Identification of molecular mechanisms for cellular drug resistance by combining drug activity and gene expression profiles View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2005-08

AUTHORS

L Rickardson, M Fryknäs, S Dhar, H Lövborg, J Gullbo, M Rydåker, P Nygren, M G Gustafsson, R Larsson, A Isaksson

ABSTRACT

Acquired drug resistance is a major problem in cancer treatment. To explore the genes involved in chemosensitivity and resistance, 10 human tumour cell lines, including parental cells and resistant subtypes selected for resistance against doxorubicin, melphalan, teniposide and vincristine, were profiled for mRNA expression of 7400 genes using cDNA microarray technology. The drug activity of 66 cancer agents was evaluated on the cell lines, and correlations between drug activity and gene expression were calculated and ranked. Hierarchical clustering of drugs based on their drug-gene correlations yielded clusters of drugs with similar mechanism of action. Genes correlated with drug sensitivity and resistance were imported into the PathwayAssist software to identify putative molecular pathways involved. A substantial number of both proapoptotic and antiapoptotic genes such as signal transducer and activator of transcription 1, mitogen-activated protein kinase 1 and focal adhesion kinase were found to be associated to drug resistance, whereas genes linked to cell cycle control and proliferation, such as cell division cycle 25A and signal transducer of activator of transcription 5A, were associated to general drug sensitivity. The results indicate that combined information from drug activity and gene expression in a resistance-based cell line panel may provide new knowledge of the genes involved in anticancer drug resistance and become a useful tool in drug development. More... »

PAGES

483

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/sj.bjc.6602699

DOI

http://dx.doi.org/10.1038/sj.bjc.6602699

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1002087779

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16012520


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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/sj.bjc.6602699'

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/sj.bjc.6602699'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/sj.bjc.6602699'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/sj.bjc.6602699'


 

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