Evidence map›Paper›PMID 21989091›Full record

ArticleJournal of translational medicine2011

Bacterial glucuronidase as general marker for oncolytic virotherapy or other biological therapies.

Michael Hess, Jochen Stritzker, Barbara Härtl, Julia B Sturm, Ivaylo Gentschev, Aladar A Szalay

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

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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.

Michael HessDepartment of Biochemistry, Biocenter, University of Würzburg, Würzburg, Germany.
Jochen Stritzker
Barbara Härtl
Julia B Sturm
Ivaylo Gentschev
Aladar A Szalay
University of Würzburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOncolytic viral tumor therapy is an emerging field in the fight against cancer with rising numbers of clinical trials and the first clinically approved product (Adenovirus for the treatment of Head and Neck Cancer in China) in this field. Yet, until recently no general (bio)marker or reporter gene was described that could be used to evaluate successful tumor colonization and/or transgene expression in other biological therapies.

methodsHere, a bacterial glucuronidase (GusA) encoded by biological therapeutics (e.g. oncolytic viruses) was used as reporter system.

resultsUsing fluorogenic probes that were specifically activated by glucuronidase we could show 1) preferential activation in tumors, 2) renal excretion of the activated fluorescent compounds and 3) reproducible detection of GusA in the serum of oncolytic vaccinia virus treated, tumor bearing mice in several tumor models. Time course studies revealed that reliable differentiation between tumor bearing and healthy mice can be done as early as 9 days post injection of the virus. Regarding the sensitivity of the newly developed assay system, we could show that a single infected tumor cell could be reliably detected in this assay.

conclusionGusA therefore has the potential to be used as a general marker in the preclinical and clinical evaluation of (novel) biological therapies as well as being useful for the detection of rare cells such as circulating tumor cells.

Indexed as

Oncolytic VirotherapyAnimalsBacteriaBiomarkersCell Line, TumorFluorescent DyesGlucuronidaseHumansMiceNeoplasmsSubstrate SpecificityTime FactorsVaccinia virusBiomarkersFluorescent DyesGlucuronidase

Identifiers

PMID21989091
PMCPMC3207905
OpenAlexW2151343142

What OpenQuestion holds

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LicenceCC BY
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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.