Unraveling regorafenib resistance: metabolic reprogramming, tumor plasticity, and novel approaches to overcome therapy failure

Abstract

Regorafenib, a multi-kinase inhibitor, has demonstrated clinical efficacy in various malignancies, including hepatocellular carcinoma (HCC), colorectal cancer (CRC), and gastrointestinal stromal tumors (GISTs). However, the emergence of resistance significantly limits its long-term therapeutic benefits. Rather than representing isolated molecular events, regorafenib resistance can be conceptualized as a dynamic process of “adaptive network collapse and rewiring”. Owing to its broad inhibition of angiogenic, stromal, and tumor-intrinsic kinases, regorafenib induces an initial collapse of signaling networks, which subsequently drives compensatory rewiring through receptor tyrosine kinase (RTK) bypass activation, cytokine-mediated feedback, and transcriptional reprogramming. Within this framework, resistance mechanisms can be hierarchically organized into drug-proximal adaptive signaling (VEGFR-associated pathways and RTK bypass), network-level regulatory processes (epigenetic modulation, drug transporters, and cancer stemness), and downstream phenotypic adaptations, including metabolic reprogramming, epithelial–mesenchymal transition (EMT), autophagy, and tumor microenvironment remodeling. These processes function in a coordinated manner to restore network robustness under sustained pharmacological pressure. Importantly, this integrative perspective provides a rationale for therapeutic intervention. While downstream adaptations may contribute to resistance maintenance, targeting key nodes of network rewiring—such as EGFR, STAT3, and microenvironmental signaling pathways—may offer more effective and durable strategies. Accordingly, combination approaches integrating regorafenib with targeted agents, immune checkpoint inhibitors (ICIs), metabolic modulators, or emerging therapeutic platforms are discussed. Overall, this review provides a systems-level understanding of regorafenib resistance and highlights the importance of mechanism-guided combination therapies and biomarker-driven strategies to improve clinical outcomes.