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Unraveling regorafenib resistance: metabolic reprogramming, tumor plasticity, and novel approaches to overcome
Xiaokun Liu1, Xiao Gao1, Yuling Yang2
1Department of Biochemistry and Molecular Biology, School of Basic Medicine, Qingdao Medical College, Qingdao University, Qingdao, 266000, Shandong, P.R. China.
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.
Insights
Regorafenib resistance in cancers like HCC and CRC is a dynamic network rewiring process. Targeting key rewiring nodes and using combination therapies can overcome resistance for better outcomes.
Area of Science:
- Oncology
- Molecular Biology
- Cancer Therapeutics
Background:
- Regorafenib is a multi-kinase inhibitor effective in hepatocellular carcinoma (HCC), colorectal cancer (CRC), and gastrointestinal stromal tumors (GISTs).
- Emergence of resistance limits the long-term therapeutic benefits of regorafenib.
- Regorafenib resistance is a dynamic process involving adaptive network collapse and rewiring.
Purpose of the Study:
- To provide a systems-level understanding of regorafenib resistance mechanisms.
- To identify key nodes and pathways involved in adaptive resistance.
- To propose mechanism-guided combination therapies for overcoming regorafenib resistance.
Main Methods:
- Review of literature on regorafenib resistance mechanisms.
- Analysis of signaling network dynamics under regorafenib treatment.
- Conceptual framework organizing resistance mechanisms hierarchically.
Main Results:
- Regorafenib resistance involves initial signaling network collapse followed by compensatory rewiring via RTK bypass, cytokine feedback, and transcriptional reprogramming.
- Resistance mechanisms include drug-proximal adaptive signaling, network-level processes (epigenetics, transporters, cancer stemness), and downstream phenotypic adaptations (metabolism, EMT, autophagy, TME remodeling).
- Targeting key rewiring nodes like EGFR, STAT3, and microenvironmental pathways is crucial for overcoming resistance.
Conclusions:
- Regorafenib resistance is a complex, coordinated adaptive process.
- Targeting network rewiring nodes and employing combination therapies (e.g., with ICIs, metabolic modulators) are promising strategies.
- Biomarker-driven approaches are essential for personalized treatment strategies to improve clinical outcomes in regorafenib-treated patients.
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