American Institute of Mathematical Sciences

Advanced
2015, 12(6): 1277-1288. doi: 10.3934/mbe.2015.12.1277

Oncogene-tumor suppressor gene feedback interactions and their control

Baltazar D. Aguda 1, , Ricardo C.H. del Rosario 2, and  Michael W.Y. Chan 3,

1. 

DiseasePathways LLC, Bethesda, Maryland, 20814, United States
2. 

Computational and Systems Biology, Genome Institute of Singapore, 60 Biopolis St., #02-01 Genome, 138672, Singapore
3. 

Department of Life Science & Institute of Molecular Biology, National Chung Cheng University, Min-Hsiung, China-Yi, Taiwan

Received  September 2014 Revised  March 2015 Published  August 2015

We propose the hypothesis that for a particular type of cancer there exists a key pair of oncogene (OCG) and tumor suppressor gene (TSG) that is normally involved in strong stabilizing negative feedback loops (nFBLs) of molecular interactions, and it is these interactions that are sufficiently perturbed during cancer development. These nFBLs are thought to regulate oncogenic positive feedback loops (pFBLs) that are often required for the normal cellular functions of oncogenes. Examples given in this paper are the pairs of MYC and p53, KRAS and INK4A, and E2F1 and miR-17-92. We propose dynamical models of the aforementioned OCG-TSG interactions and derive stability conditions of the steady states in terms of strengths of cycles in the qualitative interaction network. Although these conditions are restricted to predictions of local stability, their simple linear expressions in terms of competing nFBLs and pFBLs make them intuitive and practical guides for experimentalists aiming to discover drug targets and stabilize cancer networks.
Keywords: p53, kras, miR-17-92, drug targets., ink4a, feedback loops, network stability, e2f1, cycle strength, myc, Oncogene-tumor suppressor gene pairs.
Mathematics Subject Classification: Primary: 92B05, 92C42; Secondary: 34C2.
Citation: Baltazar D. Aguda, Ricardo C.H. del Rosario, Michael W.Y. Chan. Oncogene-tumor suppressor gene feedback interactions and their control. Mathematical Biosciences & Engineering, 2015, 12 (6) : 1277-1288. doi: 10.3934/mbe.2015.12.1277
References:
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[28]

K. Tago, M. Funakoshi-Tago, H. Itoh, Y. Furukawa, J. Kikuchi, T. Kato, K. Suzuki and K. Yanagisawa, Arf tumor suppressor disrupts the oncogenic positive feedback loop including c-Myc and DDX5,, Oncogene, 34 (2015), 314.  doi: 10.1038/onc.2013.561.  Google Scholar

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P. Takahashi, A. Polson and D. Reisman, Elevated transcription of the p53 gene in early S-phase leads to a rapid DNA-damage response during S-phase of the cell cycle,, Apoptosis, 16 (2011), 950.  doi: 10.1007/s10495-011-0623-z.  Google Scholar

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show all references

References:
[1]

B. D. Aguda, Network pharmacology of glioblastoma,, Curr Drug Discov Technol., 10 (2013), 125.   Google Scholar

[2]

B. D. Aguda, The significance of the feedback loops between KRas and Ink4a in pancreatic cancer,, in Molecular Diagnostics and Therapy of Pancreatic Cancer (ed. A. Azmi), (2014), 281.  doi: 10.1016/B978-0-12-408103-1.00012-1.  Google Scholar

[3]

B. D. Aguda and A. B. Goryachev, From pathways databases to network models of switching behavior,, PLoS Comput Biol., 3 (2007), 1674.  doi: 10.1371/journal.pcbi.0030152.  Google Scholar

[4]

B. D. Aguda, Y. Kim, H. S. Kim, A. Friedman and H. A. Fine, Qualitative network modeling of the Myc-p53 control system of cell proliferation and differentiation,, Biophys J., 101 (2011), 2082.  doi: 10.1016/j.bpj.2011.09.052.  Google Scholar

[5]

B. D. Aguda, Y. Kim, M. G. Piper-Hunter, A. Friedman and C. B. Marsh, MicroRNA regulation of a cancer network: Consequences of the feedback loops involving miR-17-92, E2F and Myc,, Proc Natl Acad Sci USA, 105 (2008), 19678.  doi: 10.1073/pnas.0811166106.  Google Scholar

[6]

R. C. Bast, B. Henessy and G. B. Mills, Jr., The biology of ovarian cancer: New opportunities for translation,, Nat Rev Cancer, 9 (2009), 415.   Google Scholar

[7]

Cancer Genome Atlas Research Network, Comprehensive genomic characterization defines human glioblastoma genes and core pathways,, Nature, 494 (2013).  doi: 10.1038/nature11903.  Google Scholar

[8]

Cancer Genome Atlas Research Network, Comprehensive molecular profiling of lung adenocarcinoma,, Nature, 511 (2014), 543.   Google Scholar

[9]

W. A. Cooper, D. C. Lam, S. A. O'Toole and J. D. Minna, Molecular biology of lung cancer,, J Thorac Dis., 5 (2013).   Google Scholar

[10]

J. Daniluk, Y. Liu, D. Deng, J. Chu, H. Huang, S. Gaiser, Z. Cruz-Monserrate, H. Wang, B. Ji and C. D. Logsdon, An NF-$\kappa$B pathway-mediated positive feedback loop amplifies Ras activity to pathological levels in mice,, J Clin Invest., 122 (2012), 1519.   Google Scholar

[11]

A. Dhooge, W. Govaerts and Y. A. Kuznetsov, MATCONT: A Matlab package for numerical bifurcation analysis of ODEs,, ACM Trans Math Softw (TOMS), 29 (2003), 141.  doi: 10.1145/779359.779362.  Google Scholar

[12]

J. Drost and R. Agami, Transformation locked in a loop,, Cell, 139 (2009), 654.  doi: 10.1016/j.cell.2009.10.035.  Google Scholar

[13]

P. A. Futreal, L. Coin, M. Marshall, T. Down, T. Hubbard, R. Wooster, N. Rahman and M. R. Stratton, A census of human cancer genes,, Nat Rev Cancer, 4 (2004), 177.  doi: 10.1038/nrc1299.  Google Scholar

[14]

P. K. Ha, S. S. Chang, C. A. Glazer, J. A. Califano and D. Sidransky, Molecular techniques and genetic alterations in head and neck cancer,, Oral Oncol, 45 (2009), 335.  doi: 10.1016/j.oraloncology.2008.05.015.  Google Scholar

[15]

http://cancer.sanger.ac.uk/cancergenome/projects/census/" target="_blank"> Google Scholar

[16]

http://ncg.kcl.ac.uk, (network of cancer genes)., ().   Google Scholar

[17]

C. Kandoth, M. D. McLellan, F. Vandin, K. Ye, B. Niu, C. Lu, M. Xie, Q. Zhang, J. F. McMichael, M. A. Wyczalkowski, M. D. Leiserson, C. A. Miller, J. S. Welch, M. J. Walter, M. C. Wendl, T. J. Ley, R. K. Wilson, B. J. Raphael and L. Ding, Mutational landscape and significance across 12 major cancer types,, Nature, 502 (2013), 333.   Google Scholar

[18]

J. E. Larsen and J. D. Minna, Molecular biology of lung cancer: Clinical applications,, Clin Chest Med., 32 (2011), 703.  doi: 10.1016/j.ccm.2011.08.003.  Google Scholar

[19]

E. Y. Lee and W. J. Muller, Oncogenes and tumor suppressor genes,, Cold Spring Harb Perpect Biol., 2 (2010).  doi: 10.1101/cshperspect.a003236.  Google Scholar

[20]

Y. Li, Y. Li, H. Zhang and Y. Chen, MicroRNA-mediated positive feedback loop and optimized bistable switch in a cancer network involving miR-17-92,, PLoS One, 6 (2011).  doi: 10.1371/journal.pone.0026302.  Google Scholar

[21]

P. Liao, W. Wang, M. Shen, W. Pan, K. Zhang, R. Wang, T. Chen, Y. Chen, H. Chen and P. Wang, A positive feedback loop between EBP2 and c-Myc regulates rDNA transcription, cell proliferation, and tumorigenesis,, Cell Death Dis., 5 (2014).  doi: 10.1038/cddis.2013.536.  Google Scholar

[22]

L. Mao, W. K. Hong and V. A. Papadimitrakopoulou, Focus on head and neck cancer,, Cancer Cell, 5 (2004), 311.  doi: 10.1016/S1535-6108(04)00090-X.  Google Scholar

[23]

G. M. Marshall, P. Y. Liu, S. Gherardi, C. J. Scarlett, A. Bedalov, N. Xu, N. Iraci, E. Valli, D. Ling, W. Thomas, M. van Bekkum, E. Sekyere, K. Jankowski, T. Trahair, K. L. Mackenzie, M. Haber, M. D. Norris, A. V. Biankin, G. Perini and T. Liu, SIRT1 promotes N-Myc oncogenesis through a positive feedback loop involving the effects of MKP3 and ERK on N-Myc protein stability,, PLoS Genet., 7 (2011).  doi: 10.1371/journal.pgen.1002135.  Google Scholar

[24]

K. Nowak, K. Kerl, D. Fehr, C. Kramps, C. Gessner, K. Killmer, B. Samans, B. Berwanger, H. Christiansen and W. Lutz, BMI1 is a target gene of E2F-1 and is strongly expressed in primary neuroblastomas,, Nucleic Acids Res., 34 (2006), 1745.  doi: 10.1093/nar/gkl119.  Google Scholar

[25]

B. Perez-Ordoñez, M. Beauchemin and R. C. Jordan, Molecular biology of squamous cell carcinoma of the head and neck,, J Clin Pathol., 59 (2006), 445.   Google Scholar

[26]

C. C. Pritchard and W. M. Grady, Colorectal cancer molecular biology moves into clinical practice,, Gut., 60 (2011), 116.  doi: 10.1136/gut.2009.206250.  Google Scholar

[27]

T. Santarius, J. Shipley, D. Brewer, M. R. Stratton and C. S. Cooper, A census of amplified and overexpressed human cancer genes,, Nat Rev Cancer, 10 (2010), 59.  doi: 10.1038/nrc2771.  Google Scholar

[28]

K. Tago, M. Funakoshi-Tago, H. Itoh, Y. Furukawa, J. Kikuchi, T. Kato, K. Suzuki and K. Yanagisawa, Arf tumor suppressor disrupts the oncogenic positive feedback loop including c-Myc and DDX5,, Oncogene, 34 (2015), 314.  doi: 10.1038/onc.2013.561.  Google Scholar

[29]

P. Takahashi, A. Polson and D. Reisman, Elevated transcription of the p53 gene in early S-phase leads to a rapid DNA-damage response during S-phase of the cell cycle,, Apoptosis, 16 (2011), 950.  doi: 10.1007/s10495-011-0623-z.  Google Scholar

[30]

D. Tamborero, A. Gonzalez-Perez, C. Perez-Llamas, J. Deu-Pons, C. Kandoth, J. Reimand, M. S. Lawrence, G. Getz, G. D. Bader, L. Ding and N. Lopez-Bigas, Comprehensive identification of mutational cancer driver genes across 12 tumor types,, Sci Rep., 3 (2013).  doi: 10.1038/srep02650.  Google Scholar

[31]

M. Vauhkonen, H. Vauhkonen and P. Sipponen, Pathology and molecular biology of gastric cancer,, Best Pract Res Clin Gastroenterol, 20 (2006), 651.  doi: 10.1016/j.bpg.2006.03.016.  Google Scholar

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