Evidence map›Paper›PMID 26699864›Full record

ArticleActa neuropathologica communications2015

PI3 kinase mutations and mutational load as poor prognostic markers in diffuse glioma patients.

Kaspar Draaisma, Maarten M J Wijnenga, Bas Weenink, Ya Gao, Marcel Smid, P Robe, Martin J van den Bent, Pim J French

Open access · goldAbstract read
In one paragraph

Article in Acta neuropathologica communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

35 citing papers in PubMed, 66 citations in OpenAlex.

  1. Review
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  5. [Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
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  15. GNIFdb: a neoantigen intrinsic feature database for glioma.Database : the journal of biological databases and curation · 2022
    Article
  16. T-cell Receptor Therapy Targeting Mutant Capicua Transcriptional Repressor in Experimental Gliomas.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022
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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 at 3 institutions in 2 countries.

Kaspar DraaismaDepartment of Neurology, Erasmus MC, Room Be 430A, POBox 2040, 3000 CA, Rotterdam, The Netherlands.
Maarten M J WijnengaDepartment of Neurology, Erasmus MC, Room Be 430A, POBox 2040, 3000 CA, Rotterdam, The Netherlands.
Bas WeeninkDepartment of Neurology, Erasmus MC, Room Be 430A, POBox 2040, 3000 CA, Rotterdam, The Netherlands.
Ya GaoDepartment of Neurology, Erasmus MC, Room Be 430A, POBox 2040, 3000 CA, Rotterdam, The Netherlands.
Marcel SmidDepartment of Medical Oncology, Erasmus MC, Rotterdam, The Netherlands.
P RobeDepartment of Neurosurgery, UMC Utrecht, Utrecht, Netherlands.
Martin J van den BentDepartment of Neurology, Erasmus MC, Room Be 430A, POBox 2040, 3000 CA, Rotterdam, The Netherlands.
Pim J FrenchDepartment of Neurology, Erasmus MC, Room Be 430A, POBox 2040, 3000 CA, Rotterdam, The Netherlands. p.french@erasmusmc.nl.
Erasmus University Rotterdam · NLErasmus MC · NLUniversity Medical Center Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRecent advances in molecular diagnostics allow diffuse gliomas to be classified based on their genetic changes into distinct prognostic subtypes. However, a systematic analysis of all molecular markers has thus far not been performed; most classification schemes use a predefined and select set of genes/molecular markers. Here, we have analysed the TCGA dataset (combined glioblastoma (GBM) and lower grade glioma (LGG) datasets) to identify all prognostic genetic markers in diffuse gliomas in order to generate a comprehensive classification scheme.

resultsOf the molecular markers investigated (all genes mutated at a population frequency >1.7 % and frequent chromosomal imbalances) in the entire glioma dataset, 57 were significantly associated with overall survival. Of these, IDH1 or IDH2 mutations are associated with lowest hazard ratio, which confirms IDH as the most important prognostic marker in diffuse gliomas. Subsequent subgroup analysis largely confirms many of the currently used molecular classification schemes for diffuse gliomas (ATRX or TP53 mutations, 1p19q codeletion). Our analysis also identified PI3-kinase mutations as markers of poor prognosis in IDH-mutated + ATRX/TP53 mutated diffuse gliomas, median survival 3.7 v. 6.3 years (P = 0.02, Hazard rate (HR) 2.93, 95 % confidence interval (CI) 1.16 - 7.38). PI3-kinase mutations were also prognostic in two independent datasets. In our analysis, no additional molecular markers were identified that further refine the molecular classification of diffuse gliomas. Interestingly, these molecular classifiers do not fully explain the variability in survival observed for diffuse glioma patients. We demonstrate that tumor grade remains an important prognostic factor for overall survival in diffuse gliomas, even within molecular glioma subtypes. Tumor grade was correlated with the mutational load (the number of non-silent mutations) of the tumor: grade II diffuse gliomas harbour fewer genetic changes than grade III or IV, even within defined molecular subtypes (e.g. ATRX mutated diffuse gliomas).

conclusionWe have identified PI3K mutations as novel prognostic markers in gliomas. We also demonstrate that the mutational load is associated with tumor grade. The increase in mutational load may partially explain the increased aggressiveness of higher grade diffuse gliomas when a subset of the affected genes actively contributes to gliomagenesis and/or progression.

Indexed as

AdultAgedAge FactorsBiomarkers, TumorBrain NeoplasmsDNA HelicasesDNA Mutational AnalysisErbB ReceptorsFemaleGliomaHumansIsocitrate DehydrogenaseMaleMiddle AgedMutationNuclear ProteinsATRX protein, humanBiomarkers, TumorDNA HelicasesEGFR protein, humanErbB ReceptorsIsocitrate DehydrogenaseNuclear ProteinsPhosphatidylinositol 3-KinasesTumor Suppressor Protein p53X-linked Nuclear Protein

Identifiers

PMID26699864
PMCPMC4690424
OpenAlexW2203070891

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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.