ArticleCancer gene therapy2007
Gene therapy of liver tumors with human liver-specific nanoparticles.
Article in Cancer gene therapy, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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.
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
7 citing papers in PubMed, 29 citations in OpenAlex.
- Polymerized Albumin Receptor of Hepatitis B Virus for Evading the Reticuloendothelial System.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Gold nanoparticle coatings as efficient adenovirus carriers to non-infectable stem cells.RSC advances · 2019Article
- Transarterial administration of integrin inhibitor loaded nanoparticles combined with transarterial chemoembolization for treating hepatocellular carcinoma in a rat model.World journal of gastroenterology · 2016Article
- Biological gene delivery vehicles: beyond viral vectors.Molecular therapy : the journal of the American Society of Gene Therapy · 2009Review
- Molecularly characterised xenograft tumour mouse models: valuable tools for evaluation of new therapeutic strategies for secondary liver cancers.Journal of biomedicine & biotechnology · 2009Article
- Advances in experimental and translational research in the treatment of hepatocellular carcinoma.Surgical oncology clinics of North America · 2008Review
- Harnessing the RNA interference pathway to advance treatment and prevention of hepatocellular carcinoma.World journal of gastroenterology · 2008Review
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of safe and efficient liver-specific gene delivery approaches offers new perspectives for the treatment of liver disease, in particular, liver cancer. We evaluated the therapeutic potential of hepatotropic nanoparticles for gene therapy of liver tumor. These nanoparticles do not contain a viral genome and display the hepatitis B virus L antigen, which is essential to confer hepatic specificity. It has not been shown whether a therapeutic effect could be obtained using L nanoparticles in a human liver tumor xenograft model. Rats bearing human hepatic (NuE) and non-hepatic tumors were injected with L nanoparticles containing a green fluorescent protein (GFP) expression plasmid. GFP expression was observed only in NuE-derived tumors but not in the non-hepatic tumor. The potential for treatment of liver tumors was analyzed using L nanoparticles containing the herpes simplex virus thymidine kinase gene, in conjunction with ganciclovir pro-drug administration. The growth of NuE-derived tumors in L particle-injected rats was significantly suppressed, but not of the non-hepatic tumor control. In summary, this is the first demonstration that nanoparticles could be used for delivery of therapeutic genes with anti-tumor activity into human liver tumors. This intravenous delivery system may be one of the major advantages as compared to many other viral vector systems.
Indexed as
Identifiers
What OpenQuestion holds
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.