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Gibbs free energy of protein-protein interactions correlates with ATP production in cancer cells

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Abstract

In this paper, we analyze several cancer cell types from two seemingly independent angles: (a) the over-expression of various proteins participating in protein-protein interaction networks and (b) a metabolic shift from oxidative phosphorylation to glycolysis. We use large data sets to obtain a thermodynamic measure of the protein-protein interaction network, namely the associated Gibbs free energy. We find a strong inverse correlation between the percentage of energy production via oxidative phosphorylation and the Gibbs free energy of the protein networks. The latter is a measure of functional dysregulation within the cell. Our findings corroborate earlier indications that signaling pathway upregulation in cancer cells is linked to the metabolic shift known as the Warburg effect; hence, these two seemingly independent characteristics of cancer phenotype may be interconnected.

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References

  1. Jose, C., Bellance, N., Rossignol, R.: Choosing between glycolysis and oxidative phosphorylation: a tumor’s dilemma? Biochim. Biophys. Acta 1807, 552–561 (2011). https://doi.org/10.1016/j.bbabio.2010.10.012

    Article  Google Scholar 

  2. Zu, X.L., Guppy, M.: Cancer metabolism: facts, fantasy, and fiction. Biochem. Biophys. Res. Commun. 313, 459–465 (2004). https://doi.org/10.1016/j.bbrc.2003.11.136

    Article  Google Scholar 

  3. Moreno-Sánchez, R., Rodríguez-Enríquez, S., Marín-Hernández, A., Saavedra, E.: Energy metabolism in tumor cells. FEBS J. 274, 1393–1418 (2007). https://doi.org/10.1111/j.1742-4658.2007.05686.x

    Article  Google Scholar 

  4. Marin-Valencia, I., Yang, C., Mashimo, T., Cho, S., Baek, H., Yang, X.-L., Rajagopalan, K.N., Maddie, M., Vemireddy, V., Zhao, Z., Cai, L., Good, L., Tu, B.P., Hatanpaa, K.J., Mickey, B.E., Matés, J.M., Pascual, J.M., Maher, E.A., Malloy, C.R., Deberardinis, R.J., Bachoo, R.M.: Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo. Cell Metab. 15, 827–837 (2012). https://doi.org/10.1016/j.cmet.2012.05.001

    Article  Google Scholar 

  5. Moreno-Sánchez, R., Rodríguez-Enríquez, S., Saavedra, E., Marín-Hernández, A., Gallardo-Pérez, J.C.: The bioenergetics of cancer: is glycolysis the main ATP supplier in all tumor cells? BioFactors Oxf. Engl. 35, 209–225 (2009). https://doi.org/10.1002/biof.31

    Article  Google Scholar 

  6. Rodríguez-Enríquez, S., Torres-Márquez, M.E., Moreno-Sánchez, R.: Substrate oxidation and ATP supply in AS-30D hepatoma cells. Arch. Biochem. Biophys. 375, 21–30 (2000). https://doi.org/10.1006/abbi.1999.1582

    Article  Google Scholar 

  7. Wu, H., Ying, M., Hu, X.: Lactic acidosis switches cancer cells from aerobic glycolysis back to dominant oxidative phosphorylation. Oncotarget 7, 40621–40629 (2016). https://doi.org/10.18632/oncotarget.9746

    Article  Google Scholar 

  8. Guppy, M., Leedman, P., Zu, X., Russell, V.: Contribution by different fuels and metabolic pathways to the total ATP turnover of proliferating MCF-7 breast cancer cells. Biochem. J. 364, 309–315 (2002). https://doi.org/10.1042/bj3640309

    Article  Google Scholar 

  9. Gatenby, R.A., Gillies, R.J.: Glycolysis in cancer: a potential target for therapy. Int. J. Biochem. Cell Biol. 39, 1358–1366 (2007). https://doi.org/10.1016/j.biocel.2007.03.021

    Article  Google Scholar 

  10. Rietman, E.A., Scott, J.G., Tuszynski, J.A., Klement, G.L.: Personalized anticancer therapy selection using molecular landscape topology and thermodynamics. Oncotarget 8, 18735 (2017). https://doi.org/10.18632/oncotarget.12932

    Article  Google Scholar 

  11. Breitkreutz, D., Hlatky, L., Rietman, E., Tuszynski, J.A.: Molecular signaling network complexity is correlated with cancer patient survivability. Proc. Natl. Acad. Sci. U. S. A. 109, 9209–9212 (2012). https://doi.org/10.1073/pnas.1201416109

    Article  ADS  Google Scholar 

  12. Kim, M.-S., Pinto, S.M., Getnet, D., Nirujogi, R.S., Manda, S.S., Chaerkady, R., Madugundu, A.K., Kelkar, D.S., Isserlin, R., Jain, S., Thomas, J.K., Muthusamy, B., Leal-Rojas, P., Kumar, P., Sahasrabuddhe, N.A., Balakrishnan, L., Advani, J., George, B., Renuse, S., Selvan, L.D.N., Patil, A.H., Nanjappa, V., Radhakrishnan, A., Prasad, S., Subbannayya, T., Raju, R., Kumar, M., Sreenivasamurthy, S.K., Marimuthu, A., Sathe, G.J., Chavan, S., Datta, K.K., Subbannayya, Y., Sahu, A., Yelamanchi, S.D., Jayaram, S., Rajagopalan, P., Sharma, J., Murthy, K.R., Syed, N., Goel, R., Khan, A.A., Ahmad, S., Dey, G., Mudgal, K., Chatterjee, A., Huang, T.-C., Zhong, J., Wu, X., Shaw, P.G., Freed, D., Zahari, M.S., Mukherjee, K.K., Shankar, S., Mahadevan, A., Lam, H., Mitchell, C.J., Shankar, S.K., Satishchandra, P., Schroeder, J.T., Sirdeshmukh, R., Maitra, A., Leach, S.D., Drake, C.G., Halushka, M.K., Prasad, T.S.K., Hruban, R.H., Kerr, C.L., Bader, G.D., Iacobuzio-Donahue, C.A., Gowda, H., Pandey, A.: A draft map of the human proteome. Nature 509, 575–581 (2014). https://doi.org/10.1038/nature13302

    Article  ADS  Google Scholar 

  13. Wilhelm, M., Schlegl, J., Hahne, H., Gholami, A.M., Lieberenz, M., Savitski, M.M., Ziegler, E., Butzmann, L., Gessulat, S., Marx, H., Mathieson, T., Lemeer, S., Schnatbaum, K., Reimer, U., Wenschuh, H., Mollenhauer, M., Slotta-Huspenina, J., Boese, J.-H., Bantscheff, M., Gerstmair, A., Faerber, F., Kuster, B.: Mass-spectrometry-based draft of the human proteome. Nature 509, 582–587 (2014). https://doi.org/10.1038/nature13319

    Article  ADS  Google Scholar 

  14. Guo, Y., Sheng, Q., Li, J., Ye, F., Samuels, D.C., Shyr, Y.: Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data. PLoS One 8, e71462 (2013). https://doi.org/10.1371/journal.pone.0071462

    Article  ADS  Google Scholar 

  15. Vaupel, P., Kallinowski, F., Okunieff, P.: Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Res 49, 6449–6465 (1989) published December 1989

    Google Scholar 

  16. Newman, M.: Networks. Oxford University Press, Oxford (2018)

    Book  Google Scholar 

  17. Pelicano, H., Xu, R.-H., Du, M., Feng, L., Sasaki, R., Carew, J.S., Hu, Y., Ramdas, L., Hu, L., Keating, M.J., Zhang, W., Plunkett, W., Huang, P.: Mitochondrial respiration defects in cancer cells cause activation of Akt survival pathway through a redox-mediated mechanism. J. Cell Biol. 175, 913–923 (2006). https://doi.org/10.1083/jcb.200512100

    Article  Google Scholar 

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Acknowledgments

JAT gratefully acknowledges generous support from NSERC (Canada).

Author information

Authors and Affiliations

  1. Chemical Engineering Department, University of Massachusetts, Amherst, MA, USA

    Stefan M. Golas

  2. Microbiology Department, University of Massachusetts, Amherst, MA, USA

    Amber N. Nguyen

  3. College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA

    Edward A. Rietman

  4. Mechanical and Industrial Engineering Department, University of Massachusetts, Amherst, MA, USA

    Edward A. Rietman

  5. Department of Physics, University of Alberta, Edmonton, AB, Canada

    Jack A. Tuszynski

  6. Department of Oncology, University of Alberta, Edmonton, AB, Canada

    Jack A. Tuszynski

  7. DIMEAS, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin, Italy

    Jack A. Tuszynski

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  1. Stefan M. Golas
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  2. Amber N. Nguyen
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  3. Edward A. Rietman
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  4. Jack A. Tuszynski
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Contributions

EAR and JAT conceived and designed the study. SMG and ANN carried out the computations. All authors contributed to the analysis and to the writing of the manuscript.

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Correspondence to Jack A. Tuszynski.

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Golas, S.M., Nguyen, A.N., Rietman, E.A. et al. Gibbs free energy of protein-protein interactions correlates with ATP production in cancer cells. J Biol Phys 45, 423–430 (2019). https://doi.org/10.1007/s10867-019-09537-1

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  • DOI: https://doi.org/10.1007/s10867-019-09537-1

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