Leveraging Machine Learning for Profiling Lipidomic Alterations in Breast Cancer Tissues: A Methodological Perspective

The lipidomic datasets utilized in this study comprise LC-MS (Liquid Chromatography-Mass Spectrometry) data in positive and negative modes, derived from breast tumor samples obtained through the METACancer FP7 project. The sample collection process and ethical approvals have been previously documented by Hilvo et al. and Denkert et al. The breast cancer samples were categorized based on the expression status of specific biomarkers: HER2, ER (Estrogen Receptor), and PR (Progesterone Receptor) (Metadata).