- Research article
- Open Access
Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway
© Orton et al; licensee BioMed Central Ltd. 2009
- Received: 13 May 2009
- Accepted: 5 October 2009
- Published: 5 October 2009
The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway.
We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors.
Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems.
- Epidermal Growth Factor Receptor
- Nerve Growth Factor
- Epidermal Growth Factor Receptor Mutation
- Epidermal Growth Factor Receptor Signalling
- Nerve Growth Factor Receptor
A common cell line used to investigate ERK signalling from growth factor receptors is the PC12 (rat pheochromocytoma) cell line. In PC12 cells, EGF stimulates a strong but transient activation of ERK, peaking at ~5 mins and returning to basal levels at ~30 mins, which leads to cellular proliferation [8, 9]. In contrast, Nerve Growth Factor (NGF) stimulates a sustained activation of ERK leading to the neuronal differentiation of PC12 cells [8, 9]. There is now compelling evidence that the duration of the ERK signal governs whether PC12 cells proliferate or withdraw from the cell cycle and differentiate into a neuronal phenotype [9, 10]. Although the PC12 system has been well studied, it is still unclear how different ERK signal dynamics can be robustly controlled by different upstream receptors utilising the same pathway. However, there are currently a number of theories such as differences in the strength of feedback loops between receptor systems [11, 12] and differences in the adaptor proteins that can bind to the receptor to initiate the ERK pathway . Numerous other growth factor receptors (such as the Insulin, Fibroblast, and Platelet-Derived receptors) also use this same ERK pathway to generate different signals and different cellular responses. Therefore, an understanding of the critical differences between the receptor systems and how they utilise the same pathway to generate different responses would be a major advance.
Alterations in the cellular genome affecting the expression or function of genes controlling cell growth are considered to be the main cause of cancer . Common alterations include mutations to the Ras and B-Raf proteins as well as mutation or overexpression of the EGFR, which all lead to the constitutive activation of ERK. Approximately 30 % of all human cancers contain a mutation to one of the ras oncogenes (Ki-ras, Ha-ras, N-ras) that causes the resulting protein to be constitutively active . A constitutively active Ras is able to continually activate Raf kinases and therefore MEK which subsequently results in the constitutive activation of ERK and uncontrolled cellular proliferation. Constitutively active Ras is typically caused by mutations that prevent GTP hydrolysis, thus locking Ras in a permanent 'on' state. One of the most common Ras mutations is a glycine to valine mutation at residue 12 (RasV12) which renders Ras insensitive to inactivation by Ras-GAP and thus locked in the 'on' state. Somatic missense mutations of B-Raf have been reported in 66 % of malignant melanomas and at lower frequencies in a wide range of other human cancers . By far the most common mutation is a single substitution of glutamic acid to valine at residue 600 (B-RafV600E) which greatly elevates the kinase activity of B-Raf and results in the constitutive activation of ERK in vivo, independent of Ras .
Mutations, deletions and overexpression resulting in constitutive activation of EGFR have long been associated with various types of cancer . The most common mutation of the EGFR found in human cancer is EGFRvIII which has been found in more than 50 % of high and low grade gliomas  and in 21 of 27 breast carcinomas [17, 18], amongst others. EGFRvIII can be caused by intragene rearrangements or alternative splicing resulting in the loss of domains I and II from the extracellular domain. EGFRvIII has a constitutively activated tyrosine kinase which results in the phosphorylation of receptor tyrosine residues and the continual recruitment of adaptor proteins, and subsequently the constitutive activation of ERK and uncontrolled cellular proliferation, independent of ligand interaction. It has also been shown that EGFRvIII is not internalised , thus avoiding the receptor degradation pathway, and is often amplified resulting in overexpression [17, 20]. Another EGFR deletion is EGFRvI which is a total deletion of the extracellular domain resulting in a constitutively active EGFR which resembles the v-erb-B oncoprotein [20, 21]. Gene amplification of the EGFR gene has also been observed in a number of different tumours and found to be present in ~40 % glioblastoma multiforme . Overexpression of EGFR was also frequently observed in breast, bladder, cervix, kidney, and ovarian tumours  as well as in lung cancer and various squamous carcinomas . Overexpression results in a greatly increased number of receptors on the cell membrane. This means that receptors randomly bump into each other with high frequency enabling them to dimerise and auto-phosphorylate in the absence of ligand and thus leads to the constitutive activation of the ERK pathway; although these receptors are degraded along the normal degradation pathway , they would be quickly replenished due to the overexpression.
Over recent years the computational modelling of biological systems has become increasingly valuable and there are now a wide variety of models of the ERK pathway available which have led to some novel insights and interesting predictions as to how this system functions . Early models of the ERK pathway were focussed on investigating the properties and behaviour of the core cascade itself. For example,  showed that the ERK cascade exhibited ultrasensitivity whilst [26, 27] showed that the activating dual phosphorylation of ERK was accomplished via a two-collision distributive mechanism. Nowadays, models routinely incorporate receptors and the plethora of adaptor proteins which can bind to them and activate the core ERK cascade. These models have been used to investigate various aspects of the biological behaviour of this system such as the role of negative feedback  and receptor internalisation  as well as the temporal dynamics of activation by different receptors [29, 30].
In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on signalling through the ERK pathway. We have generated a new model of the EGF activated ERK pathway which was based on a previously published model by  and has been verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations causing constitutive activation, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our results suggest that different routes to ERK activation are being utilised in different cancerous situations, which therefore has interesting implications for drug selection strategies. Furthermore, our model also highlights the importance of receptor degradation in normal EGF signalling, and suggests that receptor degradation is a key difference between the signalling from different growth factor receptors - specifically the EGF and NGF receptors. Detailed information on the model as well as our analysis results is presented below.
In this study, we were interested in investigating what effects various cancerous alterations had on signalling through the EGF activated ERK pathway. Initially, we took the original Brown EGF model (downloaded from BioModels ) and investigated what effects introducing a Ras or an EGFR mutation had on ERK signalling (Figure 2a); to accomplish this, the software tool COPASI  was used for the construction, simulation and analysis of models. Under normal conditions, the original Brown model correctly predicts that EGF stimulates the transient activation of ERK (Figures 2b). Furthermore, when Ras is mutated causing it to be constitutively active, the model correctly predicts that ERK is also constitutively activated (Figure 2b). However, when EGFR is mutated causing it to be constitutively active, the Brown model incorrectly predicts that ERK is only transiently activated (Figure 2b). This is certainly incorrect because, as described above, mutations in EGFR that cause it to be constitutively active are well known to lead to the constitutive activation of ERK and to the subsequent development of cancer. After brief investigations, we found that the reason for this incorrect prediction was that the negative feedback loop from active ERK to SOS (via p90Rsk) is very strong and rapidly shuts down the Ras to ERK signalling pathway, resulting in only a transient activation of ERK despite the constitutive activation of EGFR. Deleting the SOS feedback loop from the model results in a sustained activation of ERK after normal EGF stimulation which suggests that it is the key process involved in terminating the signal from the EGF receptor in the Brown model (Figure 2c); in contrast, deleting the Akt to Raf-1 feed-forward loop has little effect on the ERK signal (Figure 2c). The ERK to SOS negative feedback loop has been well characterised [3–7, 33] and there is therefore little doubt that it does exist. However, our results here strongly suggest that due to this feedback loop, an alternative to the SOS-Ras-Raf-1 pathway must exist in order for mutated EGFR to constitutively activate ERK. In addition, making EGFR constitutively active made little difference to the model behaviour because, in the Normal Brown EGF model, all of the receptors are very rapidly activated by EGF and they remain activated because the degradation of receptors is not taken into account. Thus, all normal EGFR are essentially constitutively active after stimulation with EGF and hence there is little difference between the normal and EGFR mutation model simulations. This highlights the potential importance of the process of receptor degradation, as without it normal EGFR receptors remain constitutively active.
One interesting point is that the SOS negative feedback loop is no longer essential for efficient signal shutdown and the transient activation of ERK, as deleting it has only a slight effect on the ERK signal (Figure 4c). Instead, receptor degradation is now the key factor in signal termination as deleting the process of receptor degradation results in the sustained activation of ERK (Figure 4c). This is a decisive improvement over the original Brown EGF model, where the SOS negative feedback loop was found to be essential for signal termination and the transient response (Figure 2c), as receptor degradation was not considered. In our model, receptor degradation is now essential because there is no negative feedback loop present on the C3G/Rap1/B-Raf pathway so the signal has to be shutdown at the receptor level to achieve a transient response, which makes the process of receptor degradation essential. This has interesting and important implications for signalling from other growth factor receptors which are discussed further in the next section.
A sensitivity analysis of the EGFR model was also performed to identify the reactions that have the most influence on the ERK signal (see Additional file 2, Figure S6; and see Additional file 3 for model parameter values and sources). Overall, reactions contained within the Rap1 pathway were found to be more sensitive than the corresponding reactions in the Ras pathway. This is to be expected given that the Ras pathway is contained within a strong negative feedback loop, thus reducing the sensitivities of the reactions contained within the loop. However, although less sensitive, the Ras pathway is still a key feature of the EGFR system. This is illustrated in the knockout plots in Figure 4d, as knocking out Ras has a greater effect on the peak of the ERK signal than knocking out Rap1. This again highlights the fact that the normal EGFR system utilises both of the pathways to relay its signal. The sensitivity analysis also highlighted EGF receptor degradation as one of the most sensitive reactions in the model. This further highlights the importance of the process of receptor degradation in addition to the knockout experiments in Figure 4c.
Our final model alteration was to investigate the effects of overexpressing the EGFR which is also a known cause of cancer. To accomplish this, the rate of receptor production was increased 100 fold to represent the increased transcription and translation of receptors. Rather than directly representing random receptor dimerisation, we simply stimulated the overexpressed receptors with EGF and analysed the differences between the normal and overexpressed systems; this is akin to the experimental strategy employed by  who ovexpressed EGFR in PC12 cells and subsequently stimulated them with EGF to investigate the effects of overexpression. The results from this experiment were extremely similar to those obtained in the EGFR mutation experiment, and therefore the simulation plots have been moved to Additional file 2 (Figure S4) as they are almost identical to the plots in Figure 6a and 6b. The overexpressed system resulted in the constitutive activation of ERK because the increased rate of receptor production counteracted the activated receptor degradation pathway, which resulted in a stable level of activated receptors on the cell membrane and the constitutive activation of the ERK pathway. Similar to the mutated EGFR receptors, the overexpressed receptors signalled predominantly via the C3G/Rap1/B-Raf as knocking out Ras or Raf-1 had little effect on the constitutive activation of ERK, whereas knocking out Rap1 of B-Raf had dramatic effects with active ERK levels falling to almost basal levels. Again, this was found to be due to the ERK to SOS (via P90Rsk) negative feedback loop shutting down the Ras pathway, and therefore implies that in cancerous situations of EGFR overexpression as well as EGFR mutation, drugs should target the Rap1 rather than Ras pathway.
Our models predict that the oncogenic EGFR signal passes almost exclusively via the Rap1 pathway and therefore predicts that drugs must target this pathway in order to effectively treat such cancers. Furthermore, our models predict that the key factor in oncogenic EGFR signalling is the ability to bypass or compensate for receptor degradation. When the receptor is overexpressed, activated receptors are still degraded but they are being constantly replenished due to the overexpression which means that there is a consistently high number of activated receptors on the membrane capable of constitutively activating the Rap1 pathway and therefore ERK. Whereas, mutated EGFR are not recognised as being active by the normal cellular machinery and are therefore not degraded which means that they too can constitutively activate the Rap1 pathway and ERK. Therefore, our model suggests that a drug capable of increasing the rate of EGFR degradation or capable of somehow tagging mutated EGFRs for degradation could also be a useful developments in cancer treatment.
Comparison of Growth Factor Signalling
As described previously, our normal EGF model predicts that receptor degradation is the key process involved in signal termination and achieving only a transient activation of ERK after EGF stimulation; if the process of receptor degradation is deleted from the EGF model, a sustained ERK signal is observed (Figure 4c) and the sensitivity analysis identified it as one of the most sensitive reactions (see Additional file 2, Figure S6). This in itself is a novel prediction from our model, which to the best of our knowledge has not been reported previously. Indeed, most existing computational models of the EGF activated ERK pathway, including the original Brown model, do not include receptor degradation [11, 29, 38] or predict that it is not necessary for signal termination [28, 33]. However, this also has wider implications with respect to ERK signalling from different growth factor receptors, and in particular could explain the differences between EGF and NGF signalling. In PC12 cells, EGF stimulates a transient activation of ERK whereas NGF stimulates a sustained activation of ERK, but it is still currently unclear how these different ERK signal dynamics can be robustly controlled by different upstream receptors utilising the same pathway. One of the known differences between the EGF and the NGF receptor systems is that whilst the EGFR is rapidly degraded, the NGF receptor TrkA is not degraded and remains active . Our model predicts that it is this difference in receptor degradation that is the key difference between the two receptor systems. This can be investigated further by deleting the process of receptor degradation from our EGF model to generate a realistic model of the NGF receptor TrkA system.
As can be seen in Figures 8, the process of receptor degradation is essential to achieve a transient response in the EGFR system whilst the SOS feedback loop is redundant, as removing it has little effect on the transient ERK signal dynamics (Figure 8A, B). In contrast, the SOS feedback loop is essential to achieve a transient response in the Insulin system (Figure 8C, D). This is because Insulin receptors are not degraded, therefore the only way to achieve a transient signal is via the SOS feedback loop to shutdown the Ras pathway. Another key to the transient signal achieved via Insulin stimulation, is the fact that the Insulin receptor is unable to utilise the Rap1 pathway, which does not contain a feedback loop. If the Insulin receptor were able to utilise this pathway a sustained signal would surely be observed. Indeed, as can be seen for the NGF receptor TrkA a sustained ERK signal is indeed observed as the TrkA receptor is not degraded and is able to utilise the Rap1 pathway (Figure 9A, B). One interesting point, is that the NGF receptor system is in fact very similar to the mutated EGFR system as both systems contain receptors that are not degraded, both can utilise the Ras and Rap1 pathways, and both result in a sustained ERK signal (Figure 9C, D). As discussed previously, the key to cancerous signalling from the EGF receptor is the ability to bypass or compensate for the process of receptor degradation. In the case of overexpressed EGFR, the process of receptor degradation is compensated for by the increased rate of production of new EGF receptors. Combining all of the above leads to the prediction that, if the only real difference between EGF and NGF receptors is indeed receptor degradation, a PC12 cell that is stimulated with EGF and has overexpressed EGFR should result in a sustained ERK signal and neuronal differentiation, not cellular proliferation. Interestingly, this prediction from our model has already been validated in a seminal experimental by  who overexpressed EGFR in PC12 cells and observed sustained ERK as well as neuronal differentiation. Therefore, this further backs up our models and predictions about receptor degradation being a critical process and a key difference between the receptor systems.
In summary, the critical difference between the EGF and the NGF systems is receptor degradation, with the EGF receptor being rapidly degraded after stimulation and therefore only generating a transient ERK signal, whilst the NGF receptor TrkA is not degraded and generates a sustained ERK signal. Whereas, the critical difference between the Insulin and the NGF systems (both of which are not degraded) is the Rap1 pathway, with the NGF receptor TrkA being able to utilise it to generate a sustained ERK signal, whilst the Insulin receptor is unable to utilise it and can only use the Ras pathway which is rapidly shutdown via the SOS feedback loop and therefore only generate a transient ERK signal. As the insulin receptor is not degraded, this makes the SOS feedback loop essential for signal termination and generating only a transient ERK signal . Whereas, as the EGF receptor is degraded, the SOS feedback loop is redundant under EGF signalling and not required for signal termination. Overall, our results suggest that the ERK pathway has evolved to be utilised by numerous upstream receptors and that the differences between ERK signalling from different growth factor receptors seem to be large scale, with entire processes (such as receptor degradation) or entire pathways (such as the Rap1 pathway) being either present or absent, rather than subtle differences in the kinetics of protein binding or activation.
In our previous work, we already showed through modelling and experimental validation that the SOS feedback loop was not required for efficient signal termination and the transient activation of ERK induced by EGF . However, as we did not consider the Rap1 pathway in this model, we incorrectly hypothesised that receptor degradation could also be redundant as the SOS feedback loop could compensate for its absence. We drew parallels to the Insulin receptor system which lacked receptor degradation, and where the SOS feedback loop had previously been shown experimentally to be essential for signal termination and generating a transient ERK response [4, 33]. Although the work presented here does not affect our previous conclusions, it does take our previous work another step forward by considering the Rap1 pathway to show that although the SOS feedback loop is indeed redundant, the process of receptor degradation is actually essential in EGF signalling. This highlights the fact that models, like our biological understanding of the pathway itself, can evolve over time and be used to suggest interesting new hypotheses and explanations for the observed data that challenge our current understanding.
In this study, we used computational modelling techniques to investigate what effects various cancerous alterations had on signalling through the EGF activated ERK pathway. We initially introduced a number of cancerous mutations into the original EGF model developed by  but found that the model incorrectly predicted the effects of an EGFR mutation due to the fact that the model was incomplete (Figure 2b). We therefore constructed a new model of the EGF activated ERK pathway by taking the original Brown EGF model and expanding it to include receptor production and degradation as well as the C3G/Rap1/B-Raf pathway, which we believed were important processes in both normal EGF and cancerous signalling. This model expansion was informed by the scientific literature, and in particular the study by  which is one of the most comprehensive and up-to-date studies of the EGF and NGF activated ERK pathway. We used our new model to investigate the effects of cancerous mutations and what the best drug targets would be, as well as using the model to conduct a comparison of different growth factor receptors, and as a result we have generated a number of interesting and novel predictions.
Our model predicts that the oncogenic EGFR signal passes almost exclusively via the Rap1 pathway and therefore predicts that drugs must target this pathway in order to effectively treat such cancers. Furthermore, our models predict that the key factor in oncogenic EGFR signalling is the ability to bypass or compensate for receptor degradation. When the receptor is overexpressed, activated receptors are still degraded but they are being constantly replenished due to the overexpression which means that there is a consistently high number of activated receptors on the membrane capable of constitutively activating the Rap1 pathway and therefore ERK. Whereas, mutated EGFR are not recognised as being active by the normal cellular machinery and are therefore not degraded which means that they too can constitutively activate the Rap1 pathway and ERK. Therefore, our model suggests that a drug capable of increasing the rate of EGFR degradation or capable of somehow tagging mutated EGFRs for degradation could be a useful developments in cancer treatment.
Our model predicts that normal EGFR signalling results in a transient ERK signal due to receptor degradation, NGF signalling results in a sustained ERK signal (via the Rap1 pathway) as there is no degradation of the TrkA receptor, and cancerous EGFR signalling results in a constitutive/sustained ERK signal (via the Rap1 pathway) because receptor degradation is either abolished or counteracted (Figure 8). Overall, this highlights the importance of the Rap1 pathway in both normal and oncogenic EGFR signalling as well as in NGF signalling. The key feature of the Rap1 pathway is that it lacks a negative feedback loop, and will therefore keep signalling if the receptor remains active; however, it should be noted that although there is no negative feedback loop currently known, one can never rule out the possibility of one being identified in the future. Furthremore, our models predict that the key difference between the EGF and NGF receptor systems is receptor degradation. The behaviour of these two receptor systems in PC12 cells has long fascinated many researchers and our simple prediction appears to be both novel and effectively explain how the two receptor systems are able to utilise the same pathway to achieve different cellular responses. Interestingly, the ERK to SOS (via P90Rsk) negative feedback loop appears to be irrelevant in both EGF and NGF signalling, therefore one may wonder why the SOS feedback loop is even there. However, the SOS feedback loop is essential for a transient ERK response to be achieved in systems such as the insulin receptor, which are not degraded and can not utilise the Rap1 pathway (Figure 8). Overall, our results suggest that the ERK pathway has evolved to be utilised by numerous upstream receptors and that the differences between ERK signalling from different growth factor receptors seem to be large scale, with entire processes (such as receptor degradation) or entire pathways (such as the Rap1 pathway) being either present or absent, rather than subtle differences in the kinetics of protein binding or activation. Therefore, as the differences between receptor systems are essentially structural, this could suggest that more qualitative modelling techniques such as Petri-Nets [39, 40] or logical process algebras [41, 42], which are more traditional tools for analysing model structure, could play important roles in the analysis and comparison of signal transduction pathways. Furthermore, as the different growth factor receptor systems appear to be so similar, this suggests that a model of one growth factor receptor systems could be readily applied to another receptor system with relatively simple modifications. Indeed, in this study we created a model of the NGF receptor based on the EGF receptor model as well as drawing comparisons to the RET receptor, and previously we created a model of the insulin receptor based on a model of the EGF receptor . However, the ERK pathway is not the only pathway initiated by growth factor receptors and as different receptors eventually lead to different biological responses, models will need to evolve in the future to include these alternative adaptor proteins and pathways, and ultimately their influence on gene expression.
A recent study by  suggested that a critical difference between the EGF and NGF systems was that a negative feedback loop existed between Raf-1 and ERK under EGF, but under NGF this was transformed into a positive feedback loop resulting in the sustained activation of ERK via Raf-1. However, studies by [9, 43], which we have used to inform our model, showed that the sustained ERK signal from NGF stimulation is a result of Rap1/B-Raf activity, and that Ras/Raf-1 is only used transiently under NGF. The EGF vs NGF phenomenon in PC12 cells has long fascinated many researchers and has been well studied, but it is still unclear exactly how different ERK signal dynamics can be robustly controlled by different upstream receptors utilising the same pathway, especially given such differing data. It is important to note here, that we are not implying that our model and the data we have used should be trusted more than any others. Rather we are implying that our model offers an interesting and alternative explanation for the observed data, we have been able to expand our model out from the traditional EGF vs NGF system to incorporate cancerous mutations as well as other growth factor receptors, and importantly we have made a number of interesting predictions which we have been able to validate through existing experimental results in the scientific literature. Only time and further laboratory data can tell which models and hypotheses are truly correct, if any, but it is important to remember that all models are simplifications of the true real-life situation, and therefore any predictions from them should be treated with some caution. In the words of George E. P. Box, "Essentially, all models are wrong, but some are useful" .
In conclusion, this study has shown how computational models can be useful tools for investigating and comparing the biological behaviour of signal transduction pathways as they can suggest new hypotheses to explain the observed biological data and help understand the dynamics of how the pathway functions. Furthermore, computational models can be readily used to investigate different disease states and suggest how drug treatment could be improved to better combat the effects of the disease. Ultimately, the behaviour of computational models needs to be validated with experimental data from the laboratory so that any predictions made from them can be trusted. Therefore, we have validated the behaviour of our model with our own as well as published experimental data and have found supporting evidence for our predictions in the scientific literature. We therefore believe that our model is a good representation of the EGF activated ERK pathway which can be expanded and applied in the future to further investigate the dynamics and functioning of growth factor receptor signalling.
This work was funded by the Department of Trade and Industry (DTI), under their Bioscience Beacon project programme. AG was funded by an industrial PhD studentship from Scottish Enterprise and Cyclacel.
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