Evidence map›Paper›PMID 25414028›Full record

ArticleCurrent gene therapy2015

Controlled gene delivery can enhance therapeutic outcome for cancer immune therapy for melanoma.

Shawna A Shirley, Cathryn G Lundberg, Fanying Li, Niculina Burcus, Richard Heller

Abstract read
In one paragraph

Article in Current gene therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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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

5 authors.

Shawna A Shirley
Cathryn G Lundberg
Fanying Li
Niculina Burcus
Richard HellerFrank Reidy Research Center for Bioelectrics, Old Dominion University, Norfolk, VA 23508, USA. rheller@odu.edu.

Funding

Efficient Delivery of Plasmid DNA to Achieve Appropriate Transgene ExpressionR01CA186730 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI HELLER, RICHARD · 2015 to 2019
$1.8M
Therapeutic Potential of IL-15 Plasmid Delivery to Tumors Using ElectroporationR01CA122518 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI HELLER, RICHARD · 2008 to 2013
$1.6M
NCI NIH HHS R01 CA122518NCI NIH HHS R01 CA186730
6 · The paper itself

Abstract

Effective delivery still remains a major hurdle in the development of gene based therapies. While technological advances have occurred that have improved delivery in general, there is still a need for controlled delivery in order to achieve therapeutic effects. Gene electrotransfer (GET) can be utilized to accomplish this. Careful selection of parameters used for delivery such as amplitude, duration and number of pulses as well as plasmid construct can be manipulated in order to achieve appropriate levels of local expression. Previously we have shown that direct delivery of the therapeutic cytokine, interleukin 12 (IL-12), to tumors using electrotransfer can generate local and systemic anti-tumor effects in pre-clinical and clinical studies. Using this model we hypothesized that modulating local gene expression using GET can affect therapeutic outcome. To test this, we used multiple GET protocols and plasmids to achieve varying levels of local IL-12 expression. We found that high local gene expression did not give rise to a better therapeutic outcome. This suggests the level and possibly the duration of gene expression are important in mediating the host immune response against melanoma. These data also emphasize the importance of considering the desired immune outcome of the therapy when selecting parameters for GET.

Indexed as

Gene Transfer TechniquesAnimalsFemaleGene ExpressionGenetic TherapyInterleukin-12MelanomaMiceMice, Inbred C57BLPlasmidsTreatment OutcomeInterleukin-12

Identifiers

PMID25414028
PMCPMC6375514

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Registered trials

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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.