Evidence map›Paper›PMID 33449451›Full record

ArticleJournal of cellular and molecular medicine2021

Construction of co-expression modules related to survival by WGCNA and identification of potential prognostic biomarkers in glioblastoma.

Jing Zhou, Hao Guo, Likun Liu, Shulan Hao, Zhi Guo, Fupeng Zhang, Yu Gao, Zhi Wang, Weiwei Zhang

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
7.1field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.

  1. Pooled it
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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 at 2 institutions in 1 country.

Jing ZhouDepartment of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China.ORCID 0000-0002-8420-5462
Hao GuoDepartment of Anesthesiology, Shanxi Provincial People's Hospital, Taiyuan, China.
Likun LiuDepartment of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China.
Shulan HaoDepartment of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China.
Zhi GuoDepartment of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China.
Fupeng ZhangDepartment of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China.
Yu GaoDepartment of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China.
Zhi WangDepartment of Anesthesiology, Shanxi Provincial People's Hospital, Taiyuan, China.
Weiwei ZhangDepartment of Anesthesiology, Shanxi Provincial People's Hospital, Taiyuan, China.
Shanxi Province Hospital of Traditional Chinese Medicine · CNShanxi Medical University · CN

Funding

the cultivation project of Science and Technology Innovation Ability of Shanxi University of Chinese Medicine 2019PY-017the National Natural Science Foundation of China 81904183the Natural Science Foundation of Shanxi Province 201801D121300the Project of Health Commission of Shanxi Province 2018078the Project of Shanxi Province Academy of Traditional Chinese Medicine 201901
6 · The paper itself

Abstract

Glioblastoma (GBM) is a malignant brain tumour with poor prognosis. The potential pathogenesis and therapeutic target are still need to be explored. Herein, TCGA expression profile data and clinical information were downloaded, and the WGCNA was conducted. Hub genes which closely related to poor prognosis of GBM were obtained. Further, the relationship between the genes of interest and prognosis of GBM, and immune microenvironment were analysed. Patients from TCGA were divided into high- and low-risk group. WGCNA was applied to the high- and low-risk group and the black module with the lowest preservation was identified which could distinguish the prognosis level of these two groups. The top 10 hub genes which were closely related to poor prognosis of patients were obtained. GO analysis showed the biological process of these genes mainly enriched in: Cell cycle, Progesterone-mediated oocyte maturation and Oocyte meiosis. CDCA5 and CDCA8 were screened out as the genes of interest. We found that their expression levels were closely related to overall survival. The difference analysis resulted from the TCGA database proved both CDCA5 and CDCA8 were highly expressed in GBM. After transfection of U87-MG cells with small interfering RNA, it revealed that knockdown of the CDCA5 and CDCA8 could influence the biological behaviours of proliferation, clonogenicity and apoptosis of GBM cells. Then, single-gene analysis was performed. CDCA5 and CDCA8 both had good correlations with genes that regulate cell cycle in the p53 signalling pathway. Moreover, it revealed that high amplification of CDCA5 was correlated with CD8

Indexed as

Biomarkers, TumorApoptosisBrain NeoplasmsComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksGlioblastomaHumansPrognosisReproducibility of ResultsTranscriptomeBiomarkers, Tumorcell cycleglioblastomahub genethe Cancer Genome Atlas (TCGA)Weighted Gene Co-expression Network Analysis (WGCNA)

Identifiers

PMID33449451
PMCPMC7875936
OpenAlexW3121425150

What OpenQuestion holds

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LicenceCC BY
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.