Evidence map›Paper›PMID 29876930›Full record

ArticleThe Journal of pathology2018

EnLIGHTenment of tumor vessel normalization and immunotherapy in glioblastoma.

Lucas Treps

Open access · bronzeAbstract readComment
PubMed Publisher
In one paragraph

Article in The Journal of pathology, 2018. 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
1.3field-weighted citation impact, top 20% 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, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Lucas TrepsLaboratory of Angiogenesis and Vascular Metabolism, Department of Oncology and Leuven Cancer Institute (LKI), KU Leuven, Leuven, Belgium.ORCID 0000-0003-0735-9000
VIB-KU Leuven Center for Cancer Biology · BE

Funding

Fondation Bettencourt SchuellerH2020 Marie Skłodowska-Curie Actions
6 · The paper itself

Abstract

Glioblastoma multiforme (GBM) is a highly vascularized and aggressive brain tumor. Despite aggressive standard care, GBM remains predominantly fatal; hence, new innovative therapies are required. Recent research published in the Journal of Pathology has identified the CGKRK peptide as a promising tool with which to specifically target the tumor vasculature from high-grade glioma. This tumor vessel-homing peptide was fused to the tumor necrosis factor superfamily member LIGHT/TNFSF14, and injected intravenously into murine orthotopic GBM models. After treatment, the tumor vasculature appeared to be less abnormal, with normalized features such as increased endothelial barrier integrity, pericyte contractility, and tumor perfusion. Moreover, CGKRK-LIGHT induced the appearance of high endothelial venules (HEVs), which are specialized structures that play a role in lymphocyte trafficking and have been shown to increase T-cell infiltration in solid tumors. Combining CGKRK-LIGHT with anti-angiogenic and immune checkpoint blockade treatments boosted HEV induction and cytotoxic T-cell infiltration, leading to a reduction in tumor burden. In this Commentary, I highlight the therapeutic opportunities provided by and the current limitations of LIGHT-vascular targeting peptide as a new approach to target GBM and enhance tumor vessel delivery and immunotherapy efficacy. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Indexed as

Brain NeoplasmsGlioblastomaAnimalsDisease Models, AnimalHumansImmunotherapyMiceTumor Necrosis Factor Ligand Superfamily Member 14VenulesTnfsf14 protein, mouseTumor Necrosis Factor Ligand Superfamily Member 14angiogenesisglioblastomaHEVhigh endothelial venulesimmunotherapyLIGHTnormalizationpericyteTNFSF14vascular targeting

Identifiers

PMID29876930
OpenAlexW2807488565

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.