title: Proteomic biomarkers for ovarian cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration.
abstract: OBJECTIVE
  To review and identify possible biomarkers for ovarian cancer (OC) in women with polycystic ovary syndrome (PCOS).
  
  
  METHODS
  Systematic literature searches of MEDLINE, EMBASE, and Cochrane using the search terms "proteomics," "proteomic," and "ovarian cancer" or "ovarian carcinoma." Proteomic biomarkers for OC were then integrated with an updated previously published database of all proteomic biomarkers identified to date in patients with PCOS.
  
  
  METHODS
  Academic department of obstetrics and gynecology in the United Kingdom.
  
  
  METHODS
  A total of 180 women identified in the six studies.
  
  
  METHODS
  Tissue samples from women with OC vs. tissue samples from women without OC.
  
  
  METHODS
  Proteomic biomarkers, proteomic technique used, and methodologic quality score.
  
  
  RESULTS
  A panel of six biomarkers was overexpressed both in women with OC and in women with PCOS. These biomarkers include calreticulin, fibrinogen-γ, superoxide dismutase, vimentin, malate dehydrogenase, and lamin B2.
  
  
  CONCLUSIONS
  These biomarkers could help improve our understanding of the links between PCOS and OC and could potentially be used to identify subgroups of women with PCOS at increased risk of OC. More studies are required to further evaluate the role these biomarkers play in women with PCOS and OC.
authors.affiliation: Division of Human Development, School of Clinical Sciences, University of Nottingham, Queen's Medical Centre Campus, Nottingham University Hospitals, Nottingham, United Kingdom. ngalazis@gmail.com
authors.forename: Nicolas
authors.initials: N
authors.lastname: Galazis
authors.forename: Olalekan
authors.initials: O
authors.lastname: Olaleye
authors.forename: Zeina
authors.initials: Z
authors.lastname: Haoula
authors.forename: Robert
authors.initials: R
authors.lastname: Layfield
authors.forename: William
authors.initials: W
authors.lastname: Atiomo
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis*; D015897:Comorbidity; D030562:Databases, Protein; D005260:Female; D006801:Humans; D016247:Information Storage and Retrieval; D009363:Neoplasm Proteins / Q000032:analysis; D010051:Ovarian Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000378:metabolism*; D010053:Ovary / Q000378:metabolism*; D011085:Polycystic Ovary Syndrome / Q000175:diagnosis / Q000453:epidemiology* / Q000378:metabolism*; D015995:Prevalence; D020543:Proteome / Q000032:analysis*; D015203:Reproducibility of Results; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D018511:Systems Integration
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins; D020543:Proteome