Serum autoantibodies profiling and early-stage cancer detection

It is now well established that an immune response to cancer is elicited in humans, as demonstrated in part by the identification of autoantibodies against a number of tumor-associated antigens in sera from patients with different types of cancer. During these past few years, proteomic approaches have been developed to identify tumor-associated antigens and their cognate autoantibodies. Detection of a panel of serum autoantibodies has thus been proposed as a new method for early cancer diagnosis. Early detection seems to be particularly adequate in high-risk populations, such as heavy smokers for lung cancer or in women with high mammographic density for breast cancer. In this review, we highlight the features of serum autoantibody biomarkers and 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, using the examples of lung and breast cancer. Finally, we discuss the challenges remaining for clinical validation.     

Tumor-associated antigen arrays for the serological diagnosis of cancer

The recognition that human tumors stimulate the production of autoantibodies against autologous cellular proteins called tumor-associated antigens (TAAs) has opened the door to the possibility that autoantibodies could be exploited as serological tools for the early diagnosis and management of cancer. Cancer-associated autoantibodies are often driven by intracellular proteins that are mutated, modified, or aberrantly expressed in tumor cells and hence are regarded as immunological reporters that could help uncover molecular events underlying tumorigenesis. Emerging evidence suggests that each type of cancer might trigger unique autoantibody signatures that reflect the nature of the malignant process in the affected organ. The advent of novel genomic, proteomic, and high throughput approaches has accelerated interest in the serum autoantibody repertoire in human cancers for the discovery of candidate TAAs. The use of individual anti-TAA autoantibodies as diagnostic or prognostic tools has been tempered by their low frequency and heterogeneity in most human cancers. However, TAA arrays comprising several antigens significantly increase this frequency and hold great promise for the early detection of cancer, monitoring cancer progression, guiding individualized therapeutic interventions, and identification of novel therapeutic targets. Our recent studies suggest that the implementation of TAA arrays in screening programs for the diagnosis of prostate cancer and other cancers should be preceded by the optimization of their sensitivity and specificity through the careful selection of the most favorable combinations of TAAs.     

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]     

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.     

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 response to cancer as a tool for biomarker discovery

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

Proteomics-based identification of human acute leukemia antigens that induce humoral immune response

The identification of panels of tumor antigens that elicit an antibody response may have utility in cancer screening, diagnosis, and establishing prognosis. Until now, autoimmunity in cancer has been mainly revealed in solid tumors. The aim of this study was to apply the proteomic approach to the identification of proteins that commonly elicit a humoral response in acute leukemia (AL). Sera from 21 newly diagnosed patients with AL, 20 patients with solid tumors, and 22 noncancer controls were analyzed for antibody-based reactivity against AL proteins resolved by two-dimensional electrophoresis. As a result, autoantibody against a protein identified by mass spectrometry as Rho GDP dissociation inhibitor 2 was detected in sera from 15 of 21 patients with AL (71%). By contrast, such antibody was detected in sera from one of 20 patients with solid tumors (5%) and one of 22 noncancer controls (4.5%). Five other protein autoantibodies were also found in AL patients with a high frequency and constituted the major target antigens of the AL autoimmune response. The findings of autoantibodies against Rho GDP dissociation inhibitor 2 and other proteins in sera of patients with AL suggest that the proteomic approach we have implemented may have utility for the development of a serum-based assay for AL screening and diagnosis.     

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.     

Proteomics-based identification of autoantibodies in the sera of healthy Chinese individuals from Beijing

The identification of panels of tumor antigens that elicit an antibody response may have utility in cancer screening, diagnosis and in establishing prognosis. However, autoantibodies normally exist in sera of healthy individuals and are enormously diversified. To explore the reservoir of autoantibody in healthy population, we performed a proteomics investigation of autoantibody profiles in the sera of 36 healthy Chinese individuals from Beijing, which may provide valuable reference information to the identification of disease-specific autoantibodies. The results showed that autoantibody profiles varied individually, but some autoantibodies were identified at a high frequency in the healthy population. The autoantibodies against alpha-enolase and those against heterogeneous nuclear ribonucleoprotein L were positive in more than 50% of the sera samples. The autoantibodies identified in more than 20% of samples included those against annexin II, F-actin capping protein beta subunit and calreticulin. Some of these autoantibodies have been previously reported to be involved in autoimmune conditions and cancers. Autoantibodies in the healthy population are important as a foundation from which disease-specific autoantibodies can be defined. Thus our report on autoantibodies in healthy individuals may be useful as a reference for defining new autoantibody biomarkers.     

Proteomic analysis of tissue samples in translational breast cancer research

In the last decade, many proteomic technologies have been applied, with varying success, to the study of tissue samples of breast carcinoma for protein expression profiling in order to discover protein biomarkers/signatures suitable for: characterization and subtyping of tumors; early diagnosis, and both prognosis and prediction of outcome of chemotherapy. The purpose of this review is to critically appraise what has been achieved to date using proteomic technologies and to bring forward novel strategies – based on the analysis of clinically relevant samples – that promise to accelerate the translation of basic discoveries into the daily breast cancer clinical practice. In particular, we address major issues in experimental design by reviewing the strengths and weaknesses of current proteomic strategies in the context of the analysis of human breast tissue specimens.     

Development and validation of a high throughput system for discovery of antigens for autoantibody detection

An assay employing a panel of tumor-associated antigens has been validated and is available commercially (EarlyCDT®-Lung) to aid the early detection of lung cancer by measurement of serum autoantibodies. The high throughput (HTP) strategy described herein was pursued to identify new antigens to add to the EarlyCDT-Lung panel and to assist in the development of new panels for other cancers. Two ligation-independent cloning vectors were designed and synthesized, producing fusion proteins suitable for the autoantibody ELISA. We developed an abridged HTP version of the validated autoantibody ELISA, determining that results reflected the performance of the EarlyCDT assay, by comparing results on both formats. Once validated this HTP ELISA was utilized to screen multiple fusion proteins prepared on small-scale, by a HTP expression screen. We determined whether the assay performance for these HTP protein batches was an accurate reflection of the performance of R&D or commercial batches. A HTP discovery platform for the identification and optimal production of tumor- associated antigens which detects autoantibodies has been developed and validated. The most favorable conditions for the exposure of immunogenic epitopes were assessed to produce discriminatory proteins for use in a commercial ELISA. This process is rapid and cost-effective compared to standard cloning and screening technologies and enables rapid advancement in the field of autoantibody assay discovery. This approach will significantly reduce timescale and costs for developing similar panels of autoantibody assays for the detection of other cancer types with the ultimate aim of improved overall survival due to early diagnosis and treatment.     

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.     

Identification of tumor antigens in human lung squamous carcinoma by serological proteome analysis

Autoantibodies against tumor antigens are promising means for cancer diagnosis and prognosis. In this study, we applied a proteomic approach to identify proteins that commonly elicit humoral response in lung squamous carcinoma (LSC). Sera from 20 newly diagnosed patients with LSC and 20 matched healthy individuals were analyzed for antibody-based reactivity against LSC proteins separated by two-dimensional electrophoresis. Autoantibodies against triosephosphate isomerase (Tim) and superoxide dismutase [Mn] (MnSOD) were detected in sera from over 20% patients with LSC but none from the normal controls. Furthermore, the occurrence of autoantibodies against Tim and MnSOD was evaluated by ELISA in an additional 40 LSC patients, 30 other types of cancer (OTC) patients, and 50 noncancer controls (NC). Results showed that frequency of autoantibody against Tim (27.5%) in LSC patients was significantly higher than that in OTC patients (6.7%, p = 0.027) and in NC (6%, p = 0.005). Likewise, frequency of autoantibody against MnSOD in LSC (20%) patients was significantly higher than that in NC (4%, p = 0.016), however, there was no significant difference when comparing to that in OTC patients (6.7%, p = 0.115). We also observed significantly increased expression and secretion of Tim and MnSOD in LSC, which possibly account for their autoantibody development. Our results indicate that autoantibody and antigen of Tim and MnSOD may be useful for screening and diagnosis of the lung squamous carcinoma.     

Profiling humoral autoimmune repertoire of dilated cardiomyopathy (DCM) patients and development of a disease-associated protein chip

Dilated cardiomyopathy (DCM) is a myocardial disease characterized by progressive depression of myocardial contractile function and ventricular dilatation. Thirty percent of DCM patients belong to the inherited genetic form; the rest may be idiopathic, viral, autoimmune, or immune-mediated associated with a viral infection. Disturbances in humoral and cellular immunity have been described in cases of myocarditis and DCM. A number of autoantibodies against cardiac cell proteins have been identified in DCM. In this study, we have profiled the autoantibody repertoire of plasma from DCM patients against a human protein array consisting of 37,200 redundant, recombinant human proteins and performed qualitative and quantitative validation of these putative autoantigens on protein microarrays to identify novel putative DCM specific autoantigens. In addition to analyzing the whole IgG autoantibody repertoire, we have also analyzed the IgG3 antibody repertoire in the plasma samples to study the characteristics of IgG3 subclass antibodies. By combining screening of a protein expression library with protein microarray technology, we have detected 26 proteins identified by the IgG antibody repertoire and 6 proteins bound by the IgG3 subclass. Several of these autoantibodies found in plasma of DCM patients, such as the autoantibody against the Kv channel-interacting protein, are associated with heart failure.     

Using proteomic approach to identify tumor-associated antigens as markers in hepatocellular carcinoma

Many studies have demonstrated that intracellular proteins, which are involved in carcinogenesis, can provoke autoantibody responses. Therefore, autoantibodies can be used clinically for cancer detection and for proteomic analysis in identification of tumor-associated antigens (TAAs) that are potentially involved in malignant transformation. Liver cancer, especially hepatocellular carcinoma (HCC), is one of the most common tumors in the world. The majority of people with HCC will die within 1 year of its detection. This high case fatality rate can partially be attributed to a lack of diagnostic methods that allow early detection. In the present study, sera from 20 patients with HCC, 30 patients with chronic hepatitis (CH), and 30 patients with liver cirrhosis (LC) as well as sera from 10 normal individuals were used in a proteomic approach to identify HCC-related TAAs. Thirty-four immunoreactive protein spots were excised from the two-dimensional gel electrophoresis (2DE), digested with trypsin, and subsequently analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Of 34 immunoreactive protein spots, 28 were identified. Seventeen of them were not only reactive with serum antibodies in HCC but also with antibodies in pre-HCC conditions, and 11 were only reactive with serum antibodies in HCC but not with antibodies in pre-HCC conditions. In the subsequent analysis, two representative proteins, HSP60 and HSP70, were selected as examples for the validation purpose. The results from immunoassay were consistent with the data from proteomic analysis, supporting our hypothesis that proteins identified with autoantibodies that have been present in precancer conditions may be not appropriate to use as TAA markers in cancer detection.     

Autoantibodies in cancer: prognostic biomarkers and immune activation

The development of proteomic technologies that display a wide variety of antigenic structures has led to the identification of autoantibodies to cancer-derived tumor antigens. These autoantibodies have been detected in sera from patients with multiple cancer types, and are being evaluated as biomarkers for early cancer detection. It is not known whether these antibodies also contribute to active immune surveillance or even tumorigenicity of developing tumors. Here, we review which tumor antigen-specific antibodies are prognostic biomarkers of cancer outcome, and emerging proteomic methods for the isolation and cloning of these antibodies for potential molecular diagnostics and therapeutics.     

Advances in clinical cancer proteomics: SELDI-ToF-mass spectrometry and biomarker discovery.

For most cancers, survival rates depend on the early detection of the disease. So far, no biomarkers exist to cope with this difficult task. New proteomic technologies have brought the hope of discovering novel early cancer-specific biomarkers in complex biological samples and/or of the setting up of new clinically relevant test systems. Novel mass spectrometry-(MS) based technologies in particular, such as surface-enhanced laser desorption/ionisation time of flight (SELDI-ToF-MS), have shown promising results in the recent literature. Here, proteomic profiles of control and disease states are compared to find biomarkers for diagnosis. This paper aims to address the authors' own work and that of other groups in clinical cancer proteomics based on SELDI-ToF-MS. Shortcomings and hopes for the future are discussed.     

Autoantibodies in cancer: prognostic biomarkers and immune activation

The development of proteomic technologies that display a wide variety of antigenic structures has led to the identification of autoantibodies to cancer-derived tumor antigens. These autoantibodies have been detected in sera from patients with multiple cancer types, and are being evaluated as biomarkers for early cancer detection. It is not known whether these antibodies also contribute to active immune surveillance or even tumorigenicity of developing tumors. Here, we review which tumor antigen-specific antibodies are prognostic biomarkers of cancer outcome, and emerging proteomic methods for the isolation and cloning of these antibodies for potential molecular diagnostics and therapeutics.     

Autoantibodies as potential biomarkers for nasopharyngeal carcinoma

Autoantibody signatures, as new biomarkers, may improve the early detection of nasopharyngeal carcinoma (NPC). We constructed a T7 phage cDNA library from mixed NPC tissues, and we isolated 31 tumor-associated proteins using biopan enrichment techniques with sera from NPC patients and from healthy population. DNA sequence analysis showed that among 31 phage-displayed proteins, 22 have sequence identity with known or putative tumor-associated proteins. The results of immunochemical reactivity of patients' sera with phage-expressed proteins showed enrichment in the number of immunogenic phage clones in the biopanning process and also confirmed that antibodies were present in the sera of patients but not in the sera of healthy donors. The autoantibody against phage-expressed protein MAGE, HSP70, Fibronectin, and CD44 measured by ELISA had greater predictive value than that against EBNA-1, respectively. The antibody levels against MAGE in sera positively correlated with the clinical stages of NPC, and the antibody levels against other three proteins partly correlated with the clinical stages of NPC. Our studies suggested that the autoantibodies against tumor-associated antigens in the sera of NPC patients could be used as a screening test for NPC. Studies of the corresponding proteins may have significances in tumor biology, novel drug development, and immunotherapy.     

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.