Evidence map›Paper›PMID 34815691›Full record

ArticleInternational journal of general medicine2021

Transcription Factor Signatures May Predict the Prognosis and Status of the Immune Microenvironment of Primary Lower-Grade Gliomas.

Peidong Liu, Ruojie Wu, Jinhao Zhang, Yiming Zhang, Chen Zhang, Lei Chen, Shengping Yu, Xuejun Yang

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 50% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 1 institution in 1 country.

Peidong Liu *Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.ORCID 0000-0002-3869-2167
Ruojie Wu *Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.
Jinhao Zhang *Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.
Yiming ZhangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.
Chen ZhangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.
Lei ChenDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.
Shengping YuDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.
Xuejun YangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, People's Republic of China.
Tianjin Medical University General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTranscription factor (TF) in glioma, including proliferation, invasion/migration, and tumor microenvironment, has been receiving increasing attention. However, there are still no systematical analyses based on global TF. Herein, using global TF target gene sets, we comprehensively investigated their relationship with prognosis and potential biological effect in lower-grade glioma (LGG). We aimed to develop a less-biased prognostic model and provide new insight for personalized management of this disease.

methodsTF target gene sets were collected from MSigDB and GRID database followed by ssGSEA calculating normalized enrichment score. Comprehensive survival analysis was combined with Kaplan-Meier and Cox algorithms. Consensus cluster and lasso regression were performed to develop prognostic signatures with validation of ROC and independent external cohort. Approaches of

resultsFourteen TFs were significantly screened based on survival. Patients were classified into 2 prognosis-related clusters based on 14-TFs features. The function of differentially expressed TF target genes between Cluster1/2 was enriched mostly on glioma invasion/migration. The prognostic model was trained by 6 out of 14-TFs followed by generating risk-score as an independent prognostic indicator. We found differences between the high/low-risk group in TMB and the immune microenvironment, where the high-risk group represented "hot-tumor". Besides, 6-TFs were correlated with m6A regulation genes.

conclusionOur findings suggested that the 6-TFs model could be used to predict prognosis and predict the status of the immune microenvironment in LGG.

Indexed as

lower-grade gliomaprognostic modelrisk signaturetranscription factor target gene settumor immune microenvironment

Identifiers

PMID34815691
PMCPMC8605870
OpenAlexW3212474904

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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.