ReviewFrontiers in immunology2026
Glycolytic reprogramming in ovarian cancer: mechanisms, immune crosstalk, and therapeutic implications.
Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer is characterized by extensive peritoneal dissemination, frequent recurrence, and chemoresistance. Glycolytic reprogramming has emerged as a central metabolic adaptation in ovarian cancer, but its significance extends beyond increased glucose consumption. In this review, we summarize how key glycolytic regulators, including GLUT1, HK2, PFKFB3, PDK1, and LDHA, are controlled by oncogenic, microenvironmental, and non-coding RNA-mediated pathways to reshape tumor metabolism. We emphasize that glycolysis supports ovarian cancer progression by promoting biosynthetic activity, redox balance, invasive dissemination, stem-like plasticity, and therapy resistance. Importantly, this review highlights glycolysis as an immunometabolic regulator of the ovarian tumor microenvironment. Lactate accumulation, macrophage reprogramming, IL-1β/NF-κB signaling, PD-L1 induction, and CD4+ T-cell metabolic remodeling collectively contribute to immune escape. Targeting glycolytic pathways may therefore provide therapeutic opportunities not only to suppress tumor growth but also to enhance chemotherapy and immunotherapy. However, metabolic heterogeneity, compensatory pathway activation, limited biomarkers, and insufficient clinical validation remain major challenges. A glycolysis-centered understanding of ovarian cancer may support biomarker-guided combination strategies and improve translational therapeutic design.
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