Overcoming cancer immunotherapy barriers via nanomaterial-mediated pyroptosis

Abstract

While cancer immunotherapy has achieved groundbreaking clinical success, its efficacy is frequently compromised by insufficient T-cell activation, the immunosuppressive tumor microenvironment (TME), and off-target toxicity. Pyroptosis, a highly immunogenic form of programmed cell death characterized by gasdermin-mediated pore formation, massive cytokine release (e.g., IL-1β and IL-18), and robust dendritic cell activation, offers a compelling strategy to overcome these limitations. This review critically examines how nanotechnology-enabled pyroptosis induction can potentiate immunotherapy by (1) classifying pyroptosis-inducing nanomaterials into five combinatorial therapeutic platforms – immune checkpoint inhibitors, vaccine adjuvants, oncolytic virus-coupled systems, innate immune sensitizers, and multi-modal hybrids; (2) elucidating their mechanisms in reshaping the TME via pyroptosis-induced immunogenicity and bystander immune cell activation; and (3) highlighting unresolved challenges, including tumor-intrinsic pyroptosis resistance, nanoparticle biodistribution barriers, and cytokine storm risks. By integrating fundamental insights with translational perspectives, this work provides a strategic framework for developing pyroptosis-nanotechnology synergies to achieve precision immune modulation.

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1. Introduction

The immune escape mechanisms of malignant tumors and the immunosuppressive tumor microenvironment (TME) constitute fundamental challenges limiting the efficacy of conventional therapeutic approaches. The clinical translation of immunotherapeutic strategies, including immune checkpoint inhibitors (ICIs), adoptive cell therapies (ACTs), cancer vaccines, oncolytic viruses (OVs), and cytokine therapies, has ushered tumor treatment into the era of “Immunotherapy 2.0”. Nevertheless, current therapies still confront critical challenges, including low response rates, TME-mediated immunosuppression, insufficient targeting specificity, and systemic toxicity. For instance, ICI efficacy depends on pre-existing tumor-infiltrating lymphocytes (TILs) but often fails in “cold” tumors due to insufficient antigen presentation; ACT requires improvement in the persistence and homing capacity of engineered T cells; cancer vaccines remain constrained by carrier-dependent antigen delivery and cross-presentation efficiency; while OVs face the dilemma between host immune clearance and tumor-selective penetration. Although cytokine therapies exert antitumor effects through direct immune cell activation, their clinical application is constrained by high-dose-induced systemic toxicity, efficacy fluctuations from short half-lives, and nonspecific expansion of pro-tumorigenic immunosuppressive cells (Fig. 1). In this context, developing innovative strategies to remodel the immune microenvironment, enhance antitumor immunity, and overcome delivery/safety limitations of current therapies has emerged as a paramount scientific challenge in the field.

Fig. 1 Current cancer immunotherapies exhibit inherent limitations. Pyroptosis-driven immune activation synergized with immunotherapies overcomes these barriers to amplify antitumor efficacy, where nanomaterial-enabled platforms critically facilitate this synergy (by Figdraw).

Programmed cell death (PCD) is a critical regulator of diverse biological processes, particularly in carcinogenesis and tumor therapy.¹ Among the three well-defined PCD forms—pyroptosis, apoptosis, and necroptosis—all can eliminate malignant cells and expose tumor antigens to potentially stimulate antitumor immunity. However, their immunogenicity diverges substantially (Table 1). Unlike apoptosis or necroptosis, pyroptosis triggers robust inflammatory responses through gasdermin (GSDM)-mediated pore formation and the massive release of damage-associated molecular patterns (DAMPs). This unique pro-inflammatory property enables pyroptosis to efficiently initiate dendritic cell (DC) maturation, cytotoxic T lymphocyte (CTL) activation, and natural killer (NK) cell recruitment, thereby converting immunologically “cold” tumors into “hot” microenvironments. This superior immunogenic capacity—evidenced by amplified antigen presentation and overridden immunosuppressive signals—positions pyroptosis as a research hotspot in cancer immunotherapy. Consequently, pyroptosis provides a mechanistic rationale for designing nanomaterials that exploit immunogenic cell death to potentiate antitumor immunity. Pyroptosis induces cell membrane pore formation mediated by GSDM family proteins, leading to cellular swelling, rupture, and massive release of DAMPs and pro-inflammatory cytokines, thereby triggering robust antitumor immune responses. Currently, identified pyroptosis activation pathways can be categorized into three types: (1) canonical pathway: nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome activation by pathogen-associated molecular patterns (PAMPs) or danger signals, leading to caspase-1-mediated cleavage of gasdermin D (GSDMD) N-terminal domains for pore formation; (2) non-canonical pathway: an intracellular lipopolysaccharide (LPS) directly activates caspase-4/5/11 to cleave GSDMD; (3) alternative regulatory pathways: including chemotherapy-induced caspase-3 cleavage of GSDME or granzyme B-mediated activation of GSDMC/GSDME. Notably, pyroptosis not only induces tumor cell death but also substantially alleviates the immunosuppressive status of the TME through released inflammatory mediators, thereby providing multiple synergistic entry points for combination immunotherapy.

Table 1 Comparison of immunogenicity among three types of programmed cell death

Cell death	Key triggers	Immunogenicity	TME impact
Pyroptosis	GSDMs, caspases	High (DAMPs/cytokine release)	Promotes DC maturation and T-cell priming
Apoptosis	Caspase-3/7	Low (limited DAMPs)	Tolerogenic TME
Necroptosis	RIPK3/MLKL	Moderate	Mixed inflammation

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At the level of antitumor immune regulation, pyroptosis exerts synergistic effects through three-pronged mechanisms: first, DAMPs such as high-mobility group protein B1 (HMGB1) and adenosine triphosphate (ATP) released during pyroptosis activate DCs to enhance antigen presentation, promoting cross-presentation of tumor-associated antigens (TAAs) and thereby amplifying CTL activation and tumor infiltration. Second, cytokines including interleukin 1β (IL-1β) and IL-18 induce Th1-polarized immune responses, stimulating interferon-γ (IFN-γ) production to counteract immunosuppression mediated by regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). Moreover, emerging studies reveal that bacterial components or pyroptotic tumor cell debris can trigger pyroptosis in tumor-infiltrating immune cells (such as tumor-associated macrophages, TAMs). This directly reshapes the TME's cellular composition by eliminating immunosuppressive cell subsets. These properties enable pyroptosis induction strategies to overcome current immunotherapy limitations through three dimensions: antigen exposure, inflammatory priming, and immune cell reprogramming.

To address these critical challenges in immunotherapy, this review introduces a structured analytical framework centered on three pillars: (1) therapeutic limitations of current approaches, (2) pyroptosis-mediated immune activation mechanisms, and (3) nanotechnology-enabled combination strategies (Fig. 1). We first provide a comprehensive analysis of existing immunotherapies and their molecular underpinnings, highlighting key clinical barriers. Next, we elucidate how canonical, non-canonical, and other pyroptotic pathways can remodel the TME through enhanced antigen presentation and immune cell recruitment. Building on these insights, we present a classification system for pyroptosis-inducing nanomaterials, categorizing them into four strategic platforms: (1) ICI-potentiating systems, (2) vaccine-adjuvant platforms, (3) OV hybrids, and (4) innate immune modulator conjugates (Table 2). Finally, we critically evaluate translational challenges, including tumor-intrinsic pyroptosis resistance, nanoparticle delivery limitations, cytokine release management, and substantial complexity in clinical translation feasibility, while proposing nanomaterial-based solutions. This work not only synthesizes fundamental mechanisms and clinical gaps but also provides a roadmap for developing precision nanotherapeutics that harness pyroptosis to revolutionize combination immunotherapy.

Table 2 An overview of pyroptosis-inducing nanomaterials based on different classifications of combination immunotherapy

Therapy type	Limitation	Nanomaterials	Cancer cell lines	Mechanisms	Ref.
Immune checkpoint inhibitors	The irAEs/checkpoint therapy resistance	HCS-FeCu	4T1	Pyroptosis regulates the immunosuppressive TME combined with anti-PD-1	140
		R@L-MRS17	4T1	Co-deliver pyroptosis inducers and macrophage-modulating drugs	141
		PMTPN	4T1	Co-deliver pyroptosis inducers and B cell-modulating drugs	142
		GSDMBNT mRNA@LNPs	HeLa, 4T1, B16F10	Combination therapy of GSDMB-mediated pyroptosis with anti-PD-1	143
Cancer vaccines	Delivery/immunogenicity-safety balance	Cu-THBQ/AX	4T1	Relieving immunosuppressive tumors via hindering efferocytosis of macrophages and promoting pyroptosis of cancer cells	144
		CDs	B16, EMT6, 4T1	A large number of in situ tumor vaccines were formed after photodynamic-induced pyroptosis	145
		Pyo-R@Gel	4T1, B16F10	Pyroptotic vesicles as tumor antigens drive potent antitumor immunity	146
Oncolytic viruses	TME/neutralizing antibodies/tumor heterogeneity	MPNPs	4T1, 4MOSC2	OVs combined with pyroptosis induces nanoprodrugs to activate pyroptosis to exert antitumor immunity	147
		ACNPs	4T1, SCC7, 4MOSC1	OVs combined with epigenetic strategies activate pyroptosis to exert anti-tumor immunity	148
Innate immune regulation	The level of activation varied greatly	NP1 + NP2	4T1, MCF-7	Photodynamic activation of pyroptosis and epigenetic activation of the cGAS-STING pathway jointly exert antitumor immunity	149
		CoF2 NN	4T1, CT26	Sonodynamic therapy simultaneously induces pyroptosis and activates the cGAS-STING pathway to exert antitumor immunity	150
Combination therapy	The irAEs and uncertainty of treatment effect	R@AZOH	CT26, B16-OVA	Pyroptosis activation combined with a variety of immunotherapy plays an antitumor role	151

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2. Limitations of current immunotherapy modalities

Clinical observations of complete remission in advanced cancers following acute bacterial infections have advanced tumor biology understanding, highlighting the dual need to target malignant cells and modulate the TME immunologically. This shift propelled immunotherapies as transformative interventions. Tumors are classically stratified into three immune phenotypes: immune-inflamed (abundant intratumoral immune infiltration), immune-excluded (T cells restricted to stroma), and immune-desert (minimal immune presence). Tumors evade immunity via disrupted antigen presentation, immune checkpoint activation, and immunosuppressive TME establishment. Consequently, diverse immunotherapeutic modalities now target vulnerabilities across the cancer-immunity cycle. While immunotherapies confirm the immune system's fundamental role across cancer types and stages, clinical responses predominantly occur in immune-inflamed phenotypes. To establish the rationale for pyroptosis-focused nanotherapeutics, we first delineate the fundamental constraints of existing immunotherapies.

2.1 Immune checkpoint inhibitors

T cell dysfunction within tumors manifests as the accumulation of hypofunctional terminally differentiated exhausted T (Tex) cells.² Tex cells acquire a drug-resistant epigenetic state refractory to reversal,^3–5 characterized by the characteristic overexpression of co-inhibitory receptors, specifically cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed death-1 (PD-1), lymphocyte-activation gene 3 (LAG-3), and T-cell immunoreceptor with Ig and ITIM domains (TIGIT). These surface molecules are collectively known as immune checkpoints.

ICIs restore antitumor immunity by disrupting co-inhibitory signaling, forming a cornerstone of immuno-oncology.^6,7 CTLA-4 intrinsically attenuates TCR signaling and extrinsically competes with CD28 for B7 ligands,⁸ critically supporting Treg functions;⁹ ipilimumab, the first FDA-approved CTLA-4 inhibitor (2010),¹⁰ thus targets both effector T cells and Tregs. PD-1 primarily suppresses T cells by inhibiting the TCR-CD28 co-stimulatory pathway;¹¹ tumor cell PD-L1 upregulation exploits this axis for immune evasion, establishing the PD-1 blockade (e.g., nivolumab, initially approved in 2014) as a fundamental TME therapy effective across multiple cancers.^12–16 LAG-3 promotes T cell exhaustion similarly to PD-1,^17–19 with its inhibition by blocking LAG-3/pMHC-II interactions,²⁰ representing a therapeutic strategy requiring ligand-induced activation.²¹ TIGIT contributes to immune evasion by competitively binding CD155/CD112 and inhibiting costimulation; its hyperactivation correlates with the NK cell dysfunction in diffused large B-cell lymphoma, though targeting clinically remains challenging. Combination immunotherapy surpasses monotherapy efficacy: the PD-1/LAG-3 blockade drives Treg conversion to effectors,²² while CTLA-4/PD-1 inhibitors exhibit complementary activity targeting distinct T-cell activation phases^23–26 despite increased toxicities.²⁷ Bispecific antibodies mitigate toxicity,^24,28 and rationally designed combinations (e.g., anti-CTLA-4 + anti-PD-1 + IL-2) significantly amplify efficacy when manageable.²⁹

Despite revolutionizing oncology and enabling unprecedented long-term remissions in some patients, ICIs face significant clinical and biological limitations. Recent cross-sectional analytical studies on ICI response rates revealed that only 12.5% of eligible patients achieved clinical benefits in 2018.³⁰ Real-world evidence demonstrates persistent therapeutic limitations, with 60–70% of melanoma patient cohorts exhibiting the highest ICI responsiveness failing to manifest objective responses to PD-1 blockade therapy.^31,32 Their efficacy remains dichotomous, benefiting only a minority of patients while the majority experience treatment failure, attributable to four key factors below.³³ First, drug resistance significantly limits the proportion of patients achieving durable clinical remission. Second, the emergence of immune-related adverse events (irAEs) severely restricts the therapeutic utility of these agents, thereby substantially compromising clinical outcomes. Furthermore, the predictive biomarker development is inadequate. Not only are the accuracy and consistency of biomarkers influenced by multiple variables, but analytical methodologies are also subject to inherent limitations.³⁴

Therapeutic resistance to ICIs can be categorized into primary resistance and secondary resistance. Primary resistance refers to the initial non-responsiveness or lack of clinical responses to ICIs. In specific cancer contexts, the expression intensity of PD-L1 exhibits a positive correlation with ICI efficacy.^31,32,35 Consequently, tumors characterized by low PD-L1 expression are more likely to develop resistance to PD-1/PD-L1 inhibitor therapy. However, the non-linear correlation between PD-L1 expression quantitation and anti-PD-1/L1 therapeutic outcomes implicates the synergistic involvement of alternative molecular mechanisms. Another evidence-based biomarker, tumor mutational burden, drives primary checkpoint therapy resistance by associating not only with a high mutational load but also with dysregulation of critical signaling pathways such as the IFN-γ axis and MHC molecules. Furthermore, host gut microbiota compositional profiles and tumor epigenetic modifications have been demonstrated to mediate primary resistance.^36–38 Notably, immune cell subpopulation distributions within TMEs and peripheral circulation significantly correlate with post-ICI clinical prognoses. The inherent complexity of these predictive frameworks for primary resistance profoundly restricts ICI clinical utility. Beyond primary resistance, acquired (secondary) resistance arises through tumor clonal evolution or therapeutic pressure selection mechanisms. Aberrant antigen presentation machinery, exemplified by neoantigen expression loss-induced immune evasion, potentially serves as a pivotal mediator of acquired resistance.^39,40 The current understanding of specific molecular pathways underlying acquired resistance remains exploratory.

The irAEs, critical determinants of ICI treatment continuity, exhibit overall incidence rates of 30–60%, with 10–20% representing grade 3/4 severe toxicities.^41,42 Toxicity profiles demonstrate target specificity: CTLA-4 inhibitors predispose patients to hypophysitis and severe colitis, whereas PD-1 blockade correlates with elevated incidences of pneumonitis, thyroiditis, and nephritis. Notably, vitiligo development secondary to autoimmune targeting of melanocyte common antigens exhibits a positive correlation with improved objective response rates and overall survival in melanoma patients.⁴³

The significant heterogeneity across disease states, model systems, and patient clinical contexts not only contributes to suboptimal response rates to ICIs but also impedes the development of precision predictive biomarkers. The complexity in data interpretation and integration within current research further limits the establishment of robust biomarkers for broadly predicting individual patients’ therapeutic responses or resistance to ICIs. Beyond the biological complexity arising from tumor and patient heterogeneity—such as temporal dynamics within the TME and inter-individual immune status variation—which thereby restricts the generalizability of tissue biomarkers, limitations additionally stem from non-standardized pre-analytical variables as well as inherent technical constraints in standardized detection methods. Collectively, these factors constitute critical constraints hampering the clinical translation of ICIs.

In summary, tumor immune microenvironment heterogeneity subjects ICI efficacy to dynamic regulation by multiple biomarkers, compounded by marked interindividual variability. Under current limitations in mechanistic comprehension, these factors critically constrain ICI clinical implementation. The absence of post-resistance sequential therapeutic strategies exacerbates patient prognostic risks, while the unpredictable nature of irAEs and lack of effective preventive measures further amplify clinical uncertainties surrounding ICI regimens.

2.2 Adoptive cell therapy

ACT employs autologous T cells to eradicate tumors by isolating, genetically engineering, expanding ex vivo, and reinfusing them, thereby bypassing the need for endogenous tumor-specific T-cell reactivation required in conventional immunotherapies.⁴⁴ To overcome natural T cell receptor (TCR) affinity limitations, engineered platforms like TCR-T and chimeric antigen receptor (CAR) systems were developed; the CAR integrates antigen-binding domains directly with T-cell signaling modules.⁴⁵ CAR-T, the most advanced ACT modality, utilizes a synthetic receptor comprising an extracellular scFv, a hinge/transmembrane domain, and an intracellular signaling domain with co-stimulatory molecules. It demonstrates significant efficacy against hematologic malignancies, evidenced by six FDA-approved products targeting antigens like CD19 and BCMA.⁴⁶

CAR-T therapy for hematologic malignancies confronts three core challenges.^47,48 First, adverse events of CAR-T therapy include both acute and chronic toxicities. Acute manifestations primarily involve cytokine release syndrome (CRS), triggered by the in vivo expansion of anti-CD19 CAR-T cells and clinically characterized by fever, hypotension, and coagulopathies.^49,50 CRS management employs a tiered approach using the IL-6 receptor antagonist tocilizumab (FDA-approved first-line therapy) supplemented with glucocorticoids.^49,50 Concurrently, CAR-T cell penetration across the blood–brain barrier induces immune effector cell-associated neurotoxicity syndrome, presenting with reversible neurological symptoms including encephalopathy and seizures, for which glucocorticoids serve as the first-line treatment under ASTCT consensus guidelines.⁵¹ Chronic toxicities encompass: (1) persistent myelosuppression; (2) heightened infection susceptibility secondary to B-cell aplasia—resulting from on-target elimination of CD19⁺ normal B cells—manifesting as early bacterial infections, invasive fungal infections, and late respiratory viral infections;⁵² and (3) secondary myeloid malignancies.⁵³ Second, significant efficacy limitations manifest as high relapse/death rates, driven primarily by antigen escape and T-cell dysfunction in heavily pretreated patients, with resistant disease portending dismal outcomes. Third, severe accessibility barriers arise from protracted vein-to-vein times (13–54 days), impeding treatment access in 31% of patients due to manufacturing failures or disease progression during waits; compounded by costs exceeding hundreds of thousands of dollars and state-dependent medicaid coverage disparities, socioeconomic factors further exacerbate healthcare inequities for vulnerable populations through constraints like first-come-first-served models.⁵³

Despite transformative success in hematologic malignancies, CAR-T therapy confronts profound limitations in solid tumors that critically constrain its clinical applicability,⁵⁴ dominated by three fundamental barriers: (1) antigen heterogeneity and target specificity, wherein the scarcity of tumor-specific antigens (TSAs) necessitates reliance on TAAs with heterogeneous expression across tumor subclones—a challenge compounded by TAAs shared in normal tissues, which precipitates on-target/off-tumor toxicity (OTOT) and severely compromises therapeutic safety;⁵⁵ (2) a hostile TME characterized by immunosuppressive elements (e.g., TGF-β, Tregs, and MDSCs) that drive T cell exhaustion via inhibitory receptors, alongside physical barriers and pathological conditions that restrict T cell infiltration, persistence, and effector functions;⁵⁶ (3) functional attenuation of CAR-T cells due to chronic antigen exposure, which induces T cell dysfunction marked by diminished cytotoxicity, proliferative capacity, and premature exhaustion, further curtailing therapeutic durability.⁵⁷

To mitigate these constraints, multidimensional strategies focus on functional augmentation,⁵⁸ TME reprogramming,^59–62 and safety refinement. Despite promising preclinical results, intrinsic challenges persist—the complexity of solid tumor antigen landscapes remains a fundamental obstacle, with current systems lacking universal solutions for antigen heterogeneity. Furthermore, all clinically approved CAR-T products utilize second-generation architectures, exhibiting notable clinical limitations. Accelerating the translation of next-generation CAR-T technologies with enhanced safety profiles has thus become imperative.

2.3 Cancer vaccines

Cancer vaccine development has been a major research focus since the emergence of immunotherapy. A pivotal milestone occurred in 1990 with the first synthetic human tumor antigen vaccine,⁶³ while the 2021 SARS-CoV-2 mRNA vaccine success reinvigorated mRNA-based cancer vaccine research.⁶⁴ The clinical development of tumor vaccines now spans multiple trial phases across diverse cancers—including lung, breast, prostate, and melanoma plus challenging malignancies like pancreatic cancer and glioblastoma^65,66—with mRNA-based vaccines emerging as a primary research focus due to rapid production, customizability, and potent immunogenicity, evidenced by over 120 active clinical trials.^67,68

Categorized by functions, vaccines include preventive types targeting oncogenic viruses (e.g., HPV) and therapeutic versions enhancing tumor-specific immunity.⁶⁹ Therapeutic cancer vaccines are classified into four major categories based on antigen delivery platforms: cellular, peptide, bacterial/viral vector, and nucleic acid vaccines. Each category exhibits its characteristic limitations. Cellular vaccines—including engineered tumor cell vaccines and autologous DC vaccines—confront efficacy limitations in autologous formats due to immune tolerance from tumor heterogeneity or insufficient DC activation, while allogeneic versions incur elevated immunogenicity risks;^70,71 DC vaccines show broad potential, but only sipuleucel-T is FDA-approved despite substantial production investments.⁷² Peptide vaccines exhibit immunogenicity dependent on the peptide length (enhanced by chemical modifications); yet, none hold FDA approval despite ongoing phase I–III trials for multiple cancers, requiring optimization for stability.^73–77 DNA vaccines suffer suboptimal immunogenicity and efficacy due to nuclear delivery barriers,⁷⁸ whereas RNA vaccines’ transient bioavailability necessitates repeated dosing to sustain immune responses.⁷⁹ Bacterial vectors leverage tumor tropism but face biosafety and manufacturing hurdles for clinical translation,^80,81 and viral platforms—including efficacy-proven virus-like particles for virus-associated cancers—carry risks of immune hyperactivation, hypersensitivity, and host tissue cross-reactivity requiring rigorous epitope safety profiling to prevent autoimmune sequelae, with all platforms challenged by efficacy durability and scalability constraints.⁸²

Mechanistically, all therapeutic vaccines (cellular, peptide, vector, or nucleic acid-based) function through DC processing of tumor antigens and MHC presentation to T cells, enabling CD8⁺ cytotoxic T cells to recognize and eliminate tumor cells via MHC class I recognition. Consequently, the development of all cancer vaccines confronts the following challenges.^66,68,83,84 First, tumor-induced immunosuppression and immune evasion represent major obstacles, wherein immunosuppressive mechanisms within the TME substantially limit vaccine efficacy despite their ability to induce immune responses.⁸⁴ Second, inadequate antigen selection and immunogenicity pose critical issues: TAAs exhibit poor immunogenicity, eliciting suboptimal immune responses, while the scarcity of TSAs restricts broad applicability. For instance, TAA-based prostate cancer vaccines demonstrate limited survival benefits despite favorable safety profiles.⁸⁵ Third, suboptimal delivery systems remain problematic due to insufficient targeting precision and stability, impairing immunogenicity.⁸⁴ Fourth, tumor heterogeneity compromises treatment durability and breadth by generating diverse and unstable antigen expression patterns, resulting in variable patient responses. Fifth, clinical trial limitations—including small sample sizes, selection bias, and regulatory hurdles—constrain robust efficacy validation. While mRNA vaccines show promise, their long-term safety requires larger confirmatory studies.^66,84 Sixth, combination therapies with other immunotherapies present unresolved complexities regarding protocol optimization and toxicity management. Seventh, personalized vaccine development encounters prohibitive costs and technical demands involving high-throughput sequencing and bioinformatics. Ultimately, the difficulty in pinpointing high-risk vaccination groups for early intervention persists. Although immunogenicity in pre-cancerous lesions is promising, breast cancer prevention studies reveal that current risk stratification methods are insufficient to leverage this potential.^86,87

2.4 Oncolytic viruses

OVs replicate selectively in malignant cells due to TME advantages, enabling localized lysis and pro-inflammatory microenvironment induction to boost systemic antitumor immunity. The immunostimulatory magnitude depends on pre-existing host immunity toward viral/tumor antigens; attenuated immunity requires temporal adaptation for effective antigen recognition and response initiation, where persistent antigen exposure may sustain paradoxical immune activation.⁸⁸ Tumor heterogeneity critically governs therapeutic efficacy in oncolytic virotherapy. Genetic diversity within tumor tissues may engender therapeutic resistance or recurrence, potentially through mechanisms involving tumor cell resistance to viral infection or lytic activity. To address this challenge, researchers employ genetic engineering to optimize viral vector infectivity and replication kinetics. Current clinical OVs incorporate transgenes for pro-inflammatory cytokines to combat immunosuppression and enhance immunogenicity. Tumor-selective promoters (hTERT and survivin)^89–91 ensure safety by minimizing off-target toxicity. Viral infection-induced interferon/DAMP release enables synergistic combinations with other immunotherapies.

Despite these advancements, OV clinical translation faces multifaceted challenges. First, insufficient tumor-targeting efficiency arises from the inherent physical barriers of solid tumors, such as dense extracellular matrices and aberrant vasculature. Second, the generation of neutralizing antibodies and the hypoxic/acidic tumor core microenvironment may lead to peritumoral necrosis/calcification and impede viral penetration. Third, as replicative biological agents, OVs require rigorous biosafety evaluations to address risks, including potential genetic recombination and off-target effects. Finally, rapid tumor lysis-mediated antigen exposure may compromise viral persistence by accelerating immune clearance. Crucially, OVs inherently embody a dual paradox: they function both as therapeutic vectors requiring efficient delivery and as immunogenic targets subjected to host immune elimination. This dichotomy underscores the core challenge in oncolytic virotherapy: achieving a dynamic equilibrium between viral cytolytic efficacy and immune-mediated viral clearance—a pivotal scientific hurdle requiring resolution.

2.5 Cytokine therapies

Cytokines are immune-mediated signaling molecules coordinating antigen-specific responses through complex networks.⁹² Over 100 cytokines regulate homeostasis and host defense, with tumor microenvironmental networks offering therapeutic targets. Cancer-associated fibroblasts (CAFs) establish protumorigenic niches via IL-6, CXCL12, and LIF secretion,⁹³ while TAMs accelerate malignancy through IL-1β/IL-6/IL-23 and induce angiogenesis via VEGF/IL-8. Conversely, IL-2 and IFNs (α/γ) demonstrate antitumor potential.⁹⁴ This dichotomy necessitates therapeutic strategies to balance immunostimulation with pathological overexpression control.

Recently, limited cytokine-based agents have received clinical approval for oncological applications, including granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-2, and IFN-α (components of sipuleucel-T vaccine), and the novel IL-15Fc fusion protein for localized bladder cancer therapy.⁹⁵ However, systemic administration of IL-2 and IFN-α frequently induces significant toxicity due to microenvironmental complexity,⁹⁶ necessitating optimization of localized delivery approaches. Compounding these challenges are inherent pharmacokinetic instability and tumor immune infiltration heterogeneity, substantially restricting clinical applicability. To counteract pathological overexpression, highly selective JAK kinase inhibitors have emerged as cornerstone therapeutic tools in cytokine inhibition strategies. JAK kinase inhibitors effectively suppress downstream signaling of pro-inflammatory cytokines (IL-6, IL-17, and IFN-γ) through the JAK-STAT axis blockade. The principal challenge in cytokine inhibition strategies lies not in drug availability but in identifying therapeutically actionable single cytokine targets or signaling pathways. The monotherapy cytokine blockade often fails to restore the immune balance. However, polypharmacological interventions risk unforeseen systemic consequences—including global immune impairment, compensatory pathway activation-mediated resistance, and potential oncogenic escalation.⁹⁷

3. Molecular mechanism of pyroptosis

Based on the limitations of current immunotherapies, inducing pyroptosis—a highly immunogenic form of inflammatory cell death—has emerged as a promising strategy to potentiate antitumor immunity by converting immunologically inert tumors into inflamed microenvironments. Pyroptosis, also known as inflammatory necrosis, is a new type of PCD, which has significant differences from apoptosis and necrosis.⁹⁸ It is mediated by GSDM proteins, which cause cell swelling, membrane perforation, and the release of inflammatory cytokines (such as IL-18 and IL-1β).⁹⁹ According to current research, there are three main molecular mechanisms of pyroptosis: canonical pathways (dependent on caspase-1), non-canonical pathways (dependent on caspase-4/5/11), and other pathways.¹⁰⁰

3.1 Canonical pathway

The canonical pathway induced by caspase-1 can be divided into two steps (Fig. 2). The activation and assembly of inflammasomes is the first step.^101,102 A variety of inflammasomes have been found, including NLRP1 inflammasome, NLRP3 inflammasome, NLRC4 inflammasome, PYRIN inflammasome, and AIM2 inflammasome.¹⁰³ As a multi-molecular complex, inflammasomes consist of pattern recognition receptors (PRRs, also known as inflammasome sensors), apoptosis-associated speck-like proteins (ASC), and downstream effector caspases.¹⁰¹ When the host immune system resists pathogenic microbial infection or internal damage factors, inflammasomes are activated and promote the development of adaptive immune responses. Inflammasomes primarily respond to PAMPs of invading pathogens and DAMPs of endogenous molecules released by the body's cell death at this point. A new nanoparticle-associated molecular pattern has also been identified in recent studies.¹⁰⁴ PRRs primarily comprise toll-like receptors (TLRs), nucleotide-binding oligomerization domain-like receptors (NLRs), retinoic acid-inducible gene-I-like receptors (RLRs), C-type lectin receptors (CLRs), and AIM2-like receptors (ALRs).^105,106 The ASC primarily functions as a bridging adaptor in inflammasomes by connecting PRRs and downstream effector caspases. The caspase-associated recruitment domain (CARD) and the pyrin domain are the two main structural domains of the ASC. Initiator or inflammatory caspases are recruited to activate platforms via homotypic CARD–domain interactions with adaptor proteins. Their subsequent dimerization and auto-cleavage activate downstream effector caspases or inflammatory substrates. In the second step, the precursor of caspase-1 (pro-caspase-1) is recruited by the aggregated ASC, which activates caspase-1 and cleaves it into two fragments, forming a dimer and becoming mature caspase-1.¹⁰² On the one hand, caspase-1 cleaves the executioner protein GSDMD at the Asp275 site, forming a 22 kDa C-terminal (GSDMD-C) and a 31 kDa N-terminal (GSDMD-N). GSDMD-N penetrates the cell membrane and forms non-selective pores with an inner diameter of about 10–14 nm, causing cell swelling and rupture, releasing secreted pro-inflammatory mediators such as HMGB1 and IL-α, and triggering pyroptosis.^107,108 On the other hand, caspase-1 also cleaves the precursors of IL-1β and IL-18 into mature IL-1β and IL-18, which are released through the pores formed by GSDMD, triggering an inflammatory response.

Fig. 2 Basic mechanisms of canonical and noncanonical pathways. Reproduced with permission from ref. 102. Copyright 2022, Springer Nature.

3.2 Noncanonical pathway

The non-canonical inflammasome pathway differs from the canonical inflammasome pathway in that it does not require the involvement of the inflammasome and is directly induced by murine caspase-11 and human caspase-4/5.¹⁰⁹ These caspases are activated by the inflammatory stimulator LPS, which is derived from Gram-negative bacteria and consists of three main components: lipid A, a core oligosaccharide chain, and a variable polysaccharide chain (O antigen).¹¹⁰ In mice, caspase-11 possesses a CARD that directly and specifically recognizes the lipid A portion of the LPS in the cytoplasm, and the two have a high affinity for each other. This recognition leads to the activation of caspase-11, which then triggers pyroptosis and cleaves GSDMD to activate caspase-1.¹¹¹ Caspase-4 and caspase-5 (human) and caspase-11 (murine) are functionally conserved but non-identical orthologues that detect cytosolic LPS via CARDs. Activation of the non-canonical inflammasome pathway relies on direct LPS (lipid A) binding-triggered oligomerization of these caspases via their CARDs, leading to the proteolytic cleavage of GSDMD and subsequent pyroptosis. This cascade operates independently of canonical inflammasome adaptors but may activate NLRP3.

Activated caspase-4/5/11 cleaves the GSDMD to generate GSDMD-N, which punches holes in the cell membrane.¹¹² The formed pores lead to K⁺ efflux, activation of the NLRP3 inflammasome, and caspase-1. Although caspase-4/5/11 is not directly involved in the processing of IL-1β or IL-18, it can participate in their processing by initiating the assembly of the inflammasome through K⁺ efflux induced via GSDMD, generating positive feedback regulation accompanied by HMGB1 and IL-α release.¹¹³ Another protein that is involved in this pyroptosis pathway is pannexin-1,¹¹⁴ which is highly expressed in many tissues and functions as a non-selective membrane channel for large molecules. Among the various molecules that pass through this channel, ATP and nucleotides play important roles in the inflammatory response. When caspase-11 catalytically cleaves pannexin-1, it activates this channel, leading to the release of ATP. This released ATP can then activate the purinergic receptor P2X7, which is a ligand-gated ion channel. Through the activation of P2X7, K⁺ and Na⁺ ions can then efflux, and Ca²⁺ can then flow inward, ultimately triggering pyroptosis. Therefore, pannexin-1 is a key protein in the LPS-triggered caspase-11-mediated pyroptosis pathway.^115,116

3.3 Other pathways

In addition to GSDMD, which can trigger pyroptosis, many studies have demonstrated that GSDME can also cause pyroptosis and elucidated its mechanism (Fig. 3).¹¹⁷ GSDME was previously thought to be associated with apoptosis due to its ability to modulate mitochondrial translocation, permeabilization, and pore formation. Some cells with high expression of GSDME undergo pyroptosis after the activation of caspase-3 by chemotherapeutic agents.¹¹⁷ The experiment further confirmed that caspase-3 not only initiates apoptosis but also cleaves GSDME to liberate its N-terminal domain, resulting in membrane pore formation.¹¹⁸ GSDME acts as a “switch” between the two modes of cell death.¹¹⁹

Fig. 3 Mechanisms of pyroptosis regulated by other GSDM proteins. Reproduced with permission from ref. 102. Copyright 2022, Springer Nature.

Furthermore, in the course of Yersinia infection, caspase-8 induces pyroptosis by cleaving GSDMD when the Yersinia effector Yop J suppresses transforming growth factor-β-activated kinase 1.¹²⁰ It eventually activates pro-caspase-8, receptor-interacting serine/threonine-protein kinase 1, and Fas-associated death domain cell death complex, triggering caspase-8-mediated pyroptosis.¹²¹ Moreover, caspase-8 can facilitate the cleavage of GSDMC, liberating the GSDMC-N fragment that enhances pyroptosis.^122,123 Furthermore, recent studies reveal that during cytotoxic lymphocyte-mediated killing of target cells, granzyme A (GZMA) enters target cells via perforin and specifically cleaves GSDMB at Lys229 and Lys244 (primarily at Lys244), releasing its N-terminal domain (GSDMB-N).¹²⁴ This discovery revises the notion that pyroptosis can only be activated via caspase, uncovering for the first time that GSDMs can perform pore formation through GZMA hydrolysis at non-aspartic acid sites, officially recognizing cytotoxic lymphocyte-induced cell death as pyroptosis.¹²⁵ In 2024, researchers demonstrated that severe starvation triggers pyroptosis via phosphorylation-induced activation of GSDMA. Nutrient stress promotes GSDMA activation through phosphorylation mediated by Unc-51-like autophagy-activating kinase 1 (ULK1). Phosphorylation of Ser353 on human GSDMA by ULK1 or the phospho-mimetic Ser353Asp mutant of GSDMA liberates GSDMA from auto-inhibition, facilitating its membrane targeting and initiation of pyroptosis.¹²⁶

4. Pyroptosis enhances tumor therapy

Pyroptosis plays dual roles in cancer: while chronic inflammation from sustained pyroptosis elevates the oncogenic risk, targeted induction of pyroptosis via inflammasomes triggers tumor cell death and suppresses proliferation/metastasis, offering a promising immunogenic strategy for cancer therapy. By leveraging GSDM-driven pore formation, pyroptosis exerts its antitumor efficacy primarily through two synergistic axes. Firstly, pyroptosis directly induces tumor cell death through cellular swelling, pore formation on the plasma membrane, and eventual rupture.¹²⁷ Secondly, pyroptosis can mediate and enhance antitumor immunity. Recent studies have found that pyroptosis of less than 15% of tumor cells is sufficient to eliminate the entire 4T1 breast tumor graft.¹²⁷ In terms of enhancing antitumor immunity, pyroptosis reprograms the suppressive TME. Despite the strong immunosuppressive conditions in the TME, pyroptosis has been shown to switch the TME from being suppressive to becoming an antitumor environment, which is fundamental to enhancing antitumor immunity.¹²⁸ Pyroptotic tumor cells enhance the phagocytosis of tumor cells by TAMs, indicating that pyroptosis enhances the immune response in the TME.¹²⁷ Tumor cell pyroptosis can also recruit tumor-associated T cells and activate DC infiltration, particularly in response to v-raf murine sarcoma viral oncogene homolog B inhibitors and mitogen-activated protein inhibitors.¹²⁹ Single-cell RNA sequencing data further supports the positive impact of pyroptosis on the immune response in the TME. GSDMA-mediated tumor cell pyroptosis increases populations of CD4⁺ T cells, CD8⁺ T cells, NK cells, and M1 macrophages while decreasing populations of monocytes, neutrophils, MDSCs, M2 macrophages, and CD4⁺FOXP3⁺ T regulatory cells.¹²⁵ This indicates that pyroptotic tumor cells actively reprogram the immune cells present in the TME. Furthermore, when combined with ICI therapy, pyroptotic tumor cells can sensitize tumors to anti-PD1 therapy, leading to enhanced tumor suppression. In “cold” tumors such as 4T1 tumors, which are unresponsive to anti-PD1 treatment, pyroptosis-inducing therapies have the potential to convert these tumors into “hot” tumors, improving the efficacy of anti-PD1 treatment and reducing tumor volume and weight. Overall, the evidence presented demonstrates that pyroptotic tumor cells can reprogram the suppressive TME towards an antitumor immune response, providing a potential avenue for enhancing immunotherapies against cancer.¹²⁷

Currently, there are three main pathways for cell pyroptosis-mediated and enhanced antitumor immunity reported. First, pyroptosis promotes the maturation of antigen-presenting cells such as DCs and TAMs. DCs can phagocytose tumor antigens and cross-present them to CD8⁺ T cells, but they need to be activated by DAMPs or cytokines.¹³⁰ These DAMPs can activate DCs through various receptors such as TLRs, myeloid differentiation primary response protein 88 (MyD88), or P2X7 purinergic receptors, enhancing their ability to process and present tumor antigens.¹³¹ Pyroptotic tumor cells can enhance DC functions to initiate antitumor immunity through the release of DAMPs such as heat shock proteins, HMGB1, CRT, or ATP, into the TME after cell lysis.¹³² Studies have reported that pyroptotic tumor cells can enhance the in vivo phagocytosis of tumor cells by TAMs by releasing various DAMPs instead of cytokines. Pyroptotic leukemia cells induced by CAR-T cells can release cytokines such as IL-1β by activating macrophages through NLRP3 inflammasome activation and ATP release.¹³³ The HMGB1 released by pyroptotic tumor cells can also induce the differentiation of pro-inflammatory M1-like macrophages.¹³⁴ Of course, it ends with a question of whether macrophages can also cross-present tumor antigens after engulfing pyroptotic tumor cells.

The second pathway is the release of pro-inflammatory cytokines such as IL-1β and IL-18. IL-1β released by pyroptotic cells is a key cytokine that induces T cell differentiation, long-lived memory T cell generation, and effector T cell function activation. IL-1β binding to the IL-1 receptor, highly expressed on naive and memory CD4⁺ T and CD8⁺ T cells, can induce naive T cell polarization towards T helper cells (TH1 and TH17) through the MyD88-STAT-dependent signaling pathway. In addition, IL-1β can promote the generation of strong and persistent primary and secondary antigen-specific CD4⁺ T and CD8⁺ T cell responses.¹³⁵ In addition, IL-1β endows CD8⁺ T cells with effector-like genes (Gzmb, Gzma, Prf1, Il2ra, and Id2), enhancing local T cell aggregation and antitumor functions. IL-18 is a key activator of NK and Th1 cells because these cells express IL18R on their surface and form a positive loop with IFN-γ.^136,137 IFN-γ exerts antitumor effects by inhibiting the secretion of immunosuppressive cytokines by regulatory T lymphocytes, including TGF-β and IL-10. In addition, IFN-γ can also induce the activation, proliferation, and granzyme B production of CD8⁺ CTLs. Furthermore, IL-18 can cause NK cell proliferation and stimulate these cells to express APC-like molecules, such as MHC class II and TCR co-stimulatory molecules, thereby activating Th1 cells and adaptive immune responses.

The third is to induce immune cell pyroptosis in the TME. Studies report that ATP released by pyroptotic tumor cells can activate macrophage pyroptosis, releasing large amounts of IL-1β.¹³⁸ Salmonella typhimurium VNP20009, which is enriched and has antitumor effects in tumors, can induce macrophages to enter a GSDMD-dependent pyroptotic-like state. These pyroptotic-like macrophages can increase the local temperature of the tumor, thereby promoting M1 polarization and exerting antitumor effects.¹³⁹ In addition, pyroptotic-like activated macrophages, DCs, and monocytes have also been reported to be in a highly activated state, capable of secreting cytoplasmic cytokines.

Although having antitumor characteristics, immune cell pyroptosis may have pro-tumor effects under certain conditions. Inflammasome-activated pyroptosis (IAP) can produce a chronic inflammatory environment that promotes tumor progression. Based on these contradictory findings, it has been proposed that IAP, which is usually activated during infection and autoimmune processes, is more likely to produce a pro-tumor chronic inflammation, while tumor-associated pyroptosis, which is initiated by chemotherapeutic drugs and cytolysis attack, leads to an acute inflammation that is favorable for antitumor immunity. However, the function of immune cell pyroptosis in the TME needs further investigation.

5. Multidimensional strategies of pyroptosis-inducing nanomaterials in synergistic cancer immunotherapy

As cancer immunotherapy evolves from monotherapy to multimodal combination therapies, precise synergistic strategies targeting distinct mechanisms of action have become crucial for overcoming therapeutic efficacy limitations. Pyroptosis, a programmed inflammatory cell death modality, remodels the immunosuppressive TME by releasing TAAs and DAMPs, which not only activate DC-mediated antigen presentation but also recruit CTLs and NK cells. Traditional pyroptosis-inducing agents (including chemotherapeutics and pathogen-derived molecular patterns) frequently cause off-target toxicity through inadequate biodistribution, with their effectiveness further diminished by the intricate nature of the local TME characterized by hypoxia, acidic pH, and infiltration of immunosuppressive cells.

Nanomaterials uniquely overcome pyroptosis therapy barriers through three design principles. Firstly, microenvironment-responsive carriers (e.g., pH/ROS-responsive smart materials) confine GSDM activation to tumors, minimizing systemic inflammation. Secondly, co-delivery capabilities enable synergistic payload combinations within single-vector systems. Thirdly, enhanced tumor accumulation occurs via enhanced permeability and retention (EPR)-driven extravasation and active targeting. Collectively, these allow precise immune modulation unattainable with conventional therapies.

This section will systematically analyze customized nanomaterial designs for pyroptosis-immunotherapy synergy through the framework of four major therapeutic categories: immune ICIs, cancer vaccines, OVs, and innate immune modulators.

5.1 Immune checkpoint inhibitors: nanoscale synergy between pyroptosis induction and T cell exhaustion reversal

ICI therapy has achieved remarkable benefits in the treatment of malignant tumors, but the clinical response rates are unsatisfactory due to the low tumor immunogenicity and the abundance of immunosuppressive cells. However, pyroptosis remodels the immunosuppressive TME through the release of TAAs and DAMPs. These molecules activate DC-mediated antigen presentation and recruit CTLs and NK cells. Exemplifying this approach, Tao et al. engineered a mild hyperthermia-responsive hollow carbon nanozyme (HCS-FeCu) capable of triggering pyroptotic immunogenic cell death, which concurrently remodeled the immunosuppressive tumor niche and potentiated PD-1 blockade therapy through coordinated antigen release and danger signal amplification (Fig. 4a).¹⁴⁰ Under light activation, HCS-FeCu generates ROS via the Tom20-Bax-caspase-3-GSDME signaling pathway, leading to plasma membrane rupture and the release of intracellular inflammatory factors. Experimental results confirmed the induction of pyroptosis, showing a significant increase in cleaved caspase-3 and GSDME expression, as well as extensive plasma membrane disruption in treated tumor cells. The treatment also led to elevated levels of IL-18 and IL-1β, supporting pyroptosis-mediated immunostimulation. In vivo experiments using murine tumor models demonstrated a dramatic inhibition of tumor growth when the nanoparticle was combined with anti-PD-1 therapy, compared to either treatment alone. Treated tumors exhibited significantly reduced volumes and prolonged overall survival rates. Immunohistochemical analyses further confirmed enhanced infiltration of CD8⁺ T cells and mature DCs in the tumor tissue, as well as increased expression of pro-inflammatory cytokines such as IFN-γ and TNF-α in serum samples.

Fig. 4 (a) HCS-FeCu induces pyroptosis and acts as an antitumor therapeutic mechanism in combination with anti-PD-1. Reproduced with permission from ref. 140. Copyright 2023, American Chemical Society. (b) Illustration of the pyroptosis-inducing self-adaptor for breast cancer immunotherapy. Reproduced with permission from ref. 141. Copyright 2025, Wiley-VCH. (c) Schematic illustration of the PMTPN to potentiate ICI therapy by initiating tumor cell pyroptosis and depleting infiltrating B cells. Reproduced with permission from ref. 142. Copyright 2025, Wiley-VCH. (d) Intratumoral administration of mRNA lipid nanoparticles encoding only the N-terminal domain of GSDMB triggers pyroptosis, eliciting antitumor immunity and facilitating anti-PD-1-mediated immunotherapy in immunologically cold tumors. Reproduced with permission from ref. 143. Copyright 2023, Springer Nature.

Overall, this study provides compelling evidence that the combination of pyroptosis-inducing nanomaterials with the PD-1 blockade produces a robust antitumor immune response by not only directly eradicating tumor cells via ROS-mediated pyroptosis but also by effectively reconditioning the TME to support a sustained T cell-mediated attack.

Unlike strategies that directly harness pyroptosis-induced immune microenvironment reprogramming and upregulated immune responses to enhance antitumor immunity, certain nanomaterials employ co-delivery systems to transport pyroptosis inducers alongside immune cell-modulating drugs into tumors, thereby further amplifying tumor immune responses. For example, Qiu et al. developed a self-adaptive nanomaterial (R@L-MRS17) to simultaneously induce pyroptosis and regulate macrophage M1 polarization, thereby enhancing the immune microenvironment and boosting the efficacy of anti-PD-L1 therapy for breast cancer (Fig. 4b).¹⁴¹ Upon light activation, R@L-MRS17 generated ROS in situ, triggering caspase-1-mediated GSDMD pyroptosis. Experimental results confirmed the pyroptosis-inducing effect, showing rapid plasma membrane swelling and rupture in breast cancer cells, accompanied by increased levels of cleaved caspase-1 and GSDMD-N, as well as elevated ICD markers such as CRT exposure and HMGB1 release. The material then degraded in the acidic TME, releasing R848 to drive macrophage M1 polarization, as evidenced by increased expression of CD80 and inducible nitric oxide synthase, along with reduced levels of CD206 and arginase-1. Additionally, DC maturation assays revealed a significant upregulation of CD80/CD86 and MHC-II expression, confirming enhanced antigen presentation and immune activation. Furthermore, R@L-MRS17 blocked CD47 to restore M1 macrophages’ recognition and phagocytosis of tumor cells, ultimately activating stepwise immune responses that effectively suppressed breast cancer growth and metastasis when combined with PD-L1 inhibition.

In addition to modulating macrophage M1 polarization, depletion of tumor-infiltrating B cells has been engineered as a unique nano-combined immune checkpoint therapeutic strategy. A notable instance is the plasma membrane targeted photodynamic nanoagonist (PMTPN) developed by Zhong et al., which reinforces ICI efficacy through dual mechanisms of tumor cell pyroptosis induction and immunosuppressive B cell depletion (Fig. 4c).¹⁴² This dual-functional design allows PMTPN to target the tumor and plasma membrane, initiating pyroptosis-mediated immunogenic cell death while simultaneously suppressing the immunosuppressive functions of infiltrating B cells. Upon light activation, PMTPN efficiently generates ROS at the plasma membrane, triggering caspase-1-mediated GSDMD-dependent pyroptosis. Experimental data confirm significant membrane rupture and cell swelling in PMTPN-treated tumor cells under light irradiation, accompanied by elevated levels of cleaved caspase-1 and GSDMD-N.

In addition to pyroptosis induction, PMTPN facilitates immune modulation by depleting immunosuppressive infiltrating B cells. PMTPN-treated tumors exhibited reduced levels of IL-10 secretion and Treg populations, contributing to increased infiltration of CTLs and NK cells. Flow cytometry analysis revealed significantly higher percentages of CD8⁺ CTLs and enhanced IFN-γ production following PMTPN treatment in combination with the PD-1 blockade, leading to the eradication of primary and distant tumors. Notably, PMTPN + light combined with αPD-L1 induced a 26.34% reduction in distant tumor weight and a 49.74% decrease in primary tumor weight compared to PMTPN + light alone, further underscoring the PMTPN's critical role in enhancing ICI efficacy.

In summary, this study introduces a novel plasma membrane-targeted photodynamic strategy to synergize pyroptosis-induced immunogenic cell death with immune modulation through B cell depletion.

Li et al. pioneered a minimalist pyroptosis-inducing nanoplatform by encapsulating mRNA encoding exclusively GSDMB-N within clinically translatable lipid nanoparticles (LNPs) (Fig. 4d).¹⁴³ This design bypasses endogenous protease dependency for pyroptosis activation, as translated GSDMB-N directly oligomerizes to permeabilize tumor cell membranes, triggering robust immunogenic cell death. Critically, GSDMB-N mRNA@LNPs synergized with the anti-PD-1 checkpoint blockade to overcome therapeutic resistance: combination therapy achieved 70% complete tumor eradication in B16F10 models and extended a median survival to 48 days, while concurrently suppressing distant untreated lesions by 92% through systemic immune activation. This single-agent strategy leverages pyroptosis-induced antigen release and innate immune activation to establish a self-sustaining cycle of T-cell priming and tumor clearance, thereby positioning mRNA-encoded GSDM fragments as a pioneering paradigm for converting immunologically inert tumors into checkpoint-responsive ecosystems.

5.2 Cancer vaccine potentiation: pyroptosis-driven in situ antigen reservoirs and intelligent adjuvant delivery

Conventional cancer vaccines fail to generate robust antitumor immunity primarily due to insufficient exposure of TAAs within an immunosuppressive microenvironment. To address this limitation, researchers are leveraging tumor cell pyroptosis induction to transform the TME into an effective antigen pool, thereby enhancing in situ tumor vaccine generation. Liu et al. engineered the Cu-THBQ/AX nanovaccine as an in situ antigen factory that forces tumor cells into pyroptosis and cuproptosis, thereby converting them into endogenous TAA reservoirs (Fig. 5a).¹⁴⁴

Fig. 5 (a) Schematic illustration of activated antitumor immunity after Cu-THBQ/AX treatment by inducing tumor cell pyroptosis, cuproptosis, and secondary necrosis. Reproduced with permission from ref. 144. Copyright 2024, American Chemical Society. (b) Schematic illustration of photocatalytic CDs inducing pyroptosis of cancer cells under WLED irradiation. Reproduced with permission from ref. 145. Copyright 2024, Wiley-VCH. (c) Schematic illustration of the preparation and application of the personalized PyoVAC. Reproduced with permission from ref. 146. Copyright 2023, Springer Nature.

Pyroptosis induction was validated by elevated caspase-3 activation and GSDME cleavage, along with morphological changes such as membrane swelling and rupture. Cuproptosis was confirmed by increased ATP7A expression and dihydrolipoamide S-acetyltransferase (DLAT) oligomerization. Additionally, macrophage efferocytosis inhibition was evidenced by reduced phospho-ERK5 (p-ERK5) expression and decreased IL-10 secretion, while macrophage polarization assays showed a shift from the M2 to M1 phenotype, with increased TNF-α and IL-12p70 levels. DC maturation was enhanced, as indicated by upregulated CD80/CD86 expression and increased secretion of proinflammatory cytokines. In vivo studies using an orthotopic 4T1 tumor-bearing mouse model demonstrated that Cu-THBQ/AX treatment significantly suppressed tumor growth and prolonged survival. Tumor inhibition rates reached 89%, with enhanced caspase-3 expression confirming pyroptosis induction. In a bilateral tumor model, Cu-THBQ/AX effectively inhibited distant tumor growth, indicating robust systemic immune activation. Flow cytometry analysis revealed increased infiltration of CD8⁺ T cells and elevated IFN-γ secretion, supporting enhanced antitumor immunity.

Overall, this study presents a novel nanovaccine strategy that integrates pyroptosis-induced immunogenicity with tumor vaccination, effectively reprogramming the TME to enhance immune responses.

The development of whole-cell cancer vaccines (WCCVs) with concurrent biosafety and therapeutic efficacy is critical for cancer immunotherapy. Pyroptotic cancer cells, owing to their elevated immunogenicity, represent a promising avenue for WCCV development. Nevertheless, the successful development of pyroptosis-based WCCVs remains to be achieved. Representative examples include the photocatalytic carbon dot (CD)-based platform developed by Cheng et al., where light-activated pyroptosis induction enables in situ fabrication of WCCVs (Fig. 5b).¹⁴⁵ This innovative approach leverages CDs as non-cytotoxic, biocompatible nanomaterials capable of generating ROS upon white light irradiation, leading to a mitochondria-caspase-3-GSDME pyroptosis pathway and proton motive force-driven mitochondrial ATP synthesis disruption. In vitro experiments confirmed that CD-treated cancer cells exhibited significant plasma membrane swelling, rupture, and increased expression of cleaved caspase-3 and GSDME-N, validating pyroptosis induction. In vivo studies demonstrated that pyroptotic cancer cells generated by CDs effectively activated macrophages (M0–M1 polarization) and enhanced MHC class II expression, promoting antigen presentation. Tumor vaccination experiments in melanoma and breast cancer mouse models confirmed the immune-preventive effects of CD-induced pyroptotic cancer cells, with immune memory facilitating rapid and specific anticancer responses upon re-exposure to the same tumor cells.

Building upon the immunogenic potential of pyroptosis, Li et al. engineered a personalized cancer vaccine platform centered on pyroptotic vesicles (Pyo)—nanoscale extracellular vesicles harvested from tumor cells undergoing GSDMD-mediated pyroptosis following LPS/nigericin treatment (Fig. 5c).¹⁴⁶ Featuring an enriched cargo of tumor antigens, DAMPs, and immunostimulatory microRNAs, these vesicles were loaded with the TLR7/8 agonist resiquimod (R848) and embedded in a biocompatible hyaluronic acid hydrogel (Pyo-R@Gel) to achieve the sustained release for targeted postsurgical delivery.

The therapeutic efficacy of Pyo-R@Gel stems from a dual-phase immunomodulatory cascade. In vitro studies confirmed that bone marrow-derived DCs internalize Pyo-R complexes, resulting in markedly enhanced maturation and elevated pro-inflammatory cytokine secretion. Complementing this intrinsic immunogenicity, sustained R848 release within the acidic TME potentiates TLR7/8 activation, further amplifying DC maturation and polarizing TAMs toward an anti-tumor M1 phenotype.

In surgically resected 4T1-Luc triple-negative breast cancer, Pyo-R@Gel implantation dramatically suppressed local recurrence and inhibited metastatic dissemination to the lungs. Similarly, in bilateral B16F10 melanoma models, treatment at the primary tumor site reduced distal tumor growth by 92% while doubling the survival. Critically, the vaccine elicited potent antigen-specific immunity: DCs exposed to vesicles derived from OVA-expressing cells significantly upregulated H-2Kb (SIINFEKL) presentation, while SIINFEKL-specific CD8⁺ T cells expanded to 26.8%. Furthermore, parallel neoantigen-specific responses were demonstrated using the Adpgk epitope in MC38 tumors.

Collectively, by harnessing the synergistic interplay between pyroptosis-derived immunogenic cargo and spatially controlled TLR agonism, this platform transcends limitations of conventional vesicle-based vaccines. It overcomes antigen heterogeneity while generating coordinated innate and adaptive immune responses that confer durable protection against tumor recurrence and metastasis, advancing personalized onco-immunotherapy.

5.3 Oncolytic virus synergy: pyroptosis-dependent viral replication amplification coupled with immune activation

OVs exert antitumor effects through selective tumor cell infection and induction of immunogenic cell death; yet, their clinical efficacy remains constrained by two critical limitations: (1) the immunosuppressive TME impeding viral proliferation/dissemination and (2) apoptosis-dominated cell death failing to sufficiently activate systemic antitumor immunity. Emerging evidence demonstrates that pyroptosis addresses these limitations via two complementary pathways: GSDM-driven membrane pore formation enables viral progeny release and self-amplifying propagation cycles, while pyroptotic secretion of inflammatory mediators induces microenvironmental reprogramming that establishes autologous tumor vaccination. Consequently, engineered nanoplatforms co-encapsulating pyroptosis triggers and OVs enable temporospatial coordination of both components, yielding synergistic therapeutic outcomes through concurrent viral titer escalation and immunologic activation. A representative paradigm is the dual-responsive STAT3 inhibitor nanoprodrug (MPNPs) engineered by Su et al., which converges with oncolytic herpes simplex virus (oHSV) to establish a self-amplifying pyroptosis-immunity cycle, thereby converting immunologically inert tumors into T cell-inflamed niches (Fig. 6a).¹⁴⁷ In this work, researchers engineered MPNPs using a ROS/pH dual-responsive carrier to stably encapsulate niclosamide. Under the dual stimulus, MPNPs are efficiently taken up by the tumor and suppressive immune cells, resulting in enhanced intracellular drug delivery. When combined with an ICP34.5/ICP47-deficient oHSV, the system not only boosts tumor penetration but also intensifies the local generation of ROS. This, in turn, promotes the activation of caspase-3 and the subsequent cleavage of GSDME into its pore-forming N-terminal fragment—key molecular events that induce pyroptosis. Experimental observations include membrane swelling and rupture in treated tumor cells, elevated levels of cleaved caspase-3 and GSDME-N, and a marked release of DAMPs. Critically, GSDM pore formation liberates viral progeny from infected cells, creating a self-amplifying cycle of viral dissemination and immunogenic cell death. When paired with the PD-1 blockade, this strategy demonstrated substantial control over both local tumor recurrence and distant metastasis, thereby potentiating the effects of ICIs.

Fig. 6 (a) Schematic representation of a dual-responsive STAT3 inhibitor nanoprodrug combined with OV elicits synergistic antitumor immune responses by igniting pyroptosis. Reproduced with permission from ref. 147. Copyright 2023, Wiley-VCH. (b) Schematic illustration of the dual-responsive epigenetic inhibitor nanoprodrug ACNPs combined with oHSV trigger cooperative immunological reactions against tumors by inducing GSDME-mediated pyroptosis. Reproduced with permission from ref. 148. Copyright 2024, American Chemical Society.

Overall, this study offers compelling evidence that integrating dual-responsive nanomedicine with oncolytic virotherapy can effectively “ignite” immunogenic pyroptosis.

Besides this, Wang et al. introduced a cutting-edge strategy that integrates a dual-responsive epigenetic inhibitor nanoprodrug (ACNPs) with oHSV to robustly trigger GSDME-mediated pyroptosis and enhance anticancer immunity (Fig. 6b).¹⁴⁸ In this platform, the DNA methyltransferase inhibitor 5-azacytidine (5-Aza) is loaded into ACNPs engineered to release their cargo in response to both ROS and acidic pH conditions in the TME, thereby precisely reversing the hypermethylated silencing of the GSDME gene. Concurrently, oHSV infection further elevates GSDME levels by reducing its ubiquitination and degradation, creating a synergistic effect that shifts cell death from apoptosis to immunogenic pyroptosis. Their combination resulted in significantly enhanced cleavage of GSDME into its active N-terminal fragment, accompanied by characteristic morphological changes such as pronounced membrane swelling and rupture. This cascade leads to the robust release of DAMPs, thereby priming them for a stronger immune response. In vivo evaluations further substantiated these findings: the combined treatment markedly suppressed tumor growth and increased tumor-infiltrating CD8⁺ T cells, while pairing with the PD-L1 blockade prolonged survival in preclinical models.

Notably, while this study bears resemblance to previous work that combined a STAT3 inhibitor nanoprodrug with oHSV for pyroptosis induction, a key difference lies in its epigenetic focus. Here, the use of 5-Aza addresses the frequently silenced status of GSDME by demethylation, a tactic that not only amplifies immediate cytotoxic effects via pyroptosis but also fosters durable immune memory. Overall, this innovative confluence of epigenetic reprogramming, oncolytic virotherapy, and checkpoint inhibition presents a promising new avenue for overcoming tumor immunosuppression and achieving prolonged cancer remission.

5.4 Innate immune regulation: nanoscale cascade control of pyroptosis signaling and cGAS-STING pathway

Emerging research indicates that boosting innate immune responses via pyroptosis triggering or cGAS-STING pathway stimulation represents a critical therapeutic paradigm to reprogram immunologically cold tumors and elicit systemic anticancer immune surveillance. The pyroptotic cascade induces immunostimulatory DAMPs through cellular membrane permeabilization, complemented by cGAS-STING-driven type I interferon production, collaboratively dismantling tumor-mediated immune evasion mechanisms. Consequently, the development of nanomaterials integrating potent pyroptosis-inducing capabilities with cGAS-STING pathway activation has become a cutting-edge research direction in cancer immunotherapy, with the central challenge lying in precise spatiotemporal coordination of these dual immunostimulatory mechanisms. Highlighting multimodal convergence, Ding et al. reported a nanotheranostic platform that achieves synergistic integration of epigenetic reprogramming and the photodynamic action, simultaneously triggering pyroptotic immunogenicity while activating cGAS-STING-mediated innate immunity, thereby establishing a unified framework for photodynamic-immunotherapeutic amplification (Fig. 7a).¹⁴⁹ In this elegant design, two complementary nanoparticle systems are fabricated: NP2 delivers decitabine to demethylate and reactivate GSDME/STING promoters—overcoming epigenetic silencing—while NP1 generates phototriggered ROS to induce mitochondrial DNA release upon near-infrared irradiation. In vitro, NP1 + NP2 combined with NIR irradiation produced dramatic morphological changes characteristic of pyroptosis—such as pronounced membrane bubbling and rupture—with significant upregulation of GSDME-N and elevated ATP and LDH release compared to NP1 alone. Concurrently, the photodynamic action induced mitochondrial dysfunctions, facilitating the release of cytosolic DNA that robustly activated the cGAS-STING signaling cascade, as evidenced by markedly increased phosphorylation levels of STING, TBK1, and IRF3. These molecular events culminated in enhanced maturation of DCs and the secretion of proinflammatory cytokines. In vivo evaluations further confirmed that the dual-modality treatment substantially inhibited tumor growth and improved antitumor immune responses, highlighting the therapeutic potential of this integrated strategy.

Fig. 7 (a) Schematic illustration of the preparation of NP1 and NP2, and the activation of the innate immune via simultaneous induction of pyroptosis and the cGAS-STING signaling pathway for enhanced T cell-mediated antitumor immunity with the synergistic effects of NP1 and NP2. Reproduced with permission from ref. 149. Copyright 2024, Wiley-VCH. (b) Schematic illustration demonstrating the preparation of CoF₂ NNs for catalytic metalloimmunotherapy via cascaded pyroptosis and cGAS-STING activation. Reproduced with permission from ref. 150. Copyright 2024, American Chemical Society. (c) Schematic plot of hydrotalcite-induced pyroptosis combined with toll-like receptor activation elicited dual stimulation of innate immunity and adaptive immunity. Reproduced with permission from ref. 151. Copyright 2025, American Chemical Society.

Overall, this study demonstrates that the strategic combination of epigenetic reprogramming with photodynamic-induced immunogenic cell death can simultaneously ignite pyroptosis and trigger the cGAS-STING pathway.

Recent mechanistic insights reveal that engineered pyroptosis-inducing nanomaterials not only drive GSDM-dependent pyroptotic burst but also facilitate mtDNA efflux into cytoplasmic compartments. The resultant DAMP–mtDNA complexes function as native cGAS agonists, creating a self-sustaining pyroptosis-STING signaling linkage that enables simplified yet potent nano-bio interfaces. For instance, Yu et al. introduced a novel, self-cascading cobalt fluoride nanoneedle system (CoF₂ NNs) that simultaneously induces pyroptosis and activates the cGAS-STING pathway to drive catalytic metalloimmunotherapy (Fig. 7b).¹⁵⁰ Under the dual influence of endogenous H₂O₂ and exogenous ultrasound irradiation, the CoF₂ NNs catalyze the production of ROS. This ROS surge critically triggers caspase-1 activation and the cleavage of GSDMD into its pore-forming N-terminal fragment, therefore initiating pyroptotic cell death. Moreover, the ROS-induced mitochondrial damage facilitates a substantial release of mtDNA, which in turn acts as an intrinsic stimulant to activate and amplify the cGAS-STING signaling cascade, as evidenced by increased phosphorylation levels of STING, TBK1, and IRF3. In vivo studies demonstrated that treatment with CoF₂ NNs under ultrasound exposure significantly suppressed tumor growth. Furthermore, levels of TNF-α, IFN-γ, and IL-6, which play pivotal roles in activating antitumor immunity, were elevated following CoF₂ NNs + US treatment. Collectively, these results demonstrate that pyroptotic cell death induction and subsequent mtDNA release remodel the TME, which promotes DC maturation and enhances T-cell infiltration.

5.5 Multimechanistic combination therapy: multidimensional synergy of pyroptosis nanoplatforms with immunotherapy

Although the combination of nanotherapeutic immunomodulators with pyroptosis-inducing nanomaterials demonstrates enhanced potential for antitumor immunity, their efficacy remains constrained by the complexity of the TME and the homogeneity of therapeutic mechanisms. To overcome the limitations of singular therapeutic mechanisms in complex TMEs, Wu et al. engineered layered double hydroxide nanoparticles (R@AZOH) that concurrently execute three immunomodulatory actions: (1) pH-triggered Zn²⁺ release activates caspase-1-GSDMD-mediated pyroptosis, liberating cryptic tumor antigens and DAMPs; (2) TLR7/8 agonist R848 promotes DC maturation via MyD88-NF-κB signaling; and (3) the material's positively charged porous framework acts as an in situ antigen depot, prolonging TAA exposure (Fig. 7c).¹⁵¹ The Zn²⁺ overload initiates the canonical caspase-1-GSDMD pathway, resulting in distinctive pyroptotic cell death. Meanwhile, the released R848 robustly activates toll-like receptor signaling, which in turn promotes the maturation of DCs as demonstrated by enhanced CD80⁺/CD86⁺ expression. Moreover, in vivo experiments revealed that treatment with R@AZOH significantly inhibited tumor growth and, when combined with ICIs, mediated systemic antitumor immunity. Overall, this study compellingly demonstrates that the integration of pyroptosis induction with multiple layers of immune modulation via TLR activation and efficient antigen presentation can orchestrate a synergistic antitumor immune response.

6. Conclusions and prospects

In this review, we systematically examine the current development status of immunotherapy, its inherent limitations, and the potential application of pyroptosis molecular mechanisms in combination with nanomedicine strategies. This manuscript is organized in three principal sections: (1) an overview of current immunotherapy strategies and their limitations; (2) a mechanistic dissection of three core pyroptosis pathways and their immune-activating properties; and (3) classification and application analysis of pyroptosis-inducing nanomaterials tailored to distinct immunotherapy modalities. Through multi-dimensional and stratified analyses, we endeavor to chart novel therapeutic avenues that address deficiencies in conventional immunotherapy.

Recent years have witnessed nanotechnology-based drug delivery systems opening new avenues for cancer therapy, where their unique size-dependent properties and programmable functionality offer innovative solutions to overcome the limitations of conventional cancer therapies. This review focuses on elucidating molecular mechanisms underlying pyroptosis-mediated immune activation, investigating design principles of engineered nanocarriers for combination immunotherapy, and advancing their clinical translation. Despite substantial progress in developing multifunctional nanovehicles targeting pyroptosis pathways and combinatorial immunotherapies, critical challenges persist in achieving large-scale clinical implementation.

First, intrinsic cellular defense pathways attenuating pyroptosis execution during treatment are yet to be fully deciphered. Systematic investigation into cancer cell-autonomous pyroptosis suppression networks is critical for engineering nanomaterials with enhanced pyroptogenic efficacy. Recent studies reveal that pyroptosis-related genes (e.g., GSDM family members GSDME/GSDMD and NLRP3) are frequently epigenetically silenced across multiple malignancies.^128,152,153 Pharmacological reversal using epigenetic modulators (HDAC inhibitors and DNMT inhibitors) can reactivate these genes, sensitizing cancer cells to pyroptosis induction. Epigenetic therapeutics (e.g., HDAC inhibitors and DNA methyltransferase inhibitors) counteract DNA/histone modification-driven silencing of pivotal pyroptosis genes in cancer cells.¹⁵⁴ Consequently, integrating epigenetic regulation of GSDM gene expression with nanomaterial-mediated pyroptosis induction emerges as a crucial research frontier.¹⁵⁵ Simultaneously, tumor cells upregulate autophagy—particularly mitophagy—as an adaptive “cytoprotective autophagy” mechanism to counteract pyroptotic stresses.¹⁵⁶ This survival strategy involves the autophagic clearance of damaged components (e.g., permeabilized mitochondria), thereby reducing endogenous pyroptosis signal generation and evading cell death.¹⁵⁷ To resolve this paradox, nanotechnology platforms can co-load autophagy inhibitors (e.g., chloroquine) with TME-responsive release mechanisms (pH-sensitive linkers and enzymatic triggers).¹⁵⁸ This spatial–temporal control enables localized autophagy blockade in tumors to amplify pyroptosis while minimizing systemic autophagy inhibition in healthy tissues. Successful implementation requires precise control over drug release kinetics and payload ratios to achieve effective suppression of tumor-protective autophagy. Furthermore, certain tumor cells exhibit robust membrane repair capacity via ESCRT-III complexes, enabling the partial reversal of pyroptotic pore formation and subsequent survival despite initial pyroptosis induction.^159,160 Therefore, co-delivering pyroptosis inducers with ESCRT inhibitors (small molecule antagonists or CHMP4B-targeting RNAi) via nanocarriers presents a viable solution.¹⁶¹ Preliminary studies on selected cytotoxic agents demonstrate that ESCRT pathway disruption significantly enhances pyroptosis-mediated lethality.¹⁶² The nanotechnology's unique strength lies in enabling tumor-specific combinatorial therapy. Through nanocarrier-mediated delivery, spatially restricted inhibition of ESCRT-III-dependent membrane repair precisely blocks repair in malignancies while preserving capacity in normal cells.

Second, the fibrotic barrier in tumors is a major factor limiting the infiltration of nanomaterials. CAFs in tumor tissues have garnered significant attention in nanomaterial-based cancer therapy research. CAFs play dual roles in the TME: on the one hand, they secrete abundant extracellular matrix (ECM) components (e.g., collagen and hyaluronic acid) to form dense physical barriers that impede nanomaterial penetration and cellular uptake, thereby reducing intratumoral drug distribution and therapeutic efficacy; on the other hand, CAFs produce immunosuppressive cytokines (TGF-β and IL-6) that promote the expansion of Tregs and MDSCs, which attenuate pyroptosis-associated immune activation and counteract antitumor effects.^163,164 To overcome the “penetration barrier”, a viable strategy involves constructing biomimetic nanomaterials coated with CAF-derived membranes to enhance tumor matrix recognition and penetration while maintaining biocompatibility.¹⁶⁵ Concurrently, localized delivery of matrix-degrading enzymes (e.g., hyaluronidase) can enzymatically digest hyaluronic acid and other ECM components, reducing barrier density and improving nanodrug penetration efficiency.¹⁶⁶ To counteract immunosuppression, specialized CAF-targeted delivery systems are essential. For instance, FAPα-targeting peptides enable the selective drug delivery to CAFs, directly blocking their immunosuppressive factor secretion.¹⁶⁷ Alternatively, CAF reprogramming strategies using shRNA-mediated silencing of key signaling pathways (e.g., TGF-β/Smad and IL-6/JAK-STAT) can attenuate CAF-driven Treg/MDSC expansion, thereby restoring pyroptosis-induced immune activation.^163,168

Third, while pyroptosis-inducing nanomaterials elicit potent antitumor immunity via ICD, their therapeutic promise is counterbalanced by dual-layered inflammatory risks requiring vigilant mitigation. Crucially, uncontrolled pyroptosis induction not only ablates malignant cells but also inadvertently compromises antitumor immunity through localized and systemic immunotoxicity. Within the TME, excessive pyroptosis induces collateral damage to infiltrating immune cells via pore-driven osmotic shock and ROS/oxidized mtDNA exposure, resulting in T cell dysfunction and DC apoptosis. Concurrently, dysregulated cytokine surges (notably IL-1β/IL-18) propagate beyond the TME, escalating into systemic inflammatory cascades manifesting as cytokine release syndrome (CRS) and irAEs. This continuous immunopathological process from local immunosuppression to systemic hyperinflammation severely undermines the therapeutic index of pyroptosis-based immunotherapy. To reconcile this dichotomy, next-generation nanomaterials must incorporate spatiotemporal precision to confine pyroptosis to tumor loci, exemplified by stimuli-responsive vectors (e.g., NIR/ph-responsive systems) that titrate cytolytic intensity below toxicity thresholds. Simultaneously, co-delivered anti-inflammatories (e.g., IL-1RA) can neutralize off-target inflammation while preserving ICD. Such integrative engineering approaches are indispensable for harnessing pyroptosis’ immunostimulatory potential without instigating pathological inflammation, thereby unlocking its full therapeutic promise.

Finally, the clinical translation and application of pyroptosis-based nanomaterial combination therapy with cancer immunotherapy remains a substantial challenge. Ideally, consortia-level initiatives should be established to integrate fragmented early-phase trial data and catalyze resources for definitive multi-center studies. Such trials can measure multiple longitudinal variables, including the systemic immune activation marker assessment in peripheral blood, radiomic modeling, and multipoint sampling of tumor specimens to detect pyroptosis-related markers and alterations in the tumor immune microenvironment. We acknowledge that such clinical trials necessitate substantial resources; therefore, rational patient stratification should prioritize tumor harboring molecular prerequisites for pyroptosis susceptibility—specifically, malignancies demonstrating high GSDM expression (e.g., GSDMD/GSDME overexpression validated via immunohistochemistry or RNA-seq) or epigenetic activation of inflammasome components (e.g., NLRP3 hypomethylation). Initial proof-of-concept trials in selected cohorts will deliver pyroptosis-inducing nanomaterials combined with ICIs (anti-PD-1/anti-CTLA-4). Data accumulation from expanded trial cohorts will facilitate a high-throughput biomarker pipeline, thereby optimizing trials that use pyroptosis-inducing nanomaterials with immunotherapy.

Author contributions

J. X., B. P., Y. X., X. C., and X. Z. conceptualized the review focus and wrote the manuscript. D. C., L. S., and M. X. performed the literature screening and data extraction. W. L. and X. Z. supervised the research and revised the manuscript. All authors approved the final version.

Conflicts of interest

There are no conflicts of interest to declare.

Data availability

No primary research results, software, or code have been included and no new data were generated or analyzed as part of this review.

Acknowledgements

This work was supported by the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2023A1515010621), the Guangzhou Science and Technology Bureau Basic Research Project of the City University (Hospital) Co-funded Project (Grant No. 2024A03J1153), the Nanshan Talent Project of the First Affiliated Hospital of Guangzhou Medical University (Grant No. 20229006), the National Natural Science Foundation of China (Grant No. 32101060 and 82201251), and the grant of State Key Laboratory of Respiratory Disease (Grant No. SKLRD-Z-202218).

Notes and references

1. L. Liu, H. Li, D. Hu, Y. Wang, W. Shao, J. Zhong, S. Yang, J. Liu and J. Zhang, Mol. Cancer, 2022, 21, 32.
2. E. J. Wherry, Nat. Immunol., 2011, 12, 492–499.
3. M. Philip, L. Fairchild, L. Sun, E. L. Horste, S. Camara, M. Shakiba, A. C. Scott, A. Viale, P. Lauer, T. Merghoub, M. D. Hellmann, J. D. Wolchok, C. S. Leslie and A. Schietinger, Nature, 2017, 545, 452–456.
4. D. R. Sen, J. Kaminski, R. A. Barnitz, M. Kurachi, U. Gerdemann, K. B. Yates, H.-W. Tsao, J. Godec, M. W. LaFleur, F. D. Brown, P. Tonnerre, R. T. Chung, D. C. Tully, T. M. Allen, N. Frahm, G. M. Lauer, E. J. Wherry, N. Yosef and W. N. Haining, Science, 2016, 354, 1165–1169.
5. M. Delacher, M. Simon, L. Sanderink, A. Hotz-Wagenblatt, M. Wuttke, K. Schambeck, L. Schmidleithner, S. Bittner, A. Pant, U. Ritter, T. Hehlgans, D. Riegel, V. Schneider, F. K. Groeber-Becker, A. Eigenberger, C. Gebhard, N. Strieder, A. Fischer, M. Rehli, P. Hoffmann, M. Edinger, T. Strowig, J. Huehn, C. Schmidl, J. M. Werner, L. Prantl, B. Brors, C. D. Imbusch and M. Feuerer, Immunity, 2021, 54, 702–720.e17.
6. P. Sharma and J. P. Allison, Cell, 2015, 161, 205–214.
7. P. Sharma and J. P. Allison, Science, 2015, 348, 56–61.
8. E. Valk, C. E. Rudd and H. Schneider, Trends Immunol., 2008, 29, 272–279.
9. K. S. Peggs, S. A. Quezada, C. A. Chambers, A. J. Korman and J. P. Allison, J. Exp. Med., 2009, 206, 1717–1725.
10. F. S. Hodi, S. J. O’Day, D. F. McDermott, R. W. Weber, J. A. Sosman, J. B. Haanen, R. Gonzalez, C. Robert, D. Schadendorf, J. C. Hassel, W. Akerley, A. J. M. Van Den Eertwegh, J. Lutzky, P. Lorigan, J. M. Vaubel, G. P. Linette, D. Hogg, C. H. Ottensmeier, C. Lebbé, C. Peschel, I. Quirt, J. I. Clark, J. D. Wolchok, J. S. Weber, J. Tian, M. J. Yellin, G. M. Nichol, A. Hoos and W. J. Urba, N. Engl. J. Med., 2010, 363, 711–723.
11. A. H. Sharpe and K. E. Pauken, Nat. Rev. Immunol., 2018, 18, 153–167.
12. H. Borghaei, L. Paz-Ares, L. Horn, D. R. Spigel, M. Steins, N. E. Ready, L. Q. Chow, E. E. Vokes, E. Felip, E. Holgado, F. Barlesi, M. Kohlhäufl, O. Arrieta, M. A. Burgio, J. Fayette, H. Lena, E. Poddubskaya, D. E. Gerber, S. N. Gettinger, C. M. Rudin, N. Rizvi, L. Crinò, G. R. Blumenschein, S. J. Antonia, C. Dorange, C. T. Harbison, F. G. Finckenstein and J. R. Brahmer, N. Engl. J. Med., 2015, 373, 1627–1639.
13. J. Brahmer, K. L. Reckamp, P. Baas, L. Crinò, W. E. E. Eberhardt, E. Poddubskaya, S. Antonia, A. Pluzanski, E. E. Vokes, E. Holgado, D. Waterhouse, N. Ready, J. Gainor, O. Arén Frontera, L. Havel, M. Steins, M. C. Garassino, J. G. Aerts, M. Domine, L. Paz-Ares, M. Reck, C. Baudelet, C. T. Harbison, B. Lestini and D. R. Spigel, N. Engl. J. Med., 2015, 373, 123–135.
14. J. Larkin, V. Chiarion-Sileni, R. Gonzalez, J. J. Grob, C. L. Cowey, C. D. Lao, D. Schadendorf, R. Dummer, M. Smylie, P. Rutkowski, P. F. Ferrucci, A. Hill, J. Wagstaff, M. S. Carlino, J. B. Haanen, M. Maio, I. Marquez-Rodas, G. A. McArthur, P. A. Ascierto, G. V. Long, M. K. Callahan, M. A. Postow, K. Grossmann, M. Sznol, B. Dreno, L. Bastholt, A. Yang, L. M. Rollin, C. Horak, F. S. Hodi and J. D. Wolchok, N. Engl. J. Med., 2015, 373, 23–34.
15. R. J. Motzer, B. Escudier, D. F. McDermott, S. George, H. J. Hammers, S. Srinivas, S. S. Tykodi, J. A. Sosman, G. Procopio, E. R. Plimack, D. Castellano, T. K. Choueiri, H. Gurney, F. Donskov, P. Bono, J. Wagstaff, T. C. Gauler, T. Ueda, Y. Tomita, F. A. Schutz, C. Kollmannsberger, J. Larkin, A. Ravaud, J. S. Simon, L.-A. Xu, I. M. Waxman and P. Sharma, N. Engl. J. Med., 2015, 373, 1803–1813.
16. S. M. Ansell, A. M. Lesokhin, I. Borrello, A. Halwani, E. C. Scott, M. Gutierrez, S. J. Schuster, M. M. Millenson, D. Cattry, G. J. Freeman, S. J. Rodig, B. Chapuy, A. H. Ligon, L. Zhu, J. F. Grosso, S. Y. Kim, J. M. Timmerman, M. A. Shipp and P. Armand, N. Engl. J. Med., 2015, 372, 311–319.
17. J. F. Grosso, C. C. Kelleher, T. J. Harris, C. H. Maris, E. L. Hipkiss, A. De Marzo, R. Anders, G. Netto, D. Getnet, T. C. Bruno, M. V. Goldberg, D. M. Pardoll and C. G. Drake, J. Clin. Invest., 2007, 117, 3383–3392.
18. J. F. Grosso, M. V. Goldberg, D. Getnet, T. C. Bruno, H.-R. Yen, K. J. Pyle, E. Hipkiss, D. A. A. Vignali, D. M. Pardoll and C. G. Drake, J. Immunol., 2009, 182, 6659–6669.
19. M. E. Keir, M. J. Butte, G. J. Freeman and A. H. Sharpe, Annu. Rev. Immunol., 2008, 26, 677–704.
20. T. Maruhashi, D. Sugiura, I. Okazaki, K. Shimizu, T. K. Maeda, J. Ikubo, H. Yoshikawa, K. Maenaka, N. Ishimaru, H. Kosako, T. Takemoto and T. Okazaki, Immunity, 2022, 55, 912–924.e8.
21. Y. Jiang, A. Dai, Y. Huang, H. Li, J. Cui, H. Yang, L. Si, T. Jiao, Z. Ren, Z. Zhang, S. Mou, H. Zhu, W. Guo, Q. Huang, Y. Li, M. Xue, J. Jiang, F. Wang, L. Li, Q. Zhong, K. Wang, B. Liu, J. Wang, G. Fan, J. Guo, L. Chen, C. J. Workman, Z. Shen, Y. Kong, D. A. A. Vignali, C. Xu and H. Wang, Cell, 2025, S0092867425001990.
22. A. S. Rolig, X. Peng, E. R. Sturgill, N. Holay, M. Kasiewicz, C. Mick, G. H. Mcgee, W. Miller, Y. Koguchi, J. Kaufmann, N. Yanamandra, S. Griffin, J. Smothers, M. Adamow, J. Lee, R. Shen, M. K. Callahan and W. L. Redmond, Sci. Transl. Med., 2025, 17, eadk3702.
23. F. A. Schildberg, S. R. Klein, G. J. Freeman and A. H. Sharpe, Immunity, 2016, 44, 955–972.
24. S. J. Dovedi, M. J. Elder, C. Yang, S. I. Sitnikova, L. Irving, A. Hansen, J. Hair, D. C. Jones, S. Hasani, B. Wang, S.-A. Im, B. Tran, D. S. Subramaniam, S. D. Gainer, K. Vashisht, A. Lewis, X. Jin, S. Kentner, K. Mulgrew, Y. Wang, M. G. Overstreet, J. Dodgson, Y. Wu, A. Palazon, M. Morrow, G. J. Rainey, G. J. Browne, F. Neal, T. V. Murray, A. D. Toloczko, W. Dall’Acqua, I. Achour, D. J. Freeman, R. W. Wilkinson and Y. Mazor, Cancer Discovery, 2021, 11, 1100–1117.
25. F. S. Hodi, V. Chiarion-Sileni, R. Gonzalez, J.-J. Grob, P. Rutkowski, C. L. Cowey, C. D. Lao, D. Schadendorf, J. Wagstaff, R. Dummer, P. F. Ferrucci, M. Smylie, A. Hill, D. Hogg, I. Marquez-Rodas, J. Jiang, J. Rizzo, J. Larkin and J. D. Wolchok, Lancet Oncol., 2018, 19, 1480–1492.
26. H. M. Zarour, Clin. Cancer Res., 2016, 22, 1856–1864.
27. E. M. Burton and H. A. Tawbi, Cancer Discovery, 2021, 11, 1008–1010.
28. W. Cheng, K. Kang, A. Zhao and Y. Wu, J. Hematol. Oncol., 2024, 17, 54.
29. P. Kaptein, C. Jacoberger-Foissac, P. Dimitriadis, P. Voabil, M. De Bruijn, S. Brokamp, I. Reijers, J. Versluis, G. Nallan, H. Triscott, E. McDonald, J. Tay, G. V. Long, C. U. Blank, D. S. Thommen and M. W. L. Teng, Sci. Transl. Med., 2022, 14, eabj9779.
30. A. Haslam and V. Prasad, JAMA Network Open, 2019, 2, e192535.
31. E. B. Garon, N. A. Rizvi, R. Hui, N. Leighl, A. S. Balmanoukian, J. P. Eder, A. Patnaik, C. Aggarwal, M. Gubens, L. Horn, E. Carcereny, M.-J. Ahn, E. Felip, J.-S. Lee, M. D. Hellmann, O. Hamid, J. W. Goldman, J.-C. Soria, M. Dolled-Filhart, R. Z. Rutledge, J. Zhang, J. K. Lunceford, R. Rangwala, G. M. Lubiniecki, C. Roach, K. Emancipator and L. Gandhi, N. Engl. J. Med., 2015, 372, 2018–2028.
32. P. A. Ott, Y.-J. Bang, S. A. Piha-Paul, A. R. A. Razak, J. Bennouna, J.-C. Soria, H. S. Rugo, R. B. Cohen, B. H. O’Neil, J. M. Mehnert, J. Lopez, T. Doi, E. M. J. Van Brummelen, R. Cristescu, P. Yang, K. Emancipator, K. Stein, M. Ayers, A. K. Joe and J. K. Lunceford, J. Clin. Oncol., 2019, 37, 318–327.
33. C. Robert, Nat. Commun., 2020, 11, 3801.
34. A. M. Holder, A. Dedeilia, K. Sierra-Davidson, S. Cohen, D. Liu, A. Parikh and G. M. Boland, Nat. Rev. Cancer, 2024, 24, 498–512.
35. D. Stenehjem, D. Tran, M. Nkrumah and S. Gupta, OncoTargets Ther., 2018, 11, 5973–5989.
36. T. E. Keenan, K. P. Burke and E. M. Van Allen, Nat. Med., 2019, 25, 389–402.
37. D. Pan, A. Kobayashi, P. Jiang, L. Ferrari De Andrade, R. E. Tay, A. M. Luoma, D. Tsoucas, X. Qiu, K. Lim, P. Rao, H. W. Long, G.-C. Yuan, J. Doench, M. Brown, X. S. Liu and K. W. Wucherpfennig, Science, 2018, 359, 770–775.
38. V. Gopalakrishnan, C. N. Spencer, L. Nezi, A. Reuben, M. C. Andrews, T. V. Karpinets, P. A. Prieto, D. Vicente, K. Hoffman, S. C. Wei, A. P. Cogdill, L. Zhao, C. W. Hudgens, D. S. Hutchinson, T. Manzo, M. Petaccia De Macedo, T. Cotechini, T. Kumar, W. S. Chen, S. M. Reddy, R. Szczepaniak Sloane, J. Galloway-Pena, H. Jiang, P. L. Chen, E. J. Shpall, K. Rezvani, A. M. Alousi, R. F. Chemaly, S. Shelburne, L. M. Vence, P. C. Okhuysen, V. B. Jensen, A. G. Swennes, F. McAllister, E. Marcelo Riquelme Sanchez, Y. Zhang, E. Le Chatelier, L. Zitvogel, N. Pons, J. L. Austin-Breneman, L. E. Haydu, E. M. Burton, J. M. Gardner, E. Sirmans, J. Hu, A. J. Lazar, T. Tsujikawa, A. Diab, H. Tawbi, I. C. Glitza, W. J. Hwu, S. P. Patel, S. E. Woodman, R. N. Amaria, M. A. Davies, J. E. Gershenwald, P. Hwu, J. E. Lee, J. Zhang, L. M. Coussens, Z. A. Cooper, P. A. Futreal, C. R. Daniel, N. J. Ajami, J. F. Petrosino, M. T. Tetzlaff, P. Sharma, J. P. Allison, R. R. Jenq and J. A. Wargo, Science, 2018, 359, 97–103.
39. S. Gettinger, J. Choi, K. Hastings, A. Truini, I. Datar, R. Sowell, A. Wurtz, W. Dong, G. Cai, M. A. Melnick, V. Y. Du, J. Schlessinger, S. B. Goldberg, A. Chiang, M. F. Sanmamed, I. Melero, J. Agorreta, L. M. Montuenga, R. Lifton, S. Ferrone, P. Kavathas, D. L. Rimm, S. M. Kaech, K. Schalper, R. S. Herbst and K. Politi, Cancer Discovery, 2017, 7, 1420–1435.
40. V. Anagnostou, K. N. Smith, P. M. Forde, N. Niknafs, R. Bhattacharya, J. White, T. Zhang, V. Adleff, J. Phallen, N. Wali, C. Hruban, V. B. Guthrie, K. Rodgers, J. Naidoo, H. Kang, W. Sharfman, C. Georgiades, F. Verde, P. Illei, Q. K. Li, E. Gabrielson, M. V. Brock, C. A. Zahnow, S. B. Baylin, R. B. Scharpf, J. R. Brahmer, R. Karchin, D. M. Pardoll and V. E. Velculescu, Cancer Discovery, 2017, 7, 264–276.
41. F. Martins, L. Sofiya, G. P. Sykiotis, F. Lamine, M. Maillard, M. Fraga, K. Shabafrouz, C. Ribi, A. Cairoli, Y. Guex-Crosier, T. Kuntzer, O. Michielin, S. Peters, G. Coukos, F. Spertini, J. A. Thompson and M. Obeid, Nat. Rev. Clin. Oncol., 2019, 16, 563–580.
42. S. Das and D. B. Johnson, J. Immunother. Cancer, 2019, 7, 306.
43. C. Hua, L. Boussemart, C. Mateus, E. Routier, C. Boutros, H. Cazenave, R. Viollet, M. Thomas, S. Roy, N. Benannoune, G. Tomasic, J.-C. Soria, S. Champiat, M. Texier, E. Lanoy and C. Robert, JAMA Dermatol., 2016, 152, 45–51.
44. S. A. Rosenberg and N. P. Restifo, Science, 2015, 348, 62–68.
45. K. Urbanska, E. Lanitis, M. Poussin, R. C. Lynn, B. P. Gavin, S. Kelderman, J. Yu, N. Scholler and D. J. Powell, Cancer Res., 2012, 72, 1844–1852.
46. L. R. C. Barros, S. C. F. Couto, D. Da Silva Santurio, E. A. Paixão, F. Cardoso, V. J. Da Silva, P. Klinger, P. D. A. C. Ribeiro, F. A. Rós, T. G. M. Oliveira, E. M. Rego, R. N. Ramos and V. Rocha, Cancers, 2022, 14, 2667.
47. S. Mailankody, J. V. Matous, S. Chhabra, M. Liedtke, S. Sidana, O. O. Oluwole, S. Malik, R. Nath, F. Anwer, J. C. Cruz, M. Htut, E. E. Karski, W. Lovelace, M. Dillon, E. Butz, W. Ying, A. Balakumaran and S. K. Kumar, Nat. Med., 2023, 29, 422–429.
48. G. Ghilardi, J. A. Fraietta, J. N. Gerson, V. M. Van Deerlin, J. J. D. Morrissette, G. C. Caponetti, L. Paruzzo, J. C. Harris, E. A. Chong, S. P. Susanibar Adaniya, J. Svoboda, S. D. Nasta, O. H. Ugwuanyi, D. J. Landsburg, E. Fardella, A. J. Waxman, E. R. Chong, V. Patel, R. Pajarillo, I. Kulikovskaya, D. B. Lieberman, A. D. Cohen, B. L. Levine, E. A. Stadtmauer, N. V. Frey, D. T. Vogl, E. O. Hexner, S. K. Barta, D. L. Porter, A. L. Garfall, S. J. Schuster, C. H. June and M. Ruella, Nat. Med., 2024, 30, 984–989.
49. S. A. Grupp, M. Kalos, D. Barrett, R. Aplenc, D. L. Porter, S. R. Rheingold, D. T. Teachey, A. Chew, B. Hauck, J. F. Wright, M. C. Milone, B. L. Levine and C. H. June, N. Engl. J. Med., 2013, 368, 1509–1518.
50. M. L. Davila, I. Riviere, X. Wang, S. Bartido, J. Park, K. Curran, S. S. Chung, J. Stefanski, O. Borquez-Ojeda, M. Olszewska, J. Qu, T. Wasielewska, Q. He, M. Fink, H. Shinglot, M. Youssif, M. Satter, Y. Wang, J. Hosey, H. Quintanilla, E. Halton, Y. Bernal, D. C. G. Bouhassira, M. E. Arcila, M. Gonen, G. J. Roboz, P. Maslak, D. Douer, M. G. Frattini, S. Giralt, M. Sadelain and R. Brentjens, Sci. Transl. Med., 2014, 6, 224ra25.
51. D. W. Lee, B. D. Santomasso, F. L. Locke, A. Ghobadi, C. J. Turtle, J. N. Brudno, M. V. Maus, J. H. Park, E. Mead, S. Pavletic, W. Y. Go, L. Eldjerou, R. A. Gardner, N. Frey, K. J. Curran, K. Peggs, M. Pasquini, J. F. DiPersio, M. R. M. Van Den Brink, K. V. Komanduri, S. A. Grupp and S. S. Neelapu, Biol. Blood Marrow Transplant., 2019, 25, 625–638.
52. K. Rejeski, M. Subklewe and F. L. Locke, Hematology, 2023, 2023, 198–208.
53. J. N. Brudno, M. V. Maus and C. S. Hinrichs, JAMA, 2024, 332, 1924.
54. B. Du, J. Qin, B. Lin, J. Zhang, D. Li and M. Liu, Cancer Cell, 2025, 43, 665–679.
55. Q. Chen, L. Lu and W. Ma, Cancers, 2022, 14, 5983.
56. Y. Tang, X. Yang, H. Hu, H. Jiang, W. Xiong, H. Mei and Y. Hu, Front. Bioeng. Biotechnol., 2023, 11, 1320807.
57. B. Du, J. Qin, B. Lin, J. Zhang, D. Li and M. Liu, Cancer Cell, 2025, 43, 665–679.
58. J. Chen, I. F. López-Moyado, H. Seo, C.-W. J. Lio, L. J. Hempleman, T. Sekiya, A. Yoshimura, J. P. Scott-Browne and A. Rao, Nature, 2019, 567, 530–534.
59. J. Zhang, J. Li, Y. Hou, Y. Lin, H. Zhao, Y. Shi, K. Chen, C. Nian, J. Tang, L. Pan, Y. Xing, H. Gao, B. Yang, Z. Song, Y. Cheng, Y. Liu, M. Sun, Y. Linghu, J. Li, H. Huang, Z. Lai, Z. Zhou, Z. Li, X. Sun, Q. Chen, D. Su, W. Li, Z. Peng, P. Liu, W. Chen, H. Huang, Y. Chen, B. Xiao, L. Ye, L. Chen and D. Zhou, Cell, 2024, 187, 3409–3426.e24.
60. G. Liu, W. Rui, H. Zheng, D. Huang, F. Yu, Y. Zhang, J. Dong, X. Zhao and X. Lin, Eur. J. Immunol., 2020, 50, 712–724.
61. M. Abdoli Shadbad, N. Hemmat, V. Khaze Shahgoli, A. Derakhshani, F. Baradaran, O. Brunetti, R. Fasano, R. Bernardini, N. Silvestris and B. Baradaran, Front. Immunol., 2022, 12, 788211.
62. K. Reinhard, B. Rengstl, P. Oehm, K. Michel, A. Billmeier, N. Hayduk, O. Klein, K. Kuna, Y. Ouchan, S. Wöll, E. Christ, D. Weber, M. Suchan, T. Bukur, M. Birtel, V. Jahndel, K. Mroz, K. Hobohm, L. Kranz, M. Diken, K. Kühlcke, Ö. Türeci and U. Sahin, Science, 2020, 367, 446–453.
63. H. Fritah, M. Graciotti, C. Lai-Lai Chiang, A.-L. Huguenin-Bergenat, R. Petremand, R. Ahmed, P. Guillaume, J. Schmidt, B. J. Stevenson, D. Gfeller, A. Harari and L. E. Kandalaft, iScience, 2023, 26, 106288.
64. L. Miao, Y. Zhang and L. Huang, Mol. Cancer, 2021, 20, 41.
65. A. V. Yaremenko, M. M. Khan, X. Zhen, Y. Tang and W. Tao, Med, 2025, 6, 100562.
66. Y. Zhou, Y. Wei, X. Tian and X. Wei, J. Hematol. Oncol., 2025, 18, 18.
67. E. J. Sayour, D. Boczkowski, D. A. Mitchell and S. K. Nair, Nat. Rev. Clin. Oncol., 2024, 21, 489–500.
68. R. Yao, C. Xie and X. Xia, Hum. Vaccines Immunother., 2024, 20, 2307187.
69. N. Sobhani, B. Scaggiante, R. Morris, D. Chai, M. Catalano, D. R. Tardiel-Cyril, P. Neeli, G. Roviello, G. Mondani and Y. Li, Cancer Treat. Rev., 2022, 109, 102429.
70. R. O. Dillman, A. N. Cornforth, G. I. Nistor, E. F. McClay, T. T. Amatruda and C. Depriest, J. Immunother. Cancer, 2018, 6, 19.
71. A. Pérez-Baños, M. A. Gleisner, I. Flores, C. Pereda, M. Navarrete, J. P. Araya, G. Navarro, C. Quezada-Monrás, A. Tittarelli and F. Salazar-Onfray, Br. J. Cancer, 2023, 129, 572–585.
72. P. W. Kantoff, C. S. Higano, N. D. Shore, E. R. Berger, E. J. Small, D. F. Penson, C. H. Redfern, A. C. Ferrari, R. Dreicer, R. B. Sims, Y. Xu, M. W. Frohlich and P. F. Schellhammer, N. Engl. J. Med., 2010, 363, 411–422.
73. D. Liu, X. Che, X. Wang, C. Ma and G. Wu, Pharmaceuticals, 2023, 16, 1384.
74. S. M. Swain, M. Shastry and E. Hamilton, Nat. Rev. Drug Discovery, 2023, 22, 101–126.
75. Z. You, W. Zhou, J. Weng, H. Feng, P. Liang, Y. Li and F. Shi, Cancer Cell Int., 2021, 21, 489.
76. L. Buonaguro and M. Tagliamonte, Front. Immunol., 2023, 14, 1210044.
77. C. Rabu, L. Rangan, L. Florenceau, A. Fortun, M. Charpentier, E. Dupré, L. Paolini, C. Beauvillain, E. Dupel, J.-B. Latouche, O. Adotevi, N. Labarrière and F. Lang, OncoImmunology, 2019, 8, e1560919.
78. M. L. (Nora) Disis, K. A. Guthrie, Y. Liu, A. L. Coveler, D. M. Higgins, J. S. Childs, Y. Dang and L. G. Salazar, JAMA Oncol., 2023, 9, 71–78.
79. J. Lee, M. C. Woodruff, E. H. Kim and J.-H. Nam, Exp. Mol. Med., 2023, 55, 1305–1313.
80. Z. Chen, T. Yong, Z. Wei, X. Zhang, X. Li, J. Qin, J. Li, J. Hu, X. Yang and L. Gan, Adv. Sci., 2024, 11, 2305081.
81. E. Caproni, R. Corbellari, M. Tomasi, S. J. Isaac, S. Tamburini, I. Zanella, M. Grigolato, A. Gagliardi, M. Benedet, C. Baraldi, L. Croia, G. Di Lascio, A. Berti, S. Valensin, E. Bellini, M. Parri, A. Grandi and G. Grandi, Cancers, 2023, 15, 3328.
82. J. C. Caldeira, M. Perrine, F. Pericle and F. Cavallo, Viruses, 2020, 12, 488.
83. A. Brandenburg, A. Heine and P. Brossart, Trends Cancer, 2024, 10, 749–769.
84. N. Gong, M.-G. Alameh, R. El-Mayta, L. Xue, D. Weissman and M. J. Mitchell, Nat. Rev. Drug Discovery, 2024, 23, 607–625.
85. P. Guasp, C. Reiche, Z. Sethna and V. P. Balachandran, Cancer Cell, 2024, 42, 1163–1184.
86. M. Graciotti and L. E. Kandalaft, Nat. Rev. Drug Discovery, 2025, 24, 134–150.
87. N. Zaidi, E. M. Jaffee and M. Yarchoan, Nat. Rev. Cancer, 2025, 25, 517–533.
88. P. R. Lowenstein, M. L. Varela and M. G. Castro, Cancer Cell, 2025, 43, 611–618.
89. T.-G. Huang, M. J. Savontaus, K. Shinozaki, B. V. Sauter and S. L. C. Woo, Gene Ther., 2003, 10, 1241–1247.
90. J. Fueyo, C. Gomez-Manzano, R. Alemany, P. S. Lee, T. J. McDonnell, P. Mitlianga, Y.-X. Shi, V. A. Levin, W. K. A. Yung and A. P. Kyritsis, Oncogene, 2000, 19, 2–12.
91. W. Wang, W. Ji, H. Hu, J. Ma, X. Li, W. Mei, Y. Xu, H.-Z. Hu, Y. Yan, Q. Song, Z. Li and C. Su, Oncotarget, 2013, 5, 150–160.
92. T. A. Waldmann, Cold Spring Harbor Perspect. Biol., 2018, 10, a028472.
93. Y. Shi, W. Gao, N. K. Lytle, P. Huang, X. Yuan, A. M. Dann, M. Ridinger-Saison, K. E. DelGiorno, C. E. Antal, G. Liang, A. R. Atkins, G. Erikson, H. Sun, J. Meisenhelder, E. Terenziani, G. Woo, L. Fang, T. P. Santisakultarm, U. Manor, R. Xu, C. R. Becerra, E. Borazanci, D. D. Von Hoff, P. M. Grandgenett, M. A. Hollingsworth, M. Leblanc, S. E. Umetsu, E. A. Collisson, M. Scadeng, A. M. Lowy, T. R. Donahue, T. Reya, M. Downes, R. M. Evans, G. M. Wahl, T. Pawson, R. Tian and T. Hunter, Nature, 2019, 569, 131–135.
94. D. Briukhovetska, J. Dörr, S. Endres, P. Libby, C. A. Dinarello and S. Kobold, Nat. Rev. Cancer, 2021, 21, 481–499.
95. K. Chamie, S. S. Chang, E. Kramolowsky, M. L. Gonzalgo, P. K. Agarwal, J. C. Bassett, M. Bjurlin, M. L. Cher, W. Clark, B. E. Cowan, R. David, E. Goldfischer, K. Guru, M. W. Jalkut, S. D. Kaffenberger, J. Kaminetsky, A. E. Katz, A. S. Koo, W. J. Sexton, S. N. Tikhonenkov, E. J. Trabulsi, A. F. Trainer, P. Spilman, M. Huang, P. Bhar, S. A. Taha, L. Sender, S. Reddy and P. Soon-Shiong, NEJM Evidence, 2022, 2, EVIDoa2200167.
96. C. T. Kureshi and S. K. Dougan, Cancer Cell, 2025, 43, 15–35.
97. M. Wang, K. L. Reynolds, K. Montazeri, E. A. Schaefer, R. J. Sullivan and M. Dougan, Clin. Gastroenterol. Hepatol., 2024, 22, 1539–1541.e2.
98. Y. Tan, Q. Chen, X. Li, Z. Zeng, W. Xiong, G. Li, X. Li, J. Yang, B. Xiang and M. Yi, J. Exp. Clin. Cancer Res., 2021, 40, 153.
99. C. Rogers, D. A. Erkes, A. Nardone, A. E. Aplin, T. Fernandes-Alnemri and E. S. Alnemri, Nat. Commun., 2019, 10, 1689.
100. M. Wang and Q. Fu, Adv. Healthcare Mater., 2023, 2301266.
101. J. Shi, W. Gao and F. Shao, Trends Biochem. Sci., 2017, 42, 245–254.
102. X. Wei, F. Xie, X. Zhou, Y. Wu, H. Yan, T. Liu, J. Huang, F. Wang, F. Zhou and L. Zhang, Cell. Mol. Immunol., 2022, 19, 971–992.
103. Y. Xue, D. Enosi Tuipulotu, W. H. Tan, C. Kay and S. M. Man, Trends Immunol., 2019, 40, 1035–1052.
104. D. Nandi, M. Shivrayan, J. Gao, J. Krishna, R. Das, B. Liu, S. Thayumanavan and A. Kulkarni, ACS Appl. Mater. Interfaces, 2021, 13, 45300–45314.
105. V. Hornung, A. Ablasser, M. Charrel-Dennis, F. Bauernfeind, G. Horvath, D. R. Caffrey, E. Latz and K. A. Fitzgerald, Nature, 2009, 458, 514–518.
106. T.-D. Kanneganti, M. Lamkanfi and G. Núñez, Immunity, 2007, 27, 549–559.
107. W. S. C. Ngai, S. Yang, X. Zeng, Y. Liu, F. Lin, X. Wang, H. Zhang, X. Fan and P. R. Chen, J. Am. Chem. Soc., 2022, 144, 5411–5417.
108. B. A. McKenzie, M. K. Mamik, L. B. Saito, R. Boghozian, M. C. Monaco, E. O. Major, J.-Q. Lu, W. G. Branton and C. Power, Proc. Natl. Acad. Sci. U. S. A., 2018, 115, E6065–E6074.
109. K. Wang, Q. Sun, X. Zhong, M. Zeng, H. Zeng, X. Shi, Z. Li, Y. Wang, Q. Zhao, F. Shao and J. Ding, Cell, 2020, 180, 941–955.e20.
110. K. P. Downs, H. Nguyen, A. Dorfleutner and C. Stehlik, Mol. Aspects Med., 2020, 76, 100924.
111. J. Shi, Y. Zhao, Y. Wang, W. Gao, J. Ding, P. Li, L. Hu and F. Shao, Nature, 2014, 514, 187–192.
112. V. A. K. Rathinam, Y. Zhao and F. Shao, Nat. Immunol., 2019, 20, 527–533.
113. S. Paik, J. K. Kim, P. Silwal, C. Sasakawa and E.-K. Jo, Cell. Mol. Immunol., 2021, 18, 1141–1160.
114. B. Zhou, C. B. Ryder, G. R. Dubyak and D. W. Abbott, Sci. Signaling, 2022, 15, eabl6781.
115. D. Yang, Y. He, R. Muñoz-Planillo, Q. Liu and G. Núñez, Immunity, 2015, 43, 923–932.
116. A. de Gassart and F. Martinon, Immunity, 2015, 43, 835–837.
117. A. A. Bhat, R. Thapa, O. Afzal, N. Agrawal, W. H. Almalki, I. Kazmi, S. I. Alzarea, A. S. A. Altamimi, P. Prasher, S. K. Singh, K. Dua and G. Gupta, Int. J. Biol. Macromol., 2023, 242, 124832.
118. Y. Wang, W. Gao, X. Shi, J. Ding, W. Liu, H. He, K. Wang and F. Shao, Nature, 2017, 547, 99–103.
119. M. Jiang, L. Qi, L. Li and Y. Li, Cell Death Discovery, 2020, 6, 112.
120. S. A. Hughes, M. Lin, A. Weir, B. Huang, L. Xiong, N. K. Chua, J. Pang, J. P. Santavanond, R. Tixeira, M. Doerflinger, Y. Deng, C.-H. Yu, N. Silke, S. A. Conos, D. Frank, D. S. Simpson, J. M. Murphy, K. E. Lawlor, J. S. Pearson, J. Silke, M. Pellegrini, M. J. Herold, I. K. H. Poon, S. L. Masters, M. Li, Q. Tang, Y. Zhang, M. Rashidi, L. Geng and J. E. Vince, EMBO J., 2023, 42, e110468.
121. K. Newton, V. M. Dixit and N. Kayagaki, Science, 2021, 374, 1076–1080.
122. J.-Y. Zhang, B. Zhou, R.-Y. Sun, Y.-L. Ai, K. Cheng, F.-N. Li, B.-R. Wang, F.-J. Liu, Z.-H. Jiang, W.-J. Wang, D. Zhou, H.-Z. Chen and Q. Wu, Cell Res., 2021, 31, 980–997.
123. J. Hou, R. Zhao, W. Xia, C.-W. Chang, Y. You, J.-M. Hsu, L. Nie, Y. Chen, Y.-C. Wang, C. Liu, W.-J. Wang, Y. Wu, B. Ke, J. L. Hsu, K. Huang, Z. Ye, Y. Yang, X. Xia, Y. Li, C.-W. Li, B. Shao, J. A. Tainer and M.-C. Hung, Nat. Cell Biol., 2020, 22, 1264–1275.
124. X. Zhong, H. Zeng, Z. Zhou, Y. Su, H. Cheng, Y. Hou, Y. She, N. Feng, J. Wang, F. Shao and J. Ding, Nature, 2023, 616, 598–605.
125. Z. Zhou, H. He, K. Wang, X. Shi, Y. Wang, Y. Su, Y. Wang, D. Li, W. Liu, Y. Zhang, L. Shen, W. Han, L. Shen, J. Ding and F. Shao, Science, 2020, 368, eaaz7548.
126. X. Li, X. Li, C. Xiang, J. Cao, J. Guo, S. Zhu, J. Tan, L. Wang, C. Gao, S. Liu, L. Zhao, B. Yuan, P. Xu, B. Yang, D. Li, B. Zhao and X.-H. Feng, Cell Rep., 2024, 43, 114728.
127. Q. Wang, Y. Wang, J. Ding, C. Wang, X. Zhou, W. Gao, H. Huang, F. Shao and Z. Liu, Nature, 2020, 579, 421–426.
128. Z. Zhang, Y. Zhang, S. Xia, Q. Kong, S. Li, X. Liu, C. Junqueira, K. F. Meza-Sosa, T. M. Y. Mok, J. Ansara, S. Sengupta, Y. Yao, H. Wu and J. Lieberman, Nature, 2020, 579, 415–420.
129. D. A. Erkes, W. Cai, I. M. Sanchez, T. J. Purwin, C. Rogers, C. O. Field, A. C. Berger, E. J. Hartsough, U. Rodeck, E. S. Alnemri and A. E. Aplin, Cancer Discovery, 2020, 10, 254–269.
130. C. M. Le Gall, J. Weiden, L. J. Eggermont and C. G. Figdor, Nat. Mater., 2018, 17, 474–475.
131. A. Hu, L. Sun, H. Lin, Y. Liao, H. Yang and Y. Mao, Signal Transduction Targeted Ther., 2024, 9, 1–59.
132. L. Apetoh, F. Ghiringhelli, A. Tesniere, A. Criollo, C. Ortiz, R. Lidereau, C. Mariette, N. Chaput, J.-P. Mira, S. Delaloge, F. André, T. Tursz, G. Kroemer and L. Zitvogel, Immunol. Rev., 2007, 220, 47–59.
133. T. Deng, C. Tang, G. Zhang and X. Wan, Cell Death Dis., 2021, 12, 1–4.
134. Z. Li, W.-J. Fu, X.-Q. Chen, S. Wang, R.-S. Deng, X.-P. Tang, K.-D. Yang, Q. Niu, H. Zhou, Q.-R. Li, Y. Lin, M. Liang, S.-S. Li, Y.-F. Ping, X.-D. Liu, X.-W. Bian and X.-H. Yao, J. Exp. Clin. Cancer Res., 2022, 41, 74.
135. B. Van Den Eeckhout, L. Van Hoecke, E. Burg, S. Van Lint, F. Peelman, N. Kley, G. Uzé, X. Saelens, J. Tavernier and S. Gerlo, npj Vaccines, 2020, 5, 1–17.
136. J. Shen, Y. Zhang, W. Tang, M. Yang, T. Cheng, Y. Chen, S. Yu, Q. Guo, L. Cao, X. Wang, H. Xiao, L. Wang, C. Wang, C.-Y. Liu and G. Meng, Nat. Immunol., 2025, 26, 416–428.
137. G. Kaplanski, Immunol. Rev., 2018, 281, 138–153.
138. N. Caronni, F. La Terza, L. Frosio and R. Ostuni, Trends Immunol., 2025, S1471490625000596.
139. L. Wu, F. Chen, X. Chang, L. Li, X. Yin, C. Li, F. Wang, C. Li, Q. Xu, H. Zhuang, N. Gu and Z.-C. Hua, J. Am. Chem. Soc., 2022, 144, 19396–19409.
140. N. Tao, L. Jiao, H. Li, L. Deng, W. Wang, S. Zhao, W. Chen, L. Chen, C. Zhu and Y.-N. Liu, ACS Nano, 2023, 17, 22844–22858.
141. Z. Qiu, Y. Zhong, Z. Lu, K. Zhang, Z. Li, J. Nie and H. Cheng, Adv. Funct. Mater., 2025, 35, 2414847.
142. Y. Zhong, Z. Qiu, K. Zhang, Z. Lu, Z. Li, Y. Cen, S. Li and H. Cheng, Adv. Mater., 2025, 37, 2415078.
143. F. Li, X.-Q. Zhang, W. Ho, M. Tang, Z. Li, L. Bu and X. Xu, Nat. Commun., 2023, 14, 4223.
144. Y. Liu, R. Niu, X. Zhang, B. Zhang, X. Chen, J. Guo, S. Song, Y. Wang, H. Zhang and Y. Zhao, ACS Nano, 2024, 18, 12386–12400.
145. Q. Cheng, T. Zhang, Q. Wang, X. Wu, L. Li, R. Lin, Y. Zhou and S. Qu, Adv. Mater., 2024, 2408685.
146. Z. Li, Y. Wang, F. Mo, T. Wolter, R. Hong, A. Barrett, N. Richmond, F. Liu, Y. Chen, X. Yang, L. Dempsey and Q. Hu, Nat. Nanotechnol., 2025 DOI:10.1038/s41565-025-01931-2.
147. W. Su, W. Qiu, S.-J. Li, S. Wang, J. Xie, Q.-C. Yang, J. Xu, J. Zhang, Z. Xu and Z.-J. Sun, Adv. Mater., 2023, 35, e2209379.
148. Y.-Y. Wang, J. Wang, S. Wang, Q.-C. Yang, A. Song, M.-J. Zhang, W.-D. Wang, Y.-T. Liu, J. Zhang, W.-M. Wang, Z. Xu and Z.-J. Sun, ACS Nano, 2024, 18, 20167–20180.
149. F. Ding, J. Liu, K. Ai, C. Xu, X. Mao, Z. Liu and H. Xiao, Adv. Mater., 2024, 36, 2306419.
150. Q. Yu, S. Sun, N. Yang, Z. Pei, Y. Chen, J. Nie, H. Lei, L. Wang, F. Gong and L. Cheng, J. Am. Chem. Soc., 2025, 147, 3161–3173.
151. J. Wu, Z. Liu, L. Wang, Z. Pei, Z. Han, X. Cui, X. Pan, J. Cao, Y. Huang, S. Sun, J. Wang, C. Cheng and L. Cheng, ACS Nano, 2025, 19, 8070–8084.
152. J. S. Muhammad, M. N. Jayakumar, N. M. Elemam, T. Venkatachalam, T. K. Raju, R. A. Hamoudi and A. A. Maghazachi, ImmunoTargets Ther., 2019, 8, 29–41.
153. Y. Ying, Y. Mao and M. Yao, Mol. Ther.–Nucleic Acids, 2019, 18, 801–814.
154. Y. Bai, Y. Pan and X. Liu, Nat. Rev. Mol. Cell Biol., 2025, 26, 501–521.
155. S. Huang, M. Shang, L. Guo, X. Sun, S. Xiao, D. Shi, D. Meng, Y. Zhao, X. Wang, R. Liu and J. Li, J. Nanobiotechnol., 2024, 22, 193.
156. G. Eskander, S. G. Abdelhamid, S. A. Wahdan and S. M. Radwan, Cell Death Discovery, 2025, 11, 56.
157. R. Miao, C. Jiang, W. Y. Chang, H. Zhang, J. An, F. Ho, P. Chen, H. Zhang, C. Junqueira, D. Amgalan, F. G. Liang, J. Zhang, C. L. Evavold, I. Hafner-Bratkovič, Z. Zhang, P. Fontana, S. Xia, M. Waldeck-Weiermair, Y. Pan, T. Michel, L. Bar-Peled, H. Wu, J. C. Kagan, R. N. Kitsis, P. Zhang, X. Liu and J. Lieberman, Immunity, 2023, 56, 2523–2541.e8.
158. Y. Deng, F. Jia, P. Jiang, L. Chen, L. Xing, X. Shen, L. Li and Y. Huang, Biomaterials, 2023, 301, 122293.
159. S. Rühl, K. Shkarina, B. Demarco, R. Heilig, J. C. Santos and P. Broz, Science, 2018, 362, 956–960.
160. J. Liu, R. Kang and D. Tang, Cancer Gene Ther., 2021, 28, 1–4.
161. Z. Li, F. Mo, Y. Wang, W. Li, Y. Chen, J. Liu, T.-J. Chen-Mayfield and Q. Hu, Nat. Commun., 2022, 13, 6321.
162. R. Zhang, S. Guan, Z. Meng, X. Deng and J. Lu, J. Agric. Food Chem., 2024, 72, 13966–13977.
163. E. Sahai, I. Astsaturov, E. Cukierman, D. G. DeNardo, M. Egeblad, R. M. Evans, D. Fearon, F. R. Greten, S. R. Hingorani, T. Hunter, R. O. Hynes, R. K. Jain, T. Janowitz, C. Jorgensen, A. C. Kimmelman, M. G. Kolonin, R. G. Maki, R. S. Powers, E. Puré, D. C. Ramirez, R. Scherz-Shouval, M. H. Sherman, S. Stewart, T. D. Tlsty, D. A. Tuveson, F. M. Watt, V. Weaver, A. T. Weeraratna and Z. Werb, Nat. Rev. Cancer, 2020, 20, 174–186.
164. X. Mao, J. Xu, W. Wang, C. Liang, J. Hua, J. Liu, B. Zhang, Q. Meng, X. Yu and S. Shi, Mol. Cancer, 2021, 20, 131.
165. D. Guo, X. Ji, H. Xie, J. Ma, C. Xu, Y. Zhou, N. Chen, H. Wang, C. Fan and H. Song, Adv. Mater., 2023, 35, 2301257.
166. J. Zou, C. Jiang, Q. Hu, X. Jia, S. Wang, S. Wan, Y. Mao, D. Zhang, P. Zhang, B. Dai and Y. Li, Nat. Commun., 2025, 16, 424.
167. H. Zhou, Y. Zhang, R. Zhang, M. Zhao, W. Chen, Y. Liu, Y. Jiang, Q. Li, Q. Miao and M. Gao, Adv. Mater., 2023, 35, 2211485.
168. M. Yang, C. Qin, L. Tao, G. Cheng, J. Li, F. Lv, N. Yang, Z. Xing, X. Chu, X. Han, M. Huo and L. Yin, Biomaterials, 2023, 301, 122253.

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Footnote

† J. Xie, B. Peng and Y. Xiao contributed equally to this work.

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