Inflammatory breast cancer cells are characterized by abrogated TGFß1-dependent cell motility and SMAD3 activity.

PURPOSE: Inflammatory breast cancer (IBC) is an aggressive form of breast cancer with elevated metastatic potential, characterized by tumor emboli in dermal and parenchymal lymph vessels. This study has investigated the hypothesis that TGFß signaling is implicated in the molecular biology of IBC. METHODS: TGFß1-induced cell motility and gene expression patterns were investigated in three IBC and three non-IBC (nIBC) cell lines. Tissue samples from IBC and nIBC patients were investigated for the expression of nuclear SMAD2, SMAD3, and SMAD4. SMAD protein levels were related to gene expression data. RESULTS: TGFß1-induced cell motility was strongly abrogated in IBC cells (P = 0.003). Genes differentially expressed between IBC and nIBC cells post TGFß1 exposure revealed attenuated expression of SMAD3 transcriptional regulators, but overexpression of MYC target genes in IBC. IBC patient samples demonstrated a near absence of SMAD3 and -4 expression in the primary tumor compared to nIBC patient samples (P < 0.001) and a further reduction of staining intensity in tumor emboli. Integration of gene and protein expression data revealed that a substantial fraction of the IBC signature genes correlated with SMAD3 and these genes are indicative of attenuated SMAD3 signaling in IBC. CONCLUSION: We demonstrate attenuated SMAD3 transcriptional activity and SMAD protein expression in IBC, together with obliterated TGFß1-induced IBC cell motility. The further reduction of nuclear SMAD expression levels in tumor emboli suggests that the activity of these transcription factors is involved in the metastatic dissemination of IBC cells, possibly by enabling collective invasion after partial EMT.

A core invasiveness gene signature reflects epithelial-to-mesenchymal transition but not metastatic potential in breast cancer cell lines and tissue samples.

INTRODUCTION: Metastases remain the primary cause of cancer-related death. The acquisition of invasive tumour cell behaviour is thought to be a cornerstone of the metastatic cascade. Therefore, gene signatures related to invasiveness could aid in stratifying patients according to their prognostic profile. In the present study we aimed at identifying an invasiveness gene signature and investigated its biological relevance in breast cancer. METHODS & RESULTS: We collected a set of published gene signatures related to cell motility and invasion. Using this collection, we identified 16 genes that were represented at a higher frequency than observed by coincidence, hereafter named the core invasiveness gene signature. Principal component analysis showed that these overrepresented genes were able to segregate invasive and non-invasive breast cancer cell lines, outperforming sets of 16 randomly selected genes (all P<0.001). When applied onto additional data sets, the expression of the core invasiveness gene signature was significantly elevated in cell lines forced to undergo epithelial-mesenchymal transition. The link between core invasiveness gene expression and epithelial-mesenchymal transition was also confirmed in a dataset consisting of 2420 human breast cancer samples. Univariate and multivariate Cox regression analysis demonstrated that CIG expression is not associated with a shorter distant metastasis free survival interval (HR = 0.956, 95%C.I. = 0.896-1.019, P = 0.186). DISCUSSION: These data demonstrate that we have identified a set of core invasiveness genes, the expression of which is associated with epithelial-mesenchymal transition in breast cancer cell lines and in human tissue samples. Despite the connection between epithelial-mesenchymal transition and invasive tumour cell behaviour, we were unable to demonstrate a link between the core invasiveness gene signature and enhanced metastatic potential.

Uncovering the molecular secrets of inflammatory breast cancer biology: an integrated analysis of three distinct affymetrix gene expression datasets.

BACKGROUND: Inflammatory breast cancer (IBC) is a poorly characterized form of breast cancer. So far, the results of expression profiling in IBC are inconclusive due to various reasons including limited sample size. Here, we present the integration of three Affymetrix expression datasets collected through the World IBC Consortium allowing us to interrogate the molecular profile of IBC using the largest series of IBC samples ever reported. EXPERIMENTAL DESIGN: Affymetrix profiles (HGU133-series) from 137 patients with IBC and 252 patients with non-IBC (nIBC) were analyzed using unsupervised and supervised techniques. Samples were classified according to the molecular subtypes using the PAM50-algorithm. Regression models were used to delineate IBC-specific and molecular subtype-independent changes in gene expression, pathway, and transcription factor activation. RESULTS: Four robust IBC-sample clusters were identified, associated with the different molecular subtypes (P<0.001), all of which were identified in IBC with a similar prevalence as in nIBC, except for the luminal A subtype (19% vs. 42%; P<0.001) and the HER2-enriched subtype (22% vs. 9%; P<0.001). Supervised analysis identified and validated an IBC-specific, molecular subtype-independent 79-gene signature, which held independent prognostic value in a series of 871 nIBCs. Functional analysis revealed attenuated TGF-ß signaling in IBC. CONCLUSION: We show that IBC is transcriptionally heterogeneous and that all molecular subtypes described in nIBC are detectable in IBC, albeit with a different frequency. The molecular profile of IBC, bearing molecular traits of aggressive breast tumor biology, shows attenuation of TGF-ß signaling, potentially explaining the metastatic potential of IBC tumor cells in an unexpected manner.