Evidence map›Paper›PMID 19300524›Full record

ArticleJournal of biomedicine & biotechnology2009

Molecularly characterised xenograft tumour mouse models: valuable tools for evaluation of new therapeutic strategies for secondary liver cancers.

Daniela Mischek, Ralf Steinborn, Helga Petznek, Christoph Bichler, Kurt Zatloukal, Michael Stürzl, Walter H Günzburg, Christine Hohenadl

Abstract read
In one paragraph

Article in Journal of biomedicine & biotechnology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Identification of Biomarkers of Necrosis in Xenografts Using Imaging Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2016
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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

8 authors.

Daniela MischekDepartment of Pathobiology, Institute of Virology, University of Veterinary Medicine, Vienna, Austria.
Ralf Steinborn
Helga Petznek
Christoph Bichler
Kurt Zatloukal
Michael Stürzl
Walter H Günzburg
Christine Hohenadl

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To develop and evaluate new therapeutic strategies for the treatment of human cancers, well-characterised preclinical model systems are a prerequisite. To this aim, we have established xenotransplantation mouse models and corresponding cell cultures from surgically obtained secondary human liver tumours. Established xenograft tumours were patho- and immunohistologically characterised, and expression levels of cancer-relevant genes were quantified in paired original and xenograft tumours and the derivative cell cultures applying RT-PCR-based array technology. Most of the characteristic morphological and immunohistochemical features of the original tumours were shown to be maintained. No differences were found concerning expression of genes involved in cell cycle regulation and oncogenesis. Interestingly, cytokine and matrix metalloproteinase encoding genes appeared to be expressed differentially. Thus, the established models are closely reflecting pathohistological and molecular characteristics of the selected human tumours and may therefore provide useful tools for preclinical analyses of new antitumour strategies in vivo.

Indexed as

Gene Expression Regulation, NeoplasticXenograft Model Antitumor AssaysAdenocarcinomaAgedAnimalsFemaleHumansImmunohistochemistryLiver NeoplasmsMaleMiceMice, SCIDMiddle AgedNeoplasm TransplantationReverse Transcriptase Polymerase Chain ReactionStatistics, Nonparametric

Identifiers

PMID19300524
PMCPMC2655652

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.