Predicting biomarkers for ovarian cancer using gene-expression microarrays

Br J Cancer. 2004 Feb 9;90(3):686-92. doi: 10.1038/sj.bjc.6601603.

Abstract

Ovarian cancer has the highest mortality rate of gynaecological cancers. This is partly due to the lack of effective screening markers. Here, we used oligonucleotide microarrays complementary to approximately 12 000 genes to establish a gene-expression microarray (GEM) profile for normal ovarian tissue, as compared to stage III ovarian serous adenocarcinoma and omental metastases from the same individuals. We found that the GEM profiles of the primary and secondary tumours from the same individuals were essentially alike, reflecting the fact that these tumours had already metastasised and acquired the metastatic phenotype. We have identified a novel biomarker, mammaglobin-2 (MGB2), which is highly expressed specific to ovarian cancer. MGB2, in combination with other putative markers identified here, could have the potential for screening.

MeSH terms

  • Biomarkers, Tumor / analysis*
  • Female
  • Forecasting
  • Gene Expression Regulation*
  • Humans
  • Immunohistochemistry
  • Mammaglobin B
  • Mass Screening
  • Myelin Proteins
  • Neoplasm Proteins
  • Oligonucleotide Array Sequence Analysis*
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / physiopathology*
  • Phenotype
  • Proteolipids
  • Reverse Transcriptase Polymerase Chain Reaction
  • Secretoglobins
  • Uteroglobin / analysis
  • Uteroglobin / biosynthesis*
  • Uteroglobin / genetics

Substances

  • Biomarkers, Tumor
  • Mammaglobin B
  • Myelin Proteins
  • Neoplasm Proteins
  • Proteolipids
  • SCGB2A1 protein, human
  • Secretoglobins
  • Uteroglobin