Evidence map›Paper›PMID 34288959›Full record

ArticlePloS one2021

Bioinformatics prediction of differential miRNAs in non-small cell lung cancer.

Kui Xiao, Shenggang Liu, Yijia Xiao, Yang Wang, Zhiruo Zhu, Yaohui Wang, De Tong, Jiehan Jiang

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

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 50% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. 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

8 authors at 2 institutions in 1 country.

Kui XiaoDepartment of Respiratory and Critical Care Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Shenggang LiuDepartment of Pulmonary and Critical Care Medicine, University of South China Affiliated Changsha Central Hospital, Changsha City, Hunan Province, China.
Yijia XiaoDepartment of Pulmonary and Critical Care Medicine, University of South China Affiliated Changsha Central Hospital, Changsha City, Hunan Province, China.
Yang WangDepartment of Pathology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Zhiruo ZhuDepartment of Respiratory and Critical Care Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Yaohui WangDepartment of Respiratory and Critical Care Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
De TongDepartment of Respiratory and Critical Care Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Jiehan JiangDepartment of Pulmonary and Critical Care Medicine, University of South China Affiliated Changsha Central Hospital, Changsha City, Hunan Province, China.ORCID 0000-0001-7516-8981
Central South University · CNChangsha Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-small cell lung cancer (NSCLC) accounts for 85% of all lung cancers. The drug resistance of NSCLC has clinically increased. This study aimed to screen miRNAs associated with NSCLC using bioinformatics analysis. We hope that the screened miRNA can provide a research direction for the subsequent treatment of NSCLC.

methodsWe screened out the common miRNAs after compared the NSCLC-related genes in the TCGA database and GEO database. Selected miRNA was performed ROC analysis, survival analysis, and enrichment analysis (GO term and KEGG pathway).

resultsA total of 21 miRNAs were screened in the two databases. And they were all highly expressed in normal and low in cancerous tissues. Hsa-mir-30a was selected by ROC analysis and survival analysis. Enrichment analysis showed that the function of hsa-mir-30a is mainly related to cell cycle regulation and drug metabolism.

conclusionOur study found that hsa-mir-30a was differentially expressed in NSCLC, and it mainly affected NSCLC by regulating the cell cycle and drug metabolism.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungGene Expression Regulation, NeoplasticLung NeoplasmsMicroRNAsRNA, NeoplasmDatabases, Nucleic AcidGene Expression ProfilingHumansBiomarkers, TumorMicroRNAsRNA, Neoplasm

Identifiers

PMID34288959
PMCPMC8294502
OpenAlexW3184716162

What OpenQuestion holds

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LicenceCC BY
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.