Surprising features of the energy-mismatched nonlinear dimer.

The quantum mechanical energy-mismatched two-state system with cubic nonlinearity in its governing equation is surprisingly rich in its dynamics and has relevance to a number of subdisciplines of physics ranging from polaron phenomena to Bose-Einstein condensation. We review some of them that have been discussed recently and describe some new results that have not, pointing out their relevance in possible experiments.

A Cell Line-based Immunohistochemical p53 Expression Pattern Control Panel.

TP53 gene mutations are known to manifest in distinct p53 immunohistochemical staining patterns; overexpression, wild-type, and null. These stratified staining patterns are routinely utilized in subtyping ovarian cancer subtypes. Three ovarian cancer cell lines were used in the construction of an immunohistochemical p53 expression pattern control panel that highlight respective TP53 mutation status. The cell line control panel sections demonstrated consistent clean and easily interpretable p53 immunohistochemical staining. Procured resection, biopsy, and cytologic specimens were submitted along with either standard control tissue or a p53 cell line control panel to pathologists of varying experience for interrater reliability analysis. Individual interrater reliability was near-perfect and was improved with the p53 cell line control panel when compared with the tissue control. The cell line control panel demonstrated decreased misinterpretation of null expression pattern as wild-type. Next-generation sequencing analysis was performed on the cell lines and select cases, in which there was discordance in p53 expression pattern interpretation. Next-generation sequencing analysis demonstrated low-frequency variant mutations in some cases in which there was reviewer discordance. This study suggests the addition of a p53 cell line expression pattern control panel could potentially increase p53 interpretation accuracy for ovarian cancer subtypes. We developed a cell line-based p53 control panel that has the potential to increase individual interrater reliability for p53 immunohistochemical expression pattern determination, support immunohistochemical optimization, and direct submission of difficult to interpret p53 staining cases to next-generation sequencing.

Claudin 4 Is differentially expressed between ovarian cancer subtypes and plays a role in spheroid formation.

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.

Identification of candidate biomarkers in ovarian cancer serum by depletion of highly abundant proteins and differential in-gel electrophoresis.

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.

Quantitative proteomic analysis by iTRAQ(R) for the identification of candidate biomarkers in ovarian cancer serum.

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(R). 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(R) 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(R) to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

ELISA for human serum leucine-rich alpha-2-glycoprotein-1 employing cytochrome c as the capturing ligand.

Leucine-rich alpha-2-glycoprotein-1 (LRG) is a serum glycoprotein of unknown function that has shown promise based on qualitative assessments as a biomarker for certain diseases including microbial infections and cancer. However, the lack of a quantitative assay for LRG has limited its application. Here an indirect enzyme-linked immunosorbent assay (ELISA) for quantifying LRG in human serum is described in which cytochrome c is employed as the capturing ligand and a monoclonal antibody specific for LRG is used to detect the captured glycoprotein. Application of this assay in quantifying LRG in various patients' sera is demonstrated. The concentration of LRG in sera of control subjects as determined by this assay is approximately 50 microg/ml. Consistent with expectations from published reports, LRG was found to be significantly elevated in the sera of some patients with a bacterial infection (toxic shock syndrome, TSS). LRG was only slightly elevated in patients infected with the human immunodeficiency virus as compared to uninfected control subjects, while normal levels of LRG were observed in patients with non-infectious diseases (inflammatory arthritis and neurological disorders, primarily Parkinson's disease). Although LRG and C-reactive protein (CRP) are both produced by the liver and are classified as acute-phase proteins, there was no significant correlation between the levels of LRG and CRP in the sera of the patients. Thus, LRG and CRP measurements are non-redundant and indicate different physiological contexts. The ELISA described in this report should be useful to further assess serum LRG as a biomarker for clinical diagnostics.

Leucine-rich alpha-2-glycoprotein-1 is upregulated in sera and tumors of ovarian cancer patients.

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). LRG1 mRNA 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.

S100A1 expression in ovarian and endometrial endometrioid carcinomas is a prognostic indicator of relapse-free survival.

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.