Evidence map›Paper›PMID 18350598›Full record

ReviewWorld journal of gastroenterology2008

Harnessing the RNA interference pathway to advance treatment and prevention of hepatocellular carcinoma.

Patrick Arbuthnot, Liam-Jed Thompson

Abstract readReview
In one paragraph

Review in World journal of gastroenterology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. HIF-1Evidence-based complementary and alternative medicine : eCAM · 2021
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Hepatocellular carcinoma: insight from animal models.Nature reviews. Gastroenterology & hepatology · 2011
    Review
  9. Article
  10. Article
  11. Article
  12. Lentiviral delivery of short hairpin RNAs.Advanced drug delivery reviews · 2009
    Review
  13. Article
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.

Patrick ArbuthnotAntiviral Gene Therapy Research Unit, Department of Molecular Medicine and Haema-tology, University of the Witwatersrand Medical School, Private Bag 3, WITS 2050, South Africa. patrick.arbuthnot@wits.ac.za
Liam-Jed Thompson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Primary liver cancer is the fifth most common malignancy in the world and is a leading cause of cancer-related mortality. Available treatment for hepatocellular carcinoma (HCC), the commonest primary liver cancer, is rarely curative and there is a need to develop therapy that is more effective. Specific and powerful gene silencing that can be achieved by activating RNA interference (RNAi) has generated enthusiasm for exploiting this pathway for HCC therapy. Many studies have been carried out with the aim of silencing HCC-related cellular oncogenes or the hepatocarcinogenic hepatitis B virus (HBV) and hepatitis C virus (HCV). Proof of principle studies have demonstrated promising results, and an early clinical trial assessing RNAi-based HBV therapy is currently in progress. Although the data augur well, there are several significant hurdles that need to be overcome before the goal of RNAi-based therapy for HCC is realized. Particularly important are the efficient and safe delivery of RNAi effecters to target malignant tissue and the limitation of unintended harmful non-specific effects.

Indexed as

Gene Expression Regulation, NeoplasticRNA InterferenceAnimalsCarcinoma, HepatocellularGenetic TherapyHepatitis BHepatitis CHumansLiver NeoplasmsMicroRNAsRisk FactorsMicroRNAs

Identifiers

PMID18350598
PMCPMC2695907

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.