Cancer scene investigation: how a cold virus became a tumor killer

Exploring the Protective Effect of Food Drugs against Viral Diseases: Interaction of Functional Food Ingredients and SARS-CoV-2, Influenza Virus, and HSV

A complex network of processes inside the human immune system provides resistance against a wide range of pathologies. These defenses form an innate and adaptive immunity, in which certain immune components work together to counteract infections. In addition to inherited variables, the susceptibility to diseases may be influenced by factors such as lifestyle choices and aging, as well as environmental determinants. It has been shown that certain dietary chemical components regulate signal transduction and cell morphologies which, in turn, have consequences on pathophysiology. The consumption of some functional foods may increase immune cell activity, defending us against a number of diseases, including those caused by viruses. Here, we investigate a range of functional foods, often marketed as immune system boosters, in an attempt to find indications of their potential protective role against diseases caused by viruses, such as the influenza viruses (A and B), herpes simplex virus (HSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in some cases mediated by gut microbiota. We also discuss the molecular mechanisms that govern the protective effects of some functional foods and their molecular constituents. The main message of this review is that discovering foods that are able to strengthen the immune system can be a winning weapon against viral diseases. In addition, understanding how the dietary components function can aid in the development of novel strategies for maintaining human bodily health and keeping our immune systems strong.

Two new species of betatorqueviruses identified in a human melanoma that metastasized to the brain

The role of viral infections in the etiology of brain cancer remains uncertain. Prior studies mostly focused on transcriptome or viral DNA integrated in tumor cells. To investigate for the presence of viral particles, we performed metagenomics sequencing on viral capsid-protected nucleic acids from 12 primary and 8 metastatic human brain tumors. One brain tumor metastasized from a skin melanoma harbored two new human anellovirus species, Torque teno mini virus Emory1 (TTMV Emory1) and Emory2 (TTMV Emory2), while the remaining 19 samples did not reveal any exogenous viral sequences. Their genomes share 63-67% identity with other TTMVs, and phylogenetic clustering supports their classification within the Betatorquevirus genus. This is the first identification of betatorqueviruses in brain tumors. The viral DNA was in its expected non-integrated circular form, and it is unclear if the viruses contributed to tumor formation. Whether the viruses originated from blood, or the primary skin tumor could not be ascertained. Overall, our results demonstrate the usefulness of viral metagenomics to detect previously unknown exogenous virus in human brain tumors. They further suggest that active viral infections are rare events in brain tumors, but support a follow-up larger scale study to quantify their frequency in different brain tumor subtypes.

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.

Second-generation HIF-activated oncolytic adenoviruses with improved replication, oncolytic, and antitumor efficacy

There is a need to develop more potent oncolytic adenoviruses that exhibit increased anti-tumor activity in patients. The HYPR-Ads are targeted oncolytic adenoviruses that specifically kill tumor cells which express active hypoxia-inducible factor (HIF). While therapeutically efficacious, the HYPR-Ads exhibited attenuated replication and oncolytic activity. To overcome these deficiencies and improve anti-tumor efficacy, we created new HIF-activated oncolytic Ads, HIF-Ad and HIF-Ad-IL4, which have two key changes: (i) a modified HIF-responsive promoter to regulate the E1A replication gene and (ii) insertion of the E3 gene region. The HIF-Ads demonstrated conditional activation of E1A expression under hypoxia. Importantly, the HIF-Ads exhibit hypoxia-dependent replication, oncolytic, and cellular release activities and potent anti-tumor efficacy, all of which are significantly greater than the HYPR-Ads. Notably, HIF-Ad-IL4 treatment led to regressions in tumor size by 70% and extensive tumor infiltration by leukocytes resulting in an anti-tumor efficacy that is up to 6-fold greater than the HYPR-Ads, HIF-Ad, and wild-type adenovirus treatment. These studies demonstrate that treatment with a HIF-activated oncolytic adenovirus leads to a measurable therapeutic response. The novel design of the HIF-Ads represents a significant improvement compared to first-generation oncolytic Ads and has great potential to increase the efficacy of this cancer therapy.

ODE models for oncolytic virus dynamics

Replicating oncolytic viruses are able to infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. This makes them potentially useful in cancer therapy, and a variety of viruses have shown promising results in clinical trials. Nevertheless, consistent success remains elusive and the correlates of success have been the subject of investigation, both from an experimental and a mathematical point of view. Mathematical modeling of oncolytic virus therapy is often limited by the fact that the predicted dynamics depend strongly on particular mathematical terms in the model, the nature of which remains uncertain. We aim to address this issue in the context of ODE modeling, by formulating a general computational framework that is independent of particular mathematical expressions. By analyzing this framework, we find some new insights into the conditions for successful virus therapy. We find that depending on our assumptions about the virus spread, there can be two distinct types of dynamics. In models of the first type (the "fast spread" models), we predict that the viruses can eliminate the tumor if the viral replication rate is sufficiently high. The second type of models is characterized by a suboptimal spread (the "slow spread" models). For such models, the simulated treatment may fail, even for very high viral replication rates. Our methodology can be used to study the dynamics of many biological systems, and thus has implications beyond the study of virus therapy of cancers.

Use of oncolytic viruses for the eradication of drug-resistant cancer cells

Targeted therapy using small-molecule inhibitors is a promising new therapy approach against cancer, but drug-resistant mutants present an obstacle to success. Oncolytic virus therapy, where viruses replicate specifically in cancer cells and kill them, is another promising therapy approach against cancer. While encouraging results have been observed in clinical trials, consistent success has not been possible so far. Based on a computational framework, I report that even if oncolytic virus therapy fails to eradicate a cancer, it can have the potential to eradicate the sub-population of drug-resistant cancer cells. Once this has occurred, targeted drug therapy can be used to induce cancer remission. For this to work, a drug resistance mutation must confer a certain fitness cost to the cell, as has been documented in the literature. The reason for this finding is that in the presence of a shared virus, the faster growing (drug-sensitive) cell population produces an amount of virus that is too much for the slower growing (drug-resistant) cell population to survive. This is derived from a population dynamic principle known as apparent competition. Therefore, a sequential combination of oncolytic virus and targeted therapies can overcome major weaknesses of either approach alone.

Towards predictive computational models of oncolytic virus therapy: basis for experimental validation and model selection

Oncolytic viruses are viruses that specifically infect cancer cells and kill them, while leaving healthy cells largely intact. Their ability to spread through the tumor makes them an attractive therapy approach. While promising results have been observed in clinical trials, solid success remains elusive since we lack understanding of the basic principles that govern the dynamical interactions between the virus and the cancer. In this respect, computational models can help experimental research at optimizing treatment regimes. Although preliminary mathematical work has been performed, this suffers from the fact that individual models are largely arbitrary and based on biologically uncertain assumptions. Here, we present a general framework to study the dynamics of oncolytic viruses that is independent of uncertain and arbitrary mathematical formulations. We find two categories of dynamics, depending on the assumptions about spatial constraints that govern that spread of the virus from cell to cell. If infected cells are mixed among uninfected cells, there exists a viral replication rate threshold beyond which tumor control is the only outcome. On the other hand, if infected cells are clustered together (e.g. in a solid tumor), then we observe more complicated dynamics in which the outcome of therapy might go either way, depending on the initial number of cells and viruses. We fit our models to previously published experimental data and discuss aspects of model validation, selection, and experimental design. This framework can be used as a basis for model selection and validation in the context of future, more detailed experimental studies. It can further serve as the basis for future, more complex models that take into account other clinically relevant factors such as immune responses.

Yeast cytosine deaminase mutants with increased thermostability impart sensitivity to 5-fluorocytosine

Prodrug gene therapy (PGT) is a treatment strategy in which tumor cells are transfected with a 'suicide' gene that encodes a metabolic enzyme capable of converting a nontoxic prodrug into a potent cytotoxin. One of the most promising PGT enzymes is cytosine deaminase (CD), a microbial salvage enzyme that converts cytosine to uracil. CD also converts 5-fluorocytosine (5FC) to 5-fluorouracil, an inhibitor of DNA synthesis and RNA function. Over 150 studies of CD-mediated PGT applications have been reported since 2000, all using wild-type enzymes. However, various forms of CD are limited by inefficient turnover of 5FC and/or limited thermostability. In a previous study, we stabilized and extended the half-life of yeast CD (yCD) by repacking of its hydrophobic core at several positions distant from the active site. Here we report that random mutagenesis of residues selected based on alignment with similar enzymes, followed by selection for enhanced sensitization to 5FC, also produces an enzyme variant (yCD-D92E) with elevated T(m) values and increased activity half-life. The new mutation is located at the enzyme's dimer interface, indicating that independent mutational pathways can lead to an increase in stability, as well as a more subtle effect on enzyme kinetics. Each independently derived set of mutations significantly improves the enzyme's performance in PGT assays both in cell culture and in animal models.

Targeted cancer gene therapy using a hypoxia inducible factor dependent oncolytic adenovirus armed with interleukin-4

There is a need for novel therapies targeting hypoxic cells in tumors. These cells are associated with tumor resistance to therapy and express hypoxia inducible factor-1 (HIF-1), a transcription factor that mediates metabolic adaptation to hypoxia and activates tumor angiogenesis. We previously developed an oncolytic adenovirus (HYPR-Ad) for the specific killing of hypoxic/HIF-active tumor cells, which we now armed with an interleukin-4 gene (HYPR-Ad-IL4). We designed HYPR-Ad-IL4 by cloning the Ad E1A viral replication and IL-4 genes under the regulation of a bidirectional hypoxia/HIF-responsive promoter. The IL-4 cytokine was chosen for its ability to induce a strong host antitumor immune response and its potential antiangiogenic activity. HYPR-Ad-IL4 induced hypoxia-dependent IL-4 expression, viral replication, and conditional cytolysis of hypoxic, but not normoxic cells. The treatment of established human tumor xenografts with HYPR-Ad-IL4 resulted in rapid and maintained tumor regression with the same potency as that of wild-type dl309-Ad. HYPR-Ad-IL4-treated tumors displayed extensive necrosis, fibrosis, and widespread viral replication. Additionally, these tumors contained a distinctive leukocyte infiltrate and prominent hypoxia. The use of an oncolytic Ad that locally delivers IL-4 to tumors is novel, and we expect that HYPR-Ad-IL4 will have broad therapeutic use for all solid tumors that have hypoxia or active HIF, regardless of tissue origin or genetic alterations.