Evidence map›Paper›PMID 22074483›Full record

ArticleRadiation oncology (London, England)2011

MiRNA expression patterns predict survival in glioblastoma.

Maximilian Niyazi, Franz Zehentmayr, Olivier M Niemöller, Sabina Eigenbrod, Hans Kretzschmar, Klaus Schulze-Osthoff, Jörg-Christian Tonn, Mike Atkinson, Simone Mörtl, Claus Belka

Abstract read
In one paragraph

Article in Radiation oncology (London, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
–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

41 citing papers in PubMed.

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  12. Genetic secrets of long-term glioblastoma survivors.Bosnian journal of basic medical sciences · 2019
    Review
  13. Article
  14. MiR-28-5p promotes human glioblastoma cell growth through inactivation of FOXO1.International journal of clinical and experimental pathology · 2019
    Article
  15. Article
  16. Review
  17. Review
  18. The Clinical Significance of OFrontiers in neurology · 2018
    Article
  19. Article
  20. Review
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

10 authors.

Maximilian NiyaziDepartment of Radiation Oncology, Ludwig-Maximilians-University Munich, Marchioninistr, 15, 81377 Munich, Germany.
Franz Zehentmayr
Olivier M Niemöller
Sabina Eigenbrod
Hans Kretzschmar
Klaus Schulze-Osthoff
Jörg-Christian Tonn
Mike Atkinson
Simone Mörtl
Claus Belka

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn order to define new prognostic subgroups in patients with glioblastoma a miRNA screen (> 1000 miRNAs) from paraffin tissues followed by a bio-mathematical analysis was performed.

methods35 glioblastoma patients treated between 7/2005 - 8/2008 at a single institution with surgery and postoperative radio(chemo)therapy were included in this retrospective analysis. For microarray analysis the febit biochip "Geniom® Biochip MPEA homo-sapiens" was used. Total RNA was isolated from FFPE tissue sections and 1100 different miRNAs were analyzed.

resultsIt was possible to define a distinct miRNA expression pattern allowing for a separation of distinct prognostic subgroups. The defined miRNA pattern was significantly associated with early death versus long-term survival (split at 450 days) (p = 0.01). The pattern and the prognostic power were both independent of the MGMT status.

conclusionsAt present, this is the first dataset defining a prognostic role of miRNA expression patterns in patients with glioblastoma. Having defined such a pattern, a prospective validation of this observation is required.

Indexed as

Biomarkers, TumorBrain NeoplasmsCluster AnalysisDNA MethylationDNA Modification MethylasesDNA Repair EnzymesFemaleGene Expression ProfilingGlioblastomaHumansKaplan-Meier EstimateMaleMicroRNAsMiddle AgedOligonucleotide Array Sequence AnalysisPrognosisBiomarkers, TumorDNA Modification MethylasesDNA Repair EnzymesMGMT protein, humanMicroRNAsTumor Suppressor Proteins

Identifiers

PMID22074483
PMCPMC3235977

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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.