

This strategy allowed us to successfully identify novel circulating autoantibodies directed against the S100A7 protein in the plasma of ovarian cancer patients. Further real-time reverse transcription-PCR and immunohistochemical studies confirmed that the S100A7 mRNA and protein were highly expressed in ovarian tumors but absent in normal and benign tissues. Moreover, a preliminary study involving 138 patients confirmed that the plasma levels of anti-S100A7 antibodies are significantly elevated in early- and late-stage ovarian cancer patients compared with healthy controls and with patients with benign gynecologic diseases.

CONCLUSIONS

This shows that our approach is a valuable tool to successfully identify autoantibodies and tumor-associated antigens in cancer patients and that future research assessing their putative clinical usefulness would be worthwhile.

Autoantibody approach for serum-based detection of head and neck cancer

Currently, no effective tool exists for screening or early diagnosis of head and neck squamous cell carcinoma (HNSCC). Here, we describe an approach for cancer detection based on analysis of patterns of serum immunoreactivity against a panel of biomarkers selected using microarray-based serologic profiling and specialized bioinformatics. We biopanned phage display libraries derived from three different HNSCC tissues to generate 5,133 selectively cloned tumor antigens. Based on their differential immunoreactivity on protein microarrays against serum immunoglobulins from 39 cancer and 41 control patients, we reduced the number of clones to 1,021. The performance of a neural network model (Multilayer Perceptron) for cancer classification on a data set of 80 HNSCC and 78 control samples was assessed using 10-fold cross-validation repeated 100 times. A panel of 130 clones was found to be adequate for building a classifier with sufficient sensitivity and specificity. Using these 130 markers on a completely new and independent set of 80 samples, an accuracy of 84.9% with sensitivity of 79.8% and specificity of 90.1% was achieved. Similar performance was achieved by reshuffling of the data set and by using other classification models. The performance of this classification approach represents a significant improvement over current diagnostic accuracy (sensitivity of 37% to 46% and specificity of 24%) in the primary care setting. The results shown here are promising and show the potential use of this approach toward eventual development of diagnostic assay with sufficient sensitivity and specificity suitable for detection of early-stage HNSCC in high-risk populations.

Autoantibodies as potential biomarkers for breast cancer

INTRODUCTION

Only a limited number of tumor markers for breast cancer are currently available. Antibodies to tumor-associated proteins may expand the number of available tumor markers for breast cancer and may be used together in a serum profile to enhance sensitivity and specificity.

METHODS

In the present study, we interrogated a breast cancer cDNA T7 phage library for tumor-associated proteins using biopan enrichment techniques with sera from normal individuals and from breast cancer patients. The enrichment of tumor-associated proteins after biopanning was tested using a plaque-lift assay and immunochemical detection. The putative tumor-associated phage clones were collected for PCR and sequencing analysis. Unique and open reading frame phage-expressed proteins were then used to develop phage protein ELISAs to measure corresponding autoantibodies using 87 breast cancer patients and 87 normal serum samples. A logistic regression model and leave-one-out validation were used to evaluate predictive accuracies with a single marker as well as with combined markers. Identities of those selected proteins were revealed through the sequence BLAST program.

RESULTS

We harvested 100 putative tumor-associated phage clones after biopan enrichment. Sequencing analysis revealed that six phage proteins were inframe and unique. Antibodies to these six phage-expressed proteins were measured by ELISAs, and the results showed that three of the phage clones had statistical significance in discriminating patients from normal individuals. BLAST results of the three proteins showed great matches to ASB-9, SERAC1, and RELT. Measurements of the three predictive phage proteins were combined in a logistic regression model that achieved 80% sensitivity and 100% specificity in prediction of sample status, whereas leave-one-out validation achieved 77.0% sensitivity and 82.8% specificity among 87 patient samples and 87 control samples. Receiver operating characteristic curve analysis and the leave-one-out method both showed that combined measurements of the three antibodies were more predictive of disease than any of the single antibodies studied, underscoring the importance of identifying multiple potential markers.

CONCLUSION

Serum autoantibody profiling is a promising approach for early detection and diagnosis of breast cancer. Rather than one autoantibody, a panel of autoantibodies appears preferable to achieve superior accuracy. Further refinements will need to be made to further improve the accuracy. Once refined, the assay must be applied to a prospective patient population to demonstrate applicability.

Mining the plasma proteome for cancer biomarkers

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

Autoantibodies to tumor-associated antigens: reporters from the immune system

Although autoantibodies have been recognized as participants in pathogenesis of tissue injury, the collateral role of autoantibodies as reporters from the immune system identifying cellular participants in tumorigenesis has not been fully appreciated. The immune system appears to be capable of sensing aberrant structure, distribution, and function of certain cellular components involved in tumorigenesis and making autoantibody responses to the tumor-associated antigens (TAAs). Autoantibodies to TAAs can report malignant transformation before standard clinical studies and may be useful as early detection biomarkers. The autoantibody response also provides insights into factors related to how cellular components may be rendered immunogenic. As diagnostic biomarkers, specific TAA miniarrays for identifying autoantibody profiles could have sufficient sensitivity in differentiating between types of tumors. Such anti-TAA profiles could also be used to monitor response to therapy. The immune system of cancer patients reveals the immune interactive sites or the autoepitopes of participants in tumorigenesis, and this information should be used in the design of immunotherapy.

Application of protein microarrays for multiplexed detection of antibodies to tumor antigens in breast cancer

There is strong preclinical evidence that cancer, including breast cancer, undergoes immune surveillance. This continual monitoring, by both the innate and the adaptive immune systems, recognizes changes in protein expression, mutation, folding, glycosylation, and degradation. Local immune responses to tumor antigens are amplified in draining lymph nodes, and then enter the systemic circulation. The antibody response to tumor antigens, such as p53 protein, are robust, stable, and easily detected in serum; may exist in greater concentrations than their cognate antigens; and are potential highly specific biomarkers for cancer. However, antibodies have limited sensitivities as single analytes, and differences in protein purification and assay characteristics have limited their clinical application. For example, p53 autoantibodies in the sera are highly specific for cancer patients, but are only detected in the sera of 10-20% of patients with breast cancer. Detection of p53 autoantibodies is dependent on tumor burden, p53 mutation, rapidly decreases with effective therapy, but is relatively independent of breast cancer subtype. Although antibodies to hundreds of other tumor antigens have been identified in the sera of breast cancer patients, very little is known about the specificity and clinical impact of the antibody immune repertoire to breast cancer. Recent advances in proteomic technologies have the potential for rapid identification of immune response signatures for breast cancer diagnosis and monitoring. We have adapted programmable protein microarrays for the specific detection of autoantibodies in breast cancer. Here, we present the first demonstration of the application of programmable protein microarray ELISAs for the rapid identification of breast cancer autoantibodies.

Humoral immunity directed against tumor-associated antigens as potential biomarkers for the early diagnosis of cancer

Over the past decade, it has been demonstrated that cancer is immunogenic, and multiple tumor antigens have been identified in cancer patients. It is now possible to potentially harness the immune response elicited by cancer growth as a potential diagnostic tool. Humoral immunity, or the development of autoantibodies against tumor-associated proteins, may be used as a marker for cancer exposure. Unlike circulating proteins that are shed by bulky tumors, serum autoantibodies are detectable even when antigen expression is minimal. This paper will review the methods used for tumor antigen discovery and overview what is known about autoantibodies targeting common cancer antigens with a focus on breast cancer. Data will be presented modeling the use of tumor antigen associated autoantibodies as a breast cancer diagnostic. The endogenous humoral immune response present in cancer patients may allow the identification of individuals exposed to the malignant transformation of somatic cells.

The human tumor-associated antigen RCAS1 in pregnancies complicated by pre-eclampsia

The human tumor-associated antigen RCAS1 (receptor-binding cancer antigen expressed on SiSo cells) is considered to play a role in the escape of tumor cells from immune surveillance and, at the same time, participates in the inhibition of the maternal immune response during pregnancy. The aim of our study was to investigate the expression of tumor-associated RCAS1 protein in the placenta and amniotic membranes and to assess and compare its concentration in amniotic fluid, maternal and cord blood sera in pregnancies complicated by pre-eclampsia. Samples were obtained from women with pre-eclampsia (N=9), pre-eclampsia with IUGR (N=4), normotensive IUGR (N=7) and healthy term controls (N=25) after delivery. Placentas were studied by immunohistochemistry, Western blot analysis and real-time (RT)-PCR. For assessment of RCAS1 protein concentrations in biological fluids, ELISA was performed. RCAS1 mRNA expression in the placentas of pre-eclamptic patients was significantly lower than in controls (p<0.01). The maternal blood serum RCAS1 protein concentration in the pre-eclampsia cases was also significantly lower than in controls (p=0.0207). The other study groups did not differ significantly. This study reveals the possible role of the RCAS1 protein in the development of pre-eclampsia through an immunological pathway.

Identification of differentially expressed proteins in ovarian cancer using high-density protein microarrays

Ovarian cancer is a leading cause of deaths, yet many aspects of the biology of the disease and a routine means of its detection are lacking. We have used protein microarrays and autoantibodies from cancer patients to identify proteins that are aberrantly expressed in ovarian tissue. Sera from 30 cancer patients and 30 healthy individuals were used to probe microarrays containing 5,005 human proteins. Ninety-four antigens were identified that exhibited enhanced reactivity from sera in cancer patients relative to control sera. The differential reactivity of four antigens was tested by using immunoblot analysis and tissue microarrays. Lamin A/C, SSRP1, and RALBP1 were found to exhibit increased expression in the cancer tissue relative to controls. The combined signals from multiple antigens proved to be a robust test to identify cancerous ovarian tissue. These antigens were also reactive with tissue from other types of cancer and thus are not specific to ovarian cancer. Overall our studies identified candidate tissue marker proteins for ovarian cancer and demonstrate that protein microarrays provide a powerful approach to identify proteins aberrantly expressed in disease states.

Pathways to implementation of serum proteomics for cancer

Proteomic and genomic technologies have been developed that can simultaneously detect large panels of cancer biomarkers in body fluids such as serum, plasma, sputum, saliva or urine. These approaches provide great promise for the early detection of cancer, but have thrust the field into the era of diagnostic multianalyte-based cancer tests with few, if any, models for the implementation of such tests. These multianalyte tests may be based on the detection of serum antibodies to tumor antigens, the presence of cancer-related proteins in serum or the presence of tumor-specific genomic changes that appear in plasma as free DNA. The application of noninvasive diagnostic approaches to detect early stage cancer will provide the physician with greater presymptomatic periods for clinical intervention, but it is uncertain how the various forces will impact their implementation in a patient care setting. Utilization will be balanced by medical follow-up pathways, commercial/reimbursement factors and regulatory issues that influence implementation of new devices in the marketplace.

Multianalyte tests for the early detection of cancer: speedbumps and barriers

It has become very clear that a single molecular event is inadequate to accurately predict the biology (or pathophysiology) of cancer. Furthermore, using any single molecular event as a biomarker for the early detection of malignancy may not comprehensively identify the majority of individuals with that disease. Therefore, the fact that technologies have arisen that can simultaneously detect several, possibly hundreds, of biomarkers has propelled the field towards the development of multianalyte-based in vitro diagnostic early detection tests for cancer using body fluids such as serum, plasma, sputum, saliva, or urine. These multianalyte tests may be based on the detection of serum autoantibodies to tumor antigens, the presence of cancer-related proteins in serum, or the presence of tumor-specific genomic changes that appear in plasma as free DNA. The implementation of non-invasive diagnostic approaches to detect early stage cancer may provide the physician with evidence of cancer, but the question arises as to how the information will affect the pathway of clinical intervention. The confirmation of a positive result from an in vitro diagnostic cancer test may involve relatively invasive procedures to establish a true cancer diagnosis. If in vitro diagnostic tests are proven to be both specific, i.e. rarely produce false positive results due to unrelated conditions, and sufficiently sensitive, i.e. rarely produce false negative results, then such screening tests offer the potential for early detection and personalized therapeutics using multiple disease-related targets with convenient and non-invasive means. Here we discuss the technical and regulatory barriers inherent in development of clinical multianalyte biomarker assays.

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.

Current management strategies for ovarian cancer

Epithelial ovarian cancer originates in the layer of cells that covers the surface of the ovaries. The disease spreads readily throughout the peritoneal cavity and to the lymphatics, often before causing symptoms. Of the cancers unique to women, ovarian cancer has the highest mortality rate. Most women are diagnosed as having advanced stage disease, and efforts to develop new screening approaches for ovarian cancer are a high priority. Optimal treatment of ovarian cancer begins with optimal cytoreductive surgery followed by combination chemotherapy. Ovarian cancer, even in advanced stages, is sensitive to a variety of chemotherapeutics. Although improved chemotherapy has increased 5-year survival rates, overall survival gains have been limited because of our inability to eradicate all disease. Technologic advances that allow us to examine the molecular machinery that drives ovarian cancer cells have helped to identify numerous therapeutic targets within these cells. In this review, we provide an overview of ovarian cancer with particular emphasis on recent advances in operative management and systemic therapies.

Targeting serum antibody for cancer diagnosis: a focus on colorectal cancer

The ability of the immune system to magnify the appearance of disease by generating relatively large amounts of antibody in response to small amounts of disease makes it a natural biosensor, and serum antibodies have emerged as promising biomarkers for the detection of cancer. This review summarizes recent progress in targeting serum antibodies for cancer diagnosis, with a particular focus on colorectal cancer (CRC). Several serum antibodies have been detected at increased levels in CRC patients, including p53, carcinoembryonic antigen, Ras, topoisomerase II-alpha, histone deacetylase 3 and 5, ubiquitin C-terminal hydrolase L3, tropomyosin and cyclin B1. As each antibody is only present in a limited proportion of patients (usually < 40%), a combination of serum antibodies that defines the 'immunological signature' of cancer needs to be developed. High-throughput methods to identify new serum antibodies for cancer diagnosis are also reviewed.

Molecular biomarkers for cancer detection in blood and bodily fluids

Cancer is a major and increasing public health problem worldwide. Traditionally, the diagnosis and staging of cancer, as well as the evaluation of response to therapy have been primarily based on morphology, with relatively few cancer biomarkers currently in use. Conventional biomarker studies have been focused on single genes or discrete pathways, but this approach has had limited success because of the complex and heterogeneous nature of many cancers. The completion of the human genome project and the development of new technologies have greatly facilitated the identification of biomarkers for assessment of cancer risk, early detection of primary cancers, monitoring cancer treatment, and detection of recurrence. This article reviews the various approaches used for development of such markers and describes markers of potential clinical interest in major types of cancer. Finally, we discuss the reasons why so few cancer biomarkers are currently available for clinical use.