Real-time PCR-based expression profiling of BRCA1-induced genes in primary breast tumors

Background

BRCA1 possesses a number of features common to transcriptional regulatory proteins, suggesting that it may regulate the expression of one or more downstream genes. It is important to determine which genes are transcriptionally influenced by BRCA1 in vivo to explain its role in tumor suppression and in cancer development. In our previous study, a BRCA1 overexpression system enabled us to define the genes whose expression levels were induced in MCF-7 breast cancer cells by using the PCR-dependent suppression subtractive hybridization technique [1].

Herein, we report the preliminary results obtained from our real-time expression profiling of normal-matched primary breast tumors for six genes, three of which were previously reported [1]. The association between the gene expression profiles and histopathological states of these tumors will contribute to the definition of possible diagnostic markers.

Methods

Breast tumors were selected following pathological analysis of fresh-frozen tissue sections. RNAs were extracted from 31 normal-matched breast tumor tissues. Synthesized cDNA samples were subjected to real-time PCR using the QuantiTect SYBR green PCR Master Mix with gene-specific primers. GAPDH is used as a housekeeping gene for normalization. The gene expression levels were quantified using the delta–delta Ct method after normalizing each tumor with its normal counterpart.

Results

The real-time expression level of BRCA1 was highly correlated with ERBIN and SMG1 (Pearson correlation, Minitab; n = 31; r = 0.765 and r = 0.673, respectively; P < 0.0001). The pairwise correlations of BRCA1 expression with those of RENT2 and OVCA1, but not with OVCA2, were at moderate levels (r = 0.41 and r = 0.46, respectively; P < 0.05). Furthermore, primary breast tumors were hierarchically clustered into two major groups based on their real-time gene expression profiles using the CLUSTER program and were visualized by TRIVIEW [2]. Cluster I tumors were characterized by a high-level expression in BRCA1 target genes (n = 20; 1.52 ± 0.6, log₂) and were low grade on average (37.5% I, 50% II, 12.5% III; n = 16). On the other hand, Cluster II included higher grade tumors (45% II, 55% III; n = 11) expressing BRCA1 target genes at a lower level (n = 11; -0.79 ± 0.7, log₂). Based on the Mann–Whitney U test, Cluster I and Cluster II were significantly different in terms of their tumor grades (W = 206; P = 0.0059).

Conclusion

This study demonstrated that real-time RT-PCR studies provide highly accurate quantitative profiling for marker gene association with tumor subtypes. The mRNA expression of ERBIN, ERBB2/HER2 binding protein, was found to be tightly correlated with that of BRCA1 in primary breast tumors, as found in MCF7 cells ectopically expressing BRCA1 [1]. The OVCA1 tumor suppressor gene (17p13.3) that displays frequent LOH in both ovarian cancer and breast cancer also showed correlation with BRCA1 in primary breast tumors used in our study. A certain degree of expression variability, part of which could be attributable to the variation in tumor grade, exists for the genes used in this study, including BRCA1. Our findings support the view that association of the patients' clinical and pathological parameters with the gene expression profiles of breast tumor samples carries great importance in the classification of tumor subtypes.