Single-cell Sequencing and Multi-omics Integration Reveals a Lipid Metabolism-Based Prognostic Model for 5-Fluorouracil Resistance in Breast Cancer

Background：Breast cancer is a major malignancy among women worldwide. Despite therapeutic advances, resistance to 5-fluorouracil (5-Fu) limits treatment efficacy. Lipid metabolism reprogramming may play a critical role in this resistance, but its mechanisms remain unclear. Methods：We integrated single-cell sequencing data and multi-omics analysis to explore molecular characteristics associated with 5-Fu resistance. Differential gene expression analysis and Cox regression were used to construct a prognostic risk model, validated in independent cohorts. Results：We developed a three-gene prognostic model (PDLIM4, SDC1, EMP1) with robust predictive performance. High-risk scores were associated with elevated lipid metabolism and distinct immune microenvironment features. Conclusion：Lipid metabolism reprogramming contributes to 5-Fu resistance in breast cancer. Our model offers a tool for risk assessment and a potential basis for therapeutic strategies targeting lipid metabolism.