Evidence map›Paper›PMID 34040139›Full record

ArticleScientific reports2021

Comprehensive analysis of competitive endogenous RNA associated with immune infiltration in lung adenocarcinoma.

Wenjie Chen, Wen Li, Zhenkun Liu, Guangzhi Ma, Yunfu Deng, Xiaogang Li, Zhu Wang, Qinghua Zhou

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 37% 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, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. Article
  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

8 authors at 2 institutions in 1 country.

Wenjie Chen *Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Wen Li *Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Zhenkun Liu *Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Guangzhi MaLung Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Yunfu DengLung Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Xiaogang LiLung Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Zhu WangLaboratory of Molecular Diagnosis of Cancer, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Qinghua ZhouLung Cancer Center, West China Hospital, Sichuan University, Chengdu, China. zhouqh135@163.com.
Sichuan University · CNTianjin Medical University General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To identify the prognostic biomarker of the competitive endogenous RNA (ceRNA) and explore the tumor infiltrating immune cells (TIICs) which might be the potential prognostic factors in lung adenocarcinoma. In addition, we also try to explain the crosstalk between the ceRNA and TIICs to explore the molecular mechanisms involved in lung adenocarcinoma. The transcriptome data of lung adenocarcinoma were obtained from The Cancer Genome Atlas (TCGA) database, and the hypergeometric correlation of the differently expressed miRNA-lncRNA and miRNA-mRNA were analyzed based on the starBase. In addition, the Kaplan-Meier survival and Cox regression model analysis were used to identify the prognostic ceRNA network and TIICs. Correlation analysis was performed to analysis the correlation between the ceRNA network and TIICs. In the differently expressed RNAs between tumor and normal tissue, a total of 190 miRNAs, 224 lncRNAs and 3024 mRNAs were detected, and the constructed ceRNA network contained 5 lncRNAs, 92 mRNAs and 10 miRNAs. Then, six prognostic RNAs (FKBP3, GPI, LOXL2, IL22RA1, GPR37, and has-miR-148a-3p) were viewed as the key members for constructing the prognostic prediction model in the ceRNA network, and three kinds of TIICs (Monocytes, Macrophages M1, activated mast cells) were identified to be significantly related with the prognosis in lung adenocarcinoma. Correlation analysis suggested that the FKBP3 was associated with Monocytes and Macrophages M1, and the GPI was obviously related with Monocytes and Macrophages M1. Besides, the LOXL2 was associated with Monocytes and Activated mast cells, and the IL22RA1 was significantly associated with Monocytes and Macrophages M1, while the GPR37 and Macrophages M1 was closely related. The constructed ceRNA network and identified Monocytes, Macrophages M1 and activated Mast cells are all prognostic factors for lung adenocarcinoma. Moreover, the crosstalk between the ceRNA network and TIICs might be a potential molecular mechanism involved.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorGene Expression Regulation, NeoplasticHumansLung NeoplasmsLymphocytes, Tumor-InfiltratingMicroRNAsPrognosisRNA, Long NoncodingRNA, MessengerBiomarkers, TumorMicroRNAsRNA, Long NoncodingRNA, Messenger

Identifiers

PMID34040139
PMCPMC8155208
OpenAlexW3164494190

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.