Evidence map›Paper›PMID 36095879›Full record

ReviewTranslational oncology2022

Current landscape and perspective of oncolytic viruses and their combination therapies.

Yinghan Su, Changqing Su, Lunxiu Qin

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Translational oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
5.8field-weighted citation impact, top 3% of its field
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

23 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
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  4. Oncolytic viruses: advanced strategies in cancer therapy.Signal transduction and targeted therapy · 2026
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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

3 authors at 2 institutions in 1 country.

Yinghan SuDepartment of General Surgery, Huashan Hospital, Cancer Metastasis Institute, Fudan University, Shanghai 200040, China; Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
Changqing SuNational Center for Liver Cancer (NCLC), Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai 200438, China. Electronic address: suchangqing@gmail.com.
Lunxiu QinDepartment of General Surgery, Huashan Hospital, Cancer Metastasis Institute, Fudan University, Shanghai 200040, China; Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China. Electronic address: qinlx@fudan.edu.cn.
Fudan University · CNSecond Military Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oncolytic virotherapy has become an important strategy in cancer immunotherapy. Oncolytic virus (OV) can reshape the tumor microenvironment (TME) through its replication-mediated oncolysis and transgene-produced anticancer effect, inducing an antitumor immune response and creating favorable conditions for the combination of other therapeutic measures. Extensive preclinical and clinical data have suggested that OV-based combination therapy has definite efficacy and promising prospects. Recently, several clinical trials of oncolytic virotherapy combined with immunotherapy have made breakthroughs. This review comprehensively elaborates the OV types and their targeting mechanisms, the selection of anticancer genes armed in OVs, and the therapeutic modes of action and strategies of OVs to provide a theoretical basis for the better design and construction of OVs and the optimization of OV-based therapeutic strategies.

Indexed as

Anticancer mechanismCancerOncolytic virusTherapeutic strategyTumor microenvironment

Identifiers

PMID36095879
PMCPMC9472052
OpenAlexW4295501003

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.