beta-catenin expression, DNA ploidy and clinicopathological features in ovarian cancer: a study in 253 patients

Wanja Kildal1, Björn Risberg, Vera M Abeler

  • 1Department of Medical Informatics, The Norwegian Radium Hospital, 0310 Oslo, Norway. wanjak@labmed.uio.no

European Journal of Cancer (Oxford, England : 1990)
|May 25, 2005
PubMed

Insights

Beta-catenin expression in ovarian cancer shows no link to genomic instability but is associated with specific tumor types and may offer prognostic value. Nuclear beta-catenin is linked to better outcomes in univariate analysis.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • The CTNNB1 gene and its protein beta-catenin regulate the Wnt signaling pathway, crucial in human malignancies.
  • Deregulation of beta-catenin is implicated in genomic instability, a hallmark of cancer.

Purpose of the Study:

  • To investigate the impact of beta-catenin expression on genomic instability in ovarian carcinoma.
  • To correlate beta-catenin localization (membrane, cytoplasmic, nuclear) with clinicopathological features and patient outcomes.

Main Methods:

  • Immunohistochemistry was used to examine beta-catenin expression in 253 ovarian carcinomas.
  • Results were analyzed in relation to DNA ploidy for genomic instability and clinical parameters.

Main Results:

  • Nuclear beta-catenin expression was significantly associated with endometroid histology (53% positivity, P<0.0001).
  • Cytoplasmic beta-catenin was prevalent (84%), with highest expression in mucinous and endometroid subtypes (92%).
  • Nuclear beta-catenin was linked to better prognostic outcomes in univariate analysis (P=0.027).

Conclusions:

  • Beta-catenin expression did not correlate with FIGO stage or genomic instability (DNA ploidy) in ovarian cancer.
  • Nuclear beta-catenin is strongly associated with endometroid histological subtype.
  • While univariate analysis suggests prognostic importance for nuclear beta-catenin, only DNA ploidy, grade, and FIGO stage were independent prognostic factors in multivariate analysis.