Molecular network pathways and functional analysis of tumor signatures associated with development of resistance to viral gene therapy

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.

Resistance Mechanisms Influencing Oncolytic Virotherapy, a Systematic Analysis

Resistance to therapy is a frequently observed phenomenon in the treatment of cancer, and as with other cancer therapeutics, therapies based on oncolytic viruses also face the challenges of resistance, such as humoral and cellular antiviral responses, and tumor-associated interferon-mediated resistance. In order to identify additional mechanisms of resistance that may contribute to therapeutic failure, we developed a systematic search strategy for studies published in PubMed. We analyzed 6143 articles on oncolytic virotherapy and found that approximately 8% of these articles use resistance terms in the abstract and/or title. Of these 439 articles, 87 were original research. Most of the findings reported pertain to resistance mediated by tumor-cell-dependent interferon signaling. Yet, mechanisms such as epigenetic modifications, hypoxia-mediated inhibition, APOBEC-mediated resistance, virus entry barriers, and spatiotemporal restriction to viral spread, although not frequently assessed, were demonstrated to play a major role in resistance. Similarly, our results suggest that the stromal compartment consisting of, but not limited to, myeloid cells, fibroblasts, and epithelial cells requires more study in relation to therapy resistance using oncolytic viruses. Thus, our findings emphasize the need to assess the stromal compartment and to identify novel mechanisms that play an important role in conferring resistance to oncolytic virotherapy.

Gene expression profiling of hematologic malignant cell lines resistant to oncolytic virus treatment

Pexa-Vec (pexastimogene devacirpvec; JX-594) has emerged as an attractive tool in oncolytic virotherapy. Pexa-Vec demonstrates oncolytic and immunotherapeutic mechanisms of action. But the determinants of resistance to Pexa-Vec are mostly unknown. We treated hemoatologic malignant cells with Pexa-Vec and examined the gene-expression pattern of sensitive and resistant cells. Human myeloid malignant cell lines (RPMI-8226, IM-9, K562, THP-1) and lymphoid cancer cell lines (MOLT4, CCRF-CEM, Ramos, U937) were treated with Pexa-Vec. Pexa-Vec was cytotoxic on myeloid cell lines in a dose-dependent manner, and fluorescent imaging and qPCR revealed that Pexa-Vec expression was low in RAMOS than IM-9 after 24 hrs and 48 hrs of infection. Gene expression profiles between two groups were analyzed by microarray. Genes with at least 2-fold increase or decrease in their expression were identified. A total of 660 genes were up-regulated and 776 genes were down-regulated in lymphoid cancer cell lines. The up- and down-regulated genes were categorized into 319 functional gene clusters. We identified the top 10 up-regulated genes in lymphoid cells. Among them three human genes (LEF1, STAMBPL1, and SLFN11) strongly correlated with viral replication. Up-regulation of PVRIG, LPP, CECR1, Arhgef6, IRX3, IGFBP2, CD1d were related to resistant to Pexa-Vec. In conclusion, lymphoid malignant cells are resistant to Pexa-Vec and displayed up-regulated genes associated with resistance to oncolytic viral therapy. These data provide potential targets to overcome resistance, and suggest that molecular assays may be useful in selecting patients for further clinical trials with Pexa-Vec.

Big Data Offers Novel Insights for Oncolytic Virus Immunotherapy

Large-scale assays, such as microarrays, next-generation sequencing and various “omics” technologies, have explored multiple aspects of the immune response following virus infection, often from a public health perspective. Yet a lack of similar data exists for monitoring immune engagement during oncolytic virus immunotherapy (OVIT) in the cancer setting. Tracking immune signatures at the tumour site can create a snapshot or longitudinally analyse immune cell activation, infiltration and functionality within global populations or individual cells. Mapping immune changes over the course of oncolytic biotherapy—from initial infection to tumour stabilisation/regression through to long-term cure or escape/relapse—has the potential to generate important therapeutic insights around virus-host interactions. Further, correlating such immune signatures with specific tumour outcomes has significant value for guiding the development of novel oncolytic virus immunotherapy strategies. Here, we provide insights for OVIT from large-scale analyses of immune populations in the infection, vaccination and immunotherapy setting. We analyse several approaches to manipulating immune engagement during OVIT. We further explore immunocentric changes in the tumour tissue following immunotherapy, and compile several immune signatures of therapeutic success. Ultimately, we highlight clinically relevant large-scale approaches with the potential to strengthen future oncolytic strategies to optimally engage the immune system.

Promising oncolytic agents for metastatic breast cancer treatment

New therapies for metastatic breast cancer patients are urgently needed. The long-term survival rates remain unacceptably low for patients with recurrent disease or disseminated metastases. In addition, existing therapies often cause a variety of debilitating side effects that severely impact quality of life. Oncolytic viruses constitute a developing therapeutic modality in which interest continues to build due to their ability to spare normal tissue while selectively destroying tumor cells. A number of different viruses have been used to develop oncolytic agents for breast cancer, including herpes simplex virus, adenovirus, vaccinia virus, measles virus, reovirus, and others. In general, clinical trials for several cancers have demonstrated excellent safety records and evidence of efficacy. However, the impressive tumor responses often observed in preclinical studies have yet to be realized in the clinic. In order for the promise of oncolytic virotherapy to be fully realized for breast cancer patients, effectiveness must be demonstrated in metastatic disease. This review provides a summary of oncolytic virotherapy strategies being developed to target metastatic breast cancer.

Optimization and preclinical design of genetically engineered viruses for human oncolytic therapy

INTRODUCTION

Oncolytic viruses (OVs) occupy a strategic niche in the dynamic era of biological and gene therapy of human cancers. However, the use of OVs is the subject of close scrutiny due to impediments such as the insufficiency of patient generalizations posed by heterogeneous tumor responses to treatment, inherent or potentially lethal viral pathogenicities, unanticipated host- or immune-related adverse effects, and the emergence of virus-resistant cancer cells. These challenges can be overcome by the design and development of more definitive (optimized, targeted, and individualized) cancer virotherapeutics.

AREAS COVERED

The translation of current knowledge and recent innovations into rational treatment prospects hinges on an iterative loop of variables pertaining to genetically engineered viral oncolytic efficacy and safety profiles, mechanism-of-action data, potencies of synergistic oncolytic viral combinations with conventional tumor, immuno-, chemo-, and radiation treatment modalities, optimization of the probabilities of treatment successes in heterogeneous (virus-sensitive and -resistant) tumor cell populations by mathematical modeling, and lessons learned from preclinical studies and human clinical trials.

EXPERT OPINION

In recent years, it has become increasingly clear that proof-of-principle is critical for the preclinical optimization of oncolytic viruses to target heterogeneous forms of cancer and to prioritize current concerns related to the efficacy and safety of oncolytic virotherapy.