Download Systems Biology Analysis Reveals NFAT5 as a novel biomarker and

Systems Biology Analysis Reveals NFAT5 as a novel
biomarker and master regulator of Inflammatory
Breast Cancer
Andrea Remo1*, Ines Simeone2,3*, Massimo Pancione2*, Pietro Parcesepe4, Pascal Finetti5, Luigi
Cerulo1,2, Stefano M. Pagnotta1, Daniel Birnbaum5, Vittorio Colantuoni1, Franco Bonetti4, François
Bertucci5, Erminia Manfrin4+, Michele Ceccarelli1,6+
1
Department of Pathology, Mater Salutis Hospital, Legnago, Italy
Department of Science and Technology, University of Sannio, Benevento, Italy
3
Bioinformatics Laboratory, BIOGEM, Ariano Irpino, Avellino, Italy.
4
Department of Pathology and Diagnosis, University of Verona, Verona, Italy
5
Department of Molecular Oncology, Institut Paoli-Calmettes, U1068 Inserm, Marseille, France
6
Qatar Computing Research Institute (QCRI), Qatar Foundation, Doha, Qatar
*
these authors contributed equally to the realization of this work.
2
+
Corresponding author: Michele Ceccarelli ([email protected]), Erminia Manfrin
([email protected])
Background
Inflammatory Breast Cancer (IBC) is the most rare and aggressive variant of breast cancer; 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.
Methods
In-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE) on IBC/non-IBC
(nIBC) gene expression data (n = 197) were employed to identify novel MRs connected to the IBC phenotype. Pathway
enrichment analysis was used to characterize predicted targets of candidate MRs. The expression pattern of the top
candidate genes 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.
Results
Using in-silico modeling of network-based strategy, we identified three top enriched MRs (NFAT5, CTNNB1, and
MGA) strongly linked to IBC phenotype. Using IHC, we confirmed that NFAT5 expression was higher in IBC than in
nIBC (70% vs. 20%; p=0.0022). Accordingly, the majority of NFAT5-positive IBC samples displayed increased
nuclear expression in comparison with nIBC samples (89% vs. 12% p<0.0001). In the IBC phenotype, potential
constitutive activation of NFAT5 was detected independently of WNT/β-catenin signaling, suggesting that a substantial
portion of IBC may be mediated by the NFAT5 pathway. Concomitant inactivation of NFAT5 or β-catenin signaling
was strongly linked to nIBC, potentially accounting for the better prognosis of this phenotype. Interestingly, MGA- and
NFAT5-regulated genes were enriched in IBCs compared to nIBCs (30% vs 7% and 23% vs 0%; p<0.0001) reinforcing
the role of NFAT5 in IBC pathogenesis.
Conclusions
We 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.
Keywords
Inflammatory breast cancer, NFAT5, MGA, CTNNB1