Evidence map›Paper›PMID 29434705›Full record

ArticleExperimental and therapeutic medicine2018

Identification of a progression-associated long non-coding RNA signature for predicting the prognosis of lung squamous cell carcinoma.

Yanyan Wang, Fang Yang, Yongzhi Zhuang

Open access · diamondAbstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2018. 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
0.4field-weighted citation impact, top 39% 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, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Multidimensional communication of microRNAs and long non-coding RNAs in lung cancer.Journal of cancer research and clinical oncology · 2019
    Review
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 at 1 institution in 1 country.

Yanyan WangDepartment of Medical Oncology, Daqing Oilfield General Hospital, Daqing, Heilongjiang 163001, P.R. China.
Fang YangDepartment of Medical Oncology, Daqing Oilfield General Hospital, Daqing, Heilongjiang 163001, P.R. China.
Yongzhi ZhuangDepartment of Medical Oncology, Daqing Oilfield General Hospital, Daqing, Heilongjiang 163001, P.R. China.
Daqing Oilfield General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) have been indicated to have prognostic roles in various cancer types. However, the association between lncRNAs and lung squamous cell carcinoma (LSCC) progression, and the prognostic value of lncRNAs as a marker for early detection of LSCC have not been systematically investigated. The present study performed a genome-wide comparative analysis in order to determine the expression profiles of 10,207 lncRNAs to investigate the expression patterns between patients with early stages of LSCC (stage I-II) and those with late-stage disease (stage III-IV). It was found that 114 lncRNAs were significantly differentially expressed between late- and early-stage LSCC and therefore associated with the progression of the malignancy. By focusing on progression-associated lncRNAs, eight lncRNAs were found to be significantly associated with overall survival of LSCC patients according to univariate Cox proportional hazards regression analysis. These eight prognostic lncRNAs were integrated into a progression-associated eight-lncRNA signature, which stratified patients into two groups with significantly different overall survival (median survival, 2.25 vs. 7.68 years; P=2.06×10

Indexed as

expression profileslong non-coding RNAslung squamous cell carcinomaprognosis

Identifiers

PMID29434705
PMCPMC5774407
OpenAlexW2770376322

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.