Evidence map›Paper›PMID 33958660›Full record

ArticleScientific reports2021

Nanoparticle-mediated tumor cell expression of mIL-12 via systemic gene delivery treats syngeneic models of murine lung cancers.

Hye-Hyun Ahn, Christine Carrington, Yizong Hu, Heng-Wen Liu, Christy Ng, Hwanhee Nam, Andrew Park, Catherine Stace, Will West, Hai-Quan Mao and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Nanovaccines for lung cancer: Platforms, mechanistic insights, and translational challenges.Chinese medical journal pulmonary and critical care medicine · 2026
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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

13 authors at 4 institutions in 1 country.

Hye-Hyun AhnDivision of Nuclear Medicine and Molecular Imaging, Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, 21205, USA.
Christine CarringtonCancer Targeting Systems, 1188 Centre Street, Newton Centre, MA, 02459, USA.
Yizong HuDepartment of Biomedical Engineering, Translational Tissue Engineering Center, Johns Hopkins University, School of Medicine, Baltimore, MD, 21287, USA.
Heng-Wen LiuDepartment of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Christy NgDepartment of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Hwanhee NamDivision of Nuclear Medicine and Molecular Imaging, Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, 21205, USA.
Andrew ParkDivision of Nuclear Medicine and Molecular Imaging, Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, 21205, USA.
Catherine StaceCancer Targeting Systems, 1188 Centre Street, Newton Centre, MA, 02459, USA.
Will WestCancer Targeting Systems, 1188 Centre Street, Newton Centre, MA, 02459, USA.
Hai-Quan MaoDepartment of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Martin G PomperDivision of Nuclear Medicine and Molecular Imaging, Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, 21205, USA.
Christopher G UllmanCancer Targeting Systems, 1188 Centre Street, Newton Centre, MA, 02459, USA. chris.ullman@paratopix.com.
Il MinnDivision of Nuclear Medicine and Molecular Imaging, Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, 21205, USA. iminn1@jhmi.edu.
Johns Hopkins University · USJohns Hopkins Medicine · USRapt Therapeutics (United States) · USTarget (United States) · US

Funding

TRANSGENIC MODELS FOR PROSTATE CANCER AND AUTOIMMUNITYP50CA058236 · NCI · JOHNS HOPKINS UNIVERSITY · PI DENMEADE, SAMUEL R · 1992 to 2020
$43.9M
Training/Dissemination-Resource for Molecular Imaging Agents in Precision MedicineP41EB024495 · NIBIB · UT SOUTHWESTERN MEDICAL CENTER · PI MARTIN G POMPER · 2017 to 2026
$11.8M
NCI NIH HHS P50 CA058236NIBIB NIH HHS P41 EB024495
6 · The paper itself

Abstract

Treatment of cancers in the lung remains a critical challenge in the clinic for which gene therapy could offer valuable options. We describe an effective approach through systemic injection of engineered polymer/DNA nanoparticles that mediate tumor-specific expression of a therapeutic gene, under the control of the cancer-selective progression elevated gene 3 (PEG-3) promoter, to treat tumors in the lungs of diseased mice. A clinically tested, untargeted, polyethylenimine carrier was selected to aid rapid transition to clinical studies, and a CpG-free plasmid backbone and coding sequences were used to reduce inflammation. Intravenous administration of nanoparticles expressing murine single-chain interleukin 12, under the control of PEG-3 promoter, significantly improved the survival of mice in both an orthotopic and a metastatic model of lung cancer with no marked symptoms of systemic toxicity. These outcomes achieved using clinically relevant nanoparticle components raises the promise of translation to human therapy.

Indexed as

Genetic TherapyGene Transfer TechniquesAnimalsDisease Models, AnimalDNAGene ExpressionHumansInjectionsInterleukin-12Lung NeoplasmsMiceMice, SCIDNanomedicineNanoparticlesPolyethyleneimineDNAInterleukin-12Polyethyleneimine

Identifiers

PMID33958660
PMCPMC8102550
OpenAlexW3158901419

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.