Discovery of microarray-identified genes associated with ovarian cancer progression

Int J Oncol. 2015;46(6):2467-78. doi: 10.3892/ijo.2015.2971. Epub 2015 Apr 20.

Abstract

Ovarian cancer is the most lethal cancer of female reproductive system. There is a consistent and urgent need to better understand its mechanism. In this study, we retrieved 186 genes that were dysregulated by at least 4-fold in 594 ovarian serous cystadenocarcinomas in comparison with eight normal ovaries, according to The Cancer Genome Atlas Ovarian Statistics data deposited in Oncomine database. DAVID analysis of these genes enriched two biological processes indicating that the cell cycle and microtubules might play critical roles in ovarian cancer progression. Among these 186 genes, 46 were dysregulated by at least 10-fold and their expression was further confirmed by the Bonome Ovarian Statistics data deposited in Oncomine, which covered 185 cases of ovarian carcinomas and 10 cases of normal ovarian surface epithelium. Six genes, including aldehyde dehydrogenase 1 family, member A2 (ALDH1A2), alcohol dehydrogenase 1B (class I), β polypeptide (ADH1B), NEL-like 2 (chicken) (NELL2), hemoglobin, β (HBB), ATP-binding cassette, sub-family A (ABC1), member 8 (ABCA8) and hemoglobin, α1 (HBA1) were identified to be downregulated by at least 10-fold in 779 ovarian cancers compared with 18 normal controls. Using mRNA expression profiles retrieved from microarrays deposited in the Gene Expression Omnibus Profiles database, RT-qPCR measurement and bioinformatics analysis, we further indicated that high expression of HBB might predict a poorer 5-year survival, high expression of ALDH1A2 and ABCA8 might predict a poor outcome; while ALDH1A2, ADH1B, HBB and ABCA8, in particular the former two genes, might be associated with drug resistance, and ALDH1A2 and NELL2 might contribute to invasiveness and metastasis in ovarian cancer. This study thus contributes to our understanding of the mechanism of ovarian cancer progression and development, and the six identified genes may be potential therapeutic targets and biomarkers for diagnosis and prognosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Line, Tumor
  • Computational Biology / methods
  • Disease Progression
  • Female
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Oligonucleotide Array Sequence Analysis / methods*
  • Ovarian Neoplasms / genetics
  • Ovarian Neoplasms / pathology*