Stem cell mitochondrial transfer rejuvenates CAR-NKT cell metabolism and antitumor activity

Stem cell mitochondrial transfer rejuvenates CAR-NKT cell metabolism and antitumor activity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Stem cell mitochondrial transfer rejuvenates CAR-NKT cell metabolism and antitumor activity Yan-Ruide Li, Bo Zhang, Shubing Wang, Yichen Zhu, Xinyuan Shen, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8953703/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Chimeric antigen receptor–engineered natural killer T (CAR-NKT) cells have emerged as a promising cancer immunotherapy owing to their potent antitumor activity, efficient tissue homing, and capacity to remodel the immunosuppressive tumor microenvironment (TME). Although strategies such as cytokine engineering and checkpoint blockade have improved CAR-NKT cell function, approaches that enhance their metabolic fitness remain limited. Here, we rejuvenate CAR-NKT cell metabolism and antitumor activity through induced pluripotent stem cell–derived mitochondrial transfer (iPSC-MT). iPSC-MT markedly enhances mitochondrial activity and metabolic fitness in CAR-NKT cells, resulting in improved effector function, memory formation, and persistence while limiting exhaustion. CAR-NKT cells enhanced by iPSC-MT (CAR-NKTMito) exhibit superior cytotoxicity in vitro and robust antitumor efficacy in vivo across multiple xenograft mouse models, including human lymphoma, liver cancer, and ovarian cancer. Notably, CAR-NKTMito cells exhibit enhanced TME modulation through effective targeting of CD1d⁺ myeloid cells, outperforming conventional iPSC-MT-enhanced CAR-T cells. Together, these findings establish mitochondrial transfer as a powerful organelle-level metabolic reprogramming strategy to enhance CAR-NKT cell function and provide a new therapeutic paradigm for improving cellular immunotherapy against cancer. Biological sciences/Biotechnology/Metabolic engineering Biological sciences/Cancer/Cancer therapy Chimeric antigen receptor (CAR) invariant natural killer T (NKT) cell cancer immunotherapy mitochondrial transfer iPSC mitochondrial activity organelle-level metabolic reprogramming strategy metabolic fitness tumor microenvironment (TME) antitumor efficacy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Chimeric antigen receptor (CAR)-engineered invariant natural killer T (CAR-NKT) cells have been explored for their antitumor activity and possess several distinctive therapeutic advantages. These include potent cytotoxicity mediated through multiple tumor-targeting mechanisms involving the CAR, the invariant T cell receptor (TCR), and natural killer receptors (NKRs), as well as an intrinsic ability to traffic to and infiltrate solid tumors 1–5 . In addition, CAR-NKT cells can actively modulate the immunosuppressive tumor microenvironment (TME) by selectively eliminating CD1d-expressing myeloid populations, thereby alleviating local immune suppression 6–8 . Despite these favorable properties, CAR-NKT cell therapies continue to face substantial challenges, particularly in solid tumors, including limited long-term in vivo persistence, progressive exhaustion, and functional dysfunction 9–11 . To address these limitations, various genetic engineering strategies have been employed to enhance CAR-NKT cell function, durability, and metabolic fitness. Among these, cytokine engineering has been widely investigated, including expression of IL-15 to promote persistence, IL-12 to induce sustained Th1-polarized antitumor responses, and IL-18 to support metabolic reprogramming and effector function 12–16 . In parallel, biomimetic in vivo scaffolds capable of sustained release of α-galactosylceramide (α-GalCer or αGC), a potent NKT cell agonist, have been developed to recruit and activate CAR-NKT cells in situ and improve solid tumor targeting 17 . However, few engineering strategies are focused on targeting cellular metabolism to improve CAR-NKT cell persistence and antitumor efficacy. Mitochondrial transfer (MT) has recently emerged as a fundamental mechanism of intercellular communication that reshapes cellular metabolism and function across diverse physiological and pathological contexts 18 . Rather than being confined to cell-autonomous regulation, mitochondria can be actively exported and transferred between developmentally unrelated cell types, thereby reprogramming the metabolic state of recipient cells. In the central nervous system, astrocytes donate mitochondria to neurons to support neuronal survival following ischemic injury, while in the peripheral nervous system, macrophage-derived mitochondria are transferred to sensory neurons to dampen inflammatory pain signaling 19,20 . In injured tissues, activated platelets deliver mitochondria to mesenchymal stem cells (MSCs) to promote angiogenesis and wound repair, as well as to neutrophils to enhance antimicrobial defense 21,22 . Conversely, MSCs can transfer mitochondria to T cells, driving regulatory T cell differentiation and suppressing pro-inflammatory cytokine production, thereby limiting tissue damage in inflammatory diseases such as arthritis 23–25 . Within the TME, MT has been increasingly implicated in immune dysregulation and cancer progression. Tumor cells can acquire mitochondria from immune cells, including T cells and macrophages, to support their metabolic demands, enhance proliferation, and promote immune evasion 26,27 . Concurrently, metabolic reprogramming within the TME and mitochondrial dysfunction in tumor-infiltrating lymphocytes compromise antitumor immunity. For example, transfer of mutated mitochondrial DNA from cancer cells to T cells induces metabolic defects, cellular senescence, and impaired effector and memory functions, resulting in diminished antitumor responses both in vitro and in vivo 26,27 . Together, these findings identify MT as a powerful regulator of immune cell fitness and tumor–immune interactions, highlighting its potential as a therapeutic target to restore immune function in cancer. Accordingly, emerging therapeutic strategies have begun to exploit MT as a means to reprogram recipient cell metabolism and function. Recent studies have demonstrated that satellite glial cells can transfer mitochondria to dorsal root ganglion sensory neurons through tunneling nanotubes, thereby protecting against peripheral neuropathy 28 . Similarly, mitochondrial donation from bone marrow stromal cells has been shown to enhance mouse CD8⁺ T cell bioenergetic capacity, improve resistance to exhaustion, and augment antitumor efficacy, underscoring the potential of MT as a strategy to restore immune cell fitness 29 . However, direct intercellular MT is inherently inefficient and poses translational challenges due to the required presence of mitochondrial donor cells 29 . The co-transfer or persistence of these highly activated donor cells can result in cellular contamination of the final cellular product, introducing non-immune cell populations alongside therapeutic immune cells. Such heterogeneity limits clinical applicability and raises significant safety concerns for therapeutic use. To address these challenges and directly investigate the potential of MT for immune cell engineering, we harness mitochondria from human induced pluripotent stem cells (iPSCs) and transfer them to CAR-NKT cells in this study, as iPSCs possess highly functional, youthful mitochondria characterized by elevated respiratory capacity, low oxidative damage, and robust bioenergetic plasticity 30 . We apply this approach to enhance human CAR-NKT cells with the goal of improving mitochondrial activity, metabolic fitness, and functional durability. We demonstrate that iPSC-MT efficiently augments CAR-NKT cell mitochondrial function, promotes effector memory differentiation, and reduces exhaustion, resulting in markedly enhanced antitumor activity. Collectively, our findings establish MT as a promising metabolic engineering strategy to rejuvenate CAR-NKT cells and improve the efficacy of CAR-NKT cell–based cancer immunotherapy. Results iPSC-derived mitochondria are efficiently and robustly transferred into human CAR-NKT cells We established a platform to generate iPSC-MT-enhanced CAR-NKT (CAR-NKT Mito ) cells from peripheral blood mononuclear cells (PBMCs) obtained from healthy donors or cancer patients (Fig. 1a and Supplementary Table 1). Human NKT cells were first isolated from PBMCs and activated using αGC stimulation to enable rapid expansion. Expanded NKT cells were subsequently transduced with CARs targeting CD19, mesothelin (MSLN), or glypican-3 (GPC3) to generate antigen-specific CAR-NKT cells. In parallel, mitochondria were isolated from iPSCs and transferred ex vivo into CAR-NKT cells via an endocytosis-mediated uptake process 31,32 , resulting in efficient mitochondrial incorporation (Fig. 1a). Mitochondria derived from iPSCs were first labeled with MitoTracker Green (MTG), a membrane potential–independent fluorescent dye that selectively stains mitochondrial mass, enabling quantitative assessment of MT efficiency in CAR-NKT cells by flow cytometry. Both CAR-NKT and CAR-NKT Mito cell products exhibited high purity (>98%), confirming the robustness of the CAR-NKT manufacturing process (Fig. 1b). CAR-NKT Mito cells demonstrated efficient uptake of iPSC-derived mitochondria, with transfer efficiency increasing proportionally to the mitochondria-to–NKT (Mito:NKT) ratio, defined here as the number of iPSC donor cells relative to the number of NKT recipient cells (Fig. 1b, c). Using a Mito:NKT ratio of 4:1, we routinely achieved iPSC-MT efficiencies exceeding 50% (Fig. 1b, c). Subset analysis revealed that CD4 single-positive (SP) CAR-NKT cells displayed a significantly greater capacity for mitochondrial uptake compared with CD8 SP and double-negative (DN) CAR-NKT cells, suggesting subset-specific differences in metabolic demand and endocytic capacity that may underlie preferential mitochondrial acquisition (Fig. 1d-f) 33,34 . Immunofluorescence imaging confirmed successful transfer of iPSC-derived mitochondria into CAR-NKT cells using two complementary labeling approaches. In the first method, iPSCs were transfected with a mito-mScarlette plasmid to label mitochondria with red fluorescence prior to isolation and transfer. Following MT, recipient CAR-NKT cells were stained with MitoTracker Green, enabling discrimination between iPSC-derived mitochondria (red) and total mitochondrial mass (green) (Fig. 1g). This approach demonstrated clear incorporation of donor mitochondria within CAR-NKT cells, with transfer efficiencies of approximately 40–60% observed at 2–3 days post-transfer (Fig. 1h). Compared with CAR-NKT cells, CAR-NKT Mito cells exhibited increased mitochondrial content and robust retention of iPSC-derived mitochondria (Fig. 1i). In a second approach, iPSC mitochondria were labeled via BacMam Mitochondria-GFP transduction prior to isolation (Supplementary Fig. 1a). Immunofluorescence analysis similarly confirmed efficient and stable detection of GFP-labeled iPSC mitochondria within recipient CAR-NKT cells (Supplementary Fig. 1a and 1b). Together, these imaging strategies validate the efficiency, stability, and reproducibility of iPSC-MT into CAR-NKT cells. Notably, efficient iPSC-MT was observed across multiple iPSC lines, including those reprogrammed from fibroblasts and primary T cells (Fig. 1j). Comparable MT efficiencies (~50% at a Mito:NKT ratio of 4:1) were consistently achieved across these distinct iPSC sources, demonstrating the robustness and reproducibility of the iPSC-MT approach. iPSC-MT increases mitochondrial polarization, metabolic activity, and effector memory features in CAR-NKT cells Given the central role of mitochondrial fitness in sustaining immune cell function, we next examined whether iPSC-MT alters mitochondrial status and metabolic programs in CAR-NKT cells. Mitochondrial membrane potential was first assessed using JC-1 staining. Compared with conventional CAR-NKT cells, CAR-NKT Mito cells exhibited a marked increase in JC-1 polymer formation, indicating enhanced mitochondrial polarization and improved mitochondrial functional integrity (Fig. 1k, l) 35 . Consistent with these findings, flow cytometry analyses revealed that CAR-NKT Mito cells displayed significantly higher levels of MTG and MitoTracker Deep Red (MDR) compared with both quiescent PBMC-derived NKT cells and CAR-NKT cells (Fig. 1m, n). MTG and MDR signals reflect mitochondrial mass and mitochondrial membrane potential, respectively, together demonstrating increased mitochondrial content coupled with preserved functional activity in CAR-NKT Mito cells 36 . To determine whether these mitochondrial changes translated into altered cellular metabolism, we performed Seahorse extracellular flux analyses. CAR-NKT Mito cells exhibited significantly elevated basal and maximal oxygen consumption rates (OCR), as well as increased spare respiratory capacity, indicating enhanced oxidative phosphorylation (Fig. 1o, p). In parallel, extracellular acidification rate (ECAR) measurements revealed increased glycolytic activity following MT (Fig. 1o, p and Supplementary Fig. 1c). These coordinated enhancements in oxidative and glycolytic metabolism support a metabolically fit state associated with effector memory differentiation and sustained functional capacity. Together, these results demonstrate that iPSC-MT profoundly enhances mitochondrial function and metabolic activity in CAR-NKT cells, providing a bioenergetic foundation for their improved performance. We next examined how iPSC-MT influences CAR-NKT cell differentiation states. CAR-NKT and CAR-NKT Mito cells were stratified based on MTG intensity into four populations—Mito⁻, Mito low , Mito med , and Mito hi —representing increasing degrees of iPSC-derived mitochondrial incorporation (Fig. 1q). Phenotypic analysis using CD45RO and CD62L revealed a progressive shift toward effector memory–like differentiation with increasing mitochondrial content (Fig. 1q, r). Specifically, Mito hi CAR-NKT cells exhibited a marked enrichment of CD62L⁻CD45RO⁺ effector memory populations compared with Mito⁻ and Mito low subsets, whereas naïve and central memory–like populations were correspondingly reduced (Fig. 1q, r). This differentiation pattern closely correlated with MTG intensity, indicating a dose-dependent relationship between mitochondrial acquisition and CAR-NKT cell fate. These findings suggest that enhanced mitochondrial content promotes effector memory programming in CAR-NKT cells, providing a mechanistic link between MT, metabolic fitness, and functional differentiation. Overall, iPSC-MT preferentially drives CAR-NKT cells toward metabolically active, effector memory–enriched states that are associated with improved antitumor functionality. CAR-NKT Mito cells exhibit enhanced effector and memory features with robust cytotoxic and cytokine-producing capacity We next analyzed the phenotype and functional properties of mature CAR-NKT and CAR-NKT Mito cell products generated after 2–3 weeks of ex vivo expansion using clinically compatible culture conditions 4,7 . To assess the generalizability and translational relevance of this approach, we evaluated three distinct CAR constructs targeting CD19, MSLN, and GPC3, which are clinically validated antigens expressed in a range of malignancies, including B cell malignancies as well as lung, ovarian, and liver cancers (Fig. 2a). All antigen-specific CAR-NKT and CAR-NKT Mito cell products were generated with high purity, efficient CAR transduction, and robust MT. Across all constructs, CAR transduction efficiencies routinely exceeded 60%, with no significant differences observed between CAR-NKT and CAR-NKT Mito cells (Fig. 2b, c). Using MTG labeling, iPSC-derived mitochondria–positive CAR-NKT Mito cells could be isolated by flow cytometric sorting with >99% purity (Fig. 2b). Both CAR-NKT and CAR-NKT Mito cells exhibited robust expansion under clinically compatible culture conditions, achieving greater than 900-fold expansion over a 3-week manufacturing period (Fig. 2d). No consistent differences in CD4 and CD8 subpopulation distributions were observed between CAR-NKT and CAR-NKT Mito products, although donor-dependent variability was noted across independent manufacturing runs (Fig. 2e). Phenotypic analysis of memory differentiation revealed that CAR-NKT Mito cells displayed a significant enrichment of effector memory–like (CD62L⁻CD45RO⁺) populations, accompanied by a corresponding reduction in naïve and central memory–like subsets (Fig. 2f, g). These findings confirm that iPSC-MT promotes effector memory differentiation in final CAR-NKT cell products (Fig. 1q, r, 2f, and g). Consistent with this phenotype, CAR-NKT Mito cells expressed higher levels of activation markers CD25 and CD44, increased production of effector cytokines including IFN-γ and TNF-α, and elevated expression of cytotoxic molecules such as granzyme B, collectively indicating enhanced activation and cytotoxic potential (Fig. 2h, i). Functionally, upon α-GC stimulation in vitro , CAR-NKT Mito cells underwent more rapid and robust expansion compared with CAR-NKT cells and secreted higher levels of Th1-associated cytokines, including IFN-γ, TNF-α, and IL-2, with modest increases in Th2-associated IL-4 (Fig. 2j-l). Together, these results demonstrate that iPSC-MT enhances the activation, effector differentiation, and functional responsiveness of CAR-NKT cell products without compromising manufacturability. CAR-NKT Mito cells display enhanced long-term tumor-killing capacity in vitro We next evaluated the in vitro antitumor activity of CAR-NKT Mito cells using a series of cytotoxicity assays across multiple human tumor models. To assess the generalizability of mitochondrial enhancement across different CAR specificities, four human tumor cell lines were selected: the CD19⁺ lymphoma cell line RAJI, the MSLN + lung cancer cell line H226, the MSLN⁺ ovarian cancer cell line OVCAR8, and the GPC3 + liver cancer cell line SKHEP-1 (Fig. 3a). All tumor cell lines were engineered to express a firefly luciferase and enhanced green fluorescent protein dual-reporter (FG), enabling quantitative assessment of viable tumor cells by luminescence-based assays and flow cytometry (Fig. 3a). Target antigen expression was confirmed by flow cytometry prior to functional analyses (Fig. 3b). Tumor-killing assays were performed using five effector cell conditions: non-CAR-engineered NKT cells, CAR-NKT cells, CAR-NKT Mito cells, and CAR-NKT or CAR-NKT Mito cells subjected to five consecutive rounds of tumor cell coculture to model chronic antigen exposure and functional exhaustion (Fig. 3c). Across all tumor models, unmodified NKT cells exhibited minimal cytotoxicity, indicating limited CAR-independent tumor killing within 24 hours (Fig. 3d). In contrast, both CAR-NKT and CAR-NKT Mito cells mediated robust tumor cell elimination, with CAR-NKT Mito cells consistently demonstrating superior cytotoxic activity (Fig. 3d). Notably, following repeated tumor stimulation, CAR-NKT cells displayed a marked reduction in killing capacity, consistent with the development of functional exhaustion (Fig. 3d). In contrast, CAR-NKT Mito cells retained potent tumor-killing activity despite repeated antigen exposure, indicating enhanced resistance to exhaustion (Fig. 3d). Consistent with these functional differences, CAR-NKT Mito cells exhibited sustained proliferative capacity following tumor coculture, even after five rounds of stimulation, accompanied by elevated production of effector cytokines (IFN-γ, TNF-α, and IL-2), increased expression of the activation marker CD69, and higher levels of cytotoxic molecules including perforin and granzyme B (Fig. 3e-i). In contrast, repeatedly stimulated CAR-NKT cells progressively lost proliferative and effector capacity and showed significantly increased expression of exhaustion-associated markers, including PD-1, TIM-3, LAG-3, CTLA-4, and TIGIT (Fig. 3e-j). Finally, CAR-NKT Mito cells did not exhibit appreciable cytotoxicity toward nonmalignant cells, including primary skeletal muscle cells and dermal fibroblasts, demonstrating antigen-specific tumor killing without detectable off-target toxicity (Fig. 3k-m). Together, these findings indicate that iPSC-MT confers durable cytotoxic function, enhanced persistence, and improved exhaustion resistance to CAR-NKT cells while maintaining target specificity and safety. CAR-NKT Mito cells exhibit transcriptional programs associated with effector memory differentiation, cytotoxicity, and enhanced metabolic regulation To define the transcriptional impact of iPSC-MT, we performed single-cell RNA sequencing (scRNA-seq) on CD19-targeting CAR-NKT and CAR-NKT Mito cells following 3 days of coculture with RAJI lymphoma cells (Fig. 4a). scRNA-seq analysis confirmed uniformly high expression of canonical NKT cell identity markers across both groups, including the invariant NKT TCR α-chain ( TRAV10 ) and the lineage-defining transcription factor ZBTB16 ( PLZF ), validating preservation of NKT cell identity (Supplementary Fig. 2a). Unsupervised uniform manifold approximation and projection (UMAP) analysis of the combined dataset revealed four major cell clusters (Fig. 4b). Gene set enrichment analysis (GSEA) annotated these clusters as naïve-like, effector/memory-like, proliferative, and resting populations (Fig. 4b and Supplementary Fig. 2b) 5,7 . Compared with CAR-NKT cells, CAR-NKT Mito cells exhibited a marked enrichment of effector/memory-like clusters, accompanied by a relative reduction in proliferative populations (Fig. 4c, d). Consistent with this shift, violin plot analyses demonstrated increased expression of gene signatures associated with effector memory differentiation, cytotoxic function, and NK-like activity in CAR-NKT Mito cells (Fig. 4e and Supplementary Fig. 2c). Notably, genes involved in cytotoxicity ( GZMK , GNLY ), cytokine signaling ( IL2RA , IL2RG ), cell survival ( STAT3 , BCL2 ), TNF signaling ( TNFRSF1B , IRF1 ), antigen presentation ( CD74 ), and growth factor and differentiation pathways ( CSF1 , CSF2 ) were upregulated, indicating enhanced effector functionality and survival capacity (Fig. 4f and Supplementary Fig. 2d). Pathway enrichment analyses further revealed that CAR-NKT Mito cells upregulated programs related to nucleotide catabolism, hypoxic response, T cell activation and differentiation, cytokine responsiveness, metabolic regulation, and cell–cell communication, consistent with an activated and metabolically adaptable state (Fig. 4g). Focused analysis of metabolic pathways showed increased expression of genes involved in fructose and mannose metabolism, glycolysis, glycerolipid and steroid metabolism, and fatty acid synthesis, alongside reduced cholesterol biosynthesis (Fig. 4h). CAR-NKT Mito cells also upregulated genes associated with mitochondrial structure and oxidative metabolism ( OPA1 , DNM1L , SDHA , ACADVL , BNIP3 , BNIP3L ) as well as glycolytic and metabolic reprogramming regulators ( PKM , LDHA , RPTOR , HIF1A ), aligning with the enhanced oxidative and glycolytic capacity observed functionally (Fig. 4i). Together, these transcriptomic analyses demonstrate that iPSC-MT drives coordinated transcriptional reprogramming toward effector memory differentiation, cytotoxic competence, and metabolic fitness in CAR-NKT cells, providing a molecular basis for their enhanced persistence and antitumor activity. CAR-NKT Mito cells exhibit enhanced CAR signaling To determine whether mitochondrial modification augments CAR-mediated signaling, we examined downstream signaling events in CAR-NKT and CAR-NKT Mito cells following antigen engagement. CD19-specific CAR-expressing cells were stimulated with plate-coated CD19 antigen to mimic CAR–antigen interaction, and signaling molecules were analyzed by Western blot (Fig. 4j). Antigen stimulation induced activation of canonical CAR/TCR-associated signaling pathways in both cell types, as evidenced by increased phosphorylation of CD3ζ, ZAP-70, LAT, and PLC-γ1, as well as downstream effectors including STAT5, c-Jun, and NF-κB (Fig. 4k, l). Notably, CAR-NKT Mito cells consistently exhibited higher levels of phosphorylation across these signaling intermediates compared with conventional CAR-NKT cells (Fig. 4k, l). These findings indicate that iPSC-MT potentiates proximal and distal CAR signaling cascades, suggesting that CAR-NKT Mito cells possess amplified signal transduction capacity upon antigen engagement (Fig. 4m). CAR-NKT Mito cells exhibit unique TME–modulating capacity compared with CAR-T Mito cells CAR-NKT cells have been reported to remodel the immunosuppressive TME through selective targeting of CD1d⁺ myeloid populations, including tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), thereby overcoming a major barrier to effective solid tumor immunotherapy 6,8,37,38 . We therefore assessed whether iPSC-MT further enhances the TME-modulating capacity of CAR-NKT cells. In addition to CAR-NKT and CAR-NKT Mito cells, we included conventional CAR-T cells and iPSC-MT–enhanced CAR-T (CAR-T Mito ) cells as controls (Supplementary Fig. 3a). Notably, MT efficiency in CAR-T cells was substantially lower than in CAR-NKT cells, reaching only ~20–30% at a mitochondria-to–T cell ratio of 4:1, highlighting intrinsic differences in mitochondrial uptake capacity between these lineages (Supplementary Fig. 3b, c). We first evaluated TME modulation using primary human HCC tumor samples enriched for TAMs and MDSCs (Fig. 5a). Upon coculture, both CAR-NKT and CAR-NKT Mito cells efficiently depleted TAMs and MDSCs, with α-GC further enhancing killing through invariant NKT TCR–CD1d engagement (Fig. 5b). Importantly, CAR-NKT Mito cells consistently exhibited superior myeloid cell–depleting activity across all patient samples tested, indicating enhanced functional potency (Fig. 5b). Neither CAR-NKT nor CAR-NKT Mito cells showed appreciable cytotoxicity toward CD1d⁻ or CD1d low immune populations within the liver TME, including T cells, NK cells, and B cells, supporting their specificity and safety (Fig. 5c-e). In contrast, neither conventional CAR-T nor CAR-T Mito cells demonstrated significant TAM or MDSC killing, underscoring a CAR-NKT–specific mechanism of TME modulation (Fig. 5f, g). These findings were further validated in a 3D tumor organoid model incorporating tumor cells and PBMC-derived, monocyte-polarized M2 macrophages to recapitulate immunosuppressive TME interactions 39,40 . M2 macrophages exhibited high expression of CD163, CD206, and CD1d, confirming their suppressive phenotype and susceptibility to NKT-mediated targeting (Fig. 5h-j). In this system, both CAR-NKT and CAR-NKT Mito cells mediated dual killing of tumor cells and TAMs, accompanied by increased expression of activation marker CD69 and cytotoxic molecules perforin and granzyme B (Fig. 5k-n). Across all tumor models tested, CAR-NKT Mito cells consistently outperformed CAR-NKT cells in both tumor and TAM elimination (Fig. 5k-n). By contrast, CAR-T and CAR-T Mito cells exhibited markedly impaired tumor killing and reduced cytotoxic molecule production, likely due to profound suppression by TAMs within the organoid system (Fig. 5o, p). Collectively, these results demonstrate that iPSC-MT uniquely amplifies the intrinsic ability of CAR-NKT cells to simultaneously target tumor cells and remodel the immunosuppressive TME (Fig. 5q). CAR-NKT Mito cells overcome myeloid-mediated suppression to sustain tumor killing, whereas CAR-T Mito cells remain constrained by TAM/MDSC-driven inhibition (Fig. 5q). This dual antitumor and TME-modulating activity distinguishes CAR-NKT Mito cells as a particularly promising platform for solid tumor immunotherapy. CAR-NKT Mito cells demonstrate superior antitumor efficacy in multiple xenograft mouse models We next evaluated the in vivo antitumor efficacy of CAR-NKT and CAR-NKT Mito cells across three xenograft mouse models representing distinct CAR specificities and disease contexts. These included a CD19⁺ RAJI-FG human lymphoma model, in which tumor cells were intravenously injected to establish systemic disease with dissemination to the liver, lung, and bone marrow (Fig. 6a-d); a GPC3⁺ SKHEP-1-FG liver cancer model, in which intravenously injected tumor cells preferentially engrafted and expanded within the liver, forming an orthotopic liver cancer model (Fig. 6e-h); and an MSLN⁺ OVCAR8-FG ovarian cancer model, in which intraperitoneal injection resulted in peritoneal tumor dissemination characteristic of advanced ovarian cancer (Fig. 6i-l). Together, these models encompass hematologic malignancy, orthotopic solid tumor growth, and disseminated peritoneal disease, providing a comprehensive assessment of CAR-NKT Mito cell antitumor activity in vivo . In all three models, robust tumor growth was observed in the expected anatomical sites, confirming successful disease establishment (Fig. 6c, g, and k). Treatment with either CAR-NKT or CAR-NKT Mito cells significantly suppressed tumor progression and prolonged animal survival (Fig. 6b-d, f-h, and j-l). Notably, CAR-NKT Mito cells consistently achieved superior tumor control compared with CAR-NKT cells across all models (Fig. 6b-d, f-h, and j-l). In both the RAJI-FG lymphoma and OVCAR8-FG ovarian cancer models, CAR-NKT Mito therapy resulted in complete tumor elimination and durable, tumor-free long-term survival (Fig. 6b-d, and j-l). Overall, these results demonstrate that iPSC-MT markedly enhances the in vivo antitumor potency of CAR-NKT cells across diverse tumor types and anatomical settings. The ability of CAR-NKT Mito cells to achieve durable tumor control and long-term survival in both hematologic and solid tumor models highlights the broad therapeutic potential of organelle-level metabolic reprogramming as a strategy to improve cellular immunotherapy. CAR-NKT Mito cells demonstrate enhanced in vivo persistence, effector memory differentiation, and reduced exhaustion across multiple xenograft models To elucidate the mechanisms underlying the superior in vivo antitumor efficacy of CAR-NKT Mito cells, we analyzed therapeutic cells recovered from xenograft-bearing mice, focusing on their persistence, tissue distribution, phenotype, and functional status. In the RAJI-FG human lymphoma model, CAR-NKT Mito cells demonstrated significantly enhanced in vivo persistence and widespread tissue infiltration, including the liver, lung, peripheral blood, and spleen (Fig. 7a, b). Consistent with sustained functional activity, plasma cytokine analyses revealed elevated levels of effector cytokines IFN-γ and TNF-α in CAR-NKT Mito cell-treated mice (Fig. 7c). Phenotypic analysis of liver-infiltrating cells further showed that CAR-NKT Mito cells expressed higher levels of activation and effector markers, including CD69 and CD25, increased expression of cytotoxic molecules perforin and granzyme B, and reduced expression of late exhaustion-associated markers, including TOX, TIM-3, LAG-3, TIGIT, and CTLA-4, compared with CAR-NKT cells (Fig. 7d-f). Together, these findings indicate that iPSC-MT supports sustained effector function while limiting terminal exhaustion in vivo . Similar phenotypic and functional advantages of CAR-NKT Mito cells were observed in the SKHEP-1-FG liver cancer and OVCAR8-FG ovarian cancer models, including enhanced persistence, increased effector activation, and reduced exhaustion (Fig. 7g-n, and Supplementary Fig. 4a, b). Notably, CAR-NKT Mito cells preferentially accumulated within tumor-relevant anatomical sites—enriching in the liver in the SK-HEP-1-FG model and in the peritoneal cavity in the OVCAR8-FG model—reflecting efficient tumor-directed trafficking and tissue-specific homing (Fig. 7g, k). Immunohistochemical analyses further confirmed robust migration and infiltration of CAR-NKT Mito cells into tumor-containing tissues (Fig. 7o-r). Overall, these results demonstrate that iPSC-MT endows CAR-NKT cells with durable in vivo persistence, enhanced effector memory differentiation, efficient tumor-site homing, and resistance to exhaustion across diverse tumor contexts. This coordinated enhancement of cellular fitness and functionality provides a mechanistic foundation for the superior antitumor efficacy of CAR-NKT Mito cells observed in vivo and establishes MT as a powerful strategy to optimize CAR-NKT cell performance in both hematologic and solid tumor settings. Discussion Organelle-level metabolic reprogramming, particularly through MT, has emerged as a promising mechanism for altering recipient cell phenotype and function 27–29 . In physiological and pathological contexts, MT most commonly occurs in vivo through cell contact–dependent mechanisms, including tunneling nanotubes, transient cell fusion events, and gap junction–mediated transfer 31,41 . In addition, mitochondria can be transferred through cell contact–independent pathways, in which extracellular mitochondria are released and subsequently internalized by neighboring or distant cells via the circulation 31,42 . Despite these advances, approaches to precisely and controllably harness MT for therapeutic immune cell engineering remain limited. In particular, cell contact–independent MT may compromise product purity through inadvertent donor cell contamination, creating heterogeneity that complicates standardization, quality control, and clinical translation. In this study, we establish a defined ex vivo approach to achieve stem cell–derived MT into CAR-NKT cells, leveraging the robust metabolic capacity of iPSC mitochondria and the unique antitumor properties of CAR-NKT cells, including multispecific tumor targeting, TME modulation, and efficient solid tumor homing 8,38,43 . By directly reprogramming cellular metabolism at the organelle level, this strategy rejuvenates CAR-NKT cell bioenergetics, persistence, and effector function while limiting exhaustion, representing a conceptual departure from conventional genetic or signaling-based CAR optimization approaches. NKT cells are governed by metabolic programs that are fundamentally distinct from those of conventional αβ T cells, reflecting their innate-like biology and rapid effector function 1,44,45 . Whereas activated CD4⁺ T cells predominantly adopt aerobic glycolysis and lactate production, NKT cells preferentially route glucose-derived carbon into the pentose phosphate pathway and mitochondrial oxidative metabolism 34 . As a consequence, NKT cell viability and effector function are highly sensitive to extracellular metabolic conditions, with elevated lactate concentrations impairing their homeostasis and cytokine production. Mitochondrial metabolism plays a particularly critical role in invariant NKT cell biology 33 : NKT cell development is exquisitely sensitive to disruptions in electron transport chain function, and mature NKT cells exhibit limited fatty acid oxidation and reduced mitochondrial respiratory reserve under steady-state conditions. At the signaling level, mitochondrial activity integrates metabolic inputs with TCR and IL-15 signaling, shaping downstream NFAT activation and effector programming 33 . Together, these features define a unique metabolic dependency landscape in NKT cells, suggesting that targeted enhancement of mitochondrial function may represent an especially effective strategy to modulate CAR-NKT cell fate and functionality, distinct from approaches applied to conventional CAR-T cells. Consistent with these intrinsic metabolic features, CAR-NKT cells exhibit metabolic programs that differ from those of conventional CAR-T cells, including a greater reliance on lipid metabolism within the TME 46–48 . These distinctive metabolic dependencies suggest that targeted enhancement of mitochondrial capacity may exert particularly pronounced effects on CAR-NKT cell function. In line with this hypothesis, CAR-NKT Mito cells demonstrated potent antitumor activity both in vitro and in vivo across multiple human tumor xenograft models, including disseminated hematologic malignancies, orthotopic liver cancer, and intraperitoneal ovarian cancer (Fig. 6). Notably, CAR-NKT Mito cells efficiently trafficked to tumor-resident tissues in all models, indicating robust tumor-homing capacity that is favorable for solid tumor therapy (Fig. 7). Beyond direct tumor cytotoxicity, CAR-NKT Mito cells effectively remodeled the immunosuppressive TME by selectively depleting CD1d⁺ myeloid populations (Fig. 5), a key barrier to effective antitumor immunity and a known limitation of conventional CAR-T therapies 49–52 . Together, these findings position CAR-NKT Mito cells as a metabolically optimized cellular therapy with unique advantages for targeting both tumor cells and the TME. Notably, because the invariant NKT TCR recognizes lipid antigens presented by the non-polymorphic MHC class I–like molecule CD1d, CAR-NKT cells are not expected to induce graft-versus-host disease (GvHD), supporting their development as off-the-shelf allogeneic cellular therapies 9,53–55 . Accordingly, multiple allogeneic CAR-NKT platforms have been generated, including products derived from peripheral blood mononuclear cells and hematopoietic stem and progenitor cells 7,14,37,56,57 . Recent clinical studies of CD19-targeting CAR-NKT cells incorporating short hairpin RNA–mediated knockdown of β2-microglobulin and CD74 to reduce HLA class I and class II expression have demonstrated feasibility, safety, and preliminary antitumor activity 58 . However, despite these advances, the in vivo persistence of allogeneic CAR-NKT cells remains limited, likely due to host-mediated immune rejection. Our findings suggest that metabolic rejuvenation via iPSC-MT may provide a complementary strategy to enhance the durability of allogeneic CAR-NKT cell therapies. CAR-NKT Mito cells exhibit enhanced bioenergetic capacity, sustained expansion, and reduced expression of exhaustion-associated markers following tumor encounter in vivo (Fig. 7), features that are consistent with improved functional persistence. Thus, organelle-level metabolic reprogramming may uniquely support the long-term survival and antitumor efficacy of allogeneic CAR-NKT cells, offering a potential solution to a major limitation of current off-the-shelf cellular immunotherapies. Finally, MT–mediated metabolic reprogramming represents a modular strategy that can be readily integrated with other approaches to enhance CAR-NKT cell function. iPSC-MT may be combined with cytokine-based augmentation, including IL-15, IL-18, or IL-21 signaling, as well as immune checkpoint modulation, to further optimize CAR-NKT cell persistence and effector activity 12,13,59–61 . Recent studies have highlighted distinct checkpoint regulatory pathways governing CAR-NKT and CAR-T cells, with CAR-NKT cell function preferentially constrained by CD96, whereas CAR-T cells are more strongly regulated by TIGIT, underscoring the need for lineage-specific combinatorial strategies 48 . The ability to metabolically fortify CAR-NKT cells is likely to be particularly advantageous in hostile TMEs characterized by hypoxia, nutrient deprivation, and immunosuppressive signaling, where conventional cellular therapies often fail 50,62–65 . Additionally, beyond iPSC-derived mitochondria, other stem cell sources, including MSCs and embryonic stem cells (ESCs), may serve as alternative mitochondrial donors for CAR-NKT cell engineering, warranting further development and systematic side-by-side comparison. Together, our findings establish organelle-level metabolic reprogramming as a versatile platform for arming CAR-NKT cells and provide a rational framework for developing next-generation cellular immunotherapies for metabolically challenging cancers. Methods Study approval This study complies with all relevant ethical regulations. All experiments involving primary HCC patient samples were approved by the Ronald Reagan UCLA Medical Center (IRB# IRB-25-0948). Animal studies were approved by the Division of Laboratory Animal Medicine at UCLA. Healthy donor PBMCs were provided by the UCLA/CFAR Virology Core Laboratory without identification information under federal and state regulations. Mice NOD.Cg- Prkdc scid Il2rg tm1Wjl /SzJ (NOD- scid IL2Rg null , NSG) mice were purchased from The Jackson Laboratory, and maintained in animal facilities of the UCLA in a temperature-controlled environment (68 °F to 79 °F) with a 12-hour light cycle. 6- to10-week-old mice were used for all experiments. All mice were bred and maintained under specific pathogen-free conditions. All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of UCLA, and all animal procedures were conducted in accordance with the animal care and use regulations of the Division of Laboratory Animal Medicine (DLAM) at UCLA. Given the nature of the lymphoma, orthotopic liver cancer, and orthotopic ovarian cancer models, there were no restrictions on tumor size or burden, making direct inferences from external measures unfeasible. No differences in tumor growth or treatment response were observed between male and female mice in these xenograft models. In some studies, both male and female mice were used within the same group or assigned to separate groups. Experimental mice were randomly assigned to treatment groups to avoid statistically significant differences in the baseline tumor burden. Cell culture media and reagents Recombinant human IL-2, IL-7, and IL-15 were purchased from PeproTech. Fetal bovine serum (FBS), and β-mercaptoethanol (β-ME) were purchased from Sigma. Penicillin-streptomycin-glutamine (P/S/G), MEM nonessential amino acids (NEAA), HEPES buffer solution, and sodium pyruvate were purchased from Gibco. Normocin was purchased from InvivoGen. The RPMI 1640 cell culture medium and the DMEM cell culture medium were purchased from Thermo Fisher Scientific. The CryoStor Cell Cryopreservation Media CS10 was purchased from MilliporeSigma. The mTeSR Plus medium used for iPSC culture was purchased from STEMCELL Technologies. The C10 medium was made of RPMI 1640 cell culture medium supplemented with FBS (10% v/v), P/S/G (1% v/v), NEAA (1% v/v), HEPES (10 mM), sodium pyruvate (1 mM), β-ME (50 μM), and Normocin (100 μg/ml). The D10 medium was made of DMEM supplemented with FBS (10% v/v), P/S/G (1% v/v), and Normocin (100 μg/ml). The R10 medium was made of RPMI 1640 supplemented with FBS (10% v/v), P/S/G (1% v/v), and Normocin (100 μg/ml). Lentiviral vectors All lentiviral vectors used in this study were constructed from a parental vector pMNDW 8,66 . The 2A sequence derived from foot-and-mouth disease virus (F2A) was used to link the inserted genes to achieve co-expression. The Lenti/FG vector was constructed by inserting a synthetic bicistronic gene encoding Fluc-P2A-EGFP into the pMNDW 8,67 . The Lenti/CAR19 vector was constructed by inserting a synthetic gene encoding human CD19-targeting CAR into the pMNDW. The Lenti/MCAR vector was constructed by inserting a synthetic gene encoding human MSLN-targeting CAR into the pMNDW. The Lenti/GCAR vector was constructed by inserting a synthetic gene encoding human GPC3-targeting CAR into the pMNDW. The synthetic gene fragments were obtained from GenScript and IDT. Lentiviruses were produced using human embryonic kidney 293T (HEK293T) cells (ATCC), following a standard transfection protocol using the Trans-IT-Lenti Transfection Reagent (Mirus Bio) and a centrifugation concentration protocol using the Amicon Ultra Centrifugal Filter Units, according to the manufacturer’s instructions (MilliporeSigma). Stable tumor cell lines Human lymphoma cell line RAJI (cat. no. CCL-86), lung cancer cell line H226 (cat. no. CRL-5826), and liver cancer cell line SKHEP1 (cat. no. HTB-52) were purchased from the ATCC. Human ovarian cancer cell line OVCAR8 was generously provided by the Division of Cancer Treatment and Diagnosis (DCTD) Tumor Repository at the National Institutes of Health (NIH). The parental tumor cell lines were transduced with lentiviral vectors encoding the intended gene(s) to produce stable tumor cell lines overexpressing FG. 72 hours post lentivector transduction, cells were subjected to flow cytometry sorting to isolate gene-engineered cells for generating stable cell lines. Four stable tumor cell lines were generated for this study, including RAJI-FG, H226-FG, SKHEP1-FG, and OVCAR8-FG cell lines. All tumor cell lines utilized in this study underwent short tandem repeat (STR) profiling, and the resulting profiles were compared to established databases to confirm accurate identification. Furthermore, the cell lines were regularly screened for mycoplasma contamination to preserve their integrity and authenticity. iPSC lines Multiple human iPSC lines were used in this study, including fibroblast-derived and T cell–derived lines. All protocols involving pluripotent stem cells were approved by the Human Embryonic Stem Cell Research Oversight Committee and the Institutional Review Board. Fibroblast-derived iPSC lines included DMD 1001 R1 (generated by RNA reprogramming of healthy female fibroblasts) 68 , iPS11 (Alstem Cell Advancements, cat. no. iPSC11), hiPS2 (UCLA Broad Stem Cell Research Center Stem Cell Core) 69 , and XFiPS xeno-free human iPSCs (UCLA Broad Stem Cell Research Center Stem Cell Core) 70 . Cells were maintained either on growth factor–reduced Matrigel (BD Biosciences, cat. no. 356231) in mTeSR complete medium (StemCell Technologies, cat. no. 05850) according to standard culture conditions. Healthy donor T cells were reprogrammed into iPSCs using a modified, integration-free episomal plasmid method (Okita et al., 2013). Briefly, 1 × 10 6 naïve/memory T cells were electroporated with 3 μg of episomal plasmids encoding OCT3/4, SOX2, KLF4, L-MYC, LIN28, and shRNA targeting TP53 using the Human T Cell Nucleofector Kit and 4D-Nucleofector system (Lonza). Following electroporation, cells were cultured in X-VIVO 15 medium (Lonza) supplemented with 10% FBS (HyClone), 50 U/mL recombinant human IL-2 (Novartis Oncology), 0.5 ng/mL recombinant human IL-15 (CellGenix), and Dynabeads Human T-Expander CD3/CD28 (Thermo Fisher Scientific) at a 1:1 bead-to-cell ratio. Two days post-transfection, PSC medium containing basic fibroblast growth factor (bFGF) and 10 μM Y-27632 was added. The medium was fully replaced with PSC medium on day 4. Emerging iPSC colonies were visible between days 20–30 and were manually picked for expansion in cGMP-grade mTeSR1 medium on Matrigel-coated (Corning) plates. Unless otherwise specified, the majority of experiments were performed using the iPS11 cell line. Liver and PBMC sample collection Primary HCC patient samples, including liver tumor and peripheral blood samples, were collected at the Ronald Reagan UCLA Medical Center from consented patients through an IRB-approved protocol (IRB-25-0948) and processed. Information regarding the patients' gender and age was not provided in this study to avoid including three or more indirect identifiers for the study participants. Patient gender was not considered in the study design and was determined based on self-reporting. Healthy donor-derived PBMCs were provided by the UCLA/CFAR Virology Core Laboratory without identification information under federal and state regulations. PBMCs were cryopreserved in Cryostor CS10 (Sigma St. Louis, MO, USA) using CoolCell (BioCision, Larkspur, CA, UCA), and were frozen in liquid nitrogen for storage and to supply all experiments. Antibodies and flow cytometry Fluorochrome-conjugated antibodies specific for human CD3 (clone HIT3a, Pacific Blue, PE, or PE-Cy7-conjugated, 1:500, cat. no. 300330, 300308, or 300316), CD4 (clone OKT4, PE-Cy7, PerCP, or FITC-conjugated, 1:500, cat. no. 317414, 317432, or 317408), CD8 (clone SK1, PE, APC-Cy7, or APC-conjugated, 1:300, cat. no. 344706, 344714, or 344722), CD14 (clone HCD14, FITC-conjugated, 1:200, cat. no. 325604), CD11b (clone W18347A, APC-conjugated, 1:500, cat. no. 340008), CD25 (clone BC96, APC-conjugated, 1:200, cat. no. 302610), CD44 (clone BJ18, PE-conjugated, 1:200, cat. no. 338808), CD45 (clone HI30, PerCP, FITC or Pacific Blue-conjugated, 1:500, cat. no. 304026, 304038, or 304022), CD69 (clone FN50, PE-Cy7 or PerCP-conjugated, 1:50, cat. no. 310912 or 310928), TCRαβ (clone I26, Pacific Blue or PE-Cy7-conjugated, 1:25, cat. no. 306715 or 306720), IFN-γ (clone B27, PE-Cy7-conjugated, 1:50, cat. no. 506518), Granzyme B (clone QA16A02, APC-conjugated, 1:2,000 or 1:5,000, cat. no. 372204), Perforin (clone dG9, PE-Cy7-conjugated, 1:50 or 1:100, cat. no. 308126), IL-2 (clone MQ1-17H12, APC-Cy7-conjugated, 1:50, cat. no. 500342), PD-1 (clone A17188A, FITC, APC, or PE-conjugated, 1:50, cat. no. 379206, 379208, or 379210), LAG-3 (clone 11C3C65, FITC, APC-Cy7, or PE-conjugated, 1:50, cat. no. 369308, 369348, or 369306), TIM-3 (clone A18087E, PE or APC-conjugated, 1:50, cat. no. 364806 or 364804), CD1d (clone 51.5, PE-Cy7-conjugated, 1:50, cat. no. 350310), CD163 (clone GHI/61, PE-conjugated, 1:200, cat. no. 333606), CD206 (clone 15-2, APC-conjugated, 1:200, cat. no. 321110), CD62L (clone W21031N, PE-Cy7-conjugated, 1:50, cat. no. 384808), and CD45RO (clone UCHL1, PE-Cy7 or APC-Cy7-conjugated, 1:100, cat. no. 304230 or 304228) were purchased from BioLegend. Fluorochrome-conjugated antibodies specific for human TCR Vα24-Jβ18 (clone 6B11, PE-conjugated, 1:10, cat. no. 552825) were purchased from BD Biosciences. Fixable Viability Dye eFluor506 (e506, 1:500) was purchased from Affymetrix eBioscience. Mouse Fc Block (anti-mouse CD16/32) was purchased from BD Biosciences, and human Fc Receptor Blocking Solution (TrueStain FcX) was purchased from BioLegend. All flow cytometry staining was performed following standard protocols, as well as specific instructions provided by the manufacturer of a particular antibody. Stained cells were analyzed using a MACSQuant Analyzer 10 flow cytometer (Miltenyi Biotech), following the manufacturers’ instructions. FlowJo software version 9 (BD Biosciences) was used for data analysis. In our study, note the use of antibodies with identical clones but differing conjugated fluorochromes, with one typical antibody listed herein. For intracellular cytokine staining, the cells were thawed and resuspended in C10 medium. Cells were stimulated with PMA (Calbiochem, cat. no. 524400; 50 ng/mL) and ionomycin (Calbiochem, cat. no. 407952.; 500 ng/mL) and incubated at 37°C for 2 hours. GolgiStop (BD Biosciences, car. No. 554724; 1.5 µL/mL) was then added to inhibit cytokine secretion, followed by an additional 4-hour incubation. Subsequently, intracellular staining was performed using the Cell Fixation/Permeabilization Kit (BD Biosciences, cat. no. 554714) according to the manufacturer’s instructions. Enzyme-linked immunosorbent cytokine assays (ELISAs) The ELISAs for detecting human cytokines were performed following a standard protocol from BD Biosciences. Supernatants from cell culture assays were collected and assayed to quantify human IFN-γ, IL-2, IL-4, and TNF-α. The capture and biotinylated pairs for detecting cytokines were purchased from BD Biosciences. The streptavidin-HRP conjugate was purchased from Invitrogen. Human cytokine standards were purchased from eBioscience. Tetramethylbenzidine substrate was purchased from KPL. The samples were analyzed for absorbance at 450 nm using an Infinite M1000 microplate reader (Tecan). iPSC mitochondrial extraction Mitochondria were isolated from iPSC cells using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874), following the manufacturer’s reagent-based protocol. Briefly, harvested iPSCs were pelleted by centrifugation and resuspended in Mitochondria Isolation Reagent A supplemented with EDTA-free protease inhibitor cocktail. Cells were incubated on ice and subsequently treated with Mitochondria Isolation Reagent B, followed by incubation on ice with intermittent vortexing. Mitochondria Isolation Reagent C was then added, and the lysates were subjected to differential centrifugation to remove nuclei and cellular debris. The post-nuclear supernatant was centrifuged to pellet the mitochondrial fraction. The mitochondrial pellet was washed once with Mitochondria Isolation Reagent C and maintained on ice prior to downstream applications. For preparation of fluorescently labeled mitochondria, iPSCs were incubated with MitoTracker Green (50 nM; Thermo Fisher Scientific, cat. no. M7514) or MitoTracker Deep Red (50 nM; Thermo Fisher Scientific, cat. no. M22426) for 30 min at 37 °C prior to mitochondrial isolation. After staining, cells were washed with PBS and processed for mitochondrial isolation as described above. Generation of CAR-NKT and CAR-NKT Mito cells Healthy donor PBMCs were sorted with MACS via Anti-iNKT Microbeads (Miltenyi Biotech, cat. no. 130-094-842) labeling to enrich NKT cells, following the manufacturer’s instructions. The enriched NKT cells were mixed with donor-matched irradiated αGC/PBMCs at a ratio of 1:1 - 1:2, followed by culturing in C10 medium supplemented with 10 ng/ml IL-7 and IL-15. On day 3, NKT cells were transduced with lentiviruses (e.g., Lenti/CAR19, Lenti/GCAR, or Lenti/MCAR) for 24 h. The resulting CAR-NKT cells were expanded for about 2 weeks in C10 medium supplemented with 10 ng/ml IL-7 and IL-15 and cryopreserved for future use. CAR-NKT Mito cells were generated by transferring mitochondria derived from iPSCs into NKT cells 24 hours after CAR transduction. iPSCs and NKT cells were counted using a hemocytometer, and the desired donor-to-recipient ratios were calculated prior to mitochondrial isolation. Mitochondria were isolated from iPSCs using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874) according to the manufacturer’s instructions. Freshly isolated mitochondria were then added to CAR-NKT cells cultured in C10 medium at the indicated ratios. Mitochondrial transfer efficiency was assessed using MitoTracker Green–labeled mitochondria followed by flow cytometric analysis. For subsequent functional assays, CAR-NKT Mito and CAR-NKT cells were FACS-sorted 2 days post–mitochondrial transfer based on FITC fluorescence, expanded in culture for an additional 2 weeks, and then used for tumor cytotoxicity and other assays. Generation of conventional CAR-T and CAR-T Mito cells Non-treated tissue culture 24-well or 12-well plates (Corning) were coated with Ultra-LEAF TM Purified Anti-Human CD3 Antibody (Clone OKT3; BioLegend, cat. no. 317326) at 1 μg/ml (500 μl/well), at room temperature for 2 hours or alternatively, overnight at 4 °C. Healthy donor PBMCs were resuspended in the C10 medium supplemented with 1 μg/ml Ultra-LEAF TM Purified Anti-Human CD28 Antibody (Clone CD28.2, BioLegend, cat. no. 302943) and 30 ng/ml IL-2, followed by seeding in the pre-coated plates at 1 x 10 6 cells/ml (1 ml/well). On day 2, cells were transduced with lentiviruses (e.g., Lenti/CAR19, Lenti/GCAR, or Lenti/MCAR) for 24 hours. The resulting CAR-T cells were expanded for about 2 weeks in C10 medium supplemented with human IL-2 and cryopreserved for future use. CAR-T Mito cells were generated by transferring mitochondria derived from iPSCs into T cells 24 hours after CAR transduction. Mitochondria were isolated from iPSCs using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874) according to the manufacturer’s instructions. Freshly isolated mitochondria were then added to CAR-T cells cultured in C10 medium at the indicated ratios. Mitochondrial transfer efficiency was assessed using MitoTracker Green–labeled mitochondria followed by flow cytometric analysis. Immunofluorescence staining and imaging A plasmid encoding mito-mScarlette containing a mitochondrial targeting sequence (MTS) was obtained from the Advanced Microscopy Facility for Mitochondrial Research. The mito-mScarlette plasmid was transfected into iPSCs using Lipofectamine 3000 (Thermo Fisher Scientific, cat. no. L3000008), according to the manufacturer’s instructions. Three days after transfection, mitochondria were isolated from iPSCs using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874). The isolated mitochondria were then co-incubated with CAR-NKT cells for 24 h. For fluorescence staining, 0.5 × 10 6 cells were collected from each experimental group and stained with MitoTracker Green (50 nM; Thermo Fisher Scientific, cat. no. M7514) for 30 min at 37 °C, followed by nuclear staining with Hoechst 33342 (Thermo Fisher Scientific, cat. no. H21486) for 5 min. Cells were washed three times with PBS and centrifuged at 300 × g to deposit onto coverslips coated with poly-L-lysine (Thermo Fisher Scientific, cat. no. A3890401). Fluorescence images were acquired using a Leica Confocal SP8-STED/FLIM/FCS microscope. In this assay, iPSC-derived mitochondria were visualized in red due to mito-mScarlette expression, whereas total mitochondria were labeled in green with MitoTracker Green. In a separate imaging assay, iPSCs were transduced with BacMam 2.0 Mitochondria-GFP (Thermo Fisher Scientific, cat. no. C10600) to label mitochondria with GFP, according to the manufacturer’s instructions. Three days after transduction, mitochondria were isolated using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874) and co-incubated with CAR-NKT cells for 24 h. Cells (0.5 × 10 6 per group) were stained with CellTracker Red (Thermo Fisher Scientific, cat. no. C34552) for 30 min and Hoechst 33342 (Thermo Fisher Scientific, cat. no. H21486) for 5 min, followed by three washes with PBS. Cells were centrifuged at 300 × g and deposited onto poly-L-lysine–coated coverslips. Fluorescence images were acquired using a Zeiss fluorescence microscope. XFe96 seahorse assay CAR-NKT and CAR-NKT Mito cells were collected and cryopreserved in liquid nitrogen. Prior to metabolic analysis, the cells were thawed and recovered in C10 medium for 24 hours before being sent to the UCLA Metabolomics Core. The recovered cells were then centrifuged onto a poly-L-lysine–coated 96-well Seahorse plate at 300 × g for 5 minutes, with 2.5 × 10 5 cells seeded per well. The culture plate was placed in the Seahorse XFe96 Analyzer (Agilent Technologies), and the standard acquisition program was executed. The assay included an equilibration step followed by sequential measurements of basal respiration, post-oligomycin injection, and post-FCCP (Carbonyl cyanide-4-(trifluoromethoxy)phenylhydrazone) injection. Each measurement cycle consisted of three loops of 3-minute mixing, 2-minute waiting, and 3-minute measuring phases. Data were analyzed using Wave 2.6.1 software (Agilent Technologies). In vitro tumor cell killing assay Liver tumor cells (1 10 4 cells per well) were co-cultured with therapeutic cells (at ratios indicated in the figures or figure legends) in Corning 96-well clear bottom black plates for 24 h in C10 medium. D-luciferin (150 mg/ml, Caliper Life Science) was added to cell cultures to quantify live tumor cells and luciferase activities were read out using an Infinite M1000 microplate reader (Tecan). Live tumor cell numbers were normalized to the luminescence signal from tumor-only wells without therapeutic cells. In vitro assays using primary HCC patient samples In one assay, the primary HCC patient samples were analyzed for the TME composition using flow cytometry. T cells were identified as CD45 + CD3 + cells, CD4 T cells were identified as CD4 + T cells, CD8 T cells were identified as CD8 + T cells, B cells were identified as CD45 + CD19 + or CD45 + CD20 + cells, NK cells were identified as CD45 + CD56 + CD3 - cells, myeloid cells were identified as CD45 + CD11b + cells, TAMs were identified as HLA-DR high CD206 high myeloid cells, MDSCs were identified as HLA-DR low CD206 low myeloid cells 71,72 . Surface expression of CD1d on the immune cells were also analyzed using flow cytometry. In another assay, the primary HCC patient samples were used to study the TME cell killing by CAR-NKT and CAR-NKT Mito cells under various conditions. Patient samples (containing 1 x 10 5 cells) were directly co-cultured with CAR-NKT or CAR-NKT Mito cells (1 x 10 5 cells), with or without the addition of αGC (100 ng/ml), in C10 medium in Corning 96-well Round Bottom Cell Culture plates for 24 hours. At the end of culture, cells were collected, and the TME cell targeting by CAR-NKT or CAR-NKT Mito cells was assessed using flow cytometry by quantifying live human myeloid cells (identified as NKT TCR - CD45 + CD11b + cells), T cells (identified as NKT TCR - CD45 + CD3 + cells), B cells (identified as NKT TCR - CD45 + CD19 + cells or NKT TCR - CD45 + CD20 + cells), and NK cells (identified as NKT TCR - CD45 + CD3 - CD56 + cells). A total of 3 primary HCC patient samples were included in this assay. Western blotting analysis Western blot analysis was performed to assess CAR-dependent signaling pathways in CAR-NKT and CAR-NKT Mito cells. Recombinant human CD19 protein (amino acids 20–291), His-tagged (Acro Biosystems, cat. no. CD9-HP2H3), was pre-coated onto 24-well culture plates at 5 µg/ml for 1 hour at 37 °C. CD19-targeting CAR-NKT or CAR-NKT Mito cells were then added and incubated for 15 minutes or 1 hour at 37 °C. Following stimulation, cells were immediately transferred to ice-cold PBS to terminate signaling and washed three times to remove residual antigen. Cells were subsequently lysed, and total protein extracts were collected for western blot analysis. Total proteins were extracted using a RIPA lysis buffer (Thermo Fisher Scientific) containing 20 mM HEPES (pH 7.6), 150 mM NaCl, 1 mM EDTA, 1% Tritonx-100, and protease/phosphatase inhibitor cocktail (Cell Signaling Technology). Protein concentration was measured using a Bicinchoninic Acid (BCA) Assay Kit (Thermo Fisher Scientific). Equal amounts of total protein were resolved on a 4–15% Mini-PROTEAN® TGX™ Precast Protein Gel (BIO-RAD) and then transferred to a polyvinylidene difluoride (PVDF) membrane by electrophoresis. The following antibodies were used to blot for the proteins of interest: anti-human p-CD3 zeta (Tyr 142) (Cell Signaling Technology, CST, cat. no. 67748), anti-human CD3 zeta (clone E8R1Q, CST, cat. no. 47434), anti-human p-ZAP70 (Tyr319) (clone 65E4, CST, cat. no. 2717), anti-human ZAP70 (clone D1C10E, CST, cat. no. 3165), anti-human p-PLC gamma 1 (Tyr783) (clone D6M95, CST, cat. no. 14008), anti-human PLC gamma 1 (clone D9H10, CST, cat. no. 5690), anti-human p-LAT (Tyr 161) (clone E9Q2R, CST, cat. no. 88077), anti-human LAT (clone E3U6J, CST, cat. no. 45533), anti-human p-c-Jun 1 (Ser73) (clone D47G9, CST, cat. no. 3270), anti-human c-Jun (clone 60A8, CST, cat. no. 9165), anti-human p-NF-kappaB p65 (Ser536) (clone 93H1, CST, cat. no. 3033), anti-human NF-kappaB p65 (clone D14E12, CST, cat. no. 8242), anti-human p-STAT5 (Tyr694) (clone D47E7, CST, cat. no. 4322), anti-human STAT5 (clone D2O6Y, CST, cat. no. 94205), and secondary anti-rabbit IgG (CST, cat. no. 7074). β-Actin (clone D6A8, CST, cat. no. 8457) was used as internal controls. Signals were visualized using a ChemiDoc ™ Imaging Systems (BIO-RAD). The data were analyzed using ImageJ (Version 1.53s). Single cell RNA sequencing (scRNA-seq) CD19-targeting CAR-NKT or CAR-NKT Mito cells were co-cultured with RAJI tumor cells at an effector-to-target (E:T) ratio of 1:5 for 72 hours. Following co-culture, viable CAR-NKT or CAR-NKT Mito cells were isolated by flow cytometry as NKT TCR⁺CD3⁺ cells and immediately submitted to the UCLA Technology Center for Genomics & Bioinformatics (TCGB) Core for library preparation and scRNA-seq. Cells were quantified using a Cell Countess II automated cell counter (Invitrogen/Thermo Fisher Scientific). A total of 20,000 cells from each experimental group were loaded on the Chromium platform (10X Genomics), and libraries were constructed using the Chromium Next GEM Single Cell 3’ Kit v3.1 and the Chromium Next GEM Chip G Single Cell Kit (10X Genomics), according to the manufacturer’s instructions. Library quality was assessed using the D1000 ScreenTape on a 4200 TapeStation System (Agilent Technologies). Libraries were sequenced on an Illumina NovaSeq using the NovaSeq S4 Reagent Kit (100 cycles; Illumina). For cell clustering and annotation, the merged digital expression matrix generated by Cellranger was analyzed using an R package Seurat (v.4.0.0) following the guidelines 73–75 . Briefly, after filtering the low-quality cells, the expression matrix was normalized using NormalizeData function, followed by selecting variable features across datasets using FindVariableFeatures and SelectIntegrationFeatures functions. To correct the batch effect, FindIntegrrationAnchors and IntegrateData functions were used based on the selected feature genes. The corrected dataset was subjected to standard Seurat workflow for dimension reduction and clustering. In this study, clusters of therapeutic cells were manually merged and annotated based on gene signatures reported from Human Protein Atlas (proteinatlas.org) and previous studies 7,76–83 . AddModuleScore was used to calculate module scores of each list of gene signatures, and FeaturePlot function was used to visualize the expression of each signature in the UMAP plots. In vivo bioluminescence imaging (BLI) BLI was performed using a Spectral Advanced Molecular Imaging HTX system (Spectral Instrument Imaging). Live animal images were captured 5 minutes after intraperitoneal (i.p.) injection of D-Luciferin (1 mg per 100 μL PBS per mouse) to obtain total body bioluminescence. The imaging data were analyzed using AURA imaging software (version 3.2.0, Spectral Instrument Imaging). In vivo antitumor efficacy study of CAR19-NKT (Mito) cells: RAJI-FG human lymphoma xenograft NSG mouse model Experimental design is shown in Fig. 6a. Briefly, on Day 0, NSG mice received i.v. inoculation of RAJI-FG human lymphoma cells (2 x 10 5 cells per mouse). On Day 7, the experimental mice received i.v. injection of Vehicle (100 μl PBS per mouse), human CAR19-NKT cells (1 x 10 7 cells in 100 μl PBS per mouse), or human CAR19-NKT Mito cells (1 x 10 7 cells in 100 μl PBS per mouse). Over the experiment, mice were monitored for survival and their tumor loads were measured twice per week using BLI. At the end of the experiment, mice were euthanized, and their tissues were collected for analysis of therapeutic cell phenotypes and functions by flow cytometry or ELISA. In vivo antitumor efficacy study of GCAR-NKT (Mito) cells: SKHEP1-FG human liver cancer xenograft NSG mouse model Experimental design is shown in Fig. 6e. Briefly, on Day 0, NSG mice received i.v. inoculation of SKHEP1-FG human liver cancer cells (5 x 10 5 cells per mouse). On Day 4, the experimental mice received i.v. injection of Vehicle (100 μl PBS per mouse), human GCAR-NKT cells (1 x 10 7 cells in 100 μl PBS per mouse), or human GCAR-NKT Mito cells (1 x 10 7 cells in 100 μl PBS per mouse). Over the experiment, mice were monitored for survival and their tumor loads were measured twice per week using BLI. At the end of the experiment, mice were euthanized, and their tissues were collected for analysis of therapeutic cell phenotypes and functions by flow cytometry or ELISA. In vivo antitumor efficacy study of MCAR-NKT (Mito) cells: OVCAR8-FG human ovarian cancer xenograft NSG mouse model Experimental design is shown in Fig. 6i. Briefly, on Day 0, NSG mice received i.p. inoculation of OVCAR8-FG human ovarian cancer cells (5 x 10 5 cells per mouse). On Day 7, the experimental mice received i.v. injection of Vehicle (100 μl PBS per mouse), human MCAR-NKT cells (1 x 10 7 cells in 100 μl PBS per mouse), or human MCAR-NKT Mito cells (1 x 10 7 cells in 100 μl PBS per mouse). Over the experiment, mice were monitored for survival and their tumor loads were measured twice per week using BLI. At the end of the experiment, mice were euthanized, and their tissues were collected for analysis of therapeutic cell phenotypes and functions by flow cytometry or ELISA. Statistical analysis Statistical data analysis was performed using GraphPad Prism 8 software (GraphPad). Student’s two-tailed t test was employed for pairwise comparisons. Ordinary one- or two-way ANOVA followed by Tukey’s or Dunnett’s multiple comparisons test was used for multiple comparisons. Log rank (Mantel-Cox) test adjusted for multiple comparisons was used for Meier survival curves analysis. Data are expressed as the mean ±SEM, unless otherwise indicated. In all figures and figure legends, n denotes the number of samples or animals utilized in the indicated experiments. A p-value of less than 0.05 was considered significant; ns indicates not significant; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Declarations Acknowledgements We thank the University of California, Los Angeles (UCLA) animal facility for providing animal support; the UCLA Translational Pathology Core Laboratory (TPCL) for providing histology support; the UCLA Technology Centre for Genomics & Bioinformatics (TCGB) facility for providing RNA-seq services; the UCLA CFAR Virology Core for providing human cells; the UCLA Broad Stem Cell Research Center (BSCRC) Flow Cytometry Core Facility for cell sorting support; and the Advanced Light Microscopy/Spectroscopy Laboratory, the Electron Imaging Center for NanoSystems, and the Nano and Pico Characterization Laboratory at the California NanoSystems Institute (CNSI) for supporting the image acquisition. This work was supported by a Partnering Opportunity for Discovery Stage Research Projects Award and a Partnering Opportunity for Translational Research Projects Awards from the California Institute for Regenerative Medicine (DISC2-11157, DISC2-13015, TRAN1-12250, and TRAN1-16050 to L.Y., DISC2-14169 to S.L.), a Department of Defense CDMRP PRCRP Impact Award (CA200456 to L.Y.), a Department of Defense Kidney Cancer Research Program Award (KC230215 to L.Y.), a UCLA BSCRC Innovation Award (to L.Y.), and an Ablon Scholars Award (to L.Y.), a UCLA Jonsson Comprehensive Cancer Center (JCCC) Seed Grant (to S.L. and L.Y.), a UCLA BSCRC Innovation Award (to S.L.), a grant from the National Institutes of Health (NIH) (GM143485, to S.L.). L.Y. is a member of UCLA Parker Institute for Cancer Immunotherapy (PICI). Y.-R.L. is a postdoctoral fellow supported by a UCLA MIMG M. John Pickett Post-Doctoral Fellow Award, a CIRM-BSCRC Postdoctoral Fellowship, a UCLA Sydney Finegold Postdoctoral Award, a UCLA Chancellor’s Award for Postdoctoral Research, and a UCLA Goodman-Luskin Microbiome Center Collaborative Research Fellowship Award. Y.Z. is a predoctoral fellow supported by a Whitcome Pre-Doctoral Fellowship in Molecular Biology. AUTHOR CONTRIBUTIONS Y-R.L., B.Z., S.W., and Y.Z. designed the experiments, analyzed the data, and wrote the manuscript. L.Y. and S.L. conceived and oversaw the study. Y-R.L. B.Z., S.W., and Y.Z. performed all experiments, with assistance from X.S., Z.S., Y.C., J.H., H.N., and Y.Y.. S.G. and V.G.A. provided the primary HCC patient samples. DECLARATION OF INTERESTS L.Y. is a scientific advisor to AlzChem and Amberstone Biosciences, and a co-founder, stockholder, and advisory board member of Appia Bio. None of the declared companies contributed to or directed any of the research reported in this article. The remaining authors declare no competing interests. The authors S. Li, L. Yang, Y.-R. Li, B. Zhang, and S. Wang have filed a patent application related to this work through UCLA Technology Development Group (UCLA TDG), titled “Stem cell mitochondrial transfer to natural killer T cells”. The patent is currently under review. Data Availability Statement All data associated with this study are present in the paper or supplemental information. The genomics data generated during this study are available from the Gene Expression Omnibus database under accession numbers GEO: GSE318930 (Reviewer token: Token: crahqyuktdihzib). Any additional information required to reanalyze the data reported in this paper is available from the corresponding authors upon request. References Courtney, A. N., Tian, G. & Metelitsa, L. S. Natural killer T cells and other innate-like T lymphocytes as emerging platforms for allogeneic cancer cell therapy. Blood 141 , 869–876 (2023). Bollino, D. & Webb, T. J. Chimeric antigen receptor-engineered natural killer and natural killer T cells for cancer immunotherapy. Transl. Res. 187 , 32–43 (2017). Rotolo, A. et al. Enhanced Anti-lymphoma Activity of CAR19-iNKT Cells Underpinned by Dual CD19 and CD1d Targeting. Cancer Cell 34 , 596-610.e11 (2018). Heczey, A. et al. Anti-GD2 CAR-NKT cells in relapsed or refractory neuroblastoma: updated phase 1 trial interim results. Nat. Med. (2023) doi:10.1038/s41591-023-02363-y. Li, Y.-R. et al. Allogeneic CD33-directed CAR-NKT cells for the treatment of bone marrow-resident myeloid malignancies. Nat. Commun. 16 , 1248 (2025). Zhou, X. et al. CAR-redirected natural killer T cells demonstrate superior antitumor activity to CAR-T cells through multimodal CD1d-dependent mechanisms. Nat. cancer (2024) doi:10.1038/s43018-024-00830-0. Li, Y.-R. et al. Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method. Nat. Biotechnol. (2024) doi:10.1038/s41587-024-02226-y. Li, Y.-R. et al. Overcoming ovarian cancer resistance and evasion to CAR-T cell therapy by harnessing allogeneic CAR-NKT cells. Med (New York, N.Y.) 100804 (2025) doi:10.1016/j.medj.2025.100804. Li, Y.-R. et al. Engineering Allorejection-Resistant CAR-NKT Cells from Hematopoietic Stem Cells for Off-The-Shelf Cancer Immunotherapy. Mol. Ther. (2024) doi:10.1016/j.ymthe.2024.04.005. Li, Y.-R. et al. Targeting triple-negative breast cancer using cord-blood CD34 + HSPC-derived mesothelin-specific CAR-NKT cells with potent antitumor activity. J. Hematol. Oncol. 18 , 86 (2025). Li, Y.-R. et al. Engineering optimal CAR constructs for allogeneic mesothelin-directed CAR-NKT cells in solid tumor immunotherapy. Blood Immunol. Cell. Ther. 100025 (2025) doi:10.1016/j.bict.2025.100025. Barragán, G. A. et al. IL-18 metabolically reprograms CAR-expressing natural killer T cells and enhances their antitumor activity against neuroblastoma. bioRxiv 2025.04.18.649551 (2025) doi:10.1101/2025.04.18.649551. Landoni, E. et al. IL-12 reprograms CAR-expressing natural killer T cells to long-lived Th1-polarized cells with potent antitumor activity. Nat. Commun. 15 , 89 (2024). Dai, Z. et al. Off-the-shelf invariant NKT cells expressing anti-PSCA CAR and IL-15 promote pancreatic cancer regression in mice. J. Clin. Invest. 135 , (2025). Liu, D. et al. IL-15 protects NKT cells from inhibition by tumor-associated macrophages and enhances antimetastatic activity. J. Clin. Invest. 122 , 2221–2233 (2012). Li, Y.-R. et al. Allogeneic stem cell-engineered EGFRvIII-specific CAR-NKT cells for treating glioblastoma with enhanced efficacy and safety. Mol. Ther. (2025) doi:10.1016/j.ymthe.2025.09.026. Li, S. et al. Engineering an in vivo charging station for CAR-redirected invariant natural killer T cells to enhance cancer therapy. Res. Sq. (2025) doi:10.21203/rs.3.rs-6215345/v1. Borcherding, N. & Brestoff, J. R. The power and potential of mitochondria transfer. Nature 623 , 283–291 (2023). Hayakawa, K. et al. Transfer of mitochondria from astrocytes to neurons after stroke. Nature 535 , 551–555 (2016). Norat, P. et al. Intraarterial Transplantation of Mitochondria After Ischemic Stroke Reduces Cerebral Infarction. Stroke (Hoboken, N.J.) 3 , (2023). Boudreau, L. H. et al. Platelets release mitochondria serving as substrate for bactericidal group IIA-secreted phospholipase A2 to promote inflammation. Blood 124 , 2173–2183 (2014). Levoux, J. et al. Platelets Facilitate the Wound-Healing Capability of Mesenchymal Stem Cells by Mitochondrial Transfer and Metabolic Reprogramming. Cell Metab. 33 , 283-299.e9 (2021). Court, A. C. et al. Mitochondrial transfer from MSCs to T cells induces Treg differentiation and restricts inflammatory response. EMBO Rep. 21 , e48052 (2020). Wu, B. et al. Mitochondrial aspartate regulates TNF biogenesis and autoimmune tissue inflammation. Nat. Immunol. 22 , 1551–1562 (2021). Giwa, R. & Brestoff, J. R. Mitochondria Transfer to CD4(+) T Cells May Alleviate Rheumatoid Arthritis by Suppressing Pro-Inflammatory Cytokine Production. Immunometabolism 4 , (2022). Saha, T. et al. Intercellular nanotubes mediate mitochondrial trafficking between cancer and immune cells. Nat. Nanotechnol. 17 , 98–106 (2022). Ikeda, H. et al. Immune evasion through mitochondrial transfer in the tumour microenvironment. Nature 638 , 225–236 (2025). Xu, J. et al. Mitochondrial transfer from glia to neurons protects against peripheral neuropathy. Nature (2026) doi:10.1038/s41586-025-09896-x. Baldwin, J. G. et al. Intercellular nanotube-mediated mitochondrial transfer enhances T cell metabolic fitness and antitumor efficacy. Cell 187 , 6614-6630.e21 (2024). Xu, X. et al. Mitochondrial regulation in pluripotent stem cells. Cell Metab. 18 , 325–332 (2013). Tiash, S., Brestoff, J. R. & Crewe, C. A guide to studying mitochondria transfer. Nat. Cell Biol. 25 , 1551–1553 (2023). Liu, Z., Sun, Y., Qi, Z., Cao, L. & Ding, S. Mitochondrial transfer/transplantation: an emerging therapeutic approach for multiple diseases. Cell Biosci. 12 , 66 (2022). Weng, X. et al. Mitochondrial metabolism is essential for invariant natural killer T cell development and function. Proc. Natl. Acad. Sci. U. S. A. 118 , (2021). Kumar, A. et al. Enhanced oxidative phosphorylation in NKT cells is essential for their survival and function. Proc. Natl. Acad. Sci. U. S. A. 116 , 7439–7448 (2019). Sivandzade, F., Bhalerao, A. & Cucullo, L. Analysis of the Mitochondrial Membrane Potential Using the Cationic JC-1 Dye as a Sensitive Fluorescent Probe. Bio-protocol 9 , (2019). Chan, J. D. et al. FOXO1 enhances CAR T cell stemness, metabolic fitness and efficacy. Nature 629 , 201–210 (2024). Li, Y.-R. et al. Multimodal targeting of metastatic renal cell carcinoma via CD70-directed allogeneic CAR-NKT cells. Cell reports. Med. 102321 (2025) doi:10.1016/j.xcrm.2025.102321. Li, Y.-R., Zhu, Y., Chen, Y. & Yang, L. The clinical landscape of CAR-engineered unconventional T cells. Trends in cancer (2025) doi:10.1016/j.trecan.2025.03.001. Li, Y.-R. et al. An Ex Vivo 3D Tumor Microenvironment-Mimicry Culture to Study TAM Modulation of Cancer Immunotherapy. Cells 11 , (2022). Li, Y.-R. et al. Targeting Immunosuppressive Tumor-Associated Macrophages Using Innate T Cells for Enhanced Antitumor Reactivity. Cancers vol. 14 (2022). Rustom, A., Saffrich, R., Markovic, I., Walther, P. & Gerdes, H.-H. Nanotubular highways for intercellular organelle transport. Science 303 , 1007–1010 (2004). Crewe, C. et al. Extracellular vesicle-based interorgan transport of mitochondria from energetically stressed adipocytes. Cell Metab. 33 , 1853-1868.e11 (2021). Li, Y.-R., Zhou, K., Zhu, Y., Halladay, T. & Yang, L. Breaking the mold: Unconventional T cells in cancer therapy. Cancer Cell (2024) doi:10.1016/j.ccell.2024.11.010. Bae, E.-A., Seo, H., Kim, I.-K., Jeon, I. & Kang, C.-Y. Roles of NKT cells in cancer immunotherapy. Arch. Pharm. Res. 42 , 543–548 (2019). Bendelac, A., Savage, P. B. & Teyton, L. The Biology of NKT Cells. Annu. Rev. Immunol. 25 , 297–336 (2007). Rossjohn, J., Pellicci, D. G., Patel, O., Gapin, L. & Godfrey, D. I. Recognition of CD1d-restricted antigens by natural killer T cells. Nat. Rev. Immunol. 12 , 845–857 (2012). Lee, M. S. & Webb, T. J. Novel lipid antigens for NKT cells in cancer. Front. Immunol. 14 , 1173375 (2023). Li, Y.-R., Chen, Y., Zhu, Y., Shen, X. & Yang, L. Abstract A021: Spatiotemporal gene profiling reveals distinct in vivo dynamics and immune checkpoint regulations of human CAR-T and CAR-NKT cells against solid tumors. Cancer Immunol. Res. 14 , A021–A021 (2026). Lv, Z., Luo, F. & Chu, Y. Strategies for overcoming bottlenecks in allogeneic CAR-T cell therapy. Front. Immunol. 14 , 1199145 (2023). Li, Y.-R., Halladay, T. & Yang, L. Immune evasion in cell-based immunotherapy: unraveling challenges and novel strategies. J. Biomed. Sci. 31 , 5 (2024). Labanieh, L., Majzner, R. G. & Mackall, C. L. Programming CAR-T cells to kill cancer. Nat. Biomed. Eng. 2 , 377–391 (2018). Johnson, A., Townsend, M. & O’Neill, K. Tumor Microenvironment Immunosuppression: A Roadblock to CAR T-Cell Advancement in Solid Tumors. Cells 11 , (2022). Lyu, Z. et al. Addressing graft-versus-host disease in allogeneic cell-based immunotherapy for cancer. Exp. Hematol. Oncol. 14 , 66 (2025). Pillai, A. B., George, T. I., Dutt, S., Teo, P. & Strober, S. Host NKT Cells Can Prevent Graft-versus-Host Disease and Permit Graft Antitumor Activity after Bone Marrow Transplantation. J. Immunol. 178 , 6242–6251 (2007). Haraguchi, K. et al. Recovery of Vα24+ NKT cells after hematopoietic stem cell transplantation. Bone Marrow Transplant. 34 , 595–602 (2004). Ramos, C. A. et al. Allogeneic NKT Cells Expressing a CD19-Specific CAR in Patients with Relapsed or Refractory B-Cell Malignancies: An Interim Analysis. Blood 138 , 2819 (2021). Ren, H. et al. Off-the-shelf dual CAR-iNKT cell immunotherapy eradicates medullary and leptomeningeal high-risk KMT2A-rearranged leukemia. Blood blood.2025029302 (2025) doi:10.1182/blood.2025029302. Ramos, C. A. et al. Off-the-Shelf CD19-Specific CAR-NKT Cells in Patients with Relapsed or Refractory B-Cell Malignancies. Transplant. Cell. Ther. 30 , S41–S42 (2024). Li, Y.-R. et al. Targeting orthotopic and metastatic pancreatic cancer with allogeneic stem cell-engineered mesothelin-redirected CAR-NKT cells. Proc. Natl. Acad. Sci. U. S. A. 122 , e2517786122 (2025). Li, Y.-R., Zhu, Y. & Yang, L. IL-15 in CAR engineering: striking an efficacy-safety balance. Trends Mol. Med. (2025) doi:10.1016/j.molmed.2025.05.014. Li, Y.-R., Zhu, Y. & Yang, L. IL-18 revives dysfunctional CAR-T cells. Trends in cancer (2025) doi:10.1016/j.trecan.2025.06.008. Li, Y.-R., Wilson, M. & Yang, L. Target tumor microenvironment by innate T cells. Front. Immunol. 13 , 999549 (2022). Li, Y.-R., Fang, Y., Lyu, Z., Zhu, Y. & Yang, L. Exploring the dynamic interplay between cancer stem cells and the tumor microenvironment: implications for novel therapeutic strategies. J. Transl. Med. 21 , 686 (2023). Majzner, R. G. & Mackall, C. L. Clinical lessons learned from the first leg of the CAR T cell journey. Nat. Med. 25 , 1341–1355 (2019). Lemoine, J., Ruella, M. & Houot, R. Born to survive: how cancer cells resist CAR T cell therapy. J. Hematol. Oncol. 14 , 1–12 (2021). Zhu, Y. et al. Development of Hematopoietic Stem Cell-Engineered Invariant Natural Killer T Cell Therapy for Cancer. Cell Stem Cell 25 , 542-557.e9 (2019). Li, Y.-R. et al. Development of allogeneic HSC-engineered iNKT cells for off-the-shelf cancer immunotherapy. Cell reports. Med. 2 , 100449 (2021). Hazim, R. A. et al. Differentiation of RPE cells from integration-free iPS cells and their cell biological characterization. Stem Cell Res. Ther. 8 , 217 (2017). Lowry, W. E. et al. Generation of human induced pluripotent stem cells from dermal fibroblasts. Proc. Natl. Acad. Sci. U. S. A. 105 , 2883–2888 (2008). Karumbayaram, S. et al. Directed differentiation of human-induced pluripotent stem cells generates active motor neurons. Stem Cells 27 , 806–811 (2009). Li, Y.-R. et al. Profiling ovarian cancer tumor and microenvironment during disease progression for cell-based immunotherapy design. iScience 26 , 107952 (2023). Li, Y.-R. et al. Protocol to profile tumor and microenvironment from ovarian cancer patient samples and evaluate cell-based therapy using in vitro killing assays. STAR Protoc. 6 , 103742 (2025). Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36 , 411–420 (2018). Tran, H. T. N. et al. A benchmark of batch-effect correction methods for single-cell RNA sequencing data. Genome Biol. 21 , 12 (2020). Jia, C. et al. Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data. Nucleic Acids Res. 45 , 10978–10988 (2017). Miller, B. C. et al. Subsets of exhausted CD8(+) T cells differentially mediate tumor control and respond to checkpoint blockade. Nat. Immunol. 20 , 326–336 (2019). Zheng, L. et al. Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science 374 , abe6474 (2021). Li, H. et al. Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma. Cell 176 , 775-789.e18 (2019). Milner, J. J. et al. Heterogenous Populations of Tissue-Resident CD8(+) T Cells Are Generated in Response to Infection and Malignancy. Immunity 52 , 808-824.e7 (2020). Beltra, J.-C. et al. Developmental Relationships of Four Exhausted CD8(+) T Cell Subsets Reveals Underlying Transcriptional and Epigenetic Landscape Control Mechanisms. Immunity 52 , 825-841.e8 (2020). Zheng, C. et al. Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing. Cell 169 , 1342-1356.e16 (2017). Wang, X., Peticone, C., Kotsopoulou, E., Göttgens, B. & Calero-Nieto, F. J. Single-cell transcriptome analysis of CAR T-cell products reveals subpopulations, stimulation, and exhaustion signatures. Oncoimmunology 10 , 1866287 (2021). Bai, Z. et al. Single-cell antigen-specific landscape of CAR T infusion product identifies determinants of CD19-positive relapse in patients with ALL. Sci. Adv. 8 , eabj2820 (2022). Additional Declarations Yes there is potential Competing Interest. L.Y. is a scientific advisor to AlzChem and Amberstone Biosciences, and a co-founder, stockholder, and advisory board member of Appia Bio. None of the declared companies contributed to or directed any of the research reported in this article. The remaining authors declare no competing interests. The authors S. Li, L. Yang, Y.-R. Li, B. Zhang, and S. Wang have filed a patent application related to this work through UCLA Technology Development Group (UCLA TDG), titled “Stem cell mitochondrial transfer to natural killer T cells”. The patent is currently under review. 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Schematic illustrating MT from iPSCs to human CAR-NKT cells derived from cancer patients or healthy donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e FACS plots showing CD19-targeting CAR-NKT cell purity and successful transfer of iPSC-derived mitochondria into CAR-NKT cells at 2 and 3 days post-transfer. The mitochondrial-to–NKT cell (Mito:NKT) ratio was 4:1, and iPSC-derived mitochondria were labeled with MitoTracker Green (MTG).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec\u003c/strong\u003e Quantification of MT efficiency into CAR-NKT cells at different Mito:NKT ratios, as measured by flow cytometry (n = 6; n indicates different healthy donors).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed\u003c/strong\u003e FACS plots showing CD4/CD8 co-receptor expression patterns in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee\u003c/strong\u003e FACS plots showing the MT efficiency into different CAR-NKT cell subpopulations. SP, single-positive; DN, double-negative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef\u003c/strong\u003e Quantification of e (n = 6; n indicates different healthy donors).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg\u003c/strong\u003e Immunofluorescence (IF) imaging showing iPSC-derived mitochondria (mito-mScarlette expression) and total mitochondrial (MitoTracker Green labeling) content in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eh\u003c/strong\u003e Quantification of MT efficiency into CAR-NKT cells at 2 and 3 days post-transfer, as measured by IF (n = 24).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ei\u003c/strong\u003e Quantification of total mitochondrial fluorescence intensity in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (n = 24). Data are presented in arbitrary units (A.U.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ej\u003c/strong\u003e Quantification of MT efficiency into CAR-NKT cells from different iPSC lines, as measured by flow cytometry (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ek\u003c/strong\u003e IF imaging of JC-1 staining in the indicated cells, with red fluorescence indicating polarized mitochondrial membranes and green fluorescence indicating depolarized mitochondria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003el\u003c/strong\u003e Quantification of \u003cstrong\u003ek\u003c/strong\u003e (n = 24).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003em \u003c/strong\u003eFACS plots showing MitoTracker Green (MTG) versus MitoTracker Deep Red (MDR) staining in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells. Quiescent NKT cells isolated from healthy donor PBMCs are included as a control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e Quantification of \u003cstrong\u003em\u003c/strong\u003e (n = 5; n indicates different NKT donors).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eo\u003c/strong\u003e and \u003cstrong\u003ep\u003c/strong\u003e Seahorse extracellular flux analysis showing oxygen consumption rate (OCR, \u003cstrong\u003eo\u003c/strong\u003e) and extracellular acidification rate (ECAR, \u003cstrong\u003ep\u003c/strong\u003e) in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eq\u003c/strong\u003e FACS plots showing the surface CD62L/CD45RO expression on the indicated cells. Based on MTG intensity, CAR-NKT cells were stratified into Mito⁻, Mito\u003csup\u003elow\u003c/sup\u003e, Mito\u003csup\u003emed\u003c/sup\u003e, and Mito\u003csup\u003ehi\u003c/sup\u003e subsets.Tn, naïve T cell; Tem, effector memory T cell; Tcm, central memory T cell; Temra, effector memory T cells re-expressing CD45RA; med, medium; hi, high.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003er \u003c/strong\u003eQuantification of \u003cstrong\u003eq\u003c/strong\u003e (n = 5).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Representative of 5 experiments. Data are presented as the mean ± SEM. ns, not significant; ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, by Student’s \u003cem\u003et\u003c/em\u003e test (\u003cstrong\u003eh\u003c/strong\u003e, \u003cstrong\u003ei\u003c/strong\u003e, and \u003cstrong\u003el\u003c/strong\u003e), or one-way ANOVA (\u003cstrong\u003ef\u003c/strong\u003e, \u003cstrong\u003ej\u003c/strong\u003e,\u003cstrong\u003e \u003c/strong\u003eand \u003cstrong\u003en\u003c/strong\u003e). The data shown in this figure were generated using CD19-targeting CAR-NKT cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/baf5783b4679ad229750574e.png"},{"id":104782226,"identity":"b281ca33-dbab-44d1-937f-b22a97b0f9ca","added_by":"auto","created_at":"2026-03-17 07:57:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7409475,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCAR-NKT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eMito\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e cells exhibit enhanced effector and memory characteristics with robust cytotoxic and cytokine-producing capacity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea \u003c/strong\u003eSchematic illustrating CAR target design for CAR-NKT cell generation and associated cancer indications. MSLN, mesothelin; GPC3, glypican 3; HCC, hepatocellular carcinoma.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e FACS plots showing CAR expression and FITC/MTG-labeled MT in the indicated CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells. CAR-NKT\u003csub\u003eMito \u003c/sub\u003ecells were purified by post-sort selection of FITC/MTG-positive cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec\u003c/strong\u003e FACS quantification of the CAR expression on the indicated cells (n = 5; n indicates different donors or patients).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed\u003c/strong\u003e Cell yield of the indicated cells (n = 5; n indicates different donors or patients).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee\u003c/strong\u003e FACS analysis of CD4 and CD8 subpopulation frequencies in the indicated cells. GCAR-NKT cell data from four healthy donors and two HCC patients are shown. SP, single-positive; DP; double-positive; DN, double-negative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef \u003c/strong\u003eFACS plots showing the surface CD62L/CD45RO expression on the indicated cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg\u003c/strong\u003e Quantification of \u003cstrong\u003ef\u003c/strong\u003e (n = 5; n indicated different donors or patients).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eh\u003c/strong\u003e FACS plots showing the activation and effector marker expression of the indicated cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ei\u003c/strong\u003e Quantification of \u003cstrong\u003eh\u003c/strong\u003e (n = 4; n indicated different donors or patients).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ej\u003c/strong\u003e-\u003cstrong\u003el\u003c/strong\u003e Studying the antigen response of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells. \u003cstrong\u003ej \u003c/strong\u003eExperimental design. \u003cstrong\u003ek\u003c/strong\u003e Growth curve of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (n = 4). \u003cstrong\u003el \u003c/strong\u003eELISA measurements of cytokine (IFN-γ, TNF-α, IL-2, and IL-4) levels in the culture supernatants collected on day 7 (n = 4).\u003c/p\u003e\n\u003cp\u003eRepresentative of 3 experiments. Data are presented as the mean ± SEM. ns, not significant; *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, by Student’s \u003cem\u003et\u003c/em\u003e test (\u003cstrong\u003ec\u003c/strong\u003e right, \u003cstrong\u003ed\u003c/strong\u003e right, \u003cstrong\u003eg\u003c/strong\u003e and \u003cstrong\u003ei\u003c/strong\u003e), one-way ANOVA (\u003cstrong\u003ec \u003c/strong\u003eleft,\u003cstrong\u003e d \u003c/strong\u003eleft, and\u003cstrong\u003e l\u003c/strong\u003e), or two-way ANOVA (\u003cstrong\u003ek\u003c/strong\u003e).\u003cstrong\u003e\u003cbr\u003e\n\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/7be0d5672194bf579fe9d83e.png"},{"id":104549735,"identity":"88dbf054-26bf-4aaa-b7fc-3aa2b2d4db6a","added_by":"auto","created_at":"2026-03-13 07:56:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":6637989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\n\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAR-NKT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eMito\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e cells exhibit potent tumor killing and sustained effector and memory functions \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e-\u003cstrong\u003ej\u003c/strong\u003e Studying the \u003cem\u003ein vitro\u003c/em\u003e tumor cell killing capacity of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells. \u003cstrong\u003ea\u003c/strong\u003e Schematics showing the four human tumor cell lines utilized in this study. All were engineered to express the firefly luciferase (Fluc) and enhanced green fluorescent protein (EGFP) dual reporters (FG). \u003cstrong\u003eb\u003c/strong\u003e FACS detection of CAR antigen expression on the indicated tumor cells. \u003cstrong\u003ec\u003c/strong\u003e Experimental design. CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells, either without tumor prestimulation or following five rounds of tumor cell stimulation, were compared. \u003cstrong\u003ed\u003c/strong\u003e Tumor cell killing data at 24 h (n = 4). \u003cstrong\u003ee\u003c/strong\u003e Fold expansion of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (n = 4). \u003cstrong\u003ef\u003c/strong\u003e Heatmap showing effector cytokine production by the indicated cells 24 h after tumor co-culture (n = 4). \u003cstrong\u003eg\u003c/strong\u003e FACS quantification of the effector activation marker CD69 on the indicated cells (n = 4). \u003cstrong\u003eh\u003c/strong\u003e FACS plots showing the production of cytotoxic molecules (i.e., Granzyme B and Perforin) by the indicated cells. \u003cstrong\u003ei\u003c/strong\u003e Quantification of \u003cstrong\u003eh\u003c/strong\u003e (n = 4). \u003cstrong\u003ej\u003c/strong\u003e Radar plots showing the immune checkpoint expression on the indicated cells (n = 4). MCAR/OVCAR8-FG data are shown for \u003cstrong\u003ef\u003c/strong\u003e-\u003cstrong\u003ej\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ek\u003c/strong\u003e-\u003cstrong\u003en\u003c/strong\u003e Studying the \u003cem\u003ein vitro\u003c/em\u003e normal cell killing capacity of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells. CAR19 data are shown. \u003cstrong\u003ek\u003c/strong\u003e Experimental design. \u003cstrong\u003el\u003c/strong\u003e Cell killing data at 24 h (n = 4). \u003cstrong\u003em\u003c/strong\u003e Fold expansion of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (n = 4). \u003cstrong\u003en\u003c/strong\u003e Heatmap showing effector cytokine production by the indicated cells 24 h after normal or tumor cell co-culture (n = 4).\u003c/p\u003e\n\u003cp\u003eRepresentative of 3 experiments. Data are presented as the mean ± SEM. ns, not significant; *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, by one-way ANOVA (\u003cstrong\u003ee\u003c/strong\u003e, \u003cstrong\u003eg\u003c/strong\u003e, \u003cstrong\u003ei\u003c/strong\u003e,\u003cstrong\u003e l, \u003c/strong\u003eand \u003cstrong\u003em\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/51e8297c46be01c5970f02a8.png"},{"id":104549734,"identity":"ebc86fa4-0c00-4312-a9a4-4025b665aa72","added_by":"auto","created_at":"2026-03-13 07:56:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":8023597,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative of 1 (\u003cstrong\u003ea\u003c/strong\u003e-\u003cstrong\u003ei\u003c/strong\u003e) and 3 (\u003cstrong\u003ej\u003c/strong\u003e-\u003cstrong\u003em\u003c/strong\u003e) experiments. Data are presented as the mean ± SEM. ns, not significant; *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, by Student’s \u003cem\u003et\u003c/em\u003e test (\u003cstrong\u003el\u003c/strong\u003e). P values shown in the violin plots were calculated using a two-tailed Wilcoxon rank-sum test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAR-NKT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eMito\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e cells exhibit enhanced effector, memory, and metabolic programs with robust CAR-mediated signaling during antitumor responses.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e-\u003cstrong\u003ei\u003c/strong\u003e Studying the transcriptomic profiles in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells during antitumor responses by single-cell RNA sequencing (scRNA-seq). \u003cstrong\u003ea\u003c/strong\u003e Experimental design. \u003cstrong\u003eb\u003c/strong\u003e Combined UMAP plot showing the formation of four major cell clusters. \u003cstrong\u003ec \u003c/strong\u003eIndividual UMAP plots showing cell cluster composition of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell samples. \u003cstrong\u003ed\u003c/strong\u003e Bar graphs showing the cell cluster proportions of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell samples. \u003cstrong\u003ee\u003c/strong\u003e Violin plots showing the expression distribution of effector/memory, and cytotoxicity gene signatures in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell samples. \u003cstrong\u003ef\u003c/strong\u003e Violin plots showing the expression of the indicated genes associated with NK cytotoxicity, cytokine signaling, and cell survival, in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell samples. \u003cstrong\u003eg\u003c/strong\u003e Pathway analyses of differentiated expressed genes comparing CAR-NKT\u003csub\u003eMito\u003c/sub\u003e with CAR-NKT cells. GO, Gene ontology ID. \u003cstrong\u003eh\u003c/strong\u003e Dot plots showing the expression of gene signatures associated with distinct metabolic pathways. Color intensity reflects the average expression level of each gene signature, while dot size represents the percentage of cells within each cluster expressing that gene signature. \u003cstrong\u003ei \u003c/strong\u003eDot plots showing the expression of genes associated with mitochondrial structure and oxidative metabolism, as well as glycolysis and metabolic reprogramming, in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ej\u003c/strong\u003e-\u003cstrong\u003em \u003c/strong\u003eStudying the CAR-mediated signaling in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells following antigen stimulation by western blot. \u003cstrong\u003ej\u003c/strong\u003e Experimental design. \u003cstrong\u003ek \u003c/strong\u003eWestern blot analysis of key downstream CAR signaling molecules in CD19-targeting CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells following CD19 antigen stimulation. \u003cstrong\u003el \u003c/strong\u003eQuantification of\u003cstrong\u003e k \u003c/strong\u003e(n = 3).\u003cstrong\u003e m\u003c/strong\u003e Schematic illustrations summarizing enhanced CAR-mediated signaling pathways observed in CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells compared with CAR-NKT cells.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/a7a93f04ec1bb9a37d98f962.png"},{"id":104549738,"identity":"2bbc53c2-2c06-4c55-bb28-9431ed256880","added_by":"auto","created_at":"2026-03-13 07:57:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6991933,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCAR-NKT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eMito\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e cells outperform CAR-T\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eMito\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e cells in modulating the immunosuppressive tumor microenvironment (TME).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea-g \u003c/strong\u003eStudying the TME modulation by CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells using primary HCC patient samples. GCAR data are shown. \u003cstrong\u003ea\u003c/strong\u003e Experimental design. TAM, tumor-associated macrophage; MDSC, myeloid-derived suppressor cell. \u003cstrong\u003eb\u003c/strong\u003e TAM/MDSC killing data at 24 h (n = 3).\u003cstrong\u003e c\u003c/strong\u003e T, B, or NK cell killing data at 24 h (n = 3). \u003cstrong\u003ed\u003c/strong\u003e FACS detection of CD1d expression on the indicated immune cells from HCC patient samples. MFI, mean florescence intensity. \u003cstrong\u003ee\u003c/strong\u003e Quantification of \u003cstrong\u003ed\u003c/strong\u003e (n = 3).\u003cstrong\u003e f\u003c/strong\u003e TAM/MDSC killing data by conventional CAR-T cells at 24 h (n = 3). \u003cstrong\u003eg\u003c/strong\u003e Diagram showing selective targeting of TAMs and MDSCs by CAR-NKT but not CAR-T cells, and enhanced targeting by CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eh\u003c/strong\u003e-\u003cstrong\u003eq\u003c/strong\u003e Studying the TME modulation by CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells using 3D tumor organoids. \u003cstrong\u003eh\u003c/strong\u003e Diagram showing the generation of M2-polarized macrophages from HCC patient PBMC samples. \u003cstrong\u003ei\u003c/strong\u003e FACS detection of CD1d and M2 markers (CD163 and CD206) on polarized macrophages.\u003cstrong\u003e j\u003c/strong\u003e Macrophage killing data at 24 h (n = 3). GCAR data are shown. \u003cstrong\u003ek\u003c/strong\u003e Experimental design to study the TME modulation using 3D tumor organoids. \u003cstrong\u003el \u003c/strong\u003eTumor and TAM killing data by CAR-NKT cells at 24 h (n = 3). \u003cstrong\u003em\u003c/strong\u003e FACS detection of the activation marker CD69 and cytotoxic molecules (Perforin and Granzyme B) in the indicated cells from 3D tumor organoids. \u003cstrong\u003en\u003c/strong\u003e Quantification of \u003cstrong\u003em\u003c/strong\u003e (n = 3). \u003cstrong\u003eo \u003c/strong\u003eTumor and TAM killing data by conventional CAR-T cells at 24 h (n = 3). \u003cstrong\u003ep\u003c/strong\u003e FACS analyses of the cytotoxic molecules (Perforin and Granzyme B) in the indicated cells from 3D tumor organoids.\u003cstrong\u003e q\u003c/strong\u003e Schematic illustrating selective targeting of immunosuppressive cells in the TME by CAR-NKT\u003csub\u003eMito\u003c/sub\u003e but not CAR-T\u003csub\u003eMito\u003c/sub\u003e cells, with suppression of CAR-T\u003csub\u003eMito\u003c/sub\u003e antitumor activity.\u003c/p\u003e\n\u003cp\u003eRepresentative of 3 experiments. Data are presented as the mean ± SEM. ns, not significant, *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, by Student’s \u003cem\u003et\u003c/em\u003e test (\u003cstrong\u003ef\u003c/strong\u003e, \u003cstrong\u003eo\u003c/strong\u003e, and \u003cstrong\u003ep\u003c/strong\u003e), or one-way ANOVA (\u003cstrong\u003eb\u003c/strong\u003e, \u003cstrong\u003ec\u003c/strong\u003e, \u003cstrong\u003ee\u003c/strong\u003e,\u003cstrong\u003e j\u003c/strong\u003e, \u003cstrong\u003el\u003c/strong\u003e, and \u003cstrong\u003en\u003c/strong\u003e).\u003cbr\u003e\n\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/99669fb0fd6d2e41463c22e9.png"},{"id":104549736,"identity":"66406ca4-653f-4d45-9ac9-95b3f0e09f24","added_by":"auto","created_at":"2026-03-13 07:56:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":12238459,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCAR-NKT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eMito \u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003ecells exhibit superior \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e antitumor efficacy across human lymphoma, liver cancer, and ovarian cancer xenograft models.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e-\u003cstrong\u003ed \u003c/strong\u003eStudying the \u003cem\u003ein vivo\u003c/em\u003e antitumor capacity of CAR19-NKT and CAR19-NKT\u003csub\u003eMito\u003c/sub\u003e cells using a Raji-FG human lymphoma xenograft mouse model. \u003cstrong\u003ea\u003c/strong\u003e Experimental design. \u003cstrong\u003eb\u003c/strong\u003e Kaplan-Meier survival curves of experimental mice over time (n = 5-7). \u003cstrong\u003ec\u003c/strong\u003e BLI images showing tumor loads in experimental mice over time. \u003cstrong\u003ed\u003c/strong\u003e Quantification of \u003cstrong\u003ec\u003c/strong\u003e (n = 5-7).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee\u003c/strong\u003e-\u003cstrong\u003eh\u003c/strong\u003e Studying the \u003cem\u003ein vivo\u003c/em\u003e antitumor capacity of GCAR-NKT and GCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells using an SKHEP1-FG human liver cancer xenograft mouse model. \u003cstrong\u003ee\u003c/strong\u003e Experimental design. \u003cstrong\u003ef\u003c/strong\u003e Kaplan-Meier survival curves of experimental mice over time (n = 6). \u003cstrong\u003eg\u003c/strong\u003e BLI images showing tumor loads in experimental mice over time. \u003cstrong\u003eh\u003c/strong\u003e Quantification of \u003cstrong\u003eg\u003c/strong\u003e (n = 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ei\u003c/strong\u003e-\u003cstrong\u003el\u003c/strong\u003e Studying the \u003cem\u003ein vivo\u003c/em\u003e antitumor capacity of MCAR-NKT and MCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells using an OVCAR8-FG human ovarian cancer xenograft mouse model. \u003cstrong\u003ei\u003c/strong\u003e Experimental design. \u003cstrong\u003ej\u003c/strong\u003e Kaplan-Meier survival curves of experimental mice over time (n = 5-7). \u003cstrong\u003ek\u003c/strong\u003e BLI images showing tumor loads in experimental mice over time. \u003cstrong\u003el\u003c/strong\u003e Quantification of \u003cstrong\u003ek\u003c/strong\u003e (n = 5-7).\u003c/p\u003e\n\u003cp\u003eRepresentative of 3 experiments. Data are presented as the mean ± SEM. ns, not significant, *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, by log rank (Mantel-Cox) test adjusted for multiple comparisons (\u003cstrong\u003eb\u003c/strong\u003e, \u003cstrong\u003ef\u003c/strong\u003e, and \u003cstrong\u003ej\u003c/strong\u003e).\u003cstrong\u003e\u003cbr\u003e\n\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/f1aee7d47aa932aa1f48167f.png"},{"id":104549732,"identity":"6c21830b-426e-449d-98a6-e6a0da267182","added_by":"auto","created_at":"2026-03-13 07:56:57","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":7850451,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCAR-NKT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eMito \u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003ecells show enhanced \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e persistence and effector function with reduced exhaustion\u003c/strong\u003e \u003cstrong\u003ecompared with CAR-NKT cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e-\u003cstrong\u003ef \u003c/strong\u003ePhenotypic and functional analysis of CAR19-NKT\u003csub\u003eMito\u003c/sub\u003e and CAR19-NKT cells isolated from Raji-FG human lymphoma xenograft mice. Data are related to main Fig. 6\u003cstrong\u003ea\u003c/strong\u003e. \u003cstrong\u003ea\u003c/strong\u003e FACS detection of the indicated therapeutic cells in the liver and bone marrow of experimental mice at day 30. \u003cstrong\u003eb\u003c/strong\u003e FACS analyses of the percentage of the indicated therapeutic cells in various organs (n = 5). \u003cstrong\u003ec\u003c/strong\u003e ELISA quantification of human IFN-γ and TNF-α levels in mouse serum collected at day 30 (n = 5). \u003cstrong\u003ed\u003c/strong\u003e Radar plots depicting the expression of exhaustion markers in the indicated therapeutic cells isolated from mouse liver (n = 5). \u003cstrong\u003ee\u003c/strong\u003e FACS detection of T cell effector markers (CD69, CD25, and PD-1) and cytotoxic molecules (Perforin and Granzyme B) in the indicated therapeutic cells isolated from mouse liver. \u003cstrong\u003ef\u003c/strong\u003e Quantification of \u003cstrong\u003ee\u003c/strong\u003e (n = 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg\u003c/strong\u003e-\u003cstrong\u003ej\u003c/strong\u003e Phenotypic and functional analysis of GCAR-NKT\u003csub\u003eMito\u003c/sub\u003e and GCAR-NKT cells isolated from SKHEP1-FG human liver cancer xenograft mice. Data are related to main Fig. 6\u003cstrong\u003ee\u003c/strong\u003e. \u003cstrong\u003eg\u003c/strong\u003e FACS analyses of the percentage of the indicated therapeutic cells in various organs at day 25 (n = 5). \u003cstrong\u003eh\u003c/strong\u003e ELISA quantification of human IFN-γ and TNF-α levels in mouse serum (n = 5). \u003cstrong\u003ei\u003c/strong\u003e Radar plots depicting the expression of exhaustion markers in the indicated therapeutic cells isolated from mouse liver (n = 5). \u003cstrong\u003ej \u003c/strong\u003eFACS quantification of T cell effector marker (CD25) and cytotoxic molecule (Perforin) in the indicated therapeutic cells isolated from mouse liver (n = 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ek\u003c/strong\u003e-\u003cstrong\u003en\u003c/strong\u003e Phenotypic and functional analysis of MCAR-NKT\u003csub\u003eMito\u003c/sub\u003e and MCAR-NKT cells isolated from OVCAR8-FG human ovarian cancer xenograft mice. Data are related to main Fig. 6\u003cstrong\u003ei\u003c/strong\u003e.\u003cstrong\u003e k\u003c/strong\u003e FACS analyses of the percentage of the indicated therapeutic cells in various organs at day 33 (n = 5). \u003cstrong\u003el\u003c/strong\u003e ELISA quantification of human IFN-γ and TNF-α levels in mouse serum (n = 5). \u003cstrong\u003em\u003c/strong\u003e Radar plots depicting the expression of exhaustion markers in the indicated therapeutic cells isolated from mouse peritoneal fluid (n = 5). \u003cstrong\u003en \u003c/strong\u003eFACS quantification of T cell effector marker (CD25) and cytotoxic molecule (Perforin) in the indicated therapeutic cells isolated from mouse peritoneal fluid (n = 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eo\u003c/strong\u003e-\u003cstrong\u003er\u003c/strong\u003e Tissue infiltration analysis of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e and CAR-NKT cells. \u003cstrong\u003eo\u003c/strong\u003e Immunohistochemical (IHC) staining showing infiltration of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e and CAR-NKT cells in the livers of SKHEP1-FG tumor–bearing mice at day 25.\u003cstrong\u003ep\u003c/strong\u003e Quantification of \u003cstrong\u003eo\u003c/strong\u003e (n = 5). \u003cstrong\u003eq\u003c/strong\u003e IHC staining showing infiltration of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e and CAR-NKT cells in the kidneys of OVCAR8-FG tumor–bearing mice at day 33. \u003cstrong\u003er\u003c/strong\u003e Quantification of \u003cstrong\u003eq\u003c/strong\u003e (n = 5).\u003c/p\u003e\n\u003cp\u003eRepresentative of 3 experiments. Data are presented as the mean ± SEM. ns, not significant, *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, by Student’s \u003cem\u003et\u003c/em\u003e test (\u003cstrong\u003eb\u003c/strong\u003e, \u003cstrong\u003ef\u003c/strong\u003e, \u003cstrong\u003eg\u003c/strong\u003e, \u003cstrong\u003ej\u003c/strong\u003e, \u003cstrong\u003ek\u003c/strong\u003e, \u003cstrong\u003en\u003c/strong\u003e,\u003cstrong\u003e q\u003c/strong\u003e, and\u003cstrong\u003e r\u003c/strong\u003e), or one-way ANOVA (\u003cstrong\u003ec\u003c/strong\u003e, \u003cstrong\u003eh\u003c/strong\u003e, and \u003cstrong\u003el\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/a5d57286e580705c9518b08c.png"},{"id":106993934,"identity":"d72995dd-3cd0-4995-8c93-b311873bf28b","added_by":"auto","created_at":"2026-04-15 15:00:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":61742627,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/3da08ed0-70aa-4aac-b992-2414c68cc8d1.pdf"},{"id":104549733,"identity":"17ef88a0-a056-42b4-aab9-ab0f75493620","added_by":"auto","created_at":"2026-03-13 07:56:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3429362,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8953703/v1/5b69ff290db3cfe1bca85f8b.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nL.Y. is a scientific advisor to AlzChem and Amberstone Biosciences, and a co-founder, stockholder, and advisory board member of Appia Bio. None of the declared companies contributed to or directed any of the research reported in this article. The remaining authors declare no competing interests. The authors S. Li, L. Yang, Y.-R. Li, B. Zhang, and S. Wang have filed a patent application related to this work through UCLA Technology Development Group (UCLA TDG), titled “Stem cell mitochondrial transfer to natural killer T cells”. The patent is currently under review.","formattedTitle":"Stem cell mitochondrial transfer rejuvenates CAR-NKT cell metabolism and antitumor activity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChimeric antigen receptor (CAR)-engineered invariant natural killer T (CAR-NKT) cells have been explored for their antitumor activity and possess several distinctive therapeutic advantages. These include potent cytotoxicity mediated through multiple tumor-targeting mechanisms involving the CAR, the invariant T cell receptor (TCR), and natural killer receptors (NKRs), as well as an intrinsic ability to traffic to and infiltrate solid tumors\u003csup\u003e1\u0026ndash;5\u003c/sup\u003e. In addition, CAR-NKT cells can actively modulate the immunosuppressive tumor microenvironment (TME) by selectively eliminating CD1d-expressing myeloid populations, thereby alleviating local immune suppression\u003csup\u003e6\u0026ndash;8\u003c/sup\u003e. Despite these favorable properties, CAR-NKT cell therapies continue to face substantial challenges, particularly in solid tumors, including limited long-term \u003cem\u003ein vivo\u003c/em\u003e persistence, progressive exhaustion, and functional dysfunction\u003csup\u003e9\u0026ndash;11\u003c/sup\u003e. To address these limitations, various genetic engineering strategies have been employed to enhance CAR-NKT cell function, durability, and metabolic fitness. Among these, cytokine engineering has been widely investigated, including expression of IL-15 to promote persistence, IL-12 to induce sustained Th1-polarized antitumor responses, and IL-18 to support metabolic reprogramming and effector function\u003csup\u003e12\u0026ndash;16\u003c/sup\u003e. In parallel, biomimetic \u003cem\u003ein vivo\u003c/em\u003e scaffolds capable of sustained release of \u0026alpha;-galactosylceramide (\u0026alpha;-GalCer or \u0026alpha;GC), a potent NKT cell agonist, have been developed to recruit and activate CAR-NKT cells \u003cem\u003ein situ\u003c/em\u003e and improve solid tumor targeting\u003csup\u003e17\u003c/sup\u003e. However, few engineering strategies are focused on targeting cellular metabolism to improve CAR-NKT cell persistence and antitumor efficacy.\u003c/p\u003e\n\u003cp\u003eMitochondrial transfer (MT) has recently emerged as a fundamental mechanism of intercellular communication that reshapes cellular metabolism and function across diverse physiological and pathological contexts\u003csup\u003e18\u003c/sup\u003e. Rather than being confined to cell-autonomous regulation, mitochondria can be actively exported and transferred between developmentally unrelated cell types, thereby reprogramming the metabolic state of recipient cells. In the central nervous system, astrocytes donate mitochondria to neurons to support neuronal survival following ischemic injury, while in the peripheral nervous system, macrophage-derived mitochondria are transferred to sensory neurons to dampen inflammatory pain signaling\u003csup\u003e19,20\u003c/sup\u003e. In injured tissues, activated platelets deliver mitochondria to mesenchymal stem cells (MSCs) to promote angiogenesis and wound repair, as well as to neutrophils to enhance antimicrobial defense\u003csup\u003e21,22\u003c/sup\u003e. Conversely, MSCs can transfer mitochondria to T cells, driving regulatory T cell differentiation and suppressing pro-inflammatory cytokine production, thereby limiting tissue damage in inflammatory diseases such as arthritis\u003csup\u003e23\u0026ndash;25\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWithin the TME, MT has been increasingly implicated in immune dysregulation and cancer progression. Tumor cells can acquire mitochondria from immune cells, including T cells and macrophages, to support their metabolic demands, enhance proliferation, and promote immune evasion\u003csup\u003e26,27\u003c/sup\u003e. Concurrently, metabolic reprogramming within the TME and mitochondrial dysfunction in tumor-infiltrating lymphocytes compromise antitumor immunity. For example, transfer of mutated mitochondrial DNA from cancer cells to T cells induces metabolic defects, cellular senescence, and impaired effector and memory functions, resulting in diminished antitumor responses both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e\u003csup\u003e26,27\u003c/sup\u003e. Together, these findings identify MT as a powerful regulator of immune cell fitness and tumor\u0026ndash;immune interactions, highlighting its potential as a therapeutic target to restore immune function in cancer.\u003c/p\u003e\n\u003cp\u003eAccordingly, emerging therapeutic strategies have begun to exploit MT as a means to reprogram recipient cell metabolism and function. Recent studies have demonstrated that satellite glial cells can transfer mitochondria to dorsal root ganglion sensory neurons through tunneling nanotubes, thereby protecting against peripheral neuropathy\u003csup\u003e28\u003c/sup\u003e. Similarly, mitochondrial donation from bone marrow stromal cells has been shown to enhance mouse CD8⁺\u0026nbsp;T cell bioenergetic capacity, improve resistance to exhaustion, and augment antitumor efficacy, underscoring the potential of MT as a strategy to restore immune cell fitness\u003csup\u003e29\u003c/sup\u003e. However, direct intercellular MT is inherently inefficient and poses translational challenges due to the required presence of mitochondrial donor cells\u003csup\u003e29\u003c/sup\u003e. The co-transfer or persistence of these highly activated donor cells can result in cellular contamination of the final cellular product, introducing non-immune cell populations alongside therapeutic immune cells. Such heterogeneity limits clinical applicability and raises significant safety concerns for therapeutic use.\u003c/p\u003e\n\u003cp\u003eTo address these challenges and directly investigate the potential of MT for immune cell engineering, we harness mitochondria from human induced pluripotent stem cells (iPSCs) and transfer them to CAR-NKT cells in this study, as iPSCs possess highly functional, youthful mitochondria characterized by elevated respiratory capacity, low oxidative damage, and robust bioenergetic plasticity\u003csup\u003e30\u003c/sup\u003e. We apply this approach to enhance human CAR-NKT cells with the goal of improving mitochondrial activity, metabolic fitness, and functional durability. We demonstrate that iPSC-MT efficiently augments CAR-NKT cell mitochondrial function, promotes effector memory differentiation, and reduces exhaustion, resulting in markedly enhanced antitumor activity. Collectively, our findings establish MT as a promising metabolic engineering strategy to rejuvenate CAR-NKT cells and improve the efficacy of CAR-NKT cell\u0026ndash;based cancer immunotherapy.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eiPSC-derived mitochondria are efficiently and robustly transferred into human CAR-NKT cells We established a platform to generate iPSC-MT-enhanced CAR-NKT (CAR-NKT\u003csub\u003eMito\u003c/sub\u003e) cells from peripheral blood mononuclear cells (PBMCs) obtained from healthy donors or cancer patients (Fig. 1a and Supplementary\u0026nbsp;Table 1). Human NKT cells were first isolated from PBMCs and activated using \u0026alpha;GC stimulation to enable rapid expansion. Expanded NKT cells were subsequently transduced with CARs targeting CD19, mesothelin (MSLN), or glypican-3 (GPC3) to generate antigen-specific CAR-NKT cells. In parallel, mitochondria were isolated from iPSCs and transferred \u003cem\u003eex vivo\u003c/em\u003e into CAR-NKT cells via an endocytosis-mediated uptake process\u003csup\u003e31,32\u003c/sup\u003e, resulting in efficient mitochondrial incorporation (Fig. 1a).\u003c/p\u003e\n\u003cp\u003eMitochondria derived from iPSCs were first labeled with MitoTracker Green (MTG), a membrane potential\u0026ndash;independent fluorescent dye that selectively stains mitochondrial mass, enabling quantitative assessment of MT efficiency in CAR-NKT cells by flow cytometry. Both CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell products exhibited high purity (\u0026gt;98%), confirming the robustness of the CAR-NKT manufacturing process (Fig. 1b). CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells demonstrated efficient uptake of iPSC-derived mitochondria, with transfer efficiency increasing proportionally to the mitochondria-to\u0026ndash;NKT (Mito:NKT) ratio, defined here as the number of iPSC donor cells relative to the number of NKT recipient cells (Fig. 1b, c). Using a Mito:NKT ratio of 4:1, we routinely achieved iPSC-MT efficiencies exceeding 50% (Fig. 1b, c). Subset analysis revealed that CD4 single-positive (SP) CAR-NKT cells displayed a significantly greater capacity for mitochondrial uptake compared with CD8 SP and double-negative (DN) CAR-NKT cells, suggesting subset-specific differences in metabolic demand and endocytic capacity that may underlie preferential mitochondrial acquisition (Fig. 1d-f)\u003csup\u003e33,34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eImmunofluorescence imaging confirmed successful transfer of iPSC-derived mitochondria into CAR-NKT cells using two complementary labeling approaches. In the first method, iPSCs were transfected with a mito-mScarlette plasmid to label mitochondria with red fluorescence prior to isolation and transfer. Following MT, recipient CAR-NKT cells were stained with MitoTracker Green, enabling discrimination between iPSC-derived mitochondria (red) and total mitochondrial mass (green) (Fig. 1g). This approach demonstrated clear incorporation of donor mitochondria within CAR-NKT cells, with transfer efficiencies of approximately 40\u0026ndash;60% observed at 2\u0026ndash;3 days post-transfer (Fig. 1h). Compared with CAR-NKT cells, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibited increased mitochondrial content and robust retention of iPSC-derived mitochondria (Fig. 1i).\u003c/p\u003e\n\u003cp\u003eIn a second approach, iPSC mitochondria were labeled via BacMam Mitochondria-GFP transduction prior to isolation (Supplementary\u0026nbsp;Fig. 1a). Immunofluorescence analysis similarly confirmed efficient and stable detection of GFP-labeled iPSC mitochondria within recipient CAR-NKT cells (Supplementary\u0026nbsp;Fig. 1a and 1b). Together, these imaging strategies validate the efficiency, stability, and reproducibility of iPSC-MT into CAR-NKT cells.\u003c/p\u003e\n\u003cp\u003eNotably, efficient iPSC-MT was observed across multiple iPSC lines, including those reprogrammed from fibroblasts and primary T cells (Fig. 1j). Comparable MT efficiencies (~50% at a Mito:NKT ratio of 4:1) were consistently achieved across these distinct iPSC sources, demonstrating the robustness and reproducibility of the iPSC-MT approach.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eiPSC-MT increases mitochondrial polarization, metabolic activity, and effector memory features in CAR-NKT cells\u003c/p\u003e\n\u003cp\u003eGiven the central role of mitochondrial fitness in sustaining immune cell function, we next examined whether iPSC-MT alters mitochondrial status and metabolic programs in CAR-NKT cells. Mitochondrial membrane potential was first assessed using JC-1 staining. Compared with conventional CAR-NKT cells, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibited a marked increase in JC-1 polymer formation, indicating enhanced mitochondrial polarization and improved mitochondrial functional integrity (Fig. 1k, l)\u003csup\u003e35\u003c/sup\u003e. Consistent with these findings, flow cytometry analyses revealed that CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells displayed significantly higher levels of MTG and MitoTracker Deep Red (MDR) compared with both quiescent PBMC-derived NKT cells and CAR-NKT cells (Fig. 1m, n). MTG and MDR signals reflect mitochondrial mass and mitochondrial membrane potential, respectively, together demonstrating increased mitochondrial content coupled with preserved functional activity in CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells\u003csup\u003e36\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTo determine whether these mitochondrial changes translated into altered cellular metabolism, we performed Seahorse extracellular flux analyses. CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibited significantly elevated basal and maximal oxygen consumption rates (OCR), as well as increased spare respiratory capacity, indicating enhanced oxidative phosphorylation (Fig. 1o, p). In parallel, extracellular acidification rate (ECAR) measurements revealed increased glycolytic activity following MT (Fig. 1o, p and Supplementary Fig. 1c). These coordinated enhancements in oxidative and glycolytic metabolism support a metabolically fit state associated with effector memory differentiation and sustained functional capacity. Together, these results demonstrate that iPSC-MT profoundly enhances mitochondrial function and metabolic activity in CAR-NKT cells, providing a bioenergetic foundation for their improved performance.\u003c/p\u003e\n\u003cp\u003eWe next examined how iPSC-MT influences CAR-NKT cell differentiation states. CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells were stratified based on MTG intensity into four populations\u0026mdash;Mito⁻, Mito\u003csup\u003elow\u003c/sup\u003e, Mito\u003csup\u003emed\u003c/sup\u003e, and Mito\u003csup\u003ehi\u003c/sup\u003e\u0026mdash;representing increasing degrees of iPSC-derived mitochondrial incorporation (Fig. 1q). Phenotypic analysis using CD45RO and CD62L revealed a progressive shift toward effector memory\u0026ndash;like differentiation with increasing mitochondrial content (Fig. 1q, r). Specifically, Mito\u003csup\u003ehi\u0026nbsp;\u003c/sup\u003eCAR-NKT cells exhibited a marked enrichment of CD62L⁻CD45RO⁺\u0026nbsp;effector memory populations compared with Mito⁻\u0026nbsp;and Mito\u003csup\u003elow\u003c/sup\u003e subsets, whereas na\u0026iuml;ve and central memory\u0026ndash;like populations were correspondingly reduced (Fig. 1q, r). This differentiation pattern closely correlated with MTG intensity, indicating a dose-dependent relationship between mitochondrial acquisition and CAR-NKT cell fate. These findings suggest that enhanced mitochondrial content promotes effector memory programming in CAR-NKT cells, providing a mechanistic link between MT, metabolic fitness, and functional differentiation. Overall, iPSC-MT preferentially drives CAR-NKT cells toward metabolically active, effector memory\u0026ndash;enriched states that are associated with improved antitumor functionality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibit enhanced effector and memory features with robust cytotoxic and cytokine-producing capacity\u003c/p\u003e\n\u003cp\u003eWe next analyzed the phenotype and functional properties of mature CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell products generated after 2\u0026ndash;3 weeks of \u003cem\u003eex vivo\u003c/em\u003e expansion using clinically compatible culture conditions\u003csup\u003e4,7\u003c/sup\u003e. To assess the generalizability and translational relevance of this approach, we evaluated three distinct CAR constructs targeting CD19, MSLN, and GPC3, which are clinically validated antigens expressed in a range of malignancies, including B cell malignancies as well as lung, ovarian, and liver cancers (Fig. 2a).\u003c/p\u003e\n\u003cp\u003eAll antigen-specific CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell products were generated with high purity, efficient CAR transduction, and robust MT. Across all constructs, CAR transduction efficiencies routinely exceeded 60%, with no significant differences observed between CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (Fig. 2b, c). Using MTG labeling, iPSC-derived mitochondria\u0026ndash;positive CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells could be isolated by flow cytometric sorting with \u0026gt;99% purity (Fig. 2b). Both CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibited robust expansion under clinically compatible culture conditions, achieving greater than 900-fold expansion over a 3-week manufacturing period (Fig. 2d). No consistent differences in CD4 and CD8 subpopulation distributions were observed between CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e products, although donor-dependent variability was noted across independent manufacturing runs (Fig. 2e).\u003c/p\u003e\n\u003cp\u003ePhenotypic analysis of memory differentiation revealed that CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells displayed a significant enrichment of effector memory\u0026ndash;like (CD62L⁻CD45RO⁺) populations, accompanied by a corresponding reduction in na\u0026iuml;ve and central memory\u0026ndash;like subsets (Fig. 2f, g). These findings confirm that iPSC-MT promotes effector memory differentiation in final CAR-NKT cell products (Fig. 1q, r, 2f, and g). Consistent with this phenotype, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells expressed higher levels of activation markers CD25 and CD44, increased production of effector cytokines including IFN-\u0026gamma; and TNF-\u0026alpha;, and elevated expression of cytotoxic molecules such as granzyme B, collectively indicating enhanced activation and cytotoxic potential (Fig. 2h, i).\u003c/p\u003e\n\u003cp\u003eFunctionally, upon \u0026alpha;-GC stimulation \u003cem\u003ein vitro\u003c/em\u003e, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells underwent more rapid and robust expansion compared with CAR-NKT cells and secreted higher levels of Th1-associated cytokines, including IFN-\u0026gamma;, TNF-\u0026alpha;, and IL-2, with modest increases in Th2-associated IL-4 (Fig. 2j-l). Together, these results demonstrate that iPSC-MT enhances the activation, effector differentiation, and functional responsiveness of CAR-NKT cell products without compromising manufacturability.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells display enhanced long-term tumor-killing capacity \u003cem\u003ein vitro\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe next evaluated the \u003cem\u003ein vitro\u003c/em\u003e antitumor activity of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells using a series of cytotoxicity assays across multiple human tumor models. To assess the generalizability of mitochondrial enhancement across different CAR specificities, four human tumor cell lines were selected: the CD19⁺\u0026nbsp;lymphoma cell line RAJI, the MSLN\u003csup\u003e+\u003c/sup\u003e lung cancer cell line H226, the MSLN⁺\u0026nbsp;ovarian cancer cell line OVCAR8, and the GPC3\u003csup\u003e+\u003c/sup\u003e liver cancer cell line SKHEP-1 (Fig. 3a). All tumor cell lines were engineered to express a firefly luciferase and enhanced green fluorescent protein dual-reporter (FG), enabling quantitative assessment of viable tumor cells by luminescence-based assays and flow cytometry (Fig. 3a). Target antigen expression was confirmed by flow cytometry prior to functional analyses (Fig. 3b).\u003c/p\u003e\n\u003cp\u003eTumor-killing assays were performed using five effector cell conditions: non-CAR-engineered NKT cells, CAR-NKT cells, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells, and CAR-NKT or CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells subjected to five consecutive rounds of tumor cell coculture to model chronic antigen exposure and functional exhaustion (Fig. 3c). Across all tumor models, unmodified NKT cells exhibited minimal cytotoxicity, indicating limited CAR-independent tumor killing within 24 hours (Fig. 3d). In contrast, both CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells mediated robust tumor cell elimination, with CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells consistently demonstrating superior cytotoxic activity (Fig. 3d). Notably, following repeated tumor stimulation, CAR-NKT cells displayed a marked reduction in killing capacity, consistent with the development of functional exhaustion (Fig. 3d). In contrast, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells retained potent tumor-killing activity despite repeated antigen exposure, indicating enhanced resistance to exhaustion (Fig. 3d).\u003c/p\u003e\n\u003cp\u003eConsistent with these functional differences, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibited sustained proliferative capacity following tumor coculture, even after five rounds of stimulation, accompanied by elevated production of effector cytokines (IFN-\u0026gamma;, TNF-\u0026alpha;, and IL-2), increased expression of the activation marker CD69, and higher levels of cytotoxic molecules including perforin and granzyme B (Fig. 3e-i). In contrast, repeatedly stimulated CAR-NKT cells progressively lost proliferative and effector capacity and showed significantly increased expression of exhaustion-associated markers, including PD-1, TIM-3, LAG-3, CTLA-4, and TIGIT (Fig. 3e-j).\u003c/p\u003e\n\u003cp\u003eFinally, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells did not exhibit appreciable cytotoxicity toward nonmalignant cells, including primary skeletal muscle cells and dermal fibroblasts, demonstrating antigen-specific tumor killing without detectable off-target toxicity (Fig. 3k-m). Together, these findings indicate that iPSC-MT confers durable cytotoxic function, enhanced persistence, and improved exhaustion resistance to CAR-NKT cells while maintaining target specificity and safety.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibit transcriptional programs associated with effector memory differentiation, cytotoxicity, and enhanced metabolic regulation\u003c/p\u003e\n\u003cp\u003eTo define the transcriptional impact of iPSC-MT, we performed single-cell RNA sequencing (scRNA-seq) on CD19-targeting CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells following 3 days of coculture with RAJI lymphoma cells (Fig. 4a). scRNA-seq analysis confirmed uniformly high expression of canonical NKT cell identity markers across both groups, including the invariant NKT TCR \u0026alpha;-chain (\u003cem\u003eTRAV10\u003c/em\u003e) and the lineage-defining transcription factor ZBTB16 (\u003cem\u003ePLZF\u003c/em\u003e), validating preservation of NKT cell identity (Supplementary\u0026nbsp;Fig. 2a).\u003c/p\u003e\n\u003cp\u003eUnsupervised uniform manifold approximation and projection (UMAP) analysis of the combined dataset revealed four major cell clusters (Fig. 4b). Gene set enrichment analysis (GSEA) annotated these clusters as na\u0026iuml;ve-like, effector/memory-like, proliferative, and resting populations (Fig. 4b and Supplementary\u0026nbsp;Fig. 2b)\u003csup\u003e5,7\u003c/sup\u003e. Compared with CAR-NKT cells, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibited a marked enrichment of effector/memory-like clusters, accompanied by a relative reduction in proliferative populations (Fig. 4c, d). Consistent with this shift, violin plot analyses demonstrated increased expression of gene signatures associated with effector memory differentiation, cytotoxic function, and NK-like activity in CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (Fig. 4e and Supplementary\u0026nbsp;Fig. 2c). Notably, genes involved in cytotoxicity (\u003cem\u003eGZMK\u003c/em\u003e, \u003cem\u003eGNLY\u003c/em\u003e), cytokine signaling (\u003cem\u003eIL2RA\u003c/em\u003e, \u003cem\u003eIL2RG\u003c/em\u003e), cell survival (\u003cem\u003eSTAT3\u003c/em\u003e, \u003cem\u003eBCL2\u003c/em\u003e), TNF signaling (\u003cem\u003eTNFRSF1B\u003c/em\u003e, \u003cem\u003eIRF1\u003c/em\u003e), antigen presentation (\u003cem\u003eCD74\u003c/em\u003e), and growth factor and differentiation pathways (\u003cem\u003eCSF1\u003c/em\u003e, \u003cem\u003eCSF2\u003c/em\u003e) were upregulated, indicating enhanced effector functionality and survival capacity (Fig. 4f and Supplementary\u0026nbsp;Fig. 2d).\u003c/p\u003e\n\u003cp\u003ePathway enrichment analyses further revealed that CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells upregulated programs related to nucleotide catabolism, hypoxic response, T cell activation and differentiation, cytokine responsiveness, metabolic regulation, and cell\u0026ndash;cell communication, consistent with an activated and metabolically adaptable state (Fig. 4g). Focused analysis of metabolic pathways showed increased expression of genes involved in fructose and mannose metabolism, glycolysis, glycerolipid and steroid metabolism, and fatty acid synthesis, alongside reduced cholesterol biosynthesis (Fig. 4h). CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells also upregulated genes associated with mitochondrial structure and oxidative metabolism (\u003cem\u003eOPA1\u003c/em\u003e, \u003cem\u003eDNM1L\u003c/em\u003e, \u003cem\u003eSDHA\u003c/em\u003e, \u003cem\u003eACADVL\u003c/em\u003e, \u003cem\u003eBNIP3\u003c/em\u003e, \u003cem\u003eBNIP3L\u003c/em\u003e) as well as glycolytic and metabolic reprogramming regulators (\u003cem\u003ePKM\u003c/em\u003e, \u003cem\u003eLDHA\u003c/em\u003e, \u003cem\u003eRPTOR\u003c/em\u003e, \u003cem\u003eHIF1A\u003c/em\u003e), aligning with the enhanced oxidative and glycolytic capacity observed functionally (Fig. 4i).\u003c/p\u003e\n\u003cp\u003eTogether, these transcriptomic analyses demonstrate that iPSC-MT drives coordinated transcriptional reprogramming toward effector memory differentiation, cytotoxic competence, and metabolic fitness in CAR-NKT cells, providing a molecular basis for their enhanced persistence and antitumor activity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibit enhanced CAR signaling\u003c/p\u003e\n\u003cp\u003eTo determine whether mitochondrial modification augments CAR-mediated signaling, we examined downstream signaling events in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells following antigen engagement. CD19-specific CAR-expressing cells were stimulated with plate-coated CD19 antigen to mimic CAR\u0026ndash;antigen interaction, and signaling molecules were analyzed by Western blot (Fig. 4j).\u003c/p\u003e\n\u003cp\u003eAntigen stimulation induced activation of canonical CAR/TCR-associated signaling pathways in both cell types, as evidenced by increased phosphorylation of CD3\u0026zeta;, ZAP-70, LAT, and PLC-\u0026gamma;1, as well as downstream effectors including STAT5, c-Jun, and NF-\u0026kappa;B (Fig. 4k, l). Notably, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells consistently exhibited higher levels of phosphorylation across these signaling intermediates compared with conventional CAR-NKT cells (Fig. 4k, l).\u003c/p\u003e\n\u003cp\u003eThese findings indicate that iPSC-MT potentiates proximal and distal CAR signaling cascades, suggesting that CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells possess amplified signal transduction capacity upon antigen engagement (Fig. 4m).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibit unique TME\u0026ndash;modulating capacity compared with CAR-T\u003csub\u003eMito\u003c/sub\u003e cells\u003c/p\u003e\n\u003cp\u003eCAR-NKT cells have been reported to remodel the immunosuppressive TME through selective targeting of CD1d⁺\u0026nbsp;myeloid populations, including tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), thereby overcoming a major barrier to effective solid tumor immunotherapy\u003csup\u003e6,8,37,38\u003c/sup\u003e. We therefore assessed whether iPSC-MT further enhances the TME-modulating capacity of CAR-NKT cells. In addition to CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells, we included conventional CAR-T cells and iPSC-MT\u0026ndash;enhanced CAR-T (CAR-T\u003csub\u003eMito\u003c/sub\u003e) cells as controls (Supplementary\u0026nbsp;Fig. 3a). Notably, MT efficiency in CAR-T cells was substantially lower than in CAR-NKT cells, reaching only ~20\u0026ndash;30% at a mitochondria-to\u0026ndash;T cell ratio of 4:1, highlighting intrinsic differences in mitochondrial uptake capacity between these lineages (Supplementary\u0026nbsp;Fig. 3b, c).\u003c/p\u003e\n\u003cp\u003eWe first evaluated TME modulation using primary human HCC tumor samples enriched for TAMs and MDSCs (Fig. 5a). Upon coculture, both CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells efficiently depleted TAMs and MDSCs, with \u0026alpha;-GC further enhancing killing through invariant NKT TCR\u0026ndash;CD1d engagement (Fig. 5b). Importantly, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells consistently exhibited superior myeloid cell\u0026ndash;depleting activity across all patient samples tested, indicating enhanced functional potency (Fig. 5b). Neither CAR-NKT nor CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells showed appreciable cytotoxicity toward CD1d⁻\u0026nbsp;or CD1d\u003csup\u003elow\u003c/sup\u003e immune populations within the liver TME, including T cells, NK cells, and B cells, supporting their specificity and safety (Fig. 5c-e). In contrast, neither conventional CAR-T nor CAR-T\u003csub\u003eMito\u003c/sub\u003e cells demonstrated significant TAM or MDSC killing, underscoring a CAR-NKT\u0026ndash;specific mechanism of TME modulation (Fig. 5f, g).\u003c/p\u003e\n\u003cp\u003eThese findings were further validated in a 3D tumor organoid model incorporating tumor cells and PBMC-derived, monocyte-polarized M2 macrophages to recapitulate immunosuppressive TME interactions\u003csup\u003e39,40\u003c/sup\u003e. M2 macrophages exhibited high expression of CD163, CD206, and CD1d, confirming their suppressive phenotype and susceptibility to NKT-mediated targeting (Fig. 5h-j). In this system, both CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells mediated dual killing of tumor cells and TAMs, accompanied by increased expression of activation marker CD69 and cytotoxic molecules perforin and granzyme B (Fig. 5k-n). Across all tumor models tested, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells consistently outperformed CAR-NKT cells in both tumor and TAM elimination (Fig. 5k-n). By contrast, CAR-T and CAR-T\u003csub\u003eMito\u003c/sub\u003e cells exhibited markedly impaired tumor killing and reduced cytotoxic molecule production, likely due to profound suppression by TAMs within the organoid system (Fig. 5o, p).\u003c/p\u003e\n\u003cp\u003eCollectively, these results demonstrate that iPSC-MT uniquely amplifies the intrinsic ability of CAR-NKT cells to simultaneously target tumor cells and remodel the immunosuppressive TME (Fig. 5q). CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells overcome myeloid-mediated suppression to sustain tumor killing, whereas CAR-T\u003csub\u003eMito\u003c/sub\u003e cells remain constrained by TAM/MDSC-driven inhibition (Fig. 5q). This dual antitumor and TME-modulating activity distinguishes CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells as a particularly promising platform for solid tumor immunotherapy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells demonstrate superior antitumor efficacy in multiple xenograft mouse models\u003c/p\u003e\n\u003cp\u003eWe next evaluated the \u003cem\u003ein vivo\u003c/em\u003e antitumor efficacy of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells across three xenograft mouse models representing distinct CAR specificities and disease contexts. These included a CD19⁺\u0026nbsp;RAJI-FG human lymphoma model, in which tumor cells were intravenously injected to establish systemic disease with dissemination to the liver, lung, and bone marrow (Fig. 6a-d); a GPC3⁺\u0026nbsp;SKHEP-1-FG liver cancer model, in which intravenously injected tumor cells preferentially engrafted and expanded within the liver, forming an orthotopic liver cancer model (Fig. 6e-h); and an MSLN⁺\u0026nbsp;OVCAR8-FG ovarian cancer model, in which intraperitoneal injection resulted in peritoneal tumor dissemination characteristic of advanced ovarian cancer (Fig. 6i-l). Together, these models encompass hematologic malignancy, orthotopic solid tumor growth, and disseminated peritoneal disease, providing a comprehensive assessment of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell antitumor activity \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eIn all three models, robust tumor growth was observed in the expected anatomical sites, confirming successful disease establishment (Fig. 6c, g, and k). Treatment with either CAR-NKT or CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells significantly suppressed tumor progression and prolonged animal survival (Fig. 6b-d, f-h, and j-l). Notably, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells consistently achieved superior tumor control compared with CAR-NKT cells across all models (Fig. 6b-d, f-h, and j-l). In both the RAJI-FG lymphoma and OVCAR8-FG ovarian cancer models, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e therapy resulted in complete tumor elimination and durable, tumor-free long-term survival (Fig. 6b-d, and j-l).\u003c/p\u003e\n\u003cp\u003eOverall, these results demonstrate that iPSC-MT markedly enhances the \u003cem\u003ein vivo\u003c/em\u003e antitumor potency of CAR-NKT cells across diverse tumor types and anatomical settings. The ability of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells to achieve durable tumor control and long-term survival in both hematologic and solid tumor models highlights the broad therapeutic potential of organelle-level metabolic reprogramming as a strategy to improve cellular immunotherapy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells demonstrate enhanced \u003cem\u003ein vivo\u003c/em\u003e persistence, effector memory differentiation, and reduced exhaustion across multiple xenograft models\u003c/p\u003e\n\u003cp\u003eTo elucidate the mechanisms underlying the superior \u003cem\u003ein vivo\u003c/em\u003e antitumor efficacy of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells, we analyzed therapeutic cells recovered from xenograft-bearing mice, focusing on their persistence, tissue distribution, phenotype, and functional status. In the RAJI-FG human lymphoma model, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells demonstrated significantly enhanced \u003cem\u003ein vivo\u003c/em\u003e persistence and widespread tissue infiltration, including the liver, lung, peripheral blood, and spleen (Fig. 7a, b). Consistent with sustained functional activity, plasma cytokine analyses revealed elevated levels of effector cytokines IFN-\u0026gamma; and TNF-\u0026alpha; in CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cell-treated mice (Fig. 7c).\u003c/p\u003e\n\u003cp\u003ePhenotypic analysis of liver-infiltrating cells further showed that CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells expressed higher levels of activation and effector markers, including CD69 and CD25, increased expression of cytotoxic molecules perforin and granzyme B, and reduced expression of late exhaustion-associated markers, including TOX, TIM-3, LAG-3, TIGIT, and CTLA-4, compared with CAR-NKT cells (Fig. 7d-f). Together, these findings indicate that iPSC-MT supports sustained effector function while limiting terminal exhaustion \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eSimilar phenotypic and functional advantages of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells were observed in the SKHEP-1-FG liver cancer and OVCAR8-FG ovarian cancer models, including enhanced persistence, increased effector activation, and reduced exhaustion (Fig. 7g-n, and Supplementary\u0026nbsp;Fig. 4a, b). Notably, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells preferentially accumulated within tumor-relevant anatomical sites\u0026mdash;enriching in the liver in the SK-HEP-1-FG model and in the peritoneal cavity in the OVCAR8-FG model\u0026mdash;reflecting efficient tumor-directed trafficking and tissue-specific homing (Fig. 7g, k). Immunohistochemical analyses further confirmed robust migration and infiltration of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells into tumor-containing tissues (Fig. 7o-r).\u003c/p\u003e\n\u003cp\u003eOverall, these results demonstrate that iPSC-MT endows CAR-NKT cells with durable \u003cem\u003ein vivo\u003c/em\u003e persistence, enhanced effector memory differentiation, efficient tumor-site homing, and resistance to exhaustion across diverse tumor contexts. This coordinated enhancement of cellular fitness and functionality provides a mechanistic foundation for the superior antitumor efficacy of CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells observed \u003cem\u003ein vivo\u0026nbsp;\u003c/em\u003eand establishes MT as a powerful strategy to optimize CAR-NKT cell performance in both hematologic and solid tumor settings.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOrganelle-level metabolic reprogramming, particularly through MT, has emerged as a promising mechanism for altering recipient cell phenotype and function\u003csup\u003e27\u0026ndash;29\u003c/sup\u003e. In physiological and pathological contexts, MT most commonly occurs \u003cem\u003ein vivo\u003c/em\u003e through cell contact\u0026ndash;dependent mechanisms, including tunneling nanotubes, transient cell fusion events, and gap junction\u0026ndash;mediated transfer\u003csup\u003e31,41\u003c/sup\u003e. In addition, mitochondria can be transferred through cell contact\u0026ndash;independent pathways, in which extracellular mitochondria are released and subsequently internalized by neighboring or distant cells via the circulation\u003csup\u003e31,42\u003c/sup\u003e. Despite these advances, approaches to precisely and controllably harness MT for therapeutic immune cell engineering remain limited. In particular, cell contact\u0026ndash;independent MT may compromise product purity through inadvertent donor cell contamination, creating heterogeneity that complicates standardization, quality control, and clinical translation.\u003c/p\u003e\n\u003cp\u003eIn this study, we establish a defined \u003cem\u003eex vivo\u003c/em\u003e approach to achieve stem cell\u0026ndash;derived MT into CAR-NKT cells, leveraging the robust metabolic capacity of iPSC mitochondria and the unique antitumor properties of CAR-NKT cells, including multispecific tumor targeting, TME modulation, and efficient solid tumor homing\u003csup\u003e8,38,43\u003c/sup\u003e. By directly reprogramming cellular metabolism at the organelle level, this strategy rejuvenates CAR-NKT cell bioenergetics, persistence, and effector function while limiting exhaustion, representing a conceptual departure from conventional genetic or signaling-based CAR optimization approaches.\u003c/p\u003e\n\u003cp\u003eNKT cells are governed by metabolic programs that are fundamentally distinct from those of conventional \u0026alpha;\u0026beta; T cells, reflecting their innate-like biology and rapid effector function\u003csup\u003e1,44,45\u003c/sup\u003e. Whereas activated CD4⁺\u0026nbsp;T cells predominantly adopt aerobic glycolysis and lactate production, NKT cells preferentially route glucose-derived carbon into the pentose phosphate pathway and mitochondrial oxidative metabolism\u003csup\u003e34\u003c/sup\u003e. As a consequence, NKT cell viability and effector function are highly sensitive to extracellular metabolic conditions, with elevated lactate concentrations impairing their homeostasis and cytokine production. Mitochondrial metabolism plays a particularly critical role in invariant NKT cell biology\u003csup\u003e33\u003c/sup\u003e: NKT cell development is exquisitely sensitive to disruptions in electron transport chain function, and mature NKT cells exhibit limited fatty acid oxidation and reduced mitochondrial respiratory reserve under steady-state conditions. At the signaling level, mitochondrial activity integrates metabolic inputs with TCR and IL-15 signaling, shaping downstream NFAT activation and effector programming\u003csup\u003e33\u003c/sup\u003e. Together, these features define a unique metabolic dependency landscape in NKT cells, suggesting that targeted enhancement of mitochondrial function may represent an especially effective strategy to modulate CAR-NKT cell fate and functionality, distinct from approaches applied to conventional CAR-T cells.\u003c/p\u003e\n\u003cp\u003eConsistent with these intrinsic metabolic features, CAR-NKT cells exhibit metabolic programs that differ from those of conventional CAR-T cells, including a greater reliance on lipid metabolism within the TME\u003csup\u003e46\u0026ndash;48\u003c/sup\u003e. These distinctive metabolic dependencies suggest that targeted enhancement of mitochondrial capacity may exert particularly pronounced effects on CAR-NKT cell function. In line with this hypothesis, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells demonstrated potent antitumor activity both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e across multiple human tumor xenograft models, including disseminated hematologic malignancies, orthotopic liver cancer, and intraperitoneal ovarian cancer (Fig. 6). Notably, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells efficiently trafficked to tumor-resident tissues in all models, indicating robust tumor-homing capacity that is favorable for solid tumor therapy (Fig. 7). Beyond direct tumor cytotoxicity, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells effectively remodeled the immunosuppressive TME by selectively depleting CD1d⁺\u0026nbsp;myeloid populations (Fig. 5), a key barrier to effective antitumor immunity and a known limitation of conventional CAR-T therapies\u003csup\u003e49\u0026ndash;52\u003c/sup\u003e. Together, these findings position CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells as a metabolically optimized cellular therapy with unique advantages for targeting both tumor cells and the TME.\u003c/p\u003e\n\u003cp\u003eNotably, because the invariant NKT TCR recognizes lipid antigens presented by the non-polymorphic MHC class I\u0026ndash;like molecule CD1d, CAR-NKT cells are not expected to induce graft-versus-host disease (GvHD), supporting their development as off-the-shelf allogeneic cellular therapies\u003csup\u003e9,53\u0026ndash;55\u003c/sup\u003e. Accordingly, multiple allogeneic CAR-NKT platforms have been generated, including products derived from peripheral blood mononuclear cells and hematopoietic stem and progenitor cells\u003csup\u003e7,14,37,56,57\u003c/sup\u003e. Recent clinical studies of CD19-targeting CAR-NKT cells incorporating short hairpin RNA\u0026ndash;mediated knockdown of \u0026beta;2-microglobulin and CD74 to reduce HLA class I and class II expression have demonstrated feasibility, safety, and preliminary antitumor activity\u003csup\u003e58\u003c/sup\u003e. However, despite these advances, the \u003cem\u003ein vivo\u003c/em\u003e persistence of allogeneic CAR-NKT cells remains limited, likely due to host-mediated immune rejection. Our findings suggest that metabolic rejuvenation via iPSC-MT may provide a complementary strategy to enhance the durability of allogeneic CAR-NKT cell therapies. CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells exhibit enhanced bioenergetic capacity, sustained expansion, and reduced expression of exhaustion-associated markers following tumor encounter \u003cem\u003ein vivo\u003c/em\u003e (Fig. 7), features that are consistent with improved functional persistence. Thus, organelle-level metabolic reprogramming may uniquely support the long-term survival and antitumor efficacy of allogeneic CAR-NKT cells, offering a potential solution to a major limitation of current off-the-shelf cellular immunotherapies.\u003c/p\u003e\n\u003cp\u003eFinally, MT\u0026ndash;mediated metabolic reprogramming represents a modular strategy that can be readily integrated with other approaches to enhance CAR-NKT cell function. iPSC-MT may be combined with cytokine-based augmentation, including IL-15, IL-18, or IL-21 signaling, as well as immune checkpoint modulation, to further optimize CAR-NKT cell persistence and effector activity\u003csup\u003e12,13,59\u0026ndash;61\u003c/sup\u003e. Recent studies have highlighted distinct checkpoint regulatory pathways governing CAR-NKT and CAR-T cells, with CAR-NKT cell function preferentially constrained by CD96, whereas CAR-T cells are more strongly regulated by TIGIT, underscoring the need for lineage-specific combinatorial strategies\u003csup\u003e48\u003c/sup\u003e. The ability to metabolically fortify CAR-NKT cells is likely to be particularly advantageous in hostile TMEs characterized by hypoxia, nutrient deprivation, and immunosuppressive signaling, where conventional cellular therapies often fail\u003csup\u003e50,62\u0026ndash;65\u003c/sup\u003e. Additionally, beyond iPSC-derived mitochondria, other stem cell sources, including MSCs and embryonic stem cells (ESCs), may serve as alternative mitochondrial donors for CAR-NKT cell engineering, warranting further development and systematic side-by-side comparison. Together, our findings establish organelle-level metabolic reprogramming as a versatile platform for arming CAR-NKT cells and provide a rational framework for developing next-generation cellular immunotherapies for metabolically challenging cancers.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy approval\u003c/p\u003e\n\u003cp\u003eThis study complies with all relevant ethical regulations. All experiments involving primary HCC patient samples were approved by the Ronald Reagan UCLA Medical Center (IRB# IRB-25-0948). Animal studies were approved by the Division of Laboratory Animal Medicine at UCLA. Healthy donor PBMCs were provided by the UCLA/CFAR Virology Core Laboratory without identification information under federal and state regulations.\u003c/p\u003e\n\u003cp\u003eMice\u003c/p\u003e\n\u003cp\u003eNOD.Cg-\u003cem\u003ePrkdc\u003csup\u003escid\u003c/sup\u003e Il2rg\u003csup\u003etm1Wjl\u003c/sup\u003e\u003c/em\u003e/SzJ\u0026nbsp;(NOD-\u003cem\u003escid\u003c/em\u003e IL2Rg\u003csup\u003enull\u003c/sup\u003e, NSG) mice were purchased from The Jackson Laboratory, and maintained in animal facilities of the UCLA in a temperature-controlled environment (68\u0026thinsp;\u0026deg;F to 79\u0026thinsp;\u0026deg;F) with a 12-hour light cycle. 6- to10-week-old mice were used for all experiments. All mice were bred and maintained under specific pathogen-free conditions. All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of UCLA, and all animal procedures were conducted in accordance with the animal care and use regulations of the Division of Laboratory Animal Medicine (DLAM) at UCLA. Given the nature of the lymphoma, orthotopic liver cancer, and orthotopic ovarian cancer models, there were no restrictions on tumor size or burden, making direct inferences from external measures unfeasible. No differences in tumor growth or treatment response were observed between male and female mice in these xenograft models. In some studies, both male and female mice were used within the same group or assigned to separate groups. Experimental mice were randomly assigned to treatment groups to avoid statistically significant differences in the baseline tumor burden.\u003c/p\u003e\n\u003cp\u003eCell culture media and reagents\u003c/p\u003e\n\u003cp\u003eRecombinant human IL-2, IL-7, and IL-15 were purchased from PeproTech. Fetal bovine serum (FBS), and \u0026beta;-mercaptoethanol (\u0026beta;-ME) were purchased from Sigma. Penicillin-streptomycin-glutamine (P/S/G), MEM nonessential amino acids (NEAA), HEPES buffer solution, and sodium pyruvate were purchased from Gibco. Normocin was purchased from InvivoGen. The RPMI 1640 cell culture medium and the DMEM cell culture medium were purchased from Thermo Fisher Scientific. The CryoStor Cell Cryopreservation Media CS10 was purchased from MilliporeSigma. The mTeSR Plus medium used for iPSC culture was purchased from STEMCELL Technologies.\u003c/p\u003e\n\u003cp\u003eThe C10 medium was made of RPMI 1640 cell culture medium supplemented with FBS (10% v/v), P/S/G (1% v/v), NEAA (1% v/v), HEPES (10 mM), sodium pyruvate (1 mM), \u0026beta;-ME (50 \u0026mu;M), and Normocin (100 \u0026mu;g/ml). The D10 medium was made of DMEM supplemented with FBS (10% v/v), P/S/G (1% v/v), and Normocin (100 \u0026mu;g/ml). The R10 medium was made of RPMI 1640 supplemented with FBS (10% v/v), P/S/G (1% v/v), and Normocin (100 \u0026mu;g/ml).\u003c/p\u003e\n\u003cp\u003eLentiviral vectors\u003c/p\u003e\n\u003cp\u003eAll lentiviral vectors used in this study were constructed from a parental vector pMNDW\u003csup\u003e8,66\u003c/sup\u003e.\u0026nbsp;The 2A sequence derived from foot-and-mouth disease virus (F2A) was used to link the inserted genes to achieve co-expression. The Lenti/FG vector was constructed by inserting a synthetic bicistronic gene encoding Fluc-P2A-EGFP into the pMNDW\u003csup\u003e8,67\u003c/sup\u003e. The Lenti/CAR19 vector was constructed by inserting a synthetic gene encoding human CD19-targeting CAR into the pMNDW. The Lenti/MCAR vector was constructed by inserting a synthetic gene encoding human MSLN-targeting CAR into the pMNDW. The Lenti/GCAR vector was constructed by inserting a synthetic gene encoding human GPC3-targeting CAR into the pMNDW. The synthetic gene fragments were obtained from GenScript and IDT. Lentiviruses were produced using human embryonic kidney 293T (HEK293T) cells (ATCC), following a standard transfection protocol using the Trans-IT-Lenti Transfection Reagent (Mirus Bio) and a centrifugation concentration protocol using the Amicon Ultra Centrifugal Filter Units, according to the manufacturer\u0026rsquo;s instructions (MilliporeSigma).\u003c/p\u003e\n\u003cp\u003eStable tumor cell lines\u003c/p\u003e\n\u003cp\u003eHuman lymphoma cell line RAJI (cat. no. CCL-86), lung cancer cell line H226 (cat. no. CRL-5826), and liver cancer cell line SKHEP1 (cat. no. HTB-52) were purchased from the ATCC. Human ovarian cancer cell line OVCAR8 was generously provided by the Division of Cancer Treatment and Diagnosis (DCTD) Tumor Repository at the National Institutes of Health (NIH). The parental tumor cell lines were transduced with lentiviral vectors encoding the intended gene(s) to produce stable tumor cell lines overexpressing FG. 72 hours post lentivector transduction, cells were subjected to flow cytometry sorting to isolate gene-engineered cells for generating stable cell lines. Four stable tumor cell lines were generated for this study, including RAJI-FG, H226-FG, SKHEP1-FG, and OVCAR8-FG cell lines. All tumor cell lines utilized in this study underwent short tandem repeat (STR) profiling, and the resulting profiles were compared to established databases to confirm accurate identification. Furthermore, the cell lines were regularly screened for mycoplasma contamination to preserve their integrity and authenticity.\u003c/p\u003e\n\u003cp\u003eiPSC lines\u003c/p\u003e\n\u003cp\u003eMultiple human iPSC lines were used in this study, including fibroblast-derived and T cell\u0026ndash;derived lines. All protocols involving pluripotent stem cells were approved by the Human Embryonic Stem Cell Research Oversight Committee and the Institutional Review Board. Fibroblast-derived iPSC lines included DMD 1001 R1 (generated by RNA reprogramming of healthy female fibroblasts)\u003csup\u003e68\u003c/sup\u003e, iPS11 (Alstem Cell Advancements, cat. no. iPSC11), hiPS2 (UCLA Broad Stem Cell Research Center Stem Cell Core)\u003csup\u003e69\u003c/sup\u003e, and XFiPS xeno-free human iPSCs (UCLA Broad Stem Cell Research Center Stem Cell Core)\u003csup\u003e70\u003c/sup\u003e. Cells were maintained either on growth factor\u0026ndash;reduced Matrigel (BD Biosciences, cat. no. \u0026nbsp;356231) in mTeSR complete medium (StemCell Technologies, cat. no. 05850) according to standard culture conditions.\u003c/p\u003e\n\u003cp\u003eHealthy donor T cells were reprogrammed into iPSCs using a modified, integration-free episomal plasmid method (Okita et al., 2013). Briefly, 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e na\u0026iuml;ve/memory T cells were electroporated with 3 \u0026mu;g of episomal plasmids encoding OCT3/4, SOX2, KLF4, L-MYC, LIN28, and shRNA targeting TP53 using the Human T Cell Nucleofector Kit and 4D-Nucleofector system (Lonza). Following electroporation, cells were cultured in X-VIVO 15 medium (Lonza) supplemented with 10% FBS (HyClone), 50 U/mL recombinant human IL-2 (Novartis Oncology), 0.5 ng/mL recombinant human IL-15 (CellGenix), and Dynabeads Human T-Expander CD3/CD28 (Thermo Fisher Scientific) at a 1:1 bead-to-cell ratio. Two days post-transfection, PSC medium containing basic fibroblast growth factor (bFGF) and 10 \u0026mu;M Y-27632 was added. The medium was fully replaced with PSC medium on day 4. Emerging iPSC colonies were visible between days 20\u0026ndash;30 and were manually picked for expansion in cGMP-grade mTeSR1 medium on Matrigel-coated (Corning) plates. Unless otherwise specified, the majority of experiments were performed using the iPS11 cell line.\u003c/p\u003e\n\u003cp\u003eLiver and PBMC sample collection\u003c/p\u003e\n\u003cp\u003ePrimary HCC patient samples, including liver tumor and peripheral blood samples, were collected at the Ronald Reagan UCLA Medical Center from consented patients through an IRB-approved protocol (IRB-25-0948) and processed. Information regarding the patients\u0026apos; gender and age was not provided in this study to avoid including three or more indirect identifiers for the study participants. Patient gender was not considered in the study design and was determined based on self-reporting.\u003c/p\u003e\n\u003cp\u003eHealthy donor-derived PBMCs were provided by the UCLA/CFAR Virology Core Laboratory without identification information under federal and state regulations. PBMCs were cryopreserved in Cryostor CS10 (Sigma St. Louis, MO, USA) using CoolCell (BioCision, Larkspur, CA, UCA), and were frozen in liquid nitrogen for storage and to supply all experiments.\u003c/p\u003e\n\u003cp\u003eAntibodies and flow cytometry\u003c/p\u003e\n\u003cp\u003eFluorochrome-conjugated antibodies specific for human CD3 (clone HIT3a, Pacific Blue, PE, or PE-Cy7-conjugated, 1:500, cat. no. 300330, 300308, or 300316), CD4 (clone OKT4, PE-Cy7, PerCP, or FITC-conjugated, 1:500, cat. no. 317414, 317432, or 317408), CD8 (clone SK1, PE, APC-Cy7, or APC-conjugated, 1:300, cat. no. 344706, 344714, or 344722), CD14 (clone HCD14, FITC-conjugated, 1:200, cat. no. 325604), CD11b (clone W18347A, APC-conjugated, 1:500, cat. no. 340008), CD25 (clone BC96, APC-conjugated, 1:200, cat. no. 302610), CD44 (clone BJ18, PE-conjugated, 1:200, cat. no. 338808), CD45 (clone HI30, PerCP, FITC or Pacific Blue-conjugated, 1:500, cat. no. 304026, 304038, or 304022), CD69 (clone FN50, PE-Cy7 or PerCP-conjugated, 1:50, cat. no. 310912 or 310928), TCR\u0026alpha;\u0026beta; (clone I26, Pacific Blue or PE-Cy7-conjugated, 1:25, cat. no. 306715 or 306720), IFN-\u0026gamma; (clone B27, PE-Cy7-conjugated, 1:50, cat. no. 506518), Granzyme B (clone QA16A02, APC-conjugated, 1:2,000 or 1:5,000, cat. no. 372204), Perforin (clone dG9, PE-Cy7-conjugated, 1:50 or 1:100, cat. no. 308126), IL-2 (clone MQ1-17H12, APC-Cy7-conjugated, 1:50, cat. no. 500342), PD-1 (clone A17188A, FITC, APC, or PE-conjugated, 1:50, cat. no. 379206, 379208, or 379210), LAG-3 (clone 11C3C65, FITC, APC-Cy7, or PE-conjugated, 1:50, cat. no. 369308, 369348, or 369306), TIM-3 (clone A18087E, PE or APC-conjugated, 1:50, cat. no. 364806 or 364804), CD1d (clone 51.5, PE-Cy7-conjugated, 1:50, cat. no. 350310), CD163 (clone GHI/61, PE-conjugated, 1:200, cat. no. 333606), CD206 (clone 15-2, APC-conjugated, 1:200, cat. no. 321110), CD62L (clone W21031N, PE-Cy7-conjugated, 1:50, cat. no. 384808), and CD45RO (clone UCHL1, PE-Cy7 or APC-Cy7-conjugated, 1:100, cat. no. 304230 or 304228) were purchased from BioLegend. Fluorochrome-conjugated antibodies specific for human TCR V\u0026alpha;24-J\u0026beta;18 (clone 6B11, PE-conjugated, 1:10, cat. no. 552825) were purchased from BD Biosciences. Fixable Viability Dye eFluor506 (e506, 1:500) was purchased from Affymetrix eBioscience. Mouse Fc Block (anti-mouse CD16/32) was purchased from BD Biosciences, and human Fc Receptor Blocking Solution (TrueStain FcX) was purchased from BioLegend. All flow cytometry staining was performed following standard protocols, as well as specific instructions provided by the manufacturer of a particular antibody. Stained cells were analyzed using a MACSQuant Analyzer 10 flow cytometer (Miltenyi Biotech), following the manufacturers\u0026rsquo; instructions. FlowJo software version 9 (BD Biosciences) was used for data analysis. In our study, note the use of antibodies with identical clones but differing conjugated fluorochromes, with one typical antibody listed herein.\u003c/p\u003e\n\u003cp\u003eFor intracellular cytokine staining, the cells were thawed and resuspended in C10 medium. Cells were stimulated with PMA (Calbiochem, cat. no. 524400; 50 ng/mL) and ionomycin (Calbiochem, cat. no. 407952.; 500 ng/mL) and incubated at 37\u0026deg;C for 2 hours. GolgiStop (BD Biosciences, car. No. 554724; 1.5 \u0026micro;L/mL) was then added to inhibit cytokine secretion, followed by an additional 4-hour incubation. Subsequently, intracellular staining was performed using the Cell Fixation/Permeabilization Kit (BD Biosciences, cat. no. 554714) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003eEnzyme-linked immunosorbent cytokine assays (ELISAs)\u003c/p\u003e\n\u003cp\u003eThe ELISAs for detecting human cytokines were performed following a standard protocol from BD Biosciences. Supernatants from cell culture assays were collected and assayed to quantify human IFN-\u0026gamma;, IL-2, IL-4, and TNF-\u0026alpha;. The capture and biotinylated pairs for detecting cytokines were purchased from BD Biosciences. The streptavidin-HRP conjugate was purchased from Invitrogen. Human cytokine standards were purchased from eBioscience. Tetramethylbenzidine substrate was purchased from KPL. The samples were analyzed for absorbance at 450 nm using an Infinite M1000 microplate reader (Tecan).\u003c/p\u003e\n\u003cp\u003eiPSC mitochondrial extraction\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMitochondria were isolated from iPSC cells using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874), following the manufacturer\u0026rsquo;s reagent-based protocol. Briefly, harvested iPSCs were pelleted by centrifugation and resuspended in Mitochondria Isolation Reagent A supplemented with EDTA-free protease inhibitor cocktail. Cells were incubated on ice and subsequently treated with Mitochondria Isolation Reagent B, followed by incubation on ice with intermittent vortexing. Mitochondria Isolation Reagent C was then added, and the lysates were subjected to differential centrifugation to remove nuclei and cellular debris. The post-nuclear supernatant was centrifuged to pellet the mitochondrial fraction. The mitochondrial pellet was washed once with Mitochondria Isolation Reagent C and maintained on ice prior to downstream applications.\u003c/p\u003e\n\u003cp\u003eFor preparation of fluorescently labeled mitochondria, iPSCs were incubated with MitoTracker Green (50 nM; Thermo Fisher Scientific, cat. no. M7514) or MitoTracker Deep Red (50 nM; Thermo Fisher Scientific, cat. no. M22426) for 30 min at 37\u0026thinsp;\u0026deg;C prior to mitochondrial isolation. After staining, cells were washed with PBS and processed for mitochondrial isolation as described above.\u003c/p\u003e\n\u003cp\u003eGeneration of CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells\u003c/p\u003e\n\u003cp\u003eHealthy donor PBMCs were sorted with MACS via Anti-iNKT Microbeads (Miltenyi Biotech, cat. no. 130-094-842) labeling to enrich NKT cells, following the manufacturer\u0026rsquo;s instructions. The enriched NKT cells were mixed with donor-matched irradiated \u0026alpha;GC/PBMCs at a ratio of 1:1 - 1:2, followed by culturing in C10 medium supplemented with 10 ng/ml IL-7 and IL-15. On day 3, NKT cells were transduced with lentiviruses (e.g., Lenti/CAR19, Lenti/GCAR, or Lenti/MCAR) for 24 h. The resulting CAR-NKT cells were expanded for about 2 weeks in C10 medium supplemented with 10 ng/ml IL-7 and IL-15 and cryopreserved for future use.\u003c/p\u003e\n\u003cp\u003eCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells were generated by transferring mitochondria derived from iPSCs into NKT cells 24 hours after CAR transduction. iPSCs and NKT cells were counted using a hemocytometer, and the desired donor-to-recipient ratios were calculated prior to mitochondrial isolation. Mitochondria were isolated from iPSCs using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874) according to the manufacturer\u0026rsquo;s instructions. Freshly isolated mitochondria were then added to CAR-NKT cells cultured in C10 medium at the indicated ratios. Mitochondrial transfer efficiency was assessed using MitoTracker Green\u0026ndash;labeled mitochondria followed by flow cytometric analysis. For subsequent functional assays, CAR-NKT\u003csub\u003eMito\u003c/sub\u003e and CAR-NKT cells were FACS-sorted 2 days post\u0026ndash;mitochondrial transfer based on FITC fluorescence, expanded in culture for an additional 2 weeks, and then used for tumor cytotoxicity and other assays.\u003c/p\u003e\n\u003cp\u003eGeneration of conventional CAR-T and CAR-T\u003csub\u003eMito\u003c/sub\u003e cells\u003c/p\u003e\n\u003cp\u003eNon-treated tissue culture 24-well or 12-well plates (Corning) were coated with Ultra-LEAF\u003csup\u003eTM\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003ePurified Anti-Human CD3 Antibody (Clone OKT3; BioLegend, cat. no. 317326) at 1 \u0026mu;g/ml (500 \u0026mu;l/well), at room temperature for 2 hours or alternatively, overnight at 4 \u0026deg;C. Healthy donor PBMCs were resuspended in the C10 medium supplemented with 1 \u0026mu;g/ml Ultra-LEAF\u003csup\u003eTM\u003c/sup\u003e Purified Anti-Human CD28 Antibody (Clone CD28.2, BioLegend, cat. no. 302943) and 30 ng/ml IL-2, followed by seeding in the pre-coated plates at 1 x 10\u003csup\u003e6\u003c/sup\u003e cells/ml (1 ml/well). On day 2, cells were transduced with lentiviruses (e.g., Lenti/CAR19, Lenti/GCAR, or Lenti/MCAR) for 24 hours. The resulting CAR-T cells were expanded for about 2 weeks in C10 medium supplemented with human IL-2 and cryopreserved for future use.\u003c/p\u003e\n\u003cp\u003eCAR-T\u003csub\u003eMito\u003c/sub\u003e cells were generated by transferring mitochondria derived from iPSCs into T cells 24 hours after CAR transduction. Mitochondria were isolated from iPSCs using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874) according to the manufacturer\u0026rsquo;s instructions. Freshly isolated mitochondria were then added to CAR-T cells cultured in C10 medium at the indicated ratios. Mitochondrial transfer efficiency was assessed using MitoTracker Green\u0026ndash;labeled mitochondria followed by flow cytometric analysis.\u003c/p\u003e\n\u003cp\u003eImmunofluorescence staining and imaging\u003c/p\u003e\n\u003cp\u003eA plasmid encoding mito-mScarlette containing a mitochondrial targeting sequence (MTS) was obtained from the Advanced Microscopy Facility for Mitochondrial Research. The mito-mScarlette plasmid was transfected into iPSCs using Lipofectamine 3000 (Thermo Fisher Scientific, cat. no. L3000008), according to the manufacturer\u0026rsquo;s instructions. Three days after transfection, mitochondria were isolated from iPSCs using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874). The isolated mitochondria were then co-incubated with CAR-NKT cells for 24 h. For fluorescence staining, 0.5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells were collected from each experimental group and stained with MitoTracker Green (50 nM; Thermo Fisher Scientific, cat. no. M7514) for 30 min at 37\u0026thinsp;\u0026deg;C, followed by nuclear staining with Hoechst 33342 (Thermo Fisher Scientific, cat. no. H21486) for 5 min. Cells were washed three times with PBS and centrifuged at 300 \u0026times; g to deposit onto coverslips coated with poly-L-lysine (Thermo Fisher Scientific, cat. no. A3890401). Fluorescence images were acquired using a Leica Confocal SP8-STED/FLIM/FCS microscope. In this assay, iPSC-derived mitochondria were visualized in red due to mito-mScarlette expression, whereas total mitochondria were labeled in green with MitoTracker Green.\u003c/p\u003e\n\u003cp\u003eIn a separate imaging assay, iPSCs were transduced with BacMam 2.0 Mitochondria-GFP (Thermo Fisher Scientific, cat. no. C10600) to label mitochondria with GFP, according to the manufacturer\u0026rsquo;s instructions. Three days after transduction, mitochondria were isolated using the Mitochondria Isolation Kit for Cultured Cells (Thermo Fisher Scientific, cat. no. 89874) and co-incubated with CAR-NKT cells for 24 h. Cells (0.5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e per group) were stained with CellTracker Red (Thermo Fisher Scientific, cat. no. C34552) for 30 min and Hoechst 33342 (Thermo Fisher Scientific, cat. no. H21486) for 5 min, followed by three washes with PBS. Cells were centrifuged at 300 \u0026times; g and deposited onto poly-L-lysine\u0026ndash;coated coverslips. Fluorescence images were acquired using a Zeiss fluorescence microscope.\u003c/p\u003e\n\u003cp\u003eXFe96 seahorse assay\u003c/p\u003e\n\u003cp\u003eCAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells were collected and cryopreserved in liquid nitrogen. Prior to\u003c/p\u003e\n\u003cp\u003emetabolic analysis, the cells were thawed and recovered in C10 medium for 24 hours before being sent to the UCLA Metabolomics Core. The recovered cells were then centrifuged onto a poly-L-lysine\u0026ndash;coated 96-well Seahorse plate at 300 \u0026times; g for 5 minutes, with 2.5 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells\u003c/p\u003e\n\u003cp\u003eseeded per well. The culture plate was placed in the Seahorse XFe96 Analyzer (Agilent Technologies), and the standard acquisition program was executed. The assay included an equilibration step followed by sequential measurements of basal respiration, post-oligomycin\u003c/p\u003e\n\u003cp\u003einjection, and post-FCCP (Carbonyl cyanide-4-(trifluoromethoxy)phenylhydrazone) injection. Each measurement cycle consisted of three loops of 3-minute mixing, 2-minute waiting, and 3-minute measuring phases. Data were analyzed using Wave 2.6.1 software (Agilent Technologies).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn vitro\u003c/em\u003e tumor cell killing assay\u003c/p\u003e\n\u003cp\u003eLiver tumor cells (1 \u003cimg width=\"10\" height=\"17\" src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1773388256.png\" alt=\"image\"\u003e 10\u003csup\u003e4\u003c/sup\u003e cells per well) were co-cultured with therapeutic cells (at ratios indicated in the figures or figure legends) in Corning 96-well clear bottom black plates for 24 h in C10 medium. D-luciferin (150 mg/ml, Caliper Life Science) was added to cell cultures to quantify live tumor cells and luciferase activities were read out using an Infinite M1000 microplate reader (Tecan). Live tumor cell numbers were normalized to the luminescence signal from tumor-only wells without therapeutic cells.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn vitro\u003c/em\u003e assays using primary HCC patient samples\u003c/p\u003e\n\u003cp\u003eIn one assay, the primary HCC patient samples were analyzed for the TME composition using flow cytometry. T cells were identified as CD45\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e+\u003c/sup\u003e cells, CD4 T cells were identified as CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8 T cells were identified as CD8\u003csup\u003e+\u003c/sup\u003e T cells, B cells were identified as CD45\u003csup\u003e+\u003c/sup\u003eCD19\u003csup\u003e+\u003c/sup\u003e or CD45\u003csup\u003e+\u003c/sup\u003eCD20\u003csup\u003e+\u003c/sup\u003e cells, NK cells were identified as CD45\u003csup\u003e+\u003c/sup\u003eCD56\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e-\u003c/sup\u003e cells, myeloid cells were identified as CD45\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e cells, TAMs were identified as HLA-DR\u003csup\u003ehigh\u003c/sup\u003eCD206\u003csup\u003ehigh\u003c/sup\u003e myeloid cells, MDSCs were identified as HLA-DR\u003csup\u003elow\u003c/sup\u003eCD206\u003csup\u003elow\u003c/sup\u003e myeloid cells\u003csup\u003e71,72\u003c/sup\u003e. Surface expression of CD1d on the immune cells were also analyzed using flow cytometry.\u003c/p\u003e\n\u003cp\u003eIn another assay, the primary HCC patient samples were used to study the TME cell killing by CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells under various conditions. Patient samples (containing 1 x 10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003ecells) were directly co-cultured with CAR-NKT or CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (1 x 10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003ecells), with or without the addition of \u0026alpha;GC (100 ng/ml), in C10 medium in Corning 96-well Round Bottom Cell Culture plates for 24 hours. At the end of culture, cells were collected, and the TME cell targeting by CAR-NKT or CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells was assessed using flow cytometry by quantifying live human myeloid cells (identified as NKT TCR\u003csup\u003e-\u003c/sup\u003eCD45\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e cells), T cells (identified as NKT TCR\u003csup\u003e-\u003c/sup\u003eCD45\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e+\u003c/sup\u003e cells), B cells (identified as NKT TCR\u003csup\u003e-\u003c/sup\u003eCD45\u003csup\u003e+\u003c/sup\u003eCD19\u003csup\u003e+\u003c/sup\u003e cells or NKT TCR\u003csup\u003e-\u003c/sup\u003eCD45\u003csup\u003e+\u003c/sup\u003eCD20\u003csup\u003e+\u003c/sup\u003e cells), and NK cells (identified as NKT TCR\u003csup\u003e-\u003c/sup\u003eCD45\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e-\u003c/sup\u003eCD56\u003csup\u003e+\u003c/sup\u003e cells). A total of 3 primary HCC patient samples were included in this assay.\u003c/p\u003e\n\u003cp\u003eWestern blotting analysis\u003c/p\u003e\n\u003cp\u003eWestern blot analysis was performed to assess CAR-dependent signaling pathways in CAR-NKT and CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells. Recombinant human CD19 protein (amino acids 20\u0026ndash;291), His-tagged (Acro Biosystems, cat. no. CD9-HP2H3), was pre-coated onto 24-well culture plates at 5 \u0026micro;g/ml for 1 hour at 37\u0026thinsp;\u0026deg;C. CD19-targeting CAR-NKT or CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells were then added and incubated for 15 minutes or 1 hour at 37\u0026thinsp;\u0026deg;C. Following stimulation, cells were immediately transferred to ice-cold PBS to terminate signaling and washed three times to remove residual antigen. Cells were subsequently lysed, and total protein extracts were collected for western blot analysis.\u003c/p\u003e\n\u003cp\u003eTotal proteins were extracted using a RIPA lysis buffer (Thermo Fisher Scientific) containing 20 mM HEPES (pH 7.6), 150 mM NaCl, 1 mM EDTA, 1% Tritonx-100, and protease/phosphatase inhibitor cocktail (Cell Signaling Technology). Protein concentration was measured using a Bicinchoninic Acid (BCA) Assay Kit (Thermo Fisher Scientific). Equal amounts of total protein were resolved on a 4\u0026ndash;15% Mini-PROTEAN\u0026reg; TGX\u0026trade; Precast Protein Gel (BIO-RAD) and then transferred to a polyvinylidene difluoride (PVDF) membrane by electrophoresis. The following antibodies were used to blot for the proteins of interest: anti-human p-CD3 zeta (Tyr 142) (Cell Signaling Technology, CST, cat. no. 67748), anti-human CD3 zeta (clone E8R1Q, CST, cat. no. 47434), anti-human p-ZAP70 (Tyr319) (clone 65E4, CST, cat. no. 2717), anti-human ZAP70 (clone D1C10E, CST, cat. no. 3165), anti-human p-PLC gamma 1 (Tyr783) (clone D6M95, CST, cat. no. 14008), anti-human PLC gamma 1 (clone D9H10, CST, cat. no. 5690), anti-human p-LAT (Tyr 161) (clone E9Q2R, CST, cat. no. 88077), anti-human LAT (clone E3U6J, CST, cat. no. 45533), anti-human p-c-Jun 1 (Ser73) (clone D47G9, CST, cat. no. 3270), anti-human c-Jun (clone 60A8, CST, cat. no. 9165), anti-human p-NF-kappaB p65 (Ser536) (clone 93H1, CST, cat. no. 3033), anti-human NF-kappaB p65 (clone D14E12, CST, cat. no. 8242), anti-human p-STAT5 (Tyr694) (clone D47E7, CST, cat. no. 4322), anti-human STAT5 (clone D2O6Y, CST, cat. no. 94205), and secondary anti-rabbit IgG (CST, cat. no. 7074). \u0026beta;-Actin (clone D6A8, CST, cat. no. 8457) was used as internal controls. Signals were visualized using a ChemiDoc\u003csup\u003e\u0026trade;\u003c/sup\u003e Imaging Systems (BIO-RAD). The data were analyzed using ImageJ (Version 1.53s).\u003c/p\u003e\n\u003cp\u003eSingle cell RNA sequencing (scRNA-seq)\u003c/p\u003e\n\u003cp\u003eCD19-targeting CAR-NKT or CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells were co-cultured with RAJI tumor cells at an effector-to-target (E:T) ratio of 1:5 for 72 hours. Following co-culture, viable CAR-NKT or CAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells were isolated by flow cytometry as NKT TCR⁺CD3⁺ cells and immediately submitted to the UCLA Technology Center for Genomics \u0026amp; Bioinformatics (TCGB) Core for library preparation and scRNA-seq. Cells were quantified using a Cell Countess II automated cell counter (Invitrogen/Thermo Fisher Scientific). A total of 20,000 cells from each experimental group were loaded on the Chromium platform (10X Genomics), and libraries were constructed using the Chromium Next GEM Single Cell 3\u0026rsquo; Kit v3.1 and the Chromium Next GEM Chip G Single Cell Kit (10X Genomics), according to the manufacturer\u0026rsquo;s instructions. Library quality was assessed using the D1000 ScreenTape on a 4200 TapeStation System (Agilent Technologies). Libraries were sequenced on an Illumina NovaSeq using the NovaSeq S4 Reagent Kit (100 cycles; Illumina).\u003c/p\u003e\n\u003cp\u003eFor cell clustering and annotation, the merged digital expression matrix generated by Cellranger was analyzed using an R package Seurat (v.4.0.0) following the guidelines\u003csup\u003e73\u0026ndash;75\u003c/sup\u003e.\u0026nbsp;Briefly, after filtering the low-quality cells, the expression matrix was normalized using NormalizeData function, followed by selecting variable features across datasets using FindVariableFeatures and SelectIntegrationFeatures functions. To correct the batch effect, FindIntegrrationAnchors and IntegrateData functions were used based on the selected feature genes. The corrected dataset was subjected to standard Seurat workflow for dimension reduction and clustering. In this study, clusters of therapeutic cells were manually merged and annotated based on gene signatures reported from Human Protein Atlas (proteinatlas.org) and previous studies\u003csup\u003e7,76\u0026ndash;83\u003c/sup\u003e. AddModuleScore was used to calculate module scores of each list of gene signatures, and FeaturePlot function was used to visualize the expression of each signature in the UMAP plots.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn vivo\u003c/em\u003e bioluminescence imaging (BLI)\u003c/p\u003e\n\u003cp\u003eBLI was performed using a Spectral Advanced Molecular Imaging HTX system (Spectral Instrument Imaging). Live animal images were captured 5 minutes after intraperitoneal (i.p.) injection of D-Luciferin (1 mg per 100\u0026nbsp;\u0026mu;L PBS per mouse) to obtain total body bioluminescence. The imaging data were analyzed using AURA imaging software (version 3.2.0, Spectral Instrument Imaging).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn vivo\u003c/em\u003e antitumor efficacy study of CAR19-NKT\u003csub\u003e(Mito)\u003c/sub\u003e cells: RAJI-FG human lymphoma xenograft NSG mouse model\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExperimental design is shown in Fig. 6a. Briefly,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eon Day 0,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNSG mice received i.v. inoculation of RAJI-FG human lymphoma cells (2 x 10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003ecells per mouse). On Day 7, the experimental mice received i.v. injection of Vehicle (100 \u0026mu;l PBS per mouse), human CAR19-NKT cells (1 x 10\u003csup\u003e7\u0026nbsp;\u003c/sup\u003ecells in 100 \u0026mu;l PBS per mouse), or human CAR19-NKT\u003csub\u003eMito\u003c/sub\u003e cells (1 x 10\u003csup\u003e7\u0026nbsp;\u003c/sup\u003ecells in 100 \u0026mu;l PBS per mouse). Over the experiment, mice were monitored for survival and their tumor loads were measured twice per week using BLI. At the end of the experiment, mice were euthanized, and their tissues were collected for analysis of therapeutic cell phenotypes and functions by flow cytometry or ELISA.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn vivo\u003c/em\u003e antitumor efficacy study of GCAR-NKT\u003csub\u003e(Mito)\u003c/sub\u003e cells: SKHEP1-FG human liver cancer xenograft NSG mouse model\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExperimental design is shown in Fig. 6e. Briefly,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eon Day 0,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNSG mice received i.v. inoculation of SKHEP1-FG human liver cancer cells (5 x 10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003ecells per mouse). On Day 4, the experimental mice received i.v. injection of Vehicle (100 \u0026mu;l PBS per mouse), human GCAR-NKT cells (1 x 10\u003csup\u003e7\u0026nbsp;\u003c/sup\u003ecells in 100 \u0026mu;l PBS per mouse), or human GCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (1 x 10\u003csup\u003e7\u0026nbsp;\u003c/sup\u003ecells in 100 \u0026mu;l PBS per mouse). Over the experiment, mice were monitored for survival and their tumor loads were measured twice per week using BLI. At the end of the experiment, mice were euthanized, and their tissues were collected for analysis of therapeutic cell phenotypes and functions by flow cytometry or ELISA.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn vivo\u003c/em\u003e antitumor efficacy study of MCAR-NKT\u003csub\u003e(Mito)\u003c/sub\u003e cells: OVCAR8-FG human ovarian cancer xenograft NSG mouse model\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExperimental design is shown in Fig. 6i. Briefly,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eon Day 0,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNSG mice received i.p. inoculation of OVCAR8-FG human ovarian cancer cells (5 x 10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003ecells per mouse). On Day 7, the experimental mice received i.v. injection of Vehicle (100 \u0026mu;l PBS per mouse), human MCAR-NKT cells (1 x 10\u003csup\u003e7\u0026nbsp;\u003c/sup\u003ecells in 100 \u0026mu;l PBS per mouse), or human MCAR-NKT\u003csub\u003eMito\u003c/sub\u003e cells (1 x 10\u003csup\u003e7\u0026nbsp;\u003c/sup\u003ecells in 100 \u0026mu;l PBS per mouse). Over the experiment, mice were monitored for survival and their tumor loads were measured twice per week using BLI. At the end of the experiment, mice were euthanized, and their tissues were collected for analysis of therapeutic cell phenotypes and functions by flow cytometry or ELISA.\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eStatistical data analysis was performed using GraphPad Prism 8 software (GraphPad). Student\u0026rsquo;s two-tailed t test was employed for pairwise comparisons. Ordinary one- or two-way ANOVA followed by Tukey\u0026rsquo;s or Dunnett\u0026rsquo;s multiple comparisons test was used for multiple comparisons. Log rank (Mantel-Cox) test adjusted for multiple comparisons was used for Meier survival curves analysis. Data are expressed as the mean \u0026plusmn;SEM, unless otherwise indicated. In all figures and figure legends, n denotes the number of samples or animals utilized in the indicated experiments. A p-value of less than 0.05 was considered significant; ns indicates not significant; *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the University of California, Los Angeles (UCLA) animal facility for providing animal support; the UCLA Translational Pathology Core Laboratory (TPCL) for providing histology support; the UCLA Technology Centre for Genomics \u0026amp; Bioinformatics (TCGB) facility for providing RNA-seq services; the UCLA CFAR Virology Core for providing human cells; the UCLA Broad Stem Cell Research Center (BSCRC) Flow Cytometry Core Facility for cell sorting support; and the Advanced Light Microscopy/Spectroscopy Laboratory, the Electron Imaging Center for NanoSystems, and the Nano and Pico Characterization Laboratory at the California NanoSystems Institute (CNSI) for supporting the image acquisition. This work was supported by a Partnering Opportunity for Discovery Stage Research Projects Award and a Partnering Opportunity for Translational Research Projects Awards from the California Institute for Regenerative Medicine (DISC2-11157, DISC2-13015, TRAN1-12250, and TRAN1-16050 to L.Y., DISC2-14169 to S.L.), a Department of Defense CDMRP PRCRP Impact Award (CA200456 to L.Y.), a Department of Defense Kidney Cancer Research Program Award (KC230215 to L.Y.), a UCLA BSCRC Innovation Award (to L.Y.), and an Ablon Scholars Award (to L.Y.), a UCLA Jonsson Comprehensive Cancer Center (JCCC) Seed Grant (to S.L. and L.Y.), a UCLA BSCRC Innovation Award (to S.L.), a grant from the National Institutes of Health (NIH) (GM143485, to S.L.). L.Y. is a member of UCLA Parker Institute for Cancer Immunotherapy (PICI). Y.-R.L. is a postdoctoral fellow supported by a UCLA MIMG M. John Pickett Post-Doctoral Fellow Award, a CIRM-BSCRC Postdoctoral Fellowship, a UCLA Sydney Finegold Postdoctoral Award, a UCLA Chancellor\u0026rsquo;s Award for Postdoctoral Research, and a UCLA Goodman-Luskin Microbiome Center Collaborative Research Fellowship Award. Y.Z. is a predoctoral fellow supported by a Whitcome Pre-Doctoral Fellowship in Molecular Biology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY-R.L., B.Z., S.W., and Y.Z. designed the experiments, analyzed the data, and wrote the manuscript. L.Y. and S.L. conceived and oversaw the study. Y-R.L. B.Z., S.W., and Y.Z. performed all experiments, with assistance from X.S., Z.S., Y.C., J.H., H.N., and Y.Y.. S.G. and V.G.A. provided the primary HCC patient samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDECLARATION OF INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL.Y. is a scientific advisor to AlzChem and Amberstone Biosciences, and a co-founder, stockholder, and advisory board member of Appia Bio. None of the declared companies contributed to or directed any of the research reported in this article. The remaining authors declare no competing interests. The authors S. Li, L. Yang, Y.-R. Li, B. Zhang, and S. Wang have filed a patent application related to this work through UCLA Technology Development Group (UCLA TDG), titled \u0026ldquo;Stem cell mitochondrial transfer to natural killer T cells\u0026rdquo;. The patent is currently under review.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data associated with this study are present in the paper or supplemental information. The genomics data generated during this study are available from the Gene Expression Omnibus database under accession numbers GEO: GSE318930 (Reviewer token: Token: crahqyuktdihzib). Any additional information required to reanalyze the data reported in this paper is available from the corresponding authors upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCourtney, A. N., Tian, G. \u0026amp; Metelitsa, L. S. Natural killer T cells and other innate-like T lymphocytes as emerging platforms for allogeneic cancer cell therapy. \u003cem\u003eBlood\u003c/em\u003e \u003cstrong\u003e141\u003c/strong\u003e, 869\u0026ndash;876 (2023).\u003c/li\u003e\n\u003cli\u003eBollino, D. \u0026amp; Webb, T. J. Chimeric antigen receptor-engineered natural killer and natural killer T cells for cancer immunotherapy. \u003cem\u003eTransl. Res.\u003c/em\u003e \u003cstrong\u003e187\u003c/strong\u003e, 32\u0026ndash;43 (2017).\u003c/li\u003e\n\u003cli\u003eRotolo, A. \u003cem\u003eet al.\u003c/em\u003e Enhanced Anti-lymphoma Activity of CAR19-iNKT Cells Underpinned by Dual CD19 and CD1d Targeting. \u003cem\u003eCancer Cell\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 596-610.e11 (2018).\u003c/li\u003e\n\u003cli\u003eHeczey, A. \u003cem\u003eet al.\u003c/em\u003e Anti-GD2 CAR-NKT cells in relapsed or refractory neuroblastoma: updated phase 1 trial interim results. \u003cem\u003eNat. Med.\u003c/em\u003e (2023) doi:10.1038/s41591-023-02363-y.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Allogeneic CD33-directed CAR-NKT cells for the treatment of bone marrow-resident myeloid malignancies. \u003cem\u003eNat. Commun.\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 1248 (2025).\u003c/li\u003e\n\u003cli\u003eZhou, X. \u003cem\u003eet al.\u003c/em\u003e CAR-redirected natural killer T cells demonstrate superior antitumor activity to CAR-T cells through multimodal CD1d-dependent mechanisms. \u003cem\u003eNat. cancer\u003c/em\u003e (2024) doi:10.1038/s43018-024-00830-0.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method. \u003cem\u003eNat. Biotechnol.\u003c/em\u003e (2024) doi:10.1038/s41587-024-02226-y.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Overcoming ovarian cancer resistance and evasion to CAR-T cell therapy by harnessing allogeneic CAR-NKT cells. \u003cem\u003eMed (New York, N.Y.)\u003c/em\u003e 100804 (2025) doi:10.1016/j.medj.2025.100804.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Engineering Allorejection-Resistant CAR-NKT Cells from Hematopoietic Stem Cells for Off-The-Shelf Cancer Immunotherapy. \u003cem\u003eMol. Ther.\u003c/em\u003e (2024) doi:10.1016/j.ymthe.2024.04.005.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Targeting triple-negative breast cancer using cord-blood CD34\u003csup\u003e+\u003c/sup\u003e HSPC-derived mesothelin-specific CAR-NKT cells with potent antitumor activity. \u003cem\u003eJ. Hematol. Oncol.\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 86 (2025).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Engineering optimal CAR constructs for allogeneic mesothelin-directed CAR-NKT cells in solid tumor immunotherapy. \u003cem\u003eBlood Immunol. Cell. Ther.\u003c/em\u003e 100025 (2025) doi:10.1016/j.bict.2025.100025.\u003c/li\u003e\n\u003cli\u003eBarrag\u0026aacute;n, G. A. \u003cem\u003eet al.\u003c/em\u003e IL-18 metabolically reprograms CAR-expressing natural killer T cells and enhances their antitumor activity against neuroblastoma. \u003cem\u003ebioRxiv\u003c/em\u003e 2025.04.18.649551 (2025) doi:10.1101/2025.04.18.649551.\u003c/li\u003e\n\u003cli\u003eLandoni, E. \u003cem\u003eet al.\u003c/em\u003e IL-12 reprograms CAR-expressing natural killer T cells to long-lived Th1-polarized cells with potent antitumor activity. \u003cem\u003eNat. Commun.\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 89 (2024).\u003c/li\u003e\n\u003cli\u003eDai, Z. \u003cem\u003eet al.\u003c/em\u003e Off-the-shelf invariant NKT cells expressing anti-PSCA CAR and IL-15 promote pancreatic cancer regression in mice. \u003cem\u003eJ. Clin. Invest.\u003c/em\u003e \u003cstrong\u003e135\u003c/strong\u003e, (2025).\u003c/li\u003e\n\u003cli\u003eLiu, D. \u003cem\u003eet al.\u003c/em\u003e IL-15 protects NKT cells from inhibition by tumor-associated macrophages and enhances antimetastatic activity. \u003cem\u003eJ. Clin. Invest.\u003c/em\u003e \u003cstrong\u003e122\u003c/strong\u003e, 2221\u0026ndash;2233 (2012).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Allogeneic stem cell-engineered EGFRvIII-specific CAR-NKT cells for treating glioblastoma with enhanced efficacy and safety. \u003cem\u003eMol. Ther.\u003c/em\u003e (2025) doi:10.1016/j.ymthe.2025.09.026.\u003c/li\u003e\n\u003cli\u003eLi, S. \u003cem\u003eet al.\u003c/em\u003e Engineering an in vivo charging station for CAR-redirected invariant natural killer T cells to enhance cancer therapy. \u003cem\u003eRes. Sq.\u003c/em\u003e (2025) doi:10.21203/rs.3.rs-6215345/v1.\u003c/li\u003e\n\u003cli\u003eBorcherding, N. \u0026amp; Brestoff, J. R. The power and potential of mitochondria transfer. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e623\u003c/strong\u003e, 283\u0026ndash;291 (2023).\u003c/li\u003e\n\u003cli\u003eHayakawa, K. \u003cem\u003eet al.\u003c/em\u003e Transfer of mitochondria from astrocytes to neurons after stroke. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e535\u003c/strong\u003e, 551\u0026ndash;555 (2016).\u003c/li\u003e\n\u003cli\u003eNorat, P. \u003cem\u003eet al.\u003c/em\u003e Intraarterial Transplantation of Mitochondria After Ischemic Stroke Reduces Cerebral Infarction. \u003cem\u003eStroke (Hoboken, N.J.)\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eBoudreau, L. H. \u003cem\u003eet al.\u003c/em\u003e Platelets release mitochondria serving as substrate for bactericidal group IIA-secreted phospholipase A2 to promote inflammation. \u003cem\u003eBlood\u003c/em\u003e \u003cstrong\u003e124\u003c/strong\u003e, 2173\u0026ndash;2183 (2014).\u003c/li\u003e\n\u003cli\u003eLevoux, J. \u003cem\u003eet al.\u003c/em\u003e Platelets Facilitate the Wound-Healing Capability of Mesenchymal Stem Cells by Mitochondrial Transfer and Metabolic Reprogramming. \u003cem\u003eCell Metab.\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 283-299.e9 (2021).\u003c/li\u003e\n\u003cli\u003eCourt, A. C. \u003cem\u003eet al.\u003c/em\u003e Mitochondrial transfer from MSCs to T cells induces Treg differentiation and restricts inflammatory response. \u003cem\u003eEMBO Rep.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, e48052 (2020).\u003c/li\u003e\n\u003cli\u003eWu, B. \u003cem\u003eet al.\u003c/em\u003e Mitochondrial aspartate regulates TNF biogenesis and autoimmune tissue inflammation. \u003cem\u003eNat. Immunol.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 1551\u0026ndash;1562 (2021).\u003c/li\u003e\n\u003cli\u003eGiwa, R. \u0026amp; Brestoff, J. R. Mitochondria Transfer to CD4(+) T Cells May Alleviate Rheumatoid Arthritis by Suppressing Pro-Inflammatory Cytokine Production. \u003cem\u003eImmunometabolism\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003cli\u003eSaha, T. \u003cem\u003eet al.\u003c/em\u003e Intercellular nanotubes mediate mitochondrial trafficking between cancer and immune cells. \u003cem\u003eNat. Nanotechnol.\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 98\u0026ndash;106 (2022).\u003c/li\u003e\n\u003cli\u003eIkeda, H. \u003cem\u003eet al.\u003c/em\u003e Immune evasion through mitochondrial transfer in the tumour microenvironment. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e638\u003c/strong\u003e, 225\u0026ndash;236 (2025).\u003c/li\u003e\n\u003cli\u003eXu, J. \u003cem\u003eet al.\u003c/em\u003e Mitochondrial transfer from glia to neurons protects against peripheral neuropathy. \u003cem\u003eNature\u003c/em\u003e (2026) doi:10.1038/s41586-025-09896-x.\u003c/li\u003e\n\u003cli\u003eBaldwin, J. G. \u003cem\u003eet al.\u003c/em\u003e Intercellular nanotube-mediated mitochondrial transfer enhances T cell metabolic fitness and antitumor efficacy. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e187\u003c/strong\u003e, 6614-6630.e21 (2024).\u003c/li\u003e\n\u003cli\u003eXu, X. \u003cem\u003eet al.\u003c/em\u003e Mitochondrial regulation in pluripotent stem cells. \u003cem\u003eCell Metab.\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 325\u0026ndash;332 (2013).\u003c/li\u003e\n\u003cli\u003eTiash, S., Brestoff, J. R. \u0026amp; Crewe, C. A guide to studying mitochondria transfer. \u003cem\u003eNat. Cell Biol.\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 1551\u0026ndash;1553 (2023).\u003c/li\u003e\n\u003cli\u003eLiu, Z., Sun, Y., Qi, Z., Cao, L. \u0026amp; Ding, S. Mitochondrial transfer/transplantation: an emerging therapeutic approach for multiple diseases. \u003cem\u003eCell Biosci.\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 66 (2022).\u003c/li\u003e\n\u003cli\u003eWeng, X. \u003cem\u003eet al.\u003c/em\u003e Mitochondrial metabolism is essential for invariant natural killer T cell development and function. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e \u003cstrong\u003e118\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003cli\u003eKumar, A. \u003cem\u003eet al.\u003c/em\u003e Enhanced oxidative phosphorylation in NKT cells is essential for their survival and function. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e \u003cstrong\u003e116\u003c/strong\u003e, 7439\u0026ndash;7448 (2019).\u003c/li\u003e\n\u003cli\u003eSivandzade, F., Bhalerao, A. \u0026amp; Cucullo, L. Analysis of the Mitochondrial Membrane Potential Using the Cationic JC-1 Dye as a Sensitive Fluorescent Probe. \u003cem\u003eBio-protocol\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, (2019).\u003c/li\u003e\n\u003cli\u003eChan, J. D. \u003cem\u003eet al.\u003c/em\u003e FOXO1 enhances CAR T cell stemness, metabolic fitness and efficacy. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e629\u003c/strong\u003e, 201\u0026ndash;210 (2024).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Multimodal targeting of metastatic renal cell carcinoma via CD70-directed allogeneic CAR-NKT cells. \u003cem\u003eCell reports. Med.\u003c/em\u003e 102321 (2025) doi:10.1016/j.xcrm.2025.102321.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Zhu, Y., Chen, Y. \u0026amp; Yang, L. The clinical landscape of CAR-engineered unconventional T cells. \u003cem\u003eTrends in cancer\u003c/em\u003e (2025) doi:10.1016/j.trecan.2025.03.001.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e An Ex Vivo 3D Tumor Microenvironment-Mimicry Culture to Study TAM Modulation of Cancer Immunotherapy. \u003cem\u003eCells\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Targeting Immunosuppressive Tumor-Associated Macrophages Using Innate T Cells for Enhanced Antitumor Reactivity. \u003cem\u003eCancers \u003c/em\u003e vol. 14 (2022).\u003c/li\u003e\n\u003cli\u003eRustom, A., Saffrich, R., Markovic, I., Walther, P. \u0026amp; Gerdes, H.-H. Nanotubular highways for intercellular organelle transport. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e303\u003c/strong\u003e, 1007\u0026ndash;1010 (2004).\u003c/li\u003e\n\u003cli\u003eCrewe, C. \u003cem\u003eet al.\u003c/em\u003e Extracellular vesicle-based interorgan transport of mitochondria from energetically stressed adipocytes. \u003cem\u003eCell Metab.\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 1853-1868.e11 (2021).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Zhou, K., Zhu, Y., Halladay, T. \u0026amp; Yang, L. Breaking the mold: Unconventional T cells in cancer therapy. \u003cem\u003eCancer Cell\u003c/em\u003e (2024) doi:10.1016/j.ccell.2024.11.010.\u003c/li\u003e\n\u003cli\u003eBae, E.-A., Seo, H., Kim, I.-K., Jeon, I. \u0026amp; Kang, C.-Y. Roles of NKT cells in cancer immunotherapy. \u003cem\u003eArch. Pharm. Res.\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 543\u0026ndash;548 (2019).\u003c/li\u003e\n\u003cli\u003eBendelac, A., Savage, P. B. \u0026amp; Teyton, L. The Biology of NKT Cells. \u003cem\u003eAnnu. Rev. Immunol.\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 297\u0026ndash;336 (2007).\u003c/li\u003e\n\u003cli\u003eRossjohn, J., Pellicci, D. G., Patel, O., Gapin, L. \u0026amp; Godfrey, D. I. Recognition of CD1d-restricted antigens by natural killer T cells. \u003cem\u003eNat. Rev. Immunol.\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 845\u0026ndash;857 (2012).\u003c/li\u003e\n\u003cli\u003eLee, M. S. \u0026amp; Webb, T. J. Novel lipid antigens for NKT cells in cancer. \u003cem\u003eFront. Immunol.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 1173375 (2023).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Chen, Y., Zhu, Y., Shen, X. \u0026amp; Yang, L. Abstract A021: Spatiotemporal gene profiling reveals distinct in vivo dynamics and immune checkpoint regulations of human CAR-T and CAR-NKT cells against solid tumors. \u003cem\u003eCancer Immunol. Res.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, A021\u0026ndash;A021 (2026).\u003c/li\u003e\n\u003cli\u003eLv, Z., Luo, F. \u0026amp; Chu, Y. Strategies for overcoming bottlenecks in allogeneic CAR-T cell therapy. \u003cem\u003eFront. Immunol.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 1199145 (2023).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Halladay, T. \u0026amp; Yang, L. Immune evasion in cell-based immunotherapy: unraveling challenges and novel strategies. \u003cem\u003eJ. Biomed. Sci.\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 5 (2024).\u003c/li\u003e\n\u003cli\u003eLabanieh, L., Majzner, R. G. \u0026amp; Mackall, C. L. Programming CAR-T cells to kill cancer. \u003cem\u003eNat. Biomed. Eng.\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 377\u0026ndash;391 (2018).\u003c/li\u003e\n\u003cli\u003eJohnson, A., Townsend, M. \u0026amp; O\u0026rsquo;Neill, K. Tumor Microenvironment Immunosuppression: A Roadblock to CAR T-Cell Advancement in Solid Tumors. \u003cem\u003eCells\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003cli\u003eLyu, Z. \u003cem\u003eet al.\u003c/em\u003e Addressing graft-versus-host disease in allogeneic cell-based immunotherapy for cancer. \u003cem\u003eExp. Hematol. Oncol.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 66 (2025).\u003c/li\u003e\n\u003cli\u003ePillai, A. B., George, T. I., Dutt, S., Teo, P. \u0026amp; Strober, S. Host NKT Cells Can Prevent Graft-versus-Host Disease and Permit Graft Antitumor Activity after Bone Marrow Transplantation. \u003cem\u003eJ. Immunol.\u003c/em\u003e \u003cstrong\u003e178\u003c/strong\u003e, 6242\u0026ndash;6251 (2007).\u003c/li\u003e\n\u003cli\u003eHaraguchi, K. \u003cem\u003eet al.\u003c/em\u003e Recovery of V\u0026alpha;24+ NKT cells after hematopoietic stem cell transplantation. \u003cem\u003eBone Marrow Transplant.\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 595\u0026ndash;602 (2004).\u003c/li\u003e\n\u003cli\u003eRamos, C. A. \u003cem\u003eet al.\u003c/em\u003e Allogeneic NKT Cells Expressing a CD19-Specific CAR in Patients with Relapsed or Refractory B-Cell Malignancies: An Interim Analysis. \u003cem\u003eBlood\u003c/em\u003e \u003cstrong\u003e138\u003c/strong\u003e, 2819 (2021).\u003c/li\u003e\n\u003cli\u003eRen, H. \u003cem\u003eet al.\u003c/em\u003e Off-the-shelf dual CAR-iNKT cell immunotherapy eradicates medullary and leptomeningeal high-risk KMT2A-rearranged leukemia. \u003cem\u003eBlood\u003c/em\u003e blood.2025029302 (2025) doi:10.1182/blood.2025029302.\u003c/li\u003e\n\u003cli\u003eRamos, C. A. \u003cem\u003eet al.\u003c/em\u003e Off-the-Shelf CD19-Specific CAR-NKT Cells in Patients with Relapsed or Refractory B-Cell Malignancies. \u003cem\u003eTransplant. Cell. Ther.\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, S41\u0026ndash;S42 (2024).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Targeting orthotopic and metastatic pancreatic cancer with allogeneic stem cell-engineered mesothelin-redirected CAR-NKT cells. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e \u003cstrong\u003e122\u003c/strong\u003e, e2517786122 (2025).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Zhu, Y. \u0026amp; Yang, L. IL-15 in CAR engineering: striking an efficacy-safety balance. \u003cem\u003eTrends Mol. Med.\u003c/em\u003e (2025) doi:10.1016/j.molmed.2025.05.014.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Zhu, Y. \u0026amp; Yang, L. IL-18 revives dysfunctional CAR-T cells. \u003cem\u003eTrends in cancer\u003c/em\u003e (2025) doi:10.1016/j.trecan.2025.06.008.\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Wilson, M. \u0026amp; Yang, L. Target tumor microenvironment by innate T cells. \u003cem\u003eFront. Immunol.\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 999549 (2022).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R., Fang, Y., Lyu, Z., Zhu, Y. \u0026amp; Yang, L. Exploring the dynamic interplay between cancer stem cells and the tumor microenvironment: implications for novel therapeutic strategies. \u003cem\u003eJ. Transl. Med.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 686 (2023).\u003c/li\u003e\n\u003cli\u003eMajzner, R. G. \u0026amp; Mackall, C. L. Clinical lessons learned from the first leg of the CAR T cell journey. \u003cem\u003eNat. Med.\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 1341\u0026ndash;1355 (2019).\u003c/li\u003e\n\u003cli\u003eLemoine, J., Ruella, M. \u0026amp; Houot, R. Born to survive: how cancer cells resist CAR T cell therapy. \u003cem\u003eJ. Hematol. Oncol.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 1\u0026ndash;12 (2021).\u003c/li\u003e\n\u003cli\u003eZhu, Y. \u003cem\u003eet al.\u003c/em\u003e Development of Hematopoietic Stem Cell-Engineered Invariant Natural Killer T Cell Therapy for Cancer. \u003cem\u003eCell Stem Cell\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 542-557.e9 (2019).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Development of allogeneic HSC-engineered iNKT cells for off-the-shelf cancer immunotherapy. \u003cem\u003eCell reports. Med.\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 100449 (2021).\u003c/li\u003e\n\u003cli\u003eHazim, R. A. \u003cem\u003eet al.\u003c/em\u003e Differentiation of RPE cells from integration-free iPS cells and their cell biological characterization. \u003cem\u003eStem Cell Res. Ther.\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 217 (2017).\u003c/li\u003e\n\u003cli\u003eLowry, W. E. \u003cem\u003eet al.\u003c/em\u003e Generation of human induced pluripotent stem cells from dermal fibroblasts. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e \u003cstrong\u003e105\u003c/strong\u003e, 2883\u0026ndash;2888 (2008).\u003c/li\u003e\n\u003cli\u003eKarumbayaram, S. \u003cem\u003eet al.\u003c/em\u003e Directed differentiation of human-induced pluripotent stem cells generates active motor neurons. \u003cem\u003eStem Cells\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 806\u0026ndash;811 (2009).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Profiling ovarian cancer tumor and microenvironment during disease progression for cell-based immunotherapy design. \u003cem\u003eiScience\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 107952 (2023).\u003c/li\u003e\n\u003cli\u003eLi, Y.-R. \u003cem\u003eet al.\u003c/em\u003e Protocol to profile tumor and microenvironment from ovarian cancer patient samples and evaluate cell-based therapy using in vitro killing assays. \u003cem\u003eSTAR Protoc.\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 103742 (2025).\u003c/li\u003e\n\u003cli\u003eButler, A., Hoffman, P., Smibert, P., Papalexi, E. \u0026amp; Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. \u003cem\u003eNat. Biotechnol.\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 411\u0026ndash;420 (2018).\u003c/li\u003e\n\u003cli\u003eTran, H. T. N. \u003cem\u003eet al.\u003c/em\u003e A benchmark of batch-effect correction methods for single-cell RNA sequencing data. \u003cem\u003eGenome Biol.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 12 (2020).\u003c/li\u003e\n\u003cli\u003eJia, C. \u003cem\u003eet al.\u003c/em\u003e Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 10978\u0026ndash;10988 (2017).\u003c/li\u003e\n\u003cli\u003eMiller, B. C. \u003cem\u003eet al.\u003c/em\u003e Subsets of exhausted CD8(+) T cells differentially mediate tumor control and respond to checkpoint blockade. \u003cem\u003eNat. Immunol.\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 326\u0026ndash;336 (2019).\u003c/li\u003e\n\u003cli\u003eZheng, L. \u003cem\u003eet al.\u003c/em\u003e Pan-cancer single-cell landscape of tumor-infiltrating T cells. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e374\u003c/strong\u003e, abe6474 (2021).\u003c/li\u003e\n\u003cli\u003eLi, H. \u003cem\u003eet al.\u003c/em\u003e Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e176\u003c/strong\u003e, 775-789.e18 (2019).\u003c/li\u003e\n\u003cli\u003eMilner, J. J. \u003cem\u003eet al.\u003c/em\u003e Heterogenous Populations of Tissue-Resident CD8(+) T Cells Are Generated in Response to Infection and Malignancy. \u003cem\u003eImmunity\u003c/em\u003e \u003cstrong\u003e52\u003c/strong\u003e, 808-824.e7 (2020).\u003c/li\u003e\n\u003cli\u003eBeltra, J.-C. \u003cem\u003eet al.\u003c/em\u003e Developmental Relationships of Four Exhausted CD8(+) T Cell Subsets Reveals Underlying Transcriptional and Epigenetic Landscape Control Mechanisms. \u003cem\u003eImmunity\u003c/em\u003e \u003cstrong\u003e52\u003c/strong\u003e, 825-841.e8 (2020).\u003c/li\u003e\n\u003cli\u003eZheng, C. \u003cem\u003eet al.\u003c/em\u003e Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e169\u003c/strong\u003e, 1342-1356.e16 (2017).\u003c/li\u003e\n\u003cli\u003eWang, X., Peticone, C., Kotsopoulou, E., G\u0026ouml;ttgens, B. \u0026amp; Calero-Nieto, F. J. Single-cell transcriptome analysis of CAR T-cell products reveals subpopulations, stimulation, and exhaustion signatures. \u003cem\u003eOncoimmunology\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 1866287 (2021).\u003c/li\u003e\n\u003cli\u003eBai, Z. \u003cem\u003eet al.\u003c/em\u003e Single-cell antigen-specific landscape of CAR T infusion product identifies determinants of CD19-positive relapse in patients with ALL. \u003cem\u003eSci. Adv.\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, eabj2820 (2022).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chimeric antigen receptor (CAR), invariant natural killer T (NKT) cell, cancer immunotherapy, mitochondrial transfer, iPSC, mitochondrial activity, organelle-level metabolic reprogramming strategy, metabolic fitness, tumor microenvironment (TME), antitumor efficacy","lastPublishedDoi":"10.21203/rs.3.rs-8953703/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8953703/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Chimeric antigen receptor–engineered natural killer T (CAR-NKT) cells have emerged as a promising cancer immunotherapy owing to their potent antitumor activity, efficient tissue homing, and capacity to remodel the immunosuppressive tumor microenvironment (TME). Although strategies such as cytokine engineering and checkpoint blockade have improved CAR-NKT cell function, approaches that enhance their metabolic fitness remain limited. Here, we rejuvenate CAR-NKT cell metabolism and antitumor activity through induced pluripotent stem cell–derived mitochondrial transfer (iPSC-MT). iPSC-MT markedly enhances mitochondrial activity and metabolic fitness in CAR-NKT cells, resulting in improved effector function, memory formation, and persistence while limiting exhaustion. CAR-NKT cells enhanced by iPSC-MT (CAR-NKTMito) exhibit superior cytotoxicity in vitro and robust antitumor efficacy in vivo across multiple xenograft mouse models, including human lymphoma, liver cancer, and ovarian cancer. Notably, CAR-NKTMito cells exhibit enhanced TME modulation through effective targeting of CD1d⁺ myeloid cells, outperforming conventional iPSC-MT-enhanced CAR-T cells. Together, these findings establish mitochondrial transfer as a powerful organelle-level metabolic reprogramming strategy to enhance CAR-NKT cell function and provide a new therapeutic paradigm for improving cellular immunotherapy against cancer.","manuscriptTitle":"Stem cell mitochondrial transfer rejuvenates CAR-NKT cell metabolism and antitumor activity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 07:56:52","doi":"10.21203/rs.3.rs-8953703/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"562bf2b0-fb6a-40d8-be39-8527fc698b09","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63424940,"name":"Biological sciences/Biotechnology/Metabolic engineering"},{"id":63424941,"name":"Biological sciences/Cancer/Cancer therapy"}],"tags":[],"updatedAt":"2026-04-03T13:05:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 07:56:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8953703","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8953703","identity":"rs-8953703","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}