A dynamical systems model for combinatorial cancer therapy enhances oncolytic adenovirus efficacy by MEK-inhibition

Personalized tumor combination therapy optimization using the single-cell transcriptome

BACKGROUND

The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment.

METHODS

Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization.

RESULTS

We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples.

CONCLUSIONS

Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

Mathematical Modeling of Oncolytic Virus Therapy Reveals Role of the Immune Response

Oncolytic adenoviruses (OAds) present a promising path for cancer treatment due to their selectivity in infecting and lysing tumor cells and their ability to stimulate the immune response. In this study, we use an ordinary differential equation (ODE) model of tumor growth inhibited by oncolytic virus activity to parameterize previous research on the effect of genetically re-engineered OAds in A549 lung cancer tumors in murine models. We find that the data are best fit by a model that accounts for an immune response, and that the immune response provides a mechanism for elimination of the tumor. We also find that parameter estimates for the most effective OAds share characteristics, most notably a high infection rate and low viral clearance rate, that might be potential reasons for these viruses' efficacy in delaying tumor growth. Further studies observing E1A and P19 recombined viruses in different tumor environments may further illuminate the extent of the effects of these genetic modifications.

Inhibition of MEK-ERK pathway enhances oncolytic vaccinia virus replication in doxorubicin-resistant ovarian cancer

Oncolytic vaccinia virus (OVV) has been reported to induce cell death in various types of cancer; however, the oncolytic activity of OVV in drug-resistant ovarian cancer remains limited. In the present study, we established doxorubicin-resistant ovarian cancer cells (A2780-R) from the A2780 human ovarian cancer cell line. Both A2780 and A2780-R cells were infected with OVV to explore its anticancer effects. Interestingly, OVV-infected A2780-R cells showed reduced viral replication and cell death compared with A2780 cells, suggesting their resistance against OVV-induced oncolysis; to understand the mechanism underlying this resistance, we explored the involvement of protein kinases. Among protein kinase inhibitors, PD0325901, an MEK inhibitor, significantly augmented OVV replication and cell death in A2780-R cells. PD0325901 treatment increased the phosphorylation of STAT3 in A2780-R cells. Moreover, cryptotanshinone, a STAT3 inhibitor, abrogated PD0325901-stimulated OVV replication. Furthermore, trametinib, a clinically approved MEK inhibitor, increased OVV replication in A2780-R cells. Transcriptomic analysis showed that the MEK inhibitor promoted OVV replication via increasing STAT3 activation and downregulating the cytosolic DNA-sensing pathway. Combined treatment with OVV and trametinib attenuated A2780-R xenograft tumor growth. These results suggest that pharmacological inhibition of MEK reinforces the oncolytic efficacy of OVV in drug-resistant ovarian cancer.

Enhancing Therapeutic Efficacy of Oncolytic Herpes Simplex Virus with MEK Inhibitor Trametinib in Some BRAF or KRAS-Mutated Colorectal or Lung Carcinoma Models

Oncolytic virus (OV) as a promising therapeutic agent can selectively infect and kill tumor cells with naturally inherited or engineered properties. Considering the limitations of OVs monotherapy, combination therapy has been widely explored. MEK inhibitor (MEKi) Trametinib is an FDA-approved kinase inhibitor indicated for the treatment of tumors with BRAF V600E or V600K mutations. In this study, the oncolytic activity in vitro and anti-tumor therapeutic efficacy in vivo when combined with oHSV and MEKi Trametinib were investigated. We found: (1) Treatment with MEKi Trametinib augmented oHSV oncolytic activity in BRAF V600E-mutated tumor cells. (2) Combination treatment with oHSV and MEKi Trametinib enhanced virus replication mediated by down-regulation of STAT1 and PKR expression or phosphorylation in BRAF V600E-mutated tumor cells as well as BRAF wt/KRAS-mutated tumor cells. (3) A remarkably synergistic therapeutic efficacy was shown in vivo for BRAF wt/KRAS-mutated tumor models, when a combination of oHSV including PD-1 blockade and MEK inhibition. Collectively, these data provide some new insights for clinical development of combination therapy with oncolytic virus, MEK inhibition, and checkpoint blockade for BRAF or KRAS-mutated tumors.

Mechanistic Modeling of a Novel Oncolytic Virus, V937, to Describe Viral Kinetic and Dynamic Processes Following Intratumoral and Intravenous Administration

V937 is an investigational novel oncolytic non-genetically modified Kuykendall strain of Coxsackievirus A21 which is in clinical development for the treatment of advanced solid tumor malignancies. V937 infects and lyses tumor cells expressing the intercellular adhesion molecule I (ICAM-I) receptor. We integrated in vitro and in vivo data from six different preclinical studies to build a mechanistic model that allowed a quantitative analysis of the biological processes of V937 viral kinetics and dynamics, viral distribution to tumor, and anti-tumor response elicited by V937 in human xenograft models in immunodeficient mice following intratumoral and intravenous administration. Estimates of viral infection and replication which were calculated from in vitro experiments were successfully used to describe the tumor response in vivo under various experimental conditions. Despite the predicted high clearance rate of V937 in systemic circulation (t_1/2 = 4.3 min), high viral replication was observed in immunodeficient mice which resulted in tumor shrinkage with both intratumoral and intravenous administration. The described framework represents a step towards the quantitative characterization of viral distribution, replication, and oncolytic effect of a novel oncolytic virus following intratumoral and intravenous administrations in the absence of an immune response. This model may further be expanded to integrate the role of the immune system on viral and tumor dynamics to support the clinical development of oncolytic viruses.

Significant Unresolved Questions and Opportunities for Bioengineering in Understanding and Treating COVID-19 Disease Progression

COVID-19 is a disease that manifests itself in a multitude of ways across a wide range of tissues. Many factors are involved, and though impressive strides have been made in studying this novel disease in a very short time, there is still a great deal that is unknown about how the virus functions. Clinical data has been crucial for providing information on COVID-19 progression and determining risk factors. However, the mechanisms leading to the multi-tissue pathology are yet to be fully established. Although insights from SARS-CoV-1 and MERS-CoV have been valuable, it is clear that SARS-CoV-2 is different and merits its own extensive studies. In this review, we highlight unresolved questions surrounding this virus including the temporal immune dynamics, infection of non-pulmonary tissue, early life exposure, and the role of circadian rhythms. Risk factors such as sex and exposure to pollutants are also explored followed by a discussion of ways in which bioengineering approaches can be employed to help understand COVID-19. The use of sophisticated in vitro models can be employed to interrogate intercellular interactions and also to tease apart effects of the virus itself from the resulting immune response. Additionally, spatiotemporal information can be gleaned from these models to learn more about the dynamics of the virus and COVID-19 progression. Application of advanced tissue and organ system models into COVID-19 research can result in more nuanced insight into the mechanisms underlying this condition and elucidate strategies to combat its effects.

Kinase inhibitors with viral oncolysis: Unmasking pharmacoviral approaches for cancer therapy

There are more than 500 kinases in the human genome, many of which are oncogenic once constitutively activated. Fortunately, numerous hyperactive kinases are druggable, and several targeted small molecule kinase inhibitors have demonstrated impressive clinical benefits in cancer treatment. However, their often cytostatic rather than cytotoxic effect on cancer cells, and the development of resistance mechanisms, remain significant limitations to these targeted therapies. Oncolytic viruses are an emerging class of immunotherapeutic agents with a specific oncotropic nature and excellent safety profile, highlighting them as a promising alternative to conventional therapeutic modalities. Nonetheless, the clinical efficacy of oncolytic virotherapy is challenged by immunological and physical barriers that limit viral delivery, replication, and spread within tumours. Several of these barriers are often associated with oncogenic kinase activity and, in some cases, worsened by the action of oncolytic viruses on kinase signaling during infection. What if inhibiting these kinases could potentiate the cancer-lytic and anti-tumour immune stimulating properties of oncolytic virotherapies? This could represent a paradigm shift in the use of specific kinase inhibitors in the clinic and provide a novel therapeutic approach to the treatment of cancers. A phase III clinical trial combining the oncolytic Vaccinia virus Pexa-Vec with the kinase inhibitor Sorafenib was initiated. While this trial failed to show any benefits over Sorafenib monotherapy in patients with advanced liver cancer, several pre-clinical studies demonstrate that targeting kinases combined with oncolytic viruses have synergistic effects highlighting this strategy as a unique avenue to cancer therapy. Herein, we review the combinations of oncolytic viruses with kinase inhibitors reported in the literature and discuss the clinical opportunities that represent these pharmacoviral approaches.

Modeling Oncolytic Viral Therapy, Immune Checkpoint Inhibition, and the Complex Dynamics of Innate and Adaptive Immunity in Glioblastoma Treatment

Oncolytic viruses are of growing interest to cancer researchers and clinicians, due to their selectivity for tumor cells over healthy cells and their immunostimulatory properties. The immune response to an oncolytic virus plays a critical role in treatment efficacy. However, uncertainty remains regarding the circumstances under which the immune system either assists in eliminating tumor cells or inhibits treatment via rapid viral clearance, leading to the cessation of the immune response. In this work, we develop an ordinary differential equation model of treatment for a lethal brain tumor, glioblastoma, using an oncolytic Herpes Simplex Virus. We use a mechanistic approach to model the interactions between distinct populations of immune cells, incorporating both innate and adaptive immune responses to oncolytic viral therapy (OVT), and including a mechanism of adaptive immune suppression via the PD-1/PD-L1 checkpoint pathway. We focus on the tradeoff between viral clearance by innate immune cells and the innate immune cell-mediated recruitment of antiviral and antitumor adaptive immune cells. Our model suggests that when a tumor is treated with OVT alone, the innate immune cells' ability to clear the virus quickly after administration has a much larger impact on the treatment outcome than the adaptive immune cells' antitumor activity. Even in a highly antigenic tumor with a strong innate immune response, the faster recruitment of antitumor adaptive immune cells is not sufficient to offset the rapid viral clearance. This motivates our subsequent incorporation of an immunotherapy that inhibits the PD-1/PD-L1 checkpoint pathway by blocking PD-1, which we combine with OVT within the model. The combination therapy is most effective for a highly antigenic tumor or for intermediate levels of innate immune localization. Extreme levels of innate immune cell activity either clear the virus too quickly or fail to activate a sufficiently strong adaptive response, yielding ineffective combination therapy of GBM. Hence, we show that the innate and adaptive immune interactions significantly influence treatment response and that combining OVT with an immune checkpoint inhibitor expands the range of immune conditions that allow for tumor size reduction or clearance.

MEK inhibition enhances oncolytic virus immunotherapy through increased tumor cell killing and T cell activation

Melanoma is an aggressive cutaneous malignancy, but advances over the past decade have resulted in multiple new therapeutic options, including molecularly targeted therapy, immunotherapy, and oncolytic virus therapy. Talimogene laherparepvec (T-VEC) is a herpes simplex type 1 oncolytic virus, and trametinib is a MEK inhibitor approved for treatment of melanoma. Therapeutic responses with T-VEC are often limited, and BRAF/MEK inhibition is complicated by drug resistance. We observed that the combination of T-VEC and trametinib resulted in enhanced melanoma cell death in vitro. Further, combination treatment resulted in delayed tumor growth and improved survival in mouse models. Tumor regression was dependent on activated CD8⁺ T cells and Batf3⁺ dendritic cells. We also observed antigen spreading and induction of an inflammatory gene signature, including increased expression of PD-L1. Triple therapy with the combination of T-VEC, MEK inhibition, and anti-PD-1 antibody further augmented responses. These data support clinical development of combination oncolytic viruses, MEK inhibitors, and checkpoint blockade in patients with melanoma.

DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity

Single-cell high-throughput technologies enable the ability to identify combination cancer therapies that account for intratumoral heterogeneity, a phenomenon that has been shown to influence the effectiveness of cancer treatment. We developed and applied an approach that identifies top-ranking drug combinations based on the single-cell perturbation response when an individual tumor sample is screened against a panel of single drugs. This approach optimizes drug combinations by choosing the minimum number of drugs that produce the maximal intracellular desired effects for an individual sample.

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple (>40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples.

Optimization and physicochemical characterization of a cationic lipid-phosphatidylcholine mixed emulsion formulated as a highly efficient vehicle that facilitates adenoviral gene transfer

Cationic lipid-based nanoparticles enhance viral gene transfer by forming electrostatic complexes with adenoviral vectors. We recently demonstrated the superior complexation capabilities of 1,2-dioleoyl-3-trimethylammonium propane (DOTAP) emulsion compared with a liposomal counterpart but the cytotoxicity of DOTAP emulsions remained a challenge. The present study is aimed at formulating an emulsion capable of acting as a highly effective viral gene transfer vehicle with reduced cytotoxicity and to physicochemically characterize the structures of virus-emulsion complexes in comparison with virus-liposome complexes when the only difference between emulsions and liposomes was the presence or absence of inner oil core. The emulsion formulation was performed by 1) reducing the content of DOTAP while increasing the content of zwitterionic lipid 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 2) optimizing the oil content. The complexation capability of formulated DOTAP:DMPC mixed emulsions was similar to those of emulsions containing DOTAP alone while displaying significantly lower cytotoxicity. The complexation capabilities of the DOTAP:DMPC mixed emulsion were serum-compatible and were monitored in a variety of cell types, whereas its liposomal counterpart was totally ineffective. Characterization by scanning electron microscopy, transmission electron microscopy, atomic force microscopy, and dynamic light scattering studies indicated that the optimized emulsions spontaneously surrounded the virus particles to generate emulsions that encapsulated the viral particles, whereas viral particles merely attached to the surfaces of the counterpart liposomes to form multiviral aggregates. Overall, these studies demonstrated that optimized DOTAP:DMPC mixed emulsions are potentially useful for adenoviral gene delivery due to less cytotoxicity and the unique ability to encapsulate the viral particle, highlighting the importance of nanoparticle formulation.

Aminoclay as a highly effective cationic vehicle for enhancing adenovirus-mediated gene transfer through nanobiohybrid complex formation

Electrostatic complexation of adenovirus (Ad) with cationic lipids or polymers has been shown to be an effective means for overcoming the limitations of adenoviral vectors and enhancing gene-transfer efficacy. However, such complexation causes cytotoxicity, limiting the use of this strategy. The present study explored the potential of 3-aminopropyl functionalized magnesium phyllosilicate (aminoclay) as a cationic vehicle for improving Ad-mediated gene transfer without inducing cytotoxicity. Aminoclay complexation produced a dose-dependent increase in Ad-mediated transgene expression in both Ad infection-sensitive and -refractory cells, thereby greatly lowering the Ad dose required for transgene expression. Unlike the case for cationic lipids (Lipofectamine) or polymers (Polybrene), the enhancement effect of aminoclay was not accompanied by significant cytotoxicity regardless of cell lines and it was not observed for nonviral plasmid vectors. Physical characterization studies revealed that nanobiohybrid complexes formed between aminoclay and Ad particles through electrostatic interactions, creating aggregates of Ad particles whose surface was shielded with aminoclay nanosheet oligomers. It appears that aminoclay complexation changes the surface charge of Ad particles from a negative to a highly positive value and thus increases Ad binding to cellular membranes, thereby providing an additional cellular entry mechanism, namely caveolae-dependent endocytosis. Aminoclay-Ad nanobiohybrids may serve as a next-generation efficient, versatile and biocompatible gene-delivery carrier.

STATEMENT OF SIGNIFICANCE

Electrostatic complexation of adenovirus with cationic materials has been shown to be an effective means for enhancing gene-transfer efficacy in vitro. However, such complexation causes cytotoxicity, limiting the use of this strategy. The present study explored the potential of a synthesized organoclay 3-aminopropyl functionalized magnesium phyllosilicate (aminoclay) as a cationic vehicle for improving Ad-mediated gene transfer. Our data indicate that nanobiohybrid complexes form between aminoclay and Ad particles through electrostatic interactions, thereby greatly enhancing Ad-mediated gene transfer. Unlike the case for either cationic lipids or cationic polymers, the enhancement effect of aminoclay was not accompanied by significant cytotoxicity regardless of cell lines. Our findings in this work highlight that aminoclay-Ad nanobiohybrids may serve as a next-generation efficient and biocompatible gene-delivery carrier.

Complex Dynamics of Virus Spread from Low Infection Multiplicities: Implications for the Spread of Oncolytic Viruses

While virus growth dynamics have been well-characterized in several infections, data are typically collected once the virus population becomes easily detectable. Earlier dynamics, however, remain less understood. We recently reported unusual early dynamics in an experimental system using adenovirus infection of human embryonic kidney (293) cells. Under identical experimental conditions, inoculation at low infection multiplicities resulted in either robust spread, or in limited spread that eventually stalled, with both outcomes occurring with approximately equal frequencies. The reasons underlying these observations have not been understood. Here, we present further experimental data showing that inhibition of interferon-induced antiviral states in cells results in a significant increase in the percentage of robust infections that are observed, implicating a race between virus replication and the spread of the anti-viral state as a central mechanism. Analysis of a variety of computational models, however, reveals that this alone cannot explain the simultaneous occurrence of both viral growth outcomes under identical conditions, and that additional biological mechanisms have to be invoked to explain the data. One such mechanism is the ability of the virus to overcome the antiviral state through multiple infection of cells. If this is included in the model, two outcomes of viral spread are found to be simultaneously stable, depending on initial conditions. In stochastic versions of such models, the system can go by chance to either state from identical initial conditions, with the relative frequency of the outcomes depending on the strength of the interferon-based anti-viral response, consistent with the experiments. This demonstrates considerable complexity during the early phase of the infection that can influence the ability of a virus to become successfully established. Implications for the initial dynamics of oncolytic virus spread through tumors are discussed.

We investigate in vitro adenovirus spread starting from the lowest infection multiplicities. This phase of virus dynamics remains poorly understood and is likely critical for ensuring that engineered oncolytic viruses successfully spread and destroy tumors. We find unexpectedly complex dynamics, which are analyzed with a combination of experiments and mathematical models. The experiments indicate that the induction of an interferon-based anti-viral state is a crucial underlying mechanism. The mathematical models demonstrate that this mechanism alone cannot explain the experiments, and that additional mechanisms must be invoked to account for the data. The models suggest that the ability of the virus to overcome the anti-viral state through multiple infection of cells might be one such mechanism.

Optimal Control Model of Tumor Treatment with Oncolytic Virus and MEK Inhibitor

Tumors are a serious threat to human health. The oncolytic virus is a kind of tumor killer virus which can infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. Mathematical models can help us to understand the tumor-virus dynamics and find better treatment strategies. This paper gives a new mathematical model of tumor therapy with oncolytic virus and MEK inhibitor. Stable analysis was given. Because mitogen-activated protein kinase (MEK) can not only lead to greater oncolytic virus infection into cancer cells, but also limit the replication of the virus, in order to provide the best dosage of MEK inhibitors and balance the positive and negative effect of the inhibitors, we put forward an optimal control problem of the inhibitor. The optimal strategies are given by theory and simulation.

Micro- and Nanoscale Technologies for Delivery into Adherent Cells

Several recent micro- and nanotechnologies have provided novel methods for biological studies of adherent cells because the small features of these new biotools provide unique capabilities for accessing cells without the need for suspension or lysis. These novel approaches have enabled gentle but effective delivery of molecules into specific adhered target cells, with unprecedented spatial resolution. We review here recent progress in the development of these technologies with an emphasis on in vitro delivery into adherent cells utilizing mechanical penetration or electroporation. We discuss the major advantages and limitations of these approaches and propose possible strategies for improvements. Finally, we discuss the impact of these technologies on biological research concerning cell-specific temporal studies, for example non-destructive sampling and analysis of intracellular molecules.

Computational modeling approaches to the dynamics of oncolytic viruses

Replicating oncolytic viruses represent a promising treatment approach against cancer, specifically targeting the tumor cells. Significant progress has been made through experimental and clinical studies. Besides these approaches, however, mathematical models can be useful when analyzing the dynamics of virus spread through tumors, because the interactions between a growing tumor and a replicating virus are complex and nonlinear, making them difficult to understand by experimentation alone. Mathematical models have provided significant biological insight into the field of virus dynamics, and similar approaches can be adopted to study oncolytic viruses. The review discusses this approach and highlights some of the challenges that need to be overcome in order to build mathematical and computation models that are clinically predictive. WIREs Syst Biol Med 2016, 8:242-252. doi: 10.1002/wsbm.1332 For further resources related to this article, please visit the WIREs website.

Treatment strategies for combining immunostimulatory oncolytic virus therapeutics with dendritic cell injections

Oncolytic viruses (OVs) are used to treat cancer, as they selectively replicate inside of and lyse tumor cells. The efficacy of this process is limited and new OVs are being designed to mediate tumor cell release of cytokines and co-stimulatory molecules, which attract cytotoxic T cells to target tumor cells, thus increasing the tumor-killing effects of OVs. To further promote treatment efficacy, OVs can be combined with other treatments, such as was done by Huang et al., who showed that combining OV injections with dendritic cell (DC) injections was a more effective treatment than either treatment alone. To further investigate this combination, we built a mathematical model consisting of a system of ordinary differential equations and fit the model to the hierarchical data provided from Huang et al. We used the model to determine the effect of varying doses of OV and DC injections and to test alternative treatment strategies. We found that the DC dose given in Huang et al. was near a bifurcation point and that a slightly larger dose could cause complete eradication of the tumor. Further, the model results suggest that it is more effective to treat a tumor with immunostimulatory oncolytic viruses first and then follow-up with a sequence of DCs than to alternate OV and DC injections. This protocol, which was not considered in the experiments of Huang et al., allows the infection to initially thrive before the immune response is enhanced. Taken together, our work shows how the ordering, temporal spacing, and dosage of OV and DC can be chosen to maximize efficacy and to potentially eliminate tumors altogether.

Quantitative impact of immunomodulation versus oncolysis with cytokine-expressing virus therapeutics

The past century's description of oncolytic virotherapy as a cancer treatment involving specially-engineered viruses that exploit immune deficiencies to selectively lyse cancer cells is no longer adequate. Some of the most promising therapeutic candidates are now being engineered to produce immunostimulatory factors, such as cytokines and co-stimulatory molecules, which, in addition to viral oncolysis, initiate a cytotoxic immune attack against the tumor. This study addresses the combined effects of viral oncolysis and T-cell-mediated oncolysis. We employ a mathematical model of virotherapy that induces release of cytokine IL-12 and co-stimulatory molecule 4-1BB ligand. We found that the model closely matches previously published data, and while viral oncolysis is fundamental in reducing tumor burden, increased stimulation of cytotoxic T cells leads to a short-term reduction in tumor size, but a faster relapse. In addition, we found that combinations of specialist viruses that express either IL-12 or 4-1BBL might initially act more potently against tumors than a generalist virus that simultaneously expresses both, but the advantage is likely not large enough to replace treatment using the generalist virus. Finally, according to our model and its current assumptions, virotherapy appears to be optimizable through targeted design and treatment combinations to substantially improve therapeutic outcomes.

CD8(+) T cell response to adenovirus vaccination and subsequent suppression of tumor growth: modeling, simulation and analysis

BACKGROUND

Using immune checkpoint modulators in the clinic to increase the number and activity of cytotoxic T lymphocytes that recognize tumor antigens can prolong survival for metastatic melanoma. Yet, only a fraction of the patient population receives clinical benefit. In short, these clinical trials demonstrate proof-of-principle but optimizing the specific therapeutic strategies remains a challenge. In many fields, CAD (computer-aided design) is a tool used to optimize integrated system behavior using a mechanistic model that is based upon knowledge of constitutive elements. The objective of this study was to develop a predictive simulation platform for optimizing anti-tumor immunity using different treatment strategies.

METHODS

To better understand the therapeutic role that cytotoxic CD8(+) T cells can play in controlling tumor growth, we developed a multi-scale mechanistic model of the biology using impulsive differential equations and calibrated it to a self-consistent data set.

RESULTS

The multi-scale model captures the activation and differentiation of naïve CD8(+) T cells into effector cytotoxic T cells in the lymph node following adenovirus-mediated vaccination against a tumor antigen, the trafficking of the resulting cytotoxic T cells into blood and tumor microenvironment, the production of cytokines within the tumor microenvironment, and the interactions between tumor cells, T cells and cytokines that control tumor growth. The calibrated model captures the modest suppression of tumor cell growth observed in the B16F10 model, a transplantable mouse model for metastatic melanoma, and was used to explore the impact of multiple vaccinations on controlling tumor growth.

CONCLUSIONS

Using the calibrated mechanistic model, we found that the cytotoxic CD8(+) T cell response was prolonged by multiple adenovirus vaccinations. However, the strength of the immune response cannot be improved enough by multiple adenovirus vaccinations to reduce tumor burden if the cytotoxic activity or local proliferation of cytotoxic T cells in response to tumor antigens is not greatly enhanced. Overall, this study illustrates how mechanistic models can be used for in silico screening of the optimal therapeutic dosage and timing in cancer treatment.

Association of oncolytic adenoviruses with chemotherapies: an overview and future directions

Oncolytic adenoviruses have been used in different preclinical and clinical studies, showing their capacity to kill tumor cells without major adverse events. However, these studies also underline the limitations of this approach. The efficacy of oncolytic adenoviruses is hampered by their limited ability to transduce some tumor types, their lack of selectivity, and their poor dissemination within tumors. In addition, the host immune response may limit oncolytic adenovirus efficacy. Combining oncolytic adenoviruses with chemotherapeutics constitutes an appealing strategy to increase their potency. The first part of this review describes the molecular basis of oncolytic adenoviruses, their use in preclinical studies and clinical trials, their limitations, and strategies to circumvent these limitations. The second part will focus on studies combining oncolytic adenoviruses with chemotherapeutic drugs, including standard chemotherapeutic drugs, molecularly targeted drugs, and other drugs that have been combined with oncolytic adenoviruses. Finally, based on these studies, we describe future directions and general rules that could be followed to identify chemotherapeutic drugs displaying additive/synergistic effects when combined with oncolytic adenoviruses.

A systems approach to integrative biology: an overview of statistical methods to elucidate association and architecture

An organism's ability to maintain a desired physiological response relies extensively on how cellular and molecular signaling networks interpret and react to environmental cues. The capacity to quantitatively predict how networks respond to a changing environment by modifying signaling regulation and phenotypic responses will help inform and predict the impact of a changing global enivronment on organisms and ecosystems. Many computational strategies have been developed to resolve cue-signal-response networks. However, selecting a strategy that answers a specific biological question requires knowledge both of the type of data being collected, and of the strengths and weaknesses of different computational regimes. We broadly explore several computational approaches, and we evaluate their accuracy in predicting a given response. Specifically, we describe how statistical algorithms can be used in the context of integrative and comparative biology to elucidate the genomic, proteomic, and/or cellular networks responsible for robust physiological response. As a case study, we apply this strategy to a dataset of quantitative levels of protein abundance from the mussel, Mytilus galloprovincialis, to uncover the temperature-dependent signaling network.

Experimental models to study drug distributions in tissue using MALDI mass spectrometry imaging

Requirements for patient safety and improved efficacy are steadily increasing in modern healthcare and are key drivers in modern drug development. New drug characterization assays are central in providing evidence of the specificity and selectivity of drugs. Meeting this need, matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) is used to study drug localization within microenvironmental tissue compartments. Thin sections of human lung tumor and rat xenograft tissues were exposed to pharmaceutical drugs by either spotting or submerging. These drugs, the epidermal growth factor receptor antagonists, erlotinib (Tarceva) and gefitinib (Iressa), and the acetylcholine receptor antagonist, tiotropium, were characterized by microenvironment localization. Intact tissue blocks were also immersed in drug solution, followed by sectioning. MALDI-MSI was then performed using a Thermo MALDI LTQ Orbitrap XL instrument to localize drug-distribution patterns. We propose three MALDI-MSI models measuring drug disposition that have been used to map the selected compounds within tissue compartments of tumors isolated from lung cancer patients.

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

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

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

Effects of heat stress on the expression of the coxsackievirus and adenovirus receptor in mouse skin keratinocytes

The aim of this study was to investigate the effects of heat stress on the expression of the coxsackievirus and adenovirus receptor (CAR) in mouse skin keratinocytes. Twenty BALB/c mice were randomly divided into two groups: the sham heat (control) and scald groups. Skin specimens were obtained 6 h after the treatments. Changes in the expression of CAR in skin keratinocyte samples were detected by immunohistochemistry, quantitative polymerase chain reaction and western blotting. In an in vitro assay, mouse skin keratinocytes were cultured and randomly divided into two groups: the normal control and heat stress groups. Six hours subsequently, the changes in CAR expression in the two groups were estimated by flow cytometry to determine the differences between the two groups. Heat stress significantly increased the expression of CAR in the mouse skin keratinocytes (P<0.05). The upregulation of CAR in mouse keratinocytes in burn wounds may be beneficial for restoring healing in organisms.

Coxsackievirus and adenovirus receptor promotes antitumor activity of oncolytic adenovirus H101 in esophageal cancer

Esophageal cancer is an intractable disease due to late diagnosis, high incidence of post-surgical locoregional recurrence and frequent distant metastasis. Oncolytic adenovirus (Ad) vectors are a promising method for cancer treatment. The H101 virus is a recombinant Ad which has replication-selective properties and replicates only in tumor cells. The coxsackievirus and adenovirus receptor (CAR) is considered a surrogate marker that monitors the outcome of Ad-mediated gene therapy. Accumulating evidence indicates that CAR expression levels are lower in various types of tumors such as ovarian, lung, breast and bladder when compared to their normal counterparts. In this study, we reported that trichostatin A (TSA) induced the expression of CAR in esophageal squamous cell carcinoma (ESCC) cell lines through the MAPK/ERK1/2 signaling pathway. The expression levels of CAR were positively related with the antitumor activity of H101. Our results suggest that TSA increases the antitumor activity of the oncolytic adenovirus H101 through the MAPK/ERK pathway.

Complex spatial dynamics of oncolytic viruses in vitro: mathematical and experimental approaches

Oncolytic viruses replicate selectively in tumor cells and can serve as targeted treatment agents. While promising results have been observed in clinical trials, consistent success of therapy remains elusive. The dynamics of virus spread through tumor cell populations has been studied both experimentally and computationally. However, a basic understanding of the principles underlying virus spread in spatially structured target cell populations has yet to be obtained. This paper studies such dynamics, using a newly constructed recombinant adenovirus type-5 (Ad5) that expresses enhanced jellyfish green fluorescent protein (EGFP), AdEGFPuci, and grows on human 293 embryonic kidney epithelial cells, allowing us to track cell numbers and spatial patterns over time. The cells are arranged in a two-dimensional setting and allow virus spread to occur only to target cells within the local neighborhood. Despite the simplicity of the setup, complex dynamics are observed. Experiments gave rise to three spatial patterns that we call "hollow ring structure", "filled ring structure", and "disperse pattern". An agent-based, stochastic computational model is used to simulate and interpret the experiments. The model can reproduce the experimentally observed patterns, and identifies key parameters that determine which pattern of virus growth arises. The model is further used to study the long-term outcome of the dynamics for the different growth patterns, and to investigate conditions under which the virus population eliminates the target cells. We find that both the filled ring structure and disperse pattern of initial expansion are indicative of treatment failure, where target cells persist in the long run. The hollow ring structure is associated with either target cell extinction or low-level persistence, both of which can be viewed as treatment success. Interestingly, it is found that equilibrium properties of ordinary differential equations describing the dynamics in local neighborhoods in the agent-based model can predict the outcome of the spatial virus-cell dynamics, which has important practical implications. This analysis provides a first step towards understanding spatial oncolytic virus dynamics, upon which more detailed investigations and further complexity can be built.

Inhibitory effect of Survivin promoter-regulated oncolytic adenovirus carrying P53 gene against gallbladder cancer

Gene therapy has become an important strategy for treatment of malignancies, but problems remains concerning the low gene transferring efficiency, poor transgene expression and limited targeting specific tumors, which have greatly hampered the clinical application of tumor gene therapy. Gallbladder cancer is characterized by rapid progress, poor prognosis, and aberrantly high expression of Survivin. In the present study, we used a human tumor-specific Survivin promoter-regulated oncolytic adenovirus vector carrying P53 gene, whose anti-cancer effect has been widely confirmed, to construct a wide spectrum, specific, safe, effective gene-viral therapy system, AdSurp-P53. Examining expression of enhanced green fluorecent protein (EGFP), E1A and the target gene P53 in the oncolytic adenovirus system validated that Survivin promoter-regulated oncolytic adenovirus had high proliferation activity and high P53 expression in Survivin-positive gallbladder cancer cells. Our in vitro cytotoxicity experiment demonstrated that AdSurp-P53 possessed a stronger cytotoxic effect against gallbladder cancer cells and hepatic cancer cells. The survival rate of EH-GB1 cells was lower than 40% after infection of AdSurp-P53 at multiplicity of infection (MOI) = 1 pfu/cell, while the rate was higher than 90% after infection of Ad-P53 at the same MOI, demonstrating that AdSurp-P53 has a potent cytotoxicity against EH-GB1 cells. The tumor growth was greatly inhibited in nude mice bearing EH-GB1 xenografts when the total dose of AdSurp-P53 was 1 × 10(9) pfu, and terminal dUTP nick end-labeling (TUNEL) revealed that the apoptotic rate of cancer cells was (33.4 ± 8.4)%. This oncolytic adenovirus system overcomes the long-standing shortcomings of gene therapy: poor transgene expression and targeting of only specific tumors, with its therapeutic effect better than the traditional Ad-P53 therapy regimen already on market; our system might be used for patients with advanced gallbladder cancer and other cancers, who are not sensitive to chemotherapy, radiotherapy, or who lost their chance for surgical treatment.

Emerging cancer vaccines: the promise of genetic vectors

Therapeutic vaccination against cancer is an important approach which, when combined with other therapies, can improve long-term control of cancer. In fact, the induction of adaptive immune responses against Tumor Associated Antigens (TAAs) as well as innate immunity are important factors for tumor stabilization/eradication. A variety of immunization technologies have been explored in last decades and are currently under active evaluation, such as cell-based, protein, peptide and heat-shock protein-based cancer vaccines. Genetic vaccines are emerging as promising methodologies to elicit immune responses against a wide variety of antigens, including TAAs. Amongst these, Adenovirus (Ad)-based vectors show excellent immunogenicity profile and have achieved immunological proof of concept in humans. In vivo electroporation of plasmid DNA (DNA-EP) is also a desirable vaccine technology for cancer vaccines, as it is repeatable several times, a parameter required for the long-term maintenance of anti-tumor immunity. Recent findings show that combinations of different modalities of immunization (heterologous prime/boost) are able to induce superior immune reactions as compared to single-modality vaccines. In this review, we will discuss the challenges and requirements of emerging cancer vaccines, particularly focusing on the genetic cancer vaccines currently under active development and the promise shown by Ad and DNA-EP heterologous prime-boost.

Dynamic modelling of oestrogen signalling and cell fate in breast cancer cells

Cancers of the breast and other tissues arise from aberrant decision-making by cells regarding their survival or death, proliferation or quiescence, damage repair or bypass. These decisions are made by molecular signalling networks that process information from outside and from within the breast cancer cell and initiate responses that determine the cell's survival and reproduction. Because the molecular logic of these circuits is difficult to comprehend by intuitive reasoning alone, we present some preliminary mathematical models of the basic decision circuits in breast cancer cells that may aid our understanding of their susceptibility or resistance to endocrine therapy.