Evidence map›Paper›PMID 28331188›Full record

ArticleScientific reports2017

Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma.

Zhi-Li Zhang, Li-Jing Zhao, Liang Chai, Shui-Hong Zhou, Feng Wang, Yan Wei, Ya-Ping Xu, Peng Zhao

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
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

25 citing papers in PubMed.

  1. Review
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  5. Identification and Validation of a Novel Prognostic Gene Model for Colorectal Cancer.Computational and mathematical methods in medicine · 2022
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  10. Review
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  20. Tissue Expression Difference between mRNAs and lncRNAs.International journal of molecular sciences · 2018
    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

8 authors.

Zhi-Li ZhangDepartment of otorhinolaryngology,the first affiliated hospital, Zhejiang University School of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China. zhangzhili_zju@126.com.
Li-Jing ZhaoDepartment of otorhinolaryngology, the second affiliated hospital, Zhejiang University school of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China.
Liang ChaiDepartment of otorhinolaryngology,the first affiliated hospital, Zhejiang University School of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China.
Shui-Hong ZhouDepartment of otorhinolaryngology,the first affiliated hospital, Zhejiang University School of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China.
Feng WangDepartment of otorhinolaryngology,the first affiliated hospital, Zhejiang University School of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China.
Yan WeiDepartment of otorhinolaryngology,the first affiliated hospital, Zhejiang University School of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China.
Ya-Ping XuDepartment of otorhinolaryngology,the first affiliated hospital, Zhejiang University School of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China.
Peng ZhaoDepartment of Oncology, The first affiliated hospital,  Zhejiang University School of medicine, 310003, Qingchun Road 79, Hangzhou city, Zhejiang province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dysregulation of mRNAs and long non-coding RNAs (lncRNAs) is one of the most important features of carcinogenesis and cancer development. However, studies integrating the expression of mRNAs and lncRNAs to predict the survival of head and neck squamous cell carcinoma (HNSC) are still limited, hitherto. In current work, we identified survival related mRNAs and lncRNAs in three datasets (TCGA dataset, E-TABM-302, GSE41613). By random forest, seven gene signatures (six mRNAs and lncRNA) were further selected to develop the risk score model. The risk score was significantly associated with survival in both training and testing datasets (E-TABM-302, GSE41613, and E-MTAB-1324). Furthermore, correlation analyses showed that the risk score is independent from clinicopathological features. According to Cox multivariable hazard model and nomogram, the risk score contributes the most to survival than the other clinical information, including gender, age, histologic grade, and alcohol taking. The Gene Set Enrichment Analysis (GSEA) indicates that the risk score is associated with cancer related pathways. In summary, the lncRNA-mRNA based risk score model we developed successfully predicts the survival of 755 HNSC samples in five datasets and two platforms. It is independent from clinical information and performs better than clinical information for prognosis.

Indexed as

Carcinoma, Squamous CellHead and Neck NeoplasmsHumansPrognosisRisk AssessmentRNA, Long NoncodingRNA, MessengerSurvival AnalysisRNA, Long NoncodingRNA, Messenger

Identifiers

PMID28331188
PMCPMC5428014

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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.