Evidence map›Paper›PMID 32647676›Full record

ArticleAnnals of translational medicine2020

Large-scale transcriptome analysis identified RNA methylation regulators as novel prognostic signatures for lung adenocarcinoma.

Lei Sun, Wen-Ke Liu, Xiao-Wei Du, Xiang-Li Liu, Gao Li, Yao Yao, Tao Han, Wen-Ya Li, Jia Gu

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

30 citing papers in PubMed, 37 citations in OpenAlex.

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  13. Biological roles of RNA mBiomarker research · 2022
    Review
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  15. Article
  16. Review
  17. Importance of NMolecular and clinical oncology · 2021
    Review
  18. MTranslational lung cancer research · 2021
    Article
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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

9 authors at 4 institutions in 1 country.

Lei SunDepartment of Thoracic Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China.
Wen-Ke LiuDepartment of Thoracic Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China.
Xiao-Wei DuDepartment of Oncology, General Hospital of Northern Theater Command, Shenyang, China.
Xiang-Li LiuDepartment of Thoracic Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China.
Gao LiDepartment of Oncology, General Hospital of Northern Theater Command, Shenyang, China.
Yao YaoDepartment of Thoracic Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China.
Tao HanDepartment of Oncology, General Hospital of Northern Theater Command, Shenyang, China.
Wen-Ya LiDepartment of Thoracic Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China.
Jia GuDepartment of Otolaryngology, The First Affiliated Hospital of China Medical University, Shenyang, China.
China Medical University · CNGeneral Hospital of Shenyang Military Region · CNFirst Hospital of China Medical University · CNJinzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe abnormal expression of genes is an essential factor affecting the prognosis of cancer. RNA modification is a way of regulating post-transcriptional levels, including m

methodsWe summarized thirty-one RNA methylation regulators. The training set was obtained from The Cancer Genome Atlas (TCGA) database, and the test set was obtained from the Gene Expression Omnibus (GEO) database. The Wilcoxon test was used to analyze the expression of RNA methylation regulators. We constructed tumor subgroup models and risk models based on the expression of those regulators. Principal component analysis (PCA) and the receiver operating characteristic (ROC) confirmed the accuracy of the models. Real-time polymerase chain reaction (PCR) validates the results

resultsMost RNA methylation regulators had distinct expressions in tumor tissues and adjacent tissues (P<0.05). All the models showed high predictive performance (AUC: 0.65-0.82), and the five-year survival of patients in each group was statistically different (P<0.05). The patients in the high-risk group were more likely to have a higher stage, more lymph node metastases, and distant metastases, showing a poor clinical outcome. Patients with high expression of NOP2 or HNRNP were more likely to have a poorly differentiated

conclusionsWith our study, we found that the expressions of most RNA methylation regulators were significantly different in cancer and para-cancerous tissues. Different molecular phenotypes constructed by RNA methylation regulators can be independent risk factors for the prognosis of lung adenocarcinoma. Our study demonstrates the critical role of RNA methylation in lung adenocarcinoma, and it is expected to supply a reference for the prognostic stratification and treatment strategy development of lung adenocarcinoma.

Indexed as

epigenetic modificationlung adenocarcinomaprognostic signatureRNA methylationThe Cancer Genome Atlas (TCGA)

Identifiers

PMID32647676
PMCPMC7333141
OpenAlexW3038120081

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.