Evidence map›Paper›PMID 37925483›Full record

ArticleScientific reports2023

MAPK signaling pathway-based glioma subtypes, machine-learning risk model, and key hub proteins identification.

Hengrui Liu, Tao Tang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed
22.7field-weighted citation impact, top 1% 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

76 citing papers in PubMed, 88 citations in OpenAlex.

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  16. Regulatory roles of MKP7/DUSP16 in cancer.Medical oncology (Northwood, London, England) · 2025
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16 more citing papers are in PubMed but not listed here.

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

2 authors at 2 institutions in 1 country.

Hengrui LiuXinkaiyuan Pharmaceuticals, Beijing, China.
Tao TangDepartment of Molecular Diagnostics, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China. tangtao@sysucc.org.cn.
Guangzhou Regenerative Medicine and Health Guangdong Laboratory · CNSun Yat-sen University Cancer Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An early diagnosis and precise prognosis are critical for the treatment of glioma. The mitogen‑activated protein kinase (MAPK) signaling pathway potentially affects glioma, but the exploration of the clinical values of the pathway remains lacking. We accessed data from TCGA, GTEx, CGGA, etc. Up-regulated MAPK signaling pathway genes in glioma were identified and used to cluster the glioma subtypes using consensus clustering. The subtype differences in survival, cancer stemness, and the immune microenvironment were analyzed. A prognostic model was trained with the identified genes using the LASSO method and was validated with three external cohorts. The correlations between the risk model and cancer-associated signatures in cancer were analyzed. Key hub genes of the gene set were identified by hub gene analysis and survival analysis. 47% of the MAPK signaling pathway genes were overexpressed in glioma. Subtypes based on these genes were distinguished in survival, cancer stemness, and the immune microenvironment. A risk model was calculated with high confidence in the prediction of overall survival and was correlated with multiple cancer-associated signatures. 12 hub genes were identified and 8 of them were associated with survival. The MAPK signaling pathway was overexpressed in glioma with prognostic value.

Indexed as

GliomaMitogen-Activated Protein KinasesCluster AnalysisHumansMachine LearningPrognosisSignal TransductionTumor MicroenvironmentMitogen-Activated Protein Kinases

Identifiers

PMID37925483
PMCPMC10625624
OpenAlexW4388340888

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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.