Dynamics of p53 and NF-κB regulation in response to DNA damage and identification of target proteins suitable for therapeutic intervention

Abstract

BackgroundThe genome is continuously attacked by a variety of agents that cause DNA damage. Recognition of DNA lesions activates the cellular DNA damage response (DDR), which comprises a network of signal transduction pathways to maintain genome integrity. In response to severe DNA damage, cells undergo apoptosis to avoid transformation into tumour cells, or alternatively, the cells enter permanent cell cycle arrest, called senescence. Most tumour cells have defects in pathways leading to DNA repair or apoptosis. In addition, apoptosis could be counteracted by nuclear factor kappa B (NF-κB), the main anti-apoptotic transcription factor in the DDR. Despite the high clinical relevance, the interplay of the DDR pathways is poorly understood. For therapeutic purposes DNA damage signalling processes are induced to induce apoptosis in tumour cells. However, the efficiency of radio- and chemotherapy is strongly hampered by cell survival pathways in tumour cells. In this study logical modelling was performed to facilitate understanding of the complexity of the signal transduction networks in the DDR and to provide cancer treatment options.ResultsOur comprehensive discrete logical model provided new insights into the dynamics of the DDR in human epithelial tumours. We identified new mechanisms by which the cell regulates the dynamics of the activation of the tumour suppressor p53 and NF-κB. Simulating therapeutic intervention by agents causing DNA single-strand breaks (SSBs) or DNA double-strand breaks (DSBs) we identified candidate target proteins for sensitization of carcinomas to therapeutic intervention. Further, we enlightened the DDR in different genetic diseases, and by failure mode analysis we defined molecular defects putatively contributing to carcinogenesis.ConclusionBy logic modelling we identified candidate target proteins that could be suitable for radio- and chemotherapy, and contributes to the design of more effective therapies.

Dynamic aberrant NF-κB spurs tumorigenesis: A new model encompassing the microenvironment

“…One of them is a higher mutation rate in the later stages [94]; this is consistent with dysregulation of the p53 network that normally links cell survival to genetic integrity [95]. As p53 interacts with RelA [71] dysregulation of the p53 network leads to the question if RelA targets are overexpressed in cancer [96], and which molecular mechanisms mediate their effects on the microenvironment [97].…”

Synergistic DNA-damaging effect in multiple myeloma with the combination of zalypsis, bortezomib and dexamethasone

“…10 In our studies, according to this hypothesis, dexamethasone and, in particular, zalypsis increased the nuclear translocation of NF-κB, indicating a potential mechanism of resistance to these agents, while bortezomib induced a decrease in this translocation. Though attenuated, this resistance mechanism was still present in both doublets containing bortezomib (ZaB and BDe).…”

“…The apoptotic induction after DNA damage can be counteracted by the activation of NF-κB, 16 a heterodimer composed of p50 and p65 subunits, which is the main pro-survival transcription factor in the DDR. 10 Our results suggest that the nuclear translocation of NF-κB induced by zalypsis and dexamethasone could be a potential mechanism of resistance to these compounds. The addition of the proteasome inhibitor bortezomib partially reverted this mechanism in double combinations and, most interestingly, was completely overcome in the triple combination.…”

Monomials and Basin Cylinders for Network Dynamics

“…Several examples from current literature on protein and gene interaction models are presented, including an example on inducing apoptosis in a cancer cell, showing the methods to be practical on real examples with up to fifteen nodes. Future problems are to extend the methods and algorithms to larger networks of dozens of nodes such as the p 53 network in [31] as well as dynamical models on aging and Alzheimer’s disease (for example [5], [9], [18], [25]).…”

“…The attracting set may have practical importance, such as a state of “apoptosis” in which a cancer cell is eliminated [36]. A recent use of the Boolean model is to help identify therapeutic interventions [23], [24], [31], [32]. By this is meant a configuration or assignment of values to a subset of nodes which guarantees that the network will terminate in a specific desirable attractor.…”