ObjectiveWomen presenting with a large or complex ovarian cyst are referred to extensive surgical staging to ensure the correct diagnosis and treatment of a possible epithelial ovarian cancer. We hypothesized that measurement of the biomarkers HE4 and CA-125 preoperatively would improve the assignment of these patients to the correct level of care.MethodsPatients diagnosed with a cystic ovarian mass and scheduled for an operation at our center of excellence for ovarian cancer surgery from 2001 to 2010 were prospectively included (n=394) and plasma was collected consecutively. Cut-off for HE4 was calculated at 75% specificity (85 pM and 71.8 pM for post and premenopausal women). For CA-125, 35 U/mL cut-off was used. The study population included women with malignant (n=114), borderline (n=45), and benign (n=215) ovarian tumors.ResultsReceiver operator characteristic (ROC) area under the curve (AUC) in the benign versus malignant cohorts was 86.8% for CA-125 and 84.4% for HE4. Negative predictive value was 91.7% when at least one of the biomarkers was positive, with only early stage epithelial ovarian cancer showing false negative results. Sensitivity at set specificity (75%) was 87% for risk of ovarian malignancy algorithm (ROMA) in the postmenopausal cohort (cut-off point, 26.0%) and 81% in the premenopausal cohort (cut-off point, 17.3%). ROC AUC in the benign versus stage I epithelial ovarian cancer was only 72% for HE4 and 76% for CA-125.ConclusionIn our study, population HE4 did not outperform CA-125. Based on our data a prospective trial with patients already diagnosed with an ovarian cyst may be conducted.

The mortality rate for patients with ovarian carcinomas is high and the available prognostic factors are insufficient. The use of biomarkers may contribute to better prediction and survival for these patients. We aimed to study the gene and protein expressions for 7 potential biomarkers, to determine if it is possible to use them as prognostic factors. Genes selected from our previous microarray analysis (2006), CLU, ITGB3, TACC1, MUC5B, CAPG, PRAME and TROAP, were analyzed in 19 of the tumors with quantitative real-time polymerase chain reaction (QPCR). We found that CLU and ITGB3 were more expressed in tumors from survivors and PRAME and CAPG were more expressed in tumors from deceased patients. None of the other 3 genes were significantly differently expressed. The protein expressions of CLU, ITGB3, PRAME and CAPG were analyzed in 43 of the tumors with western blot for semiquantitative analysis. We established that the mRNA and protein expressions correlated and that all 4 proteins were significantly differently expressed. Further, immunohistochemistry (IHC) was used to localize the expression of the proteins in the tumor samples. According to our results, the 4 biomarkers CLU, ITGB3, PRAME and CAPG may be used as prognostic factors for patients with stage III serous ovarian adenocarcinomas.

HE4 and CA125 have a good ability to diagnose the more aggressive type II tumors but a poor diagnostic ability when patients are presenting with slow-growing type I in the early stage. Our results support the hypothesis that EOC should be looked upon as several different diseases, and that we lack biomarkers for sub-groups of EOC.

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BackgroundEpithelial-derived ovarian adenocarcinoma (EOC) is the most deadly gynecologic tumor, and the principle cause of the poor survival rate is diagnosis at a late stage. Screening and diagnostic biomarkers with acceptable specificity and sensitivity are lacking. Ovarian cyst fluid should harbor early ovarian cancer biomarkers because of its closeness to the tumor. We investigated ovarian cyst fluid as a source for discovering biomarkers for use in the diagnosis of EOC.ResultsUsing quantitative mass spectrometry, iTRAQ MS, we identified 837 proteins in cyst fluid from benign, EOC stage I, and EOC stage III. Only patients of serous histology were included in the study. Comparing the benign (n = 5) with the malignant (n = 10) group, 87 of the proteins were significantly (p < 0.05) differentially expressed. Two proteins, serum amyloid A-4 (SAA4) and astacin-like metalloendopeptidase (ASTL), were selected for verification of the iTRAQ method and external validation with immunoblot in a larger cohort with mixed histology, in plasma (n = 68), and cyst fluid (n = 68). The protein selections were based on either high significance and high fold change or abundant appearance and several peptide recognitions in the sample sets (p = 0.04, FC = 1.95) and (p < 0.001, FC = 8.48) for SAA4 and ASTL respectively. Both were found to be significantly expressed (p < 0.05), but the methods did not correlate concerning ASTL.ConclusionsFluid from ovarian cysts connected directly to the primary tumor harbor many possible new tumor-specific biomarkers. We have identified 87 differentially expressed proteins and validated two candidates to verify the iTRAQ method. However several of the proteins are of interest for validation in a larger setting.

Ovarian cancer is the leading cause of death among patients with gynecological cancers, but the biology of these tumors is still among the least understood of all major human malignancies. In this study, comparative genomic hybridization was used to determine chromosomal alterations in 98 stage III serous papillary adenocarcinomas. The tumors were grouped according to survival and the main prognostic factors stage and surgical outcome. There were chromosomal imbalances that were significantly more common in tumors from patients who died than in tumors from patients who survived: gains of 1q24-qter and losses of 4p, 4q31.1-qter, 5q12-q22, 8p, 16q, and X. Furthermore, we observed that gains of 8q23-8q24.2 and losses of 4p, 4q13-4q26, 4q31.1-qter, 5q12-q22, 8p, and 16q were significantly more common in tumors from patients with macroscopic residual tumor after primary surgery, compared to tumors from those who had undergone radical surgery. Gains of 3q13.3-qter, 6p, 7q21-q31, and 11q13-q23 and losses of 4q31.1-qter and 16q were more common in stage IIIc tumors than in stage IIIa+b tumors. On the basis of our results, we suggest that there are biological differences among the groups mentioned above and that absence of chromosomal aberrations in specific regions predicts a good clinical outcome for individual patients.

BackgroundChemotherapy resistance remains a major obstacle in the treatment of women with ovarian cancer. Establishing predictive markers of chemoresponse would help to individualize therapy and improve survival of ovarian cancer patients. Chemotherapy resistance in ovarian cancer has been studied thoroughly and several non-overlapping single genes, gene profiles and copy number alterations have been suggested as potential markers. The objective of this study was to explore genetic alterations behind chemotherapy resistance in ovarian cancer with the ultimate aim to find potential predictive markers.MethodsTo create the best opportunities for identifying genetic alterations of importance for resistance, we selected a homogenous tumor material concerning histology, stage and chemotherapy. Using high-resolution whole genome array comparative genomic hybridization (CGH), we analyzed the tumor genomes of 40 fresh-frozen stage III ovarian serous carcinomas, all uniformly treated with combination therapy paclitaxel/carboplatin. Fisher's exact test was used to identify significant differences. Subsequently, we examined four genes in the significant regions (EVI1, MDS1, SH3GL2, SH3KBP1) plus the ABCB1 gene with quantitative real-time polymerase chain reaction (QPCR) to evaluate the impact of DNA alterations on the transcriptional level.ResultsWe identified gain in 3q26.2, and losses in 6q11.2-12, 9p22.3, 9p22.2-22.1, 9p22.1-21.3, Xp22.2-22.12, Xp22.11-11.3, and Xp11.23-11.1 to be significantly associated with chemotherapy resistance. In the gene expression analysis, EVI1 expression differed between samples with gain versus without gain, exhibiting higher expression in the gain group.ConclusionIn conclusion, we detected specific genetic alterations associated with resistance, of which some might be potential predictive markers of chemotherapy resistance in advanced ovarian serous carcinomas. Thus, further studies are required to validate these findings in an independent ovarian tumor series.

BackgroundWe aimed to investigate the use of ovarian cyst fluid as a source for biomarker discovery and to find novel biomarkers for use in the diagnosis of epithelial ovarian tumors.ResultsOvarian cyst fluids from 218 women were collected and 192 (benign n = 129, malignant n = 63) were analyzed using mass spectrometry. 1180 peaks were detected, 221 of which were differently expressed between benign and malignant ovarian tumors. Seventeen peaks had receiver operating curve and area under the curve values >0.70; the majority of these represented peaks for apolipoproteins C-III and C-I (ApoC-I), transthyretin (TTR), serum amyloid A4 (SAA4), and protein C inhibitor (PCI). ApoC-III, PCI, and serum CA125, with an ROC AUC 0.94 was the best combination for diagnosing epithelial ovarian cancer. ApoC-III and PCI was analyzed with ELISA in the original cohort (n = 40) and in 40 new cyst fluid samples for confirmation with an independent method and validation. Results from MS and ELISA for ApoC-III correlated well (p = 0.04). In the validation set, ApoC-III was significantly (p = 0.001) increased in the malignant epithelial ovarian cancers.ConclusionsFluid from ovarian cysts connected directly to the primary tumor harbor many possible new tumor-specific biomarkers. Biomarkers found in ovarian cyst fluid may be used as molecular imaging targets for early diagnostics and prediction of therapy. Plasma abundant proteins are also influencing the cystic fluid proteome. Methods for isolating less frequent cyst fluid proteins are needed.