title: Uncovering the molecular secrets of inflammatory breast cancer biology: an integrated analysis of three distinct affymetrix gene expression datasets.
abstract: 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.
  
  
  METHODS
  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-β signaling in IBC.
  
  
  CONCLUSIONS
  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-β signaling, potentially explaining the metastatic potential of IBC tumor cells in an unexpected manner.
authors: Translational Cancer Research Unit, Oncology Center, General Hospital Sint-Augustinus, Antwerp, Wilrijk, Belgium. Steven.VanLaere@GZA.be
authors: Steven J
authors: SJ
authors: Van Laere
authors: Naoto T
authors: NT
authors: Ueno
authors: Pascal
authors: P
authors: Finetti
authors: Peter
authors: P
authors: Vermeulen
authors: Anthony
authors: A
authors: Lucci
authors: Fredika M
authors: FM
authors: Robertson
authors: Melike
authors: M
authors: Marsan
authors: Takayuki
authors: T
authors: Iwamoto
authors: Savitri
authors: S
authors: Krishnamurthy
authors: Hiroko
authors: H
authors: Masuda
authors: Peter
authors: P
authors: van Dam
authors: Wendy A
authors: WA
authors: Woodward
authors: Patrice
authors: P
authors: Viens
authors: Massimo
authors: M
authors: Cristofanilli
authors: Daniel
authors: D
authors: Birnbaum
authors: Luc
authors: L
authors: Dirix
authors: James M
authors: JM
authors: Reuben
authors: François
authors: F
authors: Bertucci
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D058922:Inflammatory Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D008875:Middle Aged; D009367:Neoplasm Staging; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000235:genetics*; D015398:Signal Transduction / Q000235:genetics
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human
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