Abstract P6-04-07: Pathway Activation Probability Score Analysis Reveals Patterns of Pathway Deregulation in Inflammatory Breast Cancer

Background: Inflammatory breast cancer (IBC) is the most aggressive manifestation of primary epithelial breast cancer and differs from non-IBC both from a clinical and a biological perspective. The high metastatic potential of IBC is highlighted by the low 5-year survival rate of 50%. In the past, we demonstrated that IBC is characterized by a specific molecular profile, partly mediated by increased NFkB-activation. In the current study we aim to identify additional molecular alterations responsible for the altered gene expression profile. Methods: We profiled 46 IBC samples and 56 non-stage matched nIBC samples using the Affymetrix HGU133plus2 platform. Using a set of recently published gene signatures (Gatza et al, PNAS, 2010) we calculated the activation probability scores for 18 distinct pathways (ER, PR, HER2, P53, P63, EGFR, RAS, SRC, TNFa, INFa, INFg, TGFb, STAT3, E2F1, PI3K, AKT, CTNNB and MYC). Unsupervised cluster analysis was performed on the IBC samples only to identify IBC-specific transcriptional heterogeneity. The silhouette-algorithm was used to test the robustness of clustering. Supervised analysis was performed to compare IBC to nIBC. All P-values were FDR-corrected. Results: Using only IBC samples, unsupervised hierarchical cluster analysis identified four robust sample clusters (Average silhouette width = 0.345; P 0.65, P Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P6-04-07.