Evidence map›Paper›PMID 35083139›Full record

ArticleFrontiers in oncology2021

Revealing the Role of lncRNA CCDC144NL-AS1 and LINC01614 in Gastric Cancer

Weiwei Sheng, Weihong Zhou, Yundi Cao, Yuejiao Zhong

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Review
  3. LINC01614: A Potential Therapeutic Target in Astrocytoma Progression.Journal of cellular and molecular medicine · 2025
    Article
  4. Review
  5. 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 at 2 institutions in 1 country.

Weiwei ShengPhysical Examination Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
Weihong ZhouPhysical Examination Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
Yundi CaoDepartment of Oncology, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.
Yuejiao ZhongDepartment of Medical Oncology, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Nanjing Drum Tower Hospital · CNNanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) are key regulators in the pathophysiology of gastric cancer, and lncRNAs have been regarded as potential biomarkers and therapeutic targets for gastric cancer. The present study performed the WGCNA analysis of the GSE70880 dataset and aimed to identify novel lncRNAs associated with gastric cancer progression. Based on the WGCNA, the lncRNAs and mRNA co-expression network were constructed. A total of four modules were identified and the eigengenes in different modules were involved in various key signaling pathways. Furthermore, the co-expression networks were constructed between the lncRNAs and mRNA; this leads to the identification of 6 modules, which participated in various cellular pathways. The survival analysis showed that high expression of CCDC144NL antisense RNA 1 (CCDC144NL-AS1) and LINC01614 was positively correlated with the poor prognosis of patients with gastric cancer. The

Indexed as

CCDC144NL-AS1gastric cancerLINC01614lncRNAsprognosisWGCNA

Identifiers

PMID35083139
PMCPMC8784853
OpenAlexW4205100329

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.