Systems analysis of effector caspase activation and its control by X-linked inhibitor of apoptosis protein

Interplay of ferroptotic and apoptotic cell death and its modulation by BH3-mimetics

Ferroptosis and apoptosis are widely considered to be independent cell death modalities. Ferroptotic cell death is a consequence of insufficient radical detoxification and progressive lipid peroxidation, which is counteracted by glutathione peroxidase-4 (GPX4). Apoptotic cell death can be triggered by a wide variety of stresses, including oxygen radicals, and can be suppressed by anti-apoptotic members of the BCL-2 protein family. Mitochondria are the main interaction site of BCL-2 family members and likewise a major source of oxygen radical stress. We therefore studied if ferroptosis and apoptosis might intersect and possibly interfere with one another. Indeed, cells dying from impaired GPX4 activity displayed hallmarks of both ferroptotic and apoptotic cell death, with the latter including (transient) membrane blebbing, submaximal cytochrome-c release and caspase activation. Targeting BCL-2, MCL-1 or BCL-XL with BH3-mimetics under conditions of moderate ferroptotic stress in many cases synergistically enhanced overall cell death and frequently skewed primarily ferroptotic into apoptotic outcomes. Surprisingly though, in other cases BH3-mimetics, most notably the BCL-XL inhibitor WEHI-539, counter-intuitively suppressed cell death and promoted cell survival following GPX4 inhibition. Further studies revealed that most BH3-mimetics possess previously undescribed antioxidant activities that counteract ferroptotic cell death at commonly employed concentration ranges. Our results therefore show that ferroptosis and apoptosis can intersect. We also show that combining ferroptotic stress with BH3-mimetics, context-dependently can either enhance and convert cell death outcomes between ferroptosis and apoptosis or can also suppress cell death by intrinsic antioxidant activities.

Integrated multiplex analysis of cell death regulators in stage II colorectal cancer suggests patients with 'persister' cell profiles fail to benefit from adjuvant chemotherapy

Objective

Inducing tumour cell apoptosis is a primary objective of chemotherapy but, to date, there are no validated biomarkers of apoptosis sensitivity or resistance. Our objective was to image multiple apoptosis pathway proteins at single cell level and determine multi-protein associations with recurrence risk and chemotherapy response in patients with stage II colorectal cancer (CRC).

Methods and analysis

Multiplexed imaging of 16 proteins in the intrinsic and extrinsic apoptosis pathways at single cell resolution on resected tissue from 194 patients with stage II CRC who either received adjuvant chemotherapy (n=108) or were treated with surgery only (n=86). K-means clustering of >600 000 cancer cells and cell level intensities of APAF1, procaspase-9, procaspase-3, XIAP, SMAC, BAX, BAK, BCL2, BCL-XL, MCL-1, procaspase-8, BID, FADD, FLIP, RIP3 and CIAP1 identified distinct cell cluster profiles.

Results

Chemotherapy-treated patients with a higher percentage of cell clusters with low procaspase-3 and high XIAP had a higher risk of recurrence. This was validated in an independent cohort of adjuvant chemotherapy-treated high-risk patients with stage II CRC. We also applied two established system models of apoptosis initiation and execution to estimate cellular apoptosis sensitivity and show that these cell clusters do not appear to have impaired mitochondrial outer membrane permeabilisation sensitivity, but downstream procaspase-3 cleavage is compromised. This represents a key characteristic of drug-tolerant 'persister' cells.

Conclusion

This study represents the most comprehensive analysis to date of apoptosis protein distribution at single cell level in CRC tumours. Our study identifies a subgroup of patients with stage II CRC with an apoptosis-resistant 'persister' cell profile who do not benefit from adjuvant chemotherapy.

Apoptotic signaling: Beyond cell death

Apoptosis is the best described form of regulated cell death, and was, until relatively recently, considered irreversible once particular biochemical points-of-no-return were activated. In this manuscript, we examine the mechanisms cells use to escape from a self-amplifying death signaling module. We discuss the role of feedback, dynamics, propagation, and noise in apoptotic signaling. We conclude with a revised model for the role of apoptosis in animal development, homeostasis, and disease.

Toward a predictive understanding of epithelial cell death

Epithelial cell death is highly prevalent during development and tissue homeostasis. While we have a rather good understanding of the molecular regulators of programmed cell death, especially for apoptosis, we still fail to predict when, where, how many and which specific cells will die in a tissue. This likely relies on the much more complex picture of apoptosis regulation in a tissular and epithelial context, which entails cell autonomous but also non-cell autonomous factors, diverse feedback and multiple layers of regulation of the commitment to apoptosis. In this review, we illustrate this complexity of epithelial apoptosis regulation by describing these different layers of control, all demonstrating that local cell death probability is a complex emerging feature. We first focus on non-cell autonomous factors that can locally modulate the rate of cell death, including cell competition, mechanical input and geometry as well as systemic effects. We then describe the multiple feedback mechanisms generated by cell death itself. We also outline the multiple layers of regulation of epithelial cell death, including the coordination of extrusion and regulation occurring downstream of effector caspases. Eventually, we propose a roadmap to reach a more predictive understanding of cell death regulation in an epithelial context.

A mathematical framework for the emergence of winners and losers in cell competition

Cell competition is a process in multicellular organisms where cells interact with their neighbours to determine a "winner" or "loser" status. The loser cells are eliminated through programmed cell death, leaving only the winner cells to populate the tissue. Cell competition is context-dependent; the same cell type can win or lose depending on the cell type it is competing against. Hence, winner/loser status is an emergent property. A key question in cell competition is: how do cells acquire their winner/loser status? In this paper, we propose a mathematical framework for studying the emergence of winner/loser status based on a set of quantitative criteria that distinguishes competitive from non-competitive outcomes. We apply this framework in a cell-based modelling context, to both highlight the crucial role of active cell death in cell competition and identify the factors that drive cell competition.

The identification of BCL-XL and MCL-1 as key anti-apoptotic proteins in medulloblastoma that mediate distinct roles in chemotherapy resistance

Medulloblastoma is the most common malignant paediatric brain tumour, representing 20% of all paediatric intercranial tumours. Current aggressive treatment protocols and the use of radiation therapy in particular are associated with high levels of toxicity and significant adverse effects, and long-term sequelae can be severe. Therefore, improving chemotherapy efficacy could reduce the current reliance on radiation therapy. Here, we demonstrated that systems-level analysis of basal apoptosis protein expression and their signalling interactions can differentiate between medulloblastoma cell lines that undergo apoptosis in response to chemotherapy, and those that do not. Combining computational predictions with experimental BH3 profiling, we identified a therapeutically-exploitable dependence of medulloblastoma cells on BCL-XL, and experimentally validated that BCL-XL targeting, and not targeting of BCL-2 or MCL-1, can potentiate cisplatin-induced cytotoxicity in medulloblastoma cell lines with low sensitivity to cisplatin treatment. Finally, we identified MCL-1 as an anti-apoptotic mediator whose targeting is required for BCL-XL inhibitor-induced apoptosis. Collectively, our study identifies that BCL-XL and MCL-1 are the key anti-apoptotic proteins in medulloblastoma, which mediate distinct protective roles. While BCL-XL has a first-line role in protecting cells from apoptosis basally, MCL-1 represents a second line of defence that compensates for BCL-XL upon its inhibition. We provide rationale for the further evaluation of BCL-XL and MCL-1 inhibitors in the treatment of medulloblastoma, and together with current efforts to improve the cancer-specificity of BCL-2 family inhibitors, these novel treatment strategies have the potential to improve the future clinical management of medulloblastoma.

Interplay of p53 and XIAP protein dynamics orchestrates cell fate in response to chemotherapy

Chemotherapeutic drugs are used to treat almost all types of cancer, but the intended response, i.e., elimination, is often incomplete, with a subset of cancer cells resisting treatment. Two critical factors play a role in chemoresistance: the p53 tumour suppressor gene and the X-linked inhibitor of apoptosis (XIAP). These proteins have been shown to act synergistically to elicit cellular responses upon DNA damage induced by chemotherapy, yet, the mechanism is poorly understood. This study introduces a mathematical model characterising the apoptosis pathway activation by p53 before and after mitochondrial outer membrane permeabilisation upon treatment with the chemotherapy Doxorubicin (Dox). "In-silico" simulations show that the p53 dynamics change dose-dependently. Under medium to high doses of Dox, p53 concentration ultimately stabilises to a high level regardless of XIAP concentrations. However, caspase-3 activation may be triggered or not depending on the XIAP induction rate, ultimately determining whether the cell will perish or resist. Consequently, the model predicts that failure to activate apoptosis in some cancer cells expressing wild-type p53 might be due to heterogeneity between cells in upregulating the XIAP protein, rather than due to the p53 protein concentration. Our model suggests that the interplay of the p53 dynamics and the XIAP induction rate is critical to determine the cancer cells' therapeutic response.

Computational modeling of DLBCL predicts response to BH3-mimetics

In healthy cells, pro- and anti-apoptotic BCL2 family and BH3-only proteins are expressed in a delicate equilibrium. In contrast, this homeostasis is frequently perturbed in cancer cells due to the overexpression of anti-apoptotic BCL2 family proteins. Variability in the expression and sequestration of these proteins in Diffuse Large B cell Lymphoma (DLBCL) likely contributes to variability in response to BH3-mimetics. Successful deployment of BH3-mimetics in DLBCL requires reliable predictions of which lymphoma cells will respond. Here we show that a computational systems biology approach enables accurate prediction of the sensitivity of DLBCL cells to BH3-mimetics. We found that fractional killing of DLBCL, can be explained by cell-to-cell variability in the molecular abundances of signaling proteins. Importantly, by combining protein interaction data with a knowledge of genetic lesions in DLBCL cells, our in silico models accurately predict in vitro response to BH3-mimetics. Furthermore, through virtual DLBCL cells we predict synergistic combinations of BH3-mimetics, which we then experimentally validated. These results show that computational systems biology models of apoptotic signaling, when constrained by experimental data, can facilitate the rational assignment of efficacious targeted inhibitors in B cell malignancies, paving the way for development of more personalized approaches to treatment.

A triple-drug combination induces apoptosis in cervical cancer-derived cell lines

Introduction

Cervical cancer is a worldwide health problem due to the number of deaths caused by this neoplasm. In particular, in 2020, 30,000 deaths of this type of tumor were reported in Latin America. Treatments used to manage patients diagnosed in the early stages have excellent results as measured by different clinical outcomes. Existing first-line treatments are not enough to avoid cancer recurrence, progression, or metastasis in locally advanced and advanced stages. Therefore, there is a need to continue with the proposal of new therapies. Drug repositioning is a strategy to explore known medicines as treatments for other diseases. In this scenario, drugs used in other pathologies that have antitumor activity, such as metformin and sodium oxamate, are analyzed.

Methods

In this research, we combined the drugs metformin and sodium oxamate with doxorubicin (named triple therapy or TT) based on their mechanism of action and previous investigation of our group against three CC cell lines.

Results

Through flow cytometry, Western blot, and protein microarray experiments, we found TT-induced apoptosis on HeLa, CaSki, and SiHa through the caspase 3 intrinsic pathway, including the critical proapoptotic proteins BAD, BAX, cytochrome-C, and p21. In addition, mTOR and S6K phosphorylated proteins were inhibited in the three cell lines. Also, we show an anti-migratory activity of the TT, suggesting other targets of the drug combination in the late CC stages.

Discussion

These results, together with our former studies, conclude that TT inhibits the mTOR pathway leading to cell death by apoptosis. Our work provides new evidence of TT against cervical cancer as a promising antineoplastic therapy.

Live-cell imaging and mathematical analysis of the “community effect” in apoptosis

As a cellular intrinsic mechanism leading to cellular demise, apoptosis was thoroughly characterized from a mechanistic perspective. Nowadays there is an increasing interest in describing the non-cell autonomous or community effects of apoptosis, especially in the context of resistance to cancer treatments. Transitioning from cell-centered to cell population-relevant mechanisms adds a layer of complexity for imaging and analyzing an enormous number of apoptotic events. In addition, the community effect between apoptotic and living cells is difficult to be taken into account for complex analysis. We describe here a robust and easy to implement method to analyze the interactions between cancer cells, while under apoptotic pressure. Using this approach we showed as proof-of-concept that apoptosis is insensitive to cellular density, while the proximity to apoptotic cells increases the probability of a given cell to undergo apoptosis.

Modulation of signaling cross-talk between pJNK and pAKT generates optimal apoptotic response

Tumor necrosis factor alpha (TNFα) is a well-known modulator of apoptosis by maintaining a balance between proliferation and cell-death in normal cells. Cancer cells often evade apoptotic response following TNFα stimulation by altering signaling cross-talks. Thus, varying the extent of signaling cross-talk could enable optimal TNFα mediated apoptotic dynamics. Herein, we use an experimental data-driven mathematical modeling to quantitate the extent of synergistic signaling cross-talk between the intracellular entities phosphorylated JNK (pJNK) and phosphorylated AKT (pAKT) that orchestrate the phenotypic apoptosis level by modulating the activated Caspase3 dynamics. Our study reveals that this modulation is orchestrated by the distinct dynamic nature of the synergism at early and late phases. We show that this synergism in signal flow is governed by branches originating from either TNFα receptor and NFκB, which facilitates signaling through survival pathways. We demonstrate that the experimentally quantified apoptosis levels semi-quantitatively correlates with the model simulated Caspase3 transients. Interestingly, perturbing pJNK and pAKT transient dynamics fine-tunes this accumulated Caspase3 guided apoptotic response. Thus, our study offers useful insights for identifying potential targeted therapies for optimal apoptotic response.

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.

Functional Genomic Identification of Predictors of Sensitivity and Mechanisms of Resistance to Multivalent Second-Generation TRAIL-R2 Agonists

Multivalent second-generation TRAIL-R2 agonists are currently in late preclinical development and early clinical trials. Herein, we use a representative second-generation agent, MEDI3039, to address two major clinical challenges facing these agents: lack of predictive biomarkers to enable patient selection and emergence of resistance. Genome-wide CRISPR knockout screens were notable for the lack of resistance mechanisms beyond the canonical TRAIL-R2 pathway (caspase-8, FADD, BID) as well as p53 and BAX in TP53 wild-type models, whereas a CRISPR activatory screen identified cell death inhibitors MCL-1 and BCL-XL as mechanisms to suppress MEDI3039-induced cell death. High-throughput drug screening failed to identify genomic alterations associated with response to MEDI3039; however, transcriptomics analysis revealed striking association between MEDI3039 sensitivity and expression of core components of the extrinsic apoptotic pathway, most notably its main apoptotic effector caspase-8 in solid tumor cell lines. Further analyses of colorectal cell lines and patient-derived xenografts identified caspase-8 expression ratio to its endogenous regulator FLIP(L) as predictive of sensitivity to MEDI3039 in several major solid tumor types and a further subset indicated by caspase-8:MCL-1 ratio. Subsequent MEDI3039 combination screening of TRAIL-R2, caspase-8, FADD, and BID knockout models with 60 compounds with varying mechanisms of action identified two inhibitor of apoptosis proteins (IAP) that exhibited strong synergy with MEDI3039 that could reverse resistance only in BID-deleted models. In summary, we identify the ratios of caspase-8:FLIP(L) and caspase-8:MCL-1 as potential predictive biomarkers for second-generation TRAIL-R2 agonists and loss of key effectors such as FADD and caspase-8 as likely drivers of clinical resistance in solid tumors.

Mitochondrial Function and Parkinson's Disease: From the Perspective of the Electron Transport Chain

Parkinson’s disease (PD) is known as a mitochondrial disease. Some even regarded it specifically as a disorder of the complex I of the electron transport chain (ETC). The ETC is fundamental for mitochondrial energy production which is essential for neuronal health. In the past two decades, more than 20 PD-associated genes have been identified. Some are directly involved in mitochondrial functions, such as PRKN, PINK1, and DJ-1. While other PD-associate genes, such as LRRK2, SNCA, and GBA1, regulate lysosomal functions, lipid metabolism, or protein aggregation, some have been shown to indirectly affect the electron transport chain. The recent identification of CHCHD2 and UQCRC1 that are critical for functions of complex IV and complex III, respectively, provide direct evidence that PD is more than just a complex I disorder. Like UQCRC1 in preventing cytochrome c from release, functions of ETC proteins beyond oxidative phosphorylation might also contribute to the pathogenesis of PD.

Can Systems Biology Advance Clinical Precision Oncology?

Precision oncology is perceived as a way forward to treat individual cancer patients. However, knowing particular cancer mutations is not enough for optimal therapeutic treatment, because cancer genotype-phenotype relationships are nonlinear and dynamic. Systems biology studies the biological processes at the systems' level, using an array of techniques, ranging from statistical methods to network reconstruction and analysis, to mathematical modeling. Its goal is to reconstruct the complex and often counterintuitive dynamic behavior of biological systems and quantitatively predict their responses to environmental perturbations. In this paper, we review the impact of systems biology on precision oncology. We show examples of how the analysis of signal transduction networks allows to dissect resistance to targeted therapies and inform the choice of combinations of targeted drugs based on tumor molecular alterations. Patient-specific biomarkers based on dynamical models of signaling networks can have a greater prognostic value than conventional biomarkers. These examples support systems biology models as valuable tools to advance clinical and translational oncological research.

An atlas of inter- and intra-tumor heterogeneity of apoptosis competency in colorectal cancer tissue at single-cell resolution

Cancer cells’ ability to inhibit apoptosis is key to malignant transformation and limits response to therapy. Here, we performed multiplexed immunofluorescence analysis on tissue microarrays with 373 cores from 168 patients, segmentation of 2.4 million individual cells, and quantification of 18 cell lineage and apoptosis proteins. We identified an enrichment for BCL2 in immune, and BAK, SMAC, and XIAP in cancer cells. Ordinary differential equation-based modeling of apoptosis sensitivity at single-cell resolution was conducted and an atlas of inter- and intra-tumor heterogeneity in apoptosis susceptibility generated. Systems modeling at single-cell resolution identified an enhanced sensitivity of cancer cells to mitochondrial permeabilization and executioner caspase activation compared to immune and stromal cells, but showed significant inter- and intra-tumor heterogeneity.

Two-level modeling approach to identify the regulatory dynamics capturing drug response heterogeneity in single-cells

Single-cell multimodal technologies reveal the scales of cellular heterogeneity impairing cancer treatment, yet cell response dynamics remain largely underused to decipher the mechanisms of drug resistance they take part in. As the phenotypic heterogeneity of a clonal cell population informs on the capacity of each single-cell to recapitulate the whole range of observed behaviors, we developed a modeling approach utilizing single-cell response data to identify regulatory reactions driving population heterogeneity in drug response. Dynamic data of hundreds of HeLa cells treated with TNF-related apoptosis-inducing ligand (TRAIL) were used to characterize the fate-determining kinetic parameters of an apoptosis receptor reaction model. Selected reactions sets were augmented to incorporate a mechanism that leads to the separation of the opposing response phenotypes. Using a positive feedback loop motif to identify the reaction set, we show that caspase-8 is able to encapsulate high levels of heterogeneity by introducing a response delay and amplifying the initial differences arising from natural protein expression variability. Our approach enables the identification of fate-determining reactions that drive the population response heterogeneity, providing regulatory targets to curb the cell dynamics of drug resistance.

CASPAM: A Triple-Modality Biosensor for Multiplexed Imaging of Caspase Network Activity

Understanding signal propagation across biological networks requires to simultaneously monitor the dynamics of several nodes to uncover correlations masked by inherent intercellular variability. To monitor the enzymatic activity of more than two components over short time scales has proven challenging. Exploiting the narrow spectral width of homo-FRET-based biosensors, up to three activities can be imaged through fluorescence polarization anisotropy microscopy. We introduce Caspase Activity Sensor by Polarization Anisotropy Multiplexing (CASPAM) a single-plasmid triple-modality reporter of key nodes of the apoptotic network. Apoptosis provides an ideal molecular framework to study interactions between its three composing pathways (intrinsic, extrinsic, and effector). We characterized the biosensor performance and demonstrated the advantages that equimolar expression has in both simplifying experimental procedure and reducing observable variation, thus enabling robust data-driven modeling. Tools like CASPAM become essential to analyze molecular pathways where multiple nodes need to be simultaneously monitored.

Apoptotic cells represent a dynamic stem cell niche governing proliferation and tissue regeneration

Stem cells (SCs) play a key role in homeostasis and repair. While many studies have focused on SC self-renewal and differentiation, little is known regarding the molecular mechanism regulating SC elimination and compensation upon loss. Here, we report that Caspase-9 deletion in hair follicle SCs (HFSCs) attenuates the apoptotic cascade, resulting in significant temporal delays. Surprisingly, Casp9-deficient HFSCs accumulate high levels of cleaved caspase-3 and are improperly cleared due to an essential caspase-3/caspase-9 feedforward loop. These SCs are retained in an apoptotic-engaged state, serving as mitogenic signaling centers by continuously releasing Wnt3 and instructing proliferation. Investigating the underlying mechanism, we reveal a caspase-3/Dusp8/p38 module responsible for Wnt3 induction, which operates in both normal and Casp9-deleted HFSCs. Notably, Casp9-deleted mice display accelerated wound repair and de novo hair follicle regeneration. Taken together, we demonstrate that apoptotic cells represent a dynamic SC niche, from which emanating signals drive SC proliferation and tissue regeneration.

Mutagenic Consequences of Sublethal Cell Death Signaling

Many human cancers exhibit defects in key DNA damage response elements that can render tumors insensitive to the cell death-promoting properties of DNA-damaging therapies. Using agents that directly induce apoptosis by targeting apoptotic components, rather than relying on DNA damage to indirectly stimulate apoptosis of cancer cells, may overcome classical blocks exploited by cancer cells to evade apoptotic cell death. However, there is increasing evidence that cells surviving sublethal exposure to classical apoptotic signaling may recover with newly acquired genomic changes which may have oncogenic potential, and so could theoretically spur the development of subsequent cancers in cured patients. Encouragingly, cells surviving sublethal necroptotic signaling did not acquire mutations, suggesting that necroptosis-inducing anti-cancer drugs may be less likely to trigger therapy-related cancers. We are yet to develop effective direct inducers of other cell death pathways, and as such, data regarding the consequences of cells surviving sublethal stimulation of those pathways are still emerging. This review details the currently known mutagenic consequences of cells surviving different cell death signaling pathways, with implications for potential oncogenic transformation. Understanding the mechanisms of mutagenesis associated (or not) with various cell death pathways will guide us in the development of future therapeutics to minimize therapy-related side effects associated with DNA damage.

Development of a protein signature to enable clinical positioning of IAP inhibitors in colorectal cancer

Resistance to chemotherapy-induced cell death is a major barrier to effective treatment of solid tumours such as colorectal cancer, CRC. Herein, we present a study aimed at developing a proteomics-based predictor of response to standard-of-care (SoC) chemotherapy in combination with antagonists of IAPs (inhibitors of apoptosis proteins), which have been implicated as mediators of drug resistance in CRC. We quantified the absolute expression of 19 key apoptotic proteins at baseline in a panel of 12 CRC cell lines representative of the genetic diversity seen in this disease to identify which proteins promote resistance or sensitivity to a model IAP antagonist [birinapant (Bir)] alone and in combination with SoC chemotherapy (5FU plus oxaliplatin). Quantitative western blotting demonstrated heterogeneous expression of IAP interactome proteins across the CRC cell line panel, and cell death analyses revealed a widely varied response to Bir/chemotherapy combinations. Baseline protein expression of cIAP1, caspase-8 and RIPK1 expression robustly correlated with response to Bir/chemotherapy combinations. Classifying cell lines into 'responsive', 'intermediate' and 'resistant' groups and using linear discriminant analysis (LDA) enabled the identification of a 12-protein signature that separated responders to Bir/chemotherapy combinations in the CRC cell line panel with 100% accuracy. Moreover, the LDA model was able to predict response accurately when cells were cocultured with Tumour necrosis factor-alpha to mimic a pro-inflammatory tumour microenvironment. Thus, our study provides the starting point for a proteomics-based companion diagnostic that predicts response to IAP antagonist/SoC chemotherapy combinations in CRC.

BAX and SMAC regulate bistable properties of the apoptotic caspase system

The initiation of apoptosis is a core mechanism in cellular biology by which organisms control the removal of damaged or unnecessary cells. The irreversible activation of caspases is essential for apoptosis, and mathematical models have demonstrated that the process is tightly regulated by positive feedback and a bistable switch. BAX and SMAC are often dysregulated in diseases such as cancer or neurodegeneration and are two key regulators that interact with the caspase system generating the apoptotic switch. Here we present a mathematical model of how BAX and SMAC control the apoptotic switch. Formulated as a system of ordinary differential equations, the model summarises experimental and computational evidence from the literature and incorporates the biochemical mechanisms of how BAX and SMAC interact with the components of the caspase system. Using simulations and bifurcation analysis, we find that both BAX and SMAC regulate the time-delay and activation threshold of the apoptotic switch. Interestingly, the model predicted that BAX (not SMAC) controls the amplitude of the apoptotic switch. Cell culture experiments using siRNA mediated BAX and SMAC knockdowns validated this model prediction. We further validated the model using data of the NCI-60 cell line panel using BAX protein expression as a cell-line specific parameter and show that model simulations correlated with the cellular response to DNA damaging drugs and established a defined threshold for caspase activation that could distinguish between sensitive and resistant melanoma cells. In summary, we present an experimentally validated dynamic model that summarises our current knowledge of how BAX and SMAC regulate the bistable properties of irreversible caspase activation during apoptosis.

Getting the Right Grip? How Understanding Electrophile Selectivity Profiles Could Illuminate Our Understanding of Redox Signaling

Significance: Electrophile signaling is coming into focus as a bona fide cell signaling mechanism. The electrophilic regulation occurs typically through a sensing event (i.e., labeling of a protein) and a signaling event (the labeling event having an effect of the proteins activity, association, etc.). Recent Advances: Herein, we focus on the first step of this process, electrophile sensing. Electrophile sensing is typically a deceptively simple reaction between the thiol of a protein cysteine, of which there are around 200,000 in the human proteome, and a Michael acceptor, of which there are numerous flavors, including enals and enones. Recent data overall paint a picture that despite being a simple chemical reaction, electrophile sensing is a discerning process, showing labeling preferences that are often not in line with reactivity of the electrophile. Critical Issues: With a view to trying to decide what brings about highly electrophile-reactive protein cysteines, and how reactive these sensors may be, we discuss aspects of the thermodynamics and kinetics of covalent/noncovalent binding. Data made available by several laboratories indicate that it is likely that specific proteins exhibit highly stereo- and chemoselective electrophile sensing, which we take as good evidence for recognition between the electrophile and the protein before forming a covalent bond. Future Directions: We propose experiments that could help us gain a better and more quantitative understanding of the mechanisms through which sensing comes about. We further extoll the importance of performing more detailed experiments on labeling and trying to standardize the way we assess protein-specific electrophile sensing.

Long noncoding RNA: a dazzling dancer in tumor immune microenvironment

Long noncoding RNAs (lncRNAs) are a class of endogenous, non-protein coding RNAs that are highly linked to various cellular functions and pathological process. Emerging evidence indicates that lncRNAs participate in crosstalk between tumor and stroma, and reprogramming of tumor immune microenvironment (TIME). TIME possesses distinct populations of myeloid cells and lymphocytes to influence the immune escape of cancer, the response to immunotherapy, and the survival of patients. However, hitherto, a comprehensive review aiming at relationship between lncRNAs and TIME is missing. In this review, we focus on the functional roles and molecular mechanisms of lncRNAs within the TIME. Furthermore, we discussed the potential immunotherapeutic strategies based on lncRNAs and their limitations.

The Oscillation Amplitude, Not the Frequency of Cytosolic Calcium, Regulates Apoptosis Induction

Although a rising concentration of cytosolic Ca²⁺ has long been recognized as an essential signal for apoptosis, the dynamical mechanisms by which Ca²⁺ regulates apoptosis are not clear yet. To address this, we constructed a computational model that integrates known biochemical reactions and can reproduce the dynamical behaviors of Ca²⁺-induced apoptosis as observed in experiments. Model analysis shows that oscillating Ca²⁺ signals first convert into gradual signals and eventually transform into a switch-like apoptotic response. Via the two processes, the apoptotic signaling pathway filters the frequency of Ca²⁺ oscillations effectively but instead responds acutely to their amplitude. Collectively, our results suggest that Ca²⁺ regulates apoptosis mainly via oscillation amplitude, rather than frequency, modulation. This study not only provides a comprehensive understanding of how oscillatory Ca²⁺ dynamically regulates the complex apoptotic signaling network but also presents a typical example of how Ca²⁺ controls cellular responses through amplitude modulation.

MicroRNA-130a regulates neurological deficit and angiogenesis in rats with ischaemic stroke by targeting XIAP

MicroRNAs (miRNAs) have already been proposed to be implicated in the development of ischaemic stroke. We aim to investigate the role of miR-130a in the neurological deficit and angiogenesis in rats with ischaemic stroke by regulating X-linked inhibitor of apoptosis protein (XIAP). Middle cerebral artery occlusion (MCAO) models were established by suture-occluded method, and MCAO rats were then treated with miR-130a mimics/inhibitors or/and altered XIAP for detection of changes of rats' neurological function, nerve damage and angiogenesis in MCAO rats. The oxygen-glucose deprivation (OGD) cellular models were established and respectively treated to determine the roles of miR-130a and XIAP in neuronal viability and apoptosis. The expression levels of miR-130a and XIAP in brain tissues of MCAO rats and OGD-treated neurons were detected. The binding site between miR-130a and XIAP was verified by luciferase activity assay. MiR-130a was overexpressed while XIAP was down-regulated in MCAO rats and OGD-treated neurons. In animal models, suppressed miR-130a improved neurological function, alleviated nerve damage and increased new vessels in brain tissues of rats with MCAO. In cellular models, miR-130a inhibition promoted neuronal viability and suppressed apoptosis. Inhibited XIAP reversed the effect of inhibited miR-130a in both MCAO rats and OGD-treated neurons. XIAP was identified as a target of miR-130a. Our study reveals that miR-130a regulates neurological deficit and angiogenesis in rats with MCAO by targeting XIAP.

A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic

PURPOSE

Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the profiling of multiple model inputs, which hampers clinical translation.

PATIENTS AND METHODS

We applied APOPTO-CELL, a prognostic model of apoptosis signaling, to showcase the establishment of computational platforms that require a reduced set of inputs. We designed two distinct and complementary pipelines: a probabilistic approach to exploit a consistent subpanel of inputs across the whole cohort (Ensemble) and a machine learning approach to identify a reduced protein set tailored for individual patients (Tree). Development was performed on a virtual cohort of 3,200,000 patients, with inputs estimated from clinically relevant protein profiles. Validation was carried out in an in-house stage III colorectal cancer cohort, with inputs profiled in surgical resections by reverse phase protein array (n = 120) and/or immunohistochemistry (n = 117).

RESULTS

Ensemble and Tree reproduced APOPTO-CELL predictions in the virtual patient cohort with 92% and 99% accuracy while decreasing the number of inputs to a consistent subset of three proteins (40% reduction) or a personalized subset of 2.7 proteins on average (46% reduction), respectively. Ensemble and Tree retained prognostic utility in the in-house colorectal cancer cohort. The association between the Ensemble accuracy and prognostic value (Spearman ρ = 0.43; P = .02) provided a rationale to optimize the input composition for specific clinical settings. Comparison between profiling by reverse phase protein array (gold standard) and immunohistochemistry (clinical routine) revealed that the latter is a suitable technology to quantify model inputs.

CONCLUSION

This study provides a generalizable framework to optimize the development of network-based prognostic assays and, ultimately, to facilitate their integration in the routine clinical workflow.

The apoptosome molecular timer synergises with XIAP to suppress apoptosis execution and contributes to prognosticating survival in colorectal cancer

The execution phase of apoptosis is a critical process in programmed cell death in response to a multitude of cellular stresses. A crucial component of this pathway is the apoptosome, a platform for the activation of pro-caspase 9 (PC9). Recent findings have shown that autocleavage of PC9 to Caspase 9 (C9) p35/p12 not only permits XIAP-mediated C9 inhibition but also temporally shuts down apoptosome activity, forming a molecular timer. In order to delineate the combined contributions of XIAP and the apoptosome molecular timer to apoptosis execution we utilised a systems modelling approach. We demonstrate that cooperative recruitment of PC9 to the apoptosome, based on existing PC9-apoptosome interaction data, is important for efficient formation of PC9 homodimers, autocatalytic cleavage and dual regulation by XIAP and the molecular timer across biologically relevant PC9 and APAF1 concentrations. Screening physiologically relevant concentration ranges of apoptotic proteins, we discovered that the molecular timer can prevent apoptosis execution in specific scenarios after complete or partial mitochondrial outer membrane permeabilisation (MOMP). Furthermore, its ability to prevent apoptosis is intricately tied to a synergistic combination with XIAP. Finally, we demonstrate that simulations of these processes are prognostic of survival in stage III colorectal cancer and that the molecular timer may promote apoptosis resistance in a subset of patients. Based on our findings, we postulate that the physiological function of the molecular timer is to aid XIAP in the shutdown of caspase-mediated apoptosis execution. This shutdown potentially facilitates switching to pro-inflammatory caspase-independent responses subsequent to Bax/Bak pore formation.

The FLAME-accelerated signalling tool (FaST) for facile parallelisation of flexible agent-based models of cell signalling

Agent-based modelling is particularly adept at modelling complex features of cell signalling pathways, where heterogeneity, stochastic and spatial effects are important, thus increasing our understanding of decision processes in biology in such scenarios. However, agent-based modelling often is computationally prohibitive to implement. Parallel computing, either on central processing units (CPUs) or graphical processing units (GPUs), can provide a means to improve computational feasibility of agent-based applications but generally requires specialist coding knowledge and extensive optimisation. In this paper, we address these challenges through the development and implementation of the FLAME-accelerated signalling tool (FaST), a software that permits easy creation and parallelisation of agent-based models of cell signalling, on CPUs or GPUs. FaST incorporates validated new agent-based methods, for accurate modelling of reaction kinetics and, as proof of concept, successfully converted an ordinary differential equation (ODE) model of apoptosis execution into an agent-based model. We finally parallelised this model through FaST on CPUs and GPUs resulting in an increase in performance of 5.8× (16 CPUs) and 53.9×, respectively. The FaST takes advantage of the communicating X-machine approach used by FLAME and FLAME GPU to allow easy alteration or addition of functionality to parallel applications, but still includes inherent parallelisation optimisation. The FaST, therefore, represents a new and innovative tool to easily create and parallelise bespoke, robust, agent-based models of cell signalling.

Down-regulated lncRNA SBF2-AS1 in M2 macrophage-derived exosomes elevates miR-122-5p to restrict XIAP, thereby limiting pancreatic cancer development

Evidence has indicated that M2 macrophages promote the progression of cancers, but few focus on the ability of M2 macrophage‐derived exosomes in pancreatic cancer (PC). This study aims to explore how M2 macrophages affect malignant phenotypes of PC through regulating long non‐coding RNA SET‐binding factor 2 antisense RNA 1 (lncRNA SBF2‐AS1)/microRNA‐122‐5p (miR‐122‐5p)/X‐linked inhibitor of apoptosis protein (XIAP) axis. THP‐1 cells were transformed into M1 macrophages by lipopolysaccharide and interferon‐γ treatment, and into M2 macrophages after interleukin‐4 treatment. The PANC‐1 PC cell line with the largest lncRNA SBF2‐AS1 expression was selected, and M2 macrophage‐derived exosomes were isolated and identified. A number of assays were applied for the examination of lncRNA SBF2‐AS1 expression, PC cell biological functions and subcellular localization of lncRNA SBF2‐AS1. XIAP expression was detected, along with the interaction among lncRNA SBF2‐AS1, miR‐122‐5p and XIAP. M2 macrophage exosomal lncRNA SBF2‐AS1 expression's effects on the tumorigenic ability of PANC‐1 cells in nude mice were also investigated. M2 macrophage‐derived exosomes promoted progression of PC cells. Overexpressed lncRNA SBF2‐AS1 promoted progression of PC cells. LncRNA SBF2‐AS1 was found to act as a competing endogenous RNA to repress miR‐122‐5p and up‐regulate XIAP. Constrained lncRNA SBF2‐AS1 in M2 macrophage‐derived exosomes contributed to restraining tumorigenic ability of PC cells. Collectively, our study reveals that constrained lncRNA SBF2‐AS1 in M2 macrophage‐derived exosomes increases miR‐122‐5p expression to restrain XIAP expression, which further inhibits PC progression.

TRAIL receptor signaling: From the basics of canonical signal transduction toward its entanglement with ER stress and the unfolded protein response

The cytokine tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is a member of the large TNF superfamily that can trigger apoptosis in transformed or infected cells by binding and activating two receptors, TRAIL receptor 1 (TRAILR1) and TRAIL receptor 2 (TRAILR2). Compared to other death ligands of the same family, TRAIL induces apoptosis preferentially in malignant cells while sparing normal tissue and has therefore been extensively investigated for its suitability as an anti-cancer agent. Recently, it was noticed that TRAIL receptor signaling is also linked to endoplasmic reticulum (ER) stress and the unfolded protein response (UPR). The role of TRAIL receptors in regulating cellular apoptosis susceptibility therefore is broader than previously thought. Here, we provide an overview of TRAIL-induced signaling, covering the core signal transduction during extrinsic apoptosis as well as its link to alternative outcomes, such as necroptosis or NF-κB activation. We discuss how environmental factors, transcriptional regulators, and genetic or epigenetic alterations regulate TRAIL receptors and thus alter cellular TRAIL susceptibility. Finally, we provide insight into the role of TRAIL receptors in signaling scenarios that engage the unfolded protein response and discuss how these findings might be translated into new combination therapies for cancer treatment.

Convergence of pathway analysis and pattern recognition predicts sensitization to latest generation TRAIL therapeutics by IAP antagonism

Second generation TRAIL-based therapeutics, combined with sensitising co-treatments, have recently entered clinical trials. However, reliable response predictors for optimal patient selection are not yet available. Here, we demonstrate that a novel and translationally relevant hexavalent TRAIL receptor agonist, IZI1551, in combination with Birinapant, a clinically tested IAP antagonist, efficiently induces cell death in various melanoma models, and that responsiveness can be predicted by combining pathway analysis, data-driven modelling and pattern recognition. Across a panel of 16 melanoma cell lines, responsiveness to IZI1551/Birinapant was heterogeneous, with complete resistance and pronounced synergies observed. Expression patterns of TRAIL pathway regulators allowed us to develop a combinatorial marker that predicts potent cell killing with high accuracy. IZI1551/Birinapant responsiveness could be predicted not only for cell lines, but also for 3D tumour cell spheroids and for cells directly isolated from patient melanoma metastases (80–100% prediction accuracies). Mathematical parameter reduction identified 11 proteins crucial to ensure prediction accuracy, with x-linked inhibitor of apoptosis protein (XIAP) and procaspase-3 scoring highest, and Bcl-2 family members strongly represented. Applied to expression data of a cohort of n = 365 metastatic melanoma patients in a proof of concept in silico trial, the predictor suggested that IZI1551/Birinapant responsiveness could be expected for up to 30% of patient tumours. Overall, response frequencies in melanoma models were very encouraging, and the capability to predict melanoma sensitivity to combinations of latest generation TRAIL-based therapeutics and IAP antagonists can address the need for patient selection strategies in clinical trials based on these novel drugs.

System-based approaches as prognostic tools for glioblastoma

BACKGROUND

The evasion of apoptosis is a hallmark of cancer. Understanding this process holistically and overcoming apoptosis resistance is a goal of many research teams in order to develop better treatment options for cancer patients. Efforts are also ongoing to personalize the treatment of patients. Strategies to confirm the therapeutic efficacy of current treatments or indeed to identify potential novel additional options would be extremely beneficial to both clinicians and patients. In the past few years, system medicine approaches have been developed that model the biochemical pathways of apoptosis. These systems tools incorporate and analyse the complex biological networks involved. For their successful integration into clinical practice, it is mandatory to integrate systems approaches with routine clinical and histopathological practice to deliver personalized care for patients.

RESULTS

We review here the development of system medicine approaches that model apoptosis for the treatment of cancer with a specific emphasis on the aggressive brain cancer, glioblastoma.

CONCLUSIONS

We discuss the current understanding in the field and present new approaches that highlight the potential of system medicine approaches to influence how glioblastoma is diagnosed and treated in the future.

Heterogeneous responses to low level death receptor activation are explained by random molecular assembly of the Caspase-8 activation platform

Ligand binding to death receptors activates apoptosis in cancer cells. Stimulation of death receptors results in the formation of intracellular multiprotein platforms that either activate the apoptotic initiator Caspase-8 to trigger cell death, or signal through kinases to initiate inflammatory and cell survival signalling. Two of these platforms, the Death-Inducing Signalling Complex (DISC) and the RIPoptosome, also initiate necroptosis by building filamentous scaffolds that lead to the activation of mixed lineage kinase domain-like pseudokinase. To explain cell decision making downstream of death receptor activation, we developed a semi-stochastic model of DISC/RIPoptosome formation. The model is a hybrid of a direct Gillespie stochastic simulation algorithm for slow assembly of the RIPoptosome and a deterministic model of downstream caspase activation. The model explains how alterations in the level of death receptor-ligand complexes, their clustering properties and intrinsic molecular fluctuations in RIPoptosome assembly drive heterogeneous dynamics of Caspase-8 activation. The model highlights how kinetic proofreading leads to heterogeneous cell responses and results in fractional cell killing at low levels of receptor stimulation. It reveals that the noise in Caspase-8 activation-exclusively caused by the stochastic molecular assembly of the DISC/RIPoptosome platform-has a key function in extrinsic apoptotic stimuli recognition.

Systems Biology Approaches Toward Understanding Primary Mitochondrial Diseases

Primary mitochondrial diseases form one of the most common and severe groups of genetic disease, with a birth prevalence of at least 1 in 5000. These disorders are multi-genic and multi-phenotypic (even within the same gene defect) and span the entire age range from prenatal to late adult onset. Mitochondrial disease typically affects one or multiple high-energy demanding organs, and is frequently fatal in early life. Unfortunately, to date there are no known curative therapies, mostly owing to the rarity and heterogeneity of individual mitochondrial diseases, leading to diagnostic odysseys and difficulties in clinical trial design. This review aims to discuss recent advances and challenges of systems approaches for the study of primary mitochondrial diseases. Although there has been an explosion in the generation of omics data, few studies have progressed toward the integration of multiple levels of omics. It is evident that the integration of different types of data to create a more complete representation of biology remains challenging, perhaps due to the scarcity of available integrative tools and the complexity inherent in their use. In addition, "bottom-up" systems approaches have been adopted for use in the iterative cycle of systems biology: from data generation to model prediction and validation. Primary mitochondrial diseases, owing to their complex nature, will most likely benefit from a multidisciplinary approach encompassing clinical, molecular and computational studies integrated together by systems biology to elucidate underlying pathomechanisms for better diagnostics and therapeutic discovery. Just as next generation sequencing has rapidly increased diagnostic rates from approximately 5% up to 60% over two decades, more recent advancing technologies are encouraging; the generation of multi-omics, the integration of multiple types of data, and the ability to predict perturbations will, ultimately, be translated into improved patient care.

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.

Bcl-2-mediated control of TRAIL-induced apoptotic response in the non-small lung cancer cell line NCI-H460 is effective at late caspase processing steps

Dysregulation of the mitochondrial signaling pathway of apoptosis induction represents a major hurdle in tumor therapy. The objective of the presented work was to investigate the role of the intrinsic (mitochondrial) apoptotic pathway in the non-small lung cancer cell line NCI-H460 upon induction of apoptosis using the highly bioactive TRAIL derivative Db-scTRAIL. NCI-H460 cells were TRAIL sensitive but an only about 3 fold overexpression of Bcl-2 was sufficient to induce a highly TRAIL resistant phenotype, confirming that the mitochondrial pathway is crucial for TRAIL-induced apoptosis induction. TRAIL resistance was paralleled by a strong inhibition of caspase-8, -9 and -3 activities and blocked their full processing. Notably, especially the final cleavage steps of the initiator caspase-8 and the executioner caspase-3 were effectively blocked by Bcl-2 overexpression. Caspase-9 knockdown failed to protect NCI-H460 cells from TRAIL-induced cell death, suggesting a minor role of this initiator caspase in this apoptotic pathway. Rather, knockdown of the XIAP antagonist Smac resulted in enhanced caspase-3 degradation after stimulation of cells with TRAIL. Of note, downregulation of XIAP had only limited effects on TRAIL sensitivity of wild-type NCI-H460 cells, but resensitized Bcl-2 overexpressing cells for TRAIL-induced apoptosis. In particular, XIAP knockdown in combination with TRAIL allowed the final cleavage step of caspase-3 to generate the catalytically active p17 fragment, whose production was otherwise blocked in Bcl-2 overexpressing cells. Together, our data strongly suggest that XIAP-mediated inhibition of final caspase-3 processing is the last and major hurdle in TRAIL-induced apoptosis in NCI-H460 cells, which can be overcome by Smac in a Bcl-2 level dependent manner. Quantitative investigation of the XIAP/Smac interplay using a mathematical model approach corroborates our experimental data strengthening the suggested roles of XIAP and Smac as critical determinants for TRAIL sensitivity.

Degradation of Bcl-2 by XIAP and ARTS Promotes Apoptosis

We describe a mechanism by which the anti-apoptotic B cell lymphoma 2 (Bcl-2) protein is downregulated to induce apoptosis. ARTS (Sept4_i2) is a tumor suppressor protein that promotes cell death through specifically antagonizing XIAP (X-linked inhibitor of apoptosis). ARTS and Bcl-2 reside at the outer mitochondrial membrane in living cells. Upon apoptotic induction, ARTS brings XIAP and Bcl-2 into a ternary complex, allowing XIAP to promote ubiquitylation and degradation of Bcl-2. ARTS binding to Bcl-2 involves the BH3 domain of Bcl-2. Lysine 17 in Bcl-2 serves as the main acceptor for ubiquitylation, and a Bcl-2 K17A mutant has increased stability and is more potent in protection against apoptosis. Bcl-2 ubiquitylation is reduced in both XIAP- and Sept4/ARTS-deficient MEFs, demonstrating that XIAP serves as an E3 ligase for Bcl-2 and that ARTS is essential for this process. Collectively, these results suggest a distinct model for the regulation of Bcl-2 by ARTS-mediated degradation.

Predicting the cell death responsiveness and sensitization of glioma cells to TRAIL and temozolomide

Genotoxic chemotherapy with temozolomide (TMZ) is a mainstay of treatment for glioblastoma (GBM); however, at best, TMZ provides only modest survival benefit to a subset of patients. Recent insight into the heterogeneous nature of GBM suggests a more personalized approach to treatment may be necessary to overcome cancer drug resistance and improve patient care. These include novel therapies that can be used both alone and with TMZ to selectively reactivate apoptosis within malignant cells. For this approach to work, reliable molecular signatures that can accurately predict treatment responsiveness need to be identified first. Here, we describe the first proof-of-principle study that merges quantitative protein-based analysis of apoptosis signaling networks with data- and knowledge-driven mathematical systems modeling to predict treatment responsiveness of GBM cell lines to various apoptosis-inducing stimuli. These include monotherapies with TMZ and TRAIL, which activate the intrinsic and extrinsic apoptosis pathways, respectively, as well as combination therapies of TMZ+TRAIL. We also successfully employed this approach to predict whether individual GBM cell lines could be sensitized to TMZ or TRAIL via the selective targeting of Bcl-2/Bcl-xL proteins with ABT-737. Our findings suggest that systems biology-based approaches could assist in personalizing treatment decisions in GBM to optimize cell death induction.

Simulating and predicting cellular and in vivo responses of colon cancer to combined treatment with chemotherapy and IAP antagonist Birinapant/TL32711

Apoptosis resistance contributes to treatment failure in colorectal cancer (CRC). New treatments that reinstate apoptosis competency have potential to improve patient outcome but require predictive biomarkers to target them to responsive patient populations. Inhibitor of apoptosis proteins (IAPs) suppress apoptosis, contributing to drug resistance; IAP antagonists such as TL32711 have therefore been developed. We developed a systems biology approach for predicting response of CRC cells to chemotherapy and TL32711 combinations in vitro and in vivo. CRC cells responded poorly to TL32711 monotherapy in vitro; however, co-treatment with 5-fluorouracil (5-FU) and oxaliplatin enhanced TL32711-induced apoptosis. Notably, cells from genetically identical populations responded highly heterogeneously, with caspases being activated both upstream and downstream of mitochondrial outer membrane permeabilisation (MOMP). These data, combined with quantities of key apoptosis regulators were sufficient to replicate in vitro cell death profiles by mathematical modelling. In vivo, apoptosis protein expression was significantly altered, and mathematical modelling for these conditions predicted higher apoptosis resistance that could nevertheless be overcome by combination of chemotherapy and TL32711. Subsequent experimental observations agreed with these predictions, and the observed effects on tumour growth inhibition correlated robustly with apoptosis competency. We therefore obtained insights into intracellular signal transduction kinetics and their population-based heterogeneities for chemotherapy/TL32711 combinations and provide proof-of-concept that mathematical modelling of apoptosis competency can simulate and predict responsiveness in vivo. Being able to predict response to IAP antagonist-based treatments on the background of cell-to-cell heterogeneities in the future might assist in improving treatment stratification approaches for these emerging apoptosis-targeting agents.

The BAX/BAK-like protein BOK is a prognostic marker in colorectal cancer

The intrinsic or mitochondrial apoptosis pathway is controlled by the interaction of antiapoptotic and pro-apoptotic members of the BCL-2 protein family. Activation of this death pathway plays a crucial role in cancer progression and chemotherapy responses. The BCL-2-related ovarian killer (BOK) possesses three BCL-2 homology domains and has been proposed to act in a similar pro-apoptotic pathway as the pro-apoptotic proteins BAX and BAK. In this study, we showed that stage II and III colorectal cancer patients possessed decreased levels of BOK protein in their tumours compared to matched normal tissue. BOK protein levels in tumours were also prognostic of clinical outcome but increased BOK protein levels surprisingly associated with earlier disease recurrence and reduced overall survival. We found no significant association of BOK protein tumour levels with ER stress markers GRP78 or GRP94 or with cleaved caspase-3. In contrast, BOK protein levels correlated with Calreticulin. These data indicate BOK as a prognostic marker in colorectal cancer and suggest that different activities of BOK may contribute to cancer progression and prognosis.

Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells

Triple negative breast cancer (TNBC) is an aggressive form of breast cancer which accounts for 15-20% of this disease and is currently treated with genotoxic chemotherapy. The BCL2 (B-cell lymphoma 2) family of proteins controls the process of mitochondrial outer membrane permeabilization (MOMP), which is required for the activation of the mitochondrial apoptosis pathway in response to genotoxic agents. We previously developed a deterministic systems model of BCL2 protein interactions, DR_MOMP that calculates the sensitivity of cells to undergo mitochondrial apoptosis. Here we determined whether DR_MOMP predicts responses of TNBC cells to genotoxic agents and the re-sensitization of resistant cells by BCL2 inhibitors. Using absolute protein levels of BAX, BAK, BCL2, BCL(X)L and MCL1 as input for DR_MOMP, we found a strong correlation between model predictions and responses of a panel of TNBC cells to 24 and 48 h cisplatin (R2 = 0.96 and 0.95, respectively) and paclitaxel treatments (R2 = 0.94 and 0.95, respectively). This outperformed single protein correlations (best performer BCL(X)L with R2 of 0.69 and 0.50 for cisplatin and paclitaxel treatments, respectively) and BCL2 proteins ratio (R2 of 0.50 for cisplatin and 0.49 for paclitaxel). Next we performed synergy studies using the BCL2 selective antagonist Venetoclax /ABT199, the BCL(X)L selective antagonist WEHI-539, or the MCL1 selective antagonist A-1210477 in combination with cisplatin. In silico predictions by DR_MOMP revealed substantial differences in treatment responses of BCL(X)L, BCL2 or MCL1 inhibitors combinations with cisplatin that were successfully validated in cell lines. Our findings provide evidence that DR_MOMP predicts responses of TNBC cells to genotoxic therapy, and can aid in the choice of the optimal BCL2 protein antagonist for combination treatments of resistant cells.

Synonymous mutations in oncogenesis and apoptosis versus survival unveiled by network modeling

Synonymous mutations, which do not alter the encoded amino acid, have been routinely assumed to be ‘neutral’ and would have no effect on phenotype or fitness. Yet increasing observations have emerged to overturn this conventional concept. However, convicted elucidation of how synonymous mutations exert biological consequences in oncogenesis is still lacking. By performing systematic analysis of the TNF-α signaling network model, we identify the critical dose which separates the cell survival and apoptosis regions and define the sensitive parameters with single-parameter sensitivity analysis. Combining with the cancer-related mutation spectra obtained from 9 cancers, our results hint that, similar as missense and nonsense mutations, synonymous mutations are also strongly correlated with the parameter sensitivity of the critical dose, providing possible causal mechanism of the mutations in cancer development. Based on such a correlation, we furthermore dissect that members of caspases family proteases (caspase3, 6, 8) could jointly inhibit NFκB activation, providing efficient pro-apoptotic behavior. Thus, we argue that apoptosis module could suppress survival module through negative feedback of caspases family on NFκB.

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.

A Stepwise Integrated Approach to Personalized Risk Predictions in Stage III Colorectal Cancer

Purpose: Apoptosis is essential for chemotherapy responses. In this discovery and validation study, we evaluated the suitability of a mathematical model of apoptosis execution (APOPTO-CELL) as a stand-alone signature and as a constituent of further refined prognostic stratification tools.Experimental Design: Apoptosis competency of primary tumor samples from patients with stage III colorectal cancer (n = 120) was calculated by APOPTO-CELL from measured protein concentrations of Procaspase-3, Procaspase-9, SMAC, and XIAP. An enriched APOPTO-CELL signature (APOPTO-CELL-PC3) was synthesized to capture apoptosome-independent effects of Caspase-3. Furthermore, a machine learning Random Forest approach was applied to APOPTO-CELL-PC3 and available molecular and clinicopathologic data to identify a further enhanced signature. Association of the signature with prognosis was evaluated in an independent colon adenocarcinoma cohort (TCGA COAD, n = 136).Results: We identified 3 prognostic biomarkers (P = 0.04, P = 0.006, and P = 0.0004 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively) with increasing stratification accuracy for patients with stage III colorectal cancer.The APOPTO-CELL-PC3 signature ranked highest among all features. The prognostic value of the signatures was independently validated in stage III TCGA COAD patients (P = 0.01, P = 0.04, and P = 0.02 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively). The signatures provided further stratification for patients with CMS1-3 molecular subtype.Conclusions: The integration of a systems-biology-based biomarker for apoptosis competency with machine learning approaches is an appealing and innovative strategy toward refined patient stratification. The prognostic value of apoptosis competency is independent of other available clinicopathologic and molecular factors, with tangible potential of being introduced in the clinical management of patients with stage III colorectal cancer. Clin Cancer Res; 23(5); 1200-12. ©2016 AACR.

Signal transduction analysis of the NLRP3-inflammasome pathway after cellular damage and its paracrine regulation

Activation of the NLRP3-inflammasome pathway and production of the inflammatory cytokine IL-1B after cellular damage caused by infarct or infection is a key process in several diseases such as acute myocardial infarction and inflammatory bowel disease. However, while the molecular triggers of the NLRP3-pathway after cellular damage are well known, the mechanisms that sustain or confine its activity are currently under investigation. We present here an Ordinary Differential Equation-based model that investigates the mechanisms of inflammasome activation and regulation in monocytes to predict IL-1β activation kinetics upon a two-step activation by Damage-Associate-Molecular-Particles (DAMP) and extracellular ATP. Assuming both activation signals to be concomitantly present or present with a delay of 12h, the model predicted a transient IL-1β activation at different concentration levels dependent on signal synchronisation. Introducing a positive feedback loop mediated by active IL-1β resulted in a sustained IL-1β activation, hence arguing for a paracrine signalling between inflammatory cells to guarantee a temporally stable inflammatory response. We then investigate mechanisms that control termination of inflammation using two recently identified molecular intervention points in the inflammasome pathway. We found that a more upstream regulation, by attenuating production of the IL-1β-proform, was more potent in attenuating active IL-1β production than direct inhibition of the NLRP3-inflammasome. Interestingly, ablating this upstream negative feedback led to a high variability of IL-1β production in monocytes from different subjects, consistent with a recent pre-clinical study. We finally discuss the relevance and implications of our findings in disease models of acute myocardial infarction and spontaneous colitis.

Doxorubicin-induced chronic dilated cardiomyopathy-the apoptosis hypothesis revisited

The chemotherapeutic agent doxorubicin (DOX) has significantly increased survival rates of pediatric and adult cancer patients. However, 10% of pediatric cancer survivors will 10-20 years later develop severe dilated cardiomyopathy (DCM), whereby the exact molecular mechanisms of disease progression after this long latency time remain puzzling. We here revisit the hypothesis that elevated apoptosis signaling or its increased likelihood after DOX exposure can lead to an impairment of cardiac function and cause a cardiac dilation. Based on recent literature evidence, we first argue why a dilated phenotype can occur when little apoptosis is detected. We then review findings suggesting that mature cardiomyocytes are protected against DOX-induced apoptosis downstream, but not upstream of mitochondrial outer membrane permeabilisation (MOMP). This lack of MOMP induction is proposed to alter the metabolic phenotype, induce hypertrophic remodeling, and lead to functional cardiac impairment even in the absence of cardiomyocyte apoptosis. We discuss findings that DOX exposure can lead to increased sensitivity to further cardiomyocyte apoptosis, which may cause a gradual loss in cardiomyocytes over time and a compensatory hypertrophic remodeling after treatment, potentially explaining the long lag time in disease onset. We finally note similarities between DOX-exposed cardiomyocytes and apoptosis-primed cancer cells and propose computational system biology as a tool to predict patient individual DOX doses. In conclusion, combining recent findings in rodent hearts and cardiomyocytes exposed to DOX with insights from apoptosis signal transduction allowed us to obtain a molecularly deeper insight in this delayed and still enigmatic pathology of DCM.