Evidence map›Paper›PMID 35194922›Full record

ArticleJournal of cellular and molecular medicine2022

Top-down stepwise refinement identifies coding and noncoding RNA-associated epigenetic regulatory maps in malignant glioma.

Yutao Huang, Xiangyu Gao, Erwan Yang, Kangyi Yue, Yuan Cao, Boyan Zhao, Haofuzi Zhang, Shuhui Dai, Lei Zhang, Peng Luo and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 37% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. 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

11 authors at 1 institution in 1 country.

Yutao HuangDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.ORCID 0000-0002-2433-8183
Xiangyu GaoDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Erwan YangDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Kangyi YueDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Yuan CaoDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Boyan ZhaoDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Haofuzi ZhangDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Shuhui DaiDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Lei ZhangDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Peng LuoDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.ORCID 0000-0003-0746-939X
Xiaofan JiangDepartment of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Xijing Hospital · CN

Funding

National Natural Science Foundation of China 81671303National Natural Science Foundation of China 81771322National Natural Science Foundation of China 81871023Youth Talent Lifting Project 17-JCJQ-QT-037
6 · The paper itself

Abstract

With the emergence of the molecular era and retreat of the histology epoch in malignant glioma, it is becoming increasingly necessary to research diagnostic/prognostic/therapeutic biomarkers and their related regulatory mechanisms. While accumulating studies have investigated coding gene-associated biomarkers in malignant glioma, research on comprehensive coding and noncoding RNA-associated biomarkers is lacking. Furthermore, few studies have illustrated the cross-talk signalling pathways among these biomarkers and mechanisms in detail. Here, we identified DEGs and ceRNA networks in malignant glioma and then constructed Cox/Lasso regression models to further identify the most valuable genes through stepwise refinement. Top-down comprehensive integrated analysis, including functional enrichment, SNV, immune infiltration, transcription factor binding site, and molecular docking analyses, further revealed the regulatory maps among these genes. The results revealed a novel and accurate model (AUC of 0.91 and C-index of 0.84 in the whole malignant gliomas, AUC of 0.90 and C-index of 0.86 in LGG, and AUC of 0.75 and C-index of 0.69 in GBM) that includes twelve ncRNAs, 1 miRNA and 6 coding genes. Stepwise logical reasoning based on top-down comprehensive integrated analysis and references revealed cross-talk signalling pathways among these genes that were correlated with the circadian rhythm, tumour immune microenvironment and cellular senescence pathways. In conclusion, our work reveals a novel model where the newly identified biomarkers may contribute to a precise diagnosis/prognosis and subclassification of malignant glioma, and the identified cross-talk signalling pathways would help to illustrate the noncoding RNA-associated epigenetic regulatory mechanisms of glioma tumorigenesis and aid in targeted therapy.

Indexed as

Brain NeoplasmsGliomaMicroRNAsRNA, Long NoncodingBiomarkers, TumorEpigenesis, GeneticGene Expression Regulation, NeoplasticHumansMolecular Docking SimulationTumor MicroenvironmentBiomarkers, TumorMicroRNAsRNA, Long NoncodingbiomarkerCox-Lasso regressioncross-talk signallingepigenetic regulationintegrative analysismalignant gliomanoncoding RNA

Identifiers

PMID35194922
PMCPMC8995455
OpenAlexW4213165228

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.