Evidence map›Paper›PMID 29238201›Full record

ArticleOncoTargets and therapy2017

Diagnostic significance of circulating long noncoding RNA PCAT6 in patients with non-small cell lung cancer.

Li Wan, Lin Zhang, Kai Fan, Jian-Jun Wang

Abstract read
In one paragraph

Article in OncoTargets and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Cancers · 2021
    Review
  6. Article
  7. Article
  8. The Role of lncRNA PCAT6 in Cancers.Frontiers in oncology · 2021
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. 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

4 authors.

Li WanDepartment of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Lin ZhangDepartment of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Kai FanDepartment of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Jian-Jun WangDepartment of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimWe have previously shown that the long noncoding RNA prostate cancer-associated transcript 6 (PCAT6) promoted the proliferation and invasion of lung adenocarcinoma (LUAD) cells. In this study, the diagnostic significance of tissue and serum PCAT6 was evaluated in non-small cell lung cancer (NSCLC). MATERIALS AND

methodsTissue expression of PCAT6 was systematically evaluated in five Gene Expression Omnibus datasets (GSE19804, GSE18842, GSE30219, GSE19188, and GSE27262). Circulating and tissue expressions of PCAT6 were detected by quantitative reverse-transcriptase polymerase chain reaction in NSCLC patients from Union Hospital.

resultsPCAT6 was significantly increased in lung cancer tissues and could be used to distinguish LUAD from adjacent normal tissues with an area under the receiver operating characteristic curve (AUC) of 0.9210 (

conclusionTogether with our previous findings, our results suggest that PCAT6 could be used as a potential diagnostic and prognostic biomarker in NSCLC.

Indexed as

diagnosislncRNAslung adenocarcinomalung squamous cell carcinomaPCAT6

Identifiers

PMID29238201
PMCPMC5713690

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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.