Graphical abstract graphic file with name fx1.jpg [59]Open in a new tab Highlights * • XCL1 expression is positively correlated with CD8^+ Tpex signature and patient response to ICB * • FX engineering remodels the immune landscape of the tumor microenvironment * • FX-armed T cells induce potent antigen spreading and control of antigenic heterogeneous tumor * • FX-armed CAR-T cells exhibit superior anti-tumor activity in murine and humanized mouse models __________________________________________________________________ Xiao et al. demonstrate that FX-engineered (Flt3L and XCL1) T cells facilitate the interaction with cross-presenting dendritic cells, promote robust antigen spreading, and induce endogenous T cell clonal expansion. This strategy demonstrates superior control of tumors with pre-existing antigenic heterogeneity in both murine and humanized mouse models. Introduction Adoptive cell therapy (ACT) has revolutionized cancer treatment, with chimeric antigen receptor (CAR)-T cells achieving remarkable success in B cell malignancies. However, their efficacy in solid tumors remains limited due to poor tumor infiltration, reduced functionality and persistence, antigen heterogeneity, and the immunosuppressive tumor microenvironment (TME).[60]^1^,[61]^2 For instance, clinical trials targeting EGFRvIII in glioblastoma[62]^3 and CD19 in leukemia[63]^4 have shown tumor escape through antigen loss, highlighting the need for strategies to overcome antigen escape. T cell receptor (TCR)-engineered T cells (TCR-T) and tumor-infiltrating lymphocyte (TIL) therapy have shown promise in solid tumors.[64]^5^,[65]^6^,[66]^7^,[67]^8 Unlike CAR-T cells, TILs or TCR-T cells are broadly activated by dendritic cell (DC) in lymph nodes (LNs) and even within the TME,[68]^2^,[69]^9^,[70]^10^,[71]^11^,[72]^12 emphasizing the importance of DC-T cell interactions. TILs’ polyclonal nature also enables broader antigen recognition, offering a potential advantage.[73]^13 Drawing insights from these therapies, strategies to harness DCs may improve the efficacy of CAR-T therapy against solid tumors. Indeed, enhancing CAR-T-DC interactions, as seen with platforms like Amph-vax, can promote CAR-T persistence and function.[74]^14 Recently, an elegant study demonstrated that the formation of a three-cell cluster (triad) consisting of DCs, CD4^+ T cells, and CD8^+ T cells is required for optimal CD8^+ T cell cytotoxicity and cancer cell elimination.[75]^15 However, DC paucity and dysfunctional states can greatly limit anti-tumor responses. Conventional type 1 dendritic cells (cDC1s) are specialized for antigen cross-presentation and T cell priming.[76]^10^,[77]^16 Anti-tumor responses of endogenous T cells often involve antigen spreading (AS), where immune responses broaden to target additional tumor antigens, which are critical for durable efficacy.[78]^17 Accumulating evidence suggests that AS significantly contributes to the overall therapeutic outcomes of cancer therapies,[79]^17 emphasizing the importance of manipulating DCs to potentiate polyclonal T cell response. While CAR-T cells armed with molecules like D40L,[80]^18 Flt3L,[81]^19 and interleukin (IL)-7/CCL19[82]^20 and Amph-vax vaccine[83]^17 have been shown to enhance AS in preclinical models, many studies focus only on DC quantity or function, not both, and are limited to immunodeficient models. Here, we show that progenitor exhausted CD8^+ T (Tpex) cells exhibit high expression of XCL1, correlating with favored prognosis. Given the critical role of the XCL1-XCR1 axis in recruiting cDC1s[84]^21^,[85]^22 and that Flt3L promotes DC development,[86]^23 we engineered T cells to overexpress Flt3L and XCL1. We demonstrated that these engineered T cells fostered potent AS, reshaped the intratumoral immune landscape, and suppressed antigenically heterogeneous tumors. Importantly, we validated the therapeutic efficacy of CAR-T cell-induced AS in a preclinical setting using a Flt3KO&hFLT3LG humanized mouse model. These findings provide compelling evidence of the feasibility and effectiveness of this optimized CAR-T cell therapy for treating solid tumors. Results XCL1 expression positively correlates with CD8^+ Tpex signature in both mouse and human tumors To explore the transcriptional profiles of antigen-specific CD8^+ T cell subsets across species, we analyzed publicly available single-cell RNA sequencing (scRNA-seq) datasets of tumors initiated by intratracheal instillation of lentivirus containing LucOS and Cre recombinase in Kras^LSL−G12D/+; p53^fl/fl mice containing SIINFEKL (SIIN) and SIYRYYGL (SIY) antigens ([87]Figure 1A),[88]^24 referencing the “ProjectTILs” T cell atlases.[89]^25 SIIN-specific T cells were categorized into five subpopulations, including Tpex and terminally exhausted T cells (Tex) ([90]Figures 1B and [91]S1A). Tpex cells exhibited higher expression of Xcl1 and Tcf7, while Tex cells expressed the exhaustion-related genes Tox and Havcr2 ([92]Figures 1B–1D), consistent with earlier reports.[93]^25 A similar pattern was observed in SIY-specific CD8^+ T cells ([94]Figures S1B–S1D). We next assessed whether this pattern holds in human cancers by examining human papillomavirus (HPV)-specific CD8^+ T cells in head and neck cancer.[95]^26 Consistent with findings in mouse models, human stem-like T cells displayed elevated expression of XCL1, TCF7, IL7R, CCR7, and SLAMF6 compared to terminally differentiated (TD) or exhausted T cells (Tex) ([96]Figures S1E and S1F). Figure 1. [97]Figure 1 [98]Open in a new tab XCL1 expression positively correlates with CD8^+ Tpex signature and patient survival (A) Schematic of the lung adenocarcinoma model from previous report. Created with BioRender.com. (B) Uniform manifold approximation and projection (UMAP) of unsupervised clustering of SIIN-specific CD8^+ T cells. (C) Single-cell expression of marker genes associated with Tpex or Tex cell. (D) Normalized average gene expression signature of query cells and reference cells. (E) Schematic of Tcf7-DTR-GFP OT-I cells in B16-OVA model, created with BioRender.com. (F) RT-qPCR results showing the expression of Xcl1 in transferred OT-I cells. (G) XCL1 expression comparison between TCF1^+ and TCF1^− OT-I cells within the tdLNs, as well as between Tpex (GFP^+TIM3^−) and Tex (GFP^−TIM3^+) OT-I cells in tumors. (H) Immunofluorescence staining of XCL1 expression on TCF1^+ CD8^+ T cells within B16-OVA tumor (scale bars, 10 μm). (I) T differentiation trajectory of single-cell transcriptomes projected by Monocle3, starting from the naive cell cluster. (J) RNA velocity analysis of single-cell transcriptomes with scTour. (K) Kaplan-Meier curve illustrating overall survival in the TCGA melanoma cohort. (L) Kaplan-Meier curve illustrating overall survival in patients with ICB therapy. (M) Enrichment of the human XCL1 and TCF7 expression on CD8^+ T cell in patients responding or non-responding to ICB therapy. All data represent the mean ± SEM and were analyzed by Student’s t test for (F) or pair Student’s t test for (G) or the Wilcoxon signed-rank test for (M). Statistical difference is delineated by ^∗p < 0.01, ∗∗p < 0.01, and ^∗∗∗∗p < 0.0001. To experimentally validate this, we transferred naive TCF1^+(GFP^+) OT-I cells isolated from Tcf7-DTR-GFP OT-I reporter mice into ovalbumin[257-264] (OVA)-expressing B16 (B16-OVA) tumor-bearing mice. Two weeks later, we isolated distinct T cell subpopulations from B16-OVA tumors and performed quantitative reverse-transcription PCR (RT-qPCR). Tpex (GFP^+TIM3^−) cells expressed higher levels of Xcl1 and Tcf7 compared to Tex (GFP^−TIM3^+) cells ([99]Figures 1E, 1F, and [100]S1G). Additionally, GFP^+CD8^+ T cells in the tumor-draining lymph nodes (tdLNs) also showed 2-fold higher XCL1 expression than GFP^− counterparts ([101]Figure 1G), and confocal microscopy confirmed co-localization of TCF1 (GFP^+) and XCL1 within tumor-infiltrating CD8^+ T cells ([102]Figure 1H). These findings together suggest that XCL1 expression may play a potential role in preserving CD8^+ Tpex cell and that the XCL1-XCR1 axis is a potential therapeutic target. Trajectory and RNA velocity analysis[103]^27 using the scRNA-seq dataset[104]^28 showed that Xcl1^+ T cells expressed progenitor-associated genes such as Klf2, Id3, and Tcf7, while late effector cells showed increased expression of effector-associated genes GzmB and Ezh2, indicating that Xcl1^+ T cells occupy an early differentiation stage ([105]Figures 1I, 1J, [106]S1H, and S1I). These observations also reinforce the notion that XCL1^+CD8^+ T cells may represent a distinct Tpex population.[107]^25^,[108]^29 XCL1 expression correlates positively with cancer patient survival and response to ICB therapy Given the established association between Tpex cells in both the tumor and tdLNs and favorable responses to immune checkpoint blockade (ICB),[109]^30 we evaluated whether the XCL1 signature correlates with patient prognosis. Analysis of the XCL1 signature in The Cancer Genome Atlas (TCGA) melanoma dataset revealed that higher XCL1 expression is associated with improved overall survival ([110]Figure S1J). To assess the prognostic value of the XCL1 signature specifically within CD8^+ T cells, we accounted for potential confounding from natural killer (NK) cells, which are known to express high levels of XCL1.[111]^22 Utilizing publicly available scRNA-seq datasets,[112]^30^,[113]^31 we found NCAM1 as a specific marker for human NK cells ([114]Figure S1K). Thus, we constructed a Cox proportional hazards model: logh(t) = logh_0 (t)+ β_1⋅XCL1+ β_2⋅CD8B+ β_3⋅(XCL1 × CD8B)+ β_4⋅NCAM1. In this model, survival risk is predicted based on the expression levels of XCL1, CD8B, and NCAM1, with an interaction term capturing the synergistic effect of XCL1 and CD8B abundance. Our analysis suggested minimal NK cell contribution to survival prediction ([115]Table S1). To further evaluate gene interactions, we multiplied gene expression values and found that the XCL1∗CD8B^hi signature was associated with improved survival in cancers such as skin cutaneous melanoma and uterine corpus endometrial carcinoma ([116]Figures 1K and [117]S1L), though bulk RNA-seq data have inherent limitations. Integration of ICB survival cohorts ([118]GSE78220 and PRJEB23709) confirmed that higher XCL1 expression in tumor-infiltrating CD45^+ cells is linked to better outcomes ([119]Figure 1L). scRNA-seq data ([120]GSE235863 ) showed that XCL1 expression in CD8^+ T cell correlates with improved ICB response ([121]Figure 1M). Given that XCL1 recruits cDC1s, and DCs support TCF1^+Ly108^+ T cells in tdLNs,[122]^32^,[123]^33^,[124]^34 we proposed that XCL1^+ Tpex cells may recruit XCR1^+ cDC1s through the XCL1-XCR1 axis to sustain self-renewal, promote effector differentiation, and initiate the de novo priming of polyclonal T cells, thereby contributing to durable tumor control. XCL1 remodels the landscape of the immunosuppressive TME and enhances tumor control To elucidate the role of XCL1 in tumor progression, we engineered B16F10 melanoma and MC38 colorectal cancer cells to stably express XCL1 ([125]Figures S2A–S2C). In vitro chemotaxis assays using iCD103 DCs[126]^35 and splenic cDC1s showed that XCL1-expressing tumor cells effectively recruited XCR1^+ DCs ([127]Figures S2D–S2F). In xenograft models, XCL1 expression significantly inhibited tumor growth of B16F10 and MC38 model ([128]Figures 2A–2D, [129]S2G, and S2H), increased infiltration of CD3^+, CD4^+ and CD8^+ T cells, and reduced frequency of tumor-associated macrophages (TAMs) ([130]Figures 2E, 2F, and [131]S2I). XCL1 also promoted substantial recruitment of DCs, especially cDC1s ([132]Figures 2G and 2H), supporting its role in promoting immune cell infiltration. We next evaluated the immune phenotype of intratumoral DCs, given that the TME can induce tolerogenic states in DCs. In tumors expressing XCL1, DCs exhibited elevated co-stimulatory molecules (CD40, CD80, and major histocompatibility complex [MHC] class II) and IL-12, without significant changes in immunoregulatory markers such as CD63[133]^36 and programmed death-ligand 1 (PD-L1) ([134]Figures 2I–2L and [135]S2J), suggesting a shift toward an immunostimulatory phenotype. Figure 2. [136]Figure 2 [137]Open in a new tab XCL1 remodels the landscape of the immunosuppressive TME and enhances tumor control (A and B) Average tumor growth curves (A) and tumor weight (B) of the B16F10 model (n = 7–8 mice). (C and D) Average tumor growth curves (C) and tumor weight (D) of the MC38 model. (E and F) Representative plots (E) and absolute number (F) of CD3^+ T, CD8^+ T, CD4^+ T, and TAM cells from [138]Figure 2A. (G and H) Representative plots and absolute number of total DCs (G) and cDC1s (H) from [139]Figure 2A. (I and J) Representative plots of mean fluorescence intensity of CD40 and CD80 (I) and statistical analysis (J). (K) Mean fluorescence intensity (MFI) of MHC class II in intratumoral DCs (n = 11–12). (L) Frequence of IL-12^+ DCs (left) and CD63^+ DCs (right) in tumors (n = 11–12). (M) Average tumor growth curves of B16F10 tumor-bearing Rag1^−/− mice. (N) Frequency of individual TCR Vβ clonotypes in [140]Figure 2A from endogenous CD8^+ T cells. (O) Imaging of CD11c^+ cells and CD8^+ cells in MC38 tumor (scale bars, 100 μm). All data represent the mean ± SEM and were analyzed by Student’s t test for (B), (D), (F)–(H), and (J)–(N) or two-way ANOVA with Tukey’s multiple-comparison test for (A), (C), and (M). Statistical difference is delineated by ns, not significant, ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗∗p < 0.0001. Given that DCs have the superior ability to initiate CD8^+ T cell immune response in the tdLNs, and that the therapeutic efficacy of XCL1 was also dependent on host T cells ([141]Figure 2M), we optimized a flow cytometry-based TCR Vβ screening system to assess CD8^+ T cell clonal diversity in the tdLNs ([142]Figures S3A and S3B), which revealed a significant expansion in the frequencies of various Vβ clonotypes ([143]Figure 2N), consistent with increased CD8^+ T cells in tdLNs ([144]Figure S2K), indicating oligoclonal expansion. To determine whether XCL1-mediated effects depend on cDC1s, we utilized a Batf3^−/− mouse model that lacks cDC1s.[145]^37 In both tumor models, XCL1’s anti-tumor effects were abolished in Batf3^−/− mice ([146]Figures S2L and S2M), with a reduced proportion in PD1^+CD39^+CD8^+ T cells ([147]Figure S2L), indicating impaired antigen-specific responses.[148]^38 These findings underscore the requirement of cDC1 and polyclonal T cell for XCL1-mediated tumor control. Beyond increasing DC numbers, spatial proximity to T cells is crucial for anti-tumor responses. Spatial profiling revealed that XCL1 facilitated the infiltration and co-localization of both DCs and CD8^+ T cells in tumors ([149]Figure 2O), further supporting its role in reshaping immune landscape of the TME and enhancing tumor control. XCL1-engineered T cells enhance T cell expansion and tumor suppression in a cDC1-dependent manner Next, to apply our findings in an ACT setting, we engineered OT-I cells to secrete XCL1 (OT-I/XCL1) via retroviral transduction and determined their effectiveness against solid tumors ([150]Figures S4A and S4B). OT-I/XCL1 cells attracted significantly more XCR1^+ cDC1s in vitro ([151]Figure S4C). In a CpG and OVA peptide immunization model, the frequencies of XCL1-expressing OT-I cells significantly increased in both spleen and LNs ([152]Figures 3A and 3B). Figure 3. [153]Figure 3 [154]Open in a new tab XCL1-engineered T cells elicit tumor suppression in a cDC1-dependent manner (A) Schematic of immunization with CpG plus OVA peptide. (B) Frequencies of OT-I in spleen and LNs. (C) Schematic of the mouse tumor model (n = 6–8 mice). (D–G) Average tumor growth curves of B16-OVA (D) and MC38-OVA (E). Individual tumor growth curves of B16-OVA (F) and MC38-OVA (G). (H) Absolute number of OT-I cells and host CD8^+ T cells in B16-OVA tumors. (I) Frequencies of IFNγ^+ in OT-I cells and host CD8^+ T cells. (J) Representative plots and frequencies of TCF1^+CD8^+ T cells in intratumoral OT-I cells. (K) Schematic of the tumor model of wild-type (WT) and Batf3^−/− mice (n = 5–7 mice). (L and M) Average tumor growth curves of B16-OVA (L) or MC38-OVA (M). All data represent the mean ± SEM and were analyzed by Student’s t test for (B) and (H)–(J) or two-way ANOVA with Tukey’s multiple-comparisons test for (D), (E), (L), and (M). Statistical difference is delineated by ^∗p < 0.05 and ^∗∗p < 0.01. We then tested the anti-tumor activity of OT-I/XCL1 in MC38-OVA and B16-OVA models. To optimize ACT efficacy, lymphodepletion is required, but sublethal total body irradiation can impair cDC1-mediated immunity. To address this, we evaluated the impact of varying irradiation doses on immune cell populations and found that a 2 Gy dose best preserved host CD8^+ T cells and cDC1s while supporting transferred T cell survival ([155]Figures S5A–S5H), which are essential for mobilizing endogenous immune response. Consequently, the suboptimal lymphodepletion dose of 2 Gy was employed in further experiments in this study. At this dose, adoptive transfer of OT-I/XCL1 cells significantly inhibited B16-OVA tumors and showed similar effects in MC38-OVA tumors ([156]Figures 3C–3G and [157]S4G). Compared to control OT-I, OT-I/XCL1 treatment significantly promoted the intratumoral infiltration of both transferred and endogenous CD8^+ T cells ([158]Figures 3H and [159]S4H) and elevated the proportion of interferon gamma (IFNγ^+) T cells ([160]Figure 3I). Additionally, OT-I/XCL1 treatment significantly enhanced TCF1 expression in the adoptively transferred T cells ([161]Figure 3J). In Batf3^−/− mice models, OT-I/XCL1-mediated tumor suppression was absent, emphasizing the essential role of endogenous cDC1s in the anti-tumor effects of XCL1 ([162]Figures 3K–3M, [163]S4I, and S4J). These results demonstrate that XCL1-engineered T cells potently enhance anti-tumor immunity in a cDC1-dependent manner. XCL1 expression enhances the quantity and functionality of intratumoral DCs The quantity and quality of DCs are pivotal for effective tumor immunotherapy.[164]^9 Following adoptive transfer of OT-I/XCL1 cells, we observed that, while the frequency of tumor-infiltrating DCs remained unchanged, the absolute number of intratumoral DCs was significantly increased, including both CD103^+ cDC1 and CD11b^+ cDC2 cells ([165]Figures 4A–4D). Given that IRF8, crucial for cDC1 development,[166]^39 can be inhibited by PGE2 in the TME,[167]^22^,[168]^40 we also focused on a CD103^−CD11b^−XCR1^+IRF8^+ DC population that is characterized as cDC1 precursors and found that OT-I/XCL1 treatment obviously increased the number of these cells in the tumors ([169]Figures 4C and 4D). The immunogenic function of DCs is essential for the efficacy of tumor immunotherapy. Next, we assessed DC activation and functionality within the tumor and observed significant upregulation of co-stimulatory molecules, including CD40, CD80, and CD86, in intratumoral DCs following OT-I/XCL1 treatment. Additionally, there was a notable decrease in the immunoregulatory molecule CD63 ([170]Figures 4E–4G).[171]^36 Importantly, OT-I/XCL1 treatment significantly enhanced the production of IL-12 and tumor necrosis factor alpha (TNF-α) by intratumoral DCs ([172]Figure 4G). We also observed significant secretion of CXCL9 ([173]Figure 4H), a key chemokine for T cell trafficking.[174]^41 Simultaneously, we also analyzed changes in the host CD8^+ TCR repertoire using TCR Vβ screening, which revealed a significant expansion in the frequency of various Vβ clonotypes within the tdLNs following OT-I/XCL1 treatment ([175]Figures 4I and 4J). Collectively, these findings indicate that the XCL1-engineered T cells boost both the quantity and functionality of host DCs, enhancing priming of endogenous T cells. Figure 4. [176]Figure 4 [177]Open in a new tab XCL1 expression enhances the quantity and functionality of intratumoral DCs (A–D) Experimental setting follows the same conditions described in [178]Figure 3C. Representative flow cytometry plots (A) and frequencies and counts (B) of intratumoral DCs. Gating strategies (C) and absolute number (D) of intratumoral cDC1, cDC2, and IRF8^+XCR1^+ cDC1 precursors. (E) Representative plots and absolute number of CD40^+CD80^+ activated tumor-infiltrating DCs. (F) Representative plots of mean fluorescence intensity of CD86 and statistical analysis. (G and H) Frequency of CD63^+ DCs, PD-L1^+ DCs (G), IL-12^+ DCs, CXCL9^+ DCs, and TNF-α^+ DCs (H) in B16-OVA tumors. (I and J) Frequency (I) and pie charts (J) of individual TCR Vβ clonotypes from endogenous CD8^+ T cell in tdLNs. All data represent the mean ± SEM and were analyzed by Student’s t test. Statistical difference is delineated by ns, not significant, ^∗p < 0.05 and ^∗∗p < 0.01. FX-engineered T cells enhance the control of tumors with pre-existing antigenic heterogeneity Cytokines like Flt3L are critical for DC development and have shown tumor-suppressive effects when delivered through CAR-T cells, oncolytic viruses, or intratumoral injection.[179]^19^,[180]^42^,[181]^43 We hypothesized that co-expression of Flt3L and XCL1 (termed FX) in T cells could further enhance anti-tumor efficacy, especially in “cold” tumors that typically exhibit limited T cell response due to a paucity of DCs.[182]^44 In the B16-OVA melanoma model, FX-engineered OT-I cell (OT-I/FX) therapy significantly reduced tumor burden compared to T cells expressing Flt3L or XCL1 alone ([183]Figures 5A and [184]S6A). TCR repertoire analysis in tdLNs showed that OT-I/FX substantially amplified the clonal expansion of host CD8^+ T cells ([185]Figure S6B). Growing evidence highlights DCs’ importance in the therapeutic efficacy of anti-PD-L1 therapy, and we assessed the combination therapeutic effects of anti-PD-L1. Both XCL1- and FX- engineered T cell therapies synergized with anti-PD-L1 treatment, significantly boosting anti-tumor responses and prolonging survival of tumor-bearing mice ([186]Figures 5B and [187]S6C). Importantly, FX-engineered T cell therapy induced a marked increase in SIIN-specific CD8^+ T cell responses ([188]Figure 5C). Furthermore, using Tcf7-DTR-GFP OT-I reporter mice, we found that OT-I/XCL1 and OT-I/FX significantly increased the proportion of TCF1^+Slamf6^+ subset within the adoptively transferred cells in the tdLNs ([189]Figure 5D), consistent with previous findings.[190]^32 Figure 5. [191]Figure 5 [192]Open in a new tab FX-engineered T cells trigger endogenous T cell responses and control of tumors with pre-existing antigen heterogeneity (A) Average tumor growth curves of B16-OVA tumor-bearing mice (n = 6–9 mice). (B) Schematic of the B16-OVA tumor model and average tumor growth curves (left) and survival curves (right) (n = 10–13 mice). (C) Representative plots and absolute number of endogenous SIINFEKL-specific CD8^+ T cells in B16-OVA tumor. (D) Frequencies of TCF1^+SlamF6^+ OT-I cells in B16-OVA tumor. (E) Average tumor growth curves of antigen-heterogeneous tumor models. (F) Representative plots of p15E-specific CD8^+ T cells. (G–I) Frequencies and absolute number of p15E-specific CD8^+ T cells (G) and SIINFEKL-specific CD8^+ T cells (H) and frequencies of p15E-specific CD107a-producing and IFNγ-producing CD8^+ T cells (I) from intratumoral endogenous CD8^+ T cells. (J) Schematic of the B16-OVA tumor model and average tumor growth curves (left) and survival curves (right) (n = 10–13 mice). All data represent the mean ± SEM and were analyzed by Student’s t test for (G)–(I) or one-way ANOVA with Tukey’s multiple-comparisons test for (C) and (D) or one-way ANOVA with Tukey’s multiple-comparisons test for (A), (B), (E), and (J) or log rank (Mantel-Cox) test for (B) and (J). Statistical difference is delineated by ^∗p < 0.05, ^∗∗p < 0.01, ^∗∗∗p < 0.001. Tumor antigenic heterogeneity is a major driver of tumor immune evasion and presents a formidable obstacle in cancer therapy. Harnessing the polyclonal responses of endogenous CD8^+ T cells holds promise for counteracting immune escape. To test effects on tumors with antigenic heterogeneity, we used a mixed B16-OVA/B16F10 model. OT-I/FX therapy consistently curbed tumor growth across various B16-OVA/B16F10 ratios, outperforming control OT-I treatment ([193]Figures 5E and [194]S6D). Tetramer-staining revealed that OT-I/FX treatment markedly increased the frequency and number of intratumoral SIIN- and p15E-specific CD8^+ T cells ([195]Figures 5F–5H and [196]S6E), with significantly elevating the proportion of IFNγ^+ and CD107a^+ p15E-specific T cells ([197]Figures 5I and [198]S6F). Single-cell TCR sequencing (scTCR-seq) further confirmed enhanced cytotoxicity among T cells targeting SIIN or p15E ([199]Figure 6K). These results collectively indicate that OT-I/FX therapy increases the number of intratumoral polyfunctional tumor-specific CD8^+ T cells. Given that XCL1 expression upregulated CD40 on tumor-infiltrating DCs ([200]Figure 4E), combining OT-I/FX with CD40 agonist (αCD40) further enhanced tumor suppression, prolonged mouse survival, and amplified the endogenous tumor-specific T cell responses ([201]Figures 5J, [202]S6G, and S6H). Together, these results show that FX-engineered T cells stimulate robust AS and polyclonal CD8^+ T cell activation, enhancing ACT efficacy against antigenically heterogeneous tumors. Figure 6. [203]Figure 6 [204]Open in a new tab scRNA-seq reveals that FX-engineered T cells significantly enhance endogenous T cell activation and promote interactions between DCs and T cells (A) Workflow of scRNA-seq experiments. Created with [205]BioRender.com. (B) Uniform manifold approximation and projection (UMAP) of unsupervised cell clusters from intratumoral CD45^+ immune cells. (C) Proportions of individual cell population identified in tumors. (D) Anti-tumor abundance of immune cell subsets across different treatment. (E) Tumor-infiltrating CD45^+ cell from [206]Figure 6A are displayed with FlowSOM. (F) Absolute counts of endogenous CD8^+ T cells (left) and total DCs (right). (G) UMAP of CD8^+ T cells subpopulations. (H) Relative abundance of CD8^+ T cells. (I and J) Heatmap of selected genes in intratumoral CD8^+ (I) and CD4^+ T cells (J). (K) Cytotoxicity scores of endogenous SIINFEKL-specific, non-SIINFEKL-specific, and p15E-specific CD8^+ T cells. (L) Coxcomb plots showing the 10 most expanded clones in tdLNs; each pie slice represents a unique CD8^+ T cell clonotype. (M) Empirical cumulative distribution function (ECDF) plot of enrichment score for inflammasome signature in intratumoral DCs. (N and O) Heatmap of co-stimulatory molecules (N) and cytokines (O) in intratumoral DCs. (P and Q) CellPhoneDB analysis of the interactions of DC-T cells (P) and T-DC cells (Q). All data represent the mean ± SEM and were analyzed by one-way ANOVA with Tukey’s multiple-comparisons test for (F) or the Wilcoxon signed-rank test for (K). scRNA-seq reveals that FX-engineered T cells significantly enhance both the infiltration and activation of T cells To investigate the remodeling of the tumor immune microenvironment induced by OT-I/FX treatments at single-cell resolution, we thus performed single-cell transcriptomic and single-cell immune repertoire sequencing analyses on tumor-infiltrating CD45^+ cells isolated from B16-OVA tumor-bearing mice ([207]Figure 6A). To accurately distinguish adoptively transferred CD45.1^+ cells from host-derived CD45.2^+ cells within the tumor, we developed an algorithm that classifies individual cells by analyzing allele-specific sequencing coverage at variant sites between the CD45.1 and CD45.2 genes. Unsupervised clustering of the single-cell gene expression profiles of host-derived CD45^+ cells identified 32 distinct clusters ([208]Figure S8A), representing 12 immune cell populations, including T cells, B cells, NK cells, monocytes/macrophages (Mono/Mac), and DCs ([209]Figures 6B and [210]S7A–S7C). The distribution of these populations varied notably across treatment conditions, with OT-I/FX therapy, whether or not combined with αCD40, significantly increasing the proportion of tumor-infiltrating CD8^+ T cells while reducing the proportion of Mono/Mac ([211]Figures 6C and [212]S7B). Further analysis revealed an increased percentage of “anti-tumoral” lymphocyte clusters in tumors treated with OT-I/FX or OT-I/FX plus αCD40 ([213]Figure 6D). Flow cytometry analysis further confirmed these results, showing a substantial increase in the absolute number of intratumoral endogenous CD8^+ T cells following OT-I/FX therapy ([214]Figures 6E and 6F). Interestingly, while scRNA-seq data suggested a relative decrease in the proportion of intratumoral DCs, flow cytometry showed an increase in the absolute increase in DC numbers in tumors treated with engineered T cells compared to control T cells ([215]Figures 6C and 6F). Concurrently, we also observed an elevated ratio of DCs to pro-tumoral Mono/Mac following OT-I/FX therapy ([216]Figure S8E). This discrepancy is likely due to the significantly increased proportion of CD8^+ T cells in the CD45^+ populations, which reduced the relative proportion of DCs despite the increase in their absolute number. To gain a deeper understanding of the changes within the TME, we profiled subpopulations of CD8^+ T cells, CD4^+ T cells, DCs, and Mono/Macs. Upon re-clustering CD8^+ T cells, we identified 9 distinct subpopulations based on known markers ([217]Figures S8C and S8D). Specifically, we observed a significantly increased frequency of effector memory CD8^+ T cells (CD8 Tem), effector CD8^+ T cells (CD8 Teff), and proliferating CD8^+ T cells with OT-I/FX treatment ([218]Figures 6G and 6H). Additionally, the ratio between “non-exhausted” and “exhausted” CD8^+ T cell clusters was the highest with combination therapy ([219]Figure S8F). Transcriptomic profiling of tumor-infiltrating host CD8^+ T cells across treatments revealed a robust activation signature in response to OT-I/FX treatment. In detail, we observed upregulation of Tbx21, Klrg1, and Id2, along with various effector molecules (e.g., Ifng, Prf1, Gzmb, and GzmK), co-inhibitory receptors (e.g., Lag3 and Havcr2), and co-stimulatory receptors (e.g., Cd27, Cd28, Tnfrsf9, and Tnfrsf18) in line with a strong activation and differentiation of effector T cells ([220]Figure 6I). Furthermore, FX-engineered T cells induced increased expression of genes associated with TCR signaling pathways, including Ifng, Nfatc1, and Nr4a1/2 ([221]Figure 6I). Differentially expressed gene (DEG) analysis also revealed upregulation of key immune function genes in combination therapy with OT-I/FX and αCD40, including Gzmb, GzmK, Ifng, and Mki67 ([222]Figure S8G). Gene set enrichment analysis (GSEA) of intratumoral host CD8^+ T cells further revealed that the combination therapy maintained a high proliferative potential and significantly upregulated multiple metabolic pathways, including oxidative phosphorylation, mTORC1 signaling, fatty acid metabolism, and pyruvate metabolism ([223]Figure S8H). These results suggest that FX-engineered T cells significantly enhance the activation and functionality of endogenous CD8^+ T cells within the TME. Among the CD4^+ T cell populations, eight distinct subpopulations were identified ([224]Figures S8I and S8J). Notably, CD4^+ regulatory T cells (Tregs) were primarily enriched with both OT-I/FX and OT-I/FX plus αCD40 treatments ([225]Figure S8K). Although FX secreting increased Treg infiltration, recent studies have identified a novel Treg subpopulation, the “fragile” Tregs, that promotes anti-tumor immunity.[226]^45 Fragile Tregs retain Foxp3 expression but lack NRP1 and exhibit reduced levels of suppressive molecules such as CD73 and IL-10.[227]^45 We observed that the majority of Tregs exhibited deficiencies in Nrp1, Nt5e, Pdcd1, and Il2ra, alongside increased expression of Satb1 and Gzmb with OT-I/FX and combination therapy ([228]Figure S8L). These characteristics suggest that these Tregs may represent the fragile Treg subset. Additionally, we found that combination therapy resulted in enhanced cytotoxic activity of intratumoral CD4^+ T cells ([229]Figure 6J). We also noted a significant shift in the Tpex to Tex ratio among endogenous T cells, as well as an increased CD8^+ T cell-to-Treg ratio ([230]Figures S8M and S8N). Collectively, these results indicate that FX-engineered T cells enhance the infiltration and activation of endogenous T cells and reshape the anti-tumor landscape within the TME. Single-cell sequencing reveals that FX engineering enhances DC-T cell interactions and promotes T cell clonal expansion The observation that OT-I/FX therapy effectively drives tumor rejection, even in the presence of antigenic heterogeneity, prompted us to further investigate T cell dynamics using scTCR-seq. Analysis of scTCR-seq data revealed a higher number of highly expanded CD8^+ T cell clones (>30) and moderately expanded CD4^+ T cell clones (5 < X ≤ 10) following OT-I/FX therapy ([231]Figures S9A–S9D). Using a cytotoxicity scoring system we developed, both SIIN- and non-SIIN-specific T cells from tumors with OT-I/FX plus αCD40 therapy exhibited significantly higher cytotoxicity scores. While the increase in cytotoxicity score for p15E-specific T cells was observed, it did not have statistical significance ([232]Figure 6K). Furthermore, we sorted CD3^+ T cells from tdLNs and performed scTCR-seq. Analysis of CDR3 sequences in host TCR clones revealed an elevated abundance of certain TCR sequences in OT-I/FX-treated mice ([233]Figure 6L). Notably, the top 10 expanded clonotypes, which represented the majority of all cells sequenced, were primarily expanded in the OT-I/XCL1 and OT-I/FX treatments ([234]Figure 6L). We also evaluated the frequency of TRBV-TRBJ pairing usage and found an enrichment of specific TRBV-TRBJ pairings in the OT-I/FX-treated groups compared to control, indicative of oligoclonal T cell expansion ([235]Figure S8E). These findings suggest the emergence of an endogenous tumor-specific T cell response. Given that XCL1 expression enhances the quantity and functionality of tumor-infiltrating DCs ([236]Figures 4A–4H), we investigated intratumoral DCs in more detail. After unsupervised clustering of the initial DC/pDC clusters, 7 subpopulations were identified, including classical DC subpopulations cDC1 and cDC2, proliferating DCs (previously identified as cycling DCs),[237]^46 as well as mregDC1 and mregDC2 ([238]Figures S9F and S9G). A significant increase in the proportion of cDC2 was observed in the FX-treated group ([239]Figure S9G). Previous reports have shown that the inflammatory TME can induce IFN-stimulated genes (ISGs) cDC2 (ISG^+ cDC2) to support anti-tumor immunity.[240]^47 We found that the gene expression profile of these cDC2 from OT-I/XCL1- and OT-I/FX-treated tumors closely resembled that of ISG^+ cDC2, indicating enhanced anti-tumor activity ([241]Figure S9H). The activation and antigen presentation of DCs are crucial for promoting antigen-specific CD8^+ T cell immunity. By scoring cDC clusters for inflammasome activation, mregDC signature, and MHC class I presentation signature, we observed a significant variance of score related to inflammasome activation and the mregDC signature following OT-I/FX treatment ([242]Figures 6M, [243]S9I, and S9J). Although the MHC class I signature did not show significant changes, several related genes ([244]Figures S9I–S9K), including H2-M2, H2-T23, Tap1, Ctss, Ctsb, and Cybb, were upregulated. Furthermore, mregDC signature was characterized by the enhanced expression of immunostimulatory molecules and signals ([245]Figures 6N and 6O), while the expression of immunoregulatory molecules remained unpredictable ([246]Figures S9L–S9N). Notably, DCs in the OT-I/FX therapy group exhibited elevated expression of key activation markers, such as Cd40 and Cd83, along with co-stimulatory cytokine genes, including Il1b, Il12b, Il15, Cxcl9, Cxcl10, and Cxcl16 ([247]Figures 6N and 6O). Additionally, these DCs also showed reduced expression of Treg-recruiting chemokines, such as Ccl17 and Ccl22 ([248]Figure 6O). Although mregDC can have dual immunostimulatory and immunoregulatory roles, OT-I/FX therapy favored the upregulation of immunostimulatory signals in DCs, thereby enhancing their immunogenic function. Emerging evidence suggests that spatial interactions between DCs and T cells are critical for inducing and sustaining T cell responses.[249]^15^,[250]^48^,[251]^49 Cell-cell communication analysis between DCs and T cells revealed several known interaction pairs, including CXCL16-CXCR6, IL15-IL-15R, and CXCL9/10-CXCR3, which contribute to recruiting cytotoxic T cells and sustaining their survival ([252]Figure 6P). We also identified other DC-T cell interactions, such as the upregulation of TNFSF9-TNFRSF9 (4-1BBL-4-1BB) interactions and a reduction in ENTPD1-ADORA2A interactions within OT-I/FX treatment ([253]Figure 6P). These DC-T cell interactions are also known to enhance DC functionality. Notably, we observed increased TNF superfamily interactions (e.g., TNFSF11-TNFRSF11A, TNFSF13B-TNFRSF13B, LTB-LTBR, and IFNG-IFNGR) between T cells and DCs ([254]Figure 6Q), which are known to induce the non-canonical nuclear factor κB pathway and promote DC activation.[255]^50^,[256]^51 Notably, the XCL1-XCR1 interaction specifically between CD8^+ T cells and DCs was upregulated following both XCL1 and FX treatment ([257]Figure 6Q). These findings suggest that FX-engineered T cells stimulate the immunogenic function of DCs and significantly enhance DC-T cell interactions within the TME. scRNA-seq analysis reveals that FX-engineered T cells reprogram intratumoral Mono/Mac phenotype TAMs exhibit diverse roles in tumor immunity, with M1-like TAMs exhibiting anti-tumor activity.[258]^52 Immunotherapy-induced CD8^+ T cells attract macrophages and skew their differentiation toward M1-like TAMs,[259]^53 which are crucial for tumor control. In our analysis, 6 Mono/Mac subpopulations were identified, including 4 macrophage subpopulations (C1qb, mt-Co1, Plin2, and Birc5) and 2 monocyte subpopulations (Ace and Chil3) ([260]Figures S10A–S10C). DEG analysis highlighted the heterogeneity in expression profile ([261]Figure S10D). RNA velocity inference with scVelo and trajectory analysis with Monocle3 to characterize cellular state transitions indicated that Mono-chil3 and Mac-plin2 represented early differentiation states within the tumor-infiltrating myeloid compartment ([262]Figures S10E and S10F). However, due to dataset limitations (e.g., lack of cross-tissue scRNA-seq and lineage tracing models such as Ms4a3^Cre mice), we were incapable of providing definitive evidence for this relationship. Across different treatment conditions, a pattern reflecting anti-tumor efficacy emerged. OT-I/FX and OT-I/FX plus αCD40 therapies showed enrichment of the Mono-Chil3 cluster within the tumor, while controls favored Mac-C1qb cluster ([263]Figure S10G). Notably, Mono-chil3 exhibited particularly higher Cd40 expression levels ([264]Figures S10H and S10I), supporting Mono-Chil3 potential in promoting anti-tumor immunity. Transcriptomic analysis revealed that over 300 genes were upregulated following OT-I/FX treatments ([265]Figure S10J), with αCD40 further boosting the expression of pro-inflammatory genes (e.g., Il1b, Tnf, Irf1, and Cxcl10) ([266]Figure S10K). Further analysis indicated that Mono-Chil3 upregulated expression of pro-inflammatory genes, including Cxcl2, Cxcl10, Ifitm6, Tnf, and Il1b, whereas Mac-C1qb was more closely associated with regulatory or immunosuppressive functions ([267]Figures S10L and S10M). To better assess the functional characteristics of these subpopulations, we performed an “anti-tumoral and pro-tumoral gene cluster” scoring analysis, which revealed that Mono-Chil3 adopted an M1-liked anti-tumoral phenotype ([268]Figures S10N and S10P). Moreover, FX engineering inhibited the expression of genes linked to M2-skewed pro-tumoral phenotypes, such as Mrc1, Trem2, Apoe, and Lpl ([269]Figure S10O). Overall, these results indicate that FX-engineered T cells drive a shift from a pro-tumoral to an anti-tumoral phenotype in Mono/Mac population. FX-armed CAR-T cells demonstrate superior tumor control in both murine and Flt3KO&hFLT3LG humanized mouse models Encouraged by prior results, we explored whether FX-armed CAR-T (CAR-FX) cells show enhanced tumor control in vivo. Although CAR-T cells do not necessarily depend on DCs for antigen presentation, we hypothesized that engaging DCs might amplify endogenous T cell responses, addressing antigen heterogeneity in solid tumors. To test this, we generated mouse CAR-FX T cells targeting humanized CD19 or B7-H3 ([270]Figure 7A) and confirmed comparable CAR expression with control CAR-T cells ([271]Figure S11A). In B16F10 tumors expressing humanized B7-H3 or CD19 (B16F10-B7-H3 and B16F10-CD19), CAR-FX T cells outperformed control CAR-T cells in tumor suppression and extended mouse survival ([272]Figures 7B–7D, [273]S11B, and [274]S11C). Similar to that observed in the OT-I/FX system, CAR-FX T cell therapy also greatly increased the intratumoral infiltration of CAR-T cells and endogenous CD8^+ T cells ([275]Figures 7E, 7F, [276]S11D, and S11E) and expanded TCR Vβ clonotypes (Vβ8.1/2, Vβ10^b) in tdLNs ([277]Figure S11F). Tumor-infiltrating CAR-FX T cells exhibited a Tpex cell phenotype, accompanied by increased cytokine production, whereas control CAR-T cells primarily exhibited a Tex phenotype ([278]Figures S11G and S11I). Notably, the frequency of Tpex cells approximately doubled with CAR-FX T cell therapy, and similar patterns of PD1^+TIM3^+ and/or PD1^+TIM3^− were observed for both transferred and endogenous CD8^+ T ([279]Figures S11G and S11H). We also observed a significant increase in infiltration of both total DCs and cDC1s within the tumors ([280]Figure S11J). Combining CAR-FX T cells with αCD40 therapy strongly suppressed tumor progression ([281]Figures 7G and [282]S11K), and using Batf3^−/− mice confirmed that CAR-FX efficacy depends on endogenous cDC1s ([283]Figure S11L). Figure 7. [284]Figure 7 [285]Open in a new tab FX-armed CAR-T cells demonstrate superior tumor control in both murine and humanized mouse models (A) Schematic depicting the constructs of mouse B7-H3 and CD19 CARs. (B–D) Average tumor growth curves of B16F10-CD19 (B) and B16F10-B7-H3 (C); survival curves of B16F10-B7-H3 tumor-bearing mice (D) (n = 5 mice). (E and F) Absolute number of CAR-T cells and endogenous CD8^+ T cells in B16F10-CD19 (E) and B16F10-B7-H3 (F) tumors. (G) Average tumor growth curves of the B16F10-B7-H3 model (n = 8–10 mice). (H) Schematic depicting the humanized B7-H3 CAR constructs. (I and J) Average tumor growth curves of the PC3 tumor model (I) and survival curves of the A375-B7-H3 tumor model in Flt3ko&hFLT3LG NSG mice (J). (K) Schematic of the humanized Flt3KO&hFLT3LG NSG mice model. (L–N) Average tumor growth curves of A375-B7-H3 (L) and PC3 (M). Survival curves of PC3 tumor-bearing Flt3ko&hFLT3LG NSG mice (N). All data represent the mean ± SEM and were analyzed by Student’s t test for (E), (F), and (K) or two-way ANOVA with Tukey’s multiple-comparisons test for (B), (C), (G), (I), (L), and (M) or log rank (Mantel-Cox) test for (D), (J), and (N). Statistical difference is delineated by ns, not significant, ^∗p < 0.05 and ^∗∗p < 0.01. For clinical translation, we designed a anti-B7-H3 humanized CAR-T (hCAR) construct to overexpress humanized FLT3LG and XCL1 (termed hCAR-FX T) ([286]Figures 7H and [287]S12A), and we then evaluated the anti-tumor activity of hCAR-FX T cells in NOD scid gamma (NSG) mice bearing PC3 human prostate cancer cells, which naturally express high levels of B7-H3, and the A375-B7-H3 CDX tumor model. The hCAR-FX T cells exhibited comparable tumor control capabilities to that of control hCAR-T in NSG mice, which lack an endogenous immune system ([288]Figures 7I and 7J). To model human immunity, we engrafted human peripheral blood mononuclear cells (PBMCs) into Flt3KO&hFLT3LG NSG mice to specifically facilitate the development of human DCs ([289]Figures 7K and [290]S12B). In this system, hCAR-FX T cells treatment significantly inhibited the progression of A375-B7-H3 melanoma and the PC3 prostate cancer ([291]Figures 7L, 7M, [292]S12C, and S12E) and extended the survival time of the PC3 tumor-bearing mice ([293]Figure 7N). Analysis of infiltrating immune cells in the A375-B7-H3 melanoma revealed that hCAR-FX T cell therapy enhanced the number of both CAR-T and DC cells ([294]Figure S12D). These findings demonstrate that strengthening Flt3L and XCL1 expression in CAR-T cells effectively limits tumor progression across multiple models, highlighting its potential for clinical translation. Discussion Antigenic heterogeneity and antigen loss represent major barriers to immune surveillance and contribute to the development of resistance against T cell-based immunotherapies, posing significant challenges to current immunotherapeutic strategies. While CAR-T therapies have yielded remarkable success against hematologic malignancies, their efficacy in solid tumors remains limited by these issues.[295]^1^,[296]^2 The clinical success of TIL therapies in solid tumors suggests that the induction of productive polyclonal T cell responses to multiple tumor antigens may provide an effective strategy to overcome antigenic escape. In this study, we proposed a promising approach to tackle antigenic heterogeneity and antigen loss in solid tumors by engineering T cells to express Flt3L and XCL1. These “FX-armed” T cells improved DC recruitment and activation in the TME, facilitated DC-T cell interaction, induced AS, and elicited broad polyclonal T cell responses. Specifically, FX-armed T cells exhibited increased production of IFNγ by T cells and IL-12 by DCs, two key cytokines that synergistically drive AS and amplify immune responses.[297]^17 The IFNγ-IL-12 feedback loop between T cells and DCs, a mechanism consistently linked to successful immunotherapy, aligns with our findings.[298]^54 Comprehensive analysis of tumor-infiltrating immune cells following FX-armed T cells treatment revealed significant reshaping of the immune landscape of the TME, with increased infiltration of CD8^+ T cells, DCs, and NK cells, along with reduced immunosuppressive populations. These changes indicate that FX expression reprograms the TME from an immunosuppressive to an immune-inflamed state. Interestingly, while FX-armed T cell treatment increased the proportion of Tregs among CD4^+ T cells, these Tregs exhibited a “fragile” phenotype associated with anti-tumor activity.[299]^45 Previous reports have shown that IFNγ can induce the formation of fragile Tregs, further emphasizing the central role of IFNγ in our strategy.[300]^45 In analyzing myeloid populations, we observed that FX expression enhanced DC infiltration and activation, particularly by promoting expression of co-stimulatory molecules such as CD40. Consequently, combining FX-armed T cells with αCD40 significantly improved survival of tumor-bearing mice. Given the crucial role of DCs in delivering TCR and co-stimulatory signals necessary for T cell activation and persistence,[301]^12 these findings raise the possibility that optimizing intact signals of DC-T cell interaction could further boost CAR-T cell efficacy, supported by recent evidence showing superior anti-tumor activity of dual TCR/CAR-T cells compared to conventional CAR-T cells in a humanized solid tumor mouse model.[302]^55 Further analysis of Mono/Mac populations showed that CD40 signaling was not restricted to DCs. FX-armed T cells treatment promoted the expansion of a Mono-Chil3 cluster characterized by high Cd40 expression and an M1-skewed anti-tumor phenotype. Recent evidence has demonstrated that CD40 signaling can stimulate macrophage anti-tumor functions through metabolic reprogramming,[303]^56 suggesting that FX expression may induce broader systemic shift toward a pro-inflammatory immune landscape. cDC1s are critical for cross-presenting antigens and activating CD8^+ T cells in both tdLNs and the TME, and their involvement in AS is increasingly recognized.[304]^2^,[305]^17^,[306]^19^,[307]^57 Immune repertoire analysis demonstrated that FX-armed T cells enhanced the expansion of diverse TCR clonotypes and increased the production of endogenous antigen-specific CD8^+ T cells. Using Batf3^−/− and Rag1^−/− mice, we confirmed that the anti-tumor effects of FX-armed T cells largely depended on cDC1s and host T cells. Cell-cell communication analysis and immunofluorescence imaging further revealed the XCL1-XCR1 axis as a key driver of the endogenous T cell response. This axis appears to support the maintenance of Tpex within tdLNs and tumors, although the mechanisms by which cDC1s regulate Tpex formation remain to be fully elucidated. We further validated this strategy in a humanized mouse model containing functional DC compartments, confirming that AS contributes to tumor control during CAR-T therapy. Nevertheless, it is important to acknowledge the limitations of this model. Most humanized mice lack fully functional LNs, which are essential for initiating immune responses. Moreover, immune dysfunction in cancer patients often extends beyond the TME, involving systemic defects such as impaired DC activity across tissues.[308]^58 This may partly explain the limited clinical success of some DC-targeted therapies.[309]^18^,[310]^19^,[311]^20 Notably, the ability of FX-armed T cells to enhance both the abundance and function of DCs could provide an advantage in overcoming these limitations. In summary, our findings suggest that FX engineering offers a promising approach for addressing the limitations of conventional CAR-T therapies in solid tumors. By promoting the quantity and quality of DCs, FX-armed T cells enhance AS and broaden the immune response, offering a potential solution to tumor heterogeneity. Future research should explore the clinical potential of this strategy, including integrating synthetic Notch (synNotch) receptors to enable precise intratumoral delivery of immunostimulatory molecules, as well as combining FX-armed T cells with immune adjuvants or cancer vaccines to further enhance therapeutic efficacy in solid tumors. Limitations of the study This study highlights the therapeutic promise of FX-engineered T cells, yet several limitations must be considered. The humanized mouse models employed lack fully functional LNs, compromising accurate assessment of immune activation. Moreover, experimental conditions may not fully recapitulate the systemic immune dysfunction observed in cancer patients, such as defective DC activity. Although combining FX-armed T cells with adjuvants or cancer vaccines is proposed for poorly immunogenic tumors, their optimization and clinical feasibility remain untested. Additionally, the precise mechanisms by which DC-T cell interactions, particularly those involving cDC1s, support the maintenance of the Tpex subset require further investigation. Lastly, pooling cells from seven mice per group for single-cell sequencing limited statistical analysis. Resource availability Lead contact Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Lianjun Zhang (zlj@ism.cams.cn). Materials availability All materials and reagents used in this study are available from the [312]lead contact upon request. Data and code availability * • Single-cell RNA-seq and TCR-seq data have been deposited at CNGBdb: CNP0006961. * • The R code required to reproduce the scRNA-seq and scTCR-seq data shown is available at the following repository: [313]https://doi.org/10.5281/zenodo.15799971. * • Any additional information required to reanalyze the data reported in this work paper is available from the [314]lead contact upon request. Acknowledgments