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Inspecting the Role of PI3K/AKT Signaling Pathway in Cancer Development Using an In Silico Modeling and Simulation Approach

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Bioinformatics and Biomedical Engineering (IWBBIO 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10813))

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Abstract

PI3K/AKT signaling pathway plays a crucial role in the control of functions related to cancer biology, including cellular proliferation, survival, migration, angiogenesis and apoptosis; what makes this signaling pathway one of the main processes involved in cancer development. The analysis and prediction of the anticancer targets acting over the PI3K/AKT signaling pathway requires of a deep understanding of its signaling elements, the complex interactions that take place between them, as well as the global behaviors that arise as a result, that is, a systems biology approach. Following this methodology, in this work, we propose an in silico modeling and simulation approach of the PI3K class I and III signaling pathways, for exploring its effect over AKT and SGK proteins, its relationship with the deregulated growth control in cancer, its role in metastasis, as well as for identifying possible control points. The in silico approach provides symbolic abstractions and accurate algorithms that allow dealing with crucial aspects of the cellular signal transduction such as compartmentalization, topology and timing. Our results show that the activation or inhibition of target signaling elements in the overall signaling pathway can change the outcome of the cell, turning it into apoptosis or proliferation.

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References

  1. Lien, E.C., Dibble, C.C., Toker, A.: PI3K signaling in cancer: beyond AKT. Curr. Opin. Cell Biol. 45, 62–71 (2017). https://doi.org/10.1016/j.ceb.2017.02.007

    Article  Google Scholar 

  2. Alves, R., Antunes, F., Salvador, A.: Tools for kinetic modeling of biochemical networks. Nat. Biotechnol. 24(6), 667–672 (2006). https://doi.org/10.1038/nbt0606-667

    Article  Google Scholar 

  3. Ciocchetta, F., Duguid, A., Guerriero, M.L.: A compartmental model of the cAMP/PKA/MAPK pathway in bio-PEPA. In: Third Workshop on Membrane Computing and Biologically Inspired Process Calculi (MeCBIC) (2009). http://dx.doi.org/10.4204/EPTCS.11.5

  4. Kerr, R.A., Bartol, T.M., Kaminsky, B., Dittrich, M., Chang, J.C., Baden, S.B., Sejnowski, T.J., Stiles, J.R.: Fast Monte Carlo simulation methods for biological reaction-diffusion systems in solution and on surfaces. SIAM J. Sci. Comput. 30(36), 3126–3149 (2008). https://doi.org/10.1137/070692017

    Article  MathSciNet  MATH  Google Scholar 

  5. Hoops, S., Sahle, S., Gauges, R., Lee, C., Pahle, J., Simus, N., Singhal, M., Xu, L., Mendes, P., Kummer, U.: COPASI: a complex pathway simulator. Bioinformatics 22(24), 3067–3074 (2006). https://doi.org/10.1093/bioinformatics/btl485

    Article  Google Scholar 

  6. Cowan, A.E., Moraru, I.I., Schaff, J.C., Slepchenko, B.M., Loew, L.M.: Spatial modeling of cell signaling networks. Methods Cell Biol. 110, 195–221 (2012). https://doi.org/10.1016/B978-0-12-388403-9.00008-4

    Article  Google Scholar 

  7. Swat, M., Thomas, G.L., Belmonte, J.M., Shirinifard, A., Hmeljak, D., Glazier, J.A.: Multi-scale modeling of tissues using CompuCell 3D. Methods Cell Biol. 110, 325–366 (2012). https://doi.org/10.1016/B978-0-12-388403-9.00013-8

    Article  Google Scholar 

  8. González-Pérez, P.P., Omicini, A., Sbaraglia, M.: A biochemically inspired coordination-based model for simulating intracellular signalling pathway. J. Simul. 27(3), 216–226 (2013). https://doi.org/10.1057/jos.2012.28

    Article  Google Scholar 

  9. Cárdenas-García, M., González-Pérez, P.P., Montagna, S., Cortés Sánchez, O., Caballero, E.H.: Modeling intercellular communication as a survival strategy of cancer cells: an in silico approach on a flexible bioinformatics framework. Bioinform. Biol. Insights 10, 5–18 (2016). https://doi.org/10.4137/BBI.S38075

    Article  Google Scholar 

  10. Gelernter, D.: Generative communication in Linda. ACM Trans. Program. Lang. Syst. 7(1), 80–112 (1985). https://doi.org/10.1145/2363.2433

    Article  MATH  Google Scholar 

  11. Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81(25), 2340–2361 (1977). https://doi.org/10.1021/j100540a008

    Article  Google Scholar 

  12. Downward, J.: Targeting RAS signalling pathways in cancer therapy. Nat. Rev. Cancer 3(1), 11–22 (2013). https://doi.org/10.1038/nrc969

    Article  Google Scholar 

  13. Goodsell, D.S.: The molecular perspective: the ras oncogene. Oncologist 4(3), 263–264 (1999)

    Google Scholar 

  14. Neves, S.R., Ram, P.T., Iyengar, R.: G protein pathways. Science 296(5573), 1636–1639 (2002). https://doi.org/10.1126/science.1071550

    Article  Google Scholar 

  15. González-Pérez, P.P., Cárdenas, M., Camacho, D., Franyuti, A., Rosas, O., Lagúnez-Otero, J.: Cellulat: an agent-based intracellular signalling model. Biosystems 68(2–3), 171–185 (2003). https://doi.org/10.1016/S0303-2647(02)00094-1

    Article  Google Scholar 

  16. Reyton-González, M.L., Cornell-Kennon, S., Schaefer, E., Kuzmic, P.: An algebraic model to determine substrate kinetic parameters by global nonlinear fit of progress curves. Anal. Biochem. 1(518), 16–24 (2017). https://doi.org/10.1016/j.ab.2016.11.001

    Article  Google Scholar 

  17. Azevedo-Silva, J., Queirós, O., Ribeiro, A., Baltazar, F., Young, K.H., Pedersen, P.L., Preto, A., Casal, M.: The cytotoxicity of 3-bromopyruvate in breast cáncer cells depends on extracelular pH. Biochem. J. 467(2), 247–258 (2015). https://doi.org/10.1042/BJ20140921

    Article  Google Scholar 

  18. Blokh, D., Stambler, I., Afrimzon, E., Shafran, Y., Korech, E., Sandbank, J., Orda, R., Zurgil, N., Deutsch, M.: The information-theory analysis of Michaelis-menten constants for detection of breast cáncer. Cancer Detec. Prev. 31(6), 489–498 (2007). https://doi.org/10.1016/j.cdp.2007.10.010

    Article  Google Scholar 

  19. Paradiso, A., Cardone, R.A., Bellizzi, A., Bagorda, A., Guerro, L., Tommasino, M., Casavola, V., Reshkin, S.J.: The Na+-H+ exchanger-1 induces cytoskeletal changes involving reciprocal RhoA and Rac1 signaling, resulting in motility and invasión in MDA-MB-435 cells. Breast Cancer Res. 6(6), R616–R628 (2004). https://doi.org/10.1186/bcr922

    Article  Google Scholar 

  20. Fritz, J., Dwyer-Nield, L., Malkinson, A.M.: Stimulation of neoplastic mouse lung cell proliferation by alveolar macrophage-derived, insulin-like growth factor-1 can be blocked by inhibiting MEK and PI3K activation. Mol. Cancer 10, 76–96 (2011). https://doi.org/10.1186/1476-4598-10-76

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Universidad Autónoma Metropolitana, Av. Vasco de Quiroga 4871, 05300, Ciudad de México, Mexico

    Pedro Pablo González-Pérez

  2. Benemérita Universidad Autónoma de Puebla, 13 sur 2702, Col. Volcanes, 72420, Puebla, Mexico

    Maura Cárdenas-García

Authors
  1. Pedro Pablo González-Pérez
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  2. Maura Cárdenas-García
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Corresponding author

Correspondence to Pedro Pablo González-Pérez .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Granada, Granada, Spain

    Francisco Ortuño

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González-Pérez, P.P., Cárdenas-García, M. (2018). Inspecting the Role of PI3K/AKT Signaling Pathway in Cancer Development Using an In Silico Modeling and Simulation Approach. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10813. Springer, Cham. https://doi.org/10.1007/978-3-319-78723-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-78723-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78722-0

  • Online ISBN: 978-3-319-78723-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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