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Ann Surg Oncol. 2012 Dec;19(13):4129-39. doi: 10.1245/s10434-012-2541-x. Epub 2012 Aug 3.

Prognostic significance of cyclin D1, β-catenin, and MTA1 in patients with invasive ductal carcinoma of the breast.

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  • 1Institute of Biochemistry and Biotechnology, Chung Shan Medical University, Taichung, Taiwan.



To investigate markers for predicting breast cancer progression, we performed a candidate gene-based study that assessed expression change of three genes, cyclin D1, β-catenin, and metastasis-associated protein-1 (MTA1), involving in aggressive phenotypes of cancerous cells, namely hyperproliferation, epithelial-mesenchymal transition, and global transcriptional regulation.


Specimens were from 150 enrolled female patients, with invasive ductal carcinoma, followed up for more than 10 years. mRNA expression of cyclin D1, β-catenin, and MTA1 in cancerous and noncancerous cells microdissected from the primary tumor site was determined by quantitative real-time PCR. The relationship between mRNA expression levels of the genes and clinicopathologic features was assessed by statistical analysis. Disease-free and overall survival (DFS and OS) were analyzed by Kaplan-Meier analysis with log-rank test and a multivariate Cox regression model.


Cyclin D1 was shown to be overexpressed in late-stage breast cancer (stage III/IV). Breast cancer with lymph node metastasis (LNM) showed significantly higher frequency of overexpressed cyclin D1, β-catenin, and MTA1 (P < 0.05). Patients carrying greater numbers of overexpressed genes had joint effects on increased risk in tumors of advanced stages (P ( trend ) = 0.03) and LNM (P ( trend ) < 0.01). In the LNM-negative group, patients whose tumors with greater number of cyclin D1, β-catenin, and MTA1 overexpressions were associated with poorer clinical outcomes, with hazard ratio of 14.79 for OS (P = 0.015) and 7.54 for DFS (P = 0.015) using multivariate Cox regression analysis during the 10-year follow-up.


Higher expression of cyclin D1, β-catenin, and MTA1 mRNAs in breast cancers may prove effective in predicting unfavorable outcomes of breast cancer.

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