Abstract
BackgroundInflammatory breast cancer (IBC) is the most rare and aggressive variant of breast cancer (BC); however, only a limited number of specific gene signatures with low generalization abilities are available and few reliable biomarkers are helpful to improve IBC classification into a molecularly distinct phenotype. We applied a network-based strategy to gain insight into master regulators (MRs) linked to IBC pathogenesis.MethodsIn-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) on IBC/non-IBC (nIBC) gene expression data (n = 197) was employed to identify novel master regulators connected to the IBC phenotype. Pathway enrichment analysis was used to characterize predicted targets of candidate genes. The expression pattern of the most significant MRs was then evaluated by immunohistochemistry (IHC) in two independent cohorts of IBCs (n = 39) and nIBCs (n = 82) and normal breast tissues (n = 15) spotted on tissue microarrays. The staining pattern of non-neoplastic mammary epithelial cells was used as a normal control.ResultsUsing in-silico modeling of network-based strategy, we identified three top enriched MRs (NFAT5, CTNNB1 or β-catenin, and MGA) strongly linked to the IBC phenotype. By IHC assays, we found that IBC patients displayed a higher number of NFAT5-positive cases than nIBC (69.2% vs. 19.5%; p-value = 2.79 10-7). Accordingly, the majority of NFAT5-positive IBC samples revealed an aberrant nuclear expression in comparison with nIBC samples (70% vs. 12.5%; p-value = 0.000797). NFAT5 nuclear accumulation occurs regardless of WNT/β-catenin activated signaling in a substantial portion of IBCs, suggesting that NFAT5 pathway activation may have a relevant role in IBC pathogenesis. Accordingly, cytoplasmic NFAT5 and membranous β-catenin expression were preferentially linked to nIBC, accounting for the better prognosis of this phenotype.ConclusionsWe provide evidence that NFAT-signaling pathway activation could help to identify aggressive forms of BC and potentially be a guide to assignment of phenotype-specific therapeutic agents. The NFAT5 transcription factor might be developed into routine clinical practice as a putative biomarker of IBC phenotype.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0492-2) contains supplementary material, which is available to authorized users.
Highlights
Inflammatory breast cancer (IBC) is the most rare and aggressive variant of breast cancer (BC); only a limited number of specific gene signatures with low generalization abilities are available and few reliable biomarkers are helpful to improve IBC classification into a molecularly distinct phenotype
We show that the nuclear expression of the Nuclear Factor of Activated T-Cell 5 (NFAT5) Transcription factor (TF) is a peculiar feature of IBC, which could be used as a potential biomarker of this disease and a possible candidate for treatments
IBC signature is enriched for dis-regulation of cell cycle In [7], an integrated analysis of gene expression and array-based comparative genomic hybridization (aCGH) microarray applied to IBCs and non-inflammatory breast cancer (nIBC) and 13,127 genes identified 24 potential candidate IBC-specific genes that accurately distinguished IBCs and nIBCs
Summary
Inflammatory breast cancer (IBC) is the most rare and aggressive variant of breast cancer (BC); only a limited number of specific gene signatures with low generalization abilities are available and few reliable biomarkers are helpful to improve IBC classification into a molecularly distinct phenotype. Using an integrated analysis of gene expression and array-based comparative genomic hybridization (aCGH), 24 potential IBC-specific oncogenes have been identified, which could be involved in IBC aggressiveness [7]. The analysis of about four hundreds of whole-genome mRNA expression profiles revealed that IBC is transcriptionally heterogeneous, that all molecular subtypes described in nIBC are detectable in IBC, albeit with a different frequency, and identified down-regulation of TGFβ as biologically relevant [9]. These advances have not yet led to clinical applications, and the need to identify clinical IBC biomarkers to improve diagnosis and treatment persists
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