Evidence map›Paper›PMID 27323413›Full record

ArticleOncotarget2016

Prognostic value and their clinical implication of 89-gene signature in glioma.

Muhammad Shahid, Kyoung Min Cho, Minh Nam Nguyen, Tae Gyu Choi, Yong Hwa Jo, Saurav Nath Aryal, Ji Youn Yoo, Hyeong Rok Yun, Jae Woong Lee, Young Gyu Eun and 6 more

Abstract readValidation Study
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Biochemistry and biophysics reports · 2025
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  3. Review
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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

16 authors.

Muhammad ShahidDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Kyoung Min ChoDepartment of Internal Medicine, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Minh Nam NguyenDepartment of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.
Tae Gyu ChoiDepartment of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.
Yong Hwa JoDepartment of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.
Saurav Nath AryalDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Ji Youn YooDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Hyeong Rok YunDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Jae Woong LeeDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Young Gyu EunDepartment of Otolaryngology-Head and Neck Surgery, Kyung Hee University Medical Center, Seoul, Republic of Korea.
Ju-Seog LeeDepartment of Systems Biology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Insug KangDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Joohun HaDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Hwi-Joong YoonDepartment of Internal Medicine, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Si-Young KimDepartment of Internal Medicine, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Sung Soo KimDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gliomas are the most common and aggressive primary tumors in adults. The current approaches, such as histological classification and molecular genetics, have limitation in prediction of individual therapeutic outcomes due to heterogeneity within the tumor groups. Recent studies have proposed several gene signatures to predict glioma's prognosis. However, most of the gene expression profiling studies have been performed on relatively small number of patients and combined probes from diverse microarray chips. Here, we identified prognostic 89 common genes from diverse microarray chips. The 89-gene signature classified patients into good and bad prognostic groups which differed in the overall survival significantly, reflecting the biological characteristics and heterogeneity. The robustness and accuracy of the gene signature as an independent prognostic factor was validated in three microarray and one RNA-seq data sets independently. By incorporating into histological classification and molecular marker, the 89-gene signature could further stratify patients with 1p/19q co-deletion and IDH1 mutation. Additionally, subset analyses suggested that the 89-gene signature could predict patients who would benefit from adjuvant chemotherapy. Conclusively, we propose that the 89-gene signature would have an independent and accurate prognostic value for clinical use. This study also offers opportunities for novel targeted treatment of individual patients.

Indexed as

TranscriptomeAdolescentAdultAgedAged, 80 and overBiomarkers, TumorBrain NeoplasmsChildFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGliomaHumansMaleMicroarray AnalysisMiddle AgedBiomarkers, Tumorchemosensitivitygene expression profilegliomaprognosis

Identifiers

PMID27323413
PMCPMC5239472

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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.