Evidence map›Paper›PMID 33934391›Full record

ArticleJournal of clinical laboratory analysis2021

A ten N6-methyladenosine-related long non-coding RNAs signature predicts prognosis of triple-negative breast cancer.

Jie Wu, Yan Cai, Gaiping Zhao, Maolan Li

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical laboratory analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 31 citations in OpenAlex.

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  12. The Key Role of RNA Modification in Breast Cancer.Frontiers in cell and developmental biology · 2022
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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 at 3 institutions in 1 country.

Jie WuKey Laboratory of Hydrodynamics (Ministry of Education), School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0000-0003-4245-875X
Yan CaiSchool of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
Gaiping ZhaoSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Maolan LiShanghai Research Center of Biliary Tract Disease, Shanghai, China.
Shanghai Jiao Tong University · CNSoutheast University · CNUniversity of Shanghai for Science and Technology · CN

Funding

National Natural Science Foundation of China 11502146National Natural Science Foundation of China 11572200National Natural Science Foundation of China 81773043
6 · The paper itself

Abstract

backgroundPatients with triple-negative breast cancer (TNBC) face a major challenge of the poor prognosis, and N6-methyladenosine-(m6A) mediated regulation in cancer has been proposed. Therefore, this study aimed to explore the prognostic roles of m6A-related long non-coding RNAs (LncRNAs) in TNBC.

methodsClinical information and expression data of TNBC samples were collected from TCGA and GEO databases. Pearson correlation, univariate, and multivariate Cox regression analysis were employed to identify independent prognostic m6A-related LncRNAs to construct the prognostic score (PS) risk model. Receiver operating characteristic (ROC) curve was used to evaluate the performance of PS risk model. A competing endogenous RNA (ceRNA) network was established for the functional analysis on targeted mRNAs.

resultsWe identified 10 independent prognostic m6A-related LncRNAs (SAMD12-AS1, BVES-AS1, LINC00593, MIR205HG, LINC00571, ANKRD10-IT1, CIRBP-AS1, SUCLG2-AS1, BLACAT1, and HOXB-AS1) and established a PS risk model accordingly. Relevant results suggested that TNBC patients with lower PS had better overall survival status, and ROC curves proved that the PS model had better prognostic abilities with the AUC of 0.997 and 0.864 in TCGA and GSE76250 datasets, respectively. Recurrence and PS model status were defined as independent prognostic factors of TNBC. These ten LncRNAs were all differentially expressed in high-risk TNBC compared with controls. The ceRNA network revealed the regulatory axes for nine key LncRNAs, and mRNAs in the network were identified to function in pathways of cell communication, signaling transduction and cancer.

conclusionOur findings proposed a ten-m6A-related LncRNAs as potential biomarkers to predict the prognostic risk of TNBC.

Indexed as

AdenosineAdultAgedBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansKaplan-Meier EstimateMiddle AgedModels, GeneticPrognosisRNA, Long NoncodingROC CurveTriple Negative Breast NeoplasmsAdenosineBiomarkers, TumorN-methyladenosineRNA, Long NoncodingceRNA networklong non-coding RNAN6-methyladenosineprognostic signaturetriple-negative breast cancer

Identifiers

PMID33934391
PMCPMC8183938
OpenAlexW3158804695

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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.