ReviewViruses2016
Big Data Offers Novel Insights for Oncolytic Virus Immunotherapy.
Review in Viruses, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Oncolytic viruses: advanced strategies in cancer therapy.Signal transduction and targeted therapy · 2026Review
- Octyl itaconate enhances VSVΔ51 oncolytic virotherapy by multitarget inhibition of antiviral and inflammatory pathways.Nature communications · 2024Article
- Oncolytic Viruses in the Era of Omics, Computational Technologies, and Modeling: Thesis, Antithesis, and Synthesis.International journal of molecular sciences · 2023Review
- Systems Biology Approaches for the Improvement of Oncolytic Virus-Based Immunotherapies.Cancers · 2023Review
- Review
- Synthetic and systems biology principles in the design of programmable oncolytic virus immunotherapies for glioblastoma.Neurosurgical focus · 2021Review
- Optimizing oncolytic virotherapy in cancer treatment.Nature reviews. Drug discovery · 2019Review
- Defining a murine ovarian cancer model for the evaluation of conditionally-replicative adenovirus (CRAd) virotherapy agents.Journal of ovarian research · 2019Article
- Activation of Nrf2 Signaling Augments Vesicular Stomatitis Virus Oncolysis via Autophagy-Driven Suppression of Antiviral Immunity.Molecular therapy : the journal of the American Society of Gene Therapy · 2017Article
- [Combination of Oncolytic Virotherapy and CAR T/NK Cell Therapy for the Treatment of Cancer].Molekuliarnaia biologiiaReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.