Evidence map›Paper›PMID 38737285›Full record

ArticleHeliyon2024

Identification of methylation driver genes for predicting the prognosis of pancreatic cancer patients based on whole-genome DNA methylation sequencing technology.

Chao Song, Ganggang Wang, Mengmeng Liu, Zijin Xu, Xin Liang, Kai Ding, Yu Chen, Wenquan Wang, Wenhui Lou, Liang Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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.

Chao SongShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200000, China.
Ganggang WangDepartment of Hepatobiliary Surgery, Pudong Hospital, Fudan University, Shanghai, 200000, China.
Mengmeng LiuDepartment of Gastroenterology, Affiliated Zhongshan Hospital of Fudan University, Qingpu Branch, Shanghai, 200000, China.
Zijin XuDepartment of General Surgery, Affiliated Zhongshan Hospital of Fudan University, Qingpu Branch, Shanghai, 200000, China.
Xin LiangCAS Key Laboratory of Nutrition, University of Chinese Academy of Sciences, Shanghai, 200000, China.
Kai DingCAS Key Laboratory of Nutrition, University of Chinese Academy of Sciences, Shanghai, 200000, China.
Yu ChenCAS Key Laboratory of Nutrition, University of Chinese Academy of Sciences, Shanghai, 200000, China.
Wenquan WangDepartment of Pancreatic Surgery, Affiliated Zhongshan Hospital of Fudan University, Shanghai, 200000, China.
Wenhui LouDepartment of Pancreatic Surgery, Affiliated Zhongshan Hospital of Fudan University, Shanghai, 200000, China.
Liang LiuShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was based on the use of whole-genome DNA methylation sequencing technology to identify DNA methylation biomarkers in tumor tissue that can predict the prognosis of patients with pancreatic cancer (PCa). TCGA database was used to download PCa-related DNA methylation and transcriptome atlas data. Methylation driver genes (MDGs) were obtained using the MethylMix package. Candidate genes in the MDGs were screened for prognostic relevance to PCa patients by univariate Cox analysis, and a prognostic risk score model was constructed based on the key MDGs. ROC curve analysis was performed to assess the accuracy of the prognostic risk score model. The effects of PIK3C2B knockdown on malignant phenotypes of PCa cells were investigated

Indexed as

Methylation driver genesPancreatic cancerPrognostic markersPrognostic risk prediction modelTCGA databaseWhole-genome DNA methylation

Identifiers

PMID38737285
PMCPMC11088258

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.