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Author Spotlight: Transmitochondrial Cybrid Generation Using Cancer Cell Lines
Published on: March 17, 2023
Exploiting metabolic vulnerabilities in cancer: From mechanisms to therapeutic opportunities
Zeng-Rong Xue1, Yuan-Yuan Xin1, Wei-Lin Jin1
1Institute of Cancer Neuroscience, Medical Frontier Innovation Research Center, The First Hospital of Lanzhou University, The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, PR China.
Abstract:
Metabolic reprogramming enables cancer cells to adapt to hostile microenvironments and resist therapy, while simultaneously revealing metabolic vulnerabilities that offer new opportunities for targeted treatment. This review is the first to propose a unified 'Mechanism-Strategy-Translation' framework, focusing on two core mechanisms underlying metabolic vulnerability: metabolic inflexibility and synthetic lethality. This dual-axis model not only elucidates how metabolic reprogramming drives tumor progression but also highlights the "Achilles' heel" of malignant tumors. The article provides an in-depth discussion of key metabolic pathways on which tumors depend (such as glucose metabolism), epigenetic regulation (e.g., lactylation), and multi-layered stress defense mechanisms-including autophagy, redox homeostasis, anti-ferroptosis, and cuproptosis-while dissecting their inherent vulnerabilities. Furthermore, it emphasizes the tripartite crosstalk among neural, immune, and metabolic components within the TME, systematically explaining how neural signals, immunometabolic reprogramming, and key metabolites collectively regulate tumorigenesis, along with a commentary on the role of microbiota in the TME. Based on these mechanisms, we summarize several emerging targets with clinical translational potential, providing clear directions for future research. Strategies such as combination therapies and dietary interventions are also considered highly promising. Despite ongoing challenges such as metabolic heterogeneity, the deepening integration of multidisciplinary approaches and advances in AI-driven multi-omics analyses are paving the way for transformative prospects in cancer therapy.
Insights
Cancer cells reprogram metabolism to survive, creating vulnerabilities. This review introduces a framework to target cancer
Area of Science:
- Oncology
- Metabolic pathways
- Cancer biology
Background:
- Cancer cells exhibit metabolic reprogramming to adapt to the tumor microenvironment (TME) and resist therapies.
- This adaptation reveals specific metabolic vulnerabilities exploitable for cancer treatment.
Purpose of the Study:
- To propose a unified 'Mechanism-Strategy-Translation' framework for understanding and targeting cancer metabolic vulnerabilities.
- To elucidate the roles of metabolic inflexibility and synthetic lethality in tumor progression.
- To review key metabolic pathways, epigenetic regulation, stress defense mechanisms, and TME crosstalk in cancer.
Main Methods:
- Review of existing literature on cancer metabolism, focusing on core mechanisms and vulnerabilities.
- Analysis of metabolic pathways, epigenetic modifications (e.g., lactylation), and stress response systems (autophagy, redox homeostasis, ferroptosis, cuproptosis).
- Examination of the interplay between neural, immune, and metabolic components within the TME, including microbiota.
Main Results:
- Identified metabolic inflexibility and synthetic lethality as key drivers of metabolic vulnerability in cancer.
- Detailed the contribution of glucose metabolism, lactylation, autophagy, redox homeostasis, anti-ferroptosis, and cuproptosis to tumor progression.
- Highlighted the tripartite crosstalk in the TME and the role of microbiota in regulating tumorigenesis.
Conclusions:
- The 'Mechanism-Strategy-Translation' framework provides a novel approach to understanding cancer metabolic vulnerabilities.
- Emerging targets and strategies, including combination therapies and dietary interventions, show clinical translational potential.
- Multidisciplinary approaches and AI-driven multi-omics analyses are crucial for overcoming challenges like metabolic heterogeneity and advancing cancer therapy.
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