Evidence map›Paper›PMID 36121511›Full record

ArticleJournal of cancer research and clinical oncology2023

Expression and prognostic signatures of m6A-related lncRNAs in hepatocellular carcinoma.

Kenan Hao, Jincheng Li, Youao Zhang, Wei Zhao, Xiaojing Chen, Jiabin Xu, Ye Tian, Xinmin Li, Jianyu Fen, Xiaofeng He

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. 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

10 authors at 1 institution in 1 country.

Kenan Hao *Division of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Jincheng Li *Division of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Youao ZhangNanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Wei ZhaoDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Xiaojing ChenDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Jiabin XuDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Ye TianDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Xinmin LiDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Jianyu FenDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
Xiaofeng HeDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China. ozonetherapy@126.com.ORCID http://orcid.org/0000-0001-8255-1874
Nanfang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundN6-methyladenosine (m6A) is a common modification and plays an important role in various biological processes, but m6A-related lncRNA functions in hepatocellular carcinoma (HCC) have not been systematically clarified.

methodsThe clinical data and RNA-seq transcriptome of 375 cases of HCC and 50 cases of normal tissues were obtained from the Cancer Gene Atlas database. Co-expression analysis was used to obtain m6A-related lncRNA. The independent prognostic factors were identified by univariate and multivariate Cox regression models. Kaplan-Meier method was used in survival analysis. The core gene of the mRNA-mRNA interaction network is related to m6A-related lncRNAs obtained by the CytoHubba plugin of Cytoscape. Gene ontology and Kyoto Gene Encyclopedia were analyzed to find out the potential mechanism. CIBERSORT algorithm was used to calculate the relative proportion of immune infiltrating cells.

resultsWe identified two subgroups (cluster 1 and cluster 2) according to the expression level. The survival analysis curve and receiver operating characteristic curve proved that this model could predict the prognosis of HCC patients. The univariate and multivariate Cox regression analyses showed the independent prognostic value. UBE2C was screened as the pivotal gene. The expression level of m6A-related lncRNAs causes changes in the tumor immune microenvironment.

conclusionThe expression levels of m6A-related lncRNAs were significantly different and the prognostic value of m6A-related lncRNAs was confirmed. The m6A-related lncRNAs are expected to be prognostic signatures in HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsRNA, Long NoncodingHumansOncogenesPrognosisTumor MicroenvironmentRNA, Long NoncodingHepatocellular carcinomalncRNAsm6APrognostic signaturesTumor immune microenvironment

Identifiers

PMID36121511
PMCPMC11796787
OpenAlexW4296322467

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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.