Proteomic biomarkers of endometrial cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration

Gynecol Endocrinol. 2013 Jul;29(7):638-44. doi: 10.3109/09513590.2013.777416. Epub 2013 Mar 25.

Abstract

There is a need for research studies into the molecular mechanisms underpinning the link between polycystic ovary syndrome (PCOS) and endometrial cancer (EC) to facilitate screening and to encourage the development of novel strategies to prevent disease progression. The objective of this review was to identify proteomic biomarkers of EC risk in women with PCOS. All eligible published studies on proteomic biomarkers for EC identified through the literature were evaluated. Proteomic biomarkers for EC were then integrated with an updated previously published database of all proteomic biomarkers identified so far in PCOS women. Nine protein biomarkers were similarly either under or over expressed in women with EC and PCOS in various tissues. These include transgelin, pyruvate kinase M1/M2, gelsolin-like capping protein (macrophage capping protein), glutathione S-transferase P, leucine aminopeptidase (cytosol aminopeptidase), peptidyl-prolyl cis-transisomerase, cyclophilin A, complement component C4A and manganese-superoxide dismutase. If validated, these biomarkers may provide a useful framework on which the knowledge base in this area could be developed and will facilitate future mathematical modelling to enhance screening and prevention of EC in women with PCOS who have been shown to be at increased risk.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Biomarkers, Tumor / metabolism*
  • Carcinoma, Endometrioid / epidemiology*
  • Carcinoma, Endometrioid / metabolism
  • Databases, Protein / statistics & numerical data
  • Endometrial Neoplasms / epidemiology*
  • Endometrial Neoplasms / metabolism
  • Female
  • Humans
  • Polycystic Ovary Syndrome / epidemiology*
  • Polycystic Ovary Syndrome / metabolism
  • Proteome / analysis
  • Proteome / metabolism
  • Proteomics / methods
  • Proteomics / statistics & numerical data
  • Risk Factors

Substances

  • Biomarkers, Tumor
  • Proteome