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Immunometabolic interactions in gynecologic cancers: Mechanisms, biomarkers, and therapeutic implications
Agapiti H Chuwa1, David H Mvunta2,3
1Department of Physiology, University of Dar es Salaam, Mbeya College of Health and Allied Sciences, Tanzania.
Abstract:
This narrative review synthesizes current evidence on immunometabolic interactions in gynecologic cancers, with emphasis on their implications for tumor biology, therapeutic response, and global cancer care. Emerging data indicate that systemic metabolic dysfunction is closely integrated with tumor microenvironment immune remodeling. Key features include enhanced glycolysis, nutrient competition, lipid accumulation, and hypoxia, which collectively impair cytotoxic T-cell function, promote immune exhaustion, and support immunosuppressive myeloid phenotypes.Although gynecologic malignancies share common immunometabolic hallmarks, distinct tumor-specific patterns are evident. Cervical cancer is characterized by human papillomavirus-associated metabolic reprogramming and immune checkpoint activation; ovarian cancer demonstrates dependence on lipid metabolism and omental adipose interactions; and endometrial cancer is strongly associated with obesity-driven insulin resistance and endocrine-inflammatory signaling. This review evaluates potential biomarkers and therapeutic strategies, including metformin, statins, and immune checkpoint inhibitor-based combinations, and clearly distinguishes between preclinical findings and clinically established interventions. Current evidence for metabolic targeting remains largely exploratory, with variable degrees of clinical validation across tumor types. In addition, this review highlights implementation challenges in low- and middle-income countries, particularly limited access to advanced molecular diagnostics and immunotherapies, and discusses opportunities for scalable, low-cost metabolic approaches. Finally, we outline future research priorities, including spatial multiomics, longitudinal metabolic profiling, and computational modeling approaches to improve patient stratification and predictive accuracy. Overall, immunometabolism represents a promising but evolving framework for improving understanding and management of gynecologic cancers, with important implications for both precision oncology and global health equity.
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