Expression profiling of BRCA1 associated breast tumors

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BRCA1-associated breast tumours frequently show unfavourable features, ie poor differentiation, high proliferation indices, aneuploidy, ER- and PgR negativity, and TP53 positivity. These data are based on single gene analysis. Expression arrays, however, allow for the simultaneous investigation of multiple genes. We have used Atlas Human Cancer cDNA Expression Arrays (Clontech), on which 588 cancer-related genes are spotted, for an exploratory analysis. Profiles of one cell line and six tumours from patients with an inherited BRCA1 gene mutation were weighed against those from 15 patients without a family history who had similar clinico-pathological characteristics which are collected in our computerised database system. Total RNA isolation was performed according to standard procedures. RNAs were used to synthesise ³²P-radiolabeled cDNA for hybridisation to the cancer cDNA expression arrays, according to the manufacturer's instructions. Data were acquired and quantified using the Molecular Dynamics PhosphoImager and ImageQuant software (Molecular Dynamics, Sunnyvale, USA). The levels of the lowest and highest expressed genes differed at 100- or 1000-fold. In an exploratory analysis we have considered only the upper 30% ranking of the signals for each tumor sample as 'high' expression (H), and the data were dichotomised: high (H) vs low (L).

In this pilot study on 6 BRCA1 and 15 sporadic tumours we observed that 14 genes showed high (H) expression levels, in all cases. Furthermore, 396 genes showed a heterogeneous expression pattern (including the EGF-R, MYC, p16, HER2/neu and uPA). These heterogeneous expression levels are consistent with our previous studies on breast cancer. Ten genes are mostly expressed at an increased level in BRCA1 tumours when compared to sporadic tumours. Interestingly the majority of these genes are known to play a role in cell adhesion, motility and invasion. Although the series of breast tumours analysed is relatively small, we were able to identify genes whose expression appears differential in BRCA1 and sporadic breast tumours. Cluster analysis, which allows for grouping of tumors and genes according to similar patterns of expression, revealed that the expression profiles of 5 out of 6 BRCA1-associated tumors are clustered in one arm. Extension of the number of genes and tumour samples will reveal additional genes.