PI3K-dependent cross-talk interactions converge with Ras as quantifiable inputs integrated by Erk

Uncovering the dynamic effects of DEX treatment on lung cancer by integrating bioinformatic inference and multiscale modeling of scRNA-seq and proteomics data

Lung cancer is one of the leading causes of cancer-related death, with a five-year survival rate of 18%. It is a priority for us to understand the underlying mechanisms affecting lung cancer therapeutics' implementation and effectiveness. In this study, we combine the power of Bioinformatics and Systems Biology to comprehensively uncover functional and signaling pathways of drug treatment using bioinformatics inference and multiscale modeling of both scRNA-seq data and proteomics data. Based on a time series of lung adenocarcinoma derived A549 cells after DEX treatment, we first identified the differentially expressed genes (DEGs) in those lung cancer cells. Through the interrogation of regulatory network of those DEGs, we identified key hub genes including TGFβ, MYC, and SMAD3 varied underlie DEX treatment. Further gene set enrichment analysis revealed the TGFβ signaling pathway as the top enriched term. Those genes involved in the TGFβ pathway and their crosstalk with the ERBB pathway presented a strong survival prognosis in clinical lung cancer samples. With the basis of biological validation and literature-based curation, a multiscale model of tumor regulation centered on both TGFβ-induced and ERBB-amplified signaling pathways was developed to characterize the dynamic effects of DEX therapy on lung cancer cells. Our simulation results were well matched to available data of SMAD2, FOXO3, TGFβ1, and TGFβR1 over the time course. Moreover, we provided predictions of different doses to illustrate the trend and therapeutic potential of DEX treatment. The innovative and cross-disciplinary approach can be further applied to other computational studies in tumorigenesis and oncotherapy. We released the approach as a user-friendly tool named BIMM (Bioinformatic Inference and Multiscale Modeling), with all the key features available at https://github.com/chenm19/BIMM.

BlotIt—Optimal alignment of Western blot and qPCR experiments

Biological systems are frequently analyzed by means of mechanistic mathematical models. In order to infer model parameters and provide a useful model that can be employed for systems understanding and hypothesis testing, the model is often calibrated on quantitative, time-resolved data. To do so, it is typically important to compare experimental measurements over broad time ranges and various experimental conditions, e.g. perturbations of the biological system. However, most of the established experimental techniques such as Western blot, or quantitative real-time polymerase chain reaction only provide measurements on a relative scale, since different sample volumes, experimental adjustments or varying development times of a gel lead to systematic shifts in the data. In turn, the number of measurements corresponding to the same scale enabling comparability is limited. Here, we present a new flexible method to align measurement data that obeys different scaling factors and compare it to existing normalization approaches. We propose an alignment model to estimate these scaling factors and provide the possibility to adapt this model depending on the measurement technique of interest. In addition, an error model can be specified to adequately weight the different data points and obtain scaling-model based confidence intervals of the finally scaled data points. Our approach is applicable to all sorts of relative measurements and does not need a particular experimental condition that has been measured over all available scales. An implementation of the method is provided with the R package blotIt including refined ways of visualization.

TGFBR3 supports anoikis through suppressing ATF4 signaling

Epithelial morphogenesis and oncogenic transformation can cause loss of cell adhesion, and detached cells are eliminated by anoikis. Here, we reveal that transforming growth factor beta receptor 3 (TGFBR3) acts as an anoikis mediator through the coordination of activating transcription factor 4 (ATF4). In breast cancer, TGFBR3 is progressively lost, but elevated TGFBR3 is associated with a histologic subtype characterized by cellular adhesion defects. Dissecting the impact of extracellular matrix (ECM) deprivation, we demonstrate that ECM loss promotes TGFBR3 expression, which in turn differentiates cell aggregates to a prosurvival phenotype and drives the intrinsic apoptotic pathway. We demonstrate that inhibition of TGFBR3 impairs epithelial anoikis by activating ATF4 signaling. These preclinical findings provide a rationale for therapeutic inhibition of ATF4 in the subgroup of breast cancer patients with low TGFBR3 expression.

Spatial organization of FcγR and TLR2/1 on phagosome membranes differentially regulates their synergistic and inhibitory receptor crosstalk

Many innate immune receptors function collaboratively to detect and elicit immune responses to pathogens, but the physical mechanisms that govern the interaction and signaling crosstalk between the receptors are unclear. In this study, we report that the signaling crosstalk between Fc gamma receptor (FcγR) and Toll-like receptor (TLR)2/1 can be overall synergistic or inhibitory depending on the spatial proximity between the receptor pair on phagosome membranes. Using a geometric manipulation strategy, we physically altered the spatial distribution of FcγR and TLR2 on single phagosomes. We demonstrate that the signaling synergy between FcγR and TLR2/1 depends on the proximity of the receptors and decreases as spatial separation between them increases. However, the inhibitory effect from FcγRIIb on TLR2-dependent signaling is always present and independent of receptor proximity. The overall cell responses are an integration from these two mechanisms. This study presents quantitative evidence that the nanoscale proximity between FcγR and TLR2 functions as a key regulatory mechanism in their signaling crosstalk.

GALECTIN-8 Is a Neuroprotective Factor in the Brain that Can Be Neutralized by Human Autoantibodies

Galectin-8 (Gal-8) is a glycan-binding protein that modulates a variety of cellular processes interacting with cell surface glycoproteins. Neutralizing anti-Gal-8 antibodies that block Gal-8 functions have been described in autoimmune and inflammatory disorders, likely playing pathogenic roles. In the brain, Gal-8 is highly expressed in the choroid plexus and accordingly has been detected in human cerebrospinal fluid. It protects against central nervous system autoimmune damage through its immune-suppressive potential. Whether Gal-8 plays a direct role upon neurons remains unknown. Here, we show that Gal-8 protects hippocampal neurons in primary culture against damaging conditions such as nutrient deprivation, glutamate-induced excitotoxicity, hydrogen peroxide (H₂O₂)-induced oxidative stress, and β-amyloid oligomers (Aβo). This protective action is manifested even after 2 h of exposure to the harmful condition. Pull-down assays demonstrate binding of Gal-8 to selected β1-integrins, including α3 and α5β1. Furthermore, Gal-8 activates β1-integrins, ERK1/2, and PI3K/AKT signaling pathways that mediate neuroprotection. Hippocampal neurons in primary culture produce and secrete Gal-8, and their survival decreases upon incubation with human function-blocking Gal-8 autoantibodies obtained from lupus patients. Despite the low levels of Gal-8 expression detected by real-time PCR in hippocampus, compared with other brain regions, the complete lack of Gal-8 in Gal-8 KO mice determines higher levels of apoptosis upon H₂O₂ stereotaxic injection in this region. Therefore, endogenous Gal-8 likely contributes to generate a neuroprotective environment in the brain, which might be eventually counteracted by human function-blocking autoantibodies.

A Loss of Epigenetic Control Can Promote Cell Death through Reversing the Balance of Pathways in a Signaling Network

Epigenetic control of regulatory networks is only partially understood. Expression of Insulin-like growth factor-II (IGF2) is controlled by genomic imprinting, mediated by silencing of the maternal allele. Loss of imprinting of IGF2 (LOI) is linked to intestinal and colorectal cancers, causally in murine models and epidemiologically in humans. However, the molecular underpinnings of the LOI phenotype are not clear. Surprisingly, in LOI cells, we find a reversal of the relative activities of two canonical signaling pathways triggered by IGF2, causing further rebalancing between pro- and anti-apoptotic signaling. A predictive mathematical model shows that this network rebalancing quantitatively accounts for the effect of receptor tyrosine kinase inhibition in both WT and LOI cells. This mechanism also quantitatively explains both the stable LOI phenotype and the therapeutic window for selective killing of LOI cells, and thus prevention of epigenetically controlled cancers. These findings suggest a framework for understanding epigenetically modified cell signaling.

Activation of AKT pathway by Nrf2/PDGFA feedback loop contributes to HCC progression

Nuclear factor erythroid-2-related factor 2 (Nrf2), a master transcription factor in the antioxidant response, has been found to be ubiquitously expressed in various cancer cells and in the regulation tumor proliferation, invasion, and chemoresistance activities. The regulatory roles of Nrf2 in controlling Hepatocellular carcinoma (HCC) progression remain unclear. In this study, we demonstrated that Nrf2 was significantly elevated in HCC cells and tissues and was correlated with poor prognosis of HCCs. Consistently, Nrf2 significantly promoted HCC cell growth both in vitro and in vivo. Further investigation suggested a novel association of Nrf2 with Platelet-Derived Growth Factor-A (PDGFA). Nrf2 promoted PDGFA transcription by recruiting specificity protein 1 (Sp1) to its promoter, resulting in increased activation of the AKT/p21 pathway and cell cycle progression of HCC cells. As a feedback loop, PDGFA enhanced Nrf2 expression and activation in an AKT dependent manner. In line with these findings, expression of Nrf2 and PDGFA were positively correlated in HCC tissues. Taken together, this study uncovers a novel mechanism of the Nrf2/PDGFA regulatory loop that is crucial for AKT-dependent HCC progression, and thereby provides potential targets for HCC therapy.

Novel DNA targeted therapies for head and neck cancers: clinical potential and biomarkers

Head and neck squamous cell carcinoma is the sixth most common cancer worldwide and despite advances in treatment over the last years, there is still a relapse rate of 50%. New therapeutic agents are awaited to increase the survival of patients. DNA repair targeted agents in combination with standard DNA damaging therapies are a recent evolution in cancer treatment. These agents focus on the DNA damage repair pathways in cancer cells, which are often involved in therapeutic resistance. Interesting targets to overcome these cancer defense mechanisms are: PARP, DNA-PK, PI3K, ATM, ATR, CHK1/2, and WEE1 inhibitors. The application of DNA targeted agents in head and neck squamous cell cancer showed promising preclinical results which are translated to multiple ongoing clinical trials, although no FDA approval has emerged yet. Biomarkers are necessary to select the patients that can benefit the most from this treatment, although adequate biomarkers are limited and validation is needed to predict therapeutic response.

Quantification of growth factor signaling and pathway cross talk by live-cell imaging

Peptide growth factors stimulate cellular responses through activation of their transmembrane receptors. Multiple intracellular signaling cascades are engaged following growth factor-receptor binding, leading to short- and long-term biological effects. Each receptor-activated signaling pathway does not act in isolation but rather interacts at different levels with other pathways to shape signaling networks that are distinctive for each growth factor. To gain insights into the specifics of growth factor-regulated interactions among different signaling cascades, we developed a HeLa cell line stably expressing fluorescent live-cell imaging reporters that are readouts for two major growth factor-stimulated pathways, Ras-Raf-Mek-ERK and phosphatidylinositol (PI) 3-kinase-Akt. Incubation of cells with epidermal growth factor (EGF) resulted in rapid, robust, and sustained ERK signaling but shorter-term activation of Akt. In contrast, hepatocyte growth factor induced sustained Akt signaling but weak and short-lived ERK activity, and insulin-like growth factor-I stimulated strong long-term Akt responses but negligible ERK signaling. To address potential interactions between signaling pathways, we employed specific small-molecule inhibitors. In cells incubated with EGF or platelet-derived growth factor-AA, Raf activation and the subsequent stimulation of ERK reduced Akt signaling, whereas Mek inhibition, which blocked ERK activation, enhanced Akt and turned transient effects into sustained responses. Our results reveal that individual growth factors initiate signaling cascades that vary markedly in strength and duration and demonstrate in living cells the dramatic effects of cross talk from Raf and Mek to PI 3-kinase and Akt. Our data further indicate how specific growth factors can encode distinct cellular behaviors by promoting complex interactions among signaling pathways.

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC₅₀ independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC₅₀ on ATP concentration that allows prediction of the IC₅₀ at different ATP concentrations in enzyme and cellular assays. Comparison of drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in a systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.

Kinetic Modeling and Analysis of the Akt/Mechanistic Target of Rapamycin Complex 1 (mTORC1) Signaling Axis Reveals Cooperative, Feedforward Regulation

Mechanistic target of rapamycin complex 1 (mTORC1) controls biosynthesis and has been implicated in uncontrolled cell growth in cancer. Although many details of mTORC1 regulation are well understood, a systems-level, predictive framework synthesizing those details is currently lacking. We constructed various mathematical models of mTORC1 activation mediated by Akt and aligned the model outputs to kinetic data acquired for growth factor-stimulated cells. A model based on a putative feedforward loop orchestrated by Akt consistently predicted how the pathway was altered by depletion of key regulatory proteins. Analysis of the successful model also elucidates two dynamical motifs: neutralization of a negative regulator, which characterizes how Akt indirectly activates mTORC1, and seesaw enzyme regulation, which describes how activated and inhibited states of mTORC1 are controlled in concert to produce a nonlinear, ultrasensitive response. Such insights lend quantitative understanding of signaling networks and their precise manipulation in various contexts.

Signal Transduction at the Single-Cell Level: Approaches to Study the Dynamic Nature of Signaling Networks

Signal transduction, or how cells interpret and react to external events, is a fundamental aspect of cellular function. Traditional study of signal transduction pathways involves mapping cellular signaling pathways at the population level. However, population-averaged readouts do not adequately illuminate the complex dynamics and heterogeneous responses found at the single-cell level. Recent technological advances that observe cellular response, computationally model signaling pathways, and experimentally manipulate cells now enable studying signal transduction at the single-cell level. These studies will enable deeper insights into the dynamic nature of signaling networks.

Selective Sparing of Human Tregs by Pharmacologic Inhibitors of the Phosphatidylinositol 3-Kinase and MEK Pathways

Phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase/extracellular signal-regulated (MEK) signaling are central to the survival and proliferation of many cell types. Multiple lines of investigation in murine models have shown that control of the PI3K pathway is particularly important for regulatory T cell (Treg) stability and function. PI3K and MEK inhibitors are being introduced into the clinic, and we hypothesized that pharmacologic inhibition of PI3K, and possibly MEK, in mixed cultures of human mononuclear cells would preferentially affect CD4(+) and CD8(+) lymphocytes compared with Tregs. We tested this hypothesis using four readouts: proliferation, activation, functional suppression, and signaling. Results showed that Tregs were less susceptible to inhibition by both δ and α isoform-specific PI3K inhibitors and by an MEK inhibitor compared with their conventional CD4(+) and CD8(+) counterparts. These studies suggest less functional reliance on PI3K and MEK signaling in Tregs compared with conventional CD4(+) and CD8(+) lymphocytes. Therefore, the PI3K and MEK pathways are attractive pharmacologic targets for transplantation and treatment of autoimmunity.

Conservation of protein abundance patterns reveals the regulatory architecture of the EGFR-MAPK pathway

Various genetic mutations associated with cancer are known to alter cell signaling, but it is not clear whether they dysregulate signaling pathways by altering the abundance of pathway proteins. Using a combination of RNA sequencing and ultrasensitive targeted proteomics, we defined the primary components-16 core proteins and 10 feedback regulators-of the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway in normal human mammary epithelial cells and then quantified their absolute abundance across a panel of normal and breast cancer cell lines as well as fibroblasts. We found that core pathway proteins were present at very similar concentrations across all cell types, with a variance similar to that of proteins previously shown to display conserved abundances across species. In contrast, EGFR and transcriptionally controlled feedback regulators were present at highly variable concentrations. The absolute abundance of most core proteins was between 50,000 and 70,000 copies per cell, but the adaptors SOS1, SOS2, and GAB1 were found at far lower amounts (2000 to 5000 copies per cell). MAPK signaling showed saturation in all cells between 3000 and 10,000 occupied EGFRs, consistent with the idea that adaptors limit signaling. Our results suggest that the relative stoichiometry of core MAPK pathway proteins is very similar across different cell types, with cell-specific differences mostly restricted to variable amounts of feedback regulators and receptors. The low abundance of adaptors relative to EGFR could be responsible for previous observations that only a fraction of total cell surface EGFR is capable of rapid endocytosis, high-affinity binding, and mitogenic signaling.

A Probabilistic Boolean Network Approach for the Analysis of Cancer-Specific Signalling: A Case Study of Deregulated PDGF Signalling in GIST

BACKGROUND

Signal transduction networks are increasingly studied with mathematical modelling approaches while each of them is suited for a particular problem. For the contextualisation and analysis of signalling networks with steady-state protein data, we identified probabilistic Boolean network (PBN) as a promising framework which could capture quantitative changes of molecular changes at steady-state with a minimal parameterisation.

RESULTS AND CONCLUSION

In our case study, we successfully applied the PBN approach to model and analyse the deregulated Platelet-Derived Growth Factor (PDGF) signalling pathway in Gastrointestinal Stromal Tumour (GIST). We experimentally determined a rich and accurate dataset of steady-state profiles of selected downstream kinases of PDGF-receptor-alpha mutants in combination with inhibitor treatments. Applying the tool optPBN, we fitted a literature-derived candidate network model to the training dataset consisting of single perturbation conditions. Model analysis suggested several important crosstalk interactions. The validity of these predictions was further investigated experimentally pointing to relevant ongoing crosstalk from PI3K to MAPK signalling in tumour cells. The refined model was evaluated with a validation dataset comprising multiple perturbation conditions. The model thereby showed excellent performance allowing to quantitatively predict the combinatorial responses from the individual treatment results in this cancer setting. The established optPBN pipeline is also widely applicable to gain a better understanding of other signalling networks at steady-state in a context-specific fashion.

Argon protects against hypoxic-ischemic brain injury in neonatal rats through activation of nuclear factor (erythroid-derived 2)-like 2

Perinatal hypoxic ischaemic encephalopathy (HIE) has a high mortality rate with neuropsychological impairment. This study investigated the neuroprotective effects of argon against neonatal hypoxic-ischaemic brain injury.In vitro cortical neuronal cell cultures derived from rat foetuses were subjected to an oxygen and glucose deprivation (OGD) challenge for 90 minutes and then exposed to 70% argon or nitrogen with 5% carbon dioxide and balanced with oxygen for 2 hours.In vivo, seven-day-old rats were subjected to unilateral common carotid artery ligation followed by hypoxic (8% oxygen balanced with nitrogen) insult for 90 minutes. They were exposed to 70% argon or nitrogen balanced with oxygen for 2 hours. In vitro, argon treatment of cortical neuronal cultures resulted in a significant increase of p-mTOR and Nuclear factor (erythroid-derived 2)-like 2(Nrf2) and protection against OGD challenge. Inhibition of m-TOR through Rapamycin or Nrf2 through siRNA abolished argon-mediated cyto-protection. In vivo, argon exposure significantly enhanced Nrf2 and its down-stream effector NAD(P)H Dehydrogenase, Quinone 1(NQO1) and superoxide dismutase 1(SOD1). Oxidative stress, neuroinflammation and neuronal cell death were significantly decreased and brain infarction was markedly reduced. Blocking PI-3K through wortmannin or ERK1/2 through U0126 attenuated argon-mediated neuroprotection.These data provide a new molecular mechanism for the potential application of Argon as a neuroprotectant in HIE.

Network Architecture Predisposes an Enzyme to Either Pharmacologic or Genetic Targeting

Chemical inhibition and genetic knockdown of enzymes are not equivalent in cells, but network-level mechanisms that cause discrepancies between knockdown and inhibitor perturbations are not understood. Here we report that enzymes regulated by negative feedback are robust to knockdown but susceptible to inhibition. Using the Raf-MEK-ERK kinase cascade as a model system, we find that ERK activation is resistant to genetic knockdown of MEK but susceptible to a comparable degree of chemical MEK inhibition. We demonstrate that negative feedback from ERK to Raf causes this knockdown-versus-inhibitor discrepancy in vivo. Exhaustive mathematical modeling of three-tiered enzyme cascades suggests that this result is general: negative autoregulation or feedback favors inhibitor potency, whereas positive autoregulation or feedback favors knockdown potency. Our findings provide a rationale for selecting pharmacologic versus genetic perturbations in vivo and point out the dangers of using knockdown approaches in search of drug targets.

Model-Based Analysis of Cell Cycle Responses to Dynamically Changing Environments

Cell cycle progression is carefully coordinated with a cell's intra- and extracellular environment. While some pathways have been identified that communicate information from the environment to the cell cycle, a systematic understanding of how this information is dynamically processed is lacking. We address this by performing dynamic sensitivity analysis of three mathematical models of the cell cycle in Saccharomyces cerevisiae. We demonstrate that these models make broadly consistent qualitative predictions about cell cycle progression under dynamically changing conditions. For example, it is shown that the models predict anticorrelated changes in cell size and cell cycle duration under different environments independently of the growth rate. This prediction is validated by comparison to available literature data. Other consistent patterns emerge, such as widespread nonmonotonic changes in cell size down generations in response to parameter changes. We extend our analysis by investigating glucose signalling to the cell cycle, showing that known regulation of Cln3 translation and Cln1,2 transcription by glucose is sufficient to explain the experimentally observed changes in cell cycle dynamics at different glucose concentrations. Together, these results provide a framework for understanding the complex responses the cell cycle is capable of producing in response to dynamic environments.

Non-canonical Activation of Akt in Serum-Stimulated Fibroblasts, Revealed by Comparative Modeling of Pathway Dynamics

The dynamic behaviors of signaling pathways can provide clues to pathway mechanisms. In cancer cells, excessive phosphorylation and activation of the Akt pathway is responsible for cell survival advantages. In normal cells, serum stimulation causes brief peaks of extremely high Akt phosphorylation before reaching a moderate steady-state. Previous modeling assumed this peak and decline behavior (i.e., “overshoot”) was due to receptor internalization. In this work, we modeled the dynamics of the overshoot as a tool for gaining insight into Akt pathway function. We built an ordinary differential equation (ODE) model describing pathway activation immediately upstream of Akt phosphorylation at Thr³⁰⁸ (Aktp³⁰⁸). The model was fit to experimental measurements of Aktp³⁰⁸, total Akt, and phosphatidylinositol (3,4,5)-trisphosphate (PIP3), from mouse embryonic fibroblasts with serum stimulation. The canonical Akt activation model (the null hypothesis) was unable to recapitulate the observed delay between the peak of PIP3 (at 2 minutes), and the peak of Aktp³⁰⁸ (at 30–60 minutes). From this we conclude that the peak and decline behavior of Aktp³⁰⁸ is not caused by PIP3 dynamics. Models for alternative hypotheses were constructed by allowing an arbitrary dynamic curve to perturb each of 5 steps of the pathway. All 5 of the alternative models could reproduce the observed delay. To distinguish among the alternatives, simulations suggested which species and timepoints would show strong differences. Time-series experiments with membrane fractionation and PI3K inhibition were performed, and incompatible hypotheses were excluded. We conclude that the peak and decline behavior of Aktp³⁰⁸ is caused by a non-canonical effect that retains Akt at the membrane, and not by receptor internalization. Furthermore, we provide a novel spline-based method for simulating the network implications of an unknown effect, and we demonstrate a process of hypothesis management for guiding efficient experiments.

Influential pathways of cell signalling (such as PI3K/Akt) are routinely communicated using simple textbook-like diagrams that show only the most widely-accepted steps of the pathway. At the same time, there are countless other molecular influences relevant to each pathway, documented in the published literature, and more are being published every week. It should perhaps come as little surprise that during a routine observation of the Akt activation pathway, a simulation of the canonical model was mathematically incompatible with our observed dynamics. To progress beyond the standard, simplified model without testing an unreasonable number of molecular candidates individually, we employed computational modeling to analyze the dynamics of pathway activation. We asked when and where a non-canonical deviation could occur, relative to the canonical pathway. We used the timing of downstream activation to solve for the possible times of upstream initiation. By categorizing unknown effects by their dynamics, we were able to prune away implausible hypotheses using an efficient number of in vitro experiments. At the end we had a single plausible explanation for non-canonical Akt activation in our cells, and we confirmed experimentally that Akt is retained at the membrane after PIP3 is no longer present.

Development of a tandem affinity phosphoproteomic method with motif selectivity and its application in analysis of signal transduction networks

Phosphorylation is an important post-translational modification that is involved in regulating many signaling pathways. Of particular interest are the growth factor mediated Ras and phosphoinositide 3-kinase (PI3K) signaling pathways which, if misregulated, can contribute to the progression of cancer. Phosphoproteomic methods have been developed to study regulation of signaling pathways; however, due to the low stoichiometry of phosphorylation, understanding these pathways is still a challenge. In this study, we have developed a multi-dimensional method incorporating electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) with tandem IMAC/TiO2 enrichment for subsequent phosphopeptide identification by LC/MS/MS. We applied this method to PDGF-stimulated NIH 3T3 cells to provide over 11,000 unique phosphopeptide identifications. Upon motif analysis, IMAC was found to enrich for basophilic kinase substrates while the subsequent TiO2 step enriched for acidophilic kinase substrates, suggesting that both enrichment methods are necessary to capture the full complement of kinase substrates. Biological functions that were over-represented at each PDGF stimulation time point, together with the phosphorylation dynamics of several phosphopeptides containing known kinase phosphorylation sites, illustrate the feasibility of this approach in quantitative phosphoproteomic studies.

Intersectin1-S, a multidomain adapter protein, is essential for malignant glioma proliferation

Glioblastomas, the most aggressive form of primary brain tumors with a tendency to invade surrounding healthy brain tissues, remains an incurable disease. Intersectin (ITSN) is a multidomain adapter protein implicated in endocytosis, exocytosis, and multiple signaling pathways. Prior research of ours has shown intersectin1-S (ITSN1-S) is critical for the migration and invasion of glioma cells by regulating several key proteins. In this study, we established ITSN1-S expression patterns in human tumor tissues. We discovered that ITSN1-S expression was positively correlated with histological grade of gliomas and with poor patient prognosis. We also found that the expression of ITSN1-S protein was essential to glioblastoma cell proliferation. Furthermore, through a series of expression constructs encoding different ITSN1-S domains, we identified the critical roles of ITSN1-S SH3 domains in the regulation of cell proliferation. This study also demonstrates evidence suggesting that the regulation of ITSN1-S on glioblastoma cells proliferation is through the Raf/MEK/ERK pathway. In conclusion, this study suggests critical roles of ITSN1-S in malignant glioma proliferation, indicating a potential usage of ITSN1-S in the therapeutic intervention as a novel molecular target.

Quantitative analysis of receptor tyrosine kinase-effector coupling at functionally relevant stimulus levels

A major goal of current signaling research is to develop a quantitative understanding of how receptor activation is coupled to downstream signaling events and to functional cellular responses. Here, we measure how activation of the RET receptor tyrosine kinase on mouse neuroblastoma cells by the neurotrophin artemin (ART) is quantitatively coupled to key downstream effectors. We show that the efficiency of RET coupling to ERK and Akt depends strongly on ART concentration, and it is highest at the low (∼100 pM) ART levels required for neurite outgrowth. Quantitative discrimination between ERK and Akt pathway signaling similarly is highest at this low ART concentration. Stimulation of the cells with 100 pM ART activated RET at the rate of ∼10 molecules/cell/min, leading at 5-10 min to a transient peak of ∼150 phospho-ERK (pERK) molecules and ∼50 pAkt molecules per pRET, after which time the levels of these two signaling effectors fell by 25-50% while the pRET levels continued to slowly rise. Kinetic experiments showed that signaling effectors in different pathways respond to RET activation with different lag times, such that the balance of signal flux among the different pathways evolves over time. Our results illustrate that measurements using high, super-physiological growth factor levels can be misleading about quantitative features of receptor signaling. We propose a quantitative model describing how receptor-effector coupling efficiency links signal amplification to signal sensitization between receptor and effector, thereby providing insight into design principles underlying how receptors and their associated signaling machinery decode an extracellular signal to trigger a functional cellular outcome.

Pharmacological suppression of the Ras/MAPK pathway in thyroid carcinoma cells can provoke opposite effects on cell migration and proliferation: The appearance of yin-yang effects and the need of combinatorial treatments

A major challenge in tumor therapy is the decrease or even the halting of cell proliferation and migration of cancerous cells. In the present study, we have analyzed the impact of a pharmacological blockade of the PI3K/Akt and MAPK/ERK1/2 signaling pathways on cell migration, proliferation and cell death in three human thyroid tumor cell lines that represent the main types of malignant thyroid carcinomas (B-CPAP, follicular; Cal-62, anaplastic; FTC-133, papillary thyroid carcinoma cells) and in which these pathways are constitutively activated. In general, pharmacological perturbation of PI3/Akt (application of MK-2206) and MEK/ERK1/2 (application of PD0325901 or U0126) signaling led to a cell line and drug-specific decrease in the proliferation and migration potential of thyroid carcinoma cells, although to a varying extent. However, one exception became apparent: in Cal-62 cells inhibition of the MEK/ERK1/2 module increased the migration rate up to 50%. This effect could be prevented by a simultaneous suppression of the PI3/Akt pathway, but also by application of the multiple kinase inhibitor sorafenib, a treatment that did not change the activation state of Akt. Thus, a pharmacological perturbation of canonical signaling pathways in thyroid carcinoma may induce drug-dependent yin-yang effects that are characterized by a simultaneous suppression of one (i.e., proliferation) and the activation of another (i.e., migration) cellular process. The appearance of such phenomena should be taken into account when therapy plans are established.

Directed migration of mesenchymal cells: where signaling and the cytoskeleton meet

Cell migration directed by spatial cues, or taxis, is a primary mechanism for orchestrating concerted and collective cell movements during development, wound repair, and immune responses. Compared with the classic example of amoeboid chemotaxis, in which fast-moving cells such as neutrophils are directed by gradients of soluble factors, directed migration of slow-moving mesenchymal cells such as fibroblasts is poorly understood. Mesenchymal cells possess a distinctive organization of the actin cytoskeleton and associated adhesion complexes as its primary mechanical system, generating the asymmetric forces required for locomotion without strong polarization. The emerging hypothesis is that the molecular underpinnings of mesenchymal taxis involve distinct signaling pathways and diverse requirements for regulation.

Data-driven modeling reconciles kinetics of ERK phosphorylation, localization, and activity states

The extracellular signal‐regulated kinase (ERK) signaling pathway controls cell proliferation and differentiation in metazoans. Two hallmarks of its dynamics are adaptation of ERK phosphorylation, which has been linked to negative feedback, and nucleocytoplasmic shuttling, which allows active ERK to phosphorylate protein substrates in the nucleus and cytosol. To integrate these complex features, we acquired quantitative biochemical and live‐cell microscopy data to reconcile phosphorylation, localization, and activity states of ERK. While maximal growth factor stimulation elicits transient ERK phosphorylation and nuclear translocation responses, ERK activities available to phosphorylate substrates in the cytosol and nuclei show relatively little or no adaptation. Free ERK activity in the nucleus temporally lags the peak in nuclear translocation, indicating a slow process. Additional experiments, guided by kinetic modeling, show that this process is consistent with ERK's modification of and release from nuclear substrate anchors. Thus, adaptation of whole‐cell ERK phosphorylation is a by‐product of transient protection from phosphatases. Consistent with this interpretation, predictions concerning the dose‐dependence of the pathway response and its interruption by inhibition of MEK were experimentally confirmed.

Evaluating strategies to normalise biological replicates of Western blot data

Western blot data are widely used in quantitative applications such as statistical testing and mathematical modelling. To ensure accurate quantitation and comparability between experiments, Western blot replicates must be normalised, but it is unclear how the available methods affect statistical properties of the data. Here we evaluate three commonly used normalisation strategies: (i) by fixed normalisation point or control; (ii) by sum of all data points in a replicate; and (iii) by optimal alignment of the replicates. We consider how these different strategies affect the coefficient of variation (CV) and the results of hypothesis testing with the normalised data. Normalisation by fixed point tends to increase the mean CV of normalised data in a manner that naturally depends on the choice of the normalisation point. Thus, in the context of hypothesis testing, normalisation by fixed point reduces false positives and increases false negatives. Analysis of published experimental data shows that choosing normalisation points with low quantified intensities results in a high normalised data CV and should thus be avoided. Normalisation by sum or by optimal alignment redistributes the raw data uncertainty in a mean-dependent manner, reducing the CV of high intensity points and increasing the CV of low intensity points. This causes the effect of normalisations by sum or optimal alignment on hypothesis testing to depend on the mean of the data tested; for high intensity points, false positives are increased and false negatives are decreased, while for low intensity points, false positives are decreased and false negatives are increased. These results will aid users of Western blotting to choose a suitable normalisation strategy and also understand the implications of this normalisation for subsequent hypothesis testing.

Crosstalk between tyrosine kinase receptors, GSK3 and BMP2 signaling during osteoblastic differentiation of human mesenchymal stem cells

Bone morphogenic proteins (BMPs) promote mesenchymal stem cell (MSC) osteogenic differentiation, whereas platelet derived growth factor (PDGF) and fibroblast growth factor (FGF) activate their proliferation through receptors tyrosine kinase (RTK). The effects of PDGF or FGF receptor signaling pathway on BMP2-induced osteoblastic differentiation was investigated in human MSC (HMSC). Inhibition of PDGF or/and FGF receptors enhanced BMP2-induced alkaline phosphatase (ALP) activity, expression of Osterix, ALP and Bone sialoprotein, and matrix calcification. These effects were associated with increased Smad-1 activity, indicating that mitogenic factors interfere with Smad signaling in HMSC differentiation. RTK activate MAPK and inhibit GSK3 through the PI3K/Akt pathway. Biochemical analysis indicated that MAPK JNK and GSK3 especially are potential signaling molecules regulating BMP-induced osteoblastic HMSC differentiation. These observations highlight that the osteogenic effects of BMP2 are modulated by mitogenic factors acting through RTK.

Negative interactions and feedback regulations are required for transient cellular response

Signal transduction is a process required to conduct information from a receptor to the nucleus. This process is vital for the control of cellular function and fate. The dynamics of signaling activation and inhibition determine processes such as apoptosis, proliferation, and differentiation. Thus, it is important to understand the factors modulating transient and sustained response. To address this question, by applying mathematical approach we have studied the factors which can alter the activation nature of downstream signaling molecules. The factors which we have investigated are loops (feed forward and feedback loops), cross-talk of signal transduction pathways, and the change in the concentration of the signaling molecules. Based on our results we conclude that among these factors feedback loop and the cross-talks which directly inhibit the target protein dominantly controls the transient cellular response.

Computational model of VEGFR2 pathway to ERK activation and modulation through receptor trafficking

Vascular Endothelial Growth Factor (VEGF) signal transduction is central to angiogenesis in development and in pathological conditions such as cancer, retinopathy and ischemic diseases. We constructed and validated a computational model of VEGFR2 trafficking and signaling, to study the role of receptor trafficking kinetics in modulating ERK phosphorylation in VEGF-stimulated endothelial cells. Trafficking parameters were optimized and validated against four previously published in vitro experiments. Based on these parameters, model simulations demonstrated interesting behaviors that may be highly relevant to understanding VEGF signaling in endothelial cells. First, at moderate VEGF doses, VEGFR2 phosphorylation and ERK phosphorylation are related in a log-linear fashion, with a stable duration of ERK activation; but with higher VEGF stimulation, phosphoERK becomes saturated, and its duration increases. Second, a large endosomal fraction of VEGFR2 makes the ERK activation reaction network less sensitive to perturbations in VEGF dosage. Third, extracellular-matrix-bound VEGF binds and activates VEGFR2, but by internalizing at a slower rate, matrix-bound VEGF-induced intracellular ERK phosphorylation is predicted to be greater in magnitude and more sustained, in agreement with experimental evidence. Fourth, different endothelial cell types appear to have different trafficking rates, which result in different levels of endosomal receptor localization and different ERK response profiles.

Receptor tyrosine kinase (RTK) signalling in the control of neural stem and progenitor cell (NSPC) development

Important developmental responses are elicited in neural stem and progenitor cells (NSPC) by activation of the receptor tyrosine kinases (RTK), including the fibroblast growth factor receptors, epidermal growth factor receptor, platelet-derived growth factor receptors and insulin-like growth factor receptor (IGF1R). Signalling through these RTK is necessary and sufficient for driving a number of developmental processes in the central nervous system. Within each of the four RTK families discussed here, receptors are activated by sets of ligands that do not cross-activate receptors of the other three families, and therefore, their activation can be independently regulated by ligand availability. These RTK pathways converge on a conserved core of signalling molecules, but differences between the receptors in utilisation of signalling molecules and molecular adaptors for intracellular signal propagation become increasingly apparent. Intracellular inhibitors of RTK signalling are widely involved in the regulation of developmental signalling in NSPC and often determine developmental outcomes of RTK activation. In addition, cellular responses of NSPC to the activation of a given RTK may be significantly modulated by signal strength. Cellular propensity to respond also plays a role in developmental outcomes of RTK signalling. In combination, these mechanisms regulate the balance between NSPC maintenance and differentiation during development and in adulthood. Attribution of particular developmental responses of NSPC to specific pathways of RTK signalling becomes increasingly elucidated. Co-activation of several RTK in developing NSPC is common, and analysis of co-operation between their signalling pathways may advance knowledge of RTK role in NSPC development.

Computational modeling of ERBB2-amplified breast cancer identifies combined ErbB2/3 blockade as superior to the combination of MEK and AKT inhibitors

Crosstalk and compensatory circuits within cancer signaling networks limit the activity of most targeted therapies. For example, altered signaling in the networks activated by the ErbB family of receptors, particularly in ERBB2-amplified cancers, contributes to drug resistance. We developed a multiscale systems model of signaling networks in ERBB2-amplified breast cancer to quantitatively investigate relationships between biomarkers (markers of network activity) and combination drug efficacy. This model linked ErbB receptor family signaling to breast tumor growth through two kinase cascades: the PI3K/AKT survival pathway and the Ras/MEK/ERK growth and proliferation pathway. The model predicted molecular mechanisms of resistance to individual therapeutics. In particular, ERBB2-amplified breast cancer cells stimulated with the ErbB3 ligand heregulin were resistant to growth arrest induced by inhibitors of AKT and MEK or coapplication of two inhibitors of the receptor ErbB2 [Herceptin (trastuzumab) and Tykerb (lapatinib)]. We used model simulations to predict the response of ErbB2-positive breast cancer xenografts to combination therapies and verified these predictions in mice. Treatment with trastuzumab, lapatinib, and the ErbB3 inhibitor MM-111 was more effective in inhibiting tumor growth than the combination of AKT and MEK inhibitors and even induced tumor regression, indicating that targeting both ErbB3 and ErbB2 may be an improved therapeutic approach for ErbB2-positive breast cancer patients.

Computational Model of Gab1/2-Dependent VEGFR2 Pathway to Akt Activation

Vascular endothelial growth factor (VEGF) signal transduction is central to angiogenesis in development and in pathological conditions such as cancer, retinopathy and ischemic diseases. However, no detailed mass-action models of VEGF receptor signaling have been developed. We constructed and validated the first computational model of VEGFR2 trafficking and signaling, to study the opposing roles of Gab1 and Gab2 in regulation of Akt phosphorylation in VEGF-stimulated endothelial cells. Trafficking parameters were optimized against 5 previously published in vitro experiments, and the model was validated against six independent published datasets. The model showed agreement at several key nodes, involving scaffolding proteins Gab1, Gab2 and their complexes with Shp2. VEGFR2 recruitment of Gab1 is greater in magnitude, slower, and more sustained than that of Gab2. As Gab2 binds VEGFR2 complexes more transiently than Gab1, VEGFR2 complexes can recycle and continue to participate in other signaling pathways. Correspondingly, the simulation results show a log-linear relationship between a decrease in Akt phosphorylation and Gab1 knockdown while a linear relationship was observed between an increase in Akt phosphorylation and Gab2 knockdown. Global sensitivity analysis demonstrated the importance of initial-concentration ratios of antagonistic molecular species (Gab1/Gab2 and PI3K/Shp2) in determining Akt phosphorylation profiles. It also showed that kinetic parameters responsible for transient Gab2 binding affect the system at specific nodes. This model can be expanded to study multiple signaling contexts and receptor crosstalk and can form a basis for investigation of therapeutic approaches, such as tyrosine kinase inhibitors (TKIs), overexpression of key signaling proteins or knockdown experiments.

The small GTPase HRas shapes local PI3K signals through positive feedback and regulates persistent membrane extension in migrating fibroblasts

An inducible activation approach is used to interrogate the positive feedback circuit underlying self-amplification of PI3K signals in fibroblasts. The results show that local positive feedback between PI3K and HRas drives asymmetric membrane extension and cell migration.

Self-amplification of phosphoinositide 3-kinase (PI3K) signaling is believed to regulate asymmetric membrane extension and cell migration, but the molecular organization of the underlying feedback circuit is elusive. Here we use an inducible approach to synthetically activate PI3K and interrogate the feedback circuitry governing self-enhancement of 3′-phosphoinositide (3-PI) signals in NIH3T3 fibroblasts. Synthetic activation of PI3K initially leads to uniform production of 3-PIs at the plasma membrane, followed by the appearance of asymmetric and highly amplified 3-PI signals. A detailed spatiotemporal analysis shows that local self-amplifying 3-PI signals drive rapid membrane extension with remarkable directional persistence and initiate a robust migratory response. This positive feedback loop is critically dependent on the small GTPase HRas. Silencing of HRas abrogates local amplification of 3-PI signals upon synthetic PI3K activation and results in short-lived protrusion events that do not support cell migration. Finally, our data indicate that this feedback circuit is likely to operate during platelet-derived growth factor–induced random cell migration. We conclude that positive feedback between PI3K and HRas is essential for fibroblasts to spontaneously self-organize and generate a productive migratory response in the absence of spatial cues.

Modeling signaling networks with different formalisms: a preview

In the last 30 years, many of the mechanisms behind signal transduction, the process by which the cell takes extracellular signals as an input and converts them to a specific cellular phenotype, have been experimentally determined. With these discoveries, however, has come the realization that the architecture of signal transduction, the signaling network, is incredibly complex. Although the main pathways between receptor and output are well-known, there is a complex net of regulatory features that include crosstalk between different pathways, spatial and temporal effects, and positive and negative feedbacks. Hence, modeling approaches have been used to try and unravel some of these complexities. We use the mitogen-activated protein kinase cascade to illustrate chemical kinetic and logic approaches to modeling signaling networks. By using a common well-known model, we illustrate here the assumptions and level of detail behind each modeling approach, which serves as an introduction to the more detailed discussions of each in the accompanying chapters in this book.

Systemic perturbation of the ERK signaling pathway by the proteasome inhibitor, MG132

Inhibition of the ubiquitin-proteasome protein degradation pathway has been identified as a viable strategy for anti-tumor therapy based on its broad effects on cell proliferation. By the same token, the variety of elicited effects confounds the interpretation of cell-based experiments using proteasome inhibitors such as MG132. It has been proposed that MG132 treatment reduces growth factor-stimulated phosphorylation of extracellular signal-regulated kinases (ERKs), at least in part through upregulation of dual specificity phosphatases (DUSPs). Here, we show that the effects of MG132 treatment on ERK signaling are more widespread, leading to a reduction in activation of the upstream kinase MEK. This suggests that MG132 systemically perturbs the intracellular phosphoproteome, impacting ERK signaling by reducing phosphorylation status at multiple levels of the kinase cascade.

EGFR/Src/Akt signaling modulates Sox2 expression and self-renewal of stem-like side-population cells in non-small cell lung cancer

Background

Cancer stem cells are thought to be responsible for the initiation and progression of cancers. In non-small cell lung cancers (NSCLCs), Hoechst 33342 dye effluxing side population (SP) cells are shown to have stem cell like properties. The oncogenic capacity of cancer stem-like cells is in part due to their ability to self-renew; however the mechanistic correlation between oncogenic pathways and self-renewal of cancer stem-like cells has remained elusive. Here we characterized the SP cells at the molecular level and evaluated its ability to generate tumors at the orthotopic site in the lung microenvironment. Further, we investigated if the self-renewal of SP cells is dependent on EGFR mediated signaling.

Results

SP cells were detected and isolated from multiple NSCLC cell lines (H1650, H1975, A549), as well as primary human tumor explants grown in nude mice. SP cells demonstrated stem-like properties including ability to self-renew and grow as spheres; they were able to generate primary and metastatic tumors upon orthotopic implantation into the lung of SCID mice. In vitro study revealed elevated expression of stem cell associated markers like Oct4, Sox2 and Nanog as well as demonstrated intrinsic epithelial to mesenchymal transition features in SP cells. Further, we show that abrogation of EGFR, Src and Akt signaling through pharmacological or genetic inhibitors suppresses the self-renewal growth and expansion of SP-cells and resulted in specific downregulation of Sox2 protein expression. siRNA mediated depletion of Sox2 significantly blocked the SP phenotype as well as its self-renewal capacity; whereas other transcription factors like Oct4 and Nanog played a relatively lesser role in regulating self-renewal. Interestingly, Sox2 was elevated in metastatic foci of human NSCLC samples.

Conclusions

Our findings suggest that Sox2 is a novel target of EGFR-Src-Akt signaling in NSCLCs that modulates self-renewal and expansion of stem-like cells from NSCLC. Therefore, the outcome of the EGFR-Src-Akt targeted therapy may rely upon the expression and function of Sox2 within the NSCLC-CSCs.

Identification of aberrant pathways and network activities from high-throughput data

Many complex diseases such as cancer are associated with changes in biological pathways and molecular networks rather than being caused by single gene alterations. A major challenge in the diagnosis and treatment of such diseases is to identify characteristic aberrancies in the biological pathways and molecular network activities and elucidate their relationship to the disease. This review presents recent progress in using high-throughput biological assays to decipher aberrant pathways and network activities. In particular, this review provides specific examples in which high-throughput data have been applied to identify relationships between diseases and aberrant pathways and network activities. The achievements in this field have been remarkable, but many challenges have yet to be addressed.

Genomics and bioinformatics of Parkinson's disease

Within the last two decades, genomics and bioinformatics have profoundly impacted our understanding of the molecular mechanisms of Parkinson's disease (PD). From the description of the first PD gene in 1997 until today, we have witnessed the emergence of new technologies that have revolutionized our concepts to identify genetic mechanisms implicated in human health and disease. Driven by the publication of the human genome sequence and followed by the description of detailed maps for common genetic variability, novel applications to rapidly scrutinize the entire genome in a systematic, cost-effective manner have become a reality. As a consequence, about 30 genetic loci have been unequivocally linked to the pathogenesis of PD highlighting essential molecular pathways underlying this common disorder. Herein we discuss how neurogenomics and bioinformatics are applied to dissect the nature of this complex disease with the overall aim of developing rational therapeutic interventions.

Data-driven modelling of receptor tyrosine kinase signalling networks quantifies receptor-specific potencies of PI3K- and Ras-dependent ERK activation

Signal transduction networks in mammalian cells, comprising a limited set of interacting biochemical pathways, are accessed by various growth factor and cytokine receptors to elicit distinct cell responses. This raises the question as to how specificity of the stimulus-response relationship is encoded at the molecular level. It has been proposed that specificity arises not only from the activation of unique signalling pathways, but also from quantitative differences in the activation and regulation of shared receptor-proximal signalling proteins. To address such hypotheses, data sets with greater precision and coverage of experimental conditions will need to be acquired, and rigorous frameworks that codify and parameterize the inherently non-linear relationships among signalling activities will need to be developed. In the present study we apply a systematic approach combining quantitative measurements and mathematical modelling to compare the signalling networks accessed by FGF (fibroblast growth factor) and PDGF (platelet-derived growth factor) receptors in mouse fibroblasts, in which the ERK (extracellular-signal-regulated kinase) cascade is activated by Ras- and PI3K (phosphoinositide 3-kinase)-dependent pathways. We show that, whereas the FGF stimulation of PI3K signalling is relatively weak, this deficiency is compensated for by a more potent Ras-dependent activation of ERK. Thus, as the modelling would predict, the ERK pathway is activated to a greater extent in cells co-stimulated with FGF and PDGF, relative to the saturated levels achieved with either ligand alone. It is envisaged that similar approaches will prove valuable in the elucidation of quantitative differences among other closely related receptor signalling networks.

MUC1 regulates PDGFA expression during pancreatic cancer progression

Pancreatic Ductal Adenocarcinoma (PDA) has one of the worst prognoses of all cancers. Mucin 1 (MUC1), a transmembrane mucin glycoprotein, is a key modulator of several signaling pathways that affect oncogenesis, motility, and metastasis. Its expression is known to be associated with poor prognosis in patients. However, the precise mechanism remains elusive. We report a novel association of MUC1 with Platelet-Derived Growth Factor-A (PDGFA). PDGFA is one of the many drivers of tumor growth, angiogenesis, and metastasis in PDA. Using mouse PDA models as well as human samples, we show clear evidence that MUC1 regulates the expression and secretion of PDGFA. This, in turn, influences proliferation and invasion of pancreatic cancer cells leading to higher tumor burden in vivo. In addition, we reveal that MUC1 over expressing cells are heavily dependent on PDGFA both for proliferation and invasion while MUC1-null cells are not. Moreover, PDGFA and MUC1 are critical for translocation of βcatenin to the nucleus for oncogenesis to ensue. Finally, we elucidate the underlying mechanism by which MUC1 regulates PDGFA expression and secretion in pancreatic cancer cells. We show that MUC1 associates with Hif1-α, a known transcription factor involved in controlling PDGFA expression. Furthermore, MUC1 facilitates Hif1-α translocation to the nucleus. In summary, we have demonstrated that MUC1-induced invasion and proliferation occurs via increased exogenous production of PDGFA. Thus, impeding MUC1 regulation of PDGFA signaling may be therapeutically beneficial for patients with PDA.

Quantitative models of signal transduction networks: How detailed should they be?

Receptor-mediated signal transduction networks, comprised of multiple biochemical pathways, control cell responses and are therefore central to normal and aberrant physiological processes. An appreciation for the inherent complexities of these networks has matured in recent years, to the point where it is now apparent that experimental measurements will need to be combined with computational modeling and analysis to best interpret and predict how individual mechanisms (proteinprotein interactions, enzymatic reactions, etc.,) are integrated at the network level. To progress along these lines, there is a major barrier to overcome: although a deep mechanistic understanding of signal transduction has been achieved, data sets of a suitably quantitative nature are still lacking. Based on our efforts to systematically acquire and analyze such measurements, we contend that the level of detail in models of signaling networks ought to be limited by the availability of quantitative data, rather than by the much greater availability of qualitative information about signaling interactions. Although this approach is sensible from a data-driven modeling perspective, it is controversial because it gives the false impression that molecular-level details are being ignored.

Features of the reversible sensitivity-resistance transition in PI3K/PTEN/AKT signalling network after HER2 inhibition

Systems biology approaches that combine experimental data and theoretical modelling to understand cellular signalling network dynamics offer a useful platform to investigate the mechanisms of resistance to drug interventions and to identify combination drug treatments. Extending our work on modelling the PI3K/PTEN/AKT signalling network (SN), we analyse the sensitivity of the SN output signal, phospho-AKT, to inhibition of HER2 receptor. We model typical aberrations in this SN identified in cancer development and drug resistance: loss of PTEN activity, PI3K and AKT mutations, HER2 overexpression, and overproduction of GSK3β and CK2 kinases controlling PTEN phosphorylation. We show that HER2 inhibition by the monoclonal antibody pertuzumab increases SN sensitivity, both to external signals and to changes in kinetic parameters of the proteins and their expression levels induced by mutations in the SN. This increase in sensitivity arises from the transition of SN functioning from saturation to non-saturation mode in response to HER2 inhibition. PTEN loss or PIK3CA mutation causes resistance to anti-HER2 inhibitor and leads to the restoration of saturation mode in SN functioning with a consequent decrease in SN sensitivity. We suggest that a drug-induced increase in SN sensitivity to internal perturbations, and specifically mutations, causes SN fragility. In particular, the SN is vulnerable to mutations that compensate for drug action and this may result in a sensitivity-to-resistance transition. The combination of HER2 and PI3K inhibition does not sensitise the SN to internal perturbations (mutations) in the PI3K/PTEN/AKT pathway: this combination treatment provides both synergetic inhibition and may prevent the SN from acquired mutations causing drug resistance. Through combination inhibition treatments, we studied the impact of upstream and downstream interventions to suppress resistance to the HER2 inhibitor in the SN with PTEN loss. Comparison of experimental results of PI3K inhibition in the PTEN upstream pathway with PDK1 inhibition in the PTEN downstream pathway shows that upstream inhibition abrogates resistance to pertuzumab more effectively than downstream inhibition. This difference in inhibition effect arises from the compensatory mechanism of an activation loop induced in the downstream pathway by PTEN loss. We highlight that drug target identification for combination anti-cancer therapy needs to account for the mutation effects on the upstream and downstream pathways.

Overexpression of MUC1 enhances proangiogenic activity of non-small-cell lung cancer cells through activation of Akt and extracellular signal-regulated kinase pathways

BACKGROUND

Angiogenesis is an important process required for tumor progression. Mucin 1 (MUC1) is a transmembrane glycoprotein that is aberrantly upregulated in many types of cancer, including non-small-cell lung cancer (NSCLC). However, the biological significance of MUC1 overexpression in lung cancer angiogenesis is not completely understood.

METHODS

We showed that enforced expression of MUC1 in two NSCLC cell lines, A549 and NCI-H460, which have a low level of endogenous MUC1, promoted their ability to induce vascular endothelial growth factor (VEGF)-dependent endothelial cell migration and tube formation.

RESULTS

There was a significant increase in VEGF expression in MUC1-overexpressing NSCLC cells. Moreover, MUC1 overexpression resulted in a marked elevation in phosphorylated Akt and extracellular signal-regulated kinase (ERK)1/2, indicative of activation of both signaling pathways. Most importantly, inhibition of Akt or ERK signaling using specific chemical inhibitors restrained the proangiogenic activity of MUC1-overexpressing NSCLC cells.

CONCLUSIONS

Taken together, our present data demonstrate that the aberrant upregulation of MUC1 favors tumor angiogenesis in NSCLC, likely through the activation of both Akt and ERK pathways and elevation of VEGF production. MUC1 may thus be a potential antiangiogenic target in NSCLC.

BIM expression in treatment-naive cancers predicts responsiveness to kinase inhibitors

Cancers with specific genetic mutations are susceptible to selective kinase inhibitors. However, there is a wide spectrum of benefit among cancers harboring the same sensitizing genetic mutations. Herein, we measured apoptotic rates among cell lines sharing the same driver oncogene following treatment with the corresponding kinase inhibitor. There was a wide range of kinase inhibitor-induced apoptosis despite comparable inhibition of the target and associated downstream signaling pathways. Surprisingly, pretreatment RNA levels of the BH3-only pro-apoptotic BIM strongly predicted the capacity of EGFR, HER2, and PI3K inhibitors to induce apoptosis in EGFR-mutant, HER2-amplified, and PIK3CA-mutant cancers, respectively, but BIM levels did not predict responsiveness to standard chemotherapies. Furthermore, BIM RNA levels in EGFR-mutant lung cancer specimens predicted response and duration of clinical benefit from EGFR inhibitors. These findings suggest assessment of BIM levels in treatment-naïve tumor biopsies may indicate the degree of benefit from single-agent kinase inhibitors in multiple oncogene-addiction paradigms.

Fungal recognition enhances mannose receptor shedding through dectin-1 engagement

The mannose receptor (MR) is an endocytic type I membrane molecule with a broad ligand specificity that is involved in both hemostasis and pathogen recognition. Membrane-anchored MR is cleaved by a metalloproteinase into functional soluble MR (sMR) composed of the extracellular domains of intact MR. Although sMR production was initially considered a constitutive process, enhanced MR shedding has been observed in response to the fungal pathogen Pneumocystis carinii. In this work, we have investigated the mechanism mediating enhanced MR shedding in response to fungi. We show that other fungal species, including Candida albicans and Aspergillus fumigatus, together with zymosan, a preparation of the cell wall of Saccharomyces cerevisiae, mimic the effect of P. carinii on sMR production and that this effect takes place mainly through β-glucan recognition. Additionally, we demonstrate that MR cleavage in response to C. albicans and bioactive particulate β-glucan requires expression of dectin-1. Our data, obtained using specific inhibitors, are consistent with the canonical Syk-mediated pathway triggered by dectin-1 being mainly responsible for inducing MR shedding, with Raf-1 being partially involved. As in the case of steady-state conditions, MR shedding in response to C. albicans and β-glucan particles requires metalloprotease activity. The induction of MR shedding by dectin-1 has clear implications for the role of MR in fungal recognition, as sMR was previously shown to retain the ability to bind fungal pathogens and can interact with numerous host molecules, including lysosomal hydrolases. Thus, MR cleavage could also impact on the magnitude of inflammation during fungal infection.

Integrated computational model of cell cycle and checkpoint reveals different essential roles of Aurora-A and Plk1 in mitotic entry

Understanding the regulation of mitotic entry is one of the most important goals of modern cell biology, and computational modeling of mitotic entry has been a subject of several recent studies. However, there are still many regulation mechanisms that remain poorly characterized. Two crucial aspects are how mitotic entry is controlled by its upstream regulators Aurora-A and Plk1, and how mitotic entry is coordinated with other biological events, especially G2/M checkpoint. In this context, we reconstructed a comprehensive computational model that integrates the mitotic entry network and the G2/M checkpoint system. Computational simulation of this model and subsequent experimental verification revealed that Aurora-A and Plk1 are redundant to the activation of cyclin B/Cdk1 during normal mitotic entry, but become especially important for cyclin B/Cdk1 activation during G2/M checkpoint recovery. Further analysis indicated that, in response to DNA damage, Chk1-mediated network rewiring makes cyclin B/Cdk1 more sensitive to the down-regulation of Aurora-A and Plk1. In addition, we demonstrated that concurrently targeting Aurora-A and Plk1 during G2/M checkpoint recovery achieves a synergistic effect, which suggests the combinational use of Aurora-A and Plk1 inhibitors after chemotherapy or radiotherapy. Thus, the results presented here provide novel insights into the regulation mechanism of mitotic entry and have potential value in cancer therapy.