Differential effects, on oncogenic pathway signalling, by derivatives of the HNF4 α inhibitor BI6015 View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

Jin-Hee Kim, Hyo Jin Eom, GyuTae Lim, Sungjin Park, Jinhyuk Lee, Seungyoon Nam, Yon Hui Kim, Jin-Hyun Jeong

ABSTRACT

BACKGROUND: Gastric cancer (GC) is a highly heterogeneous disease with few "targeted" therapeutic options. Previously, we demonstrated involvement of the transcription factor HNF4α in human GC tumours, and the developmental signal mediator, WNT5A, as a prognostic GC biomarker. One previously developed HNF4α antagonist, BI6015, while not advancing beyond preclinical stages, remains useful for studying GC. METHODS: Here, we characterised the antineoplastic signalling activity of derivatives of BI6015, including transfer of the nitro group from the para position, relative to a methyl group on its benzene ring, to the ortho- and meta positions. We assessed binding efficacy, through surface plasmon resonance and docking studies, while biologic activity was assessed by antimitogenic efficacy against a panel of GC cell lines, and dysregulated transcriptomes, followed by pathway and subpathway analysis. RESULTS: The para derivative of BI6105 was found substantially more growth inhibitory, and effective, in downregulating numerous oncogenic signal pathways, including the embryonic cascade WNT. The ortho and meta derivatives, however, failed to downregulate WNT or other embryonic signalling pathways, unable to suppress GC growth. CONCLUSION: Straightforward strategies, employing bioinformatics analyses, to facilitate the effective design and development of "druggable" transcription factor inhibitors, are useful for targeting specific oncogenic signalling pathways, in GC and other cancers. More... »

PAGES

488-498

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41416-018-0374-5

DOI

http://dx.doi.org/10.1038/s41416-018-0374-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112285934

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30792535


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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.10.1038/s41416-018-0374-5'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41416-018-0374-5'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41416-018-0374-5'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41416-018-0374-5'


 

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