Integration of single-cell and bulk RNA-seq via machine learning to reveal ferroptosis- and lipid metabolism-driven immune landscape heterogeneity and predict immunotherapy response in colon cancer

In this study, we conducted a comprehensive analysis of ferroptosis-lipid metabolism interactions in colon cancer by integrating bulk transcriptomic and single-cell RNA sequencing data. The prognostic model constructed on the basis of lipid metabolism and ferroptosis-related genes has potential as an independent prognostic biomarker for colon cancer patients and may serve as a predictor of immunotherapy response, facilitating the optimization of personalized therapeutic strategies.