Tumor-associated antigen arrays for the serological diagnosis of cancer

Anti-ovarian antibodies in sera of patients with ovarian tumors

AIM OF PAPER

The purpose of this study was to assess the presence of anti-ovarian autoantibodies in sera of patients with ovarian tumors.

MATERIALS AND METHODS

The study group consisted of 82 patients treated at the Division of Gynecological Surgery, Poznan University of Medical Sciences, Poland in 2007-2011. 46 patients with malignant ovarian tumors and 36 patients diagnosed with benign ovarian tumor were included into the study. Age-matched healthy control groups consisted of 15 women and 19 men. Anti-ovarian autoantibodies in serum were assessed with the use of indirect immunofluorescence. The presence of anti-ovarian autoantibodies in serum was correlated with clinical and histopathological features of the disease.

RESULTS

Serum anti-ovarian autoantibodies were found in 59% (27/46) of patients with malignant ovarian tumors, compared to 55% (20/36) and 26% (4/15) of patients with benign ovarian tumors and healthy female controls respectively. The difference was statistically significant (P=0.04). All serum samples from the male controls were negative. Anti-ovarian antibodies occurred more often among advanced stage (III and IV stage according to FIGO, P=0.037) and grade 3 (P=0.049) ovarian cancers, however, there were no differences in median progression-free survival (P=0.388). The presence of anti-ovarian antibodies was neither influenced by histopathological type of the tumor, menopausal status, presence of ascites nor CA125 levels. Seropositivity for anti-ovarian antibodies was correlated positively with patients' age and negatively with tumor size.

CONCLUSIONS

Anti-ovarian autoantibodies develop with higher frequency in ovarian cancer comparing to healthy controls, however with similar proportion to benign ovarian tumors patients. The presence of antibodies against normal ovarian tissue correlates with ovarian cancer aggressiveness.

A cancer/testis antigen microarray to screen autoantibody biomarkers of non-small cell lung cancer

Cancer/testis antigens (CTAs) are highly immunogenic in many tumors, especially in non-small cell lung cancer (NSCLC). A low-density protein microarray, which consisted of 72 CTAs and six non-CTAs, was used to screen for lung cancer-related autoantibodies. The CTA panel of NY-ESO-1, XAGE-1, ADAM29 and MAGEC1, had sensitivity and specificity values of 33% and 96%, respectively. When examined in a test set, this panel of markers had sensitivity and specificity values of 36% and 89%, respectively. This array of markers preferentially detected NSCLC, but did not detect breast cancer, and non-cancer lung disease.

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

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

RNASET2--an autoantigen in anaplastic large cell lymphoma identified by protein array analysis

Characterising tumour-associated antigens (TAAs) not only represents an important approach to the identification of new diagnostic/prognostic markers, but can also provide information on disease processes and additional potential therapeutic targets. Preliminary screening of a protein macroarray, containing more than 12,000 different proteins, with sera from anaplastic lymphoma kinase (ALK)-negative and ALK-positive anaplastic large cell lymphoma (ALCL) patients identified ribonuclease and tumour suppressor protein Ribonuclease T2 (RNASET2), phosphatase lipid phosphate phosphatase-related protein type 3 (LPPR3) and apoptotic adaptor molecule Fas-associating protein (FADD) as ALK-negative ALCL-associated TAAs. Further validation of these observations was confirmed using the ALCL sera in reverse ELISAs. The circulating anti-RNASET2 autoantibodies present in ALCL patients' sera also recognised eukaryotically expressed RNASET2 protein. RNASET2 expression was then investigated in normal tissues and in lymphomas to explore its clinical potential. RNASET2 protein and mRNA levels showed highest expression in the spleen, leucocytes and pancreas. RNASET2 protein expression was not restricted to ALK-negative ALCL (81%), being expressed in ALK-positive ALCL (65%) as well as in a number of other lymphomas. The immunological recognition of RNASET2, its expression in ALCL and other lymphomas together with its known tumourigenic properties suggest that further studies on this autoantigen are warranted.

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

BACKGROUND

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

OBJECTIVE

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

METHOD

Plaque-spot serological assay.

RESULTS

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

CONCLUSION

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

Serum autoantibodies to pancreatic cancer antigens as biomarkers of pancreatic cancer in a San Francisco Bay Area case-control study

BACKGROUND

Screening and early diagnosis tools are lacking for pancreatic adenocarcinoma; most patients are diagnosed with metastatic disease. Autoantibodies to tumor-associated antigens (TAAs) can be present months to years before diagnosis and hold promise as biomarkers for early detection.

METHODS

TAAs to pancreatic cancer autoantibodies CTDSP1 (carboxy-terminal domain, RNA polymerase II, polypeptide A, small phosphatase 1), MAPK9 (mitogen-activated protein kinase 9), and NR2E3 (nuclear receptor subfamily 2, group E, member 3), which were identified as potentially promising biomarkers in exploratory studies, were evaluated in serum from participants (300 cases, 300 controls) in a population-based case-control pancreatic cancer study in the San Francisco Bay Area. Patients were identified through cancer registry rapid case ascertainment, newly diagnosed from 1995 to 1999 and followed up through 2008. Autoantibody levels were analyzed as continuous and grouped (quartiles) variables. Multivariable unconditional logistic regression was used to compute odds ratios (ORs) as estimates of autoantibody levels associated with disease status. Kaplan-Meier product limit estimates and multivariable Cox proportional hazards regression were used to assess autoantibody levels associated with case survival duration.

RESULTS

Cases had higher levels of CTDSP1 (P = .004), MAPK9 (P = .0002), and NR2E3 (P ≤ .0001) autoantibodies than controls (fourth vs first quartile: CTDSP1 OR = 1.7, MAPK9 OR = 2.5, NR2E3 OR = 4.0). High body mass index and tobacco use were associated with levels in controls but were not statistical confounders. High CTDSP1 levels were somewhat associated with better survival (hazard ratio = 0.77, P = .07).

CONCLUSIONS

Combined with previous results, this study contributes evidence that cancer-related host immune-response factors may be useful diagnostic screening tools and prognostic indicators for pancreatic cancer. Further studies are needed to critically assess the value of autoantibody panels to TAAs in diagnostic screening, prognosis, and immunotherapy of pancreatic and other cancers.

Detection methodology based on target molecule-induced sequence-specific binding to a single-stranded oligonucleotide

We have recently developed a mix-and-read format homogeneous antigen peptide based assay for detection of the antibodies (Tian, L.; Heyduk, T. Anal. Chem. 2009, 81, 5218-5225) that employed for target detection a simple biophysical mechanism of target antibody induced annealing between two complementary oligonucleotides attached to the antigen peptide. In this work, we propose and experimentally validate an alternative variant of this assay format in which target antibody binding to antigen peptide-oligonucleotide conjugate produces a complex with high sequence-specific binding affinity to a single-stranded capture oligonucleotide. This new assay format can be used for preparing various solid-surface based assays by immobilizing the capture oligonucleotide. This assay design is not limited to antibody detection. We demonstrate that it can also be employed for detecting proteins or pathogenic bacteria using oligonucleotide-labeled antibodies as target recognition elements. Preparation of these solid-surface based assays is simplified because all interactions with the solid surfaces are mediated by well-understood oligonucleotide-oligonucleotide interactions and because of the relative ease of immobilizing oligonucleotides on various solid surfaces. These unique aspects of the assay design also allow microarray-style multiplexing that could be most useful for multiplexed antibody profiling for diagnosis and analysis of cancer, autoimmune, and infectious diseases.

The use of antigen microarrays in antibody profiling

Technological advances in the field of microarray production and analysis lead to the development of protein microarrays. Of these, antigen microarrays are one particular format that allows the study of antigen-antibody interactions in a miniaturized and highly multiplexed fashion. Here, we describe the parallel detection of antibodies with different specificities in human serum, a procedure also called antibody profiling. Autoantigens printed on microarray slides are reacted with test sera and the bound antibodies are identified by fluorescently labeled secondary reagents. Reactivity patterns generated this way characterize individuals and can help design novel diagnostic tools.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Screening of autoantibodies as potential biomarkers for hepatocellular carcinoma by using T7 phase display system

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide. Autoantibodies to tumor-associated proteins in the serum profile, as new biomarkers, may improve the early detection of HCC.

METHODS

In this study, we interrogated a HCC cDNA T7 phage library for tumor-associated proteins using biopan enrichment techniques with HCC patient and normal sera. The enrichment of tumor-associated proteins after biopanning was tested using plaque assay and immunochemical detection. The putative tumor-associated phage clones were collected for PCR and sequencing analysis. Identities of those selected sequences were revealed through the sequence BLAST program. The identified phage-expressed proteins were then used to develop phage protein ELISA to measure matching autoantibodies using 70 HCC patients, 50 chronic hepatitis patients, and 70 normal serum samples. The logistic regression model and leave-one-out validation were used to evaluate predictive accuracies with a single marker as well as with combined markers.

RESULTS

Twenty-six phage-displayed proteins have sequence identity with known or putative tumor-associated proteins. Immunochemical reactivity of patient sera with phage-expressed proteins showed that the autoantibodies to phage-expressed protein CENPF, DDX3, HSPA4, HSPA5, VIM, LMNB1, and TP53 had statistical significance in HCC patients. Measurements of the seven autoantibodies combined in a logistic regression model showed that combined measurements of these autoantibodies was more predictive of disease than any single antibody alone, underscoring the importance of identifying multiple potential markers.

CONCLUSION

Autoantibody in the serum profiling is a promising approach for early detection and diagnosis of HCC. The panel of autoantibodies appears preferable to achieve superior accuracy rather than an autoantibody alone, and may have significant relevance to tumor biology, novel drug development, and immunotherapies.

Using proteomic approach to identify tumor-associated proteins as biomarkers in human esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in China. The lower survival rate of ESCC is attributed to late diagnosis and poor therapeutic efficacy; therefore, the identification of tumor-associated proteins as biomarkers for early diagnosis, and the discovery of novel targets for therapeutic intervention, seems very important for increasing the survival rate of ESCC. To identify tumor-associated proteins as biomarkers in ESCC, we have analyzed ESCC tissues and adjacent normal tissues by two-dimensional electrophoresis (2DE) and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The results showed that a total of 104 protein spots with different expression levels were found on 2DE, and 47 proteins were eventually identified by MALDI-TOF MS. Among these identified proteins, 33 proteins including keratin 17 (KRT17), biliverdin reductase B (BLVRB), proteasome activator subunit 1 (PSME1), manganese superoxide dismutase (MnSOD), high-mobility group box-1(HMGB1), heat shock protein 70 (HSP70), peroxiredoxin (PRDX1), keratin 13 (KRT13), and so on were overexpressed, and 14 proteins including cystatin B (CSTB), tropomyosin 2 (TPM2), annexin 1 (ANX1), transgelin (TAGLN), keratin 19 (KRT19), stratifin (SFN), and so on were down-expressed in ESCC. Biological functions of these proteins are associated with cell proliferation, cell motility, protein folding, oxidative stress, and signal transduction. In the subsequent study using immunoassay on ESCC serum samples and tissue-array slides, two representative proteins, HSP70 and HMGB1, were selected as examples for the purpose of validation. The results showed that both HSP70 and HMGB1 can induce autoantibody response in ESCC sera and have higher expression in ESCC tissues. Especially, the frequency of antibodies to HSP70 in ESCC sera was significantly higher than that in normal human sera. The preliminary results suggest that some of these identified proteins might contribute to esophageal cell differentiation and carcinogenesis, certain proteins could be used as tumor-associated antigen (TAA) biomarkers in cancer diagnosis, and further studies on these identified proteins should provide more evidence of how these proteins are involved in carcinogenesis of ESCC.

Autoantibodies to tailor-made panels of tumor-associated antigens in breast carcinoma

Autoantibodies (AAbs) to tumor-associated antigens (TAAs) have been identified in the sera of cancer patients. In a previous review published in this journal, we have focused on recent knowledge related to circulating AAbs to individual TAAs in breast carcinoma. This review will focus on recent knowledge related to AAb assays to tailor-made panels of TAAs in breast carcinoma. So far, AAb assays to the following tailor-made panels of TAAs have been assessed in breast carcinoma: (1) p53, c-myc, HER2, NY-ESO-1, BRCA2, and MUC1, (2) IMP1, p62, Koc, p53, c-MYC, cyclin B1, and survivin, (3) PPIA, PRDX2, FKBP52, HSP-60, and MUC1, (4) MUC1, HER2, p53, and IGFBP2, (5) p53, HER2, IGFBP-2, and TOPO2α, (6) survivin and livin, (7) ASB-9, SERAC1, and RELT, and (8) p16, p53, and c-myc. Assessment of serum AAbs to a tailor-made panel of TAAs provides better sensitivity to diagnosis of breast carcinoma than measuring serum AAbs to a single TAA. Nevertheless, measurement of serum AAbs to a panel of TAAs for screening and early diagnosis of breast carcinoma is still investigational and should be carried out along with traditional diagnostic studies.

Interactions of MCP1 with components of the replication machinery in mammalian cells

Eukaryotic DNA replication starts with the assembly of a pre-replication complex (pre-RC) at replication origins. We have previously demonstrated that Metaphase Chromosome Protein 1 (MCP1) is involved in the early events of DNA replication. Here we show that MCP1 associates with proteins that are required for the establishment of the pre-replication complex. Reciprocal immunoprecipitation analysis showed that MCP1 interacted with Cdc6, ORC2, ORC4, MCM2, MCM3 and MCM7, with Cdc45 and PCNA. Immunofluorescence studies demonstrated the co-localization of MCP1 with some of those proteins. Moreover, biochemical studies utilizing chromatin-immunoprecipitation (ChIP) revealed that MCP1 preferentially binds replication initiation sites in human cells. Interestingly, although members of the pre-RC are known to interact with some hallmarks of heterochromatin, our co-immunoprecipitation and immunofluorescence analyses showed that MCP1 did not interact and did not co-localize with heterochromatic proteins including HP1β and MetH3K9. These observations suggest that MCP1 is associated with replication factors required for the initiation of DNA replication and binds to the initiation sites in loci that replicate early in S-phase. In addition, immunological assays revealed the association of MCP1 forms with histone H1 variants and mass spectrometry analysis confirmed that MCP1 peptides share common sequences with H1.2 and H1.5 subtypes.

The identification of auto-antibodies in pancreatic cancer patient sera using a naturally fractionated Panc-1 cell line

The immunogenic nature of cancer can be explored to distinguish pancreatic cancer from related non-cancer conditions. We describe a liquid-based microarray approach followed by statistical analysis and confirmation for discovery of auto-immune biomarkers for pancreatic cancer. Proteins from the Panc-1 pancreatic cancer cell line were fractionated using a 2-D liquid separation method into over 1052 fractions and spotted onto nitrocellulose coated glass slides. The slides were hybridized with 37 pancreatic cancer sera, 24 chronic pancreatitis sera and 23 normal sera to detect elevated levels of reactivity against the proteins in spotted fractions. The response data obtained from protein microarrays was first analyzed by Wilcoxon Rank-Sum Tests to generate two lists of fractions that positively responded to the cancer sera and showed p-values less than 0.02 in the pairwise comparison between cancer specimens and normal and chronic pancreatitis specimens. The top 3 fractions with the lowest correlations were combined in receiver operating characteristic analyses. The area-under-the-curve (AUC) values are 0.813 and 0.792 for cancer vs. normal and cancer vs. pancreatitis respectively. Outlier-Sum statistics were then applied to the microarray data to determine the existence of outliers exclusive in cancer sera. The selected fractions were identified by LC-MS/MS. We further confirmed the occurrence of outliers with three proteins among cancer samples in a confirmation experiment using a separate dataset of 165 serum samples containing 48 cancer sera and 117 non-cancer controls. Phosphoglycerate kinase 1 (PGK1) elicited greater reactivity in 20.9% (10 in 48) of the samples in the cancer group, while no outlier was present in the non-cancer groups.

Usage of cancer associated autoantibodies in the detection of disease

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

Osteopontin is a tumor autoantigen in prostate cancer patients

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

Tumour auto-antibody screening: performance of protein microarrays using SEREX derived antigens

Background

The simplicity and potential of minimal invasive testing using serum from patients make auto-antibody based biomarkers a very promising tool for use in diagnostics of cancer and auto-immune disease. Although several methods exist for elucidating candidate-protein markers, immobilizing these onto membranes and generating so called macroarrays is of limited use for marker validation. Especially when several hundred samples have to be analysed, microarrays could serve as a good alternative since processing macro membranes is cumbersome and reproducibility of results is moderate.

Methods

Candidate markers identified by SEREX (serological identification of antigens by recombinant expression cloning) screenings of brain and lung tumour were used for macroarray and microarray production. For microarray production recombinant proteins were expressed in E. coli by autoinduction and purified His-tag (histidine-tagged) proteins were then used for the production of protein microarrays. Protein arrays were hybridized with the serum samples from brain and lung tumour patients.

Result

Methods for the generation of microarrays were successfully established when using antigens derived from membrane-based selection. Signal patterns obtained by microarrays analysis of brain and lung tumour patients' sera were highly reproducible (R = 0.92-0.96). This provides the technical foundation for diagnostic applications on the basis of auto-antibody patterns. In this limited test set, the assay provided high reproducibility and a broad dynamic range to classify all brain and lung samples correctly.

Conclusion

Protein microarray is an efficient means for auto-antibody-based detection when using SEREX-derived clones expressing antigenic proteins. Protein microarrays are preferred to macroarrays due to the easier handling and the high reproducibility of auto-antibody testing. Especially when using only a few microliters of patient samples protein microarrays are ideally suited for validation of auto-antibody signatures for diagnostic purposes.

Serum immunoreactivity of SMP30 and its tissues expression in hepatocellular carcinoma

OBJECTIVES

To detect serum antibody against SMP30 in HCC patients and to evaluate its potential associations with HCC patient's clinical parameter and expression levels in HCC tissues.

DESIGN AND METHODS

Serum antibody to SMP30 was tested by ELISA method; SMP30 mRNA and protein expression in HCC patients were analyzed using the methods of in situ nucleic acid hybridization and immunohistochemistry, respectively.

RESULTS

The highest relevance of SMP30 antibody was associated with HCC (32.4%). The positive rate of SMP30 antibody was not related to the age of patients, tumor size, metastasis and infections of HBV, but the positive rate for SMP30 antibody in the HCC sera with alpha-fetoprotein (AFP) negative was higher (43.6%) compared with that AFP positive (26.2%). Both SMP30 mRNA and protein expression levels were downregulated in HCC and upregulated in adjacent tissues.

CONCLUSIONS

SMP30 may be useful for HCC serologic screening, especially for the patients with AFP negative.

Multidimensional glycan arrays for enhanced antibody profiling

Carbohydrate-binding antibodies play a critical role in basic and clinical research. Monoclonal antibodies that bind glycans are used to measure carbohydrate expression, and serum antibodies to glycans can be important elements of the immune response to pathogens and vaccines. Carbohydrate antigen arrays, or glycan arrays, have emerged as powerful tools for the high-throughput analysis of carbohydrate-protein interactions. Our group has focused on the development and application of neoglycoprotein arrays, a unique array format wherein carbohydrates are covalently attached to a carrier protein prior to immobilization on the surface. The neoglycoprotein format permits variations of glycan structure, glycan density, and neoglycoprotein density on a single array. The focus of this study was on the effects of neoglycoprotein density on antibody binding. First, we evaluated binding of five monoclonal antibodies (81FR2.2, HE-195, HE-193, B480, and Z2A) to the blood group A antigen and found that neoglycoprotein density had a substantial effect on recognition. Next, we profiled serum antibodies in 15 healthy individuals and showed that inclusion of multiple neoglycoprotein densities helps distinguish different subpopulations of antibodies. Finally, we evaluated immune responses induced by a prostate cancer vaccine and showed that variations in neoglycoprotein density enable one to detect antibody responses that could not be detected otherwise. Neoglycoprotein density is a useful element of diversity for evaluating antibody recognition and, when combined with variations in glycan structure and glycan density, provides multidimensional glycan arrays with enhanced performance for monoclonal antibody development, biomarker discovery, and vaccine optimization.

Characterization of new serum biomarkers in breast cancer using lipid microarrays

Breast cancer is the most common form of cancer among women. Compared with other serum polypeptides, autoantibodies have many appealing features as biomarkers including sensitivity, stability, and easy detection. Anti-lipid autoantibodies are routinely used in the diagnosis of autoimmune diseases, but their potential for cancer diagnosis has not been explored. Dysregulation of cellular signaling in cancer cells would be expected to lead to irregular metabolism of many lipids, which could be sensed by the immune system and cause the production of autoantibodies. Discovery of anti-lipid antibodies could be used as biomarkers for early breast cancer diagnosis. We describe here a more sensitive and accurate method for lipid microarray detection using dual fluorescent labeling, and used it to examine global anti-lipid profiles in the MMTV-Neu transgenic breast cancer model. We conclude that, at the current technology, lipid microarray is not a preferred method for anti-lipid antibody detection in breast cancer animal models. Our result will help the future application of lipid microarrays in identifying anti-lipid autoantibodies in breast cancer and other human diseases.

Development of autoantibody signatures as novel diagnostic biomarkers of non-small cell lung cancer

PURPOSE

To select autoantibody signatures as noninvasive biomarkers of non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

A phage cDNA expression library was constructed with fresh samples from 30 lung cancer patients and biopanned using serum pools of 10 NSCLC patients and 10 healthy controls. A six-phage peptide detector was discovered by two-step immunoscreenings and was validated in an independent set of 90 NSCLC patients and 90 matched healthy controls, 30 NSCLC patients with chemotherapy, and 12 chronic obstructive pulmonary disease (COPD) patients. The expression of a peptide target was validated by using immunohistochemistry. Factors affecting NSCLC-related death were evaluated by Cox regression analysis.

RESULTS

Six phage peptide clones showing higher seroreactivity than others in 30 NSCLC patients were selected for diagnostic validation. The six-phage peptide detector was able to discriminate between NSCLC patients and healthy controls with a sensitivity and specificity of >92%, and had similar validity for indicating NSCLC at early stage. The seroreactivity of the six phage peptides was significantly higher in the NSCLC patients than in those with chemotherapy and the COPD patients, respectively. Of the six phage peptides, one encoded a peptide showing 100% homology to olfactomedin 1. Expression of olfactomedin 1 protein was significantly higher in lung adenocarcinoma than in lung cancer of other histologic types and normal lung tissues. The autoantibody signature was not associated with the prognosis of the NSCLC patients.

CONCLUSIONS

The six-phage peptide detector stands out as promising diagnostic biomarkers for NSCLC, unlikely for NSCLC relapse after chemotherapy. Olfactomedin 1 may be a novel target of lung adenocarcinoma.

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

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

Diagnostic and prognostic biomarker discovery strategies for autoimmune disorders

Current clinical, laboratory or radiological parameters cannot accurately diagnose or predict disease outcomes in a range of autoimmune disorders. Biomarkers which can diagnose at an earlier time point, predict outcome or help guide therapeutic strategies in autoimmune diseases could improve clinical management of this broad group of debilitating disorders. Additionally, there is a growing need for a deeper understanding of multi-factorial autoimmune disorders. Proteomic platforms offering a multiplex approach are more likely to reflect the complexity of autoimmune disease processes. Findings from proteomic based studies of three distinct autoimmune diseases are presented and strategies compared. It is the authors' view that such approaches are likely to be fruitful in the movement of autoimmune disease treatment away from reactive decisions and towards a preventative stand point.

Up-regulated proteins in the fluid bathing the tumour cell microenvironment as potential serological markers for early detection of cancer of the breast

Breast cancer is by far the most common diagnosed form of cancer and the leading cause of cancer death in women today. Clinically useful biomarkers for early detection of breast cancer could lead to a significant reduction in mortality. Here we describe a detailed analysis using gel-based proteomics in combination with mass spectrometry and immunohistochemistry (IHC) of the tumour interstitial fluids (TIF) and normal interstitial fluids (NIF) collected from 69 prospective breast cancer patients. The goal of this study was to identify abundant cancer up-regulated proteins that are externalised by cells in the tumour microenvironment of most if not all these lesions. To this end, we applied a phased biomarker discovery research strategy to the analysis of these samples rather than comparing all samples among each other, with inherent inter and intra-sample variability problems. To this end, we chose to use samples derived from a single tumour/benign tissue pair (patient 46, triple negative tumour), for which we had well-matched samples in terms of epithelial cell numbers, to generate the initial dataset. In this first phase we found 110 proteins that were up-regulated by a factor of 2 or more in the TIF, some of which were confirmed by IHC. In the second phase, we carried out a systematic computer assisted analysis of the 2D gels of the remaining 68 TIF samples in order to identify TIF 46 up-regulated proteins that were deregulated in 90% or more of all the available TIFs, thus representing common breast cancer markers. This second phase singled out a set of 26 breast cancer markers, most of which were also identified by a complementary analysis using LC-MS/MS. The expression of calreticulin, cellular retinoic acid-binding protein II, chloride intracellular channel protein 1, EF-1-beta, galectin 1, peroxiredoxin-2, platelet-derived endothelial cell growth factor, protein disulfide isomerase and ubiquitin carboxyl-terminal hydrolase 5 were further validated using a tissue microarray containing 70 malignant breast carcinomas of various grades of atypia. A significant number of these proteins have already been detected in the blood/plasma/secretome by others. The next steps, which include biomarker prioritization based on the hierarchal evaluation of these markers, antibody and antigen development, assay development, analytical validation, and preliminary testing in the blood of healthy and breast cancer patients, are discussed.

Microarrays with varying carbohydrate density reveal distinct subpopulations of serum antibodies

Antigen arrays have become important tools for profiling complex mixtures of proteins such as serum antibodies. These arrays can be used to better understand immune responses, discover new biomarkers, and guide the development of vaccines. Nevertheless, they are not perfect and improved array designs would enhance the information derived from this technology. In this study, we describe and evaluate a strategy for varying antigen density on an array and then use the array to study binding of lectins, monoclonal antibodies, and serum antibodies. To vary density, neoglycoproteins containing differing amounts of carbohydrate were synthesized and used to make a carbohydrate microarray with variations in both structure and density. We demonstrate that this method provides variations in density on the array surface within a range that is relevant for biological recognition events. The array was used to evaluate density dependent binding properties of three lectins (Vicia villosa lectin B4, Helix pomatia agglutinin, and soybean agglutinin) and three monoclonal antibodies (HBTn-1, B1.1, and Bric111) that bind the tumor-associated Tn antigen. In addition, serum antibodies were profiled from 30 healthy donors. The results show that variations in antigen density are required to detect the full spectrum of antibodies that bind a particular antigen and can be used to reveal differences in antibody populations between individuals that are not detectable using a single antigen density.

Tumor-Associated Antigens and Biomarkers in Cancer and Immune Therapy

Cancer has currently overtaken heart disease as the major cause of mortality in the United States. The Human Genome Project, advances in informatics, miniaturization of sample collection, and increased knowledge of cell signaling pathways has revolutionized the study of disease. Genomics, proteomics, and metabolomics are currently being used to develop molecular signatures for disease diagnosis, prognosis, and therapeutic efficacy. Tumor-associated antigens discovered by these methods are being used to develop passive (humoral) as well as active immunotherapy strategies to stimulate the immune system. Development and validation of biomarkers on a parallel track with therapeutics can speed development times by accurate screening of patient populations and substituting surrogate markers that correlate well with clinical outcomes.

Identification of a new panel of serum autoantibodies associated with the presence of in situ carcinoma of the breast in younger women

PURPOSE

We examined the feasibility of using a panel of autoantibodies to multiple tumor-associated proteins as a method for early detection of breast cancer and, more particularly, carcinoma in situ (CIS).

EXPERIMENTAL DESIGN

PPIA, PRDX2, and FKBP52 were identified as early-stage breast cancer autoantigens by proteomic approaches. The seroreactivity of a panel of antibodies consisting of these three antigens and two previously described autoantigens, HSP60 and MUC1, was tested on 235 samples (60 from primary breast cancer patients, 82 from CIS patients, and 93 from healthy controls) with the use of specific ELISAs. FKBP52, PPIA, and PRDX2 mRNA and protein expression levels were evaluated by reverse transcription-PCR and immunohistochemistry in early-stage breast tumors.

RESULTS

Three of five autoantibodies, FKBP52, PPIA, and PRDX2, showed significantly increased reactivity in primary breast cancer and CIS compared with healthy controls. When combined, the five markers significantly discriminated primary breast cancer [receiver operating characteristic area under the curve, 0.73; 95% confidence interval (95% CI), 0.60-0.79] and CIS (receiver operating characteristic area under the curve, 0.80; 95% CI, 0.71-0.85) from healthy individuals. Importantly, the receiver operating characteristic-area under the curve value of the autoantibody panel was able to distinguish CIS, including high grades, from healthy controls in women under the age of 50 years (receiver operating characteristic area under the curve, 0.85; 95% CI, 0.61-0.92). Finally, only FKBP52 mRNA and protein levels were found to be increased in CIS and primary breast cancer compared with healthy breast tissue.

CONCLUSIONS

This autoantibody assay against a panel of five antigens allows for an accurate discrimination between early-stage breast cancer, especially CIS, and healthy individuals. These results could be of interest in detecting early breast cancer as an aid to mammography, especially in women under the age of 50 years with aggressive cancers.

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.

Sperm-associated antigen 9, a novel biomarker for early detection of breast cancer

To date, there have been no tumor biomarkers validated and incorporated into oncologic practice for the early diagnosis of breast cancer. Recently, we showed that sperm-associated antigen 9 (SPAG9), a member of cancer testis (CT) antigen family, is associated with ovarian carcinomas. In the present study, we investigated SPAG9 expression and humoral immune response in breast cancer. We further evaluated the diagnostic potential of autoantibodies to SPAG9 protein in various stages, grades, and histotypes of breast cancer. We analyzed the association of SPAG9 immunoreactivity score (IRS) with predicted risk of breast cancer recurrence over 10 years. Our reverse transcription-PCR and immunohistochemical analyses revealed SPAG9 expression in 88% breast cancer specimens independent of tumor stages and grades. Further, the humoral immune response against SPAG9 was detected in 80% breast cancer patients with SPAG9-expressing tumors. The linear regression modeling predicted a direct relationship between presence of lymphovascular invasion and high SPAG9 IRS, whereas the univariate and multivariate logistic regression models predicted a strong association of SPAG9 IRS with tumor grade. Further, our data indicated a significant higher trend of SPAG9 IRS with the predicted high risk of breast cancer recurrence. The present investigation reports for the first time SPAG9 expression and humoral immune response in early stages and low-grade breast cancer. Although our data indicated that autoantibodies against SPAG9 represent a promising approach for the development of biomarker, further large-scale validation studies are required to establish its potential use in early diagnosis and monitoring of breast cancer recurrence.

Seromic analysis of antibody responses in non-small cell lung cancer patients and healthy donors using conformational protein arrays

Analysis of antibody responses to self-antigens has driven the development of the field of tumor immunology, with the identification of many protein targets found in cancer but with limited expression in normal tissues. Protein microarray technologies offer an unprecedented platform to assay the serological response of cancer patients to tumor antigens in a comprehensive fashion, against many proteins simultaneously. We developed an array containing 329 full-length proteins, originally identified as antigenic in various cancer patients by serological expression cloning (SEREX), that were immobilized as folded, functional products accessible for antibody binding. To validate the use of these microarrays, we selected 31 sera from non-small cell lung cancer patients previously known to react to the following antigens by ELISA: LAGE-1/CTAG2, MAGEA4, TP53, SSX and SOX2. These sera were compared with 22 sera from healthy donors for reactivity against a series of antigens present on microarrays. The sensitivity and specificity of the arrays compared favorably with standard ELISA techniques (94% concordance). We present here a stringent strategy for data analysis and normalization that is applicable to protein arrays in general, and describe findings suggesting that this approach is suitable for defining potential antigenic targets for cancer vaccine development, serum antibody signatures with clinical value, characterization of predictive serum markers for experimental therapeutics, and eventually for the serological definition of the cancer proteome (seromics).

Cancer-associated antigens and antigen arrays in serological diagnostics of malignant tumors

The appearance of antibodies to cancer-associated antigens in biological fluids (particularly, in blood sera) of cancer patients is now a well-established fact, and their detection by immunochemical methods is a promising approach to diagnostics of malignant neoplasms. In this review, we consider some immunobiological aspects of the most extensively studied cancer-associated B-cell antigens, various applications of autoantibodies as cancer biomarkers, and prospects for the use of antigen arrays for improving diagnostic sensitivity.

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

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

Combining gene expression signatures and autoantibody profiles in human meningioma

Gene expression profiling has emerged as powerful technique for studying the mechanisms of tumor genesis and development. Seroreactivity profiling of tumor antigens is a more recent technique that further contributes to the understanding of tumors and that offers itself for noninvasive tumor diagnosis. We performed expression profiling of 55,000 transcripts and expressed-sequence-tags for 24 meningiomas and related these data to autoantibody profiles of more than 50 antigens immunogenic in the autologous patients. The expression values of antigens in WHO grade I meningioma were significantly higher if the patients' sera reacted with these antigens as confirmed by a two-tailed Wilcoxon-Mann-Whitney test. Specifically, KIAA1344 that was previously identified as frequent antigen marker in meningioma, showed increased expression if antigens against KIAA1344 were detected in autologous patients. Our study is the first to combine genome-wide expression signatures and comprehensive seroreactivity patterns toward a more complete view on tumor immunology, especially concerning the overall role of the level of gene expression on the immunogenicity of meningioma antigens.

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.

Overview and introduction to clinical proteomics

As the field of clinical proteomics progresses, discovery of disease biomarkers becomes paramount. However, the immediate challenges are to establish standard operating procedures for both clinical specimen handling and reduction of sample complexity and to increase the ability to detect proteins and peptides present in low amounts. The traditional concept of a disease biomarker is shifting toward a new paradigm, namely, that an ensemble of proteins or peptides would be more efficient than a single protein/peptide in the diagnosis of disease. Because clinical proteomics usually requires easy access to well-defined fresh clinical specimens (including morphologically consistent tissue and properly pretreated body fluids of sufficient quantity), biorepository systems need to be established. Here, we address these questions and emphasize the necessity of developing various microdissection techniques for tissue specimens, multidimensional fractionation for body fluids, and other related techniques (including bioinformatics), tools which could become integral parts of clinical proteomics for disease biomarker discovery.

Label-free detection of protein-protein interactions at the GaAs/water interface through surface infrared spectroscopy: discrimination between specific and nonspecific interactions by using secondary structure analysis

Here, we propose a label-free detection of protein-protein interactions that enables simultaneous qualitative analysis of target proteins by using Fourier transform infrared (FTIR) absorption spectroscopy in multiple internal reflection geometry (MIR-FTIR). Using this method, the target proteins were detected based on the peak height of the amide I and amide II bands, while discrimination of specific and nonspecific signals is made based on the secondary structure of the analytes, which is determined through second-derivative analysis of the amide I band. As a model system, an antigen peptide was immobilized on the surface of GaAs, which was transparent to mid-infrared light, and the interaction with its antibody was examined in aqueous media. We demonstrated that the binding of the antibody to the antigen immobilized on a GaAs surface selectively gave rise to beta-sheet amide I vibrations (1639 and 1690 cm-1), while no structurally related signals were induced by nonspecifically adsorbed proteins. The peak height of the beta-peak (1639 cm-1) in the amide I band linearly increased with the antiserum concentration as well as that of the amide II band. The detection limit (S/N = 3) was a 1:36 000 dilution for the amide I signal. In addition, through the use of surface-sensitive MIR-FTIR, the present sensor selectively detected the antigen-antibody interactions at the surfaces without being affected by the presence of bulk species, enabling rapid and wash-free detection. Our method provides not only rapid label-free detection of protein-protein interactions but a more accurate discrimination between specific and nonspecific interactions through the use of the secondary structure of the target proteins as a measure for the specific signals.

Protein microarray platforms for clinical proteomics

Proteomics for clinical applications is presently in a state of transition. It has become clear that the classical approaches based on 2-DE and/or MS need to be complemented by different kinds of technologies. The well-known problems include sample complexity, sensitivity, quantitation, reproducibility, and analysis time. We suggest that the new technologies for clinical proteomics can be supported by antibody-centric protein microarray platforms. These platforms presently include antibody microarrays and lysate, or reverse capture/reverse phase protein microarrays. Other forms of these arrays are in less mature developmental stages, including ORF and self assembling protein microarrays. Bioinformatic support for interpreting these arrays is becoming more available as the whole field of systems biology begins to mature. The present set of applications for these platforms is profoundly focused on certain common cancers, immunology, and cystic fibrosis. However, we predict that many more disease entities will become studied as knowledge of the power and availability of these platforms becomes more widely established. We anticipate that these platforms will eventually evolve to accommodate label-free detection technologies, human genome-scale numbers of analytes, and increases in analytic and bioinformatic speeds.

Autoantibody microarrays for biomarker discovery

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