Evidence map›Paper›PMID 34282054›Full record

ArticleAging2021

LncRNA AC079630.4 expression associated with the progression and prognosis in lung cancer.

Li-Fang Wang, Li-Ping Wu, Jian-Dong Wen

Abstract read
In one paragraph

Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation.Journal of experimental & clinical cancer research : CR · 2024
    Review
  4. LncRNATranslational cancer research · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. 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

3 authors.

Li-Fang WangDrug Clinical Trial Office, Ganzhou People's Hospital, Ganzhou 341000, China.
Li-Ping WuDrug Clinical Trial Office, Ganzhou People's Hospital, Ganzhou 341000, China.
Jian-Dong WenDrug Clinical Trial Office, Ganzhou People's Hospital, Ganzhou 341000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mounting evidence has demonstrated the important role of long non-coding RNAs (lncRNAs) in the development and progression of lung cancer. In this study, we combined the methods of bioinformatics analysis and experimental validation, and aim to investigate the clinical significance and underlying mechanism of the novel lncRNA AC079630.4 in lung cancer. Finally, we found that AC079630.4 was significantly down-regulated in lung cancer tissues, including in its subtypes. Samples with low AC079630.4 expression had a more advanced pathological stage and a worse prognosis than those with high expression. In functional prediction, the KEGG pathway of apoptosis and the TRAIL signaling pathway were enriched in the samples with high AC079630.4 expression. In experimental validation, AC079630.4 over-expression could significantly inhibit the proliferation and clonality, and up-regulated the receptors of TRAIL (TRAIL-R1 and TRAIL-R2) in lung cancer cells. In conclusion, we adopted the methods of bioinformatics analysis and experimental validation, and identified a novel lncRNA of AC079630.4 as a tumor suppressor in lung cancer.

Indexed as

ApoptosisBiomarkers, TumorCarcinoma, Non-Small-Cell LungCell Line, TumorCell ProliferationFemaleGene Expression Regulation, NeoplasticGenes, Tumor SuppressorHumansLungLung NeoplasmsMaleMiddle AgedPrognosisRNA, Long NoncodingSignal TransductionBiomarkers, TumorRNA, Long NoncodingTNF-Related Apoptosis-Inducing LigandTNFSF10 protein, humanAC079630.4lncRNAlung cancerprognosisprogression

Identifiers

PMID34282054
PMCPMC8351710

What OpenQuestion holds

Textmetadata
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.