Evidence map›Paper›PMID 18483501›Full record

ArticleCancer gene therapy2008

Systemic delivery of HK Raf-1 siRNA polyplexes inhibits MDA-MB-435 xenografts.

Q Leng, P Scaria, P Lu, M C Woodle, A J Mixson

Open access · bronzeAbstract read
In one paragraph

Article in Cancer gene therapy, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

27 citing papers in PubMed, 56 citations in OpenAlex.

  1. An effective tumor-inhibiting siRNA delivery platform.Biochemical and biophysical research communications · 2026
    Article
  2. Review
  3. Review
  4. Systemic dual delivery of a tumor-inhibiting plasmid expressing p16 and shRaf.Biochemical and biophysical research communications · 2025
    Article
  5. Review
  6. Article
  7. Nucleic acid-based drugs for patients with solid tumours.Nature reviews. Clinical oncology · 2024
    Review
  8. Article
  9. Review
  10. Peptide carriers to the rescue: overcoming the barriers to siRNA delivery for cancer treatment.Translational research : the journal of laboratory and clinical medicine · 2019
    Review
  11. Article
  12. Review
  13. Article
  14. Functional peptides for siRNA delivery.Advanced drug delivery reviews · 2017
    Review
  15. Article
  16. Article
  17. Harnessing RNAi nanomedicine for precision therapy.Molecular and cellular therapies · 2014
    Review
  18. Article
  19. Lipopeptide delivery of siRNA to the central nervous system.Methods in molecular biology (Clifton, N.J.) · 2013
    Article
  20. Buffering capacity and size of siRNA polyplexes influence cytokine levels.Molecular therapy : the journal of the American Society of Gene Therapy · 2012
    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

5 authors at 2 institutions in 1 country.

Q LengDepartment of Pathology, University of Maryland, Baltimore, MD 21201, USA.
P Scaria
P Lu
M C Woodle
A J Mixson
University of Maryland, Baltimore · USSirnaomics (United States) · US

Funding

Gene Delivery of P53 in a Tumor-bearing Mouse ModelR01CA096984 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI MIXSON, ARCHIBALD JAMES · 2004 to 2007
$1.1M
SYSTEMIC DELIVERY OF P53 INHIBITS BREAST CANCERR29CA070394 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI MIXSON, ARCHIBALD JAMES · 1997 to 2001
$199k
NCI NIH HHS CA70394NCI NIH HHS R01 CA096984NCI NIH HHS R29 CA070394
6 · The paper itself

Abstract

Our past research has focused on identifying an effective carrier composed of histidine and lysine for delivery of nucleic acid into cells. For this purpose, we developed histidine-lysine-rich (HK) polymers with specific sequences and branching. We have found that branched HK polymers in complex with Raf-1 siRNA markedly decreased Raf-1 mRNA and induced apoptosis in cell lines in vitro. The primary focus of the present study was to determine an effective carrier to deliver siRNA systemically to tumor xenografts. After comparing HK:Raf-1 polyplexes for their in-vivo efficacy, we investigated in greater detail whether one of these polymers, H3K(+H)4b, in complex with Raf-1 siRNA, inhibited the growth of MDA-MB-435 xenografts. H3K(+H)4b is a four-branched HK peptide whose predominant repeating sequence within the terminal arm is -HHHK-. After the first tail-vein injection in a mouse model, there was a statistically significant reduction in tumor size between the H3K(+H)4b:Raf-1 siRNA-treated and the control groups (P<0.01). By the third injection, there was nearly a 50% reduction in the Raf-1 siRNA-treated group compared to the control siRNA-treated or -untreated group. Consistent with a significant effect of the HK:Raf-1 polyplex on the tumor, there were marked histological changes, increased apoptosis and fewer vessels in the Raf-1 siRNA-treated group. Raf-1 protein within the tumor was significantly decreased after treatment with the HK:Raf-1 siRNA polyplex compared to the control treatment groups. Despite the striking effect on the tumor by the HK Raf-1 siRNA, there was little evidence of toxicity in normal tissues with this therapy. By harnessing the ability to modify the amino-acid sequence and branching of HK polymers, we expect continued development of HK polymers as in-vivo carriers of siRNA.

Indexed as

Transplantation, HeterologousAnimalsCell Line, TumorFemaleHistidineHumansImmunohistochemistryKi-67 AntigenLysineMiceMice, NudePlatelet Endothelial Cell Adhesion Molecule-1Proto-Oncogene Proteins c-rafRNA, Small InterferingTransfectionHistidineKi-67 AntigenLysinePlatelet Endothelial Cell Adhesion Molecule-1Proto-Oncogene Proteins c-rafRNA, Small Interfering

Identifiers

PMID18483501
PMCPMC5502125
OpenAlexW1983770184

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.