title: Evaluation of glycomic profiling as a diagnostic biomarker for epithelial ovarian cancer.
abstract: BACKGROUND
  Prior studies suggested that glycans were differentially expressed in patients with ovarian cancer and controls. We hypothesized that glycan-based biomarkers might serve as a diagnostic test for ovarian cancer and evaluated the ability of glycans to distinguish ovarian cancer cases from matched controls.
  
  
  METHODS
  Serum samples were obtained from the tissue-banking repository of the Gynecologic Oncology Group, and included healthy female controls (n = 100), women diagnosed with low malignant potential (LMP) tumors (n = 52), and epithelial ovarian cancers (EOC) cases (n = 147). Cases and controls were matched on age at enrollment within ±5 years. Serum samples were analyzed by glycomics analysis to detect abundance differences in glycan expression levels. A two-stage procedure was carried out for biomarker discovery and validation. Candidate classifiers of glycans that separated cases from controls were developed using a training set in the discovery phase and the classification performance of the candidate classifiers was assessed using independent test samples that were not used in discovery.
  
  
  RESULTS
  The patterns of glycans showed discriminatory power for distinguishing EOC and LMP cases from controls. Candidate glycan-based biomarkers developed on a training set (sensitivity, 86% and specificity, 95.8% for distinguishing EOC from controls through leave-one-out cross-validation) confirmed their potential use as a detection test using an independent test set (sensitivity, 70% and specificity, 86.5%).
  
  
  CONCLUSIONS
  Formal investigations of glycan biomarkers that distinguish cases and controls show great promise for an ovarian cancer diagnostic test. Further validation of a glycan-based test for detection of ovarian cancer is warranted.
  
  
  CONCLUSIONS
  An emerging diagnostic test based on the knowledge gained from understanding the glycobiology should lead to an assay that improves sensitivity and specificity and allows for early detection of ovarian cancer.
authors.affiliation: Authors' Affiliations: Division of Biostatistics, Department of Public Health Sciences; Department of Chemistry, University of California, Davis; UC Davis Cancer Center; and Division of Gynecologic Oncology, UC Davis Medical Center, Sacramento, California.
authors.forename: Kyoungmi
authors.initials: K
authors.lastname: Kim
authors.forename: L Renee
authors.initials: LR
authors.lastname: Ruhaak
authors.forename: Uyen Thao
authors.initials: UT
authors.lastname: Nguyen
authors.forename: Sandra L
authors.initials: SL
authors.lastname: Taylor
authors.forename: Lauren
authors.initials: L
authors.lastname: Dimapasoc
authors.forename: Cynthia
authors.initials: C
authors.lastname: Williams
authors.forename: Carol
authors.initials: C
authors.lastname: Stroble
authors.forename: Sureyya
authors.initials: S
authors.lastname: Ozcan
authors.forename: Suzanne
authors.initials: S
authors.lastname: Miyamoto
authors.forename: Carlito B
authors.initials: CB
authors.lastname: Lebrilla
authors.forename: Gary S
authors.initials: GS
authors.lastname: Leiserowitz
mesh_terms: D014408:Biomarkers, Tumor / Q000097:blood*; D000077216:Carcinoma, Ovarian Epithelial; D016022:Case-Control Studies; D015331:Cohort Studies; D005260:Female; D054794:Glycomics / Q000379:methods; D006801:Humans; D008875:Middle Aged; D009375:Neoplasms, Glandular and Epithelial / Q000097:blood* / Q000175:diagnosis*; D010051:Ovarian Neoplasms / Q000097:blood* / Q000175:diagnosis*
chemical_list: D014408:Biomarkers, Tumor