Evidence map›Paper›PMID 27835574›Full record

ArticleOncotarget2016

Identification of a seven-miRNA signature as prognostic biomarker for lung squamous cell carcinoma.

Xujie Gao, Yupeng Wu, Wenwen Yu, Hui Li

Abstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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  7. Prognostic gene biomarker identification in liver cancer by data mining.American journal of translational research · 2021
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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

4 authors.

Xujie GaoDepartment of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Yupeng WuDepartment of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Wenwen YuDepartment of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Hui LiDepartment of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpecific biomarkers for outcome prediction of lung squamous cell carcinoma (LUSC) are still lacking. This study assessed the prognostic value of differentially expressed miRNAs of LUSC patients.

resultsTwelve of the 133 most significantly altered miRNAs were associated with overall survival (OS) across different clinical subclasses of the Cancer Genome Atlas (TCGA) LUSC cohort. A linear prognostic model of seven miRNAs was developed to divide patients into high- and low-risk groups. Patients assigned to the high-risk group exhibited poor OS compared with patients in the low-risk group, which was further validated in the validation cohort and entire LUSC cohort.

methodsMiRNA expression profiles with clinical information of 447 LUSC patients were obtained from TCGA. Most significantly altered miRNAs were identified between tumor and normal samples. Using survival analysis and supervised principal components method, a seven-miRNA signature for prediction of OS of LUSC patients was established. Survival receiver operating characteristic (ROC) analysis was used to assess the performance of survival prediction. The biological relevance of predicted miRNA targets was also analyzed using bioinformatics method.

conclusionsThe current study suggests that seven-miRNA signature may have clinical implications in the outcome prediction of LUSC.

Indexed as

TranscriptomeAgedArea Under CurveBiomarkers, TumorCarcinoma, Squamous CellDatabases, GeneticFemaleGene Expression ProfilingGenetic Predisposition to DiseaseHumansKaplan-Meier EstimateLinear ModelsLung NeoplasmsMaleMicroRNAsMiddle AgedBiomarkers, TumorMicroRNAslung squamous cell carcinomamicroRNAprognostic marker

Identifiers

PMID27835574
PMCPMC5348421

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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.