Modeling the effects of HER/ErbB1-3 coexpression on receptor dimerization and biological response

Comparative analysis of ANN performance of four feature extraction methods used in the detection of epileptic seizures

Epilepsy, a prevalent neurological disorder characterized by disrupted brain activity, affects over 70 million individuals worldwide, as reported by the World Health Organization (WHO). The development of computer-aided diagnosis systems has become vital in assessing epilepsy severity promptly and initiating timely treatment. These systems enable the detection of epileptic seizures by analyzing the electrical activity in the EEG recordings of the patients. In addition, it helps doctors to choose suitable treatment by quickly determining the type, duration, and characteristics of seizures and increases the patient's quality of life. The proposed computer-aided diagnosis system in this study comprises three modules: preprocessing, feature extraction, and classification. The initial module employs a low-pass Chebyshev II filter to eliminate noise artifacts from signal recordings. The second module involves deriving feature vectors using Bispectrum Analysis, Empirical Mode Decomposition, Discrete Wavelet Transform, and Wavelet Packet Analysis. The third module employs the Artificial Neural Networks method for epileptic seizure detection. This study not only enables the comparison of feature extraction efficacy among Bispectrum Analysis, Empirical Mode Decomposition, Discrete Wavelet Transform, and Wavelet Packet Analysis techniques, but it also reveals that Bispectrum Analysis and Empirical Mode Decomposition yield the highest accuracy rate. The method achieves 100% accuracy in detecting epileptic seizures. Additionally, sensitivity analysis has been conducted to enhance the success of Discrete Wavelet Transform and Wavelet Packet Analysis methods and to identify significant features.

Origin of diverse phosphorylation patterns in the ERBB system

Intercellular signals induce various cellular responses, including growth, proliferation, and differentiation, via the dynamic processes of signal transduction pathways. For cell fate decisions, ligand-binding induces the phosphorylation of ERBB receptors, which in turn activate downstream molecules. The ERBB family includes four subtypes, which diverged through two gene duplications from a common ancestor. Differences in the expression patterns of the subtypes have been reported between different organs in the human body. However, how these different expression properties influence the diverse phosphorylation levels of ERBB proteins is not well understood. Here we study the origin of the phosphorylation responses by experimental and mathematical analyses. The experimental measurements clarified that the phosphorylation levels heavily depend on the ERBB expression profiles. We developed a mathematical model consisting of the four subtypes as monomers, homodimers, and heterodimers and estimated the rate constants governing the phosphorylation responses from the experimental data. To understand the origin of the diversity, we analyzed the effects of the expression levels and reaction rates of the ERBB subtypes on the diversity. The difference in phosphorylation rates between ERBB subtypes showed a much greater contribution to the diversity than did the dimerization rates. This result implies that divergent evolution in phosphorylation reactions rather than in dimerization reactions after whole genome duplications was essential for increasing the diversity of the phosphorylation responses.

Split-enzyme immunoassay to monitor EGFR-HER2 heterodimerization on cell surfaces

Over 30,000 protein-protein interactions with pathological implications have been identified; yet, discovering and investigating drugs that target these specific interactions is greatly limited by the inability to monitor native protein-protein interactions (PPIs) efficiently. The two most frequently used tools to monitor PPIs, resonance-energy transfer (RET) assays and protein complementation assays (PCA), face significant limitations. RET assays have a narrow working range of 10 to 50 Å, while PCA require permanent attachment of a reporter probe to a protein of interest by chemical conjugation or genetic engineering. We developed a non-invasive assay platform to measure PPIs without modifications to the proteins of interest and is functional at a greater working range than RET assays. We demonstrate our approach by monitoring the EGFR-HER2 heterodimerization on relevant cell surfaces, utilizing various EGFR- and HER2-specific binders (e.g., Fab, DARPin, and VHH) fused with small fragments of a tri-part split-luciferase derived from NanoLuc®. Following independent binding of the binder fusions to their respective targets, the dimerization of EGFR and HER2 induces complementation of the luciferase fragments into a functional native structure, producing glow-type luminescence. We have confirmed the functionality of the platform to monitor EGFR-HER2 dimerization induction and inhibition. STATEMENT OF SIGNIFICANCE: We describe a platform technology for rapid monitoring of protein-protein interactions (PPIs). Our approach is uses a luciferase split into three parts - two short peptide "tags" and a large third fragment. Each of the short peptides can be fused to antibodies which bind to domains of a target antigens which orients the two tags and facilitates refolding of an active enzyme. To our knowledge this is the first example of a split-enzyme used to monitor PPIs without requiring any modification of the target proteins. We demonstrate our approach on the important PPI of HER2 and EGFR. Significantly, we quantify stimulation and inhibition of these partners, opening the possibility of using our approach to assess potential drugs without engineering cells.

Genotype Driven Therapy for Non-Small Cell Lung Cancer: Resistance, Pan Inhibitors and Immunotherapy

Eighty-five percent of patients with lung cancer present with Non-small Cell Lung Cancer (NSCLC). Targeted therapy approaches are promising treatments for lung cancer. However, despite the development of targeted therapies using Tyrosine Kinase Inhibitors (TKI) as well as monoclonal antibodies, the five-year relative survival rate for lung cancer patients is still only 18%, and patients inevitably become resistant to therapy. Mutations in Kirsten Ras Sarcoma viral homolog (KRAS) and epidermal growth factor receptor (EGFR) are the two most common genetic events in lung adenocarcinoma; they account for 25% and 20% of cases, respectively. Anaplastic Lymphoma Kinase (ALK) is a transmembrane receptor tyrosine kinase, and ALK rearrangements are responsible for 3-7% of NSCLC, predominantly of the adenocarcinoma subtype, and occur in a mutually exclusive manner with KRAS and EGFR mutations. Among drug-resistant NSCLC patients, nearly half exhibit the T790M mutation in exon 20 of EGFR. This review focuses on some basic aspects of molecules involved in NSCLC, the development of resistance to treatments in NSCLC, and advances in lung cancer therapy in the past ten years. Some recent developments such as PD-1-PD-L1 checkpoint-based immunotherapy for NSCLC are also covered.

The HER3 pathway as a potential target for inhibition in patients with biliary tract cancers

INTRODUCTION

Expression of human epidermal growth factor receptor (HER)2 and HER3 have been investigated in small BTC studies using variable scoring systems.

METHODS

HER2 and HER3 overexpression/amplification were explored following internationally agreed guidelines using immunohistochemistry (IHC) and fluorescent in-situ hybridisation (FISH), respectively. Logistic regression and survival analysis (Kaplan Meier, Log rank test and Cox Regression) were used for statistical analysis.

RESULTS

Sixty-seven eligible patients with Stage I/II (31.3%) or III/IV (68.7%) disease at diagnosis were included. Membrane HER2 overexpression/amplification was identified in 1 patient (1%). HER3 overexpression was predominantly cytoplasmic; the rate of overexpression/amplification of HER3 in membrane and cytoplasm was 16% [ampullary cancer (AMP) (1/13; 8%), gallbladder cancer (GBC) (1/10; 10%), intra-hepatic cholangiocarcinoma (ICC) (6/26; 23%), extra-hepatic cholangiocarcinoma (ECC) (3/18; 17%)] and 24% [AMP (1/13; 8%), GBC (1/10; 10%), ICC (10/26; 38%), ECC (4/18; 22%)], respectively.

CONCLUSIONS

A significant subset of patients with BTC expressed HER3. Inhibition of HER3 warrants further investigation. A better understanding of the downstream effects of HER3 in BTC requires further mechanistic investigations to identify new biomarkers and improve patient selection for future clinical trials.

Homo- and Heterodimerization of Proteins in Cell Signaling: Inhibition and Drug Design

Protein dimerization controls many physiological processes in the body. Proteins form homo-, hetero-, or oligomerization in the cellular environment to regulate the cellular processes. Any deregulation of these processes may result in a disease state. Protein-protein interactions (PPIs) can be inhibited by antibodies, small molecules, or peptides, and inhibition of PPI has therapeutic value. PPI drug discovery research has steadily increased in the last decade, and a few PPI inhibitors have already reached the pharmaceutical market. Several PPI inhibitors are in clinical trials. With advancements in structural and molecular biology methods, several methods are now available to study protein homo- and heterodimerization and their inhibition by drug-like molecules. Recently developed methods to study PPI such as proximity ligation assay and enzyme-fragment complementation assay that detect the PPI in the cellular environment are described with examples. At present, the methods used to design PPI inhibitors can be classified into three major groups: (1) structure-based drug design, (2) high-throughput screening, and (3) fragment-based drug design. In this chapter, we have described some of the experimental methods to study PPIs and their inhibition. Examples of homo- and heterodimers of proteins, their structural and functional aspects, and some of the inhibitors that have clinical importance are discussed. The design of PPI inhibitors of epidermal growth factor receptor heterodimers and CD2-CD58 is discussed in detail.

A peptidomimetic with a chiral switch is an inhibitor of epidermal growth factor receptor heterodimerization

Among different types of EGFR dimers, EGFR-HER2 and HER2-HER3 are well known in different types of cancers. Targeting dimerization of EGFR will have a significant impact on cancer therapies. A symmetric peptidomimetic was designed to inhibit the protein-protein interaction of EGFR. The peptidomimetic (Cyclo(1,10)PpR (R) Anapa-FDDF-(R)-Anapa)R, compound 18) was shown to exhibit antiproliferative activity with an IC₅₀ of 194 nM in HER2-expressing breast cancer cell lines and 18 nM in lung cancer cell lines. The peptidomimetic has a Pro-Pro sequence in the structure to stabilize the β-turn and a β-amino acid, amino napthyl propionic acid. To investigate the effect of the chirality of β-amino acid on the structure of the peptide and its antiproliferative activity, diastereoisomers of compound 18 were designed and synthesized. Structure-activity relationships of these compounds indicated that there is a chiral switch at β-amino acid in the designed compound. The peptidomimetic with R configuration at β-amino acid and with a L-Pro-D-Pro sequence was the most active compound (18). Using enzyme complement fragmentation assay and proximity ligation assay, we show that compound 18 inhibits HER2:HER3 and EGFR:HER2 dimerization. Surface plasmon resonance studies suggested that compound 18 binds to the HER2 extracellular domain and in particular to domain IV. The anticancer activity of compound 18 was evaluated using a xenograft model of breast cancer in mice; compound 18 suppressed the tumor growth in mice compared to control. Compound 18 was also shown to have a synergistic effect with erlotinib on EGFR mutated lung cancer cell lines.

Robustness analysis of the detailed kinetic model of an ErbB signaling network by using dynamic sensitivity

The ErbB receptor signaling pathway plays an important role in the regulation of cellular proliferation, survival and differentiation, and dysregulation of the pathway is linked to various types of human cancer. Mathematical models have been developed as a practical complementary approach to deciphering the complexity of ErbB receptor signaling and elucidating how the pathways discriminate between ligands to induce different cell fates. In this study, we developed a simulator to accurately calculate the dynamic sensitivity of extracellular-signal-regulated kinase (ERK) activity (ERK*) and Akt activity (Akt*), downstream of the ErbB receptors stimulated with epidermal growth factor (EGF) and heregulin (HRG). To demonstrate the feasibility of this simulator, we estimated how the reactions critically responsible for ERK* and Akt* change with time and in response to different doses of EGF and HRG, and predicted that only a small number of reactions determine ERK* and Akt*. ERK* increased steeply with increasing HRG dose until saturation, while showing a gently rising response to EGF. Akt* had a gradual wide-range response to HRG and a blunt response to EGF. Akt* was sensitive to perturbations of intracellular kinetics, while ERK* was more robust due to multiple, negative feedback loops. Overall, the simulator predicted reactions that were critically responsible for ERK* and Akt* in response to the dose of EGF and HRG, illustrated the response characteristics of ERK* and Akt*, and estimated mechanisms for generating robustness in the ErbB signaling network.

EGFR signaling pathways are wired differently in normal 184A1L5 human mammary epithelial and MDA-MB-231 breast cancer cells

Because of differences in the downstream signaling patterns of its pathways, the role of the human epidermal growth factor family of receptors (HER) in promoting cell growth and survival is cell line and context dependent. Using two model cell lines, we have studied how the regulatory interaction network among the key proteins of HER signaling pathways may be rewired upon normal to cancerous transformation. We in particular investigated how the transcription factor STAT3 and several key kinases' involvement in cancer-related signaling processes differ between normal 184A1L5 human mammary epithelial (HME) and MDA-MB-231 breast cancer epithelial cells. Comparison of the responses in these cells showed that normal-to-cancerous cellular transformation causes a major re-wiring of the growth factor initiated signaling. In particular, we found that: i) regulatory interactions between Erk, p38, JNK and STAT3 are triangulated and tightly coupled in 184A1L5 HME cells, and ii) STAT3 is only weakly associated with the Erk-p38-JNK pathway in MDA-MB-231 cells. Utilizing the concept of pathway substitution, we predicted how the observed differences in the regulatory interactions may affect the proliferation/survival and motility responses of the 184A1L5 and MDA-MB-231 cells when exposed to various inhibitors. We then validated our predictions experimentally to complete the experiment-computation-experiment iteration loop. Validated differences in the regulatory interactions of the 184A1L5 and MDA-MB-231 cells indicated that instead of inhibiting STAT3, which has severe toxic side effects, simultaneous inhibition of JNK together with Erk or p38 could be a more effective strategy to impose cell death selectively to MDA-MB-231 cancer cells while considerably lowering the side effects to normal epithelial cells. Presented analysis establishes a framework with examples that would enable cell signaling researchers to identify the signaling network structures which can be used to predict the phenotypic responses in particular cell lines of interest.

Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability

In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 ([Formula: see text]), the convective flow rate of mAb through vascular pores ([Formula: see text]), the endocytic transport rate of mAb through vascular endothelium ([Formula: see text]), the degradation rate of mAb-HER2 complexes ([Formula: see text]) and the concentration of shed HER2 extracellular domain in circulation ([Formula: see text]). [Formula: see text] was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. [Formula: see text] was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability.

A New Method to Study Heterodimerization of Membrane Proteins and Its Application to Fibroblast Growth Factor Receptors

The activity of receptor tyrosine kinases (RTKs) is controlled through their lateral association in the plasma membrane. RTKs are believed to form both homodimers and heterodimers, and the different dimers are believed to play unique roles in cell signaling. However, RTK heterodimers remain poorly characterized, as compared with homodimers, because of limitations in current experimental methods. Here, we develop a FRET-based methodology to assess the thermodynamics of hetero-interactions in the plasma membrane. To demonstrate the utility of the methodology, we use it to study the hetero-interactions between three fibroblast growth factor receptors-FGFR1, FGFR2, and FGFR3-in the absence of ligand. Our results show that all possible FGFR heterodimers form, suggesting that the biological roles of FGFR heterodimers may be as significant as the homodimer roles. We further investigate the effect of two pathogenic point mutations in FGFR3 (A391E and G380R) on heterodimerization. We show that each of these mutations stabilize most of the heterodimers, with the largest effects observed for FGFR3 wild-type/mutant heterodimers. We thus demonstrate that the methodology presented here can yield new knowledge about RTK interactions and can further our understanding of signal transduction across the plasma membrane.

Structure-activity relationships of peptidomimetics that inhibit PPI of HER2-HER3

Human epidermal growth factor receptor-2 (HER2) is a tyrosine kinase family protein receptor that is known to undergo heterodimerization with other members of the family of epidermal growth factor receptors (EGFR) for cell signaling. Overexpression of HER2 and deregulation of signaling has implications in breast, ovarian, and lung cancers. We have designed several peptidomimetics to block the HER2-mediated dimerization, resulting in antiproliferative activity for cancer cells. In this work, we have investigated the structure-activity relationships of peptidomimetic analogs of Compound 5. Compound 5 was conformationally constrained by N- and C-terminal modification and cyclization as well as by substitution with d-amino acids at the N-and C-termini. Among the compounds studied in this work, a peptidomimetic Compound 21 with d-amino acid substitution and its N- and C-termini capped with acetyl and amide functional groups and a reversed sequence compared to that of Compound 5 exhibited better antiproliferative activity in HER2-overexpressed breast, ovarian, and lung cancer cell lines. Compound 21 was further evaluated for its protein-protein interaction (PPI) inhibition ability using enzyme fragment complementation assay, proximity ligation assay, and Western blot analysis. Results suggested that Compound 21 is able to block HER2:HER3 interaction and inhibit phosphorylation of the kinase domain of HER2. The mode of binding of Compound 21 to HER2 protein was modeled using a docking method. Compound 21 seems to bind to domain IV of HER2 near the PPI site of EGFR:HER2, and HER:HER3 and inhibit PPI.

WASF3 provides the conduit to facilitate invasion and metastasis in breast cancer cells through HER2/HER3 signaling

The WASF3 gene is overexpressed in high-grade breast cancer and promotes invasion and metastasis but does not affect proliferation. The HER2/ERBB2/NEU gene is also frequently overexpressed in breast cancer and has been shown to promote invasion and metastasis in these tumors. Here we show that WASF3 in present in the HER2 immunocomplex and suppression of WASF3 function leads to suppression of invasion even in the presence of HER2 expression. Overexpression of both HER2 and WASF3 in non-metastatic MCF7 breast cancer cells promotes invasion and metastasis more significantly than either gene alone. HER2 forms homodimers as well as heterodimers with other HER family members and we now show that the ability of WASF3 to promote invasion is highly dependent on the HER2/HER3 heterodimer. The engagement of WASF3 with the HER2/HER3 complex facilitates its phospho-activation and transcriptional upregulation, which is facilitated by HER2/HER3 activation of JAK/STAT signaling. In breast cancer cells overexpressing HER2, therefore, WASF3 is specifically required to facilitate the invasion/metastasis response. Targeting WASF3, therefore, could be a potential therapeutic approach to suppress metastasis of HER2-overexpressing breast tumors.

Lapatinib Plasma and Tumor Concentrations and Effects on HER Receptor Phosphorylation in Tumor

PURPOSE

The paradigm shift in cancer treatment from cytotoxic drugs to tumor targeted therapies poses new challenges, including optimization of dose and schedule based on a biologically effective dose, rather than the historical maximum tolerated dose. Optimal dosing is currently determined using concentrations of tyrosine kinase inhibitors in plasma as a surrogate for tumor concentrations. To examine this plasma-tumor relationship, we explored the association between lapatinib levels in tumor and plasma in mice and humans, and those effects on phosphorylation of human epidermal growth factor receptors (HER) in human tumors.

EXPERIMENTAL DESIGN

Mice bearing BT474 HER2+ human breast cancer xenografts were dosed once or twice daily (BID) with lapatinib. Drug concentrations were measured in blood, tumor, liver, and kidney. In a randomized phase I clinical trial, 28 treatment-naïve female patients with early stage HER2+ breast cancer received lapatinib 1000 or 1500 mg once daily (QD) or 500 mg BID before evaluating steady-state lapatinib levels in plasma and tumor.

RESULTS

In mice, lapatinib levels were 4-fold higher in tumor than blood with a 4-fold longer half-life. Tumor concentrations exceeded the in vitro IC90 (~ 900 nM or 500 ng/mL) for inhibition of HER2 phosphorylation throughout the 12-hour dosing interval. In patients, tumor levels were 6- and 10-fold higher with QD and BID dosing, respectively, compared to plasma trough levels. The relationship between tumor and plasma concentration was complex, indicating multiple determinants. HER receptor phosphorylation varied depending upon lapatinib tumor concentrations, suggestive of changes in the repertoire of HER homo- and heterodimers.

CONCLUSION

Plasma lapatinib concentrations underestimated tumor drug levels, suggesting that optimal dosing should be focused on the site of action to avoid to inappropriate dose escalation. Larger clinical trials are required to determine optimal dose and schedule to achieve tumor concentrations that maximally inhibit HER receptors.

TRIAL REGISTRATION

CLINICAL TRIAL REGISTRATION

NCT00359190.

Orchestration of ErbB3 signaling through heterointeractions and homointeractions

Members of the ErbB family of receptor tyrosine kinases are capable of both homointeractions and heterointeractions. Because each receptor has a unique set of binding sites for downstream signaling partners and differential catalytic activity, subtle shifts in their combinatorial interplay may have a large effect on signaling outcomes. The overexpression and mutation of ErbB family members are common in numerous human cancers and shift the balance of activation within the signaling network. Here we report the development of a spatial stochastic model that addresses the dynamics of ErbB3 homodimerization and heterodimerization with ErbB2. The model is based on experimental measures for diffusion, dimer off-rates, kinase activity, and dephosphorylation. We also report computational analysis of ErbB3 mutations, generating the prediction that activating mutations in the intracellular and extracellular domains may be subdivided into classes with distinct underlying mechanisms. We show experimental evidence for an ErbB3 gain-of-function point mutation located in the C-lobe asymmetric dimerization interface, which shows enhanced phosphorylation at low ligand dose associated with increased kinase activity.

Effect of phosphorylation on EGFR dimer stability probed by single-molecule dynamics and FRET/FLIM

Deregulation of epidermal growth factor receptor (EGFR) signaling has been correlated with the development of a variety of human carcinomas. EGF-induced receptor dimerization and consequent trans- auto-phosphorylation are among the earliest events in signal transduction. Binding of EGF is thought to induce a conformational change that consequently unfolds an ectodomain loop required for dimerization indirectly. It may also induce important allosteric changes in the cytoplasmic domain. Despite extensive knowledge on the physiological activation of EGFR, the effect of targeted therapies on receptor conformation is not known and this particular aspect of receptor function, which can potentially be influenced by drug treatment, may in part explain the heterogeneous clinical response among cancer patients. Here, we used Förster resonance energy transfer/fluorescence lifetime imaging microscopy (FRET/FLIM) combined with two-color single-molecule tracking to study the effect of ATP-competitive small molecule tyrosine kinase inhibitors (TKIs) and phosphatase-based manipulation of EGFR phosphorylation on live cells. The distribution of dimer on-times was fitted to a monoexponential to extract dimer off-rates (koff). Our data show that pretreatment with gefitinib (active conformation binder) stabilizes the EGFR ligand-bound homodimer. Overexpression of EGFR-specific DEP-1 phosphatase was also found to have a stabilizing effect on the homodimer. No significant difference in the koff of the dimer could be detected when an anti-EGFR antibody (425 Snap single-chain variable fragment) that allows for dimerization of ligand-bound receptors, but not phosphorylation, was used. These results suggest that both the conformation of the extracellular domain and phosphorylation status of the receptor are involved in modulating the stability of the dimer. The relative fractions of these two EGFR subpopulations (interacting versus free) were obtained by a fractional-intensity analysis of ensemble FRET/FLIM images. Our combined imaging approach showed that both the fraction and affinity (surrogate of conformation at a single-molecule level) increased after gefitinib pretreatment or DEP-1 phosphatase overexpression. Using an EGFR mutation (I706Q, V948R) that perturbs the ability of EGFR to dimerize intracellularly, we showed that a modest drug-induced increase in the fraction/stability of the EGFR homodimer may have a significant biological impact on the tumor cell's proliferation potential.

Dimerization drives EGF receptor endocytosis through two sets of compatible endocytic codes

We have shown that epidermal growth factor (EGF) receptor (EGFR) endocytosis is controlled by EGFR dimerization. However, it is not clear how the dimerization drives receptor internalization. We propose that EGFR endocytosis is driven by dimerization, bringing two sets of endocytic codes, one contained in each receptor monomer, in close proximity. Here, we tested this hypothesis by generating specific homo- or hetero-dimers of various receptors and their mutants. We show that ErbB2 and ErbB3 homodimers are endocytosis-deficient due to the lack of endocytic codes. Interestingly, EGFR-ErbB2 or EGFR-ErbB3 heterodimers are also endocytosis-deficient. Moreover, the heterodimer of EGFR and the endocytosis-deficient mutant EGFRΔ1005–1017 is also impaired in endocytosis. These results indicate that two sets of endocytic codes are required for receptor endocytosis. We found that an EGFR/PDGFR heterodimer is endocytosis-deficient, although both EGFR and PDGFR homodimers are endocytosis-competent, indicating that two compatible sets of endocytic codes are required. Finally, we found that to mediate the endocytosis of the receptor dimer, the two sets of compatible endocytic codes, one contained in each receptor molecule, have to be spatially coordinated.

The ErbB4 CYT2 variant protects EGFR from ligand-induced degradation to enhance cancer cell motility

The epidermal growth factor receptor (EGFR) is a member of the ErbB family that can promote the migration and proliferation of breast cancer cells. Therapies that target EGFR can promote the dimerization of EGFR with other ErbB receptors, which is associated with the development of drug resistance. Understanding how interactions among ErbB receptors alter EGFR biology could provide avenues for improving cancer therapy. We found that EGFR interacted directly with the CYT1 and CYT2 variants of ErbB4 and the membrane-anchored intracellular domain (mICD). The CYT2 variant, but not the CYT1 variant, protected EGFR from ligand-induced degradation by competing with EGFR for binding to a complex containing the E3 ubiquitin ligase c-Cbl and the adaptor Grb2. Cultured breast cancer cells overexpressing both EGFR and ErbB4 CYT2 mICD exhibited increased migration. With molecular modeling, we identified residues involved in stabilizing the EGFR dimer. Mutation of these residues in the dimer interface destabilized the complex in cells and abrogated growth factor-stimulated cell migration. An exon array analysis of 155 breast tumors revealed that the relative mRNA abundance of the ErbB4 CYT2 variant was increased in ER+ HER2- breast cancer patients, suggesting that our findings could be clinically relevant. We propose a mechanism whereby competition for binding to c-Cbl in an ErbB signaling heterodimer promotes migration in response to a growth factor gradient.

Systems analysis of drug-induced receptor tyrosine kinase reprogramming following targeted mono- and combination anti-cancer therapy

The receptor tyrosine kinases (RTKs) are key drivers of cancer progression and targets for drug therapy. A major challenge in anti-RTK treatment is the dependence of drug effectiveness on co-expression of multiple RTKs which defines resistance to single drug therapy. Reprogramming of the RTK network leading to alteration in RTK co-expression in response to drug intervention is a dynamic mechanism of acquired resistance to single drug therapy in many cancers. One route to overcome this resistance is combination therapy. We describe the results of a joint in silico, in vitro, and in vivo investigations on the efficacy of trastuzumab, pertuzumab and their combination to target the HER2 receptors. Computational modelling revealed that these two drugs alone and in combination differentially suppressed RTK network activation depending on RTK co-expression. Analyses of mRNA expression in SKOV3 ovarian tumour xenograft showed up-regulation of HER3 following treatment. Considering this in a computational model revealed that HER3 up-regulation reprograms RTK kinetics from HER2 homodimerisation to HER3/HER2 heterodimerisation. The results showed synergy of the trastuzumab and pertuzumab combination treatment of the HER2 overexpressing tumour can be due to an independence of the combination effect on HER3/HER2 composition when it changes due to drug-induced RTK reprogramming.

erbB3 is an active tyrosine kinase capable of homo- and heterointeractions

Often considered to be a "dead" kinase, erbB3 is implicated in escape from erbB-targeted cancer therapies. Here, heregulin stimulation is shown to markedly upregulate kinase activity in erbB3 immunoprecipitates. Intact, activated erbB3 phosphorylates tyrosine sites in an exogenous peptide substrate, and this activity is abolished by mutagenesis of lysine 723 in the catalytic domain. Enhanced erbB3 kinase activity is linked to heterointeractions with catalytically active erbB2, since it is largely blocked in cells pretreated with lapatinib or pertuzumab. erbB2 activation of erbB3 is not dependent on equal surface levels of these receptors, since it occurs even in erbB3-transfected CHO cells with disproportionally small amounts of erbB2. We tested a model in which transient erbB3/erbB2 heterointeractions set the stage for erbB3 homodimers to be signaling competent. erbB3 homo- and heterodimerization events were captured in real time on live cells using single-particle tracking of quantum dot probes bound to ligand or hemagglutinin tags on recombinant receptors.

Profiling epidermal growth factor receptor and heregulin receptor 3 heteromerization using receptor tyrosine kinase heteromer investigation technology

Heteromerization can play an important role in regulating the activation and/or signal transduction of most forms of receptors, including receptor tyrosine kinases (RTKs). The study of receptor heteromerization has evolved extensively with the emergence of resonance energy transfer based approaches such as bioluminescence resonance energy transfer (BRET). Here, we report an adaptation of our Receptor-Heteromer Investigation Technology (Receptor-HIT) that has recently been published as the G protein-coupled receptor (GPCR) Heteromer Identification Technology (GPCR-HIT). We now demonstrate the utility of this approach for investigating RTK heteromerization by examining the functional interaction between the epidermal growth factor (EGF) receptor (EGFR; also known as erbB1/HER1) and heregulin (HRG) receptor 3 (HER3; also known as erbB3) in live HEK293FT cells using recruitment of growth factor receptor-bound protein 2 (Grb2) to the activated receptors. We found that EGFR and HER3 heteromerize specifically as demonstrated by HRG inducing a BRET signal between EGFR/Rluc8 and Grb2/Venus only when HER3 was co-expressed. Similarly, EGF stimulation promoted a specific BRET signal between HER3/Rluc8 and Grb2/Venus only when EGFR was co-expressed. Both EGF and HRG effects on Grb2 interaction are dose-dependent, and specifically blocked by EGFR inhibitor AG-1478. Furthermore, truncation of HER3 to remove the putative Grb2 binding sites appears to abolish EGF-induced Grb2 recruitment to the EGFR-HER3 heteromer. Our results support the concept that EGFR interacts with Grb2 in both constitutive and EGF-dependent manners and this interaction is independent of HER3 co-expression. In contrast, HER3-Grb2 interaction requires the heteromerization between EGFR and HER3. These findings clearly indicate the importance of EGFR-HER3 heteromerization in HER3-mediated Grb2-dependent signaling pathways and supports the central role of HER3 in the diversity and regulation of HER family functioning.

Influences of excluded volume of molecules on signaling processes on the biomembrane

We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by monotonically increasing; increasing then decreasing in a bell-shaped curve; or increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.

A comprehensive, multi-scale dynamical model of ErbB receptor signal transduction in human mammary epithelial cells

The non-receptor tyrosine kinase Src and receptor tyrosine kinase epidermal growth factor receptor (EGFR/ErbB1) have been established as collaborators in cellular signaling and their combined dysregulation plays key roles in human cancers, including breast cancer. In part due to the complexity of the biochemical network associated with the regulation of these proteins as well as their cellular functions, the role of Src in EGFR regulation remains unclear. Herein we present a new comprehensive, multi-scale dynamical model of ErbB receptor signal transduction in human mammary epithelial cells. This model, constructed manually from published biochemical literature, consists of 245 nodes representing proteins and their post-translational modifications sites, and over 1,000 biochemical interactions. Using computer simulations of the model, we find it is able to reproduce a number of cellular phenomena. Furthermore, the model predicts that overexpression of Src results in increased endocytosis of EGFR in the absence/low amount of the epidermal growth factor (EGF). Our subsequent laboratory experiments also suggest increased internalization of EGFR upon Src overexpression under EGF-deprived conditions, further supporting this model-generated hypothesis.

The F-BAR protein PACSIN2 regulates epidermal growth factor receptor internalization

Signaling via growth factor receptors, including the epidermal growth factor (EGF) receptor, is key to various cellular processes, such as proliferation, cell survival, and cell migration. In a variety of human diseases such as cancer, aberrant expression and activation of growth factor receptors can lead to disturbed signaling. Intracellular trafficking is crucial for proper signaling of growth factor receptors. As a result, the level of cell surface expression of growth factor receptors is an important determinant for the outcome of downstream signaling. BAR domain-containing proteins represent an important family of proteins that regulate membrane dynamics. In this study, we identify a novel role for the F-BAR protein PACSIN2 in the regulation of EGF receptor signaling. We show that internalized EGF as well as the (activated) EGF receptor translocated to PACSIN2-positive endosomes. Furthermore, loss of PACSIN2 increased plasma membrane expression of the EGF receptor in resting cells and increased EGF-induced phosphorylation of the EGF receptor. As a consequence, EGF-induced activation of Erk and Akt as well as cell proliferation were enhanced in PACSIN2-depleted cells. In conclusion, this study identifies a novel role for the F-BAR-domain protein PACSIN2 in regulating EGF receptor surface levels and EGF-induced downstream signaling.

Integrated experimental and model-based analysis reveals the spatial aspects of EGFR activation dynamics

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models to determine the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: (1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, (2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and (3) receptor phosphorylation kinetics at the cell surface and early endosomes are comparable. We validated the last finding by measuring the EGFR dephosphorylation rates at various times following ligand addition both in whole cells and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks.

Inhibition of protein-protein interaction of HER2-EGFR and HER2-HER3 by a rationally designed peptidomimetic

Protein-protein interactions (PPI) play a crucial role in many biological processes and modulation of PPI using small molecules to target hot spots has therapeutic value. As a model system we will use PPI of human epidermal growth factor receptors (EGFRs). Among the four EGFRs, EGFR-HER2 and HER2-HER3 are well known in cancer. We have designed a small molecule that is targeted to modulate HER2-mediated signaling. Our approach is novel because the small molecule designed disrupts dimerization not only of EGFR-HER2, but also of HER2-HER3. In the present study we have shown, using surface plasmon resonance analysis, that a peptidomimetic, compound 5, binds specifically to HER2 protein extracellular domain and disrupts the dimerization of EGFRs. To evaluate the effect of compound 5 on HER2 signaling in vitro, Western blot and PathHunter assays were used. Results indicated that compound 5 inhibits the phosphorylation of HER2 kinase domain and inhibits the heterodimerization in a dose-dependent manner. Molecular modeling methods were used to model the PPI of HER2-HER3 heterodimer.

Model-based selection of the robust JAK-STAT activation mechanism

JAK-STAT pathway family is a principal signaling mechanism in eukaryotic cells. Evolutionary conserved roles of this mechanism include control over fundamental processes such as cell growth or apoptosis. Deregulation of the JAK-STAT signaling is frequently associated with cancerogenesis. JAK-STAT pathways become hyper-activated in many human tumors. Therefore, components of these pathways are an attractive target for drugs, which design requires as adequate models as possible. Although, in principle, JAK-STAT signaling is relatively simple, the ambiguities in a receptor activation prevent a clear explanation of the underlying molecular mechanism. Here, we compare four variants of a computational model of the JAK1/2-STAT1 signaling pathway. These variants capture known, basic discrepancies in the mechanism of activation of a cytokine receptor, in the context of all key components of the pathway. We carry out a comparative analysis using mass action kinetics. The investigated differences are so marginal that all models satisfy a goodness of fit criteria to the extent that the state of the art Bayesian model selection (BMS) method fails to significantly promote one model. Therefore, we comparatively investigate changes in a robustness of the JAK1/2-STAT1 pathway variants using the global sensitivity analysis method (GSA), complemented with the identifiability analysis (IA). Both BMS and GSA are used to analyze the models for the varying parameter values. We found out that, both BMS and GSA, narrowed down to the receptor activation component, slightly promote the least complex model. Further, insightful, comprehensive GSA, motivated by the concept of robustness, allowed us to show that the precise order of reactions of a ligand binding and a receptor dimerization is not as important as the on-membrane pre-assembly of the dimers in the absence of ligand. The main value of this work is an evaluation of the usefulness of different model selection methods in a frequently encountered, but not much discussed case of a model of a considerable size, which has several variants differing at peripheries. In such situation, all considered variants can reach nearly perfect agreement with respect to their numerical simulations results and, most often, the sufficient experimental data to test against is not available. We argue that in such an adverse setting, the GSA and IA, although not directly corresponding to the model selection problem, can be more informative than the representative, generalizability-based approaches to this task. An additional insight into how the responsibility for the network dynamics spreads among model parameters, enables more conscious, expert-mediated choice of the preferred model.

Tav4SB: integrating tools for analysis of kinetic models of biological systems

Background

Progress in the modeling of biological systems strongly relies on the availability of specialized computer-aided tools. To that end, the Taverna Workbench eases integration of software tools for life science research and provides a common workflow-based framework for computational experiments in Biology.

Results

The Taverna services for Systems Biology (Tav4SB) project provides a set of new Web service operations, which extend the functionality of the Taverna Workbench in a domain of systems biology. Tav4SB operations allow you to perform numerical simulations or model checking of, respectively, deterministic or stochastic semantics of biological models. On top of this functionality, Tav4SB enables the construction of high-level experiments. As an illustration of possibilities offered by our project we apply the multi-parameter sensitivity analysis. To visualize the results of model analysis a flexible plotting operation is provided as well. Tav4SB operations are executed in a simple grid environment, integrating heterogeneous software such as Mathematica, PRISM and SBML ODE Solver. The user guide, contact information, full documentation of available Web service operations, workflows and other additional resources can be found at the Tav4SB project’s Web page: http://bioputer.mimuw.edu.pl/tav4sb/.

Conclusions

The Tav4SB Web service provides a set of integrated tools in the domain for which Web-based applications are still not as widely available as for other areas of computational biology. Moreover, we extend the dedicated hardware base for computationally expensive task of simulating cellular models. Finally, we promote the standardization of models and experiments as well as accessibility and usability of remote services.

An adaptive coarse graining method for signal transduction in three dimensions

The spatio-temporal landscape of the plasma membrane regulates activation and signal transduction of membrane bound receptors by restricting their two-dimensional mobility and by inducing receptor clustering. This regulation also extends to complex formation between receptors and adaptor proteins, which are the intermediate signaling molecules involved in cellular signaling that relay the received cues from cell surface to cytoplasm and eventually to the nucleus. Although their investigation poses challenging technical difficulties, there is a crucial need to understand the impact of the receptor diffusivity, clustering, and spatial heterogeneity, and of receptor-adaptor protein complex formation on the cellular signal transduction patterns. Building upon our earlier studies, we have developed an adaptive coarse-grained Monte Carlo method that can be used to investigate the role of diffusion, clustering and membrane corralling on receptor association and receptor-adaptor protein complex formation dynamics in three dimensions. The new Monte Carlo lattice based approach allowed us to introduce spatial resolution on the 2-D plasma membrane and to model the cytoplasm in three-dimensions. Being a multi-resolution approach, our new method makes it possible to represent various parts of the cellular system at different levels of detail and enabled us to utilize the locally homogeneous assumption when justified (e.g., cytoplasmic region away from the cell membrane) and avoid its use when high spatial resolution is needed (e.g., cell membrane and cytoplasmic region near the membrane) while keeping the required computational complexity manageable. Our results have shown that diffusion has a significant impact on receptor-receptor dimerization and receptor-adaptor protein complex formation kinetics. We have observed an "adaptor protein hopping" mechanism where the receptor binding proteins may hop between receptors to form short-lived transient complexes. This increased residence time of the adaptor proteins near cell membrane and their ability to frequently change signaling partners may explain the increase in signaling efficiency when receptors are clustered. We also hypothesize that the adaptor protein hopping mechanism can cause concurrent or sequential activation of multiple signaling pathways, thus leading to crosstalk between diverse biological functions.

ErbB1 dimerization is promoted by domain co-confinement and stabilized by ligand binding

The extent to which ligand occupancy and dimerization contribute to erbB1 signaling is controversial. To examine this, we utilized two-color Quantum Dot tracking for visualization of erbB1 homodimerization and quantification of the dimer off rate (k_off) on living cells. Kinetic parameters were extracted using a 3-state Hidden Markov Model to identify transition rates between free, co-confined, and dimerized states. We report that dimers composed of 2 ligand-bound receptors are long-lived and their k_off is independent of kinase activity. By comparison, unliganded dimers have >4-fold faster k_off. Transient co-confinement of receptors promotes repeated encounters and enhances dimer formation. Mobility decreases >6-fold when ligand-bound receptors dimerize. Blockade of erbB1 kinase activity or disruption of actin networks results in faster diffusion of receptor dimers. These results implicate both signal propagation and the cortical cytoskeleton in reduced mobility of signaling-competent erbB1 dimers.

Cross-talk and modulation of signaling between somatostatin and growth factor receptors

The process of homo- and/or heterodimerization of G-protein coupled receptors (GPCRs) and receptor tyrosine kinase (RTK) families are crucial for implicating the fundamental properties of receptor proteins including receptor expression, trafficking, and desensitization as well as signal transduction. The members of GPCR and RTK family constitute largest cell surface receptor proteins and regulate physiological functions of cells in response to external and internal stimuli. Notably, GPCRs and RTKs play major role in regulation of several key cellular functions which are associated with several pathological conditions including cancer biology, neurodegenerative and cardiovascular diseases. The focus of this review is to highlight the recent findings on the possible cross-talk between somatostatin receptors (members of GPCR family) and growth factor receptors like epidermal growth factor receptors (members of RTK family). Furthermore, functional consequences of such an interaction in modulation of signaling pathways linked to pathological conditions specifically in cancer are discussed.

Dissociation of epidermal growth factor receptor and ErbB2 heterodimers in the presence of somatostatin receptor 5 modulate signaling pathways

Epidermal growth factor through the stimulation of epidermal growth factor receptor (EGFR) plays a critical role in the activation of MAPKs and phosphatidylinositol-3-protein kinase/AKT cell survival pathways attributed in many pathological conditions. At the cellular level, such functions involve EGFR overactivation and phosphorylation. In the present study, we describe that human embryonic kidney-293 cells transfected with somatostatin (SST) receptor 5 (SSTR5) exhibit inhibition of EGFR phosphorylation and modulate MAPK and phosphatidylinositol-3-protein kinase/AKT cell survival signaling. Furthermore, suppression of EGFR by using small interference RNA and an antagonist (AG1478) potentiates the SST effect via activation of SSTR5 on signaling molecules. In wild-type human embryonic kidney-293 cells, EGFR/ErbB2 exists as constitutive heterodimers. The presence of SSTR5 leads to the dissociation of the heteromeric complex of EGFR/ErbB2 and display preferential heterodimerization between SSTR5 and EGFR in an agonist-dependent manner. These findings highlight a new undiscovered mechanism and potential role of SSTR5 to attenuate the EGFR-mediated signaling pathways involved in tumorigenesis. Our data indicate that the activation and/or overexpression of SST receptors along with the inhibition of EGFR will serve as an important therapeutic approach in the treatment of ErbB-positive tumors.

Spatial aspects in biological system simulations

Mathematical models of the dynamical properties of biological systems aim to improve our understanding of the studied system with the ultimate goal of being able to predict system responses in the absence of experimentation. Despite the enormous advances that have been made in biological modeling and simulation, the inherently multiscale character of biological systems and the stochasticity of biological processes continue to present significant computational and conceptual challenges. Biological systems often consist of well-organized structural hierarchies, which inevitably lead to multiscale problems. This chapter introduces and discusses the advantages and shortcomings of several simulation methods that are being used by the scientific community to investigate the spatiotemporal properties of model biological systems. We first describe the foundations of the methods and then describe their relevance and possible application areas with illustrative examples from our own research. Possible ways to address the encountered computational difficulties are also discussed.

Phosphoproteomics-based modeling defines the regulatory mechanism underlying aberrant EGFR signaling

Background

Mutation of the epidermal growth factor receptor (EGFR) results in a discordant cell signaling, leading to the development of various diseases. However, the mechanism underlying the alteration of downstream signaling due to such mutation has not yet been completely understood at the system level. Here, we report a phosphoproteomics-based methodology for characterizing the regulatory mechanism underlying aberrant EGFR signaling using computational network modeling.

Methodology/Principal Findings

Our phosphoproteomic analysis of the mutation at tyrosine 992 (Y992), one of the multifunctional docking sites of EGFR, revealed network-wide effects of the mutation on EGF signaling in a time-resolved manner. Computational modeling based on the temporal activation profiles enabled us to not only rediscover already-known protein interactions with Y992 and internalization property of mutated EGFR but also further gain model-driven insights into the effect of cellular content and the regulation of EGFR degradation. Our kinetic model also suggested critical reactions facilitating the reconstruction of the diverse effects of the mutation on phosphoproteome dynamics.

Conclusions/Significance

Our integrative approach provided a mechanistic description of the disorders of mutated EGFR signaling networks, which could facilitate the development of a systematic strategy toward controlling disease-related cell signaling.

HER-2 signaling, acquisition of growth factor independence, and regulation of biological networks associated with cell transformation

Activated oncogenes are the dominant drivers of malignant progression in human cancer, yet little is known about how the transformation from proto-oncogene to activated oncogene drives the expression of transformed phenotypes. An isogenic model of HER-2-mediated transformation of human mammary epithelial cells was used along with HER-2-amplified human breast cancers to investigate how HER-2 activation alters its properties as a signaling molecule and changes the networks of HER-2-regulated genes. Our results show that full oncogenic activation of HER-2 is the result of a transition in which activated HER-2 acquires dominant signaling properties that qualitatively alter the network of genes regulated by the activated oncogene compared with the proto-oncogene. Consequently, gene expression programs related to invasion, cell stress, and stemness become regulated by HER-2 in a manner not observed in nontransformed cells, even when HER-2 is overexpressed. Our results offer novel insights into biological processes that come under the control of HER-2 after it acquires full oncogenic potential.

Spatio-temporal modeling of signaling protein recruitment to EGFR

Background

A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.

Results

The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCγ1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.

Conclusions

Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

Cancer systems biology

Cancer is a complex and heterogeneous disease, not only at a genetic and biochemical level, but also at a tissue, organism, and population level. Multiple data streams, from reductionist biochemistry in vitro to high-throughput "-omics" from clinical material, have been generated with the hope that they encode useful information about phenotype and, ultimately, tumour behaviour in response to drugs. While these data stand alone in terms of the biology they represent, there is the enticing prospect that if incorporated into systems biology models, they can help understand complex systems behaviour and provide a predictive framework as an additional tool in understanding how tumours change and respond to treatment over time. Since these biological data are heterogeneous and frequently qualitative rather than quantitative, at the present time a single systems biology approach is unlikely to be effective; instead, different computational and mathematical approaches should be tailored to different types of data, and to each other, in order to test and re-test hypotheses. In time, these models might converge and result in usable tractable models which accurately represent human cancer. Likewise, biologists and clinicians need to understand what the requirements of systems biology are so that compatible data are produced for computational modelling. In this review, we describe some theoretical approaches (data-driven and process-driven) and experimental methodologies which are being used in cancer research and the clinical context where they might be applied.

Rapid and sustained nuclear-cytoplasmic ERK oscillations induced by epidermal growth factor

Although the ERK pathway has a central role in the response of cells to growth factors, its regulatory structure and dynamics are incompletely understood. To investigate ERK activation in real time, we expressed an ERK–GFP fusion protein in human mammary epithelial cells. On EGF stimulation, we observed sustained oscillations of the ERK–GFP fusion protein between the nucleus and cytoplasm with a periodicity of ∼15 min. The oscillations were persistent (>45 cycles), independent of cell cycle phase, and were highly dependent on cell density, essentially disappearing at confluency. Oscillations occurred even at ligand doses that elicited very low levels of ERK phosphorylation, and could be detected biochemically in both transfected and nontransfected cells. Mathematical modeling revealed that negative feedback from phosphorylated ERK to the cascade input was necessary to match the robustness of the oscillation characteristics observed over a broad range of ligand concentrations. Our characterization of single-cell ERK dynamics provides a quantitative foundation for understanding the regulatory structure of this signaling cascade.

HER/ErbB receptor interactions and signaling patterns in human mammary epithelial cells

BACKGROUND

Knowledge about signaling pathways is typically compiled based on data gathered using different cell lines. This approach implicitly assumes that the cell line dependence is not important. However, different cell lines do not always respond to a particular stimulus in the same way, and lack of coherent data collected from closely related cellular systems can be detrimental to the efforts to understand the regulation of biological processes. To address this issue, we created a clone library of human mammary epithelial (HME) cells that expresses different levels of HER2 and HER3 receptors in combination with endogenous EGFR/HER1. Using our clone library, we have quantified the receptor activation patterns and systematically tested the validity of the existing hypotheses about the interaction patterns between HER1-3 receptors.

RESULTS

Our study identified HER2 as the dominant dimerization partner for both EGFR and HER3. Contrary to earlier suggestions, we find that lateral interactions with HER2 do not lead to strong transactivation between EGFR and HER3, i.e., EGFR activation and HER3 activation are only weakly linked in HME cells. We also find that observed weak transactivation is uni-directional where stimulation of EGFR leads to HER3 activation whereas HER3 stimulation does not activate the EGFR. Repeating our experiments at lower cell confluency established that cell confluency is not a major factor in the observed interaction patterns. We have also quantified the dependence of the kinetics of Erk and Akt activation on different HER receptors. We found that HER3 signaling makes the strongest contribution to Akt activation and that, stimulation of either EGFR or HER3 leads to significant Erk activation.

CONCLUSION

Our study shows that clone cell libraries can be a powerful resource in systems biology research by making it possible to differentiate between various hypotheses in a consistent cellular background. Using our constructed clone library we profiled the cell signaling patterns to establish the role of HER2 in the crosstalk between EGFR and HER3 receptors in HME cells. Our results for HME cells show that the weak linkage between EGFR and HER3 pathways can lead to distinct downstream cellular signaling patterns in response to the ligands of these two receptors.

Oncogenic EGFR signaling networks in glioma

The epidermal growth factor receptor (EGFR) is a primary contributor to glioblastoma (GBM) initiation and progression. Here, we examine how EGFR and key downstream signaling networks contribute to the hallmark characteristics of GBM such as rapid cancer cell proliferation and diffused invasion. Additionally, we discuss current therapeutic options for GBM patients and elaborate on the mechanisms through which EGFR promotes chemoresistance. We conclude by offering a perspective on how the potential of integrative systems biology may be harnessed to develop safe and effective treatment strategies for this disease.

Functional genomics and proteomics approaches to study the ERBB network in cancer

Substantial progress in functional genomic and proteomic technologies has opened new perspectives in biomedical research. The sequence of the human genome has been mostly determined and opened new visions on its complexity and regulation. New technologies, like RNAi and protein arrays, allow gathering knowledge beyond single gene analysis. Increasingly, biological processes are studied with systems biological approaches, where qualitative and quantitative data of the components are utilized to model the respective processes, to predict effects of perturbations, and to then refine these models after experimental testing. Here, we describe the potential of applying functional genomics and proteomics, taking the ERBB family of growth-factor receptors as an example to study the signaling network and its impact on cancer.

Stochastic simulations of ErbB homo and heterodimerisation: potential impacts of receptor conformational state and spatial segregation

ErbB overexpression is linked to carcinogenesis. It is hypothesised that this is due to increased receptor density and receptor clustering, leading to increased receptor dimerisation and activation. Herein, spatial stochastic simulations have been performed to shed light receptor dimerisation processes. First, ligand-independent homodimerisation, is considered, based upon constitutive oligomerisation estimates (14%) in A431 cells that overexpress epidermal growth factor receptor (EGFR). When autocrine stimulation is blocked, ligand-independent EGFR activation is demonstrated by persistent, low levels of phosphorylation. The possibility that ligand-independent signalling is due to the fluctuation of EGFR conformation is considered. The agent-based model predicts the frequency (expressed as a probability) that uniformly distributed receptors would need to flux to the open conformation to reach 14% EGFR dimers at high receptor density. Simulations suggest that ligand-independent EGFR homodimerisation is highly density dependent, since collisions between 'open', dimerisation-competent receptors are a rare event at low receptor levels. Simulations that incorporate receptor clustering lower the threshold for homodimerisation of unoccupied receptors as well as the estimate of the probability for fluxing to the dimer-competent conformation. The impact of ErbB receptor clustering patterns on hetero and homodimerisation rates is also considered, using immunoelectron microscopy data derived from SKBR3 breast cancer cells that express ErbB2>>EGFR>ErbB3. Partial spatial segregation of ErbB receptors has a profound effect on simulated heterodimerisation rates. Despite the general assumption that ErbB2 is a preferred heterodimerising partner for other ErbBs, it is predicted that most ErbB2 will form homodimers. Overall, it is proposed that both receptor density and membrane spatial organisation contribute to the carcinogenesis process.

System theoretical investigation of human epidermal growth factor receptor-mediated signalling

The partitioning of biological networks into coupled-functional modules is being increasingly applied for developing predictive models of biological systems. This approach has the advantage that predicting a system-level response does not require a mechanistic description of the internal dynamics of each module. Identification of the input-output characteristics of the network modules and the connectivity between the modules provide the necessary quantitative representation of system dynamics. However, the determination of the input-output relationships of the modules is not trivial; it requires the controlled perturbation of module inputs and systematic analysis of experimental data. In this report, the authors apply a system theoretical analysis approach to derive the time-dependent input-output relationships of the functional module for the human epidermal growth factor receptor (HER) mediated Erk and Akt signalling pathways. Using a library of cell lines expressing endogenous levels of epidermal growth factor receptor (EGFR) and varying levels of HER2, the authors show that a transfer function-based representation can be successfully applied to quantitatively characterise information transfer in this system.

Multiple mechanisms are responsible for transactivation of the epidermal growth factor receptor in mammary epithelial cells

The number of distinct signaling pathways that can transactivate the epidermal growth factor receptor (EGFR) in a single cell type is unclear. Using a single strain of human mammary epithelial cells, we found that a wide variety of agonists, such as lysophosphatidic acid (LPA), uridine triphosphate, growth hormone, vascular endothelial growth factor, insulin-like growth factor-1 (IGF-1), and tumor necrosis factor-alpha, require EGFR activity to induce ERK phosphorylation. In contrast, hepatocyte growth factor can stimulate ERK phosphorylation independent of the EGFR. EGFR transactivation also correlated with an increase in cell proliferation and could be inhibited with metalloprotease inhibitors. However, there were significant differences with respect to transactivation kinetics and sensitivity to different inhibitors. In particular, IGF-1 displayed relatively slow transactivation kinetics and was resistant to inhibition by the selective ADAM-17 inhibitor WAY-022 compared with LPA-induced transactivation. Studies using anti-ligand antibodies showed that IGF-1 transactivation required amphiregulin production, whereas LPA was dependent on multiple ligands. Direct measurement of ligand shedding confirmed that LPA treatment stimulated shedding of multiple EGFR ligands, but paradoxically, IGF-1 had little effect on the shedding rate of any ligand, including amphiregulin. Instead, IGF-1 appeared to work by enhancing EGFR activation of Ras in response to constitutively produced amphiregulin. This enhancement of EGFR signaling was independent of both receptor phosphorylation and PI-3-kinase activity, suggestive of a novel mechanism. Our studies demonstrate that within a single cell type, the EGFR autocrine system can couple multiple signaling pathways to ERK activation and that this modulation of EGFR autocrine signaling can be accomplished at multiple regulatory steps.

Quantitative modeling perspectives on the ErbB system of cell regulatory processes

The complexities of the processes involved in ErbB-mediated regulation of cellular phenotype are broadly appreciated, so much so that it might be reasonably argued that this highly studied system provided significant impetus for the systems perspective on cell signaling processes in general. Recent years have seen major advances in the level of characterization of the ErbB system as well as our ability to make measurements of the system. This new data provides significant new insight, while at the same time creating new challenges for making quantitative statements and predictions with certainty. Here, we discuss recent advances in each of these directions and the interplay between them, with a particular focus on quantitative modeling approaches to interpret data and provide predictive power. Our discussion follows the sequential order of ErbB pathway activation, beginning with considerations of receptor/ligand interactions and dynamics, proceeding to the generation of intracellular signals, and ending with determination of cellular phenotype. As discussed herein, these processes become increasingly difficult to describe or interpret in terms of traditional models, and we review emerging methodologies to address this complexity.

Quantifying the effects of co-expressing EGFR and HER2 on HER activation and trafficking

The human epidermal growth factor receptor (HER) system is an intricately regulated system that plays critical roles in development and tumorigenesis. Here, we apply integrated experimentation and modeling to analyze HER receptor activation in a panel of cell lines expressing endogenous levels of EGFR/HER1 and different levels of HER2. A mathematical model that includes the fundamental processes involved in receptor activation and trafficking was used to fit the experimental data, and values of the independent parameters for active receptor dimer formation affinities, trafficking rates and relative phosphorylation levels were estimated. Obtained parameter values quantitatively support the existing ideas on the effect of HER2 on EGFR dynamics, and enable us to predict the abundances of various phosphorylated receptor dimers in the cell lines.