Evidence map›Paper›PMID 32457603›Full record

ArticleFrontiers in pharmacology2020

Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer.

Shuoling Chen, Chang Gao, Yangyuan Wu, Zunnan Huang

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

Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
5.3field-weighted citation impact, top 3% 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

26 citing papers in PubMed, 48 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

4 authors at 2 institutions in 1 country.

Shuoling ChenKey Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Guangdong Medical University, Dongguan, China.
Chang GaoKey Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Guangdong Medical University, Dongguan, China.
Yangyuan WuKey Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Guangdong Medical University, Dongguan, China.
Zunnan HuangKey Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Guangdong Medical University, Dongguan, China.
Guangdong Medical College · CNGuangdong Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundmiRNAs and genes can serve as biomarkers for the prognosis and therapy of cervical tumors whose metastasis into lymph nodes is closely associated with disease progression and poor prognosis.

methodsR software and Bioconductor packages were employed to identify differentially expressed miRNAs (DEMs) from The Cancer Genome Atlas (TCGA) database. GEO2R detected differentially expressed genes (DEGs) in the GSE7410 dataset originating from the Gene Expression Omnibus (GEO). A Cox proportional hazard regression model was established to select prognostic miRNA biomarkers. Online tools such as TargetScan and miRDB predicted target genes, and overlapping DEGs and target genes were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) function annotations were performed to discern the potential functions of consensus genes. STRING and Cytoscape screened key genes and constructed a regulatory network.

resultsA combination of four miRNAs (down-regulated miR-502 and miR-145, up-regulated miR-142 and miR-33b) was identified as an independent prognostic signature of cervical cancer. A total of 94 consensus genes were significantly enriched in 7 KEGG pathways and 19 GO function annotations including the cAMP signaling pathway, the plasma membrane, integral components of the plasma membrane, cell adhesion, etc. The module analysis suggested that

conclusionsThis study demonstrates that a four-miRNA signature can be a prognostic biomarker, and seven key genes are significantly associated with lymph node metastasis in cervical cancer patients. These miRNAs and key genes have the potential to be therapeutic targets for cervical cancer. Among them, two miRNAs (miR-502 and miR-33b) and two key genes (

Indexed as

cervical cancerkey genelymph node metastasismiRNAprognostic signature

Identifiers

PMID32457603
PMCPMC7226536
OpenAlexW3022894636

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.