Differential gene expression analysis of ovarian cancer in a population isolate

Eur J Gynaecol Oncol. 2008;29(4):357-63.


Gene expression products represent candidate biomarkers with the potential for early screening and therapy of patients with ovarian serous carcinoma. The present study, using patients that originate from the population isolate of South Tyrol, Italy, substantiates the feasibility of differential gene expression analysis in a genetically isolated population for the identification of potential markers of ovarian cancer. Gene expression profiles of fresh-frozen ovarian serous papillary carcinoma samples were analyzed and compared to normal ovarian control tissues using oligonucleotide microarrays complementary to 14,500 human genes. Supervised analysis of gene expression profiling data identified 225 genes that are down-regulated and 635 that are up-regulated in malignant compared to normal ovarian tissues. Class-prediction analysis identified 40 differentially expressed genes for further investigation as potential classifiers for ovarian cancer, including 20 novel candidates. Our findings provide a glimpse into the potential of population isolate genomics in oncological research.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Case-Control Studies
  • Cystadenocarcinoma, Serous / genetics*
  • Cystadenocarcinoma, Serous / metabolism
  • Cystadenocarcinoma, Serous / pathology
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Italy
  • Neoplasms, Glandular and Epithelial / genetics*
  • Neoplasms, Glandular and Epithelial / metabolism
  • Neoplasms, Glandular and Epithelial / pathology
  • Oligonucleotide Array Sequence Analysis
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / metabolism
  • Ovarian Neoplasms / pathology
  • Ovary / metabolism*
  • Ovary / pathology
  • Population Groups / genetics*
  • RNA, Neoplasm / genetics
  • RNA, Neoplasm / metabolism


  • Biomarkers, Tumor
  • RNA, Neoplasm