Evidence map›Paper›PMID 35189810›Full record

ArticleBMC gastroenterology2022

Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients.

Jun-Mei Wang, Xuan Li, Peng Yang, Wen-Bin Geng, Xiao-Yong Wang

Open access · goldAbstract read
In one paragraph

Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Non-coding RNA-Mediated N6-Methyladenosine (mNon-coding RNA research · 2024
    Review
  5. Article
  6. NJournal of translational internal medicine · 2024
    Article
  7. The emerging role of mFrontiers in cell and developmental biology · 2023
    Review
  8. Article
  9. Article
  10. Article
  11. 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

5 authors at 3 institutions in 1 country.

Jun-Mei Wang *Department of Gastroenterology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, 213000, China.
Xuan Li *Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, China.
Peng YangDepartment of Gastroenterology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, 213000, China.
Wen-Bin GengDepartment of Gastroenterology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, 213000, China.
Xiao-Yong WangDepartment of Gastroenterology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, 213000, China. wxy20009@126.com.
Nanjing Medical University · CNChangzhou No.2 People's Hospital · CNDalian Medical University · CN

Funding

Changzhou special fund for introducing foreign talents CQ20204037oung medical talents of Jiangsu province QNRC2016269the international science and technology cooperation fund of Changzhou, China CZ20190021
6 · The paper itself

Abstract

backgroundAccumulating studies have demonstrated that lncRNAs play vital roles in the prognosis of gastric cancer (GC); however, the prognostic value of N6-methyladenosine-related lncRNAs has not been fully reported in GC. This study aimed to construct and validate an m6A-related lncRNA pair signature (m6A-LPS) for predicting the prognosis of GC patients.

methodsGC cohort primary data were downloaded from The Cancer Genome Atlas. We analysed the coexpression of m6A regulators and lncRNAs to identify m6A-related lncRNAs. Based on cyclical single pairing along with a 0-or-1 matrix and least absolute shrinkage and selection operator-penalized regression analyses, we constructed a novel prognostic signature of m6A-related lncRNA pairs with no dependence upon specific lncRNA expression levels. All patients were divided into high-risk and low-risk group based on the median risk score. The predictive reliability was evaluated in the testing dataset and whole dataset with receiver operating characteristic (ROC) curve analysis. Gene set enrichment analysis was used to identify potential pathways.

resultsFourteen m6A-related lncRNA pairs consisting of 25 unique lncRNAs were used to construct the m6A-LPS. Kaplan-Meier analysis showed that the high-risk group had poor prognosis. The area under the curve for 5-year overall survival was 0.906, 0.827, and 0.882 in the training dataset, testing dataset, and whole dataset, respectively, meaning that the m6A-LPS was highly accurate in predicting GC patient prognosis. The m6A-LPS served as an independent prognostic factor for GC patients after adjusting for other clinical factors (p < 0.05). The m6A-LPS had more accuracy and a higher ROC value than other prognostic models for GC. Functional analysis revealed that high-risk group samples mainly showed enrichment of extracellular matrix receptor interactions and focal adhesion. Moreover, N-cadherin and vimentin, known biomarkers of epithelial-mesenchymal transition, were highly expressed in high-risk group samples. The immune infiltration analysis showed that resting dendritic cells, monocytes, and resting memory CD4 T cells were significantly positively related to the risk score. Thus, m6A-LPS reflected the infiltration of several types of immune cells.

conclusionsThe signature established by pairing m6A-related lncRNAs regardless of expression levels showed high and independent clinical prediction value in GC patients.

Indexed as

RNA, Long NoncodingStomach NeoplasmsBiomarkers, TumorHumansPrognosisReproducibility of ResultsBiomarkers, TumorRNA, Long NoncodingEpithelial mesenchymal cell transitionGastric cancerImmune cell infiltrationlncRNAN6-methyladenosine

Identifiers

PMID35189810
PMCPMC8862389
OpenAlexW4213135126

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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.