Automated quantitative analysis of DCC tumor suppressor protein in ovarian cancer tissue microarray shows association with β-catenin levels and outcome in patients with epithelial ovarian cancer

Citation:

Bamias A, Yu Z, Weinberger PM, Markakis S, Kowalski D, Camp RL, Rimm DL, Dimopoulos MA, Psyrri A. Automated quantitative analysis of DCC tumor suppressor protein in ovarian cancer tissue microarray shows association with β-catenin levels and outcome in patients with epithelial ovarian cancer. Annals of Oncology [Internet]. 2006;17(12):1797 - 1802.

Abstract:

Background: The deleted in colorectal cancer (DCC) protein, the product of DCC tumor suppressor gene, is frequently altered in cancer. Preclinical data demonstrate that DCC regulates β-catenin levels. Here, we sought to determine the association of DCC with β-catenin protein levels, clinicopathological parameters and patient outcome in ovarian cancer using a method of in situ compartmentalized protein analysis. Methods: A tissue array composed of 150 advanced-stage ovarian cancers, treated with surgical debulking and platinum-paclitaxel (Taxol) combination chemotherapy, was constructed. For evaluation of protein expression, we used an immunofluorescence-based method of automated in situ quantitative measurement of protein analysis (AQUA). Results: One hundred and twelve patients (74%) had sufficient tissue for AQUA. The median follow-up time for the entire cohort was 33 months. Patients with low nuclear DCC expression had a 3-year progression-free survival (PFS) rate of 0% compared with 33% of those with high DCC expression (P = 0.0067). In multivariate analysis, low nuclear DCC expression level retained its prognostic significance for PFS. Between DCC and β-catenin, a significant relationship was found, where tumors with low DCC had low β-catenin and vice versa (P = 0.003). Conclusions: Low nuclear DCC levels predict for poor patient outcome inepithelial ovarian cancer. DCC may exert its antitumor function, in part, through regulation of β-catenin levels. © 2006 Oxford University Press.

Notes:

Cited By :5Export Date: 21 February 2017

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