Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma.

as key transcriptional regulators enriched in survival-associated CpG sites, linking their activity to patient survival outcomes. Collectively, our findings highlight valuable epigenetic biomarkers and provide a predictive model to assess PDAC risk levels post-surgery, offering the potential for improved patient stratification and personalized therapeutic strategies.

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Publication Details

Journal
PubMed
Published
2026-09-01
DOI
https://doi.org/10.1016/j.premed.2026.100046
Primary Topic
Pancreatic and Hepatic Oncology Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma.

Yining Zhao, Bo Aber Zhang, Yu Zhang
PubMed
Pancreatic and Hepatic Oncology Research
article

Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma.

Yining Zhao, Bo Aber Zhang, Yu Zhang
article en

Abstract

as key transcriptional regulators enriched in survival-associated CpG sites, linking their activity to patient survival outcomes. Collectively, our findings highlight valuable epigenetic biomarkers and provide a predictive model to assess PDAC risk levels post-surgery, offering the potential for improved patient stratification and personalized therapeutic strategies.

PubMedVol. 7
Washington University in St. Louis (US)
Good health and well-being
Openalex Percentile: Top 40%
Pancreatic and Hepatic Oncology Research
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