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

Circulating autoantibodies to LGALS3BP: a novel biomarker for cancer

Purpose. Circulating autoantibodies have been extensively investigated as possible markers for early diagnosis of cancer. The present study was carried out to investigate whether anti-LGALS3BP IgG autoantibodies could be classified as a biomarker for malignant tumors. Methods. An in-house developed enzyme-linked immunosorbent assay was used to detect autoantibodies to LGALS3BP in sera from 71 patients with various types of cancers and 54 healthy subjects matched by age and gender. Results. Patients with cancer have significant higher circulating levels of anti-LGALS3BP antibodies as compared to control subjects (P < 0.001). The test has a sensitivity of 33% and a specificity of 98%. Conclusions. Anti-LGALS3BP IgG autoantibodies are a promising biomarker for malignant tumors and could play a role in the development of a multimarker assay for the early detection of cancer.

Profiling the IgOme: meeting the challenge

The entire repertoire of antibodies in our serum, the IgOme, is a historical record of our past experiences and a reflection of our immune status at any given moment. Understanding the dynamics of the IgOme and how the diversity and specificities of serum antibodies change in response to disease and maintenance of homeostasis can directly impact the ability to design and develop novel vaccines, diagnostics and therapeutics. Here we review both direct and indirect methodologies that are being developed to map the complexity and specificities of the antibodies in polyclonal serum - the IgOme.

Sporadic colon cancer murine models demonstrate the value of autoantibody detection for preclinical cancer diagnosis

Although autoantibody detection has been proposed for diagnosis of colorectal cancer, little is known about their initial production and development correlation with cancer progression. Azoxymethane/dextran sodium sulfate (AOM/DSS)-treated mice developed colon adenocarcinoma in the distal colon similar to human sporadic colon cancer. We assessed this model together with AOM and DSS-only models for their applicability to early detection of cancer. All AOM/DSS-treated mice produced autoantibodies to tumor-associated antigens analogous to those observed in human colon cancer patients. Autoantibody response was related to tumor antigen overexpression. Cancer autoantibodies were detected 21 days after starting treatment, when no malignant histopathological features were detectable, and they increased according to tumor progression. When carcinogenesis was induced separately by AOM or DSS, only those mice that developed malignant lesions produced significant levels of autoantibodies. These findings demonstrate that autoantibody development is an early event in tumorigenesis and validates its use for preclinical colon cancer diagnosis.

Cell-material interactions revealed via material techniques of surface patterning

Cell-material interactions constitute a key fundamental topic in biomaterials study. Various cell cues and matrix cues as well as soluble factors regulate cell behaviors on materials. These factors are coupled with each other as usual, and thus it is very difficult to unambiguously elucidate the role of each regulator. The recently developed material techniques of surface patterning afford unique ways to reveal the underlying science. This paper reviews the pertinent material techniques to fabricate patterns of microscale and nanoscale resolutions, and corresponding cell studies. Some issues are emphasized, such as cell localization on patterned surfaces of chemical contrast, and effects of cell shape, cell size, cell-cell contact, and seeding density on differentiation of stem cells. Material cues to regulate cell adhesion, cell differentiation and other cell events are further summed up. Effects of some physical properties, such as surface topography and matrix stiffness, on cell behaviors are also discussed; nanoscaled features of substrate surfaces to regulate cell fate are summarized as well. The pertinent work sheds new insight into the cell-material interactions, and is stimulating for biomaterial design in regenerative medicine, tissue engineering, and high-throughput detection, diagnosis, and drug screening.

Influence of MRE11, RAD50 and NIBRIN protein expression on survival in pancreatic carcinoma after curative resection

The MRE11/RAD50/NIBRIN complex, a protein complex that repairs DNA double-strand breaks, could serve as an early marker for new lesions in pancreatic cancer. We determined the expression of MRE11, RAD50 and NIBRIN, and their possible prognostic value regarding survival. Forty-one patients with ductal adenocarcinoma of the pancreas were included. All underwent curative surgery. Immunohistochemistry was performed for MRE11, RAD50 and NIBRIN. Subsequent analyses were based on a modified immunoreactive score. Statistical analysis was conducted using the statistics program "R". The mean follow-up period was 509 days. The mean age of the patients was 67±8 years, male=56%, female=44%. Eighty-seven percent underwent a Kausch-Whipple procedure, whereas a left side resection was performed in 22% of patients. Positive lymph nodes were found in 80% of cases, and patients were staged UICC IIa (12%), IIb (56%) and IV (29%). Overall significant results were found for MRE11 (p=0.02) and NIBRIN (p=0.01) expression and postoperative survival. We found a significant relation between the expression of MRE11, NIBRIN and the postoperative survival of patients with ductal adenocarcinoma. The link between the expression of the MRN complex, ATM and pancreatic cancer can be used to develop new treatment options for pancreatic carcinoma.

Serologic autoantibodies as diagnostic cancer biomarkers--a review

Current diagnostic techniques used for the early detection of cancers are successful but subject to detection bias. A recent focus lies in the development of more accurate diagnostic tools. An increase in serologic autoantibody levels has been shown to precede the development of cancer disease symptoms. Therefore, autoantibody levels in patient blood serum have been proposed as diagnostic biomarkers for early-stage diagnosis of cancers. Their clinical application has, however, been hindered by low sensitivity, specificity, and low predictive value scores. These scores have been shown to improve when panels of multiple diagnostic autoantibody biomarkers are used. A five-marker biomarker panel has been shown to increase the sensitivity of prostate cancer diagnosis to 95% as compared with 12.2% for prostate-specific antigen alone. New potential biomarker panels were also discovered for lung, colon, and stomach cancer diagnosis with sensitivity of 76%, 65.4%, and 50.8%, respectively. Studies in breast and liver cancer, however, seem to favor single markers, namely α-2-HS-glycoprotein and des-γ-carboxyprothrombin with sensitivities of 79% and 89% for the early detection of the cancers. The aim of this review is to discuss the relevance of autoantibodies in cancer diagnosis and to outline the current methodologies used in the detection of autoantibodies. The review concludes with a discussion of the autoantibodies currently used in the diagnosis of cancers of the prostate, breast, lung, colon, stomach, and liver. A discussion of the potential future use of autoantibodies as diagnostic cancer biomarkers is also included in this review.

Autoantibody biomarkers identified by proteomics methods distinguish ovarian cancer from non-ovarian cancer with various CA-125 levels

PURPOSE

CA-125 has been a valuable marker for detecting ovarian cancer, however, it is not sensitive enough to detect early-stage disease and not specific to ovarian cancer. The purpose of our study was to identify autoantibody markers that are specific to ovarian cancer regardless of CA-125 levels.

METHODS

Top-down and iTRAQ quantitative proteomics methods were used to identify high-frequency autoantibodies in ovarian cancer. Protein microarrays comprising the recombinant autoantigens were screened using serum samples from various stages of ovarian cancer with diverse levels of CA-125 as well as benign and healthy controls. ROC curve and dot blot analyses were performed to validate the sensitivity and specificity of the autoantibody markers.

RESULTS

The proteomics methodologies identified more than 60 potential high-frequency autoantibodies in ovarian cancer. Individual serum samples from ovarian cancer stages I-IV compared to control samples that were screened on a microarray containing native recombinant autoantigens revealed a panel of stage I high-frequency autoantibodies. Preliminary ROC curve and dot blot analyses performed with the ovarian cancer samples showed higher specificity and sensitivity as compared to CA-125. Three autoantibody markers exhibited higher specificity in various stages of ovarian cancer with low and normal CA-125 levels.

CONCLUSIONS

Proteomics technologies are suitable for the identification of protein biomarkers and also the identification of autoantibody biomarkers when combined with protein microarray screening. Using native recombinant autoantigen arrays to screen autoantibody markers, it is possible to identify markers with higher sensitivity and specificity than CA-125 that are relevant to early detection of ovarian cancer.

The membrane molecule RCAS1 induces immune cell apoptosis via the RCAS1-RCAS1R pathway

Tumor-associated antigen receptor-binding cancer antigen expressed on SiSo cells (RCAS1) has been identified as an estrogen-responsive gene and reportedly acts as a ligand for a putative receptor present in a variety of human cell lines and peripheral lymphocytes, thus leading them to apoptosis. In this study, we investigated the biological function of RCAS1 in vitro in inducing the apoptosis of immune cells. We detected the expression of the RCAS1 receptor (RCAS1R) in the cell lines, and investigated the mechanisms behind the apoptosis induced by RCAS1. HeLa cells were transfected with recombinant adenovirus Ad-RCAS1. RCAS1 induced the apoptosis of activated T cells, K562 cells and phytohemagglutinin (PHA)-activated Jurkat cells via the RCAS1-RCAS1R pathway. The expression of RCAS1R was induced. The intracellular overexpression of RCAS1 inhibited the growth of Jurkat and K562 cells. The expression of RCAS1 negatively correlated with the expression of glycogen synthase kinase 3β (GSK3β), but positively correlated with the expression of phosphorylated GSK3β (phGSK3β). RCAS1 expression was identified as a brown staining pattern in the breast cancer specimens. These findings may provide insight into the mechanisms through which tumor cells escape from immune surveillance.

Tumor autoantibodies as biomarkers for predicting ovarian cancer recurrence

Ovarian cancer (OVCA) has a high incidence of recurrence and a high rate of mortality. We performed a pilot study to evaluate the usefulness of tumor autoantibodies to tumor associated antigens (TAA) to predict OVCA recurrence. A validation study with 56 antigens, previously identified in the initial phase of the study, along with 13 known tumor antigens on protein arrays was performed on an independent cohort of recurrent and non-recurrent OVCA patients. Statistical analyses revealed that a panel of 3 antigens predicted recurrence at a median time of 9.07 months prior to clinical recurrence in a study population, where majority of patients had CA125 values less than 35 U/ml, with an average sensitivity, specificity and accuracy of 94.7%, 86.7% and 93.3% respectively. One of the top 3 antigens has been associated with the development of polymyositis (PM) which has been shown in some cases to precede the occurrence of ovarian carcinoma. Our results indicate that these 3 antigens have potential for predicting recurrence at an early time and may have better prognostic utility than CA125 alone for early therapeutic intervention. These biomarkers could guide us to identify those patients that could benefit most from maintenance or consolidation therapy.

Antibody repertoire profiling using bacterial display identifies reactivity signatures of celiac disease

A general strategy to identify serum antibody specificities associated with a given disease state and peptide reagents for their detection was developed using bacterial display peptide libraries and multiparameter flow cytometry (MPFC). Using sera from patients with celiac disease (CD) (n = 45) or healthy subjects (n = 40), bacterial display libraries were screened for peptides that react specifically with antibodies from CD patients and not with those from healthy patients. The libraries were screened for peptides that simultaneously cross-react with CD patient antibodies present in two separate patient groups labeled with spectrally distinct fluorophores but do not react with unlabeled non-CD antibodies, thus affording a quantitative separation. A panel of six unique peptide sequences yielded 85% sensitivity and 91% specificity (AUC = 0.91) on a set of 60 samples not used for discovery, using leave-one-out cross-validation. Individual peptides were dissimilar with known CD-specific antigens tissue transglutaminase (tTG) and deamidated gliadin, and the classifier accuracy was independent of anti-tTG antibody titer. These results demonstrate that bacterial display/MPFC provides a highly effective tool for the unbiased discovery of disease-associated antibody specificities and peptide reagents for their detection that may have broad utility for diagnostic development.

Early detection of cancer in the general population: a blinded case-control study of p53 autoantibodies in colorectal cancer

Background:

Recent reports from cancer screening trials in high-risk populations suggest that autoantibodies can be detected before clinical diagnosis. However, there is minimal data on the role of autoantibody signatures in cancer screening in the general population.

Methods:

Informative p53 peptides were identified in sera from patients with colorectal cancer using an autoantibody microarray with 15-mer overlapping peptides covering the complete p53 sequence. The selected peptides were evaluated in a blinded case–control study using stored serum from the multimodal arm of the United Kingdom Collaborative Trial of Ovarian Cancer Screening where women gave annual blood samples. Cases were postmenopausal women who developed colorectal cancer following recruitment, with 2 or more serum samples preceding diagnosis. Controls were age-matched women with no history of cancer.

Results:

The 50 640 women randomised to the multimodal group were followed up for a median of 6.8 (inter-quartile range 5.9–8.4) years. Colorectal cancer notification was received in 101 women with serial samples of whom 97 (297 samples) had given consent for secondary studies. They were matched 1 : 1 with 97 controls (296 serial samples). The four most informative peptides identified 25.8% of colorectal cancer patients with a specificity of 95%. The median lead time was 1.4 (range 0.12–3.8) years before clinical diagnosis.

Conclusion:

Our findings suggest that in the general population, autoantibody signatures are detectable during preclinical disease and may be of value in cancer screening. In colorectal cancer screening in particular, where the current need is to improve compliance, it suggests that p53 autoantibodies may contribute towards risk stratification.

PanelComposer: a web-based panel construction tool for multivariate analysis of disease biomarker candidates

Measuring and evaluating diagnostic efficiency is important in biomarker discovery and validation. The receiver operating characteristic (ROC) curve is a graphical plot for assessing the performance of a classifier or predictor that can be used to test the sensitivity and specificity of diagnostic biomarkers. In this study, we describe PanelComposer, a Web-based software tool that uses statistical results from proteomic expression data and validates biomarker candidates based on ROC curves and the area under the ROC curve (AUC) values using a logistic regression model and provides an ordered list that includes ROC graphs and AUC values for proteins (individually or in combination). This tool allows users to easily compare and assess the effectiveness and diagnostic efficiency of single or multiprotein biomarker candidates. PanelComposer is available publicly at http://panelcomposer.proteomix.org/ and is compatible with major Web browsers.

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.

Anti-idiotypic monobodies for immune response profiling

A major goal in the study of autoimmune disease is the identification of biomarkers of disease to allow early diagnosis and initiation of treatment. The production of autoantibodies is the key feature of most autoimmune disease, so much effort has focused on characterizing the antigens reactive with these antibodies. However, even for the most well understood autoimmune diseases like rheumatoid arthritis and systemic lupus erythematosus, identification of antigens that detect autoantibodies in all patients have yet to be discovered. We describe a novel strategy for deriving mimotopes to disease-specific serum antibodies by selecting anti-idiotypic monobodies from a large molecular diversity library. Monobodies are derived by partial randomization of two surface exposed loops of a fibronectin domain scaffold in a phage display vector. The phage library is selected for binding to serum antibodies using a subtractive panning strategy. We evaluated this strategy by selecting the monobody library on a pool of serum immunoglobulin derived from a group of rheumatoid arthritis patients and evaluated selected clones for multi-patient reactivity and specificity for rheumatoid arthritis. The use of the fibronectin scaffold to derive stable, easy to produce molecular probes for diagnosis of autoimmune disease could be of significant value in improving diagnostic assays for virtually any disease that exhibits a characteristic immune response.

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.

Autoantibodies as biomarkers for ovarian cancer

Ovarian cancer (OVCA) has the highest mortality of all gynecologic cancers. The poor survival rate is due to the lack of diagnostic screening tests and high incidence of recurrence in OVCA patients resistant to chemotherapy that leads to a more aggressive form of the disease. Therefore, a search for biomarkers holds great promise not only for early detection of OVCA at presymptomatic stage and for monitoring the course of the disease during the first-line chemotherapy treatment but also for identifying those women whose disease is likely to recur. Research efforts have sought to unravel the complexity of the tumor specific proteome by profiling immune responses generated against tumor associated antigens (TAAs) using multianalyte-based analytical discovery platforms readily adaptable to clinical diagnostic screening tests. The occurrence of tumor-specific autoantibodies directed to respective TAAs can be observed before the development of clinical symptoms. Evaluation of the level of tumor autoantibodies during the time of tumor debulking followed by first-line chemotherapy for the prediction of early recurrence as well as their correlation with other clinical parameters to evaluate their prognostic value has been conducted in various clinical studies. The anti-tumor immune response against OVCA is the ultimate key to the development of multiple immune-based therapeutic strategies that have been proposed and tested in different clinical trials that may have beneficial impact on the disease outcome in OVCA patients.

Tumor-associated autoantibody signature for the early detection of gastric cancer

Autoantibodies against tumor-associated antigens are very attractive biomarkers for the development of noninvasive serological tests for the early detection of cancer because of their specificity and stability in the sera. In our study, we applied T7 phage display-based serological analysis of recombinant cDNA expression libraries technique to identify a representative set of antigens eliciting humoral responses in patients with gastric cancer (GC), produced phage-antigen microarrays and exploited them for the survey of autoantibody repertoire in patients with GC and inflammatory diseases. We developed procedures for data normalization and cutoff determination to define sero-positive signals and ranked them by the signal intensity and frequency of reactivity. To identify autoantibodies with the highest diagnostic value, a 1,150-feature microarray was tested with sera from 100 patients with GC and 100 cancer-free controls, and then the top-ranked 86 antigens were used for the production of focused array that was tested with an independent validation set comprising serum samples from 235 patients with GC, 154 patients with peptic ulcer and gastritis and 213 healthy controls. The receiver operating characteristic curve analysis showed that 45-autoantibody signature could discriminate GC and healthy controls with area under the curve (AUC) of 0.79 (59% sensitivity and 90% specificity), GC and peptic ulcer with AUC of 0.76 and GC and gastritis with AUC of 0.64. Moreover, it could detect early GC with equal sensitivity than advanced GC. Interestingly, the autoantibody production did not correlate with histological type, H. pylori status, grade, localization and size of the primary tumor, whereas it appeared to be associated with the metastatic disease.

Emerging technology of in situ cell free expression protein microarrays

Recently, in situ protein microarrays have been developed for large scale analysis and high throughput studies of proteins. In situ protein microarrays produce proteins directly on the solid surface from pre-arrayed DNA or RNA. The advances in in situ protein microarrays are exemplified by the ease of cDNA cloning and cell free protein expression. These technologies can evaluate, validate and monitor protein in a cost effective manner and address the issue of a high quality protein supply to use in the array. Here we review the importance of recently employed methods: PISA (protein in situ array), DAPA (DNA array to protein array), NAPPA (nucleic acid programmable protein array) and TUSTER microarrays and the role of these methods in proteomics.

Antibody profiling with protein antigen microarrays in early stage cancer

INTRODUCTION

Proteins not present in normal cells, that is, cancer cells, may elicit a host immune response that leads to the generation of antibodies that might react with these tumor-associated proteins. In recent years, a growing number of reports have showed that autoantibody profiling may provide an alternative approach for the detection of cancer. However, most studies of antigen-autoantibody reactivity have relied on recombinant proteins. Recombinant proteins lack the proper post-translational modifications present in native proteins. Because of this limitation, native or natural protein antigen microarrays are gaining popularity for profiling antibody responses.

AREAS COVERED

i) To illustrate some examples of autoantibodies as signatures for early stage cancer; ii) to briefly outline the various protein antigen microarray platforms; iii) to illustrate the use of native or natural protein microarrays in the discovery of potential biomarkers and iv) to discuss the advantages of native protein antigen microarrays over other approaches.

EXPERT OPINION

The nature of protein microarray platforms is conducive to multiplexing, which amplifies the potential for uncovering effective biomarkers for many significant diseases. However, the major challenge will be in integrating microarray platforms into multiplexed clinical diagnostic tools, as the main drawback is the reproducibility and coefficient of variation of the results from array to array, and the transportability of the array platform to a more automatable platform.

Serologic laboratory findings in malignancy

Autoantibodies are extremely promising diagnostic and prognostic biomarkers of cancer, and have the potential to promote early diagnosis and to make a large impact by improving patient outcome and decreasing mortality. Moreover, autoantibodies may be useful reagents in the identification of subjects at risk for cancer, bearing premalignant tissue changes. Great efforts are being made in many laboratories to validate diagnostic panels of autoantibodies with high sensitivity and specificity that could be useful in a clinical setting. It is likely that prospective studies of sufficiently large cohorts of patients and controls using high-throughput technology may allow the identification of biomarkers with diagnostic significance, and perhaps of discrete antigen phenotypes with clinical significance. The identification of TAAs may also be essential for the development of anticancer vaccines, because autoantibodies found in cancer sera target molecules involved in signal transduction, cell-cycle regulation, cell proliferation, and apoptosis, playing important roles in carcinogenesis. On this basis, molecular studies of antigenantibody systems in cancer promise to yield valuable information on the carcinogenic process. TAAs identified by serum antibodies in cancer sera can be natural immunogenic molecules, useful as targets for cancer immunotherapy. An important problem encountered in the practice of medicine is the identification of healthy individuals in the general population who unknowingly are at high risk of developing cancer. For the rheumatologist, a related problem is the identification of those patients with rheumatic diseases who are at high risk for developing a malignant process. These problems encountered in the fields of cancer and the rheumatic diseases can in the future be helped by new diagnostic instruments based on antibodies. The need for promoting the early diagnosis of cancer is a recognized major public health problem in need of significant research support for the validation of multiple promising but inconclusive studies, with the intention of producing diagnostic panels of autoantibodies in various types of cancers. Cancer developing in patients with rheumatic diseases is also an important problem requiring prospective longterm follow-up studies of patients with rheumatic diseases, particularly because some of the new biologic therapies seem to increase the cancer risk. It is possible that a panel of autoantibodies common to patients with cancer and the rheumatic diseases may prove to be of value in the identification of those patients with ADs at high risk for neoplasms.

Parallel factor analysis of ovarian autofluorescence as a cancer diagnostic

BACKGROUND AND OBJECTIVES

Endogenous fluorescence from certain amino acids, structural proteins, and enzymatic co-factors in tissue is altered by carcinogenesis. We evaluate the potential of these changes in fluorescence to predict a diagnosis of malignancy and to estimate the risk of developing ovarian cancer.

STUDY DESIGN/MATERIALS AND METHODS

Ovarian biopsies were interrogated over 270-550 nm excitation and fluorescence was collected from 290 to 700 nm. Two hundred forty-nine measurements were performed on 49 IRB-consented patients undergoing oophorectomy. Data are analyzed using parallel factor analysis to determine excitation and emission spectra of the underlying fluorophores that contribute to the total detected fluorescence intensity.

RESULTS

Using multivariate normal distribution fits and cross-validation techniques, sensitivity and specificity of 88% and 93%, respectively, are achieved when classifying malignant samples versus others, while 88% and 80%, respectively, are achieved when classifying normal post-menopausal patients as being either at high- or low-risk of developing ovarian cancer based on their personal and family history of cancer. Performance of classifying cancer increases when the normal group does not include benign neoplasm and endometriosis samples. Performance of high- versus low-risk classification decreases when normal samples include both pre- and post-menopausal women. Excitation over 270-400 and 380-560 nm, respectively, have the best diagnostic performance for cancer detection and risk-status assessment.

CONCLUSIONS

Assessing the endogenous fluorescence could be useful in screening women at increased risk of developing ovarian cancer.

Multicenter study identified molecular blood-born protein signatures for Wilms Tumor

Wilms Tumor (WT) is the most common renal childhood tumor. Recently, we reported a cDNA microarray expression pattern that varied between WTs with different risk histology. Since the Societé Internationale d'Oncologie Pédiatrique (SIOP) in Europe initiates treatment without a histological confirmation, it is important to identify blood-born markers that indicate WT development. In a multicenter study, we established an autoantibody signature by using an array with 1,827 recombinant E. coli clones. This array was screened with sera of patients with WT recruited by SIOP or the Children's Oncology Group (COG). We report an extended number of antigens that are reactive with autoantibodies present in sera from patients with WT. We established an autoantibody signature that separates untreated patients with WT recruited in SIOP from non-WT controls with a specificity of 0.83 and a sensitivity of 0.82 at standard deviations of 0.02 and 0.04, respectively. Likewise, patients recruited in the COG in the United States were separated from the controls with an accuracy of 0.83 at a standard deviation of 0.02. Proteins that were most significant include zinc finger proteins (e.g., ZFP 346), ribosomal proteins and the protein fascin that has been associated with various types of cancer including renal cell carcinoma. Our study provides first evidence for autoantibody signatures for WTs and suggests that these may be most informative before chemotherapy. We present the first multicenter study of autoantibody signatures in patients with WT. We established an autoantibody signature that separates patients with WT from controls.

Development of autoantibody signatures as biomarkers for early detection of colorectal carcinoma

PURPOSE

To select autoantibody signatures for early detection of colorectal cancer (CRC).

EXPERIMENTAL DESIGN

A phage cDNA expression library was constructed with fresh tumors from 30 CRC patients and biopanned by using serum pools of 20 CRC patients and 20 healthy controls. A classifier was discovered in the training set of 30 CRC patients at stages I and II and 30 matched healthy controls and then blindly validated in an independent set of 60 CRC patients, 60 healthy controls, 52 polyps patients, and 30 autoimmune diseases patients. Expression of proteins was examined by using immunohistochemistry.

RESULTS

Five-phage peptide clones showing higher discriminatory power than others in training set were selected for validation. The five-phage peptide classifier was able to discriminate between early CRC patients and healthy controls, with sensitivities of 90.0% to 92.7% and specificities of 91.7% to 93.3%. In those with serum carcinoembryonic antigen less than 5 ng/mL, the classifier was efficient in discriminating CRC from healthy controls, with an area under the curve of 0.975. The classifier was able to discriminate all of the 9 patients with serrated adenoma from healthy controls. Thirteen (43.3%) of the patients with autoimmune diseases were misclassified. Of the five phage peptides, one encoded a peptide identical to immunoglobulin G (IgG) heavy-chain constant region. IgG immunostaining was stronger in mesenchymal cells than in cancer cells in the tumors and was apparent in serrated adenoma.

CONCLUSIONS

The five-phage peptide classifier stands out as promising early diagnostic biomarkers for CRC, but it is unsuitable for discriminating CRC from autoimmune diseases. Truncated IgGs generated from the tumors might be novel CRC-associated antigens.

Therapeutic cancer vaccines and translating vaccinomics science to the global health clinic: emerging applications toward proof of concept

As vaccines evolve to be a more common treatment for some cancers, further research is needed to improve the process of developing vaccines and assessing response to treatment. Vaccinomics involves a wide-ranging integration of multiple high throughput technologies including transcriptional, translational, and posttranslational population-based assessments of the human genome, transcriptome, proteome, and immunome. Vaccinomics combines the fields of immunogenetics, immunogenomics, immunoproteomics, and basic immunology to create vaccines that are tailor made to an individual or groups of individuals. This broad range of omics applications to tumor immunology includes antigen discovery, diagnostic biomarkers, cancer vaccine development, predictors of immune response, and clinical response biomarkers. These technologies have aided in the advancement of cancer vaccine development, as illustrated in examples including NY-ESO-1 originally defined by SEREX, and HER2/neu peptides analyzed via high-throughput epitope prediction methods. As technology improves, it presents an opportunity to improve cancer immunotherapy on a global scale, and attention must also be given to utilize these high-throughput methods for the understanding of cancer and immune signatures across populations.

Immunogenicity of autoantigens

Background

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

Results

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

Conclusions

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

Maternal blood serum and plasma human tumor-associated antigen RCAS1 during the course of uncomplicated pregnancies: a prospective study

PROBLEM

we aimed to investigate the expression of the tumor-associated RCAS1 protein in maternal blood of uncomplicated pregnancies.

METHOD OF STUDY

maternal blood was obtained from women with uncomplicated pregnancies (N = 43) at 11-13, 20-22, 32-34, 37-38 weeks of gestation, and immediately after delivery. Serum RCAS1 concentration was studied by ELISA, and plasma mRNA was subjected to real-time (RT)-PCR.

RESULTS

serum RCAS1 protein concentration was significantly up-regulated at 11-13 and 20-22 weeks than that at 32-34 weeks and after delivery. RCAS1 mRNA level was significantly increased at 11-13 weeks than that at 37-38 weeks. A significant positive correlation was defined between RCAS1 serum concentration at 11-13 weeks and gestational age at delivery and that between plasma RCAS1 mRNA levels at 37-38 weeks and umbilical cord blood base excess. A significant negative correlation was found between RCAS1 serum concentration at 37-38 weeks and umbilical cord blood pH at delivery.

CONCLUSIONS

RCAS1 protein might have importance in the development of uncomplicated pregnancies and for the prediction of pregnancy outcome.

Akt3 controls vascular endothelial growth factor secretion and angiogenesis in ovarian cancer cells

The PI3 kinase/Akt pathway is commonly deregulated in human cancers, functioning in such processes as proliferation, glucose metabolism, survival and motility. We have previously described a novel function for one of the Akt isoforms (Akt3) in primary endothelial cells: the control of VEGF-induced mitochondrial biogenesis. We sought to determine if Akt3 played a similar role in carcinoma cells. Because the PI3 kinase/Akt pathway has been strongly implicated as a key regulator in ovarian carcinoma, we tested the role of Akt3 in this tumor type. Silencing of Akt3 by shRNA did not cause an overt reduction in mitochondrial gene expression in a series of PTEN positive ovarian cancer cells. Rather, we find that blockade of Akt3, results in smaller, less vascularized tumors in a xenograft mouse model that is correlated with a reduction in VEGF expression. We find that blockade of Akt3, but not Akt1, results in a reduction in VEGF secretion and retention of VEGF protein in the endoplasmic reticulum (ER). The reduction in secretion under conditions of Akt3 blockade is, at least in part, due to the down regulation of the resident golgi protein and reported tumor cell marker, RCAS1. Conversely, over-expression of Akt3 results in an increase in RCAS1 expression and in VEGF secretion. Silencing of RCAS1 using siRNA inhibits VEGF secretion. These findings suggest an important role for Akt3 in the regulation of RCAS1 and VEGF secretion in ovarian cancer cells.

Depletion of the histone chaperone tNASP inhibits proliferation and induces apoptosis in prostate cancer PC-3 cells

BACKGROUND

NASP (Nuclear Autoantigenic Sperm Protein) is a histone chaperone that is present in all dividing cells. NASP has two splice variants: tNASP and sNASP. Only cancer, germ, transformed, and embryonic cells have a high level of expression of the tNASP splice variant. We examined the consequences of tNASP depletion for prostate cancer PC-3 cells.

METHODS

tNASP was depleted from prostate cancer PC-3 cells, cervical cancer HeLa cells, and prostate epithelial PWR-1E cells using lentivirus expression of tNASP shRNA. Cell cycle changes were studied by proliferation assay with CFSE labeling and double thymidine synchronization. Gene expression profiles were detected using RT(2)Profiler PCR Array, Western and Northern blotting.

RESULTS

PC-3 and HeLa cells showed inhibited proliferation, increased levels of cyclin-dependant kinase inhibitor p21 protein and apoptosis, whereas non-tumorigenic PWR-1E cells did not. All three cell types showed decreased levels of HSPA2. Supporting in vitro experiments demonstrated that tNASP, but not sNASP is required for activation of HSPA2.

CONCLUSIONS

Our results demonstrate that PC-3 and HeLa cancer cells require tNASP to maintain high levels of HSPA2 activity and therefore viability, while PWR-1E cells are unaffected by tNASP depletion. These different cellular responses most likely arise from changes in the interaction between tNASP and HSPA2 and disturbed tNASP chaperoning of linker histones. This study has demonstrated that tNASP is critical for the survival of prostate cancer cells and suggests that targeting tNASP expression can lead to a new approach for prostate cancer treatment.

Autoantibodies against MMP-7 as a novel diagnostic biomarker in esophageal squamous cell carcinoma

AIM: To evaluate the diagnostic values of serum autoantibodies against matrix metalloproteinase-7 (MMP-7) in patients with esophageal squamous cell carcinoma (ESCC).

METHODS: The MMP-7 cDNA was cloned from ESCC tissues, and MMP-7 was expressed and purified from a prokaryotic system. MMP-7 autoantibodies were then measured in sera from 50 patients with primary ESCC and 58 risk-matched controls, using a reverse capture enzyme-linked immunosorbent assay (ELISA) in which autoantibodies to MMP-7 bound to the purified MMP-7 proteins. In addition, MMP-7 autoantibody levels in sera from 38 gastric cancer patients and from control serum samples were also tested.

RESULTS: The optimum conditions for recombinant MMP-7 protein expression were determined as 0.04 mmol/L Isopropyl-β-D-Thiogalactopyranoside (IPTG) induction at 37°C for four hours. The levels of serum autoantibodies against MMP-7 were significantly higher in patients with ESCC than in the matched-control samples (OD450 = 1.69 ± 0.08 vs OD450 = 1.55 ± 0.10, P < 0.001). The area under the receiver operating characteristic (ROC) curve was 0.87. The sensitivity and specificity for detection of ESCC were 78.0% and 81.0%, respectively, when the OD450 value was greater than 1.65. Although the levels of autoantibodies against MMP-7 were also significantly higher in patients with gastric cancer compared to control samples (OD450 = 1.62 ± 0.06 vs OD450 = 1.55 ± 0.10, P < 0.001), the diagnostic accuracy was less significant than in ESCC patients. The area of ROC curve was 0.75, whereas the sensitivity and specificity were 60.5% and 71.7%, respectively, when the cut-off value of OD450 was set at 1.60.

CONCLUSION: Serum autoantibody levels of MMP-7 may be a good diagnostic biomarker for esophageal squamous cell carcinoma.

Expression of the human cancer/testis antigen NY-SAR-35 is activated by CpG island hypomethylation

The novel cancer/testis antigen gene, NY-SAR-35, is expressed exclusively in normal testis and in various histological types of tumor. However, the NY-SAR-35 gene expression is observed to be aberrant in several cancer cell lines and tissues. The analysis of methylation status of the NY-SAR-35 gene promoter in various cancer cell lines showed that its expression was related to methylation of the promoter region. Treatment of human cancer cell lines with the demethylating agent 5-aza-2'-deoxycytidine activated the expression of the NY-SAR-35 gene. In addition, transfection experiments on various fragments of the CpG-rich gene promoter indicate that in vitro methylation of the NY-SAR-35 gene promoter results in the loss of promoter activity. The expression of NY-SAR-35 is therefore activated by hypomethylation of the CpG island in the gene promoter.

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.

Identification of SEC61β and its autoantibody as biomarkers for colorectal cancer

BACKGROUND

To identify novel serological biomarkers for human colorectal cancer (CRC), we analyzed CRC tissues using gel-assisted digestion and isobaric tags with related and absolute quantitation (iTRAQ) labeling mass spectrometry (MS). By comparing pairs of tumor tissues and matched normal tissues, we discovered the SEC61β with expression changes 3.3-fold and a marginal statistical significance (p=0.052) previously.

METHODS

SEC61β expression in CRC tissues was further analyzed by western blotting and immunohistochemistry. We next assessed the putative diagnostic value of the SEC61β autoantibody as a serum marker.

RESULTS

Using western blotting analysis, SEC61β expression was increased 1.9-fold in tumor tissues. Immunohistochemical analysis of 64 CRC specimens showed that SEC61β was positively detected in 64% of the tumors, but weakly or not detected in >80% of the adjacent nontumor epithelial cells. Western blot analysis with plasma samples showed that the sensitivity and specificity of the SEC61β autoantibody from patients with CRC were 79% and 75%, respectively. Importantly, the results of the SEC61β autoantibody for early detection of colorectal cancer revealed a higher sensitivity of 77% than the carcinoembryonic antigen (CEA) assay.

CONCLUSIONS

Measurement of SEC61β autoantibody levels may provide an alternative detection indicator for CRC, particularly among early-stage patients.

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

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

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

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

Exploring the immunoproteome for ovarian cancer biomarker discovery

Most scientific efforts towards early detection of ovarian cancer are commonly focused on the discovery of tumour-associated antigens (TAA). Autologous antibodies against TAA, however, may serve as more sensitive diagnostic markers. They circulate in the blood before TAA and are usually more abundant than the TAAs themselves as a result of amplification through the humoral immune response. Accumulating evidence also suggests that a humoral response already exists during malignant transformation when aberrant gene expression is translated into premalignant cellular changes. This article reviews the current knowledge about autoantibodies against TAA in ovarian cancer and presents current immunoproteomic approaches for their detection.

Seromic profiling of colorectal cancer patients with novel glycopeptide microarray

Cancer-associated autoantibodies hold promise as sensitive biomarkers for early detection of cancer. Aberrant post-translational variants of proteins are likely to induce autoantibodies, and changes in O-linked glycosylation represent one of the most important cancer-associated post-translational modifications (PTMs). Short aberrant O-glycans on proteins may introduce novel glycopeptide epitopes that can elicit autoantibodies because of lack of tolerance. Technical barriers, however, have hampered detection of such glycopeptide-specific autoantibodies. Here, we have constructed an expanded glycopeptide array displaying a comprehensive library of glycopeptides and glycoproteins derived from a panel of human mucins (MUC1, MUC2, MUC4, MUC5AC, MUC6 and MUC7) known to have altered glycosylation and expression in cancer. Seromic profiling of patients with colorectal cancer identified cancer-associated autoantibodies to a set of aberrant glycopeptides derived from MUC1 and MUC4. The cumulative sensitivity of the array analysis was 79% with a specificity of 92%. The most prevalent of the identified autoantibody targets were validated as authentic cancer immunogens by showing expression of the epitopes in cancer using novel monoclonal antibodies. Our study provides evidence for the value of glycopeptides and other PTM-peptide arrays in diagnostic measures.

Identification of MST1/STK4 and SULF1 proteins as autoantibody targets for the diagnosis of colorectal cancer by using phage microarrays

The characterization of the humoral response in cancer patients is becoming a practical alternative to improve early detection. We prepared phage microarrays containing colorectal cancer cDNA libraries to identify phage-expressed peptides recognized by tumor-specific autoantibodies from patient sera. From a total of 1536 printed phages, 128 gave statistically significant values to discriminate cancer patients from control samples. From this, 43 peptide sequences were unique following DNA sequencing. Six phages containing homologous sequences to STK4/MST1, SULF1, NHSL1, SREBF2, GRN, and GTF2I were selected to build up a predictor panel. A previous study with high-density protein microarrays had identified STK4/MST1 as a candidate biomarker. An independent collection of 153 serum samples (50 colorectal cancer sera and 103 reference samples, including healthy donors and sera from other related pathologies) was used as a validation set to study prediction capability. A combination of four phages and two recombinant proteins, corresponding to MST1 and SULF1, achieved an area under the curve of 0.86 to correctly discriminate cancer from healthy sera. Inclusion of sera from other different neoplasias did not change significantly this value. For early stages (A+B), the corrected area under the curve was 0.786. Moreover, we have demonstrated that MST1 and SULF1 proteins, homologous to phage-peptide sequences, can replace the original phages in the predictor panel, improving their diagnostic accuracy.

Protein microarray signature of autoantibody biomarkers for the early detection of breast cancer

Cancer patients spontaneously generate autoantibodies (AAb) to tumor-derived proteins. To detect AAb, we have probed novel high-density custom protein microarrays (NAPPA) expressing 4988 candidate tumor antigens with sera from patients with early stage breast cancer (IBC), and bound IgG was measured. We used a three-phase serial screening approach. First, a prescreen was performed to eliminate uninformative antigens. Sera from stage I-III IBC (n = 53) and healthy women (n = 53) were screened for AAb to all 4988 protein antigens. Antigens were selected if the 95th percentile of signal of cases and controls were significantly different (p < 0.05) and if the number of cases with signals above the 95th percentile of controls was significant (p < 0.05). These 761 antigens were screened using an independent set of IBC sera (n = 51) and sera from women with benign breast disease (BBD) (n = 39). From these, 119 antigens had a partial area under the ROC curve (p < 0.05), with sensitivities ranging from 9-40% at >91% specificity. Twenty-eight of these antigens were confirmed using an independent serum cohort (n = 51 cases/38 controls, p < 0.05). Using all 28 AAb, a classifier was identified with a sensitivity of 80.8% and a specificity of 61.6% (AUC = 0.756). These are potential biomarkers for the early detection of breast cancer.

Autoantibodies against stress-induced phosphoprotein-1 as a novel biomarker candidate for ovarian cancer

Detection of autoantibodies against tumor-associated antigens (TAA) has recently been shown to be a powerful tool for early detection of various cancers. The aim of this study was to investigate the possibility of using autoantibodies against TAA as novel biomarkers by a proteomics-based approach in patients with ovarian cancer. We used two-dimensional differential gel electrophoresis analysis of immuno-precipitated tumor antigens (2D-DITA) to compare the levels of autoantibodies in pretreatment and posttreatment sera of patients with ovarian cancers. The identified autoantibodies were validated by SYBR Green real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC). We further evaluated the level of autoantibody in sera of 68 ovarian cancer patients by an enzyme-linked immunosorbent assay (ELISA). The autoantibody directed against stress-induced phosphoprotein-1 (STIP-1) emerged as a novel biomarker candidate for ovarian cancer. SYBR Green PCR and IHC confirmed that the STIP-1 mRNA and protein expression levels were significantly up-regulated in ovarian cancers compared with normal and benign tumors (P = 0.003 and P < 0.001, respectively). A preliminary ELISA study showed that the serum levels of anti-STIP-1 autoantibodies were significantly elevated in ovarian cancer patients compared with healthy controls (P = 0.03). The results suggest that 2D-DITA is a useful tool to detect autoantibodies and that STIP-1 is a potential biomarker candidate for ovarian cancers.

Lung cancer-associated auto-antibodies measured using seven amino acid peptides in a diagnostic blood test for lung cancer

Autoantibody profiling is a developing approach that incorporates immune recognition of myriad aberrant cancer proteins into a single diagnostic assay. We have previously described methodology to screen T7-phage NSCLC-cDNA libraries for phage-expressed proteins recognized by NSCLC-associated antibodies, and developed a multiplex assay that has excellent ability to discriminate NSCLC from control samples. This follow-up report describes the development and testing of a diagnostic autoantibody assay that uses seven amino-acid peptides as capture proteins. A random-peptide M13-phage library was screened for proteins recognized by cancer-associated antibodies. One hundred twenty-one NSCLC case and control samples were divided into two groups for training and validation, or alternately, evaluated sequentially in a leave-one-out analysis. Candidate antibody-markers were ranked by statistical discrimination between cases and controls. Receiver-Operating-Characteristic (ROC-AUC) suggested the predictive potential of various marker combinations. A five-marker combination (AUC = 0.982) afforded 90% sensitivity and 73% specificity in a training-and-testing strategy. Leave-one-out validation provided similar class prediction. Data confirm the potential of antibody profiling to provide high levels of cancer prediction. Random peptide libraries offer a universal source of capture proteins for antibody profiling that obviates the need for tumor-specific library construction and abrogates inherent problems with tumor heterogeneity during biomarker discovery.

Weighted Area Under the Receiver Operating Characteristic Curve and Its Application to Gene Selection

Partial area under the ROC curve (PAUC) has been proposed for gene selection in Pepe et al. (2003) and thereafter applied in real data analysis. It was noticed from empirical studies that this measure has several key weaknesses, such as an inability to reflect nonuniform weighting of different decision thresholds, resulting in large numbers of ties. We propose the weighted area under the ROC curve (WAUC) in this paper to address the problems associated with PAUC. Our proposed measure enjoys a greater flexibility to describe the discrimination accuracy of genes. Nonparametric and parametric estimation methods are introduced, including PAUC as a special case, along with theoretical properties of the estimators. We also provide a simple variance formula, yielding a novel variance estimator for nonparametric estimation of PAUC, which has proven challenging in previous work. The proposed methods permit sensitivity analyses, whereby the impact of differing weight functions on gene rankings may be assessed and results may be synthesized across weights. Simulations and re-analysis of two well-known microarray datasets illustrate the practical utility of WAUC.

Analysis of the expression of human tumor antigens in ovarian cancer tissues

Biomarkers for early detection of cancer have great clinical diagnostic potential. Numerous reports have documented the generation of humoral immune responses that are triggered in response to changes in protein expression patterns in tumor tissues and these biomarkers are referred to as tumor associated antigens (TAAs). Using a high-throughput technology, we previously identified 65 proteins as diagnostically useful TAAs by profiling the humoral immune responses in ovarian cancer (OVCA) patients. Here we determined the expression status of some of those TAAs in tissues from OVCA patients. The protein expression patterns of 4 of those 65 antigens, namely NASP, RCAS1, Nijmegen breakage syndrome1 (NBS1) and eIF5A, along with p53 and Her2 (known molecular prognosticators) and two proteins that interact with NBS1, MRE11 and RAD50, were assessed by immunohistochemistry (IHC). NASP and RCAS1 proteins were more frequently expressed in ovarian cancer tissues than with normal ovarian tissue and serous cystadenomas and MRE11 was less frequently expressed. When evaluated simultaneously, only NASP and MRE11 remained statistically significant with sensitivity of 66% and specificity of 89%. None of these proteins' expression levels were prognostic for survival. Together, our results indicate that occurrence of humoral immune responses against some of these TAAs in OVCA patients is triggered by antigen protein overexpression.

Improving seroreactivity-based detection of glioma

Seroreactivity profiling emerges as valuable technique for minimal invasive cancer detection. Recently, we provided first evidence for the applicability of serum profiling of glioma using a limited number of immunogenic antigens. Here, we screened 57 glioma and 60 healthy sera for autoantibodies against 1827 Escherichia coli expressed clones, including 509 in-frame peptide sequences. By a linear support vector machine approach, we calculated mean specificity, sensitivity, and accuracy of 100 repetitive classifications. We were able to differentiate glioma sera from sera of the healthy controls with a specificity of 90.28%, a sensitivity of 87.31% and an accuracy of 88.84%. We were also able to differentiate World Health Organization grade IV glioma sera from healthy sera with a specificity of 98.45%, a sensitivity of 80.93%, and an accuracy of 92.88%. To rank the antigens according to their information content, we computed the area under the receiver operator characteristic curve value for each clone. Altogether, we found 46 immunogenic clones including 16 in-frame clones that were informative for the classification of glioma sera versus healthy sera. For the separation of glioblastoma versus healthy sera, we found 91 informative clones including 26 in-frame clones. The best-suited in-frame clone for the classification glioma sera versus healthy sera corresponded to the vimentin gene (VIM) that was previously associated with glioma. In the future, autoantibody signatures in glioma not only may prove useful for diagnosis but also offer the prospect for a personalized immune-based therapy.

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.

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer

Mucinous epithelial ovarian cancers are clinically and morphologically distinct from the other histopathologic subtypes of ovarian cancer. Unlike other ovarian subtypes, epidemiologic studies have indicated that tobacco exposure is a significant risk factor for developing mucinous ovarian cancer. Detection of autoantibody reactivity is useful in biomarker discovery and for explaining the role of important pathophysiologic pathways in disease. In order to study if there are specific antibody biomarkers in the plasma samples of mucinous ovarian cancer patients, we have initiated a screen by employing a 'reverse capture antibody microarray' platform that uses native host antigens derived from mucinous ovarian tissues as 'baits' for the capture of differentially labelled patient and control autoantibodies. Thirty-five autoantibodies that were significantly elevated in the cancer plasma samples compared with healthy controls, and six autoantibodies that segregated smoking and non-smoking patients were identified. Functional annotation of the antibody targets has identified nine target antigens involved in integrin and Wnt signalling pathways. Immunohistochemistry of archived ovarian specimens showed significant overexpression of eight of the nine target antigens in mucinous ovarian tumour tissues, suggesting that plasma autoantibodies from mucinous ovarian cancer patients might have heightened reactivities with epitopes presented by these overexpressed antigens. Autoantibody profiling may have an unexpected utility in uncovering key signalling pathways that are dysregulated in the system of interest.