Background: New biomarkers that replace or are used in conjunction with the current ovarian cancer diagnostic antigen, CA125, are needed for detection of ovarian cancer in the presurgical setting, as well as for detection of disease recurrence. We previously demonstrated the upregulation of leucine-rich alpha-2-glycoprotein-1 (LRG1) in the sera of ovarian cancer patients compared to healthy women using quantitative mass spectrometry.Methods: LRG1 was quantified by ELISA in serum from two relatively large cohorts of women with ovarian cancer and benign gynecological disease. The expression of LRG1 in ovarian cancer tissues and cell lines was examined by gene microarray, reverse-transcriptase polymerase chain reaction (RT-PCR), Western blot, immunocytochemistry and mass spectrometry.Results: Mean serum LRG1 was higher in 58 ovarian cancer patients than in 56 healthy women (89.33 ± 77.90 vs. 42.99 ± 9.88 ug/ml; p = 0.0008) and was highest among stage III/IV patients. In a separate set of 193 pre-surgical samples, LRG1 was higher in patients with serous or clear cell ovarian cancer (145.82 ± 65.99 ug/ml) compared to patients with benign gynecological diseases (82.53 ± 76.67 ug/ml, p < 0.0001). CA125 and LRG1 levels were moderately correlated (r = 0.47, p < 0.0001).LRG1mRNA levels were higher in ovarian cancer tissues and cell lines compared to their normal counterparts when analyzed by gene microarray and RT-PCR. LRG1 protein was detected in ovarian cancer tissue samples and cell lines by immunocytochemistry and Western blotting. Multiple iosforms of LRG1 were observed by Western blot and were shown to represent different glycosylation states by digestion with glycosidase. LRG1 protein was also detected in the conditioned media of ovarian cancer cell culture by ELISA, Western blotting, and mass spectrometry.Conclusions: Serum LRG1 was significantly elevated in women with ovarian cancer compared to healthy women and women with benign gynecological disease, and was only moderately correlated with CA125. Ovarian cancer cells secrete LRG1 and may contribute directly to the elevated levels of LRG1 observed in the serum of ovarian cancer patients. Future studies will determine whether LRG1 may serve as a biomarker for presurgical diagnosis, disease recurrence, and/or as a target for therapy.

Background: Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ^®.Results: Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ^®to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified.Conclusions: This study provides the first analysis of immunodepleted serum in combination with iTRAQ^®to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients. We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients. Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population. These data demonstrate that the Proseek® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

Claudin 4 is a cellular adhesion molecule that is frequently overexpressed in ovarian cancer and other epithelial cancers. In this study, we sought to determine whether the expression of claudin 4 is associated with outcome in ovarian cancer patients and may be involved in tumor progression. We examined claudin 4 expression in ovarian cancer tissues and cell lines, as well as by immunohistochemical staining of tissue microarrays (TMAs; n = 500), spheroids present in patients’ ascites, and spheroids formed in vitro. Claudin 4 was expressed in nearly 70% of the ovarian cancer tissues examined and was differentially expressed across ovarian cancer subtypes, with the lowest expression in clear cell subtype. No association was found between claudin 4 expression and disease-specific survival in any subtype. Claudin 4 expression was also observed in multicellular spheroids obtained from patients’ ascites. Using an in vitro spheroid formation assay, we found that NIH:OVCAR5 cells treated with shRNA against claudin 4 required a longer time to form compact spheroids compared to control NIH:OVCAR5 cells that expressed high levels of claudin 4. The inability of the NIH:OVCAR5 cells treated with claudin 4 shRNA to form compact spheroids was verified by FITC-dextran exclusion. These results demonstrate a role for claudin 4 and tight junctions in spheroid formation and integrity.

The formation of 3D multicellular spheroids in the ascites fluid of ovarian cancer patients is an understudied component of the disease progression. Spheroids are less sensitive to chemotherapy, in part due to the protection afforded by their structure, but also due to their slower proliferation rate. Previous studies suggest that the cell adhesion molecule Nectin-4 plays a key role in the formation of ovarian cancer spheroids. In this study, we further examined the role of Nectin-4 at early time points in spheroid formation using real-time digital photography. Human NIH:OVCAR5 ovarian cancer cells formed aggregates within 8 h, which further contracted into compact spheroids over 24 h. In contrast, Nectin-4 knockdown cells did not form tightly compacted spheroids. Synthetic peptides derived from Nectin-4 were tested for their ability to alter spheroid formation in two ovarian cancer cell lines. Nectin-4 peptide 10 (N4-P10) had an immediate effect on disrupting ovarian cancer spheroid formation, which continued for over 24 h, while a scrambled version of the peptide had no effect. N4-P10 inhibited spheroid formation in a concentration-dependent manner and was not cytotoxic; suggesting that N4-P10 treatment could maintain the cancer cells as single cells which may be more sensitive to chemotherapy.

The proteomic analysis of body fluids is a growing technology for the identification of protein biomarkers of disease. Given that Papanicolaou tests (Pap tests) are routinely performed on over 30 million women annually in the U.S. to screen for cervical cancer, we examined the residual Pap test fluid as a source of protein for analysis by mass spectrometry (MS). In the liquid-based Pap test, cervical cells are collected from the ectocervix and placed into an alcohol-based fixative prior to staining and pathologic examination. We hypothesized that proteins shed by cells of the female genital tract can be detected in the Pap test fixative by MS-based proteomic techniques. We examined the feasibility of using residual fluid from discarded Pap tests with cytologically “normal” results to optimize sample preparation for MS analysis. The protein composition of the cell-free Pap test fluid was determined by silver staining of sodium dodecyl sulfate -polyacrylamide gels, and the abundance of serum proteins was examined by Western immunoblot using an antibody against human serum albumin. Both pooled and individual samples were trypsin digested and analyzed by two-dimensional MS/MS. Proteins were identified by searching against the Human Uniprot database, and characterized for localization, function and relative abundance.