Evidence map›Paper›PMID 31328722›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2019

Potential Five-MicroRNA Signature Model for the Prediction of Prognosis in Patients with Wilms Tumor.

Yihang Gong, Baojia Zou, Jianxu Chen, Lei Ding, Peiping Li, Jiafan Chen, Jiandi Chen, Baimeng Zhang, Jian Li

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 26 citations in OpenAlex.

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  8. CircHN1 affects cell proliferation and migration in gastric cancer.Journal of clinical laboratory analysis · 2020
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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

9 authors at 2 institutions in 1 country.

Yihang GongDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Baojia ZouDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Jianxu ChenDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Lei DingDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Peiping LiDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Jiafan ChenDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Jiandi ChenDepartment of Endocrinology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Baimeng ZhangDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Jian LiDepartment of Hepatobiliary Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China (mainland).
Fifth Affiliated Hospital of Sun Yat-sen University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Wilms tumor (WT) is the most common type of pediatric renal malignancy, and is associated with poor prognosis. The aim of the present study was to identify microRNA (miRNA) signatures which might predict prognosis and categorize WTs into high- and low-risk subgroups. MATERIAL AND METHODS The miRNA expression profiles of WT patients and normal samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment database. Differentially expressed miRNAs between WT patients and normal samples were identified using the EdgeR package. Subsequently, correlations between differentially expressed miRNAs and the prognosis of overall survival were analyzed. Enrichment analyses for the targeted mRNAs were conducted via the Database for Annotation, Visualization, and Integration Discovery. RESULTS A total of 154 miRNAs were identified as differentially expressed in WT. Of those, 18 miRNAs were associated with overall survival (P<0.05). A prognostic signature of 5 differentially expressed miRNAs (i.e., has-mir-149, has-mir-7112, has-mir-940, has-mir-1248, and has-mir-490) was constructed to classify the patients into high- and low-risk subgroups. The targeted mRNAs of these prognostic miRNAs were primarily enriched in Gene Ontology terms (i.e., protein autophosphorylation, protein dephosphorylation, and stress-activated MAPK cascade) and the Kyoto Encyclopedia of Genes and Genomes signaling pathways (i.e., MAPK, AMPK, and PI3K-Akt). CONCLUSIONS The 5-miRNA signature model might be useful in determining the prognosis of WT patients. As a promising prediction tool, this prognosis signature might serve as a potential biomarker for WT patients.

Indexed as

Biomarkers, TumorChinaDown-RegulationGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyGenetic Predisposition to DiseaseHumansKaplan-Meier EstimateMicroRNAsPatientsPrognosisRNA, MessengerTranscriptomeUp-RegulationWilms TumorBiomarkers, TumorMicroRNAsMIRN149 microRNA, humanMIRN490 microRNA, humanMIRN940 microRNA, humanRNA, Messenger

Identifiers

PMID31328722
PMCPMC6668497
OpenAlexW2962880403

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.