ArticleAging2020
Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer.
Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- AIF1L as a Ferroptosis-Linked Biomarker in Microsatellite States-Driven Colorectal Cancer: Functional and Diagnostic Insights From Multiomics Analysis.Human mutation · 2025Article
- DNA methylation-driven gene FAM3D promotes colorectal cancer growth via the ATF4-SESN2-mTORC1 pathway.Aging · 2024Article
- Identification of POU4F1 as a novel prognostic biomarker and therapeutic target in esophageal squamous cell carcinoma.Cancer cell international · 2024Article
- Genome wide identification of novel DNA methylation driven prognostic markers in colorectal cancer.Scientific reports · 2024Article
- Four methylation-driven genes detected by linear discriminant analysis model from early-stage colorectal cancer and their methylation levels in cell-free DNA.Frontiers in oncology · 2022Article
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Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aberrant promoter methylation and ensuing abnormal gene expression are important epigenetic mechanisms that contribute to colorectal oncogenesis. Yet, the prognostic significance of such methylation-driven genes in colorectal cancer (CRC) remains obscure. Herein, a total of 181 genes were identified as the methylation-driven molecular features of CRC by integrated analysis of the expression profiles and the matched DNA methylation data from The Cancer Genome Atlas (TCGA) database. Among them, a five-gene signature (POU4F1, NOVA1, MAGEA1, SLCO4C1, and IZUMO2) was developed as a risk assessment model for predicting the clinical outcomes in CRC. The Kaplan-Meier analysis and Harrell's C index demonstrated that the risk assessment model significantly distinguished the patients in high or low-risk groups (
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Registered trials
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.