A VEGF-A signature was able to distinguish VEGF treated and naïve HUVEC's in the GSE18913 dataset.

<p>The 2D scatterplot of the principal component analysis showed that the centroïds had an observed Euclidean distance different from the expected Euclidean distance (p<0.0001). The first principal component of each sample is plotted along the X-axis, while the second principal component is plotted along the Y-axis. VEGF-A treated HUVEC samples are represented in blue and VEGF-A untreated samples are represented in red. Centroïds of both conditions are indicated by a black dot. (Panel A). After conversion to an activation score, the VEGF-A treated HUVEC's showed higher VEGF-A activation score in a time dependent relation (PANEL B AND C).</p

Forest plots of meta-analysis using a random effects model of the β-Catenin BRCA, E2F1, p63, PR, PI3K, RAS and VEGF pathway.

<p>The VEGF and BRCA signature was overall not significantly associated with clinical outcome. The other pathways showed significant association with survival after meta-analysis using 6 datasets (Québec, North Carolina, Melbourne, Niigata, Boston A, Boston B). Note the larger 95% Confidence intervals of the Québec dataset due to lower number of patients. Along the X-axis, hazard ratios are indicated by the centre of each square for each dataset. The meta-analysis used a weighted method (shown by the size of the squares/and the percentages indicated for each dataset) based upon confidence interval/number of patients. The 95% confidence interval for each hazard ratio is indicated by the width of the blue lines originating from the squares. The vertical red line shows the overall hazard ratio after meta-analysis, with the width of the diamond as the 95% confidence interval.</p

A Venn diagram is showing combined results of the meta-analysis: β-Catenin, E2F1, p63 and PI3K activation scores showed significant association with survival and were significantly correlated with all three prognostic signatures (WHR/IGS/GGI) after meta-analysis.

<p>PR and RAS activation scores were associated with clinical outcome, but did not consistently correlate with prognostic signatures. *Negative correlation coefficient **borderline significance with clinical outcome.</p

Estimates of Pearson rho correlation coefficients after meta-analysis of six datasets between pathway activation scores and prognostic gene signatures: wound healing response signature (WHR)/Invasiveness gene signature IGS and Genomic grade Index (GGI).

<p>Most significant correlations are shown. (Threshold p-value adjusted for multiple testing = 0.0025).</p

Table 2 shows the consistent correlations of the β-Catenin activation scores and WHR/IGS/GGI in each separate dataset (Québec, North Carolina, Melbourne, Niigata, Boston A and Boston B dataset).

<p>Overall Rho Coefficients were estimated by a meta-analysis approach using random models effects.</p