Evidence map›Paper›PMID 32922032›Full record

ArticleOncoTargets and therapy2020

Construction of a circRNA-Related ceRNA Prognostic Regulatory Network in Breast Cancer.

Huan Song, Jian Sun, Weimin Kong, Ye Ji, Dian Xu, Jianming Wang

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

13 citing papers in PubMed, 40 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

6 authors at 2 institutions in 1 country.

Huan Song *Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, People's Republic of China.
Jian Sun *Department of Thoracic Surgery, The First People's Hospital of Yancheng City, Yancheng 224006, People's Republic of China.
Weimin Kong *Department of Thoracic Surgery, The First People's Hospital of Yancheng City, Yancheng 224006, People's Republic of China.
Ye JiDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, People's Republic of China.
Dian XuDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, People's Republic of China.
Jianming WangDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, People's Republic of China.ORCID 0000-0002-9151-284X
Nanjing Medical University · CNNantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAccumulating evidence has indicated that circRNAs are closely involved in tumorigenesis and progression of human cancers. However, the molecular mechanism underlying function of circRNAs in breast cancer has not been thoroughly elucidated. Currently, we aimed to characterize the circRNA-related competing endogenous RNA (ceRNA) regulatory network in breast cancer and to construct prognostic model. MATERIALS AND

methodsFirst, we constructed circRNA expression profiles for paired breast cancer in a Chinese population using a human circRNA microarray. Expression profiles of circRNAs, miRNAs, and mRNAs were retrieved from our circRNA dataset, the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. We applied the limma and edgeR packages to identify differentially expressed RNAs. Weighted gene correlation network analysis (WGCNA) was used to identify critical modules of mRNAs. Next, a ceRNA network was established based on circRNA-miRNA and miRNA-mRNA intersections. Both Cox regression analysis and ROC curve analysis were performed to generate prognostic model. Additionally, we performed Gene Set Enrichment Analysis (GSEA) on prognostic signatures.

resultsTotal of 59 circRNAs, 98 miRNAs and 3966 mRNAs were identified as differentially expressed RNAs. We first identified 38 miRNA-mRNA pairs and 38 circRNA-miRNA pairs to construct the circRNA-miRNA-mRNA regulatory network and then generated a prognostic model based on 7 signatures (MMD, SLC29A4, CREB5, FOS, ANKRD29, MYOCD, and PIGR), and patients with high-risk scores presented poor prognosis. Several cancer-related pathways were enriched, including the TGF-β pathway, the focal adhesion pathway, and the JAK-STAT signaling pathway, and 20 prognostic ceRNA regulatory networks were subsequently identified.

conclusionIn all, we screened a series of dysregulated circRNAs, miRNAs, and mRNAs, and constructed circRNA-related ceRNA network in breast cancer. Our findings may help to deepen the understanding of circRNA-related regulatory mechanisms. Moreover, we generated a prognostic model that provided new insight into postoperative management for breast cancer.

Indexed as

breast cancerceRNAcircRNAmiRNAmRNAncRNATCGA

Identifiers

PMID32922032
PMCPMC7455596
OpenAlexW3050005255

What OpenQuestion holds

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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.