Multimodal data integration in early-stage breast cancer.
Ontology highlight
ABSTRACT: The use of biomarkers in breast cancer has significantly improved patient outcomes through targeted therapies, such as hormone therapy anti-Her2 therapy and CDK4/6 or PARP inhibitors. However, existing knowledge does not fully encompass the diverse nature of breast cancer, particularly in triple-negative tumors. The integration of multi-omics and multimodal data has the potential to provide new insights into biological processes, to improve breast cancer patient stratification, enhance prognosis and response prediction, and identify new biomarkers. This review presents a comprehensive overview of the state-of-the-art multimodal (including molecular and image) data integration algorithms developed and with applicability to breast cancer stratification, prognosis, or biomarker identification
SUBMITTER: Llinas-Bertran A
PROVIDER: S-EPMC11973824 | biostudies-literature | 2025 Apr
REPOSITORIES: biostudies-literature
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