4.8 Article

Quantitative in situ analysis of β-catenin expression in breast cancer shows decreased expression is associated with poor outcome

Journal

CANCER RESEARCH
Volume 66, Issue 10, Pages 5487-5494

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/0008-5472.CAN-06-0100

Keywords

-

Categories

Funding

  1. NCI NIH HHS [R21 CA100825] Funding Source: Medline
  2. NIEHS NIH HHS [K08 ES11571] Funding Source: Medline

Ask authors/readers for more resources

The role of beta-catenin in breast cancer and its prognostic value is controversial. The prognostic value had been assessed previously in a series of nonquantitative immunohistochemical studies with conflicting results. In efforts to clarify the relationship between beta-catenin protein expression and breast cancer prognosis, we have assessed a retrospective 600 case cohort of breast cancer tumors from the Yale Pathology archives on tissue microarrays. They were assessed using automated quantitative analysis (AQUA) with a series of array-embedded cell lines for which the beta-catenin concentration was standardized by an ELISA assay. The expression levels of the standard clinical markers HER2, estrogen receptor (ER), progesterone receptor (PR), and Ki-67 were also assessed on the same cohort. X-tile software was used to select optimal protein concentration cutpoints and to evaluate the outcome using a training set and a validation set. We found that low-level expression of membranous beta-catenin is associated with significantly worse outcome (38% versus 76%, 10-year survival, validation set log-rank P = 0.0016). Multivariate analysis of this marker, assessed in a proportional hazards model with tumor size, age, node status, nuclear grade, ER, PR, HER2, and Ki-67, is still highly significant with a hazard ratio of 6.8 (P < 0.0001, 95% confidence interval, 3.1-15.1). These results suggest that loss of beta-catenin expression at the membrane, as assessed by objective quantitative analysis methods, may be useful as a prognostic marker or may be part of a useful algorithm for prognosis in breast cancer.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available