FROM OMICS TO DRUGS. COMBINATORIAL TARGETING KEY NODES IN
APOPTOSIS NETWORK.
A. Kel1,2,*), A. Gluch1), V. Poroikov3), O. Koborova3), A. Zakharov3) and G.
Selivanova4)
1)
BIOBASE GmbH, Wolfenbuettel, Germany
2)
Institute of Chemical Biology and Fundamental Medicine Siberian Branch of Russian
Academy of Sciences, Novosibirsk, Russia
3)
Institute of Biomedical Chemistry of Russian Academy of Medical Sciences,
Moscow, Russia
4)
Microbiology and Tumor Biology Center (MTC), Karolinska Institutet, Sweden
e-mail: ake@biobase.de
*
Corresponding author
Key words:
Motivation and Aim:In this study, we analyzed a large scale gene expression study of
treatment of breast cancer cell line by antitumor drugs – RITA and Nutlin, whose direct
targets are p53 and Mdm2.
Methods and Algorithms: We have applied ExPlain™ computer system [1] , which
allows to analyze composite structure of promoters, identify transcription factors
involved in regulation of these processes, and perform topological modeling of signal
transduction processes leading to stopping of cell proliferation and apoptosis.
Results: We found that several transcription factors, such as E2F1, Fox and Egr factors,
and c-myc play an important role at the early stages of these processes switching
specific regulatory program of entrance into cell quiescence phase (G0 phase) or
programmed cell death. We also found that transcription factors as ETF, c-myb, ZEB1,
Crx, Oct, and Fox families are key factors contributing to the downregulation of prosurvival genes upon p53 reactivation by RITA antitumor drug leading to apoptosis of
cancer cells. Topological modeling of the signal transduction network upstream of these
transcription factors using ExPlain™ tools allows us to reveal key-nodes of such
network, which might master-regulate the whole program of cell survival which is
balancing versus the program of entrance into cell quiescence phase and apoptosis.
Among them we identified subunits of PI3K kinase. Experimental inhibition of this
kinase in combination with RITA triggers tumor cells to apoptosis. We consider such
key-nodes as the most perspective targets for novel anticancer drugs.
Conclusion: Finally, we applied the powerful chemo-informatics approach based on the
computer toll PASS [2], which allowed us to search for prospective leads among
libraries of small molecular compounds targeting in combined manner the key nodes
found by the ExPlain™ system. We identified several drug candidate whose application
on the cancer cells in the combination with RITA low concentration treatment shifts
balance of survival mechanisms in tumor cells towards apoptosis.
Acknowledgements: This work was partially supported by EU grant Net2Drug (LSHBCT-2007-037590).
References:
[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] Alexey Lagunin, Alla Stepanchikova, Dmitrii Filimonov, Vladimir Poroikov: PASS:
prediction of activity spectra for biologically active substances. Bioinformatics 16(8):
747-748 (2000)