Evidence map›Paper›PMID 19038000›Full record

ArticleCancer science2009

Using gene expression profiling to identify a prognostic molecular spectrum in gliomas.

Mitsuaki Shirahata, Shigeyuki Oba, Kyoko Iwao-Koizumi, Sakae Saito, Noriko Ueno, Masashi Oda, Nobuo Hashimoto, Shin Ishii, June A Takahashi, Kikuya Kato

Open access · greenAbstract read
In one paragraph

Article in Cancer science, 2009. 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
1.2field-weighted citation impact, top 21% 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

17 citing papers in PubMed, 26 citations in OpenAlex.

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  13. Proteomic analysis of glioma chemoresistance.Current neuropharmacology · 2012
    Article
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  16. Biology, genetics and imaging of glial cell tumours.The British journal of radiology · 2011
    Review
  17. Article
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 at 3 institutions in 1 country.

Mitsuaki ShirahataDepartment of Neurosurgery, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin Sakyoku, Kyoto, 606-8507, Japan.
Shigeyuki Oba
Kyoko Iwao-Koizumi
Sakae Saito
Noriko Ueno
Masashi Oda
Nobuo Hashimoto
Shin Ishii
June A Takahashi
Kikuya Kato
Kyoto University · JPOsaka International Cancer Institute · JPNara Institute of Science and Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histopathological classification of gliomas is often clinically inadequate due to the diversity of tumors that fall within the same class. The goal of the present study was to identify prognostic molecular features in diffusely infiltrating gliomas using gene expression profiling. We selected 3456 genes expressed in gliomas, including 3012 genes found in a gliomal expressed sequence tag collection. The expression levels of these genes in 152 gliomas (100 glioblastomas, 21 anaplastic astrocytomas, 19 diffuse astrocytomas, and 12 anaplastic oligodendrogliomas) were measured using adapter-tagged competitive polymerase chain reaction, a high-throughput reverse transcription-polymerase chain reaction technique. We applied unsupervised and supervised principal component analyses to elucidate the prognostic molecular features of the gliomas. The gene expression data matrix was significantly correlated with the histological grades, oligo-astro histology, and prognosis. Using 110 gliomas, we constructed a prediction model based on the expression profile of 58 genes, resulting in a scheme that reliably classified the glioblastomas into two distinct prognostic subgroups. The model was then tested with another 42 tissues. Multivariate Cox analysis of the glioblastoma patients using other clinical prognostic factors, including age and the extent of surgical resection, indicated that the gene expression profile was a strong and independent prognostic parameter. The gene expression profiling identified clinically informative prognostic molecular features in astrocytic and oligodendroglial tumors that were more reliable than the traditional histological classification scheme.

Indexed as

Gene Expression ProfilingBrain NeoplasmsGliomaHumansPrognosis

Identifiers

PMID19038000
PMCPMC11159015
OpenAlexW2088032107

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.