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Potential tumor biomarkers identified in ovarian cyst fluid by quantitative proteomic analysis,iTRAQ
Authors:Bj?rg Kristjansdottir  Kristina Levan  Karolina Partheen  Elisabet Carlsohn  Karin Sundfeldt
Affiliation:1.Institute of Clinical Sciences, Department of Obstetrics and Gynecology, University of Gothenburg, Gothenburg S-413 45, Sweden;2.Proteomics Core Facility at Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden
Abstract:

Background

Epithelial-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.

Results

Using 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.

Conclusions

Fluid 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.
Keywords:Ovarian adenocarcinoma   Ovarian cyst fluid   Tumor biomarker   Mass spectrometry   iTRAQ
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