This Special Issue aims to highlight recent advances in understanding the complex interplay among cancer metabolism, cell death, and signal cross talk, and to explore how these processes may be decoded through multiomics and translated into AI-driven cancer therapy. Metabolic reprogramming is a defining feature of malignant progression and influences proliferation, metastasis, immune escape, and treatment resistance. Concurrently, multiple forms of regulated cell death, including apoptosis, ferroptosis, necroptosis, pyroptosis, and autophagy-related death, are increasingly recognized as being tightly linked to metabolic states and intracellular signaling networks. Elucidating this multidimensional crosstalk is essential for identifying mechanistic vulnerabilities and novel therapeutic opportunities. This Special Issue welcomes original research and authoritative reviews employing genomics, transcriptomics, proteomics, metabolomics, and single-cell or spatial multiomics approaches to investigate these regulatory axes. Submissions addressing computational biology and artificial intelligence for biomarker discovery, patient stratification, and therapeutic prediction are also encouraged. Through integrating mechanistic insights with emerging technologies, this collection seeks to advance precision oncology and foster innovative strategies for cancer treatment.