AUTOANTIBODY PROFILING TO IDENTIFY BIOMARKERS OF KEY PATHOGENIC PATHWAYS IN MUCINOUS OVARIAN CANCER

2.1. Clinical Specimens

The ovarian plasma and tissue samples for this study were selected from the Ob/Gyn Epidemiology Center and tumor bank at the Laboratory of Gynecologic Oncology at Brigham and Women’s Hospital. The plasma samples collected at the Ob/Gyn Epidemiology Center were from a population-based case-control study of ovarian cancer, and a NIH Early Detection Research Network (EDRN) pre-operative/post-operative study. The studies were approved by the Brigham and Women’s Hospital and Dartmouth Medical Center’s Institutional Review Boards. The normal controls were identified and invited through town books in Massachusetts and Drivers’ License lists in New Hampshire and sampled to match the age and residence of the tumor cases. The tumor tissues collected at the Laboratory of Gynecologic Oncology at Brigham and Women’s Hospital used protocols approved by the Institutional Review Boards. The histopathological characteristics of the samples were provided by specialists in gynecologic pathology. Patient’s consent was obtained before the collection of clinical samples.

2.2. Reverse capture antibody array profiling using tumor tissue-derived native antigens

The detailed protocols can be found in published references (28, 29), with minor modifications. Briefly, human IgG was isolated from 20 microliters of each cancer plasma sample using the Melon™ Gel IgG Spin Purification Kit (Pierce Biotechnology, Rockford, IL), according to the manufacturer’s instruction. The control IgG was pooled from 20 age-matched healthy women. 100 micrograms of purified cancer and control IgGs were labeled for 45 minutes with Cy3 and Cy5 mono-Reactive Dye Packs (GE Healthcare Bio-Sciences Corp., Piscataway, NJ), respectively, in Extraction/Labeling Buffer from the Ab Microarray Express Buffer Kit (Clontech Laboratories Inc, Mountain View, CA). Uncoupled Flours were removed by using the Zeba™ Desalt Spin Columns (Pierce Biotechnology, Rockford, IL). For native antigen preparation, 200 mg of frozen tissue were ground with 0.5 g of alumina in a mortar. 1-2 ml of prechilled Extracted/Labeling Buffer was added and the paste was centrifuged to collect the supernatant. Protein concentrations of the extracts were determined using microBCA Protein Assay Reagent Kit (Pierce Biotechnology, Rockford, IL). For each microarray incubation, 200 μg of protein extracts were diluted in 5 ml of Incubation Buffer provided by the Ab Microarray Express Buffer Kit (Clontech Laboratories Inc, Mountain View, CA), and applied to the AB Microarray-500 slide (Clontech Laboratories Inc, Mountain View, CA). After incubation for 45 min at room temperature with gentle rocking, the array slide was washed three times with phosphate-buffered saline (PBS). 100 μg of each labeled cancer plasma IgG were combined with equal amounts of pooled labeled control IgG and added to each slide and allowed to hybridize at room temperature for 45 minutes. The array was then washed with the Wash Buffers provided by the Ab Microarray Express Buffer kit, once with water, spin-dried, and scanned with a ScanArray 4000XL scanner (Perkin Elmer, Waltham, MA) to obtain Cy5 and Cy3 images. To confirm the microarray results for each cancer plasma sample, another microarray incubation was performed by swapping the fluorescent dyes in the labeling of cancer and control IgGs.

2.3. Analysis of the array data and identification of significant autoantibody biomarkers

The Cy5 and Cy3 images of the antibody array experiments of the eleven cancer plasma samples were analyzed by GenePix Pro 6.0 microarray image analysis software (MDS Inc, Toronto, Canada) to produce background-subtracted fluorescence intensity data. Log₂-transformed normalized fluorescence intensity ratios were median-centered and averaged for the dye swapping experiments. Significance Analysis of Microarrays (SAM) method (30) were first used to identify autoantibodies with statistically significant changes in intensity ratios relative to normal, by assimilating a set of t-tests. Each autoantibody is assigned a test score on the basis of its change in intensity relative to the standard deviation of repeated measurements. The biomarkers were ranked according to the calculated false discovery rate, with a false discovery rate of 3.832% as the cut-off point. The array data were also analyzed using a normal mixture approach (31) for the detection of autoantibody biomarkers. Transformed z-scores of one-sample t-statistics were clustered into the null group (corresponding to antibodies that are not different between healthy and cancer samples) and the non-null group (corresponding to antibodies that are different between healthy and cancer samples). The ranking of biomarkers was based on the estimated posterior probability that an individual antibody is null. Those biomarkers that were identified as significant in both methods were then entered into the functional annotation and enrichment analysis. The SAM method with two-class t-statistics was performed on the same dataset to identify autoantibody biomarkers that segregate mucinous ovarian cancer patients with and without a smoking history.

2.4. Functional annotation and enrichment analysis

Functional annotation and enrichment analysis of the biomarkers was performed using web-based DAVID Functional Annotation Tool (http://david.abcc.ncifcrf.gov/summary.jsp). GenBank accession numbers of the high-ranking biomarkers were submitted to the on-line software to search for significant association of the biomarker clusters with relevant Gene Ontolgoy (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.

2.5. Immunohistochemistry to determine the expression levels of pathway-specific tumor antigens

A panel of five normal ovarian, ten borderline and fifteen invasive mucinous ovarian tumor tissues were used for the immunohistochemical staining for pathway-specific tumor antigens. 7-□m sections were cut from the paraffin-archived tissues, mounted on Superfrost Plus microscopic slides (Fisher Scientific, Pittsburgh, PA), and incubated at 50°C for 4 hr. The sections were de-paraffinized in xylene and rehydrated with a descending series of ethanol. For antigen unmasking, sections were immersed in antigen-unmasking solution (Vector Laboratories, Burlingame, CA) and boiled in a microwave oven for 10 min. Endogenous peroxidase activity was quenched using 0.3% H₂O₂ in methanol for 20 min. The sections were then blocked with normal horse serum for 20 min and were subsequently incubated overnight with primary antibodies at 4°C. All primary antibodies were purchased from BD Biosciences (San Jose, CA) and were used in 1:70-100 dilutions. After incubation, VECTASTAIN Elite Avidin-Biotin Complex kit and the substrate diaminobenzidine (DAB) (Vector Laboratories, Burlingame, CA) were used for color development. The sections were counterstained lightly with hematoxylin (Fisher Scientific, Pittsburgh, PA), dehydrated with an ascending series of ethanol, cleared in xylene, and mounted in Permount (Fisher Scientific, Pittsburgh, PA). The staining was quantified with a semiquantitative scoring system. The weighted score was obtained by multiplying the staining intensity score (3+, strong positive stain in cells; 2+, moderate stain in cells; 1+, weak stain in cells; 0, no evidence of stain) and score for the percentage of positive cells (3+, most of cells stained; 2+, half of cells stained; 1+, few cells stained; 0, no cells stained). Two observers scored the slides independently, and the scores for all cases were compared for discrepancies. The data obtained were analyzed by Mann-Whitney test with MINITAB statistical software (Minitab, State College, PA) as the data were not normally distributed. The staining of a tumor sample is considered as significantly different from that of the normal ovaries when P < 0.05.

3.1. Autoantibody profiling of mucinous plasma by reverse capture antibody array platform

We explored the use of an innovative “reverse capture antibody array” method to profile the autoantibodies of eleven cases of mucinous ovarian cancer plasma samples. The clinicopathologic information of the patients is listed in Table S1. The “reverse capture antibody array” method is based on the concept of dual-antibody sandwich ELISA assay (28, 32). This method (Figure S1) uses native protein antigens extracted from a pool of six mucinous tumor tissues and captured by the monoclonal antibodies on a commercial high-density antibody microarray as “baits” to bind fluorescently labeled human immunoglobulins (IgGs) purified from patient and control plasma samples (29). The competitive binding between patient and control antibodies to the antigens is visualized by fluorescence intensities of the two dyes.

The results of a representative array experiment are presented in Figure 1. To control for any labeling artifacts and confirm the differential antibody profiles, a second microarray hybridization was performed by reversing the fluorescent dyes in the labeling of antibodies. Authentic difference in the antibody titer will show reverse color change on the same spots in the two arrays (Figure 1). Analysis of antibody array data using the analysis package “Significance Analysis of Microarrays” (SAM) (30) resulted in the identification of thirty-seven potential autoantibody biomarkers that are significantly elevated in the mucinous cases as compared to normal controls (Figure 2a, and Table S2), and six autoantibody biomarkers that can differentiate smoking and nonsmoking cases (Figure 2b). Furthermore, we also analyzed the data using a normal mixture approach (31) for the detection of autoantibody biomarkers, which is based on the clustering of transformed z-scores of t-statistics into the null group (corresponding to antibodies that are not different between healthy and cancer samples) and the non-null group (corresponding to antibodies that are different between healthy and cancer samples). SAM generated false discovery rate for the identified marker list, whereas the mixture approach provided the estimation of the posterior probability that an individual antibody is null and hence the ranking of antibodies in decreasing order of the posterior probabilities. Tables S2 and S3 present respectively the statistics of SAM, and the top ranking autoantibodies of normal mixture model, respectively, for the autoantibodies that were elevated in the mucinous cases. There are thirty-five such antibody biomarkers that are identified as significant with the use of both SAM and the normal mixture approach (Table 1).

3.2. Annotation analysis of the targets of identified antibody biomarkers

To interrogate the potential functions and the associated pathways of the targets of identified antibody biomarkers in ovarian tumors, we performed a functional annotation and enrichment analysis of the thirty-five autoantibody biomarkers using DAVID Functional Annotation Tool (33). Functional annotation of the antibody targets suggested that mucinous ovarian plasma samples are enriched with antibodies that target nucleoproteins, as in many autoimmune diseases, as well as antibodies that target intracellular cell organization and signaling proteins (Table 2). In particular, search in Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated significant enrichment of six elevated tumor autoantibodies that target antigens involved in integrins-mediated pathway, and three tumor autoantibodies that target antigens in Wnt signaling pathways (Table 3, and Figure S2).

3.3. Elevated expression of the pathway-associated antibody antigens in mucinous ovarian tumors

The finding of autoantibodies in cancer plasmas that target integrins and Wnt signaling pathways may suggest that these two pathways are deregulated in mucinous ovarian cancer. To corroborate this finding, we employed antibodies that are specific to the marker antigens in the immunohistochemical staining of a panel of archived ovarian specimens that include normal ovaries, borderline and invasive mucinous ovarian tumors. The results of immunohistochemistry (Figure 3) showed significant overexpression of all pathway-associated tumor antigens except GIT1 in mucinous ovarian tumors, suggesting that these pathways might be aberrantly activated in mucinous ovarian tumors and the host immune system might have heightened reactivities with epitopes presented by these antigens.