Evidence map›Paper›PMID 25546404›Full record

ArticlePloS one2014

Subclassification of newly diagnosed glioblastomas through an immunohistochemical approach.

Siobhan Conroy, Frank A E Kruyt, Justin V Joseph, Veerakumar Balasubramaniyan, Krishna P Bhat, Michiel Wagemakers, Roelien H Enting, Annemiek M E Walenkamp, Wilfred F A den Dunnen

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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

9 authors.

Siobhan ConroyDepartment of Pathology and Medical Biology (Division of Pathology), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Frank A E KruytDepartment of Medical Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Justin V JosephDepartment of Medical Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Veerakumar BalasubramaniyanDepartment of Neuroscience, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Krishna P BhatDepartment of Pathology, University of Texas, MD Anderson Cancer Center, Houston, Texas, United States of America.
Michiel WagemakersDepartment of Neurosurgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Roelien H EntingDepartment of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Annemiek M E WalenkampDepartment of Medical Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Wilfred F A den DunnenDepartment of Pathology and Medical Biology (Division of Pathology), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular signatures in Glioblastoma (GBM) have been described that correlate with clinical outcome and response to therapy. The Proneural (PN) and Mesenchymal (MES) signatures have been identified most consistently, but others including Classical (CLAS) have also been reported. The molecular signatures have been detected by array techniques at RNA and DNA level, but these methods are costly and cannot take into account individual contributions of different cells within a tumor. Therefore, the aim of this study was to investigate whether subclasses of newly diagnosed GBMs could be assessed and assigned by application of standard pathology laboratory procedures. 123 newly diagnosed GBMs were analyzed for the tumor cell expression of 23 pre-identified proteins and EGFR amplification, together allowing for the subclassification of 65% of the tumors. Immunohistochemistry (IHC)-based profiling was found to be analogous to transcription-based profiling using a 9-gene transcriptional signature for PN and MES subclasses. Based on these data a novel, minimal IHC-based scheme for subclass assignment for GBMs is proposed. Positive staining for IDH1R132H can be used for PN subclass assignment, high EGFR expression for the CLAS subtype and a combined high expression of PTEN, VIM and/or YKL40 for the MES subclass. The application of the proposed scheme was evaluated in an independent tumor set, which resulted in similar subclass assignment rates as those observed in the training set. The IHC-based subclassification scheme proposed in this study therefore could provide very useful in future studies for stratification of individual patient samples.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorErbB ReceptorsFemaleGene Expression ProfilingGlioblastomaHumansImmunohistochemistryMaleMiddle AgedTranscriptomeBiomarkers, TumorErbB Receptors

Identifiers

PMID25546404
PMCPMC4278713

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Registered trials

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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.