Cancer is the second leading cause of death globally, and colorectal cancer (CRC) is among the five most common cancers. The small GTPase KRAS is an oncogene that is mutated in~30% of all CRCs. Pharmacological treatments of CRC are currently unsatisfactory, but much hope rests on network-centric approaches to drug development and cancer treatment. These approaches, however, require a better understanding of how networks downstream of Ras oncoproteins are connected in a particular tissue contexthere colon and CRC. Previously we have shown that competition for binding to a 'hub' protein, such as Ras, can induce a rewiring of signal transduction networks. In this study, we analysed 56 established and predicted effectors that contain a structural domain with the potential ability to bind to Ras oncoproteins and their link to pathways coordinating intestinal homoeostasis and barrier function. Using protein concentrations in colon tissue and Ras-effector binding affinities, a computational network model was generated that predicted how effectors differentially and competitively bind to Ras in colon context. The model also predicted both qualitative and quantitative changes in Ras-effector complex formations with increased levels of active Rasto simulate its upregulation in cancersimply as an emergent property of competition for the same binding interface on the surface of Ras. We also considered how the number of Ras-effector complexes at the membrane can be increased by additional domains present in some effectors that are recruited to the membrane in response to specific conditions (inputs/stimuli/growth factors) in colon context and CRC.

Ras is a plasma membrane (PM)-associated signaling hub protein that interacts with its partners (effectors) in a mutually exclusive fashion. We have shown earlier that competition for binding and hence the occurrence of specific binding events at a hub protein can modulate the activation of downstream pathways. Here, using a mechanistic modeling approach that incorporates high-quality proteomic data of Ras and 56 effectors in 29 (healthy) human tissues, we quantified the amount of individual Ras-effector complexes, and characterized the (stationary) Ras “wiring landscape” specific to each tissue. We identified nine effectors that are in significant amount in complex with Ras in at least one of the 29 tissues. We simulated both mutant- and stimulus-induced network re-configurations, and assessed their divergence from the reference scenario, specifically discussing a case study for two stimuli in three epithelial tissues. These analyses pointed to 32 effectors that are in significant amount in complex with Ras only if they are additionally recruited to the PM, e.g. via membrane-binding domains or domains binding to activated receptors at the PM. Altogether, our data emphasize the importance of tissue context for binding events at the Ras signaling hub.

BackgroundSignal transduction is the process through which cells communicate with the external environment, interpret stimuli and respond to them. This mechanism is controlled by signaling cascades, which play the role of intracellular transmitter, being able to transmit biochemical information between cell membrane and nucleus. In theory as well as in practice, it has been shown that a perturbation can propagate upstream (and not only downstream) a cascade, by a mechanism known as retroactivity. This study aims to compare the conditions on biochemical parameters which favor one or the other direction of signaling in such a cascade.ResultsFrom a mathematical point of view, we show that the steady states of a cascade of arbitrary length n are described by an iterative map of second order, meaning that the cascade tiers are actually coupled three-by-three. We study the influence of the biochemical parameters in the control of the direction of transmission – upstream and/or downstream – along a signaling cascade. A numerical and statistical approach, based on the random scan of parameters describing a 3-tier signaling cascade, provides complementary findings to the analytical study. In particular, computing the likelihood of parameters with respect to various signaling regimes, we identify conditions on biochemical parameters which enhance a specific direction of propagation corresponding to forward or retro-signaling regimes. A compact graphical representation is designed to relay the gist of these conditions.ConclusionsThe values of biochemical parameters such as kinetic rates, Michaelis-Menten constants, total concentrations of kinases and of phosphatases, determine the propensity of a cascade to favor or impede downstream or upstream signal transmission. We found that generally there is an opposition between parameter sets favoring forward and retro-signaling regimes. Therefore, on one hand our study supports the idea that in most cases, retroactive effects can be neglected when a cascade which is efficient in forward signaling, is perturbed by an external ligand inhibiting the activation at some tier of the cascade. This result is relevant for therapeutic methodologies based on kinase inhibition. On the other hand, our study highlights a less-known part of the parameter space where, although the forward signaling is inefficient, the cascade can interestingly act as a retro-signaling device.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0303-2) contains supplementary material, which is available to authorized users.

Background Ras is a key cellular signaling hub that controls numerous cell fates via multiple downstream effector pathways. While pathways downstream of effectors such as Raf, PI3K and RalGDS are extensively described in the literature, how other effectors signal downstream of Ras is often still enigmatic. Methods A comprehensive and unbiased Ras-effector network was reconstructed downstream of 43 effector proteins (converging onto 12 effector classes) using public pathway and protein–protein interaction (PPI) databases. The output is an oriented graph of pairwise interactions defining a 3-layer signaling network downstream of Ras. The 2290 proteins comprising the network were studied for their implication in signaling crosstalk and feedbacks, their subcellular localizations, and their cellular functions. Results The final Ras-effector network consists of 2290 proteins that are connected via 19,080 binary PPIs, increasingly distributed across the downstream layers, with 441 PPIs in layer 1, 1660 in layer 2, and 16,979 in layer 3. We identified a high level of crosstalk among proteins of the 12 effector classes. A class-specific Ras sub-network was generated in CellDesigner (.xml file) and a functional enrichment analysis thereof shows that 58% of the processes have previously been associated to a respective effector pathway, with the remaining providing insights into novel and unexplored functions of specific effector pathways. Conclusions Our large-scale and cell general Ras-effector network is a crucial steppingstone towards defining the network boundaries. It constitutes a ‘reference interactome’ and can be contextualized for specific conditions, e.g. different cell types or biopsy material obtained from cancer patients. Further, it can serve as a basis for elucidating systems properties, such as input–output relationships, crosstalk, and pathway redundancy. Graphical abstract

Quantitative systems pharmacology holds the promises of integrating results from laboratory animals or in vitro human systems into the design of human pharmacokinetic/pharmacodynamic (PK/PD) models allowing for precision and personalized medicine. However, reliable and general in vitro-to-in vivo extrapolation and