Evidence map›Paper›PMID 15286681›Full record

ReviewCancer gene therapy2004

Oncolytic viral therapies.

Eugene Lin, John Nemunaitis

Abstract readReview
PubMed Publisher
In one paragraph

Review in Cancer gene therapy, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
6.5field-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

58 citing papers in PubMed, 127 citations in OpenAlex.

  1. Oncolytic viruses: advanced strategies in cancer therapy.Signal transduction and targeted therapy · 2026
    Review
  2. Review
  3. Therapeutic Applications for Oncolytic Self-Replicating RNA Viruses.International journal of molecular sciences · 2022
    Review
  4. Interventional oncology: new techniques and new devices.The British journal of radiology · 2022
    Review
  5. Review
  6. Article
  7. Electrical Stimulation for Immune Modulation in Cancer Treatments.Frontiers in bioengineering and biotechnology · 2021
    Review
  8. Review
  9. Article
  10. Analysis of a Multiple Delays Model for Treatment of Cancer with Oncolytic Virotherapy.Computational and mathematical methods in medicine · 2019
    Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. Review
  16. Article
  17. Oncolytic adenovirus-mediated short hairpin RNA targeting MYCN gene induces apoptosis by upregulating RKIP in neuroblastoma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2015
    Article
  18. Review
  19. Review
  20. Is cancer gene therapy an empty suit?The Lancet. Oncology · 2013
    Review
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

2 authors at 2 institutions in 1 country.

Eugene LinMary Crowley Medical Research Center, Dallas, Texas, USA.
John Nemunaitis
Mary Crowley Cancer Research Center · USTexas Oncology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular research has vastly advanced our understanding of the mechanism of cancer growth and spread. Targeted approaches utilizing molecular science have yielded provocative results in the treatment of cancer. Oncolytic viruses genetically programmed to replicate within cancer cells and directly induce toxic effect via cell lysis or apoptosis are currently being explored in the clinic. Safety has been confirmed and despite variable efficacy results several dramatic responses have been observed with some oncolytic viruses. This review summarizes results of clinical trials with oncolytic viruses in cancer.

Indexed as

Virus Physiological PhenomenaGenetic TherapyHumansNeoplasmsViruses

Identifiers

PMID15286681
OpenAlexW2053390368

What OpenQuestion holds

Textmetadata
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.