Recent translational research: microarray expression profiling of breast cancer – beyond classification and prognostic markers?

Table 1 Correlation coefficients for selected gene pairs in breast cancer microarray data

^a If more than one probe was present for a gene, the one with the highest correlation and the fewest missing data values was used. ^b Correlation coefficients calculated from log₁₀ intensity ratios from van't Veer and colleagues [11]. The 78 sporadic tumors and 20 BRCA1/BRCA2 tumors were used to compute the correlations. ^c Correlation coefficients calculated from log₂ intensity ratios from Sørlie and colleagues [4]. ^d Correlation coefficients calculated from log₂ intensity ratios from Sotiriou and colleagues [5]. ^e Correlation coefficients calculated from intensity values from West and colleagues [3]. The R ² value for the plot of ERBB2 and GRB7 in Fig. 2a is based on log₁₀(intensity). ^f N/A, data for one or both the two genes not included in the publicly distributed data set. ^g The strength of the positive correlation is reduced by the wide range of values for the progesterone receptor (PGR) in the strong estrogen receptor message (ESR1) subgroup (Fig. 5c). ^h PGR values for 39 of 49 samples were negative. ⁱ The strength of the negative correlation is reduced by the wide range of values for TGFβ2 in the weak ESR1 subgroup (Fig. 5e).

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