Effects of Bcl-2 levels on Fas signaling-induced caspase-3 activation: molecular genetic tests of computational model predictions

Impact of the environmental endocrine disruptor flutamide on cryptorchidism: Molecular mechanisms involving connexin-43 and p38-MAPK signaling

Cryptorchidism, a condition associated with male infertility, is exacerbated by exposure to environmental endocrine disruptors such as flutamide. This study investigates the molecular mechanisms of cryptorchidism and potential interventions targeting endocrine disruptor-induced testicular damage. A rat model of congenital cryptorchidism was established via prenatal flutamide exposure, and testes were harvested at postnatal day 90. Testicular histology, transcriptome sequencing, bioinformatic analysis, sperm analysis, immunohistochemistry, and lentiviral vector transfection were conducted. Cryptorchid testes exhibited impaired seminiferous tubule development, significant reductions in sperm count, and increased sperm abnormalities. Tight and gap junction proteins essential for blood-testis barrier (BTB) integrity, including Claudin-11, Occludin, and Connexin-43, were markedly downregulated. Transcriptomic analysis revealed activation of the p38 MAPK signaling pathway and excessive apoptosis in cryptorchid testes. Overexpression of Connexin-43 restored BTB integrity and suppressed the p38 MAPK pathway, rescuing spermatogenesis. These findings underscore the role of environmental anti-androgens in cryptorchidism pathogenesis and highlight Connexin-43 as a potential therapeutic target for mitigating testicular damage caused by endocrine disruptors.

A biochemical necroptosis model explains cell-type-specific responses to cell death cues

Necroptosis is a form of regulated cell death associated with degenerative disorders, autoimmune and inflammatory diseases, and cancer. To better understand the biochemical mechanisms regulating necroptosis, we constructed a detailed computational model of tumor necrosis factor-induced necroptosis based on known molecular interactions from the literature. Intracellular protein levels, used as model inputs, were quantified using label-free mass spectrometry, and the model was calibrated using Bayesian parameter inference to experimental protein time course data from a well-established necroptosis-executing cell line. The calibrated model reproduced the dynamics of phosphorylated mixed lineage kinase domain-like protein, an established necroptosis reporter. A subsequent dynamical systems analysis identified four distinct modes of necroptosis signal execution, distinguished by rate constant values and the roles of the RIP1 deubiquitinating enzymes A20 and CYLD. In one case, A20 and CYLD both contribute to RIP1 deubiquitination, in another RIP1 deubiquitination is driven exclusively by CYLD, and in two modes either A20 or CYLD acts as the driver with the other enzyme, counterintuitively, inhibiting necroptosis. We also performed sensitivity analyses of initial protein concentrations and rate constants to identify potential targets for modulating necroptosis sensitivity within each mode. We conclude by associating numerous contrasting and, in some cases, counterintuitive experimental results reported in the literature with one or more of the model-predicted modes of necroptosis execution. In all, we demonstrate that a consensus pathway model of tumor necrosis factor-induced necroptosis can provide insights into unresolved controversies regarding the molecular mechanisms driving necroptosis execution in numerous cell types under different experimental conditions.

Mathematical Models of Death Signaling Networks

This review provides an overview of the progress made by computational and systems biologists in characterizing different cell death regulatory mechanisms that constitute the cell death network. We define the cell death network as a comprehensive decision-making mechanism that controls multiple death execution molecular circuits. This network involves multiple feedback and feed-forward loops and crosstalk among different cell death-regulating pathways. While substantial progress has been made in characterizing individual cell death execution pathways, the cell death decision network is poorly defined and understood. Certainly, understanding the dynamic behavior of such complex regulatory mechanisms can be only achieved by applying mathematical modeling and system-oriented approaches. Here, we provide an overview of mathematical models that have been developed to characterize different cell death mechanisms and intend to identify future research directions in this field.

Examination of Fas-Induced Apoptosis of Murine Thymocytes in Thymic Tissue Slices Reveals That Fas Is Dispensable for Negative Selection

The death receptor Fas can induce cell death through the extrinsic pathway of apoptosis in a variety of cells, including developing thymocytes. Although Fas-induced cell death has been researched and modeled extensively, most of the studies have been done in vitro because of the lethality of Fas triggering in vivo. Thus, little is known about the time line of this type of cell death in vivo, specifically, how does the presence of macrophages and pro-survival cytokines affect apoptosis progression. In addition, although the sequence and timing of events during intrinsic pathway activation in thymocytes in situ have been described, no corresponding data for the extrinsic pathway are available. To address this gap in our knowledge, we established a novel system to study Fas-induced thymocyte cell death using tissue explants. We found that within 1 h of Fas ligation, caspase 3 was activated, within 2 h phosphatidylserine was externalized to serve as an "eat-me" signal, and at the same time, we observed signs of cell loss, likely due to efferocytosis. Both caspase 3 activation and phosphatidylserine exposure were critical for cell loss. Although Fas ligand (FasL) was delivered simultaneously to all cells, we observed significant variation in the entry into the cell death pathway. This model also allowed us to revisit the role of Fas in negative selection, and we ruled out an essential part for it in the deletion of autoreactive thymocytes. Our work provides a timeline for the apoptosis-associated events following Fas triggering in situ and confirms the lack of involvement of Fas in the negative selection of thymocytes.

AZD4320, A Dual Inhibitor of Bcl-2 and Bcl-xL, Induces Tumor Regression in Hematologic Cancer Models without Dose-limiting Thrombocytopenia

PURPOSE

Targeting Bcl-2 family members upregulated in multiple cancers has emerged as an important area of cancer therapeutics. While venetoclax, a Bcl-2-selective inhibitor, has had success in the clinic, another family member, Bcl-x_L, has also emerged as an important target and as a mechanism of resistance. Therefore, we developed a dual Bcl-2/Bcl-x_L inhibitor that broadens the therapeutic activity while minimizing Bcl-x_L-mediated thrombocytopenia.

EXPERIMENTAL DESIGN

We used structure-based chemistry to design a small-molecule inhibitor of Bcl-2 and Bcl-x_L and assessed the activity against in vitro cell lines, patient samples, and in vivo models. We applied pharmacokinetic/pharmacodynamic (PK/PD) modeling to integrate our understanding of on-target activity of the dual inhibitor in tumors and platelets across dose levels and over time.

RESULTS

We discovered AZD4320, which has nanomolar affinity for Bcl-2 and Bcl-x_L, and mechanistically drives cell death through the mitochondrial apoptotic pathway. AZD4320 demonstrates activity in both Bcl-2- and Bcl-x_L-dependent hematologic cancer cell lines and enhanced activity in acute myeloid leukemia (AML) patient samples compared with the Bcl-2-selective agent venetoclax. A single intravenous bolus dose of AZD4320 induces tumor regression with transient thrombocytopenia, which recovers in less than a week, suggesting a clinical weekly schedule would enable targeting of Bcl-2/Bcl-x_L-dependent tumors without incurring dose-limiting thrombocytopenia. AZD4320 demonstrates monotherapy activity in patient-derived AML and venetoclax-resistant xenograft models.

CONCLUSIONS

AZD4320 is a potent molecule with manageable thrombocytopenia risk to explore the utility of a dual Bcl-2/Bcl-x_L inhibitor across a broad range of tumor types with dysregulation of Bcl-2 prosurvival proteins.

MicroRNA-135a-5p Promotes the Functional Recovery of Spinal Cord Injury by Targeting SP1 and ROCK

Emerging evidence indicates that microRNAs play a pivotal role in neural remodeling after spinal cord injury (SCI). This study aimed to investigate the mechanisms of miR-135a-5p in regulating the functional recovery of SCI by impacting its target genes and downstream signaling. The gene transfection assay and luciferase reporter assay confirmed the target relationship between miR-135a-5p and its target genes (specificity protein 1 [SP1] and Rho-associated kinase [ROCK]1/2). By establishing the H₂O₂-induced injury model, miR-135a-5p transfection was found to inhibit the apoptosis of PC12 cells by downregulating the SP1 gene, which subsequently induced downregulation of pro-apoptotic proteins (Bax, cleaved caspase-3) and upregulation of anti-apoptotic protein Bcl-2. By measuring the neurite lengths of PC12 cells, miR-135a-5p transfection was found to promote axon outgrowth by downregulating the ROCK1/2 gene, which subsequently caused upregulation of phosphate protein kinase B (AKT) and phosphate glycogen synthase kinase 3β (GSK3β). Use of the rat SCI models showed that miR-135a-5p could increase the Basso, Beattie, and Bresnahan (BBB) scores, indicating neurological function recovery. In conclusion, the miR-135a-5p-SP1-Bax/Bcl-2/caspase-3 and miR-135a-5p-ROCK-AKT/GSK3β axes are involved in functional recovery of SCI by regulating neural apoptosis and axon regeneration, respectively, and thus can be promising effective therapeutic strategies in SCI.

What Will B Will B: Identifying Molecular Determinants of Diverse B-Cell Fate Decisions Through Systems Biology

B-cells are the poster child for cellular diversity and heterogeneity. The diverse repertoire of B lymphocytes, each expressing unique antigen receptors, provides broad protection against pathogens. However, B-cell diversity goes beyond unique antigen receptors. Side-stepping B-cell receptor (BCR) diversity through BCR-independent stimuli or engineered organisms with monoclonal BCRs still results in seemingly identical B-cells reaching a wide variety of fates in response to the same challenge. Identifying to what extent the molecular state of a B-cell determines its fate is key to gaining a predictive understanding of B-cells and consequently the ability to control them with targeted therapies. Signals received by B-cells through transmembrane receptors converge on intracellular molecular signaling networks, which control whether each B-cell divides, dies, or differentiates into a number of antibody-secreting distinct B-cell subtypes. The signaling networks that interpret these signals are well known to be susceptible to molecular variability and noise, providing a potential source of diversity in cell fate decisions. Iterative mathematical modeling and experimental studies have provided quantitative insight into how B-cells achieve distinct fates in response to pathogenic stimuli. Here, we review how systems biology modeling of B-cells, and the molecular signaling networks controlling their fates, is revealing the key determinants of cell-to-cell variability in B-cell destiny.

Apoptosis: A mammalian cell bioprocessing perspective

Apoptosis is a form of programmed and controlled cell death that accounts for the majority of cellular death in bioprocesses. Cell death affects culture longevity and product quality; it is instigated by several stresses experienced by the cells within a bioreactor. Understanding the factors that cause apoptosis as well as developing strategies that can protect cells is crucial for robust bioprocess development. This review aims to a) address apoptosis from a bioprocess perspective; b) describe the significant apoptotic mechanisms linking them to the most relevant stresses encountered in bioreactors; c) discuss the design of operating conditions in order to avoid cell death; d) focus on industrially relevant cell lines; and e) present anti-apoptosis strategies including cell engineering and model-based optimization of bioprocesses. In addition, the importance of apoptosis in quality-by-design bioprocess development from clone screening to production scale are highlighted.

Betulinic acid as apoptosis activator: Molecular mechanisms, mathematical modeling and chemical modifications

A natural product betulinic acid (BA) has gained a huge significance in the recent years for its strong cytotoxicity. Surprisingly, in spite of being an interesting cancer protecting agent on a variety of tumor cells, the normal cells and tissues are rarely affected by BA. Betulinic acid and analogues (BAs) generally exert through the mechanisms that provokes an event of direct cell death and bypass the resistance to normal chemotherapeutics. Although the major mechanism associated with its ability to induce direct cell death is mitochondrial apoptosis, there are several other mechanisms explored recently. Importantly, mathematical modeling of apoptosis has been an important tool to explore the precise mechanism involved in mitochondrial apoptosis. Thus, this review is an endeavor to sum up the molecular mechanisms underlying the action of BA and future directions to apply mathematical modeling technique to better understand the precise mechanism of BA-induced apoptosis. The last section of the review encompasses the plausible structural modifications and formulations to enhance the therapeutic efficacy of BA.

In silico modelling of apoptosis induced by photodynamic therapy

Photodynamic therapy (PDT) is an emergent technique used for the treatment of several diseases. After PDT, cells die by necrosis, apoptosis or autophagy. Necrosis is produced immediately during photodynamic therapy by high concentration of reactive oxygen species, apoptosis and autophagy are triggered by mild or low doses of light and photosensitizer. In this work we model the cell response to low doses of PDT assuming a bi-dimensional matrix of interacting cells. For each cell of the matrix we simulate in detail, with the help of the Gillespie's algorithm, the two main chemical pathways leading to apoptosis. We unveil the role of both pathways in the cell death rate of the tumor, as well as the relevance of several molecules in the process. Our model suggests values of concentrations for several species of molecules to enhance the effectiveness of PDT.

The optimal regulation mode of Bcl-2 apoptotic switch revealed by bistability analysis

In most cell types, apoptosis occurs by the mitochondrial outer membrane permeability (MOMP)-mediated pathway, which is controlled by Bcl-2 family proteins (often referred to as Bcl-2 apoptotic switch). These proteins, which display a range of bioactivities, can be divided into four types: effectors, inhibitors, activators and sensitizers. Although the complex interactions among Bcl-2 family members have been studied intensively, a unifying hypothesis for the mechanism they use to regulate MOMP remains elusive. The bistable behaviors are often used to explain the all-or-none decisions of apoptosis. Here, we attempt to reveal the optimal interaction mode by comparing the bistable performances of three different modes (direct activation, indirect activation, and unified mode) proposed by biologists. Using the method that combines mathematical analysis and numerical simulation, we discover that bistability can only emerge from the unified mode when proteins synthesis and degradation are considered, which is in favor of it as an optimal regulation mode of Bcl-2 apoptotic switch. The parameter sensitivity analysis for the unified mode further consolidates this view. Moreover, two-parameter bifurcation analysis suggests that the sensitizers lower the threshold of activation of Bax, but have a negative influence on the width of the bistability region. Our study may provide mechanistic insights into the heterogeneity of tumor cells and the efficiency of BH3 mimetic-mediated killing of cancer cells, and suggest that a combination treatment might be required to overcome apoptosis resistance in the Bcl-2 family targeted therapies.

Libidibia ferrea presents antiproliferative, apoptotic and antioxidant effects in a colorectal cancer cell line

Colorectal cancer is noted for being one of the most frequent of tumors, with expressive morbidity and mortality rates. In new drug discovery, plants stand out as a source capable of yielding safe and high-efficiency products. Well known in Brazilian popular medicine, Libidibia ferrea (Mart. Ex Tul.) L.P. Queiroz var. ferrea (better known as "ironwood" or "jucá"), has been used to treat a wide spectrum of conditions and to prevent cancer. Using methodologies that involved flow cytometry, spectrophotometry and RT-qPCR assays, crude extracts of the fruits of L. ferrea (20T, 40T, 60T and 80T) were evaluated at 24h and/or 48h for: their ability to inhibit cell proliferation; induce apoptosis through Bcl-2, caspase-3 and Apaf-1; their antioxidant activity and effects on important targets related to cell proliferation (EGFR and AKT) in the HT-29 human colorectal cancer lineage. The results revealed high antiproliferative potential as compared to the controls, induction of apoptosis through the intrinsic pathway, and probable tumor inhibition activity under the mediation of important targets in tumorigenesis. In addition, L. ferrea revealed antioxidant, lipid peroxidation and chemoprotective effects in healthy cells. Thus, L. ferrea derivatives have important anticancer effects, and may be considered promising candidate for colorectal cancer therapy.

Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy

The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed "cyclotherapy". Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs.

Minimal systems analysis of mitochondria-dependent apoptosis induced by cisplatin

Recently, it was reported that the role of mitochondria-reactive oxygen species (ROS) generating pathway in cisplatin-induced apoptosis is remarkable. Since a variety of molecules are involved in the pathway, a comprehensive approach to delineate the biological interactions of the molecules is required. However, quantitative modeling of the mitochondria-ROS generating pathway based on experiment and systemic analysis using the model have not been attempted so far. Thus, we conducted experiments to measure the concentration changes of critical molecules associated with mitochondrial apoptosis in both human mesothelioma H2052 and their ρ(0) cells lacking mitochondrial DNA (mtDNA). Based on the experiments, a novel mathematical model that can represent the essential dynamics of the mitochondrial apoptotic pathway induced by cisplatin was developed. The kinetic parameter values of the mathematical model were estimated from the experimental data. Then, we have investigated the dynamical properties of this model and predicted the apoptosis levels for various concentrations of cisplatin beyond the range of experiments. From parametric perturbation analysis, we further found that apoptosis will reach its saturation level beyond a certain critical cisplatin concentration.

Effect of baicalin on hippocampal damage in kainic acid-induced epileptic mice

The aim of the present study was to determine the effect of baicalin on the expression of miR-497 and its target B-cell lymphoma-2 (Bcl-2) in the hippocampus of kainic acid (KA)-induced epileptic mice. To establish status epilepticus (SE), 0.1 µg/5 µl KA was injected into the lateral cerebral ventricle in mice, which then received an intraperitoneal injection of baicalin (100 mg/kg) after 1 and 8 h. Hematoxylin and eosin staining was used to observe the pathological changes in morphology and neuronal apoptosis was determined by terminal transferase-mediated dUTP nick end-labeling staining. Western blot analysis was used to detect the expression of Bcl-2 and cleaved caspase-3 proteins in the hippocampus, while reverse transcription-quantitative polymerase chain reaction was used to quantify hippocampal miR-497 expression. The results showed that baicalin significantly attenuated neuronal damage and apoptosis in the hippocampus 72 h after SE. In addition, baicalin decreased SE-induced expression of miR-497 and cleaved caspase-3 protein, while upregulating the expression of Bcl-2 protein. In conclusion, the present results suggest that baicalin possesses potent antiapoptotic properties and attenuates hippocampal injury in mice after SE, which may be associated with the downregulation of miR-497 and cleaved caspase-3 and the upregulation of Bcl-2.

Reduction of apoptosis by proanthocyanidin-induced autophagy in the human gastric cancer cell line MGC-803

Proanthocyanidins are flavonoids that are widely present in the skin and seeds of various plants, with the highest content in grape seeds. Many experiments have shown that proanthocyanidins have antitumor activity both in vivo and in vitro. Autophagy and apoptosis of tumor cells induced by drugs are two of the major causes of tumor cell death. However, reports on the effect of autophagy induced by drugs in tumor cells are not consistent and suggest that autophagy can have synergistic or antagonistic effects with apoptosis. This research was aimed at investigating whether proanthocyanidins induced autophagy and apoptosis in human gastric cancer cell line MGC-803 cells and to identify the mechanism of proanthocyanidins action to further determine the effect of proanthocyanidins-induced autophagy on apoptosis. MTT assay was used to examine the proanthocyanidin cytotoxicity against human gastric cancer cell line MGC-803. Transmission electron microscopy and monodansylcadaverine (MDC) staining were used to detect autophagy. Annexin V APC/7-AAD double staining and Hoechst 33342/propidium iodide (PI) double staining were used to explore apoptosis. Western blotting was used to determine expression of proteins related to autophagy and apoptosis. Real-time quantitative PCR technology was used to determine the mRNA level of Beclin1 and BCL-2. The results showed that proanthocyanidins exhibit a significant inhibitory effect on the human gastric cancer cell line MGC-803 proliferation in vitro and simultaneously activate autophagy and apoptosis to promote cell death. Furthermore, when proanthocyanidin-induced autophagy is inhibited, apoptosis increases significantly, proanthocyanidins can be used together with autophagy inhibitors to enhance cytotoxicity.

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

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

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

A mathematical model of cellular metabolism during ischemic stroke and hypothermia

Stroke is a major cause of death and disability worldwide. Therapeutic hypothermia is a potentially useful neuroprotective treatment. A mathematical model of brain metabolism during stroke is extended here to simulate the effect of hypothermia on cell survival. Temperature decreases were set to reduce chemical reaction rates and slow diffusion through ion channels according to the Q10 rule. Heat delivery to tissues was set to depend on metabolic heat generation rate and perfusion. Two cooling methods, scalp and vascular, were simulated to approximate temperature variation in the brain during treatment. Cell death was assumed to occur at continued cell membrane depolarization. Simulations showed that hypothermia to 34.5 °C induced within 1-1.5 h of stroke onset could extend cell survival time by at least 5 h in tissue with perfusion reduced by 80% of normal. There was good agreement between simulated metabolite dynamics and those reported in rat model studies.

Stochasticity of intranuclear biochemical reaction processes controls the final decision of cell fate associated with DNA damage

A massive integrative mathematical model of DNA double-strand break (DSB) generation, DSB repair system, p53 signaling network, and apoptosis induction pathway was constructed to explore the dominant factors of unknown criteria of cell fate decision. In the proposed model, intranuclear reactions were modeled as stochastic processes and cytoplasmic reactions as deterministic processes, and both reaction sets were simulated simultaneously. The simulated results at the single-cell level showed that the model generated several sustained oscillations (pulses) of p53, Mdm2, ATM, and Wip1, and cell-to-cell variability in the number of p53 pulses depended on IR intensity. In cell populations, the model generated damped p53 oscillations, and IR intensity affected the amplitude of the first p53 oscillation. Cells were then subjected to the same IR dose exhibiting apoptosis induction variability. These simulated results are in quantitative agreement with major biological findings observed in human breast cancer epithelial MCF7, NIH3T3, and fibrosarcoma cells, demonstrating that the proposed model was concededly biologically appropriate. Statistical analysis of the simulated results shows that the generation of multiple p53 pulses is a prerequisite for apoptosis induction. Furthermore, cells exhibited considerable individual variability in p53 dynamics, which correlated with intrinsic apoptosis induction. The simulated results based on the proposed model demonstrated that the stochasticity of intranuclear biochemical reaction processes controls the final decision of cell fate associated with DNA damage. Applying stochastic simulation to an exploration of intranuclear biochemical reaction processes is indispensable in enhancing the understanding of the dynamic characteristics of biological multi-layered systems of higher organisms.

Cell-to-cell variability in cell death: can systems biology help us make sense of it all?

One of the most common observations in cell death assays is that not all cells die at the same time, or at the same treatment dose. Here, using the perspective of the systems biology of apoptosis and the context of cancer treatment, we discuss possible sources of this cell-to-cell variability as well as its implications for quantitative measurements and computational models of cell death. Many different factors, both within and outside of the apoptosis signaling networks, have been correlated with the variable responses to various death-inducing treatments. Systems biology models offer us the opportunity to take a more synoptic view of the cell death process to identify multifactorial determinants of the cell death decision. Finally, with an eye toward 'systems pharmacology', we discuss how leveraging this new understanding should help us develop combination treatment strategies to compel cancer cells toward apoptosis by manipulating either the biochemical state of cancer cells or the dynamics of signal transduction.

Harnessing system models of cell death signalling for cytotoxic chemotherapy: towards personalised medicine approaches?

Most cytotoxic chemotherapeutics are believed to kill cancer cells by inducing apoptosis. Understanding the factors that contribute to impairment of apoptosis in cancer cells is therefore critical for the development of novel therapies that circumvent the widespread chemoresistance. Apoptosis, however, is a complex and tightly controlled process that can be induced by different classes of chemotherapeutics targeting different signalling nodes and pathways. Moreover, apoptosis initiation and apoptosis execution strongly depend on patient-specific, genomic and proteomic signatures. Here, we will review recent translational studies that suggest a critical link between the sensitivity of cancer cells to initiate apoptosis and clinical outcome. Next we will discuss recent advances in the field of system modelling of apoptosis pathways for the prediction of treatment responses. We propose that initiation of mitochondrial apoptosis, defined as the process of mitochondrial outer membrane permeabilisation (MOMP), is a dose-dependent decision process that allows for a prediction of individual therapy responses and therapeutic windows. We provide evidence in contrast that apoptosis execution post-MOMP may be a binary decision that dictates whether apoptosis is executed or not. We will discuss the implications of this concept for the future use of novel adjuvant therapeutics that specifically target apoptosis signalling pathways or which may be used to reduce the impact of cell-to-cell heterogeneity on therapy responses. Finally, we will discuss the technical and regulatory requirements surrounding the use and implications of system-based patient stratification tools for the future of personalised oncology.

Customizing the therapeutic response of signaling networks to promote antitumor responses by drug combinations

Drug resistance, de novo and acquired, pervades cellular signaling networks (SNs) from one signaling motif to another as a result of cancer progression and/or drug intervention. This resistance is one of the key determinants of efficacy in targeted anti-cancer drug therapy. Although poorly understood, drug resistance is already being addressed in combination therapy by selecting drug targets where SN sensitivity increases due to combination components or as a result of de novo or acquired mutations. Additionally, successive drug combinations have shown low resistance potential. To promote a rational, systematic development of combination therapies, it is necessary to establish the underlying mechanisms that drive the advantages of combination therapies, and design methods to determine drug targets for combination regimens. Based on a joint systems analysis of cellular SN response and its sensitivity to drug action and oncogenic mutations, we describe an in silico method to analyze the targets of drug combinations. Our method explores mechanisms of sensitizing the SN through a combination of two drugs targeting vertical signaling pathways. We propose a paradigm of SN response customization by one drug to both maximize the effect of another drug in combination and promote a robust therapeutic response against oncogenic mutations. The method was applied to customize the response of the ErbB/PI3K/PTEN/AKT pathway by combination of drugs targeting HER2 receptors and proteins in the down-stream pathway. The results of a computational experiment showed that the modification of the SN response from hyperbolic to smooth sigmoid response by manipulation of two drugs in combination leads to greater robustness in therapeutic response against oncogenic mutations determining cancer heterogeneity. The application of this method in drug combination co-development suggests a combined evaluation of inhibition effects together with the capability of drug combinations to suppress resistance mechanisms before they become clinically manifest.

The mathematical model of the Bcl-2 family mediated MOMP regulation can perform a non-trivial pattern recognition

Interactions between individual members of the B-cell lymphoma 2 (Bcl-2) family of proteins form a regulatory network governing mitochondrial outer membrane permeabilization (MOMP). Bcl-2 family initiated MOMP causes release of the inter-membrane pro-apoptotic proteins to cytosol and creates a cytosolic environment suitable for the executionary phase of apoptosis. We designed the mathematical model of this regulatory network where the synthesis rates of the Bcl-2 family members served as the independent inputs. Using computational simulations, we have then analyzed the response of the model to up-/downregulation of the Bcl-2 proteins. Under several assumptions, and using estimated reaction parameters, a non-linear stimulus-response emerged, whose characteristics are associated with bistability and switch-like behavior. Interestingly, using the principal component analysis (PCA) we have shown that the given model of the Bcl-2 family interactions classifies the random combinations of inputs into two distinct classes, and responds to these by one of the two qualitatively distinct outputs. As we showed, the emergence of this behavior requires specific organization of the interactions between particular Bcl-2 proteins.

Protective effects of p38 MAPK inhibitor SB202190 against hippocampal apoptosis and spatial learning and memory deficits in a rat model of vascular dementia

Vascular dementia (VaD) is a common age-related neurodegenerative disease resulting from chronic hypoxia. In the present study, we examined the protective effects of p38 MAPK inhibitor SB202190 against hippocampal apoptosis and spatial learning and memory deficits in a chronic hypoperfusion rat model of VaD established by permanent bilateral carotid occlusion (2-VO). Sixty rats were randomly divided into sham-operated, VaD model, and VaD plus SB202190 groups (n = 20/group). After sham/2-VO surgery, rats were administered 0.1% DMSO (sham-operated and VaD groups) or SB202190 by intracerebroventricular injection. One week after inhibitor/vehicle treatment, hippocampal p38 MAPK phosphorylation was higher in the model group than in the SB202190 group (P < 0.01). Compared to the model group, the SB202190 group exhibited significantly shorter escape latencies in the Morris water maze hidden platform trials (P < 0.01) and longer times in the original platform quadrant during probe trials (P < 0.01). The SB202190 group also showed significantly reduced neuronal apoptosis in the hippocampus compared to VaD model rats (P < 0.01) as well as higher (antiapoptotic) Bcl-2 expression and lower (proapoptotic) caspase-3 expression (P < 0.01 for both). In conclusion, blockade of the p38 MAPK signaling pathway by SB202190 following permanent 2-OV reduced apoptosis of hippocampal neurons and rescued spatial learning and memory deficits.

Decision-tree based model analysis for efficient identification of parameter relations leading to different signaling states

In systems biology, a mathematical description of signal transduction processes is used to gain a more detailed mechanistic understanding of cellular signaling networks. Such models typically depend on a number of parameters that have different influence on the model behavior. Local sensitivity analysis is able to identify parameters that have the largest effect on signaling strength. Bifurcation analysis shows on which parameters a qualitative model response depends. Most methods for model analysis are intrinsically univariate. They typically cannot consider combinations of parameters since the search space for such analysis would be too large. This limitation is important since activation of a signaling pathway often relies on multiple rather than on single factors. Here, we present a novel method for model analysis that overcomes this limitation. As input to a model defined by a system of ordinary differential equations, we consider parameters for initial chemical species concentrations. The model is used to simulate the system response, which is then classified into pre-defined classes (e.g., active or not active). This is combined with a scan of the parameter space. Parameter sets leading to a certain system response are subjected to a decision tree algorithm, which learns conditions that lead to this response. We compare our method to two alternative multivariate approaches to model analysis: analytical solution for steady states combined with a parameter scan, and direct Lyapunov exponent (DLE) analysis. We use three previously published models including a model for EGF receptor internalization and two apoptosis models to demonstrate the power of our approach. Our method reproduces critical parameter relations previously obtained by both steady-state and DLE analysis while being more generally applicable and substantially less computationally expensive. The method can be used as a general tool to predict multivariate control strategies for pathway activation and to suggest strategies for drug intervention.

Partial equilibrium approximations in apoptosis. I. The intracellular-signaling subsystem

Apoptosis is one of the most basic biological processes. In apoptosis, tens of species are involved in many biochemical reactions with times scales of widely differing orders of magnitude. By the law of mass action, the process is mathematically described with a large and stiff system of ODEs (ordinary differential equations). The goal of this work is to simplify such systems of ODEs with the PEA (partial equilibrium approximation) method. In doing so, we propose a general framework of the PEA method together with some conditions, under which the PEA method can be justified rigorously. The main condition is the principle of detailed balance for fast reactions as a whole and the framework provides some meaningful physical insights of the full chemical kinetics. With the justified method as a tool, we simplify the Fas-signaling pathway model due to Hua et al. [6] under the empirical assumption that nine reactions therein can be well regarded as relatively fast. This paper reports our simplification, together with numerical results which confirm the reliability of both our simplified model and the empirical assumption.

Death ligand concentration and the membrane proximal signaling module regulate the type 1/type 2 choice in apoptotic death signaling

Apoptotic death pathways are frequently activated by death ligand induction and subsequent activation of the membrane proximal signaling module. Death receptors cluster upon binding to death ligands, leading to formation of a membrane proximal death-inducing-signaling-complex (DISC). In this membrane proximal signalosome, initiator caspases (caspase 8) are processed resulting in activation of both type 1 and type 2 pathways of apoptosis signaling. How the type 1/type 2 choice is made is an important question in the systems biology of apoptosis signaling. In this study, we utilize a Monte Carlo based in silico approach to elucidate the role of membrane proximal signaling module in the type 1/type 2 choice of apoptosis signaling. Our results provide crucial mechanistic insights into the formation of DISC signalosome and caspase 8 activation. Increased concentration of death ligands was shown to correlate with increased type 1 activation. We also study the caspase 6 mediated system level feedback activation of apoptosis signaling and its role in the type 1/type 2 choice. Our results clarify the basis of cell-to-cell stochastic variability in apoptosis activation and ramifications of this issue is further discussed in the context of therapies for cancer and neurodegenerative disorders.

Mitochondrial VDAC and hexokinase together modulate plant programmed cell death

The voltage-dependent anion channel (VDAC) and mitochondrially located hexokinase have been implicated both in pathways leading to cell death on the one hand, and immortalization in tumor formation on the other. While both proteins have also been implicated in death processes in plants, their interaction has not been explored. We have examined cell death following heterologous expression of a rice VDAC in the tobacco cell line BY2 and in leaves of tobacco plants and show that it is ameliorated by co-expression of hexokinase. Hexokinase also abrogates death induced by H2O2. We conclude that the ratio of expression of the two proteins and their interaction play a major role in modulating death pathways in plants.

Modeling heterogeneous responsiveness of intrinsic apoptosis pathway

BACKGROUND

Apoptosis is a cell suicide mechanism that enables multicellular organisms to maintain homeostasis and to eliminate individual cells that threaten the organism's survival. Dependent on the type of stimulus, apoptosis can be propagated by extrinsic pathway or intrinsic pathway. The comprehensive understanding of the molecular mechanism of apoptotic signaling allows for development of mathematical models, aiming to elucidate dynamical and systems properties of apoptotic signaling networks. There have been extensive efforts in modeling deterministic apoptosis network accounting for average behavior of a population of cells. Cellular networks, however, are inherently stochastic and significant cell-to-cell variability in apoptosis response has been observed at single cell level.

RESULTS

To address the inevitable randomness in the intrinsic apoptosis mechanism, we develop a theoretical and computational modeling framework of intrinsic apoptosis pathway at single-cell level, accounting for both deterministic and stochastic behavior. Our deterministic model, adapted from the well-accepted Fussenegger model, shows that an additional positive feedback between the executioner caspase and the initiator caspase plays a fundamental role in yielding the desired property of bistability. We then examine the impact of intrinsic fluctuations of biochemical reactions, viewed as intrinsic noise, and natural variation of protein concentrations, viewed as extrinsic noise, on behavior of the intrinsic apoptosis network. Histograms of the steady-state output at varying input levels show that the intrinsic noise could elicit a wider region of bistability over that of the deterministic model. However, the system stochasticity due to intrinsic fluctuations, such as the noise of steady-state response and the randomness of response delay, shows that the intrinsic noise in general is insufficient to produce significant cell-to-cell variations at physiologically relevant level of molecular numbers. Furthermore, the extrinsic noise represented by random variations of two key apoptotic proteins, namely Cytochrome C and inhibitor of apoptosis proteins (IAP), is modeled separately or in combination with intrinsic noise. The resultant stochasticity in the timing of intrinsic apoptosis response shows that the fluctuating protein variations can induce cell-to-cell stochastic variability at a quantitative level agreeing with experiments. Finally, simulations illustrate that the mean abundance of fluctuating IAP protein is positively correlated with the degree of cellular stochasticity of the intrinsic apoptosis pathway.

CONCLUSIONS

Our theoretical and computational study shows that the pronounced non-genetic heterogeneity in intrinsic apoptosis responses among individual cells plausibly arises from extrinsic rather than intrinsic origin of fluctuations. In addition, it predicts that the IAP protein could serve as a potential therapeutic target for suppression of the cell-to-cell variation in the intrinsic apoptosis responsiveness.

Monte carlo study elucidates the type 1/type 2 choice in apoptotic death signaling in healthy and cancer cells

Apoptotic cell death is coordinated through two distinct (type 1 and type 2) intracellular signaling pathways. How the type 1/type 2 choice is made remains a central problem in the biology of apoptosis and has implications for apoptosis related diseases and therapy. We study the problem of type 1/type 2 choice in silico utilizing a kinetic Monte Carlo model of cell death signaling. Our results show that the type 1/type 2 choice is linked to deterministic versus stochastic cell death activation, elucidating a unique regulatory control of the apoptotic pathways. Consistent with previous findings, our results indicate that caspase 8 activation level is a key regulator of the choice between deterministic type 1 and stochastic type 2 pathways, irrespective of cell types. Expression levels of signaling molecules downstream also regulate the type 1/type 2 choice. A simplified model of DISC clustering elucidates the mechanism of increased active caspase 8 generation and type 1 activation in cancer cells having increased sensitivity to death receptor activation. We demonstrate that rapid deterministic activation of the type 1 pathway can selectively target such cancer cells, especially if XIAP is also inhibited; while inherent cell-to-cell variability would allow normal cells stay protected.

STL-based analysis of TRAIL-induced apoptosis challenges the notion of type I/type II cell line classification

Extrinsic apoptosis is a programmed cell death triggered by external ligands, such as the TNF-related apoptosis inducing ligand (TRAIL). Depending on the cell line, the specific molecular mechanisms leading to cell death may significantly differ. Precise characterization of these differences is crucial for understanding and exploiting extrinsic apoptosis. Cells show distinct behaviors on several aspects of apoptosis, including (i) the relative order of caspases activation, (ii) the necessity of mitochondria outer membrane permeabilization (MOMP) for effector caspase activation, and (iii) the survival of cell lines overexpressing Bcl2. These differences are attributed to the activation of one of two pathways, leading to classification of cell lines into two groups: type I and type II. In this work we challenge this type I/type II cell line classification. We encode the three aforementioned distinguishing behaviors in a formal language, called signal temporal logic (STL), and use it to extensively test the validity of a previously-proposed model of TRAIL-induced apoptosis with respect to experimental observations made on different cell lines. After having solved a few inconsistencies using STL-guided parameter search, we show that these three criteria do not define consistent cell line classifications in type I or type II, and suggest mutants that are predicted to exhibit ambivalent behaviors. In particular, this finding sheds light on the role of a feedback loop between caspases, and reconciliates two apparently-conflicting views regarding the importance of either upstream or downstream processes for cell-type determination. More generally, our work suggests that these three distinguishing behaviors should be merely considered as type I/II features rather than cell-type defining criteria. On the methodological side, this work illustrates the biological relevance of STL-diagrams, STL population data, and STL-guided parameter search implemented in the tool Breach. Such tools are well-adapted to the ever-increasing availability of heterogeneous knowledge on complex signal transduction pathways.

Apoptosis, a major form of programmed cell death, plays a crucial role in shaping organs during development and controls homeostasis and tissue integrity throughout life. Defective apoptosis is often involved in cancer development and progression. Current understanding of externally triggered apoptosis is that death results from the activation of one out of two parallel signal transduction pathways. This leads to a classification of cell lines in two main types: type I and II. In the context of chemotherapy, understanding the cell-line-specific molecular mechanisms of apoptosis is important since this could guide drug usage. Biologists investigate the details of signal transduction pathways often at the single cell level and construct models to assess their current understanding. However, no systematic approach is employed to check the consistency of model predictions and experimental observations on various cell lines. Here we propose to use a formal specification language to encode the observed properties and a systematic approach to test whether model predictions are consistent with expected properties. Such property-guided model development and model revision approaches should guarantee an optimal use of the often heterogeneous experimental data.

Data-driven modeling of SRC control on the mitochondrial pathway of apoptosis: implication for anticancer therapy optimization

Src tyrosine kinases are deregulated in numerous cancers and may favor tumorigenesis and tumor progression. We previously described that Src activation in NIH-3T3 mouse fibroblasts promoted cell resistance to apoptosis. Indeed, Src was found to accelerate the degradation of the pro-apoptotic BH3-only protein Bik and compromised Bax activation as well as subsequent mitochondrial outer membrane permeabilization. The present study undertook a systems biomedicine approach to design optimal anticancer therapeutic strategies using Src-transformed and parental fibroblasts as a biological model. First, a mathematical model of Bik kinetics was designed and fitted to biological data. It guided further experimental investigation that showed that Bik total amount remained constant during staurosporine exposure, and suggested that Bik protein might undergo activation to induce apoptosis. Then, a mathematical model of the mitochondrial pathway of apoptosis was designed and fitted to experimental results. It showed that Src inhibitors could circumvent resistance to apoptosis in Src-transformed cells but gave no specific advantage to parental cells. In addition, it predicted that inhibitors of Bcl-2 antiapoptotic proteins such as ABT-737 should not be used in this biological system in which apoptosis resistance relied on the deficiency of an apoptosis accelerator but not on the overexpression of an apoptosis inhibitor, which was experimentally verified. Finally, we designed theoretically optimal therapeutic strategies using the data-calibrated model. All of them relied on the observed Bax overexpression in Src-transformed cells compared to parental fibroblasts. Indeed, they all involved Bax downregulation such that Bax levels would still be high enough to induce apoptosis in Src-transformed cells but not in parental ones. Efficacy of this counterintuitive therapeutic strategy was further experimentally validated. Thus, the use of Bax inhibitors might be an unexpected way to specifically target cancer cells with deregulated Src tyrosine kinase activity.

Properties of cell death models calibrated and compared using Bayesian approaches

Using models to simulate and analyze biological networks requires principled approaches to parameter estimation and model discrimination. We use Bayesian and Monte Carlo methods to recover the full probability distributions of free parameters (initial protein concentrations and rate constants) for mass-action models of receptor-mediated cell death. The width of the individual parameter distributions is largely determined by non-identifiability but covariation among parameters, even those that are poorly determined, encodes essential information. Knowledge of joint parameter distributions makes it possible to compute the uncertainty of model-based predictions whereas ignoring it (e.g., by treating parameters as a simple list of values and variances) yields nonsensical predictions. Computing the Bayes factor from joint distributions yields the odds ratio (∼20-fold) for competing 'direct' and 'indirect' apoptosis models having different numbers of parameters. Our results illustrate how Bayesian approaches to model calibration and discrimination combined with single-cell data represent a generally useful and rigorous approach to discriminate between competing hypotheses in the face of parametric and topological uncertainty.

Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP

MOTIVATION

TRAIL has been widely studied for the ability to kill cancer cells selectively, but its clinical usefulness has been hindered by the development of resistance. Multiple compounds have been identified that sensitize cancer cells to TRAIL-induced apoptosis. The drug LY303511 (LY30), combined with TRAIL, caused synergistic (greater than additive) killing of multiple cancer cell lines. We used mathematical modelling and ordinary differential equations to represent how LY30 and TRAIL individually affect HeLa cells, and to predict how the combined treatment achieves synergy.

RESULTS

Model-based predictions were compared with in vitro experiments. The combination treatment model was successful at mimicking the synergistic levels of cell death caused by LY30 and TRAIL combined. However, there were significant failures of the model to mimic upstream activation at early time points, particularly the slope of caspase-8 activation. This flaw in the model led us to perform additional measurements of early caspase-8 activation. Surprisingly, caspase-8 exhibited a transient decrease in activity after LY30 treatment, prior to strong activation. cFLIP, an inhibitor of caspase-8 activation, was up-regulated briefly after 30 min of LY30 treatment, followed by a significant down-regulation over prolonged exposure. A further model suggested that LY30-induced fluctuation of cFLIP might result from tilting the ratio of two key species of reactive oxygen species (ROS), superoxide and hydrogen peroxide. Computational modelling extracted novel biological implications from measured dynamics, identified time intervals with unexplained effects, and clarified the non-monotonic effects of the drug LY30 on cFLIP during cancer cell apoptosis.

Theoretical Analysis of Fas Ligand-Induced Apoptosis with an Ordinary Differential Equation Model

Upon the treatment of Fas ligand, different types of cells exhibit different apoptotic mechanisms, which are determined by a complex network of biological pathways. In order to derive a quantitative interpretation of the cell sensitivity and apoptosis pathways, we have developed an ordinary differential equation model. Our model is intended to include all of the known major components in apoptosis pathways mediated by Fas receptor. It is composed of 29 equations using a total of 49 rate constants and 13 protein concentrations. All parameters used in our model were derived through nonlinear fitting to experimentally measured concentrations of four selected proteins in Jurkat T-cells, including caspase-3, caspase-8, caspase-9, and Bid. Our model is able to correctly interpret the role of kinetic parameters and protein concentrations in cell sensitivity to FasL. It reveals the possible reasons for the transition between type-I and type-II pathways and also provides some interesting predictions, such as the more decisive role of Fas over Bax in apoptosis pathway and a possible feedback mechanism between type-I and type-II pathways. But our model failed in predicting FasL-induced apoptotic mechanism of NCI-60 cells from their gene-expression levels. Limitations in our model are also discussed.

Systems analysis of cancer cell heterogeneity in caspase-dependent apoptosis subsequent to mitochondrial outer membrane permeabilization

Deregulation of apoptosis is a hallmark of carcinogenesis. We here combine live cell imaging and systems modeling to investigate caspase-dependent apoptosis execution subsequent to mitochondrial outer membrane permeabilization (MOMP) in several cancer cell lines. We demonstrate that, although most cell lines that underwent MOMP also showed robust and fast activation of executioner caspases and apoptosis, the colorectal cancer cell lines LoVo and HCT-116 Smac(-/-), similar to X-linked inhibitor of apoptosis protein (XIAP)-overexpressing HeLa (HeLa XIAP(Adv)) cells, only showed delayed and often no caspase activation, suggesting apoptosis impairment subsequent to MOMP. Employing APOPTO-CELL, a recently established model of apoptosis subsequent to MOMP, this impairment could be understood by studying the systemic interaction of five proteins that are present in the apoptosis pathway subsequent to MOMP. Using APOPTO-CELL as a tool to study detailed molecular mechanisms during apoptosis execution in individual cell lines, we demonstrate that caspase-9 was the most important regulator in DLD-1, HCT-116, and HeLa cells and identified additional cell line-specific co-regulators. Developing and applying a computational workflow for parameter screening, systems modeling identified that apoptosis execution kinetics are more robust against changes in reaction kinetics in HCT-116 and HeLa than in DLD-1 cells. Our systems modeling study is the first to draw attention to the variability in cell specific protein levels and reaction rates and to the emergent effects of such variability on the efficiency of apoptosis execution and on apoptosis impairment subsequent to MOMP.

PEG-liposomal oxaliplatin induces apoptosis in human colorectal cancer cells via Fas/FasL and caspase-8

Since cellular uptake of PEG [poly(ethylene glycol)]-liposomal L-OHP (oxaliplatin) induces bioactive changes in CRC (colorectal cancer), we have investigated its apoptotic effect and anticancer mechanism. Human CRC SW480 cells were treated with PEG-liposomal L-OHP and a caspase-8 inhibitor [Z-IETD-FMK (benzyloxycarbonyl-Ile-Glu-Thr-dl-Asp-fluoromethylketone)]. Apoptosis was measured by FCM (flow cytometry) and TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick-end labelling) assay. Expression of Fas/FasL and cytochrome c was detected using FCM and an immunofluorescence assay. Expression of caspase-8, Bid, caspase-9, caspase-7 and activated caspase-3 (P17) was examined by Western blot analyses. The results indicated that PEG-liposomal L-OHP (28 μg/ml L-OHP) induced marked apoptosis in SW480 cells compared with 28 μg/ml free L-OHP. The expression levels of Fas, FasL, cytochrome c, caspase-9, caspase-7 and activated caspase-3 proteins were up-regulated, with a corresponding increase in apoptosis; however, expression of caspase-8 and Bid were down-regulated as apoptosis increased. When cells were treated with Z-IETD-FMK, apoptosis was inhibited, but there was little impact on the expression of Fas, FasL, cytochrome c, Bid, caspase-9, caspase-7 and activated caspase-3. These findings indicate that PEG-liposomal L-OHP enhances the anticancer potency of the chemotherapeutic agent; moreover, Fas/FasL and caspase-8 signalling pathways play a key role in mediating PEG-liposomal L-OHP-induced apoptosis.

The molecular mechanism of apoptosis upon caspase-8 activation: quantitative experimental validation of a mathematical model

Caspase-8 (CASP8) is a cysteine protease that plays a pivotal role in the extrinsic apoptotic signaling pathway via death receptors. The kinetics, dynamics, and selectivity with which the pathway transmits apoptotic signals to downstream molecules upon CASP8 activation are not fully understood. We have developed a system for using high-sensitivity FRET-based biosensors to monitor the protease activity of CASP8 and its downstream effector, caspase-3, in living single cells. Using this system, we systematically investigated the caspase cascade by regulating the magnitude of extrinsic signals received by the cell. Furthermore, we determined the molar concentration of five caspases and Bid required for hierarchical transmission of apoptotic signals in a HeLa cell. Based on these quantitative experimental data, we validated a mathematical model suitable for estimation of the kinetics and dynamics of caspases, which predicts the minimal concentration of CASP8 required to act as an initiator. Consequently, we found that less than 1% of the total CASP8 proteins are sufficient to set the apoptotic program in motion if activated. Taken together, our findings demonstrate the precise cascade of CASP8-mediated apoptotic signals through the extrinsic pathway.

PDCD5-regulated cell fate decision after ultraviolet-irradiation-induced DNA damage

Programmed cell death 5 (PDCD5) is a human apoptosis-related molecule that is involved in both the cytoplasmic caspase-3 activity pathway (by regulating Bax translocation from cytoplasm to mitochondria) and the nuclear pathway (by interacting with Tip60). In this study, we developed a mathematical model of the PDCD5-regulated switching of the cell response from DNA repair to apoptosis after ultraviolet irradiation-induced DNA damage. We established the model by combining several hypotheses with experimental observations. Our simulations indicate that the ultimate cell response to DNA damage is dependent on a signal threshold mechanism, and the PDCD5 promotion of Bax translocation plays an essential role in PDCD5-regulated cell apoptosis. Furthermore, the model simulations revealed that PDCD5 nuclear translocation can attenuate cell apoptosis, and PDCD5 interactions with Tip60 can accelerate DNA damage-induced apoptosis, but the final cell fate decision is insensitive to the PDCD5-Tip60 interaction. These results are consistent with experimental observations. The effect of recombinant human PDCD5 was also investigated and shown to sensitize cells to DNA damage by promoting caspase-3 activity.

Pharmacodynamic modelling of biomarker data in oncology

The development of pharmacodynamic (PD) biomarkers in oncology has implications for design of clinical protocols from preclinical data and for predicting clinical outcomes from early clinical data. Two classes of biomarkers have received particular attention. Phosphoproteins in biopsy samples are markers of inhibition of signalling pathways, target sites for many novel agents. Biomarkers of apoptosis in plasma can measure tumour cell killing by drugs in phase I clinical trials. The predictive power of PD biomarkers is enhanced by data modelling. With pharmacokinetic models, PD models form PK/PD models that predict the time course both of drug concentration and drug effects. If biomarkers of drug toxicity are also measured, the models can predict drug selectivity as well as efficacy. PK/PD models, in conjunction with disease models, make possible virtual clinical trials, in which multiple trial designs are assessed in silico, so the optimal trial design can be selected for experimental evaluation.

Role of the common γ chain in cell cycle progression of human malignant cell lines

The γ-chain (γc) is a transducing element shared between several cytokine receptors whose alteration causes X-linked severe combined immunodeficiency. Recently, a direct involvement of γc in self-sufficient growth in a concentration-dependent manner was described, implying a direct relationship between the amount of the molecule and its role in cell cycle progression. In this study, we evaluate whether γc expression could interfere in cell cycle progression also in malignant hematopoietic cells. Here, we first report that in the absence of γc expression, lymphoblastoid B-cell lines (BCLs) die at a higher extent than control cells. This phenomenon is caspase-3 independent and is associated to a decreased expression of the antiapoptotic Bcl-2 family members. By contrast, increased expression of γc protein directly correlates with spontaneous cell growth in several malignant hematopoietic cell lines. We, also, find that the knockdown of γc protein through short interfering RNA is able to decrease the cell proliferation rate in these malignancies. Furthermore, an increased expression of all D-type cyclins is found in proliferating neoplastic cells. In addition, a direct correlation between the amount of γc and cyclins A2 and B1 expression is found. Hence, our data demonstrate that the amount of the γc is able to influence the transcription of genes involved in cell cycle progression, thus being directly involved in the regulatory control of cell proliferation of malignant hematopoietic cells.

A modular model of the apoptosis machinery

Using a modular principle of computer hardware as a metaphor, we defined and implemented in the BioUML platform a module concept for biological pathways. BioUML provides a user interface to create modular models and convert them automatically into plain models for further simulations. Using this approach, we created the apoptosis model including 13 modules: death stimuli (TRAIL, CD95L, and TNF-α)-induced activation of caspase-8; survival stimuli (p53, EGF, and NF-κB) regulation; the mitochondria level; cytochrome C- and Smac-induced activation of caspase-3; direct activation of effector caspases by caspase-8 and - 12; PARP and apoptosis execution phase modules. Each module is based on earlier published models and extended by data from the Reactome and TRANSPATH databases. The model ability to simulate the apoptosis-related processes was checked; the modules were validated using experimental data.

AVAILABILITY

http://www.biouml.org/apoptosis.shtml .