In the present paper, we describe multiple levels of cross-talk between the PI3K (phosphoinositide 3-kinase)/Akt and Ras/MAPK (mitogen-activated protein kinase) signalling pathways. Experimental data and computer simulations demonstrate that cross-talk is context-dependent and that both pathways can activate or inhibit each other. Positive influence of the PI3K pathway on the MAPK pathway is most effective at sufficiently low doses of growth factors, whereas negative influence of the MAPK pathway on the PI3K pathway is mostly pronounced at high doses of growth factors. Pathway cross-talk endows a cell with emerging capabilities for processing and decoding signals from multiple receptors activated by different combinations of extracellular cues.

Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exploit experimental and computational approaches to reveal how a concordant interplay between the insulin and epidermal growth factor (EGF) signaling networks can potentiate mitogenic signaling. In HEK293 cells, insulin is a poor activator of the Ras/ERK (extracellular signal-regulated kinase) cascade, yet it enhances ERK activation by low EGF doses. We find that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Computational modeling unveils how critical network nodes, the adaptor proteins GAB1 and insulin receptor substrate (IRS), Src kinase, and phosphatase SHP2, convert insulin-induced increase in the phosphatidylinositol-3,4,5-triphosphate (PIP 3 ) concentration into enhanced Ras/ERK activity. The model predicts and experiments confirm that insulin-induced amplification of mitogenic signaling is abolished by disrupting PIP 3 -mediated positive feedback via GAB1 and IRS. We demonstrate that GAB1 behaves as a non-linear amplifier of mitogenic responses and insulin endows EGF signaling with robustness to GAB1 suppression. Our results show the feasibility of using computational models to identify key target combinations and predict complex cellular responses to a mixture of external cues.

Grb2-associated binder 1 (GAB1) is a scaffold protein involved in numerous interactions that propagate signaling by growth factor and cytokine receptors. Here we explore in silico and validate in vivo the role of GAB1 in the control of mitogenic (Ras/MAPK) and survival (phosphatidylinositol 3-kinase (PI3K)/Akt) signaling stimulated by epidermal growth factor (EGF). We built a comprehensive mechanistic model that allows for reliable predictions of temporal patterns of cellular responses to EGF under diverse perturbations, including different EGF doses, GAB1 suppression, expression of mutant proteins, and pharmacological inhibitors. We show that the temporal dynamics of GAB1 tyrosine phosphorylation is significantly controlled by positive GAB1-PI3K feedback and negative MAPK-GAB1 feedback. Our experimental and computational results demonstrate that the essential function of GAB1 is to enhance PI3K/Akt activation and extend the duration of Ras/MAPK signaling. By amplifying positive interactions between survival and mitogenic pathways, GAB1 plays the critical role in cell proliferation and tumorigenesis.

BackgroundCell-to-cell variability in protein expression can be large, and its propagation through signaling networks affects biological outcomes. Here, we apply deterministic and probabilistic models and biochemical measurements to study how network topologies and cell-to-cell protein abundance variations interact to shape signaling responses.ResultsWe observe bimodal distributions of extracellular signal-regulated kinase (ERK) responses to epidermal growth factor (EGF) stimulation, which are generally thought to indicate bistable or ultrasensitive signaling behavior in single cells. Surprisingly, we find that a simple MAPK/ERK-cascade model with negative feedback that displays graded, analog ERK responses at a single cell level can explain the experimentally observed bimodality at the cell population level. Model analysis suggests that a conversion of graded input–output responses in single cells to digital responses at the population level is caused by a broad distribution of ERK pathway activation thresholds brought about by cell-to-cell variability in protein expression.ConclusionsOur results show that bimodal signaling response distributions do not necessarily imply digital (ultrasensitive or bistable) single cell signaling, and the interplay between protein expression noise and network topologies can bring about digital population responses from analog single cell dose responses. Thus, cells can retain the benefits of robustness arising from negative feedback, while simultaneously generating population-level on/off responses that are thought to be critical for regulating cell fate decisions.

We explored the crosstalk between cell survival (phosphatidylinositol 3-kinase (PI3K)/Akt) and mitogenic (Ras/Raf/MEK/extracellular signal-regulated kinase (ERK)) signaling pathways activated by an epidermal growth factor (EGF) and analyzed their sensitivity to small molecule inhibitors in the PI3K-mutant estrogen receptor (ER)-positive MCF7 and T47D breast cancer cells. In contrast to MCF7 cells, ERK phosphorylation in T47D cells displayed resistance to MEK inhibition by several structurally different compounds, such as U0126, PD 098059 and PD 198306, MEK suppression by small interfering RNA (siRNA) and was also less sensitive to PI3K inhibition by wortmannin. Similar effect was observed in PI3K-wild type ER-positive BT-474 cells, albeit to a much lesser extent.MEK-independent ERK activation was induced only by ErbB receptor ligands and was resistant to inhibition of several kinases and phosphatases that are known to participate in the regulation of Ras/ mitogen-activated protein kinase (MAPK) cascade. Although single agents against PDK1 or Akt did not affect EGF-induced ERK phosphorylation, a combination of PI3K/Akt and MEK inhibitors synergistically suppressed ERK activation and cellular growth. siRNA-mediated silencing of class I PI3K or Akt1/2 genes also significantly decreased U0126-resistant ERK phosphorylation.Our data suggest that in T47D cells ErbB family ligands induce a dynamic, PI3K/Akt-sensitive and MEK-independent compensatory ERK activation circuit that is absent in MCF7 cells. We discuss candidate proteins that can be involved in this activation circuitry and suggest that PDZ-Binding

There is strong evidence that deregulation of prolactin (PRL) signaling contributes to pathogenesis and chemoresistance of breast cancer. Therefore, understanding cross-talk between distinct signal transduction pathways triggered by activation of the prolactin receptor (PRL-R), is essential for elucidating the pathogenesis of metastatic breast cancer. In this study, we applied a sequential inhibitory analysis of various signaling intermediates to examine the hierarchy of protein interactions within the PRL signaling network and to evaluate the relative contributions of multiple signaling branches downstream of PRL-R to the activation of the extracellular signal-regulated kinases ERK1 and ERK2 in T47D and MCF-7 human breast cancer cells. Quantitative measurements of the phosphorylation/activation patterns of proteins showed that PRL simultaneously activated Src family kinases (SFKs) and the JAK/STAT, phosphoinositide-3 (PI3)-kinase/Akt and MAPK signaling pathways. The specific blockade or siRNA-mediated suppression of SFK/FAK, JAK2/STAT5, PI3-kinase/PDK1/Akt, Rac/PAK or Ras regulatory circuits revealed that (1) the PI3-kinase/Akt pathway is required for activation of the MAPK/ERK signaling cascade upon PRL stimulation; (2) PI3-kinase-mediated activation of the c-Raf-MEK1/2-ERK1/2 cascade occurs independent of signaling dowstream of STATs, Akt and PKC, but requires JAK2, SFKs and FAK activities; (3) activated PRL-R mainly utilizes the PI3-kinase-dependent Rac/PAK pathway rather than the canonical Shc/Grb2/SOS/Ras route to initiate and sustain ERK1/2 signaling. By interconnecting diverse signaling pathways PLR may enhance proliferation, survival, migration and invasiveness of breast cancer cells.

The qualitative and quantitative measurement of protein abundance and protein modification states are essential in understanding their role in diverse cellular processes. Traditional Western blotting technique, though sensitive, is prone to produce substantial errors and is not readily adapted to highthroughput technologies. We propose a modified immunoblotting procedure, which is based on simultaneous transfer of proteins from multiple gel-strips onto the same membrane, and is compatible with any conventional gel electrophoresis system. As a result, the data output per single blotting cycle can readily be increased up to ten-fold. In contrast to the traditional "one protein detection per electrophoresis cycle", this procedure allows simultaneous monitoring of up to nine different proteins. In addition to maintaining the ability to detect picogram quantities of protein, the modified system substantially improves data accuracy by reducing signal errors by two-fold. Multi-strip Western blotting procedure allows making statistically reliable side-by-side comparisons of different or repeated sets of data. Compared to the traditional methods, this approach provides a more economical, reproducible and effective procedure, facilitating the generation of large amounts of high-quality quantifiable data.

The qualitative and quantitative measurements of protein abundance and modification states are essential in understanding their functions in diverse cellular processes. Typical Western blotting, though sensitive, is prone to produce substantial errors and is not readily adapted to high-throughput technologies. Multistrip Western blotting is a modified immunoblotting procedure based on simultaneous electrophoretic transfer of proteins from multiple strips of polyacrylamide gels to a single membrane sheet. In comparison with the conventional technique, Multistrip Western blotting increases the data output per single blotting cycle up to ten-fold, allows concurrent monitoring of up to nine different proteins from the same loading of the sample, and substantially improves the data accuracy by reducing immunoblotting-derived signal errors. This approach enables statistically reliable comparison of different or repeated sets of data, and therefore is beneficial to apply in biomedical diagnostics, systems biology and cell signaling research.