Evidence map›Paper›PMID 31930167›Full record

ArticleMolecular therapy oncolytics2020

Generation of a Tumor-Specific Chemokine Gradient Using Oncolytic Vesicular Stomatitis Virus Encoding CXCL9.

Elizabeth C Eckert, Rebecca A Nace, Jason M Tonne, Laura Evgin, Richard G Vile, Stephen J Russell

Open access · goldAbstract read
In one paragraph

Article in Molecular therapy oncolytics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

30 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
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  6. Oncolytic viruses: advanced strategies in cancer therapy.Signal transduction and targeted therapy · 2026
    Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Targeting cytokine and chemokine signaling pathways for cancer therapy.Signal transduction and targeted therapy · 2024
    Review
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  18. Article
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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

6 authors at 1 institution in 1 country.

Elizabeth C EckertDepartment of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Rebecca A NaceDepartment of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Jason M TonneDepartment of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Laura EvginDepartment of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Richard G VileDepartment of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Stephen J RussellDepartment of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Mayo Clinic in Arizona · US

Funding

Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement - Dr. Timothy Curry)UL1TR002377 · NCATS · MAYO CLINIC ROCHESTER · PI VESNA D GAROVIC · 2017 to 2026
$78.4M
NRSA Training CoreTL1TR002380 · NCATS · MAYO CLINIC ROCHESTER · PI Felicity T. B. Enders, ANTHONY John WINDEBANK · 2017 to 2026
$6.0M
NCATS NIH HHS TL1 TR002380NCATS NIH HHS UL1 TR002377
6 · The paper itself

Abstract

Genetically modified vesicular stomatitis virus (VSV) is an attractive agent for cancer treatment due to rapid intratumoral replication and observed clinical responses. Although VSV selectively kills malignant cells and can boost antitumor immunity, limited induction of intratumoral immune infiltration remains a barrier to efficacy in some cancer models. Here we engineered the oncolytic VSV platform to encode the T cell chemokine CXCL9, which is known to mediate the recruitment of activated CD8

Indexed as

chemokinechemokine gradientCXCL9oncolytic virotherapyvesicular stomatitis virus

Identifiers

PMID31930167
PMCPMC6951834
OpenAlexW2995385016

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.