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.
While most women with ovarian cancer will achieve complete remission after treatment, the majority will relapse within two years, highlighting the need for novel therapies. Cancer stem cells (CSC) have been identified in ovarian cancer and most other carcinomas as a small population of cells that can self-renew. CSC are more chemoresistant and radio-resistant than the bulk tumor cells; it is likely that CSC are responsible for relapse, the major problem in cancer treatment. CD133 has emerged as one of the most promising markers for CSC in ovarian cancer. The hypothesis driving this study is that despite their low numbers in ovarian cancer tumors, CSC can be eradicated using CD133 targeted therapy and tumor growth can be inhibited.
Biorepositories worldwide collect human serum samples and store them for future research. Currently, hundreds of biorepositories across the world store human serum samples in refrigerators, freezers, or liquid nitrogen without following any specific cryopreservation protocol. This method of storage is both expensive and potentially detrimental to the biospecimens. To decrease both cost of storage and the freeze/thaw stresses, we explored the feasibility of storing archival human serum samples at non-cryogenic temperatures using isothermal vitrification. When biospecimens are vitrified, biochemical reactions can be stopped, the specimen ceases to degrade, and macromolecules can be stabilized without requiring cryogenic storage. In this study, 0.2, 0.4, or 0.8M trehalose; 0, 0.005 or 0.01M dextran; and 0 or 10% (v/v) glycerol was added to human serum samples. The samples were either dried diffusively as sessile droplets or desiccated under vacuum after they are adsorbed onto glass microfiber filters. The glass transition temperatures (Tg) of the desiccated samples were measured by temperature-ramp Fourier Transform Infrared (FTIR) spectroscopy. Sera samples vitrified at 4±2°C when 0.8M trehalose and 0.01M dextran were added and the samples were vacuum dried for two hours. Western immunoblotting showed that vitrified serum proteins were minimally degraded when stored for up to one month at 4°C. About 80% of all proteins were recovered after storage at 4°C on glass microfiber filters, and recovery did not decrease with storage time. These results demonstrated the feasibility of long-term storage of vitrified serum at hypothermic (and non-cryogenic) temperatures.
Following initial standard chemotherapy (platinum/taxol), more than 75% of those patients with advanced stage epithelial ovarian cancer (EOC) experience a recurrence. There are currently no accurate prognostic tests that, at the time of the diagnosis/surgery, can identify those patients with advanced stage EOC who will respond to chemotherapy. Using a novel mathematical theory, we have developed three prognostic biomarker models (complex mathematical functions) that-based on a global gene expression analysis of tumor tissue collected during surgery and prior to the commencement of chemotherapy-can identify with a high accuracy those patients with advanced stage EOC who will respond to the standard chemotherapy [long-term survivors (>7 yrs)] and those who will not do so [short-term survivors (<3 yrs)]. Our three prognostic biomarker models were developed with 34 subjects and validated with 20 unknown (new and different) subjects. Both the overall biomarker model sensitivity and specificity ranged from 95.83% to 100.00%. The 12 most significant genes identified, which are also the input variables to the three mathematical functions, constitute three distinct gene networks with the following functions: 1) production of cytoskeletal components, 2) cell proliferation, and 3) cell energy production. The first gene network is directly associated with the mechanism of action of anti-tubulin chemotherapeutic agents, such as taxanes and epothilones. This could have a significant impact in the discovery of new, more effective pharmacological treatments that may significantly extend the survival of patients with advanced stage EOC.
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.
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.
Ovarian cancer is the fifth leading cause of cancer death for women in the US, yet survival rates are over 90% when it is diagnosed at an early stage, highlighting the need for biomarkers for early detection. To enhance the discovery of tumor-specific proteins that could represent novel serum biomarkers for ovarian cancer, we depleted serum of highly abundant proteins which can mask the detection of proteins present in serum at low concentrations. Three commercial immunoaffinity columns were used in parallel to deplete the highly abundant proteins in serum from 60 patients with serous ovarian carcinoma and 60 non-cancer controls. Medium and low abundance serum proteins from each serum pool were then evaluated by the quantitative proteomic technique of differential in-gel electrophoresis. The number of protein spots that were elevated in ovarian cancer sera by at least twofold ranged from 36 to 248, depending upon the depletion and separation methods. From the 33 spots picked for MS analysis, nine different proteins were identified, including the novel candidate ovarian cancer biomarkers leucine-rich alpha2 glycoprotein-1 and ficolin 3. Western blotting validated the relative increases in serum protein levels for three of the proteins identified, demonstrating the utility of this approach for the identification of novel serum biomarkers for ovarian cancer.
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(R).
We sought to investigate the expression levels of S100A1 in ovarian cancer cell lines and tissues to correlate S100A1 with subtype, stage, grade, and relapse-free survival. S100A1 messenger RNA and protein were up-regulated in ovarian cancer cell lines and tumors compared with normal ovarian cell lines and tissues by gene microarray analysis, reverse transcriptase-polymerase chain reaction, quantitative reverse transcriptase-polymerase chain reaction, and Western immunoblotting. In the study, 63.7% of serous, 21.2% of clear cell, 11.2% of endometrioid, and 3% of mucinous ovarian (1/31) cancers were S100A1+ by immunohistochemical staining of tissue microarrays (n = 500). S100A1 expression increased with increasing Silverberg grade but not stage in serous tumors. Endometrial tissue microarrays (n = 127) were 9.4% S100A1+; no correlation with stage or grade and S100A1 was found. In the endometrioid subtype of ovarian and endometrial cancers, relapse-free survival was decreased for patients with S100A1+ tumors. These data suggest that S100A1 is a marker for poor prognosis of endometrioid subtypes of cancer.
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