Evidence map›Paper›PMID 31807021›Full record

ArticleOncoTargets and therapy2019

Downregulation Of microRNA-133b And Its Clinical Value In Non-Small Cell Lung Cancer.

Guan-Yu Chen, Lin Ruan

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 38% 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

7 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

2 authors at 1 institution in 1 country.

Guan-Yu ChenDepartments of Anesthesiology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
Lin RuanDepartments of Anesthesiology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
Tumor Hospital of Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies have investigated the expression of miR-133b in non-small cell lung cancer (NSCLC); however, its underlying mechanism in relation to the pathogenesis of NSCLC remains unclear.

methodsThe aim of this study was to investigate the correlation between miR-133b expression and clinical parameters based on the Cancer Genome Atlas (TCGA) and real-time quantitative real-time PCR (RT-qPCR) data. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify the biological function of miR-133b. A protein-protein interaction (PPI) network was constructed to screen for hub genes. The Gene Expression Profiling Interaction Analysis (GEPIA) and the Human Protein Atlas databases (HPAD) were employed to validate the hub genes. The cBioPortal database was used to identify neighboring genes with alteration frequencies greater than 20% gene alterations.

resultsmiR-133b was downregulated in NSCLC tissues, and expression was correlated with lymph node metastasis (P < 0.05). A total of 362 genes were considered as the potential targets of miR-133b in NSCLC. These candidate target genes highly enriched in various key pathways such as the PI3K-Akt pathways, P53 signal pathways, and ECM-receptor interaction. PPI revealed 10 genes as hub genes with node degrees ≥10.

conclusionThe study validated that miR-133b is downregulated in NSCLC. In addition, miR-133b might function as a biomarker for the diagnosis and prognosis of NSCLC. Bioinformatics analysis revealed that miR-133b could be involved in NSCLC metastasis.

Indexed as

microarraymiR-133bmiRNA-sequencingnon-small cell lung cancerquantitative real-time PCR

Identifiers

PMID31807021
PMCPMC6844227
OpenAlexW2985549943

What OpenQuestion holds

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LicenceCC BY-NC
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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.