Evidence map›Paper›PMID 28944214›Full record

ReviewFrontiers in oncology2017

Oncolytic Viruses-Interaction of Virus and Tumor Cells in the Battle to Eliminate Cancer.

Anwen Howells, Giulia Marelli, Nicholas R Lemoine, Yaohe Wang

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

76 citing papers in PubMed.

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  17. Oncolytic Virotherapy: A New Paradigm in Cancer Immunotherapy.International journal of molecular sciences · 2024
    Review
  18. Review
  19. Review
  20. Article

16 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Anwen HowellsCentre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.
Giulia MarelliCentre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.
Nicholas R LemoineCentre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.
Yaohe WangCentre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.

Funding

Medical Research Council MR/M015696/1Medical Research Council MR/N027655/1
6 · The paper itself

Abstract

Oncolytic viruses (OVs) are an emerging treatment option for many cancer types and have recently been the focus of extensive research aiming to develop their therapeutic potential. The ultimate aim is to design a virus which can effectively replicate within the host, specifically target and lyse tumor cells and induce robust, long lasting tumor-specific immunity. There are a number of viruses which are either naturally tumor-selective or can be modified to specifically target and eliminate tumor cells. This means they are able to infect only tumor cells and healthy tissue remains unharmed. This specificity is imperative in order to reduce the side effects of oncolytic virotherapy. These viruses can also be modified by various methods including insertion and deletion of specific genes with the aim of improving their efficacy and safety profiles. In this review, we have provided an overview of the various virus species currently being investigated for their oncolytic potential and the positive and negative effects of a multitude of modifications used to increase their infectivity, anti-tumor immunity, and treatment safety, in particular focusing on the interaction of tumor cells and OVs.

Indexed as

cancer treatmenthost factorsoncolytic virusselectivitytumor cells

Identifiers

PMID28944214
PMCPMC5596080

What OpenQuestion holds

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Registered trials

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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.