[Colloquium] Seminar Announcement: Key-nodes in signal transduction network are potent drug targets for combating survival of tumor cells

[Ninfa Mayorga]

Computation Institute

Speaker: Alexander Kel, PhD, CSO, GeneXplain GmbH, Germany
Host: Andrey Rzhetsky
Date: March 1, 2011
Time: 1:00 PM - 2:00 PM
Location: The University of Chicago, Searle 240a, 5735 S. Ellis Avenue

Key-nodes in signal transduction network are potent drug targets for  
combating survival of tumor cells

Alexander Kel1), Angela Gluch2), Vladimir Poroikov3) and Galina  
Selivanova4)

1) geneXplain, Wolfenbuettel, Germany
2)BIOBASE GmbH, Wolfenbuettel, Germany
3) Institute of Biomedical Chemistry of Russian Academy of Medical
Sciences, Moscow, Russia
4) Microbiology and Tumor Biology Center (MTC), Karolinska Institutet,
Sweden

In this study, we analyzed large scale gene expression and ChIP-seq  
data from a study of a breast cancer cell line treated with the  
antineoplastic agents RITA and Nutlin, the direct targets of which are  
p53 and Mdm2. We analyzed the composite promoter structure of  
differentially expressed genes, thus identifying combinations of  
transcription factors potentially involved in the regulation of these  
genes. We found that transcription factors of Elk, Oct, Pax and E2F  
families are key factors contributing to the down-regulation of pro- 
survival genes upon p53 reactivation by RITA, which leads to apoptosis  
of cancer cells. Topological modeling of the signal transduction  
network upstream of these transcription factors [1] allowed us to  
reveal key-nodes - potent master-regulators of the cell survival  
program that prevent efficient apoptosis of cancer cells. Such key- 
nodes can be considered as prospective targets for novel anticancer  
drugs. We applied a powerful cheminformatics ligand based approach  
using the computer tool PASS [2], which allowed us to scan a library  
of over 30 million small molecules and identify prospective leads  
targeting in combined manner the key nodes found in this study. As a  
result of this approach, two novel prospective antineoplastic agents  
were identified and experimentally validated in a cellular assay  
confirming their synergistic potential in highly selective triggering  
of apoptosis of cancer cells.

The current approach for the integrated analysis of the '-omics' data  
and for identification of causative biomarkers and drug targets was  
introduced as a basis for the novel systems biology tool, geneXplain  
platform(tm) (www.genexplain.com) (Fig.1).

Fig.1. geneXplain Platform(tm)- a toolbox for bioinformatics,systems  
biology and cheminformatics. It identifies key nodes (shown in red) -  
potential master-regulators of the disease genes.

This work was partially supported by EU grant Net2Drug (LSHB- 
CT-2007-037590).

[1] Kel A, Voss N, Valeev T, Stegmaier P, Kel-Margoulis O, Wingender  
E. ExPlain: finding upstream drug targets in disease gene regulatory  
networks. SAR QSAR Environ Res. 2008;19(5-6):481-94.
[2] Poroikov V., Filimonov D. PASS: Prediction of Biological Activity  
Spectra for Substances. In: Predictive Toxicology. Ed. by Christoph  
Helma. Taylor & Francis, 2005; 459-478.


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