Evidence map›Paper›PMID 33230136›Full record

ArticleScientific reports2020

A novel methylation signature predicts radiotherapy sensitivity in glioma.

Yuemei Feng, Guanzhang Li, Zhongfang Shi, Xu Yan, Zhiliang Wang, Haoyu Jiang, Ye Chen, Renpeng Li, You Zhai, Yuanhao Chang and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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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

12 authors.

Yuemei FengDepartment of Pathophysiololgy, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Guanzhang LiDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Zhongfang ShiDepartment of Pathophysiololgy, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Xu YanDepartment of Pathophysiololgy, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Zhiliang WangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Haoyu JiangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Ye ChenDepartment of Pathophysiololgy, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Renpeng LiDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
You ZhaiDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Yuanhao ChangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Wei ZhangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. zhangwei_vincent@126.com.
Fang YuanDepartment of Pathophysiololgy, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China. florayuan@vip.sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma (GBM) is the most common and malignant cancer of the central nervous system, and radiotherapy is widely applied in GBM treatment; however, the sensitivity to radiotherapy varies in different patients. To solve this clinical dilemma, a radiosensitivity prediction signature was constructed in the present study based on genomic methylation. In total, 1044 primary GBM samples with clinical and methylation microarray data were involved in this study. LASSO-COX, GSVA, Kaplan-Meier survival curve analysis, and COX regression were performed for the construction and verification of predictive models. The R programming language was used as the main tool for statistical analysis and graphical work. Via the integration analysis of methylation and the survival data of primary GBM, a novel prognostic and radiosensitivity prediction signature was constructed. This signature was found to be stable in prognosis prediction in the TCGA and CGGA databases. The possible mechanism was also explored, and it was found that this signature is closely related to DNA repair functions. Most importantly, this signature could predict whether GBM patients could benefit from radiotherapy. In summary, a radiosensitivity prediction signature for GBM patients based on five methylated probes was constructed, and presents great potential for clinical application.

Indexed as

DNA MethylationGene Expression Regulation, NeoplasticAdultAgedBrainBrain NeoplasmsDatabases, GeneticDNA RepairFemaleGamma RaysGene Expression ProfilingGlioblastomaHumansKaplan-Meier EstimateMaleMicroarray AnalysisNeoplasm Proteins

Identifiers

PMID33230136
PMCPMC7683673

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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.