Evidence map›Paper›PMID 31852837›Full record

ArticleAging2019

Molecular subtypes based on DNA methylation predict prognosis in colon adenocarcinoma patients.

Changshun Yang, Yu Zhang, Xiaoqin Xu, Weihua Li

Open access · greenAbstract read
In one paragraph

Article in Aging, 2019. 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
3.7field-weighted citation impact, top 6% 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, 64 citations in OpenAlex.

  1. Article
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  11. Computational Analysis of High-Dimensional DNA Methylation Data for Cancer Prognosis.Journal of computational biology : a journal of computational molecular cell biology · 2022
    Review
  12. Article
  13. Article
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  17. Article
  18. Identification of RORγ as a favorable biomarker for colon cancer.The Journal of international medical research · 2021
    Article
  19. Article
  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

4 authors at 2 institutions in 1 country.

Changshun YangDepartment of Surgical Oncology, Fujian Provincial Hospital, Fuzhou 350001, China.
Yu ZhangDepartment of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350001, China.
Xiaoqin XuSchool of Public Health, Fujian Medical University, Fuzhou 350001, China.
Weihua LiDepartment of Surgical Oncology, Fujian Provincial Hospital, Fuzhou 350001, China.
Fujian Medical University · CNFujian Provincial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor heterogeneity makes early diagnosis and effective treatment of colon adenocarcinoma difficult. As an important regulator of gene expression, DNA methylation can influence tumor heterogeneity. In this study, we explored the prognostic value of subtypes based on DNA methylation status in 424 colon adenocarcinoma samples from the Cancer Genome Atlas database. Differences in DNA methylation levels were associated with differences in T, N, and M category, age, stage, and prognosis. Seven subgroups were identified based on consensus clustering using 356 CpG sites that significantly influenced survival. Finally, a prognostic model was constructed and used to classify samples in a testing dataset into seven DNA methylation subgroups based on the classification results of a training dataset. These specific classifications based on DNA methylation may help account for heterogeneity within previously established molecular subgroups of colon adenocarcinoma and could potentially aid in the development of more effective personalized treatments.

Indexed as

AdenocarcinomaBiomarkers, TumorColonic NeoplasmsDisease ProgressionDNA MethylationFemaleHumansMaleMiddle AgedPrognosisBiomarkers, Tumorbioinformaticscolon adenocarcinomaDNA methylationprognostic prediction modelTCGA database

Identifiers

PMID31852837
PMCPMC6949097
OpenAlexW2995540821

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.