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Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer

Overview of attention for article published in Journal of Translational Medicine, May 2015
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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53 Mendeley
Title
Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer
Published in
Journal of Translational Medicine, May 2015
DOI 10.1186/s12967-015-0492-2
Pubmed ID
Authors

Andrea Remo, Ines Simeone, Massimo Pancione, Pietro Parcesepe, Pascal Finetti, Luigi Cerulo, Halima Bensmail, Daniel Birnbaum, Steven J Van Laere, Vittorio Colantuoni, Franco Bonetti, François Bertucci, Erminia Manfrin, Michele Ceccarelli

Abstract

Inflammatory 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. In-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. Using 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. 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 52 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 21%
Researcher 7 13%
Student > Bachelor 6 11%
Student > Doctoral Student 5 9%
Student > Master 5 9%
Other 8 15%
Unknown 11 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 34%
Agricultural and Biological Sciences 9 17%
Medicine and Dentistry 8 15%
Computer Science 3 6%
Immunology and Microbiology 1 2%
Other 3 6%
Unknown 11 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 August 2015.
All research outputs
#12,728,685
of 22,800,560 outputs
Outputs from Journal of Translational Medicine
#1,428
of 3,991 outputs
Outputs of similar age
#117,000
of 264,364 outputs
Outputs of similar age from Journal of Translational Medicine
#34
of 91 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,991 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,364 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.