In vitro and in silico multidimensional modeling of oncolytic tumor virotherapy dynamics

Spatiotemporal spread of oncolytic virus in a heterogeneous cell population

Oncolytic (cancer-killing) virus treatment is a promising new therapy for cancer, with many viruses currently being tested for their ability to eradicate tumors. One of the major stumbling blocks to the development of this treatment modality has been preventing spread of the virus to non-cancerous cells. Our recent ability to manipulate RNA and DNA now allows for the possibility of creating designer viruses specifically targeted to cancer cells, thereby significantly reducing unwanted side effects in patients. In this study, we use a partial differential equation model to determine the characteristics of a virus needed to contain spread of an oncolytic virus within a spherical tumor and prevent it from spreading to non-cancerous cells outside the tumor. We find that oncolytic viruses that have different infection rates or different cell death rates in cancer and non-cancerous cells can be made to stay within the tumor. We find that there is a minimum difference in infection rates or cell death rates that will contain the virus and that this threshold value depends on the growth rate of the cancer. Identification of these types of thresholds can help researchers develop safer strains of oncolytic viruses allowing further development of this promising treatment.

Murine colon cancer derived cells exhibit heterogeneous resistance profiles against an oncolytic virus

Oncolytic virotherapy has shown efficacy in various animal models and a few human cancers. However, there are still significant limitations for the implementation of these therapies. One such limitation is the emergence of cellular resistances, which may appear rapidly considering the high genetic heterogeneity of most tumors. We previously showed that cellular resistance to an oncolytic virus can be mediated by the chronic activation of innate immunity. Here, we explored the existence of additional resistance mechanisms in murine colon cancer-derived cells. For this purpose, we isolated two cellular clones that were resistant to the oncolytic virus VSV-D51. While one of the clones showed a strong resistance profile associated with increased cytokine-mediated antiviral responses, the other clone showed a lower level of resistance that involves cytoskeletal reorganization, signaling by small GTPases, and cell structural changes. These results demonstrate the capacity of tumor cells to deploy heterogeneous mechanisms of resistance to oncolytic viruses.

Octyl itaconate enhances VSVΔ51 oncolytic virotherapy by multitarget inhibition of antiviral and inflammatory pathways

The presence of heterogeneity in responses to oncolytic virotherapy poses a barrier to clinical effectiveness, as resistance to this treatment can occur through the inhibition of viral spread within the tumor, potentially leading to treatment failures. Here we show that 4-octyl itaconate (4-OI), a chemical derivative of the Krebs cycle-derived metabolite itaconate, enhances oncolytic virotherapy with VSVΔ51 in various models including human and murine resistant cancer cell lines, three-dimensional (3D) patient-derived colon tumoroids and organotypic brain tumor slices. Furthermore, 4-OI in combination with VSVΔ51 improves therapeutic outcomes in a resistant murine colon tumor model. Mechanistically, we find that 4-OI suppresses antiviral immunity in cancer cells through the modification of cysteine residues in MAVS and IKKβ independently of the NRF2/KEAP1 axis. We propose that the combination of a metabolite-derived drug with an oncolytic virus agent can greatly improve anticancer therapeutic outcomes by direct interference with the type I IFN and NF-κB-mediated antiviral responses.

Molecular insights and promise of oncolytic virus based immunotherapy

Discovering a therapeutic that can counteract the aggressiveness of this disease's mechanism is crucial for improving survival rates for cancer patients and for better understanding the most different types of cancer. In recent years, using these viruses as an anticancer therapy has been thought to be successful. They mostly work by directly destroying cancer cells, activating the immune system to fight cancer, and expressing exogenous effector genes. For the treatment of tumors, oncolytic viruses (OVs), which can be modified to reproduce only in tumor tissues and lyse them while preserving the healthy non-neoplastic host cells and reinstating antitumor immunity which present a novel immunotherapeutic strategy. OVs can exist naturally or be created in a lab by altering existing viruses. These changes heralded the beginning of a new era of less harmful virus-based cancer therapy. We discuss three different types of oncolytic viruses that have already received regulatory approval to treat cancer as well as clinical research using oncolytic adenoviruses. The primary therapeutic applications, mechanism of action of oncolytic virus updates, future views of this therapy will be covered in this chapter.

Oncolytic Viruses in the Era of Omics, Computational Technologies, and Modeling: Thesis, Antithesis, and Synthesis

Oncolytic viruses (OVs) are the frontier therapy for refractory cancers, especially in integration with immunomodulation strategies. In cancer immunovirotherapy, the many available "omics" and systems biology technologies generate at a fast pace a challenging huge amount of data, where apparently clashing information mirrors the complexity of individual clinical situations and OV used. In this review, we present and discuss how currently big data analysis, on one hand and, on the other, simulation, modeling, and computational technologies, provide invaluable support to interpret and integrate "omic" information and drive novel synthetic biology and personalized OV engineering approaches for effective immunovirotherapy. Altogether, these tools, possibly aided in the future by artificial intelligence as well, will allow for the blending of the information into OV recombinants able to achieve tumor clearance in a patient-tailored way. Various endeavors to the envisioned "synthesis" of turning OVs into personalized theranostic agents are presented.

Modelling the spatial dynamics of oncolytic virotherapy in the presence of virus-resistant tumour cells

Oncolytic virotherapy is a promising form of cancer treatment that uses native or genetically engineered viruses to target, infect and kill cancer cells. Unfortunately, this form of therapy is not effective in a substantial proportion of cancer patients, partly due to the occurrence of infection-resistant tumour cells. To shed new light on the mechanisms underlying therapeutic failure and to discover strategies that improve therapeutic efficacy we designed a cell-based model of viral infection. The model allows us to investigate the dynamics of infection-sensitive and infection-resistant cells in tumour tissue in presence of the virus. To reflect the importance of the spatial configuration of the tumour on the efficacy of virotherapy, we compare three variants of the model: two 2D models of a monolayer of tumour cells and a 3D model. In all model variants, we systematically investigate how the therapeutic outcome is affected by the properties of the virus (e.g. the rate of viral spread), the tumour (e.g. production rate of resistant cells, cost of resistance), the healthy stromal cells (e.g. degree of resistance to the virus) and the timing of treatment. We find that various therapeutic outcomes are possible when resistant cancer cells arise at low frequency in the tumour. These outcomes depend in an intricate but predictable way on the death rate of infected cells, where faster death leads to rapid virus clearance and cancer persistence. Our simulations reveal three different causes of therapy failure: rapid clearance of the virus, rapid selection of resistant cancer cells, and a low rate of viral spread due to the presence of infection-resistant healthy cells. Our models suggest that improved therapeutic efficacy can be achieved by sensitizing healthy stromal cells to infection, although this remedy has to be weighed against the toxicity induced in the healthy tissue.

Persistent Infection of a Canine Histiocytic Sarcoma Cell Line with Attenuated Canine Distemper Virus Expressing Vasostatin or Granulocyte-Macrophage Colony-Stimulating Factor

Canine histiocytic sarcoma (HS) represents a neoplasia with poor prognosis. Due to the high metastatic rate of HS, there is urgency to improve treatment options and to prevent tumor metastases. Canine distemper virus (CDV) is a single-stranded negative-sense RNA (ssRNA (-)) virus with potentially oncolytic properties. Moreover, vasostatin and granulocyte-macrophage colony-stimulating factor (GM-CSF) are attractive molecules in cancer therapy research because of their anti-angiogenetic properties and potential modulation of the tumor microenvironment. In the present study, an in vitro characterization of two genetically engineered viruses based on the CDV strain Onderstepoort (CDV-Ond), CDV-Ondneon-vasostatin and CDV-Ondneon-GM-CSF was performed. Canine histiocytic sarcoma cells (DH82 cells) were persistently infected with CDV-Ond, CDV-Ondneon, CDV-Ondneon-vasostatin and CDV-Ondneon-GM-CSF and characterized on a molecular and protein level regarding their vasostatin and GM-CSF production. Interestingly, DH82 cells persistently infected with CDV-Ondneon-vasostatin showed a significantly increased number of vasostatin mRNA transcripts. Similarly, DH82 cells persistently infected with CDV-Ondneon-GM-CSF displayed an increased number of GM-CSF mRNA transcripts mirrored on the protein level as confirmed by immunofluorescence and Western blot. In summary, modified CDV-Ond strains expressed GM-CSF and vasostatin, rendering them promising candidates for the improvement of oncolytic virotherapies, which should be further detailed in future in vivo studies.

Differential In Vitro Growth and Cell Killing of Cancer versus Benign Prostate Cells by Oncolytic Parainfluenza Virus

The development of effective oncolytic viruses will require understanding the differences in virus replication and killing between normal and cancer cells. Here, we have evaluated infections of metastatic cancer (22Rv1) and benign non-tumorigenic (BPH-1) prostate cell lines with a mutant parainfluenza virus 5 (P/V/F) encoding a defective V protein and a hyperfusogenic F protein. Under low multiplicity of infection (MOI), the P/V/F mutant efficiently spread in 22Rv1 cells but was restricted in BPH-1 cells due to type-I interferon (IFN-I) responses. In mixed co-cultures, the P/V/F mutant showed specificity towards and spread within the 22Rv1 cells versus BPH-1 cells. Under high MOI conditions, both BPH-1 and 22Rv1 cells showed efficient infection by the P/V/F mutant. However, compared to BPH-1 cells, the 22Rv1 cancer cells showed increased cytopathic effect, higher induction of caspase-8 and -9, and extensive syncytia formation. In 22Rv1 spheroid cultures, P/V/F infection was less efficient compared to monolayers, but the virus was able to spread through spheroids and induce death. These data indicate that IFN-I sensitivity is a major determinant of specificity of P/V/F spread through populations of cancer versus benign cells, and additionally, differences in activation of apoptotic pathways and syncytia formation can contribute to differential outcomes in cancer versus benign cells.

Nonlocal multiscale modelling of tumour-oncolytic viruses interactions within a heterogeneous fibrous/non-fibrous extracellular matrix

In this study we investigate computationally tumour-oncolytic virus (OV) interactions that take place within a heterogeneous extracellular matrix (ECM). The ECM is viewed as a mixture of two constitutive phases, namely a fibre phase and a non-fibre phase. The multiscale mathematical model presented here focuses on the nonlocal cell-cell and cell-ECM interactions, and how these interactions might be impacted by the infection of cancer cells with the OV. At macroscale we track the kinetics of cancer cells, virus particles and the ECM. At microscale we track (i) the degradation of ECM by matrix degrading enzymes (MDEs) produced by cancer cells, which further influences the movement of tumour boundary; (ii) the re-arrangement of the microfibres that influences the re-arrangement of macrofibres (i.e., fibres at macroscale). With the help of this new multiscale model, we investigate two questions: (i) whether the infected cancer cell fluxes are the result of local or non-local advection in response to ECM density; and (ii) what is the effect of ECM fibres on the the spatial spread of oncolytic viruses and the outcome of oncolytic virotherapy.

Stochastic Analysis of Nonlinear Cancer Disease Model through Virotherapy and Computational Methods

Cancer is a common term for many diseases that can affect anybody. A worldwide leading cause of death is cancer, according to the World Health Organization (WHO) report. In 2020, ten million people died from cancer. This model identifies the interaction of cancer cells, viral therapy, and immune response. In this model, the cell population has four parts, namely uninfected cells (x), infected cells (y), virus-free cells (v), and immune cells (z). This study presents the analysis of the stochastic cancer virotherapy model in the cell population dynamics. The model results have restored the properties of the biological problem, such as dynamical consistency, positivity, and boundedness, which are the considerable requirements of the models in these fields. The existing computational methods, such as the Euler Maruyama, Stochastic Euler, and Stochastic Runge Kutta, fail to restore the abovementioned properties. The proposed stochastic nonstandard finite difference method is efficient, cost-effective, and accommodates all the desired feasible properties. The existing standard stochastic methods converge conditionally or diverge in the long run. The solution by the nonstandard finite difference method is stable and convergent over all time steps.

The phosphoinositide 3-kinase inhibitor ZSTK474 increases the susceptibility of osteosarcoma cells to oncolytic vesicular stomatitis virus VSVΔ51 via aggravating endoplasmic reticulum stress

Blockage of phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signal pathway is effective to increase the cytotoxic effects of oncolytic virus on cancer cells, but the detailed mechanisms are still largely unknown. Based on this, the present study managed to investigate the anti-tumor effects of PI3K inhibitor ZSTK474 and oncolytic vesicular stomatitis virus VSVΔ51 combination treatments on osteosarcoma (OS) in vitro and in vivo. Specifically, ZSTK474 aggravated the inhibiting effects of VSVΔ51 on osteosarcoma development by triggering endoplasmic reticulum (ER)-stress mediated apoptotic cell death. Mechanistically, either ZSTK474 or VSVΔ51 alone had limited effects on cell viability in osteosarcoma cells, while ZSTK474 and VSVΔ51 combination treatments significantly induced osteosarcoma cell apoptosis. Interestingly, VSVΔ51 increased the expression levels of IRE1α and p-PERK to initiate ER stress in osteosarcoma cells, which were aggravated by co-treating cells with ZSTK474. Next, the promoting effects of ZSTK474-VSVΔ51 combined treatment on osteosarcoma cell death were abrogated by the ER-stress inhibitor 4-phenyl butyric acid (4-PBA), indicating that ZSTK474 enhanced the cytotoxic effects of VSVΔ51 on osteosarcoma cells in an ER-stress dependent manner. Finally, the xenograft tumor-bearing mice models were established, and the results showed that ZSTK474-VSVΔ51 combined treatment synergistically hindered tumorigenesis of osteosarcoma cells in vivo. Taken together, our data suggested that ZSTK474 was a novel agent to enhance the cytotoxic effects of VSVΔ51 on osteosarcoma by aggravating ER-stress, and the present study might provide alternative therapy treatments for osteosarcoma in clinic.

Alphavirus-Driven Interferon Gamma (IFNg) Expression Inhibits Tumor Growth in Orthotopic 4T1 Breast Cancer Model

Interferon gamma (IFNg) is a pleiotropic cytokine that can potentially reprogram the tumor microenvironment; however, the antitumor immunomodulatory properties of IFNg still need to be validated due to variable therapeutic outcomes in preclinical and clinical studies. We developed a replication-deficient Semliki Forest virus vector expressing IFNg (SFV/IFNg) and evaluated its immunomodulatory antitumor potential in vitro in a model of 3D spheroids and in vivo in an immunocompetent 4T1 mouse breast cancer model. We demonstrated that SFV-derived, IFN-g-stimulated bone marrow macrophages can be used to acquire the tumoricidal M1 phenotype in 3D nonattached conditions. Coculturing SFV/IFNg-infected 4T1 spheroids with BMDMs inhibited spheroid growth. In the orthotopic 4T1 mouse model, intratumoral administration of SFV/IFNg virus particles alone or in combination with the Pam3CSK4 TLR2/1 ligand led to significant inhibition of tumor growth compared to the administration of the control SFV/Luc virus particles. Analysis of the composition of intratumoral lymphoid cells isolated from tumors after SFV/IFNg treatment revealed increased CD4⁺ and CD8⁺ and decreased T-reg (CD4⁺/CD25⁺/FoxP3⁺) cell populations. Furthermore, a significant decrease in the populations of cells bearing myeloid cell markers CD11b, CD38, and CD206 was observed. In conclusion, the SFV/IFNg vector induces a therapeutic antitumor T-cell response and inhibits myeloid cell infiltration in treated tumors.

An Agent-Based Model of Combination Oncolytic Viral Therapy and Anti-PD-1 Immunotherapy Reveals the Importance of Spatial Location When Treating Glioblastoma

Simple Summary

A combination of oncolytic viral therapy and immunotherapy provides an alternative option to the standard of care for treating the lethal brain tumor glioblastoma (GBM). Although this combination therapy shows promise, there are many unknown questions regarding how the tumor landscape and spatial dosing strategies impact the effectiveness of the treatment. Our study aims to shed light on these questions using a novel spatially explicit computational model of GBM response to treatment. Our results suggest that oncolytic viral dosing in the location of highest tumor cell density leads to substantial tumor size reduction over viral dosing in the center of the tumor. These results can help to inform future clinical trials and more effective treatment strategies for oncolytic viral therapy in GBM patients.

Abstract

Oncolytic viral therapies and immunotherapies are of growing clinical interest due to their selectivity for tumor cells over healthy cells and their immunostimulatory properties. These treatment modalities provide promising alternatives to the standard of care, particularly for cancers with poor prognoses, such as the lethal brain tumor glioblastoma (GBM). However, uncertainty remains regarding optimal dosing strategies, including how the spatial location of viral doses impacts therapeutic efficacy and tumor landscape characteristics that are most conducive to producing an effective immune response. We develop a three-dimensional agent-based model (ABM) of GBM undergoing treatment with a combination of an oncolytic Herpes Simplex Virus and an anti-PD-1 immunotherapy. 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 and including a mechanism of adaptive immune suppression via the PD-1/PD-L1 checkpoint pathway. We utilize the spatially explicit nature of the ABM to determine optimal viral dosing in both the temporal and spatial contexts. After proposing an adaptive viral dosing strategy that chooses to dose sites at the location of highest tumor cell density, we find that, in most cases, this adaptive strategy produces a more effective treatment outcome than repeatedly dosing in the center of the tumor.

Quantitative imaging and dynamics of tumor therapy with viruses

Cancer therapy remains challenging due to the myriad presentations of the disease and the vast genetic diversity of tumors that continuously evolve and often become resistant to therapy. Viruses can be engineered to specifically infect, replicate, and kill tumor cells (tumor virotherapy). Moreover, the viruses can be "armed" with therapeutic genes to enhance their oncolytic effect. Using viruses to treat cancer is exciting and novel and in principle can be used for a broad variety of tumors. However, the approach is distinctly different from other cancer therapies since success depends on establishment of an infection within the tumor and ongoing propagation of the oncolytic virus within the tumor itself. Therefore, the target itself amplifies the therapy. This introduces complex dynamics especially when the immune system is taken into consideration as well as the physical and other biological barriers to virus growth. Understanding these dynamics not only requires mathematical and computational models but also approaches for the noninvasive monitoring of the virus and tumor populations. In this perspective, we discuss strategies and current results to achieve this important goal of understanding these dynamics in pursuit of optimization of oncolytic virotherapy.

Measles Virus as an Oncolytic Immunotherapy

Measles virus (MeV) preferentially replicates in malignant cells, leading to tumor lysis and priming of antitumor immunity. Live attenuated MeV vaccine strains are therefore under investigation as cancer therapeutics. The versatile MeV reverse genetics systems allows for engineering of advanced targeted, armed, and shielded oncolytic viral vectors. Therapeutic efficacy can further be enhanced by combination treatments. An emerging focus in this regard is combination immunotherapy, especially with immune checkpoint blockade. Despite challenges arising from antiviral immunity, availability of preclinical models, and GMP production, early clinical trials have demonstrated safety of oncolytic MeV and yielded promising efficacy data. Future clinical trials with engineered viruses, rational combination regimens, and comprehensive translational research programs will realize the potential of oncolytic immunotherapy.

Modeling the Efficacy of Oncolytic Adenoviruses In Vitro and In Vivo: Current and Future Perspectives

Oncolytic adenoviruses (OAd) selectively target and lyse tumor cells and enhance anti- tumor immune responses. OAds have been used as promising cancer gene therapies for many years and there are a multitude of encouraging pre-clinical studies. However, translating OAd therapies to the clinic has had limited success, in part due to the lack of realistic pre-clinical models to rigorously test the efficacy of OAds. Solid tumors have a heterogenous and hostile microenvironment that provides many barriers to OAd treatment, including structural and immunosuppressive components that cannot be modeled in two-dimensional tissue culture. To replicate these characteristics and bridge the gap between pre-clinical and clinical success, studies must test OAd therapy in three-dimensional culture and animal models. This review focuses on current methods to test OAd efficacy in vitro and in vivo and the development of new model systems to test both oncolysis and immune stimulatory components of oncolytic adenovirotherapy.