Identification of signaling pathways modulated by RHBDD2 in breast cancer cells: a link to the unfolded protein response View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-05

AUTHORS

E. Lacunza, M. E. Rabassa, R. Canzoneri, M. Pellon-Maison, M. V. Croce, C. M. Aldaz, M. C. Abba

ABSTRACT

Rhomboid domain containing 2 (RHBDD2) was previously observed overexpressed and amplified in breast cancer samples. In order to identify biological pathways modulated by RHBDD2, gene expression profiles of RHBDD2 silenced breast cancer cells were analyzed using whole genome human microarray. Among the statistically significant overrepresented biological processes, we found protein metabolism—with the associated ontological terms folding , ubiquitination, and proteosomal degradation—cell death, cell cycle, and oxidative phosphorylation. In addition, we performed an in silico analysis searching for RHBDD2 co-expressed genes in several human tissues. Interestingly, the functional analysis of these genes showed similar results to those obtained with the microarray data, with negative regulation of protein metabolism and oxidative phosphorylation as the most enriched gene ontology terms. These data led us to hypothesize that RHBDD2 might be involved in endoplasmic reticulum (ER) stress response. Thus, we specifically analyzed the unfolding protein response (UPR) of the ER stress process. We used a lentivirus-based approach for stable silencing of RHBDD2 mRNA in the T47D breast cancer cell line, and we examined the transcriptional consequences on UPR genes as well as the phenotypic effects on migration and proliferation processes. By employing dithiothreitol as an UPR inducer, we observed that cells with silenced RHBDD2 showed increased expression of ATF6, IRE1, PERK, CRT, BiP, ATF4, and CHOP (p <0.01). We also observed that RHBDD2 silencing inhibited colony formation and decreased cell migration. Based on these studies, we hypothesize that RHBDD2 overexpression in breast cancer could represent an adaptive phenotype to the stressful tumor microenvironment by modulating the ER stress response. More... »

PAGES

379-388

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12192-013-0466-3

DOI

http://dx.doi.org/10.1007/s12192-013-0466-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027193113

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24078384


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12192-013-0466-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12192-013-0466-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12192-013-0466-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12192-013-0466-3'


 

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