Evidence map›Paper›PMID 31637882›Full record

ArticleYonsei medical journal2019

A Two-DNA Methylation Signature to Improve Prognosis Prediction of Clear Cell Renal Cell Carcinoma.

Shanping Shi, Shazhou Ye, Xiaoyue Wu, Mingjun Xu, Renjie Zhuo, Qi Liao, Yang Xi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Yonsei medical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. The regulation roles of miRNAs in Helicobacter pylori infection.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    Review
  4. Review
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

7 authors.

Shanping ShiDiabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0002-0672-4419
Shazhou YeDiabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0001-5181-5902
Xiaoyue WuDiabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0003-3784-0751
Mingjun XuDiabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0001-5924-7129
Renjie ZhuoDepartment of Preventative Medicine, Medical School of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0001-7944-8550
Qi LiaoDepartment of Preventative Medicine, Medical School of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0001-8769-9325
Yang XiDiabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, Zhejiang, China. xiyang@nbu.edu.cn.ORCID https://orcid.org/0000-0001-8630-5945

Funding

Natural Science Foundation of Zhejiang Province LY17C060002
6 · The paper itself

Abstract

purposeEffective biomarkers and models are needed to improve the prognostic prospects of clear cell renal cell carcinoma (ccRCC). The purpose of this work was to identify DNA methylation biomarkers and to evaluate the utility of DNA methylation analysis for ccRCC prognosis. MATERIALS AND

methodsAn overview of genome-wide methylation of ccRCC tissues derived from The Cancer Genome Atlas (TCGA) database was download for analysis. DNA methylation signatures were identified using Cox regression methods. The potential clinical significance of methylation biomarkers acting as a novel prognostic markers was analyzed using the Kaplan-Meier method and receiver operating characteristic (ROC) curves.

resultsThis study analyzed data for 215 patients with information on 23171 DNA methylation sites and identified a two-DNA methylation signature (cg18034859, cg24199834) with the help of a step-wise multivariable Cox regression model. The area under the curve of ROCs for the two-DNA methylation signature was 0.819. The study samples were stratified into low- and high-risk classifications based on an optimal threshold, and the two groups showed markedly different survival rates. Moreover, the two-DNA methylation marker was suitable for patients of varying ages, sex, stages (I and IV), and histologic grade (G2).

conclusionThe two-DNA methylation signature was deemed to be a potential novel prognostic biomarker of use in increasing the accuracy of predicting overall survival of ccRCC patients.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorCarcinoma, Renal CellDatabases, GeneticDNA MethylationFemaleHumansKaplan-Meier EstimateKidney NeoplasmsMaleMiddle AgedMultivariate AnalysisPrognosisRisk FactorsBiomarkers, TumorbiomarkersCarcinomaDNA methylationprognosisrenal cell

Identifiers

PMID31637882
PMCPMC6813151

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