Evidence map›Paper›PMID 31959204›Full record

ArticleClinical epigenetics2020

A DNA methylation signature to improve survival prediction of gastric cancer.

Yaojun Peng, Qiyan Wu, Lingxiong Wang, Huan Wang, Fan Yin

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
4.6field-weighted citation impact, top 4% 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

47 citing papers in PubMed, 75 citations in OpenAlex.

  1. Review
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  10. A review on trends in development and translation of omics signatures in cancer.Computational and structural biotechnology journal · 2024
    Review
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  16. New insight into the CNC-bZIP member, NFE2L3, in human diseases.Frontiers in cell and developmental biology · 2024
    Review
  17. Article
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  19. Computational Analysis of High-Dimensional DNA Methylation Data for Cancer Prognosis.Journal of computational biology : a journal of computational molecular cell biology · 2022
    Review
  20. 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 1 institution in 1 country.

Yaojun PengCollege of Graduate, The First Medical Centre, Chinese PLA General Hospital, Beijing, China.
Qiyan WuDepartment of Oncology, The First Medical Centre, Chinese PLA General Hospital, Beijing, China.
Lingxiong WangDepartment of Oncology, The First Medical Centre, Chinese PLA General Hospital, Beijing, China.
Huan WangDepartment of Scientific Research Administration, The First Medical Centre, Chinese PLA General Hospital, Beijing, China. wanghuanhuadian@163.com.
Fan YinDepartment of Oncology, The Second Medical Centre & National Clinical Research Center of Geriatric Disease, Chinese PLA General Hospital, Beijing, China. yinfancying@163.com.ORCID 0000-0001-5460-1117
Chinese PLA General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe current Union International Committee on Cancer or the American Joint Committee on Cancer TNM stage system has shown valuable but insufficient estimation for subsets of gastric cancer and prediction for prognosis patients. Thus, there is an urgent need to identify diagnostic, prognostic, and predictive biomarkers to improve patients' outcomes. Our aim was to perform an integrative analysis on publicly available datasets to identify epigenetic changes that may play key role in the initiation and progression of gastric cancer, based on which we set to develop a DNA methylation signature to improve survival prediction of gastric cancer.

resultsA total of 340 methylation-related differentially expression genes (mrDEGs) were screened in gastric cancer patients from The Cancer Genome Atlas (TCGA) project. Pathway enrichment analysis revealed that they were involved in the biological process related to initiation and progression of gastric cancer. Based on the mrDEGs identified, we developed a DNA methylation signature consisting of ten gene members (SCNN1B, NFE2L3, CLDN2, RBPMS2, JPH2, GBP6, COL4A5, SMKR1, PPP1R14A, and ARL4D) according to their methylation β value. This innovative DNA methylation signature was associated with cancer recurrence, while it showed independence of cancer recurrence and TNM stage for survival prediction. Combination of this DNA methylation signature and TNM stage improved overall survival prediction in the receiver operating characteristic analysis. We also verified that two individual genes (PPP1R14A and SCNN1B) of the identified prognostic signature were regulated by promoter region methylation in a panel of gastric cell lines.

conclusionsThis study presents a powerful DNA methylation signature by performing analyses integrating multi-source data including transcriptome, methylome, and clinical outcome of gastric cancer patients from TCGA. The identified DNA methylation signature may be used to refine the current prognostic model and facilitate further stratification of patients in the future clinical trials. Further experimental studies are warranted to unveil the regulatory mechanism and functional role of all the individual genes of the DNA methylation signature. Also, clinical investigations in large GC patient cohorts are greatly needed to validate our findings.

Indexed as

DNA MethylationEpithelial Sodium ChannelsFemaleHumansIntracellular Signaling Peptides and ProteinsKaplan-Meier EstimateMaleMiddle AgedMuscle ProteinsNeoplasm Recurrence, LocalNeoplasm StagingPrognosisPromoter Regions, GeneticRNA-SeqStomach NeoplasmsEpithelial Sodium ChannelsIntracellular Signaling Peptides and ProteinsMuscle ProteinsPPP1R14A protein, humanSCNN1B protein, humanDNA methylationEpigeneticsGastric cancerIntegrative analysisPrognosisTCGA

Identifiers

PMID31959204
PMCPMC6972030
OpenAlexW3006239280

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.