Article

Epigenetic profile drives accurate survival prediction in breast cancer via a multi-omics machine learning model

2026-07-22

Abstract excerpt

Abstract Accurate overall survival (OS) prediction is key for personalized treatment in breast cancer, but mutation burden alone is insufficient. To improve prognostic accuracy, we integrated genomic, transcriptomic, proteomic, epigenetic, and clinical features from 802 breast cancer patients to develop BANDOL (Breast cancer Analysis with Neoplastic Data and Omics Learning), a Random Survival Forest model. BANDOL...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: dce139d0-ae22-5889-92ae-4f49e0b24206
DOI: 10.24072/pcjournal.758

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Epigenetic profile drives accurate survival prediction in breast cancer via a multi-omics machine learning modelDOI 10.24072/pcjournal.758Read

Epigenetic profile drives accurate survival prediction in breast cancer via a multi-omics machine learning modelSemantic proximity Read

Identification and validation of a novel prognostic signature with DNA methylation-driven genes for survival prediction of breast cancerSemantic proximity Read

Integrated Multi-Omics Analysis for the Identification of Disease-Associated Variations and Prognostic Biomarkers in Triple-Negative Breast Cancer (TNBC)Semantic proximity Read

Deep learning based on multi-omics integration identifies potential therapeutic targets in breast cancerSemantic proximity Read

Subclassification of Breast Cancer through Comprehensive Multi-omics Data to Benefit Distinct Survival OutcomesSemantic proximity Read

Comprehensive multi-omics analysis of breast cancer reveals distinct long-term prognostic subtypesSemantic proximity Read

Genomic Machine Learning Model Predicts Radiation Therapy Benefit in Early-Stage Breast Cancer Patients with High AccuracySemantic proximity Read

Machine learning-driven identification and immunohistochemical validation of an integrated immune-inflammatory phenotype for disease-free survival stratification in breast cancer.Semantic proximity Read

Integrative analysis of epigenetic subtypes in acute myeloid Leukemia: A multi-center study combining machine learning for prognostic and therapeutic insightsSemantic proximity Read

Multi-Omics Prognostic Marker Discovery and Survival Modeling: A Case Study on Pan-Cancer Survival Analyses in Women’s CancersSemantic proximity Read

Immune-related gene data-based molecular subtyping related to the prognosis of breast cancer patients.Semantic proximity Read

Construction of a prognostic 6-gene signature for breast cancer based on multi-omics and single-cell dataSemantic proximity Read