Evidence map›Paper›PMID 29707762›Full record

ArticleInternational journal of cancer2018

Identification of a five-lncRNA signature for predicting the risk of tumor recurrence in patients with breast cancer.

Jie Li, Weida Wang, Peng Xia, Linyun Wan, Li Zhang, Lei Yu, Lily Wang, Xi Chen, Yun Xiao, Chaohan Xu

Abstract read
In one paragraph

Article in International journal of cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

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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

10 authors.

Jie LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Weida WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Peng XiaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Linyun WanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Li ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Lei YuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Lily WangDivision of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL.
Xi ChenDivision of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL.
Yun XiaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Chaohan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.ORCID 0000-0001-5145-8757

Funding

iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTACU24CA210954 · NCI · BAYLOR COLLEGE OF MEDICINE · PI ZHANG, BING · 2016 to 2020
$4.9M
Integrative prediction models for metastasis risk in colon cancerR01CA158472 · NCI · VANDERBILT UNIVERSITY · PI BEAUCHAMP, ROBERT DANIEL, CHEN, XI STEVEN · 2012 to 2016
$2.3M
Integrative statistical models for TNBC biomarker discoveryR01CA200987 · NCI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CHEN, XI STEVEN · 2016 to 2020
$1.8M
National Cancer Institute (USA) R01CA158472National Cancer Institute (USA) R01CA200987National Cancer Institute (USA) U24CA210954NCI NIH HHS R01 CA158472NCI NIH HHS R01 CA200987NCI NIH HHS U24 CA210954
6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) are a major class of non-coding RNAs, and the functional deregulations of lncRNAs have been shown to be associated with the development and progression of BC. In this work, we conduct an integrative analysis on five re-annotated lncRNA expression datasets from the Gene Expression Omnibus (GEO) which included a total of 891 BC samples. We identified a five-lncRNA signature that was significantly associated with DFS in the training cohort of 327 patients. We found the five-lncRNA signature could effectively stratify patients in the training dataset into high- and low-risk groups with significantly different DFS (p = 3.29 × 10

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorBreast NeoplasmsCohort StudiesFemaleFollow-Up StudiesGene Expression ProfilingHumansMiddle AgedNeoplasm Recurrence, LocalPrognosisRNA, Long NoncodingROC CurveSurvival RateBiomarkers, TumorRNA, Long Noncodingarray re-annotationbreast cancerlncRNA signatureprognosistumor recurrence

Identifiers

PMID29707762
PMCPMC6519083

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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.