Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma.

doi:10.1016/j.ijmedinf.2025.105883

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Article

Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma.

International journal of medical informatics - 1 Jul 2025

Zaccaria Gian Maria, Altini Nicola, Mongelli Valentina, Marino Francescomaria, Bevilacqua Vitoantonio

Abstract excerpt

BACKGROUND: In Pancreatic Ductal Adenocarcinoma (PDAC), current prognostic scores are unable to fully capture the biological heterogeneity of the disease. While some approaches investigating the role of multi-omics in PDAC are emerging, the analysis of methylation data is under exploited. MATERIALS AND METHODS: We analyzed CpG sites from two publicly available datasets, the TCGA-PAAD used as discovery set and the...

Read the complete abstract on PubMed

Topics

Humans
Carcinoma, Pancreatic Ductal
Prognosis
Machine Learning
Pancreatic Neoplasms
DNA Methylation

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Epigenomics

CpG Islands

Female

Male

Mutation

Proto-Oncogene Proteins p21(ras)

Middle Aged

Tumor Suppressor Protein p53

Source

Open in PubMed

Identifiers

PMID: 40157244
DOI: 10.1016/j.ijmedinf.2025.105883

Genes

KRAS
TP53
C2
C3

Provenance

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