Evidence map›Paper›PMID 33167941›Full record

ArticleBMC cancer2020

A nuclear transport-related gene signature combined with IDH mutation and 1p/19q codeletion better predicts the prognosis of glioma patients.

Zheng Zhu, Yang Lan, Lihong Wang, Jia Ge, Jiao Wang, Feng Liu, Zhicheng He, Hua Zhang, Min Luo, Dandan Lin and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 45% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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  4. Review
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

13 authors at 2 institutions in 1 country.

Zheng ZhuInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Yang LanInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Lihong WangInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Jia GeInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Jiao WangInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Feng LiuInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Zhicheng HeInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Hua ZhangInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Min LuoInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Dandan LinInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Yaoyao TanInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Yuanyuan XuInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China.
Tao LuoInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, 400038, China. lty3169@163.com.
Southwest Hospital · CNArmy Medical University · CN

Funding

the Chongqing Basic Research Project cstc2016jcyjA2194the National Natural Science Foundation of China 81602196the National Natural Science Foundation of China 81702456
6 · The paper itself

Abstract

backgroundThe nuclear transport system has been proposed to be indispensable for cell proliferation and invasion in cancers. Prognostic biomarkers and molecular targets in nuclear transport systems have been developed. However, no systematic analysis of genes related to nuclear transport in gliomas has been performed. An integrated prognostic classification involving mutation and nuclear transport gene signatures has not yet been explored.

methodsIn the present study, we analyzed gliomas from a training cohort (TCGA dataset, n = 660) and validation cohort (CGGA dataset, n = 668) to develop a prognostic nuclear transport gene signature and generate an integrated classification system. Gene set enrichment analysis (GSEA) showed that glioblastoma (GBM) was mainly enriched in nuclear transport progress compared to lower-grade glioma (LGG). Then, we developed a nuclear transport risk score (NTRS) for gliomas with a training cohort. NTRS was significantly correlated with clinical and genetic characteristics, including grade, age, histology, IDH status and 1p/19q codeletion, in the training and validation cohorts.

resultsSurvival analysis revealed that patients with a higher NTRS exhibited shorter overall survival. NTRS showed better prognostic value compared to classical molecular markers, including IDH status and 1p/19q codeletion. Furthermore, univariate and multivariate analyses indicated that NTRS was an independent prognostic factor for gliomas. Enrichment map and Gene Ontology analysis demonstrated that signaling pathways related to the cell cycle were enriched in the NTRS

conclusionsNTRS is associated with poor outcomes and could be an independent prognostic marker in diffuse gliomas. Prognostic classification combined with IDH mutation, 1p/19q codeletion and NTRS could better predict the survival of glioma patients.

Indexed as

Chromosome DeletionMutationTranscriptomeActive Transport, Cell NucleusAdolescentAdultAgedBiomarkers, TumorBrain NeoplasmsChildChromosomes, Human, Pair 1Chromosomes, Human, Pair 19FemaleFollow-Up StudiesGene Expression Regulation, NeoplasticGliomaBiomarkers, TumorIsocitrate DehydrogenaseCGGAClassificationGene signatureGliomasNuclear transportPrognosisTCGA

Identifiers

PMID33167941
PMCPMC7654069
OpenAlexW3101066988

What OpenQuestion holds

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LicenceCC BY
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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.