Evidence map›Paper›PMID 30250531›Full record

ArticleOncology letters2018

Identification of six key miRNAs associated with breast cancer through screening large-scale microarray data.

Faqing Liang, Meng Yang, Ning Tong, Jinju Fang, Yanbin Pan, Jianmin Li, Xiao Zhang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2018. 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
0.6field-weighted citation impact, top 39% 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, 12 citations in OpenAlex.

  1. miRNAs in Signal Transduction of SMAD Proteins in Breast Cancer.International journal of molecular sciences · 2024
    Article
  2. Review
  3. Review
  4. Review
  5. International journal of molecular sciences · 2019
    Article
  6. Article
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

7 authors at 4 institutions in 1 country.

Faqing LiangDepartment of Breast Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.
Meng YangDepartment of Dermatology, The Third Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530031, P.R. China.
Ning TongDepartment of Neurology, Heze Minicipal Hospital, Heze, Shandong 274000, P.R. China.
Jinju FangDepartment of Dermatology, The Third Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530031, P.R. China.
Yanbin PanDepartment of Dermatology, The Third Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530031, P.R. China.
Jianmin LiDepartment of Dermatology, The Third Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530031, P.R. China.
Xiao ZhangDepartment of Breast Surgery, Hospital of The University of Electronic Science and Technology of China and The Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, P.R. China.
Guangxi Medical University · CNHeze Municipal Hospital · CNUniversity of Electronic Science and Technology of China · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast Cancer (BC) is one of the most common primary malignant tumors, which is life threatening. Previous studies have demonstrated that microRNAs (miRNA) may regulate or affect the incidence of BC. However, results of these studies are inconsistent, due to factors including the different sequencing platforms and sample selection methods used. To explore the key miRNAs involved in the pathogenesis of BC, and to use these miRNAs to monitor the tumor progression of BC, a systematic review was performed on the previous studies examining BC miRNA; the function of the target genes that were modulated by these key miRNAs were also analyzed. A total of 8 representative miRNA datasets examining the pathogenesis of BC were selected. Key miRNAs were identified by comparing the overlap between these datasets. Then, the target genes of these key miRNAs were predicted through TargetScan. Furthermore, functional enrichment analysis of target genes and transcription factor (TF) binding analysis was also performed using the Database for Annotation, Visualization and Integrated Discovery and Tfacts database, respectively. A total of 6 key miRNAs were identified by comparing the differentially expressed miRNAs datasets in the pathogenesis of BC. Compared with normal tissues, 3 miRNAs were upregulated: Hsa-miR-21b; hsa-miR-29b; and hsa-miR-155; and 3 miRNAs were downregulated: Hsa-miR-10b; hsa-miR-125; and hsa-miR-145. The target genes regulated by the up- and downregulated miRNAs were significantly enriched in the biological processes of 'transcriptional regulation', and these target genes depended on RNA polymerase II promoter and DNA template, respective to the up- and downregulated genes. The downregulated key miRNAs were specifically enriched in the biological processes of 'ephrin receptor signaling pathway' (GO: 0048013) and 'axon guidance' (GO: 0007411). TF analysis of the key miRNA target genes revealed that 104 TFs interacted with the 319 target genes of the upregulated miRNAs, while the 92 TFs interacted with the 254 target genes of the downregulated miRNAs. In total, there were 133 TFs and 63 (47.3%) TFs shared by the 2 types (up- and downregulated) of target genes. In summary, 6 key miRNAs in BC were identified by systematic review; the corresponding target genes and TFs that bind to these target genes were also identified, and the potential functions of target genes were revealed. These data may be beneficial to increasing the accuracy of BC treatment through monitoring miRNA.

Indexed as

breast cancerfunction and pathways enrichmentmicroRNAsystematic analysis

Identifiers

PMID30250531
PMCPMC6144940
OpenAlexW2884890703

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.