Evidence map›Paper›PMID 32821169›Full record

ArticleCancer management and research2020

Construction and Comprehensive Analysis of a ceRNA Network to Reveal Potential Novel Biomarkers for Triple-Negative Breast Cancer.

Lifei Ma, Guiqin Song, Meiyu Li, Xiuqing Hao, Yong Huang, Jinping Lan, Siqian Yang, Zetian Zhang, Guohui Zhang, Jiao Mu

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 44% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Lifei MaCollege of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Guiqin SongCollege of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Meiyu LiDepartment of Forensic Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Xiuqing HaoDepartment of Pathology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Yong HuangCollege of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Jinping LanCollege of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Siqian YangCollege of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, People's Republic of China.
Zetian ZhangDepartment of Gastroenterology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Guohui ZhangDepartment of Forensic Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.
Jiao MuDepartment of Forensic Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People's Republic of China.ORCID 0000-0002-3488-0056
Hebei North University · CNZhejiang Sci-Tech University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTriple-negative breast cancer (TNBC) is the most common and aggressive type of breast cancer with an unfavourable outcome worldwide. Novel therapeutic targets are urgently required to explore this malignancy. This study explored the ceRNA network and the important genes for predicting the therapeutic targets.

methodsIt identified the differentially expressed genes of mRNAs, lncRNAs and miRNAs between TNBC and non-TNBC samples in four cohorts (TCGA, GSE38959, GSE45827 and GSE65194) to explore the novel therapeutic targets for TNBC. Downstream analyses, including functional enrichment analysis, ceRNA network, protein-protein interaction and survival analysis, were then conducted by bioinformatics analysis. Finally, the potential core protein of the ceRNA network in TNBC was validated by immunohistochemistry.

resultsA total of 1,045 lncRNAs and 28 miRNAs were differentially expressed in the TCGA TNBC samples, and the intersections of 282 mRNAs (176 upregulations and 106 downregulations) between the GEO and TCGA databases were identified. A ceRNA network composed of 7 lncRNAs, 62 mRNAs, 12 miRNAs and 244 edges specific to TNBC was established. The functional assay showed dysregulated genes, and GO, DO and KEGG enrichment analysis were performed. Survival analysis showed that mRNA

conclusionThus, our study presents an enhanced understanding of the ceRNA network in TNBC, where the key gene

Indexed as

ceRNA networkleukemia inhibitory factor receptornovel biomarkersoverall survivaltriple-negative breast cancer

Identifiers

PMID32821169
PMCPMC7423243
OpenAlexW3047150668

What OpenQuestion holds

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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.