Dynamics of p53 and NF-κB regulation in response to DNA damage and identification of target proteins suitable for therapeutic intervention

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Activation of p53 signaling and regression of breast and prostate carcinoma cells by spirooxindole-benzimidazole small molecules

This study discusses the synthesis and use of a new library of spirooxindole-benzimidazole compounds as inhibitors of the signal transducer and activator of p53, a protein involved in regulating cell growth and cancer prevention. The text includes the scientific details of the [3 + 2] cycloaddition (32CA) reaction between azomethine ylide 7a and ethylene 3a within the framework of Molecular Electron Density Theory. The mechanism of the 32CA reaction proceeds through a two-stage one-step process, with emphasis on the highly asynchronous transition state structure. The anti-cancer properties of the synthesized compounds, particularly 6a and 6d, were evaluated. The inhibitory effects of these compounds on the growth of tumor cells (MDA-MB 231 and PC-3) were quantified using IC50 values. This study highlights activation of the p53 pathway by compounds 6a and 6d, leading to upregulation of p53 expression and downregulation of cyclin D and NF-κB in treated cells. Additionally, we explored the binding affinity of spirooxindole analogs, particularly compound 6d, to MDM2, a protein involved in regulation of p53. The binding mode and position of compound 6d were compared with those of a co-crystallized standard ligand, suggesting its potential as a lead compound for further preclinical research.

A computational model of the DNA damage-induced IKK/ NF-κB pathway reveals a critical dependence on irradiation dose and PARP-1

The activation of IKK/NF-κB by genotoxic stress is a crucial process in the DNA damage response. Due to the anti-apoptotic impact of NF-κB, it can affect cell-fate decisions upon DNA damage and therefore interfere with tumor therapy-induced cell death. Here, we developed a dynamical model describing IKK/NF-κB signaling that faithfully reproduces quantitative time course data and enables a detailed analysis of pathway regulation. The approach elucidates a pathway topology with two hubs, where the first integrates signals from two DNA damage sensors and the second forms a coherent feedforward loop. The analyses reveal a critical role of the sensor protein PARP-1 in the pathway regulation. Introducing a method for calculating the impact of changes in individual components on pathway activity in a time-resolved manner, we show how irradiation dose influences pathway activation. Our results give a mechanistic understanding relevant for the interpretation of experimental and clinical studies.

Reinvestigation of Passerini and Ugi scaffolds as multistep apoptotic inducers via dual modulation of caspase 3/7 and P53-MDM2 signaling for halting breast cancer

Selective induction of breast cancer apoptosis is viewed as the mainstay of various ongoing oncology drug discovery programs. Passerini scaffolds have been recently exploited as selective apoptosis inducers via a caspase 3/7 dependent pathway. Herein, the optimized Passerini caspase activators were manipulated to synergistically induce P53-dependent apoptosis via modulating the closely related P53-MDM2 signaling axis. The adopted design rationale and synthetic routes relied on mimicking the general thematic features of lead MDM2 inhibitors incorporating multiple aromatic rings. Accordingly, the cyclization of representative Passerini derivatives and related Ugi compounds into the corresponding diphenylimidazolidine and spiro derivative was performed, resembling the nutlin-based and spiro MDM-2 inhibitors, respectively. The study was also extended to explore the apoptotic induction capacity of the scaffold after simplification and modifications. MTT assay on MCF-7 and MDA-MB231 breast cancer cells compared to normal fibroblasts (WI-38) revealed their promising cytotoxic activities. The flexible Ugi derivatives 3 and 4, cyclic analog 8, Passerini adduct 12, and the thiosemicarbazide derivative 17 were identified as the study hits regarding cytotoxic potency and selectivity, being over 10-folds more potent (IC50 = 0.065-0.096 μM) and safer (SI = 4.4-18.7) than doxorubicin (IC50 = 0.478 μM, SI = 0.569) on MCF-7 cells. They promoted apoptosis induction via caspase 3/7 activation (3.1-4.1 folds) and P53 induction (up to 4 folds). Further apoptosis studies revealed that these compounds enhanced gene expression of BAX by 2 folds and suppressed Bcl-2 expression by 4.29-7.75 folds in the treated MCF-7 cells. Docking simulations displayed their plausible binding modes with the molecular targets and highlighted their structural determinants of activities for further optimization studies. Finally, in silico prediction of the entire library was computationally performed, showing that most of them could be envisioned as drug-like candidates.

Novel spirooxindole based benzimidazole scaffold: In vitro, nanoformulation and in vivo studies on anticancer and antimetastatic activity of breast adenocarcinoma

The present work provided in vitro anticancer investigation of novel spirooxindole based benzimidazole scaffold SP1 and its nanoformulation with in vivo evaluation of anticancer and antimetastatic activity as potential drug for breast adenocarcinoma. The synthesized compound SP1 exhibited potent growth inhibitory efficacy against four types of human cancer (breast, prostate, colon and lung) cell lines with IC₅₀ = 2.4, 3.4, 7.24 and 7.81 µM and selectivity index 5.79, 4.08, 1.93 and 1.78 respectively. Flow cytometric analysis illustrated that SP1 exhibited high apoptotic effect on all tested cancer cell lines (38.22-52.3 %). The mode of action of this promising compound was declared by its ability to upregulate the gene expression of p21 (2.29-3.91 folds) with suppressing cyclin D (1.9-8.93 folds) and NF-κB (1.26-1.44 fold) in the treated cancer cells. Also, it enhanced the protein expression of apoptotic marker p53 and moderate binding affinity for MDM2 (K_D;7.94 μM). Notwithstanding these promising impressive findings, its selectivity against cancer cell lines and safety on normal cells were improved by nanoformulation. Therefore, SP1 was formulated as ultra-flexible niosomal nanovesicles (transethoniosomes). The ultra-deformability is attributable to the synergism between ethanol and edge activators in improving the flexibility of the nanovesicular membrane. F8 exhibited high deformability index (DI) of (23.48 ± 1.4). It was found that % SP1 released from the optimized transethoniosomal formula (F8) after 12 h (Q_12h) was 84.17 ± 1.29 % and its entrapment efficiency (%EE) was 76.48 ± 1.44 %. Based upon the very encouraging and promising in vitro results, an in vivo study was carried out in female Balb/c mice weighing (15-25 g). SP1 did halt the proliferation of breast cancer cells as well as suppressed the metastasis in other organs like liver, lung and heart.

Patient-Specific Modeling of Diffuse Large B-Cell Lymphoma

Personalized medicine aims to tailor treatment to patients based on their individual genetic or molecular background. Especially in diseases with a large molecular heterogeneity, such as diffuse large B-cell lymphoma (DLBCL), personalized medicine has the potential to improve outcome and/or to reduce resistance towards treatment. However, integration of patient-specific information into a computational model is challenging and has not been achieved for DLBCL. Here, we developed a computational model describing signaling pathways and expression of critical germinal center markers. The model integrates the regulatory mechanism of the signaling and gene expression network and covers more than 50 components, many carrying genetic lesions common in DLBCL. Using clinical and genomic data of 164 primary DLBCL patients, we implemented mutations, structural variants and copy number alterations as perturbations in the model using the CoLoMoTo notebook. Leveraging patient-specific genotypes and simulation of the expression of marker genes in specific germinal center conditions allows us to predict the consequence of the modeled pathways for each patient. Finally, besides modeling how genetic perturbations alter physiological signaling, we also predicted for each patient model the effect of rational inhibitors, such as Ibrutinib, that are currently discussed as possible DLBCL treatments, showing patient-dependent variations in effectiveness and synergies.

P53 vs NF-κB: the role of nuclear factor-kappa B in the regulation of p53 activity and vice versa

The onco-suppressor p53 is a transcription factor that regulates a wide spectrum of genes involved in various cellular functions including apoptosis, cell cycle arrest, senescence, autophagy, DNA repair and angiogenesis. p53 and NF-κB generally have opposing effects in cancer cells. While p53 activity is associated with apoptosis induction, the stimulation of NF-κB has been demonstrated to promote resistance to programmed cell death. Although the transcription factor NF-κB family is considered as the master regulator of cancer development and maintenance, it has been mainly studied in relation to its ability to regulate p53. This has revealed the importance of the crosstalk between NF-κB, p53 and other crucial cell signaling pathways. This review analyzes the various mechanisms by which NF-κB regulates the activity of p53 and the role of p53 on NF-κB activity.

Concepts in Boolean network modeling: What do they all mean?

Boolean network models are one of the simplest models to study complex dynamic behavior in biological systems. They can be applied to unravel the mechanisms regulating the properties of the system or to identify promising intervention targets. Since its introduction by Stuart Kauffman in 1969 for describing gene regulatory networks, various biologically based networks and tools for their analysis were developed. Here, we summarize and explain the concepts for Boolean network modeling. We also present application examples and guidelines to work with and analyze Boolean network models.

p53 modeling as a route to mesothelioma patients stratification and novel therapeutic identification

Background

Malignant pleural mesothelioma (MPM) is an orphan disease that is difficult to treat using traditional chemotherapy, an approach which has been effective in other types of cancer. Most chemotherapeutics cause DNA damage leading to cell death. Recent discoveries have highlighted a potential role for the p53 tumor suppressor in this disease. Given the pivotal role of p53 in the DNA damage response, here we investigated the predictive power of the p53 interactome model for MPM patients’ stratification.

Methods

We used bioinformatics approaches including omics type analysis of data from MPM cells and from MPM patients in order to predict which pathways are crucial for patients’ survival. Analysis of the PKT206 model of the p53 network was validated by microarrays from the Mero-14 MPM cell line and RNA-seq data from 71 MPM patients, whilst statistical analysis was used to identify the deregulated pathways and predict therapeutic schemes by linking the affected pathway with the patients’ clinical state.

Results

In silico simulations demonstrated successful predictions ranging from 52 to 85% depending on the drug, algorithm or sample used for validation. Clinical outcomes of individual patients stratified in three groups and simulation comparisons identified 30 genes that correlated with survival. In patients carrying wild-type p53 either treated or not treated with chemotherapy, FEN1 and MMP2 exhibited the highest inverse correlation, whereas in untreated patients bearing mutated p53, SIAH1 negatively correlated with survival. Numerous repositioned and experimental drugs targeting FEN1 and MMP2 were identified and selected drugs tested. Epinephrine and myricetin, which target FEN1, have shown cytotoxic effect on Mero-14 cells whereas marimastat and batimastat, which target MMP2 demonstrated a modest but significant inhibitory effect on MPM cell migration. Finally, 8 genes displayed correlation with disease stage, which may have diagnostic implications.

Conclusions

Clinical decisions related to MPM personalized therapy based on individual patients’ genetic profile and previous chemotherapeutic treatment could be reached using computational tools and the predictions reported in this study upon further testing in animal models.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1650-0) contains supplementary material, which is available to authorized users.

Logic Modeling in Quantitative Systems Pharmacology

Here we present logic modeling as an approach to understand deregulation of signal transduction in disease and to characterize a drug's mode of action. We discuss how to build a logic model from the literature and experimental data and how to analyze the resulting model to obtain insights of relevance for systems pharmacology. Our workflow uses the free tools OmniPath (network reconstruction from the literature), CellNOpt (model fit to experimental data), MaBoSS (model analysis), and Cytoscape (visualization).

Mice lacking NF-κB1 exhibit marked DNA damage responses and more severe gastric pathology in response to intraperitoneal tamoxifen administration

Tamoxifen (TAM) has recently been shown to cause acute gastric atrophy and metaplasia in mice. We have previously demonstrated that the outcome of Helicobacter felis infection, which induces similar gastric lesions in mice, is altered by deletion of specific NF-κB subunits. Nfkb1^-/- mice developed more severe gastric atrophy than wild-type (WT) mice 6 weeks after H. felis infection. In contrast, Nfkb2^-/- mice were protected from this pathology. We therefore hypothesized that gastric lesions induced by TAM may be similarly regulated by signaling via NF-κB subunits. Groups of five female C57BL/6 (WT), Nfkb1^-/-, Nfkb2^-/- and c-Rel^-/- mice were administered 150 mg/kg TAM by IP injection. Seventy-two hours later, gastric corpus tissues were taken for quantitative histological assessment. In addition, groups of six female WT and Nfkb1^-/- mice were exposed to 12 Gy γ-irradiation. Gastric epithelial apoptosis was quantified 6 and 48 h after irradiation. TAM induced gastric epithelial lesions in all strains of mice, but this was more severe in Nfkb1^-/- mice than in WT mice. Nfkb1^-/- mice exhibited more severe parietal cell loss than WT mice, had increased gastric epithelial expression of Ki67 and had an exaggerated gastric epithelial DNA damage response as quantified by γH2AX. To investigate whether the difference in gastric epithelial DNA damage response of Nfkb1^-/- mice was unique to TAM-induced DNA damage or a generic consequence of DNA damage, we also assessed gastric epithelial apoptosis following γ-irradiation. Six hours after γ-irradiation, gastric epithelial apoptosis was increased in the gastric corpus and antrum of Nfkb1^-/- mice. NF-κB1-mediated signaling regulates the development of gastric mucosal pathology following TAM administration. This is associated with an exaggerated gastric epithelial DNA damage response. This aberrant response appears to reflect a more generic sensitization of the gastric mucosa of Nfkb1^-/- mice to DNA damage.

COMPUTATIONAL METHODS FOR ASYNCHRONOUS BASINS

For a Boolean network we consider asynchronous updates and define the exclusive asynchronous basin of attraction for any steady state or cyclic attractor. An algorithm based on commutative algebra is presented to compute the exclusive basin. Finally its use for targeting desirable attractors by selective intervention on network nodes is illustrated with two examples, one cell signalling network and one sensor network measuring human mobility.

Formal modeling and analysis of the hexosamine biosynthetic pathway: role of O-linked N-acetylglucosamine transferase in oncogenesis and cancer progression

The alteration of glucose metabolism, through increased uptake of glucose and glutamine addiction, is essential to cancer cell growth and invasion. Increased flux of glucose through the Hexosamine Biosynthetic Pathway (HBP) drives increased cellular O-GlcNAcylation (hyper-O-GlcNAcylation) and contributes to cancer progression by regulating key oncogenes. However, the association between hyper-O-GlcNAcylation and activation of these oncogenes remains poorly characterized. Here, we implement a qualitative modeling framework to analyze the role of the Biological Regulatory Network in HBP activation and its potential effects on key oncogenes. Experimental observations are encoded in a temporal language format and model checking is applied to infer the model parameters and qualitative model construction. Using this model, we discover step-wise genetic alterations that promote cancer development and invasion due to an increase in glycolytic flux, and reveal critical trajectories involved in cancer progression. We compute delay constraints to reveal important associations between the production and degradation rates of proteins. O-linked N-acetylglucosamine transferase (OGT), an enzyme used for addition of O-GlcNAc during O-GlcNAcylation, is identified as a key regulator to promote oncogenesis in a feedback mechanism through the stabilization of c-Myc. Silencing of the OGT and c-Myc loop decreases glycolytic flux and leads to programmed cell death. Results of network analyses also identify a significant cycle that highlights the role of p53-Mdm2 circuit oscillations in cancer recovery and homeostasis. Together, our findings suggest that the OGT and c-Myc feedback loop is critical in tumor progression, and targeting these mediators may provide a mechanism-based therapeutic approach to regulate hyper-O-GlcNAcylation in human cancer.

Synergistic DNA-damaging effect in multiple myeloma with the combination of zalypsis, bortezomib and dexamethasone

Despite new advances in multiple myeloma treatment and the consequent improvement in overall survival, most patients relapse or become refractory to treatment. This suggests that new molecules and combinations that may further inhibit important survival pathways for these tumor cells are needed. In this context, zalypsis is a novel compound, derived from marine organisms, with a powerful preclinical anti-myeloma effect based on the sensitivity of malignant plasma cells to DNA-damage induction; and it has already been tested in a phase I/II clinical trial in multiple myeloma. We hypothesized that the addition of this compound to the combination of bortezomib plus dexamethasone may improve efficacy with acceptable toxicity. The triple combination demonstrated strong synergy and higher efficacy compared with double combinations; not only in vitro, but also ex vivo and, especially, in in vivo experiments. The triple combination triggers cell death, mainly through a synergistic induction of DNA damage and a decrease in the nuclear localization of nuclear factor kappa B. Our findings support the clinical evaluation of this combination for relapsed and refractory myeloma patients.

DNA Damage and Pulmonary Hypertension

Pulmonary hypertension (PH) is defined by a mean pulmonary arterial pressure over 25 mmHg at rest and is diagnosed by right heart catheterization. Among the different groups of PH, pulmonary arterial hypertension (PAH) is characterized by a progressive obstruction of distal pulmonary arteries, related to endothelial cell dysfunction and vascular cell proliferation, which leads to an increased pulmonary vascular resistance, right ventricular hypertrophy, and right heart failure. Although the primary trigger of PAH remains unknown, oxidative stress and inflammation have been shown to play a key role in the development and progression of vascular remodeling. These factors are known to increase DNA damage that might favor the emergence of the proliferative and apoptosis-resistant phenotype observed in PAH vascular cells. High levels of DNA damage were reported to occur in PAH lungs and remodeled arteries as well as in animal models of PH. Moreover, recent studies have demonstrated that impaired DNA-response mechanisms may lead to an increased mutagen sensitivity in PAH patients. Finally, PAH was linked with decreased breast cancer 1 protein (BRCA1) and DNA topoisomerase 2-binding protein 1 (TopBP1) expression, both involved in maintaining genome integrity. This review aims to provide an overview of recent evidence of DNA damage and DNA repair deficiency and their implication in PAH pathogenesis.

Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling

Discovery of efficient anti-cancer drug combinations is a major challenge, since experimental testing of all possible combinations is clearly impossible. Recent efforts to computationally predict drug combination responses retain this experimental search space, as model definitions typically rely on extensive drug perturbation data. We developed a dynamical model representing a cell fate decision network in the AGS gastric cancer cell line, relying on background knowledge extracted from literature and databases. We defined a set of logical equations recapitulating AGS data observed in cells in their baseline proliferative state. Using the modeling software GINsim, model reduction and simulation compression techniques were applied to cope with the vast state space of large logical models and enable simulations of pairwise applications of specific signaling inhibitory chemical substances. Our simulations predicted synergistic growth inhibitory action of five combinations from a total of 21 possible pairs. Four of the predicted synergies were confirmed in AGS cell growth real-time assays, including known effects of combined MEK-AKT or MEK-PI3K inhibitions, along with novel synergistic effects of combined TAK1-AKT or TAK1-PI3K inhibitions. Our strategy reduces the dependence on a priori drug perturbation experimentation for well-characterized signaling networks, by demonstrating that a model predictive of combinatorial drug effects can be inferred from background knowledge on unperturbed and proliferating cancer cells. Our modeling approach can thus contribute to preclinical discovery of efficient anticancer drug combinations, and thereby to development of strategies to tailor treatment to individual cancer patients.

Dynamic aberrant NF-κB spurs tumorigenesis: a new model encompassing the microenvironment

Recently it was discovered that a transient activation of transcription factor NF-κB can give cells properties essential for invasiveness and cancer initiating potential. In contrast, most oncogenes to date were characterized on the basis of mutations or by their constitutive overexpression. Study of NF-κB actually leads to a far more dynamic perspective on cancer: tumors caused by diverse oncogenes apparently evolve into cancer after loss of feedback regulation for NF-κB. This event alters the cellular phenotype and the expression of hormonal mediators, modifying signals between diverse cell types in a tissue. The result is a disruption of stem cell hierarchy in the tissue, and pervasive changes in the microenvironment and immune response to the malignant cells.

MONOMIALS AND BASIN CYLINDERS FOR NETWORK DYNAMICS

We describe methods to identify cylinder sets inside a basin of attraction for Boolean dynamics of biological networks. Such sets are used for designing regulatory interventions that make the system evolve towards a chosen attractor, for example initiating apoptosis in a cancer cell. We describe two algebraic methods for identifying cylinders inside a basin of attraction, one based on the Groebner fan that finds monomials that define cylinders and the other on primary decomposition. Both methods are applied to current examples of gene networks.

Modelling the onset of senescence at the G1/S cell cycle checkpoint

BACKGROUND

DNA damage (single or double-strand breaks) triggers adapted cellular responses. These responses are elicited through signalling pathways, which activate cell cycle checkpoints and basically lead to three cellular fates: cycle arrest promoting DNA repair, senescence (permanent arrest) or cell death. Cellular senescence is known for having a tumour-suppressive function and its regulation arouses a growing scientific interest. Here, we advance a qualitative model covering DNA damage response pathways, focusing on G1/S checkpoint enforcement, supposedly more sensitive to arrest than G2/M checkpoint.

RESULTS

We define a discrete, logical model encompassing ATM (ataxia telangiectasia mutated) and ATR (ATM and Rad3-related) pathways activation upon DNA damage, as well as G1/S checkpoint main components. It also includes the stress responsive protein p38MAPK (mitogen-activated protein kinase 14) known to be involved in the regulation of senescence. The model has four outcomes that convey alternative cell fates: proliferation, (transient) cell cycle arrest, apoptosis and senescence. Different levels of DNA damage are considered, defined by distinct combinations of single and double-strand breaks. Each leads to a single stable state denoting the cell fate adopted upon this specific damage. A range of model perturbations corresponding to gene loss-of-function or gain-of-function is compared to experimental mutations.

CONCLUSIONS

As a step towards an integrative model of DNA-damage response pathways to better cover the onset of senescence, our model focuses on G1/S checkpoint enforcement. This model qualitatively agrees with most experimental observations, including experiments involving mutations. Furthermore, it provides some predictions.

Experimental design, validation and computational modeling uncover DNA damage sensing by DNA-PK and ATM

Reliable and efficient detection of DNA damage constitutes a vital capability of human cells to maintain genome stability. Following DNA damage, the histone variant H2AX becomes rapidly phosphorylated by the DNA damage response kinases DNA-PKcs and ATM. H2AX phosphorylation plays a central role in signal amplification leading to chromatin remodeling and DNA repair initiation. The contribution of DNA-PKcs and ATM to H2AX phosphorylation is however puzzling. Although ATM is required, DNA-PKcs can substitute for it. Here we analyze the interplay between DNA-PKcs and ATM with a computational model derived by an iterative workflow: switching between experimental design, experiment and model analysis, we generated an extensive set of time-resolved data and identified a conclusive dynamic signaling model out of several alternatives. Our work shows that DNA-PKcs and ATM enforce a biphasic H2AX phosphorylation. DNA-PKcs can be associated to the initial, and ATM to the succeeding phosphorylation phase of H2AX resulting into a signal persistence detection function for reliable damage sensing. Further, our model predictions emphasize that DNA-PKcs inhibition significantly delays H2AX phosphorylation and associated DNA repair initiation.

Integrative modelling of the influence of MAPK network on cancer cell fate decision

The Mitogen-Activated Protein Kinase (MAPK) network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision) in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR) over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3) activating mutations.

Depending on environmental conditions, strongly intertwined cellular signalling pathways are activated, involving activation/inactivation of proteins and genes in response to external and/or internal stimuli. Alterations of some components of these pathways can lead to wrong cell behaviours. For instance, cancer-related deregulations lead to high proliferation of malignant cells enabling sustained tumour growth. Understanding the precise mechanisms underlying these pathways is necessary to delineate efficient therapeutical approaches for each specific tumour type. We particularly focused on the Mitogen-Activated Protein Kinase (MAPK) signalling network, whose involvement in cancer is well established, although the precise conditions leading to its positive or negative influence on cell proliferation are still poorly understood. We tackled this problem by first collecting sparse published biological information into a comprehensive map describing the MAPK network in terms of stylised chemical reactions. This information source was then used to build a dynamical Boolean model recapitulating network responses to characteristic stimuli observed in selected bladder cancers. Systematic model simulations further allowed us to link specific network components and interactions with proliferative/anti-proliferative cell responses.

Friend or foe: emerging role of nuclear factor kappa-light-chain-enhancer of activated B cells in cell senescence

The nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) proteins are a family of ubiquitously expressed transcription factors that regulate the response to cellular stress. They mediate innate and adaptive immunity through the initiation of an inflammatory response to pro-inflammatory signals. The role of persistent inflammation in aiding tumor development has led to the NF-κB family of transcription factors being strongly implicated in promoting cancer. However, recent studies have now revealed that NF-κB can also function as a tumor suppressor through the induction of cellular senescence. Cellular senescence is a stable cell cycle arrest that normal cells undergo in response to a variety of intrinsic and extrinsic stimuli including: progressive telomere shortening, changes in telomeric structure, or other forms of genotoxic stress. Senescence can compromise tissue repair and regeneration, contributing to tissue and organismal aging via the accumulation of senescent cells, depletion of stem/progenitor cells and secretion of an array of inflammatory cytokines, chemokines, and matrix metalloproteinases. Senescence can also lead to the removal of potentially cancerous cells, thereby acting as a potent tumor suppressor mechanism. Herein, we review the evidence indicating a role for NF-κB in tumor suppression via cellular senescence and suggest that depending upon the subunit expressed, the biological context, and the type and intensity of the signal, NF-κB can indeed promote senescence growth arrest.

Dynamics of DNA damage induced pathways to cancer

Chemotherapy is commonly used in cancer treatments, however only 25% of cancers are responsive and a significant proportion develops resistance. The p53 tumour suppressor is crucial for cancer development and therapy, but has been less amenable to therapeutic applications due to the complexity of its action, reflected in 66,000 papers describing its function. Here we provide a systematic approach to integrate this information by constructing a large-scale logical model of the p53 interactome using extensive database and literature integration. The model contains 206 nodes representing genes or proteins, DNA damage input, apoptosis and cellular senescence outputs, connected by 738 logical interactions. Predictions from in silico knock-outs and steady state model analysis were validated using literature searches and in vitro based experiments. We identify an upregulation of Chk1, ATM and ATR pathways in p53 negative cells and 61 other predictions obtained by knockout tests mimicking mutations. The comparison of model simulations with microarray data demonstrated a significant rate of successful predictions ranging between 52% and 71% depending on the cancer type. Growth factors and receptors FGF2, IGF1R, PDGFRB and TGFA were identified as factors contributing selectively to the control of U2OS osteosarcoma and HCT116 colon cancer cell growth. In summary, we provide the proof of principle that this versatile and predictive model has vast potential for use in cancer treatment by identifying pathways in individual patients that contribute to tumour growth, defining a sub population of “high” responders and identification of shifts in pathways leading to chemotherapy resistance.

Characterization of direct radiation-induced immune function and molecular signaling changes in an antigen presenting cell line

Radiation therapy is a widely used cancer treatment and pre-transplantation conditioning regimen that has the potential to influence anti-tumor and post-transplantation immune responses. Although conventionally fractionated radiation doses can suppress immune responses by depleting lymphocytes, single high doses of local tumor radiation can enhance immune responses. Using phospho-flow cytometry analysis of a human monocytic cell line, we identified novel radiation-induced changes in the phosphorylation state of NFκB family members known in other cell types to maintain and regulate immune function. These phosphorylation changes were p53 independent, but were strongly dependent upon ATM activation due to DNA damage. We found that radiation promotes the activation and APC functional maturation through phosphorylation of NFκB Essential Modulator (NEMO). Our results and the analytic methods are especially well suited to the study of functional changes in APC when radiation is used for immune modulation in clinical protocols.