Mathematical Biosciences and Engineering, 2015, 12(6): 1289-1302. doi: 10.3934/mbe.2015.12.1289.

Primary: 92C42; Secondary: 94C15.

Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

Algebraic and topological indices of molecular pathway networks in human cancers

1. Department of Mathematical Sciences, University of Wisconsin – Milwaukee, P.O. Box 413, Milwaukee, WI 53201-0413
2. Newman-Lakka Institute, Tufts University School of Medicine, Boston, MA 02111
3. Cross Cancer Institute, University of Alberta, Edmonton, T6G 2E1
4. Cross Cancer Institute and Department of Physics, University of Alberta, Edmonton, T6G 2E1

   

Protein-protein interaction networks associated with diseases have gained prominence as an area of research.We investigate algebraic and topological indices for protein-protein interaction networks of 11 human cancers derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We find a strong correlationbetween relative automorphism group sizes and topological network complexities on the one hand and five year survival probabilities on the other hand. Moreover, we identify several protein families (e.g. PIK, ITG, AKT families) that are repeated motifs in many of the cancer pathways. Interestingly, these sources of symmetry are often central rather than peripheral. Our results can aide in identification of promising targets for anti-cancer drugs. Beyond that, we provide a unifying framework to study protein-protein interaction networks of families of related diseases (e.g. neurodegenerative diseases, viral diseases, substance abuse disorders).
  Figure/Table
  Supplementary
  Article Metrics

Keywords automorphism groups; Protein-protein interaction networks; cyclomatic number.

Citation: Peter Hinow, Edward A. Rietman, Sara Ibrahim Omar, Jack A. Tuszyński. Algebraic and topological indices of molecular pathway networks in human cancers. Mathematical Biosciences and Engineering, 2015, 12(6): 1289-1302. doi: 10.3934/mbe.2015.12.1289

References

  • 1. Nature, 406 (2000), 378-382.
  • 2. Pharmacy and Therapeutics, 36 (2011), 225-227.
  • 3. Algorithmica, 40 (2004), 51-62.
  • 4. Cambridge University Press, Cambridge, 2001.
  • 5. Proc. Natl. Acad. Sci. USA, 109 (2012), 9209-9212.
  • 6. Expert Opin. Drug Discov., 8 (2013), 7-20.
  • 7. Pharmacol. Therapeut., 138 (2013), 333-408.
  • 8. Symmetry, 2 (2010), 1683-1709, arXiv:1006.3923.
  • 9. Nat. Rev. Drug Discov., 10 (2011), 563-564.
  • 10. Nucleic Acid Res., 37 (2009), 1-13.
  • 11. Nature Protocols, 4 (2009), 44-57, http://david.abcc.ncifcrf.gov/
  • 12. John Wiley & Sons, Hoboken, NJ, 2008.
  • 13. Nucleic Acid Res., 28 (2000), 23-30, http://www.genome.jp/kegg/.
  • 14. Nucleic Acid Res., 32 (2004), D277-D280.
  • 15. In A Voronkov, editor, The Alan Turing Centenary, pages 181-195. EasyChair, 2012,http://vlsicad.eecs.umich.edu/BK/SAUCY/.
  • 16. Computer Science Review, 3 (2009), 199-243.
  • 17. Landes Bioscience, Austin, TX, 2006.
  • 18. Springer Verlag, Dordrecht, Heidelberg, New York, London, 2012.
  • 19. Discr. Appl. Math., 156 (2008), 3525-3531.
  • 20. http://seer.cancer.gov/.
  • 21. Theor. Biol. Med. Model., 8 (2011), p21.
  • 22. Genome Res., 13 (2003), 2498-2504. http://cytoscape.org.
  • 23. BioSystems, 113 (2013), 149-154.
  • 24. University of St Andrews, St Andrews, United Kingdom, 2013. http://www.gap-system.org.
  • 25. BMC Syst. Biol., 7 (2013), p90.
  • 26. Phys. Rev. E, 78 (2008), 046102, arXiv:0802.4318.
  • 27. Bioinformatics, 25 (2009), 1470-1471, http://bioconductor.org.

 

This article has been cited by

  • 1. Edward A. Rietman, John Platig, Jack A. Tuszynski, Giannoula Lakka Klement, Thermodynamic measures of cancer: Gibbs free energy and entropy of protein–protein interactions, Journal of Biological Physics, 2016, 42, 3, 339, 10.1007/s10867-016-9410-y
  • 2. Ellen Kure Fischer, Antonio Drago, A molecular pathway analysis stresses the role of inflammation and oxidative stress towards cognition in schizophrenia, Journal of Neural Transmission, 2017, 124, 7, 765, 10.1007/s00702-017-1730-y
  • 3. Edward Rietman, Jack A. Tuszynski, , Theoretical and Applied Aspects of Systems Biology, 2018, Chapter 8, 139, 10.1007/978-3-319-74974-7_8

Reader Comments

your name: *   your email: *  

Copyright Info: 2015, Peter Hinow, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved