ArticleTranslational cancer research2025
Development and validation of an
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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
2 citing papers in PubMed.
- Molecular mechanisms and therapeutic strategies: DNA methylation in pancreatic cancer.Cancer biology & therapy · 2026Review
- UHRF1 as an epigenetic therapeutic target in Cancer.Molecular biology reports · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: DNA methylation plays a crucial role in the onset and progression of cancer. However, the complex technology and high costs required for methylation detection limit its clinical application. DNA methylation regulators are essential for maintaining the precision and stability of gene methylation, and their aberrant expression can lead to abnormal methylation levels. Whereas the role of combinatorial methylation regulators in pancreatic cancer (PCA) risk remains unclear, we developed a model using 20 DNA methylation regulators to predict patient prognosis and assess treatment response. Methods: Gene expression and clinical data from 331 PCA patients [The Cancer Genome Atlas (TCGA)-PCA, n=177; Gene Expression Omnibus (GEO)-PCA, n=154] were analyzed. TCGA data were used as the training set, and GEO data were used as the validation set. Inclusion criteria were complete survival data. Univariate and least absolute shrinkage and selection operator (LASSO)-Cox regression identified prognostic DNA methylation regulators. The model's predictive accuracy was validated using time-dependent receiver operating characteristic (ROC) curves. Differences in immune cell infiltration and drug sensitivity were also assessed. Results: A total of 331 PCA patients were analyzed, with a median overall survival (OS) of 1.2 and 1.4 years, respectively. Univariate Cox regression identified seven DNA methylation regulators ( Conclusions: Our findings suggest that the prognostic model, which is based on
Indexed as
Identifiers
What OpenQuestion holds
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.