Evidence map›Paper›PMID 27105492›Full record

ArticleOncotarget2016

Relapse-related long non-coding RNA signature to improve prognosis prediction of lung adenocarcinoma.

Meng Zhou, Wanying Xu, Xiaolong Yue, Hengqiang Zhao, Zhenzhen Wang, Hongbo Shi, Liang Cheng, Jie Sun

Open access · diamondAbstract 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 69 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 1 pooled it
7.7field-weighted citation impact, top 2% 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

69 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

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  5. Effects of Helicobacter pylori Infection on the Development of Chronic Gastritis.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2023
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9 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Meng ZhouCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Wanying XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Xiaolong YueMedical Oncology Department, Affiliated Tumor Hospital, Harbin Medical University, Harbin 150001, PR China.
Hengqiang ZhaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Zhenzhen WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Hongbo ShiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Liang ChengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Jie SunCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Harbin Medical University · CNThird Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing evidence has highlighted the important roles of dysregulated long non-coding RNA (lncRNA) expression in tumorigenesis, tumor progression and metastasis. However, lncRNA expression patterns and their prognostic value for tumor relapse in lung adenocarcinoma (LUAD) patients have not been systematically elucidated. In this study, we evaluated lncRNA expression profiles by repurposing the publicly available microarray expression profiles from a large cohort of LUAD patients and identified specific lncRNA signature closely associated with tumor relapse in LUAD from significantly altered lncRNAs using the weighted voting algorithm and cross-validation strategy, which was able to discriminate between relapsed and non-relapsed LUAD patients with sensitivity of 90.9% and specificity of 81.8%. From the discovery dataset, we developed a risk score model represented by the nine relapse-related lncRNAs for prognosis prediction, which classified patients into high-risk and low-risk subgroups with significantly different recurrence-free survival (HR=45.728, 95% CI=6.241-335.1; p=1.69e-04). The prognostic value of this relapse-related lncRNA signature was confirmed in the testing dataset and other two independent datasets. Multivariable Cox regression analysis and stratified analysis showed that the relapse-related lncRNA signature was independent of other clinical variables. Integrative in silico functional analysis suggested that these nine relapse-related lncRNAs revealed biological relevance to disease relapse, such as cell cycle, DNA repair and damage and cell death. Our study demonstrated that the relapse-related lncRNA signature may not only help to identify LUAD patients at high risk of relapse benefiting from adjuvant therapy but also could provide novel insights into the understanding of molecular mechanism of recurrent disease.

Indexed as

AdenocarcinomaAdenocarcinoma of LungAdultAgedArea Under CurveBiomarkers, TumorFemaleGene Expression ProfilingHumansKaplan-Meier EstimateLung NeoplasmsMaleMiddle AgedNeoplasm Recurrence, LocalRNA, Long NoncodingROC CurveBiomarkers, TumorRNA, Long Noncodinglong non-coding RNAlung adenocarcinomaprognosisrecurrence-free survivalrelapse

Identifiers

PMID27105492
PMCPMC5045428
OpenAlexW2340454682

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.