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.     

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.     

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]     

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.     

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.     

Autoantibody biomarkers in the detection of cancer

By definition, tumor biomarkers are selective molecules that can distinguish between patients with cancer and controls. Serum tumor markers have been the most widely used approach for cancer detection. However, the limitations of these markers, which are based on the measurement of tumor antigens, preclude their general use in cancer screening and diagnosis. Here we give an overview of recent cancer biomarker developments based on the detection of autoantibodies produced against tumor antigens in patients' sera. This new detection method can measure the autoantibodies for a spectrum of tumor antigens in a single assay, with sensitivity and specificity exceeding those obtained using the conventional antigen determination method. Autoantibodies against serum cancer biomarkers offer a novel technology for cancer detection.     

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.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

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.     

Autoantibody biomarker opens a new gateway for cancer diagnosis

The list of cancer markers of current interest has grown considerably, but none of the markers used in clinical work is a true tumor marker. These cancer biomarkers are based on the determination of tumor antigens. Here, we report a single method of autoantibody enzyme immunoassay (EIA) screens for a spectrum of serum tumor markers. A comparison of the autoantibody-based EIA to conventional antigen EIA kits, using receiver operating characteristic (ROC) plots, showed that the autoantibody EIA can significantly enhance the sensitivity and specificity of tumor markers. The detection of serum autoantibodies for a spectrum of serum tumor markers, as demonstrated here, suggests that most, if not all, serum cancer biomarkers produce autoantibodies. A unique autoantibody biomarker screening method, as presented here, might therefore facilitate achieving the accurate and early diagnosis of cancer.     

Random glycopeptide bead libraries for seromic biomarker discovery

Identification of disease-specific biomarkers is important to address early diagnosis and management of disease. Aberrant post-translational modifications (PTM) of proteins such as O-glycosylations (O-PTMs) are emerging as triggers of autoantibodies that can serve as sensitive biomarkers. Here we have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I(2)/NaBH(4) and TFA) for release of glycopeptides and sequence determination by ESI-Orbitrap-MS(n). As proof-of-principle, tumor -specific glycopeptide reporter epitopes were built-in into the libraries and were detected by tumor-specific monoclonal antibodies and autoantibodies from cancer patients. Sequenced and identified glycopeptides were resynthesized at the preparative scale by automated parallel peptide synthesis and printed on microarrays for validation and broader analysis with larger sets of sera. We further showed that chemical synthesis of the monosaccharide O-glycopeptide library (Tn-glycoform) could be diversified to other tumor glycoforms by on-bead enzymatic glycosylation reactions with recombinant glycosyltransferases. Hence, we have developed a high-throughput flexible platform for rapid discovery of O-glycopeptide biomarkers and the method has applicability in other types of assays such as lectin/antibody/enzyme specificity studies as well as investigation of other PTMs.     

Potential application of non-small cell lung cancer-associated autoantibodies to early cancer diagnosis

To identify a panel of tumor associated autoantibodies which can potentially be used as biomarkers for the early diagnosis of non-small cell lung cancer (NSCLC). Thirty-five unique and in-frame expressed phage proteins were isolated. Based on the gene expression profiling, four proteins were selected for further study. Both receiver operating characteristic curve analysis and leave-one-out method revealed that combined measurements of four antibodies produced have better predictive accuracies than any single marker alone. Leave-one-out validation also showed significant relevance with all stages of NSCLC patients. The panel of autoantibodies has a high potential for detecting early stage NSCLC.     

Breast tumor metastasis: analysis via proteomic profiling

The ability to predict the metastatic behavior of a patient's cancer, as well as to detect and eradicate such recurrences, remain major clinical challenges in oncology. While many potential molecular biomarkers have been identified and tested previously, none have greatly improved the accuracy of specimen evaluation over routine histopathological criteria and, to date, they predict individual outcomes poorly. The ongoing development of high-throughput proteomic profiling technologies is opening new avenues for the investigation of cancer and, through application in tissue-based studies and animal models, will facilitate the identification of molecular signatures that are associated with breast tumor cell phenotype. The appropriate use of these approaches has the potential to provide efficient biomarkers, and to improve our knowledge of tumor biology. This, in turn, will enable the development of targeted therapeutics aimed at ameliorating the lethal dissemination of breast cancer. In this review, we focus on the accumulating proteomic signatures of breast tumor progression, particularly those that correlate with the occurrence of distant metastases, and discuss some of the expected future developments in the field.     

Breast tumor metastasis: analysis via proteomic profiling

The ability to predict the metastatic behavior of a patient’s cancer, as well as to detect and eradicate such recurrences, remain major clinical challenges in oncology. While many potential molecular biomarkers have been identified and tested previously, none have greatly improved the accuracy of specimen evaluation over routine histopathological criteria and, to date, they predict individual outcomes poorly. The ongoing development of high-throughput proteomic profiling technologies is opening new avenues for the investigation of cancer and, through application in tissue-based studies and animal models, will facilitate the identification of molecular signatures that are associated with breast tumor cell phenotype. The appropriate use of these approaches has the potential to provide efficient biomarkers, and to improve our knowledge of tumor biology. This, in turn, will enable the development of targeted therapeutics aimed at ameliorating the lethal dissemination of breast cancer. In this review, we focus on the accumulating proteomic signatures of breast tumor progression, particularly those that correlate with the occurrence of distant metastases, and discuss some of the expected future developments in the field.     

Tissue proteomics for cancer biomarker development: laser microdissection and 2D-DIGE

Novel cancer biomarkers are required to achieve early diagnosis and optimized therapy for individual patients. Cancer is a disease of the genome, and tumor tissues are a rich source of cancer biomarkers as they contain the functional translation of the genome, namely the proteome. Investigation of the tumor tissue proteome allows the identification of proteomic signatures corresponding to clinico-pathological parameters, and individual proteins in such signatures will be good biomarker candidates. Tumor tissues are also a rich source for plasma biomarkers, because proteins released from tumor tissues may be more cancer specific than those from non-tumor cells. Two-dimensional difference gel electrophoresis (2D-DIGE) with novel ultra high sensitive fluorescent dyes (CyDye DIGE Fluor satulation dye) enables the efficient protein expression profiling of laser-microdissected tissue samples. The combined use of laser microdissection allows accurate proteomic profiling of specific cells in tumor tissues. To develop clinical applications using the identified biomarkers, collaboration between research scientists, clinicians and diagnostic companies is essential, particularly in the early phases of the biomarker development projects. The proteomics modalities currently available have the potential to lead to the development of clinical applications, and channeling the wealth of produced information towards concrete and specific clinical purposes is urgent.     

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.     

Urinary proteomic profiling for diagnostic bladder cancer biomarkers

The ability to detect and monitor bladder cancer in noninvasively obtained urine samples is a major goal. While a number of protein biomarkers have been identified and commercially developed, none have greatly improved the accuracy of sample evaluation over invasive cystoscopy. The ongoing development of high-throughput proteomic profiling technologies will facilitate the identification of molecular signatures that are associated with bladder disease. The appropriate use of these approaches has the potential to provide efficient biomarkers for the early detection and monitoring of recurrent bladder cancer. Identification of disease-associated proteins will also advance our knowledge of tumor biology, which, in turn, will enable development of targeted therapeutics aimed at reducing morbidity from bladder cancer. In this article, we focus on the accumulating proteomic signatures of urine in health and disease, and discuss expected future developments in this field of research.     

Proteomic analysis of cancer tissues: shedding light on carcinogenesis and possible biomarkers

Lung, gastric, colorectal, pancreatic, and esophageal cancers, as well as hepatocellular carcinoma (HCC), were the six most common and highly fatal cancers for Japanese men in Japan in 2003, while for women uterine cervical cancer could also be added to this list. To identify diagnostic or therapeutic biomarkers for these cancers, investigators are nowadays performing proteomic analyses of cancer tissues and cells, and revealing a large number of molecules which are diagnostic, prognostic and informative of carcinogenesis. From reports of proteomic analyses of cancerous tissues and noncancerous tissues sampled from HCC, and pancreatic, esophageal, gastric, colorectal, lung and uterine cervical cancers, we classified the proteins into digestive enzymes, growth factors, cell adhesion molecules, calcium-binding proteins, proteases, protease inhibitors, transporter proteins, structural molecules, apoptosis inhibitor, molecular chaperone, as well as proteins related to cell growth, cell differentiation, cell transformation, tumor invasion, carcinogen metabolism, and others. The aim of this study was to understand carcinogenesis of major cancers from a proteomics perspective using samples from cancer patients, and to elucidate their tumor biomarkers.     

Cancer proteomics

Conclusion The future of cancer diagnostics will be based on a panel of proteomic biomarkers. They could be used to detect cancer at an early stage, to predict and to direct therapies. Enzymes and related proteins are important biological molecules, which could serve as cancer biomarkers. These biomarkers could be intact or fragments of proteins. The challenge is to be able to find and validate these potential biomarkers as clinical diagnostics. With the advances in proteomic technologies, we are closer than ever to find these “new” enzyme molecules or fragments. The translation of newly discovered biomarkers could provide an opportunity to revolutionize the era of personalized medicine.