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Pyroptosis is a gasdermin (GSDM)-mediated lytic form of regulated cell death (RCD) that can either enhance antitumor immunity or maintain tumor-promoting inflammation, depending on the cellular source, signaling intensity, timing, and composition of the tumor immune microenvironment (TIME). Metabolic reprogramming, a hallmark of cancer, can regulate pyroptosis at multiple levels, including inflammasome priming, cysteine-aspartic protease (caspase) activation, GSDM expression and cleavage, membrane pore formation, and cytokine release. Conversely, pyroptosis may influence tumor metabolism through the release of interleukin-1 beta (IL-1β), interleukin-18 (IL-18), damage-associated molecular patterns (DAMPs), and extracellular vesicles (EVs), and may thereby alter nutrient utilization, oxygen availability, immune-cell recruitment, and inflammatory feedback loops; however, direct tumor-specific causal evidence for this reverse direction remains limited. This review advances beyond a pathway catalog by applying a four-level evidence hierarchy: Level I direct cancer-specific causality, Level II tumor-context cell-resolved mechanisms, Level III mechanistic evidence from non-cancer models, and Level IV correlative or computational associations. Further distinctions are made among cysteine-aspartic protease-1/gasdermin D (caspase-1/GSDMD), cysteine-aspartic protease-4/5/11/gasdermin D (caspase-4/5/11/GSDMD), cysteine-aspartic protease-3/gasdermin E (caspase-3/GSDME), cysteine-aspartic protease-8/gasdermin C/gasdermin D (caspase-8/GSDMC/GSDMD), and granzyme/gasdermin (Gzm/GSDM) axes, alongside an evaluation of the evidence supporting glucose, lipid, mitochondrial, epigenetic, and immunometabolic regulation. Finally, the review addresses potential reasons for the failure of pyroptosis-targeted metabolic therapies, identifies patient populations most likely to benefit or be harmed, and outlines how biomarker-guided trials should integrate GSDM activation, metabolic state, cytokine output, and TIME composition to translate this crosstalk into precision cancer therapy.
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He et al. (2026) studied this question.
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