Rejuvenating endogenous antitumor immunity via a chimeric receptor-engineered oncolytic virus targeting tumor-associated macrophages

Chaolong Lin; Shaopeng Li; Rui Lou; Wenzhong Teng; Yang Tian; Chenxi Feng; Naizhen Wang; Yipeng Rao; Yaning Qin; Lu Li; Xiaoxuan Huang; Yisen Lin; Jun Zhang; Ningshao Xia; Chenghao Huang

doi:10.1126/sciadv.aef6767

. 2026 Sep 18;12(38):eaef6767. doi: 10.1126/sciadv.aef6767

Rejuvenating endogenous antitumor immunity via a chimeric receptor-engineered oncolytic virus targeting tumor-associated macrophages

Chaolong Lin ^1,^2,^†, Shaopeng Li ^1,^2,^†, Rui Lou ^1,^2,^†, Wenzhong Teng ^1,^2,^†, Yang Tian ^1,^2,^†, Chenxi Feng ^1,^2,^†, Naizhen Wang ^1,², Yipeng Rao ^1,², Yaning Qin ^1,², Lu Li ^1,², Xiaoxuan Huang ^1,², Yisen Lin ^1,², Jun Zhang ^1,², Ningshao Xia ^1,^2,^3,^*, Chenghao Huang ^1,^2,^*

^¹State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China.

^²National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China.

^³School of Life Sciences, Xiamen University, Xiamen, 361102, China.

Corresponding author. Email: nsxia@xmu.edu.cn (N.X.);

Corresponding author. Email: huangchenghao@xmu.edu.cn (C.H.)

^†

These authors contributed equally to this work.

Roles

Chaolong Lin: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing

Shaopeng Li: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Rui Lou: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Wenzhong Teng: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Yang Tian: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Chenxi Feng: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Naizhen Wang: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Yipeng Rao: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Yaning Qin: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Lu Li: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Xiaoxuan Huang: Formal analysis, Investigation, Methodology, Validation, Visualization

Yisen Lin: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft

Jun Zhang: Conceptualization, Formal analysis, Investigation, Project administration, Supervision, Writing - original draft

Ningshao Xia: Conceptualization, Formal analysis, Funding acquisition, Project administration, Resources, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing

Chenghao Huang: Conceptualization, Data curation, Funding acquisition, Project administration, Resources, Supervision, Visualization, Writing - original draft, Writing - review & editing

PMCID: PMC13588179 PMID: 42758830

Abstract

Immunosuppressive tumor-associated macrophages (TAMs) create a barrier to effective antitumor immunity and promote therapeutic resistance. Reeducating TAMs to enhance their antitumor capabilities through phenotypic remodeling remains challenging. Here, we report a modular oncolytic herpesvirus platform, engineered with a PD-L1–specific chimeric receptor integrated into the viral envelope protein (CAR-oHSV). This design endows the virus with dual tropism, enabling it to target both tumor cells and TAMs within the tumor microenvironment. In virus-resistant tumor models, CAR-oHSV preferentially targets PD-L1⁺ TAMs and triggers a STING-dependent reprogramming into a CXCL9⁺ phenotype, enhancing their tumor antigen cross-presentation capability and inducing an endogenous antitumor T cell response. Furthermore, this platform can synergize with adoptive T cell therapy and immune checkpoint blockade therapy to overcome immunotherapy resistance. Collectively, our findings define a precision-oncolytic platform that dismantles TAM-mediated immunosuppression while amplifying adaptive immunity, offering a promising translational avenue for cancer immunotherapy.

INTRODUCTION

Tumor-associated macrophages (TAMs) have emerged as pivotal players in tumor progression and metastasis, mediating immunosuppressive effects on adaptive immune cells within the tumor microenvironment (TME) and contributing to therapy resistance (1). Although targeting TAMs presents a promising avenue for innovative cancer therapies, there are currently no effective strategies that consistently provide clinical benefit.

The integration of oncolytic viruses (OVs) with gene therapy offers a versatile approach for cancer treatment (2). This dual-pronged strategy leverages the inherent ability of OVs to selectively infect and lyse tumor cells while simultaneously serving as vectors for the delivery of therapeutic genes (3). Clinical trials using oncolytic herpesvirus (oHSV) encoding granulocyte-macrophage colony-stimulating factor (GM-CSF), such as T-VEC and RP1, have demonstrated promising results in melanoma treatment (4, 5). However, innate immune cells, particularly TAMs, can clear viruses and thus limit the efficacy of virotherapy (6–10). Therefore, developing genetically engineered OVs capable of targeting TAMs represents a promising approach to overcome macrophage-mediated viral clearance and/or reprogram TAMs toward an antitumor phenotype (11).

TAMs, aside from tumor cells, are the primary population expressing programmed cell death ligand 1 (PD-L1) in human tumors (12). PD-L1 engages programmed death-1 (PD-1) on T cells, resulting in T cell inhibition and promotion of a more immunosuppressive TME (13). Although immune checkpoint blockade (ICB) has demonstrated significant efficacy in melanoma and other malignancies, both primary and acquired resistance remain substantial barriers (14, 15). Insufficient T cell infiltration into tumors is a critical factor limiting therapeutic success (15). Therefore, innovative strategies to enhance T cell infiltration within the TME are urgently needed and could substantially expand the number of patients who benefit from immunotherapy.

Here, we engineered a PD-L1-directed chimeric antigen receptor (CAR) oHSV, designed to induce PD-L1-dependent oncolysis of target cells and to stimulate immune responses in TAMs, thereby augmenting antitumor immunity.

RESULTS

PD-L1-positive TAMs are associated with poorer outcomes in cancers and serve as ideal targets for oHSV

To elucidate the immunoregulatory roles of TAMs in cancer progression and identify potential retargeting receptors for oHSV, we initially applied the CIBERSORT algorithm to quantify macrophage infiltration across various cancer types and found that macrophage infiltration was markedly elevated (Fig. 1A). We then conducted a univariate Cox regression analysis to examine the association between patient survival and immune cell infiltration scores and found that macrophage infiltration was significantly correlated with adverse prognosis in various cancer types (Fig. 1B). Furthermore, our findings indicate that tumors from ICB non-responders exhibited higher TAM abundance than those from ICB responders, suggesting that elevated TAM levels are associated with poor response to ICB therapy (Fig. 1, C and D).

Fig. 1. — (A) Heatmap illustrating macrophage infiltration levels in normal (N) and tumor (T) tissues, based on data from the TCGA database (Wilcoxon test, two-sided). (B) Forest plots depicting hazard ratios of macrophage infiltration in relation to overall survival in various cancers (log-rank test). (C and D) TAM quantification in the indicated datasets (Wilcoxon rank-sum test). “NR” denotes non-responders and “R” denotes responders. (E) Immune-inhibitory scores were calculated for each tumor-infiltrating immune cell using the integrated datasets GSE151091, GSE215120, and GSE139829. (F) Comparative pathway enrichment analysis showing significantly enriched immune-inhibitory signatures in macrophages isolated from tumor tissues relative to those from matched normal tissues. (G) Differential expression of immune-inhibitory genes within key immune-suppressive pathways in macrophages from both tumor and normal tissues. (H) Comparison of immune-inhibitory gene expression levels in macrophages derived from tumor and normal tissues (Wilcoxon test, two-sided). (I to N) Kaplan-Meier curves depicting patient survival based on high (H) and low (L) PD-L1 expression and macrophage infiltration levels (log-rank test). Error bars show mean ± SD. *P < 0.05, ** P < 0.01, ***P < 0.001, **** P < 0.0001.

Single-cell immune profiling of 125,569 immune cells obtained from 22 melanoma and 22 normal samples revealed that TAMs constitute the predominant immune cell subset and exhibit the highest immune inhibitory scores in tumors compared to normal tissues (Fig. 1E and fig. S1A). To identify critical immunosuppressive signals in TAMs, we analyzed differential signaling pathways between macrophages in tumor and normal tissues. The top five immunosuppressive pathways identified in TAMs were primarily related to regulation of T cell immune tolerance, antigen processing and presentation, and T cell activation and proliferation (Fig. 1F). Further cross-analysis of these significantly enriched pathways with immune inhibitory gene sets revealed differential expression of three immunosuppressive genes in TAMs: HAVCR2, CD274, and FOXP3 (Fig. 1G). Gene expression analysis demonstrated significant upregulation of CD274 in TAMs from tumor samples (Fig. 1H), and as PD-L1-positive TAMs reportedly suppress T cell function (16), these results suggest that CD274 may serve as a notable marker of immunosuppressive TAMs. We further assessed the prognostic impact of CD274 expression and macrophage infiltration on patient survival and observed that patients with high macrophage infiltration and high CD274 expression experienced significantly poorer survival outcomes compared to those with low macrophage infiltration and low CD274 expression (Fig. 1, I to N and fig. S1, B to G). Altogether, these findings underscore CD274 as a hallmark of immunosuppressive TAMs and suggest it may serve as an ideal retargeting receptor for oHSV-based TAM targeting strategies.

Generation of a PD-L1-directed CAR oHSV enabling specific infection of PD-L1-positive cells

HSV glycoprotein D (gD) plays a crucial role in viral entry by interacting with various natural receptors such as Nectin-1 and herpesvirus entry mediator (HVEM) (17). Modifications to gD enable it to target alternative receptors, such as HER2 and EGFR, but reportedly affect viral infection (18, 19). To determine whether gD can be engineered to present CARs against PD-L1 (αPD-L1 CAR), we incorporated an anti-PD-L1 nanobody (αPD-L1) into the non-receptor binding domain of gD, thereby creating a PD-L1-specific CAR oHSV (gD^αPD-L1) (Fig. 2, A and B). We observed robust expression of αPD-L1 CARs on the membrane of gD^αPD-L1-infected cells (Fig. 2, C and D). Our findings indicate that gD^αPD-L1 retains a replication capacity comparable to its parental strain in U-2 OS cells, which are susceptible to infection (Fig. 2E), implying efficient viral entry via natural receptors. To determine if gD^αPD-L1 entry relies on PD-L1 expression, we observed that gD^αPD-L1 failed to infect PD-L1-knockout B16-F10 cells but efficiently infected wild-type (WT) B16-F10 cells (fig. S2, A and B). Notably, its infectivity increased substantially in PD-L1-overexpressing B16-F10 cells (Fig. 2, F and G), indicating that gD^αPD-L1 selectively infects cells in a PD-L1-dependent manner. gD^αPD-L1 also exhibited dose-dependent cytotoxicity corresponding to its entry efficiency (Fig. 2H and fig. S2, C to E). To further confirm that gD^αPD-L1 specifically enters cells through PD-L1, the entry of gD^αPD-L1 was effectively inhibited in a dose-dependent manner by both PD-L1-hIgG and αPD-L1 proteins (Fig. 2, I and J and fig. S2, F to H). Additionally, the dose-dependent cytotoxic effect of gD^αPD-L1 was completely abolished by the addition of PD-L1-hIgG proteins (fig. S2I). These findings demonstrate that gD^αPD-L1 specifically targets cells through engagement with PD-L1 on the cell surface.

Recent studies, including our own, have demonstrated that oHSV enhances interferon (IFN) responses (Fig. 2K and fig. S3, A and B), which in turn upregulate PD-L1 expression in the TME and contribute to tumor resistance to oncolytic immunotherapy (20, 21). To determine whether IFN-induced upregulation of PD-L1 expression enhances virus attachment and thereby amplifies infection efficiency to achieve bystander effects, we found that gD^αPD-L1 attached to B16-F10 cells more efficiently than gD^WT (Fig. 2L and fig. S3, C and D). More importantly, treatment with biologically relevant doses of IFNs, which upregulated PD-L1 without inducing cytotoxicity, markedly increased the attachment efficiency of gD^αPD-L1 (Fig. 2, K to M and fig. S3, C to G). Therefore, IFNs treatment significantly enhanced the cytotoxicity of gD^αPD-L1 (Fig. 2N and fig. S3H). Moreover, the cell-killing efficacy of gD^αPD-L1 in B16-F10 cells was markedly reduced upon blocking virus-induced IFN-β with anti-IFNAR1 antibodies (Fig. 2O); however, this blockade did not affect cytotoxicity in PD-L1-overexpressing B16-F10 cells. These findings suggest that endogenously expressed IFN-β interacts with IFNAR1 through an autocrine mechanism, promoting PD-L1 expression and potentially facilitating viral entry and oncolysis.

Retargeting oHSV to PD-L1 broadens its viral tropism and amplifies its oncolytic efficacy

We aimed to assess the oncolytic efficacy of PD-L1-directed CAR oHSV on a panel of mouse tumor cell lines characterized by diverse natural gD receptors and varying PD-L1 expression levels (fig. S4, A to F). In tumor cell lines with or without natural gD receptors, dose-response analyses demonstrated that gD^αPD-L1 had markedly enhanced oncolytic activity (Fig. 3A and fig. S4, G to O), with EC₅₀ values 4.24- to 47.90-fold lower than those of gD^WT (fig. S4P). This finding indicates that gD^αPD-L1 possesses potent and broad-spectrum oncolytic activity. The oncolytic efficacy of gD^αPD-L1 shows a strong positive correlation with PD-L1 levels, unlike with Nectin-1 and HVEM (Fig. 3, B to D). To identify which virus receptor significantly influences gD^αPD-L1 entry, we engineered B16-F10 cells to express either HVEM or Nectin-1 (Fig. 3, E to F and fig. S4Q). In B16-F10^HVEM cells, gD^αPD-L1 entry was significantly blocked by PD-L1-hIgG in a dose-dependent manner, unlike with HVEM proteins (Fig. 3, G and H), suggesting that gD^αPD-L1 entry into B16-F10 cells depends more on PD-L1 than HVEM. In B16-F10^Nectin-1 cells, gD^αPD-L1 entry was more effectively inhibited by Nectin-1 proteins than by PD-L1-hIgG (Fig. 3, I and J), indicating a greater reliance on the Nectin-1 receptor in Nectin-1-sufficient cells. These findings corroborate the conclusion that endogenously expressed PD-L1 sufficiently directs gD^αPD-L1 entry into cells, alongside Nectin-1.

Fig. 3. — (A) Cytotoxic effects of gD^WT and gD^αPD-L1. (B to D) Correlation between the cytotoxicity of gD^αPD-L1 and the levels of its entry receptors across mouse tumor cell lines. (E) Viral infectivity in B16-F10 cell variants overexpressing various entry receptors. (F) Relative GFP quantification in viral infectivity assays. (G to J) Effects of PD-L1-hIgG, HVEM, or Nectin-1 proteins on the infectivity of gD^WT and gD^αPD-L1 in B16-F10 cells overexpressing HVEM or Nectin-1. (K) Schematic of the treatment regimen in nude mice inoculated with B16-F10 cells. (L) Growth curves of B16-F10 tumors (n = 7 mice/group). (M) Schematic of the treatment regimen in nude mice inoculated with MC38 cells. (N) Growth curves of MC38 tumors (n = 8 mice/group). Error bars show mean ± SD from three independent experiments (A to J). A Spearman’s correlation test in (B to D), an unpaired Student’s two-tailed t test (F) and a repeated measures ANOVA (L and N) were used. Vehicle, saline; s.c., subcutaneous injection; i.t., intratumoral injection. Cartoons were created using Adobe Illustrator (K and M).

We further assessed the antitumor efficacy of gD^αPD-L1 in vivo using nude mice, an immunodeficient model that enables evaluation of oHSV’s exclusive oncolytic effects. The findings revealed that gD^αPD-L1 exhibited significantly greater oncolytic efficacy than gD^WT in tumor models established using both B16-F10 (natural gD receptor-deficient) and MC38 (natural gD receptor-sufficient) tumor cells (Fig. 3, K to N). Collectively, these observations demonstrate that gD^αPD-L1 possesses broader antitumor activity and enhanced tumoricidal effectiveness.

PD-L1 upregulation on tumor cells can be shielded by cis interaction with αPD-L1 CAR

We investigated the function of αPD-L1 CARs displayed on the gD^αPD-L1 virus. Infection of mouse tumor cell lines with gD^αPD-L1 resulted in the presentation of membrane-anchored αPD-L1 CARs on the surfaces of infected cells (fig. S5, A and B). Our results indicate that substantial PD-L1 upregulation on virus-infected cells can be masked by either envelope-displayed or membrane-anchored αPD-L1 CARs (fig. S5, C and D). These αPD-L1 CARs directly inhibit the interaction between PD-1 and PD-L1 in vitro and alleviated PD-L1-induced immunosuppression in a Jurkat cell-based reporter assay (fig. S5, E and F). These in vitro findings demonstrate that display of αPD-L1 CARs on the gD^αPD-L1 viral envelope significantly enhances T cell activity.

We employed the MC38 tumor model to evaluate the non-replicative functions of gD^αPD-L1. Our results demonstrated that UV-inactivated gD^αPD-L1 exhibited remarkable therapeutic efficacy, leading to complete tumor regression in some mice (fig. S5, G and H). These findings underscore the potential of gD^αPD-L1 as a potent immune checkpoint inhibitor for cancer therapy.

gD^αPD-L1 induces potent antitumor responses and augments effector T cell functionality

To further evaluate the in vivo antitumor efficacy of gD^αPD-L1, we employed a murine B16-F10 tumor model (Fig. 4A), which is inherently resistant to both conventional oHSV virotherapy and anti-PD-L1 therapy (15). In the gD^αPD-L1-treated group, we observed significant tumor growth inhibition and prolonged survival of tumor-bearing mice (Fig. 4B). Notably, gD^αPD-L1 demonstrated substantially greater therapeutic efficacy in immunocompetent models compared to immunodeficient nude mice (Fig. 3, L and N and Fig. 4, C and D), underscoring its immunomodulatory function in cancer therapy. Similar outcomes were obtained in a second resistant model with subcutaneous or orthotopic GL261 tumors (Fig. 4, E and F).

To elucidate the mechanisms underlying gD^αPD-L1-mediated tumor control, we analyzed intratumoral virus dissemination post-infection. Virus titers in natural gD receptor-deficient B16-F10 tumor tissue showed that gD^αPD-L1 replicated more efficiently than gD^WT (Fig. 4G), indicating superior viral dissemination. To determine whether this advantage was maintained in natural gD receptor-sufficient tumors, we examined intratumoral viral dissemination after infection in MC38 tumors. Consistent with the in vitro replication advantage of gD^αPD-L1 in MC38 cells (fig. S5I), gD^αPD-L1 also produced higher intratumoral viral titers than gD^WT in MC38 tumors (fig. S5, J and K), suggesting that PD-L1 engagement provides an additional route for gD^αPD-L1 entry and propagation.

We next examined the inflammatory response within the tumors. IHC analysis revealed increased oHSV infection and tumor cell apoptosis in gD^αPD-L1-treated tumors (Fig. 4H). Enhanced oncolysis may trigger robust immune responses in the TME; accordingly, IHC analysis demonstrated increased infiltration of innate (NK cells) and adaptive immune cells (CD4⁺ and CD8⁺ T lymphocytes) in virus-treated tumors (fig. S6, A and B). Interestingly, TAM infiltration was significantly reduced in tumors treated with gD^αPD-L1. Flow cytometric analysis confirmed that CD4⁺ and CD8⁺ T cells isolated from gD^αPD-L1-injected tumors exhibited significantly higher expression of activation markers IFN-γ and granzyme B (GZMB) than those from mock- or gD^WT-injected tumors (Fig. 4I and fig. S7, A to C). These findings suggest that gD^αPD-L1 virotherapy stimulates T cells to eliminate established tumors. Depletion studies confirmed that the antitumor efficacy of gD^αPD-L1 required CD8⁺ T cells, but not CD4⁺ T cells or NK cells (Fig. 4, J and K).

To further investigate the mechanisms underlying the observed antitumor response, we performed single-cell RNA sequencing (scRNA-seq) analysis of tumor-infiltrating lymphocytes (TILs) (fig. S8, A to D). Treatment with gD^αPD-L1 significantly increased the proportion of T cells while reducing the frequencies of monocytic myeloid-derived suppressor cells (M-MDSCs) and macrophages (fig. S8E). Neutrophil infiltration was significantly lower in gD^αPD-L1-treated tumors compared to gD^WT-treated tumors. Importantly, we observed an increased proportion of effector CD8⁺ T cells and a significant reduction in exhausted CD8⁺ T cells following gD^αPD-L1 treatment (fig. S8, F to H). In the gD^αPD-L1-treated group, there was selective enrichment of CD8⁺ effector memory (Tem) cells characterized by the expression of activation markers such as Gzmb, Gzmk, Cxcr3, and Klrk1 (Fig. 4, L to M and fig. S8K) (22–28). Notably, CXCR3 expression on CD8⁺ T cells was higher in the gD^αPD-L1-treated group than in the gD^WT-treated group, providing direct evidence that gD^αPD-L1 promotes the accumulation of CXCR3⁺ CD8⁺ T cells within the TME (Fig. 4N). Consistently, CD8⁺ Tem cells were strongly enriched for pathways involved in T cell-mediated immunity compared to total CD8⁺ T cells (fig. S8L). In addition, genes associated with T cell exhaustion were downregulated, while genes linked to T cell immunity and memory functions were upregulated following gD^αPD-L1 treatment (fig. S8M). To further validate these transcriptomic findings, we performed flow-cytometric analysis of tumor-infiltrating CD8⁺ T cells. Consistent with the scRNA-seq data, gD^αPD-L1 treatment significantly increased the frequencies of both CD8⁺ Tem cells and CXCR3⁺ CD8⁺ T cells compared with gD^WT treatment (Fig. 4, O and P and fig. S9, A to D).

Collectively, these data indicate that gD^αPD-L1 therapy promotes adaptive immunity by restructuring the T cell compartment, enriching for effector and memory phenotypes, and diminishing T cell exhaustion.

gD^αPD-L1 directly targets PD-L1-positive TAMs and initiates tumor regression

To determine whether the antitumor activity of gD^αPD-L1 results from direct targeting of PD-L1⁺ immune cells, we utilized a murine tumor model bearing PD-L1-knockout B16-F10 cells (Fig. 5A). Remarkably, gD^αPD-L1 treatment significantly inhibited tumor growth in this model (Fig. 5B). Similar findings were observed in another resistant tumor model with PD-L1-knockout GL261 tumors (fig. S10, A and B), indicating that gD^αPD-L1 mediates antitumor responses predominantly through targeting PD-L1⁺ immune cells. These results further suggest that, in virus-resistant and PD-L1-deficient tumors, the therapeutic efficacy of gD^αPD-L1 is mediated primarily through the targeting and reprogramming of PD-L1⁺ immune cells rather than through direct tumor cell infection.

Fig. 5. — (A) Treatment schematic. (B) Growth curves of PD-L1-knockout B16-F10 tumors (n = 7 mice/group). (C) Representative IHC images and quantification of PD-L1-positive cells in B16-F10 and MC38 tumors. Scale bars, 50 μm. For each group (n = 3), twelve high-power fields per tumor were randomly selected to quantify immune cells co-localized with PD-L1. (D) Schematic for immune cell depletion experiments. (E) Growth curves of PD-L1-knockout B16-F10 tumors after depletion of specific immune cell populations. (F) Infectivity of gD^αPD-L1 in PD-L1-positive immune cells within B16-F10 tumors. Representative IHC staining images in virus-treated B16-F10 tumors. Scale bars, 50 μm. For each group (n = 3), twelve high-power fields per tumor were randomly selected to quantify the proportion of PD-L1 and HSV-1 double-positive cells among CD68⁺, CD11c⁺, or Ly6G⁺ cells. (G) PD-L1 expression in macrophages isolated from spleens or tumors of B16-F10-bearing C57BL/6 mice. (H) Relative quantification of viral infectivity in macrophages. (I) Schematic and quantification of viral infectivity in BMDMs. (J) Flow cytometric analysis of PD-L1 levels in BMDMs after infection. (K) Co-implantation schematic with virus-infected BMDMs and tumor cells. (L and M) Growth curves of B16-F10 tumors in the presence of virus-infected WT BMDMs or PD-L1-knockout BMDMs. (N) Treatment schematic in Cd274-CKO mice inoculated with PD-L1-knockout B16-F10 cells. (O) Growth curves of PD-L1-knockout B16-F10 tumors (n = 6 mice/group). Error bars show mean ± SD from three independent experiments (G to J). Statistical analyses were performed by repeated-measures ANOVA (B, E, L, M, and O), unpaired two-tailed Student’s t test (F to H), or one-way ANOVA (C, I, and J). Mock, culture medium; Vehicle, saline. (I) and (K) were created using BioRender [Lin, C. (2026); https://BioRender.com/o8wekca, and https://BioRender.com/b5bi4oj] and (A, B, and N) were created using Adobe Illustrator.

To identify the primary PD-L1⁺ immune cell targets of gD^αPD-L1, we performed IHC staining across various tumor models. In line with scRNA-seq results (fig. S10, C and D), TAMs, neutrophils, and dendritic cells (DCs) exhibited high PD-L1 expression (Fig. 5C and fig. S10, E and F), indicating their potential as targets. Consistent with our mouse data, PD-L1 was detected in human tumor-infiltrating myeloid populations, including macrophages and DCs, providing supportive evidence for the potential applicability of gD^αPD-L1-mediated targeting of PD-L1-expressing TAMs in human tumors (fig. S10G). Depletion experiments demonstrated that removal of TAMs—but not DCs or neutrophils—significantly impaired the therapeutic efficacy of gD^αPD-L1, highlighting the critical role of TAMs in mediating gD^αPD-L1-induced tumor regression (Fig. 5, D and E and fig. S10, H to L).

We further performed IHC staining to assess in situ infection of gD^αPD-L1 in PD-L1⁺ TAMs. Treatment with gD^αPD-L1 resulted in increased viral infection of PD-L1⁺ TAMs within tumors (Fig. 5F and fig. S10M). Treatment with gD^αPD-L1 did not increase viral infection of PD-L1⁺ DCs within tumors, possibly because TAMs, which express relatively higher levels of PD-L1, are more susceptible to gD^αPD-L1 infection than DCs. Given that TAMs displayed significantly higher PD-L1 expression than splenic macrophages, gD^αPD-L1 infected TAMs more efficiently (Fig. 5, G and H and fig. S11, A and B). Additionally, we utilized bone marrow-derived macrophages (BMDMs), which possess more physiological characteristics and can be readily obtained, for subsequent functional studies. gD^αPD-L1 infected BMDMs more efficiently than gD^WT (Fig. 5I and fig. S11C). Upregulation of PD-L1 on virus-infected BMDMs could be masked by either envelope-displayed or membrane-anchored αPD-L1 CARs (Fig. 5J and fig. S11D). Notably, gD^αPD-L1-treated BMDMs, but not PD-L1-knockout BMDMs, significantly reduced tumor volume (Fig. 5, K to M and fig. S11, E to H), demonstrating that the antitumor effect of gD^αPD-L1-treated BMDMs depends on successful viral infection. Although gD^αPD-L1 could also infect bone marrow-derived dendritic cells (BMDCs) (fig. S11, I to K), adoptive transfer of gD^αPD-L1-treated BMDCs did not affect tumor growth (fig. S11, L and M), further confirming that the antitumor efficacy of gD^αPD-L1 is independent of DCs.

Finally, to assess the importance of PD-L1⁺ TAMs in gD^αPD-L1-mediated antitumor responses, we generated myeloid-specific Cd274-knockout mice (Cd274-CKO) (Fig. 5N and fig. S11, N to P). Ablation of Cd274 in myeloid cells completely abolished the therapeutic efficacy of gD^αPD-L1 (Fig. 5O), underscoring the essential role of selective infection of TAMs by gD^αPD-L1 in driving tumor regression.

gD^αPD-L1 reprograms TAMs towards a pro-inflammatory phenotype

To elucidate the mechanisms by which gD^αPD-L1 reprograms TAMs, we classify macrophages into eight subsets (Fig. 6A and fig. S12A) (22, 23). Among all TAM subpopulations, CXCL9⁺ TAMs exhibited the most pronounced differences between the gD^αPD-L1- and gD^WT-treated groups (Fig. 6B). Recent studies indicate that CXCL9, produced by TAMs, critically regulates the recruitment and localization of CXCR3-expressing stem-like CD8⁺ T (Tstem) cells, which are essential for the clinical efficacy of anti-PD-L1 therapy (29, 30). Notably, immune-suppressive TAM subsets, including lipid-associated TAMs (LA-TAMs), were reduced in tumors treated with gD^αPD-L1 (Fig. 6C). PD-L1 was highly expressed on CXCL9⁺ TAMs and was positively correlated with both CXCL9 and CXCL10 expression levels (Fig. 6D and fig. S12B). Within the TME of B16-F10 tumors, PD-L1 was the predominant entry receptor for gD^αPD-L1 infection in TAMs compared to other natural entry receptors (fig. S12, C to K), indicating that PD-L1-directed viral targeting may contribute to TAM reprogramming.

We next examined signaling pathway alterations in TAMs. Genes associated with antiviral and inflammatory responses were enriched in the gD^αPD-L1 group relative to the gD^WT group (Fig. 6E). Genes preferentially upregulated in CXCL9⁺ TAMs, compared with other TAM subsets, were associated with responses to IFN-β, viral infection, and activation of innate immune pathways (Fig. 6F). These features suggest that CXCL9⁺ TAMs acquire a heightened antiviral and inflammatory state. Such an antiviral program may limit productive viral replication in macrophages, thereby favoring functional reprogramming rather than sustained viral amplification or macrophage cell depletion.

Differential gene expression analysis revealed that genes enriched in CXCL9⁺ TAMs are involved in IFN stimulation and antigen presentation processes, while pro-tumoral genes were more highly expressed in other TAM subsets (Fig. 6G). In TAMs from gD^αPD-L1-treated tumors, both MHC-I-restricted antigen presentation and MHC-II-related genes were upregulated compared to gD^WT (Fig. 6H). Importantly, IL-10 signaling, associated with immunotherapy resistance (31, 32), was downregulated in gD^αPD-L1-treated tumors. Further gene expression analysis showed that the upregulated genes in gD^αPD-L1-treated tumors were predominantly involved in antigen processing and presentation (Fig. 6I). We also observed enhanced ligand-receptor interactions between CXCL9⁺ TAMs and CD8⁺ Tem cells in gD^αPD-L1-treated tumors, indicating an increased capacity for T cell priming and activation (Fig. 6J).

To further investigate TAM modulation by gD^αPD-L1, we profiled the dynamics of PD-L1⁺ TAMs using flow cytometry (Fig. 6K and fig. S13, A and B). The proportion of PD-L1⁺ TAMs initially declined sharply and gradually recovered after treatment, suggesting virus-induced clearance of a subset of these cells. Across multiple models, gD^αPD-L1 treatment significantly increased the proportion of CXCL9⁺ TAMs after treatment (Fig. 6, L and M and fig. S13, C to E), supporting the conclusion that gD^αPD-L1 specifically targets and reprograms PD-L1⁺ TAMs into a CXCL9⁺ phenotype. Collectively, these data demonstrate that gD^αPD-L1 mediates PD-L1-dependent infection, leading to the depletion of a subset of TAMs, with the remaining TAMs reprogrammed toward a pro-inflammatory (CXCL9⁺) phenotype.

Collectively, gD^αPD-L1 treatment reshapes TAMs toward a pro-inflammatory, immunostimulatory phenotype by activating the CXCL9/CXCL10 signaling axis and enhancing antigen-presentation capacity.

gD^αPD-L1 promotes TAM immune activation via STING-dependent CXCL9/CXCL10 signaling

To characterize the cytokine response in gD^αPD-L1-infected macrophages, we analyzed cytokine production in BMDMs following gD^αPD-L1 infection. We observed a significant increase in CXCL9 and CXCL10 secretion in the supernatants of gD^αPD-L1-infected BMDMs (Fig. 7, A and B), with levels notably higher than those seen in gD^αPD-L1-infected B16-F10 cells or BMDCs (fig. S14, A and B). Tumors treated with gD^αPD-L1 also showed markedly elevated CXCL9 and CXCL10 compared to gD^WT-treated tumors (Fig. 7C). ELISA analysis demonstrated that gD^αPD-L1 treatment significantly increased intratumoral CXCL9 and CXCL10 levels (Fig. 7D), whereas scRNA-seq analysis revealed that macrophages were the predominant source of these two chemokines after treatment (fig. S14, C to F). To confirm the antitumor activity of CXCL9 and CXCL10 produced by gD^αPD-L1-infected TAMs, we conducted depletion experiments. The therapeutic benefits of gD^αPD-L1 were eliminated by administering anti-CXCL9/10 antibodies or clodronate liposomes (Fig. 7, E and F). Moreover, myeloid-specific Cxcl9-deficient mice showed impaired responses to gD^αPD-L1 therapy (Fig. 7, G and H and fig. S14, G and H), confirming that CXCL9/CXCL10 production following TAM targeting is crucial for gD^αPD-L1-mediated antitumor activity.

Fig. 7. — (A) Relative levels of indicated cytokines and chemokines in the supernatants of BMDMs under various treatments. (B) Concentrations of CXCL9 and CXCL10 in BMDM supernatants after treatment. (C) Levels of CXCL9 and CXCL10 in B16-F10 tumors following treatment. (D) Levels of CXCL9 and CXCL10 in TAMs isolated from tumors following treatment. (E) Schematic of experimental design for macrophage depletion or CXCL9/CXCL10 blockade. (F) Growth curves of PD-L1-knockout B16-F10 tumors (n = 8 mice/group). (G) Treatment scheme for Cxcl9-CKO mice inoculated with PD-L1-knockout B16-F10 cells. (H) Growth curves of PD-L1-knockout B16-F10 tumors (n = 11 mice/group). (I) CXCL9 and CXCL10 production by BMDMs infected with gD^αPD-L1 in the presence or absence of Syk, STING, or STAT1 inhibitors. (J) Treatment scheme for Sting-KO mice inoculated with PD-L1-knockout B16-F10 cells. (K) Growth curves of PD-L1-knockout B16-F10 tumors (n = 10 mice/group). (L) Supernatant levels of CXCL9 and CXCL10 in Sting-knockout BMDMs after viral infection. Error bars show mean ± SD from three independent experiments (B-D, I, and L). An ordinary one-way ANOVA (B to D, I, and L) and a repeated measures ANOVA (F, H, and K). Mock, culture medium; Vehicle, saline. Cartoons were created using Adobe Illustrator (E, G, and J).

To dissect the signaling pathway underlying CXCL9/CXCL10 induction in infected macrophages, we used specific kinase inhibitors (33–35). STING inhibition markedly reduced CXCL9/CXCL10 production, whereas inhibition of Syk or STAT1 had no significant effect (Fig. 7I). Importantly, gD^αPD-L1 failed to elicit antitumor activity in STING-knockout (Sting-KO) mice (Fig. 7, J and K), and STING-deficient BMDMs did not upregulate CXCL9/CXCL10 after gD^αPD-L1 infection (Fig. 7L and fig. S14I). Additionally, high CXCR3 expression on intratumoral T cells was observed in gD^αPD-L1-treated tumors, highlighting its role in T cell trafficking and function (fig. S14J). The antitumor efficacy of gD^αPD-L1-treated BMDMs was abrogated by FTY720 treatment, indicating a requirement for migratory T cells in mediating this effect (fig. S14, K and L). Collectively, these findings demonstrate that cGAS/STING-mediated CXCL9/CXCL10 secretion by gD^αPD-L1-targeted TAMs enhances T cell infiltration and suppresses tumor growth.

gD^αPD-L1 sensitizes tumors to cancer immunotherapy and exhibits a favorable safety profile

To assess the safety profile of gD^αPD-L1, we evaluated systemic toxicity following high-dose intravenous administration. Serum biochemistry analyses revealed no evidence of hepatotoxicity, cardiotoxicity, or nephrotoxicity in mice treated with gD^αPD-L1 (Fig. 8, A to E), and body weights remained stable (Fig. 8F). Histopathological examination detected no treatment-related abnormalities in any examined organs (Fig. 8G). Hematological analyses showed no significant leukocytosis, anemia or other abnormalities (Fig. 8, H to K and fig. S15, A to C). These results indicate that gD^αPD-L1 is safe and well-tolerated in mice.

Fig. 8. — (A to E) Plasma levels of alanine transaminase (ALT), aspartate aminotransferase (AST), creatinine (CREA), urea (UREA) and creatine kinase (CK) at the indicated time points upon virus injection (5 × 10⁷ PFU). (F) Monitoring of body weights (n = 5 mice/group). (G) Representative images of H&E-stained sections from various organs on day 7. Scale bars, 100 μm. (H to K), Blood counts of white blood cells (WBC), lymphocytes, granulocytes, monocytes at specified time points following viral injection (5 × 10⁷ PFU). (L) Schematic of treatment protocol evaluating the therapeutic efficacy of oHSV in combination with ICB therapy. (M) Growth curves of B16-F10 tumors (n = 6 or 7 mice/group). (N) Schematic of treatment protocol evaluating oHSV in combination with OT-1 cell adoptive transfer. (O) Growth curves of B16-F10-OVA tumors (n = 7 or 8 mice/group). (P) Treatment scheme for C57BL/6 mice inoculated with B16-F10-lucM cells. (Q) Tumor growth measured by luciferase-based bioluminescence imaging. (R) Survival curves. Error bars show mean ± SD . A repeated measures ANOVA (A to F and H to K) and an unpaired Student’s two tailed t test (A, H, and I) and a repeated measures ANOVA (M and O) and a log-rank test (R) were used. Vehicle, saline; i.v., intravenous injection. Cartoons were created using Adobe Illustrator (L, N, and P).

We next evaluated the potential of gD^αPD-L1 to enhance the efficacy of cancer immunotherapy. Combination therapy with gD^αPD-L1 and either anti-PD-1 or anti-CTLA-4 antibodies resulted in significantly improved antitumor effects compared to monotherapy (Fig. 8, L and M). We further examined the synergy between gD^αPD-L1 and adoptive T cell therapy (Fig. 8N). Mice treated with both gD^αPD-L1 and OT-1 cells exhibited markedly superior tumor growth control compared to those receiving gD^WT and OT-1 cells or any single treatment (Fig. 8O). These findings highlight the capacity of gD^αPD-L1 to overcome resistance to ICB or adoptive T cell therapy.

Systemic delivery of oHSV in a lung metastasis model demonstrated that mice treated with active gD^αPD-L1 had superior control of lung metastasis and prolonged survival compared to those receiving inactivated gD^αPD-L1, with no obvious toxicity observed as assessed by body weight, behavior, or overall condition (Fig. 8, P to R).

Together, these results demonstrate a robust strategy that combines dual targeting of tumor cells and TAMs in the TME with PD-L1 blockade to rejuvenate exhausted T cell responses. These findings highlight the therapeutic potential of using OVs to retarget inhibitory immune checkpoints on immunosuppressive cells, providing a promising avenue for the development of safe and effective cancer immunotherapies.

DISCUSSION

Although the direct intratumoral injection of OVs is effective in treating locoregional melanoma lesions, a significant portion of patients either fail to respond or experience disease recurrence after an initial response (5, 36). Furthermore, its efficacy against disseminated metastatic disease remains limited (37). Understanding the underlying causes of this unresponsiveness and developing strategies to enhance the efficacy and response rates of virotherapy are therefore essential. OVs face several challenges, notably from the host immune system, which can rapidly clear the viruses before they exert their therapeutic effects (9). Additionally, the heterogeneity and complexity of the TME across different tumors can impede viral distribution and oncolysis, thereby diminishing therapeutic outcomes (37, 38). Recent advances in genetic engineering offer avenues to improve the tumor selectivity of OVs and to arm the viruses with multiple therapeutic “weapons,” potentially expanding their efficacy and clinical relevance in cancer treatment (39). Building on these insights, we developed a CAR-directed oHSV engineering platform capable of retargeting cells through the receptor-of-interest and displaying antibody-based drugs on the viral surface. While this PD-L1-targeted CAR is fused to a viral protein—distinct from traditional CARs in CAR-T cells, which contain T cell activation domains—both approaches utilize chimeric receptors for retargeting purposes. Notably, CAR-directed viral engineering elicited potent antitumor responses by dually targeting PD-L1-positive tumor cells and TAMs.

Nectin-1 mediates HSV entry more efficiently than other receptors. Nevertheless, variation in Nectin-1 expression across tumor types, and even within tumors of the same histology, limits its utility as a biomarker for predicting HSV-mediated oncolysis (40). Consequently, broadening the viral tropism and increasing infection efficiency are prerequisites for more effective oncolysis of target cells. In this study, we demonstrated that bypass infection occurs through high-affinity interactions between gD^αPD-L1 and PD-L1 receptors, facilitating viral entry into PD-L1-positive cells. Our engineering strategy allows the chimeric gD to also bind to its natural receptors, enabling gD^αPD-L1 to utilize three infection pathways simultaneously and thereby ensuring productive infection of target cells. Compared to Nectin-1 and HVEM, PD-L1 is more broadly and strongly expressed across cancer types (41). Notably, our results demonstrated that PD-L1 expression was significantly upregulated in an autocrine IFN milieu, potentially inducing a bystander effect that promotes gD^αPD-L1 infection and spread among tumor cells, thus enhancing oncolysis (fig. S16).

Developing OVs that can evade macrophage-mediated inactivation remains challenging, as macrophages are adept at phagocytosing and destroying viruses (11). Therefore, robust viral infection specifically targeting these detrimental cells could reprogram their protumoral genetic profiles, yielding enhanced therapeutic effects. Our data showed that gD^αPD-L1 initiates PD-L1-dependent infection in TAMs, depletes them, and stimulates their immune activation through a STING-dependent pathway, amplifying CXCL9/CXCL10 signaling. These chemokines recruit effector T cells, which are pivotal to the antitumor immune response (fig. S16). This finding is consistent with previous studies showing that activation of STING signaling in TAMs augments antitumor immunity via TAM reprogramming (42, 43), that elevated levels of macrophage-derived CXCL9 and CXCL10 are associated with effective ICB responses (24, 44). However, the precise molecular determinants of TAM fate remain to be fully defined. The divergent fates of TAM subsets after gD^αPD-L1 treatment likely reflect the interplay between receptor-dependent viral entry and cell-intrinsic antiviral programs. Although PD-L1 facilitates initial engagement and preferential infection, its abundance alone does not determine whether TAMs are eliminated or reprogrammed. We propose that TAMs with weaker antiviral defenses permit productive HSV replication and undergo lytic death, whereas those with stronger antiviral programs restrict replication while sensing viral components, thereby favoring STING-dependent reprogramming into CXCL9⁺ TAMs. Consistent with this model, CXCL9⁺ TAMs displayed enhanced antiviral and interferon-response signatures relative to other TAM subsets. Thus, TAM reprogramming and depletion may represent alternative outcomes of the same PD-L1-directed viral infection, determined by the balance between productive HSV replication and intrinsic antiviral responses. Functionally, reprogrammed TAMs may serve dual and temporally distinct roles during therapy: they may initially amplify antitumor immunity by inducing CXCL9/CXCL10 and recruiting CXCR3⁺ CD8⁺ T cells, and subsequently contribute to viral restriction and clearance in vivo. In this framework, gD^αPD-L1 transiently converts an immunosuppressive myeloid niche into a proinflammatory state sufficient to initiate a durable downstream antitumor immune cascade, even if later macrophage-mediated antiviral activity limits viral persistence.

Using scRNA-seq and flow cytometry, we assessed dynamic changes in TAM phenotypes following treatment and found an expansion of proinflammatory CXCL9⁺ TAMs with elevated IFN and antigen presentation signatures in conjunction with increased CXCR3⁺ CD8⁺ Tem cells. Prior studies suggest that CD8⁺ Tem cells expressing high CXCR3 and GZMK levels, but low TOX, likely represent tumor-specific TILs, which persistently engage with antigen-presenting cells in the TME and exhibit enhanced cytotoxic activity against tumor cells (45, 46). We thus propose that inducing IFN signaling in TAMs may restore anti-tumor immunity in “cold” tumors. Although cDC1s are central to efficient CD8⁺ T cell cross-priming, gD^αPD-L1 retained partial efficacy in Batf3-deficient mice, suggesting that other myeloid populations can partially compensate for cDC1 loss. Among these, gD^αPD-L1-induced CXCL9⁺ TAMs displayed enhanced MHC-I antigen-processing and antigen-presentation programs, consistent with a role in sustaining local CD8⁺ T cell recruitment, maintenance, and effector function. Thus, rather than replacing cDC1s as classical cross-priming cells, CXCL9⁺ TAMs may help preserve intratumoral T cell immunity when cDC1 function is compromised. Whether they can directly prime naïve CD8⁺ T cells in the absence of cDC1s warrants further investigation.

OVs are primarily administered intratumorally in clinical settings; thus, exploring intravenous delivery is crucial for expanding their therapeutic potential. While systemic administration of gD^αPD-L1 demonstrated superior therapeutic efficacy in a B16-F10 lung metastasis model, the multifaceted antitumor effects of gD^αPD-L1, including improved tumor selectivity, oncolytic activity, T cell reinvigoration, TAM immune activation, and enhanced sensitivity to other immunotherapies, were evident. However, systemic delivery may permit viral infection of other PD-L1-expressing cells, such as dendritic cells, macrophages, and fibroblasts. Notably, we observed no significant toxicity in preclinical models, even at doses up to 5 × 10⁷ PFU. This may be attributed to (i) preferential viral targeting of the TME with high PD-L1 expression, particularly in cells expressing PD-L1 at high levels, and (ii) the tumor-selective nature of OVs, which renders normal cells inherently resistant to infection and thereby limits viral replication and dissemination in healthy tissues. Though off-target effects cannot be excluded, this approach appears to be relatively safe, especially for intratumoral administration. Although human melanoma scRNA-seq data showing enriched PD-L1 expression in TAMs further support the translational rationale for PD-L1-directed TAM targeting in human cancers, this CAR-directed viral engineering strategy could feasibly be adapted to a human version of the virus by replacing the murine PD-L1-specific nanobody with a human PD-L1-specific nanobody. Nevertheless, additional work, including tropism validation and efficacy evaluation, will be required in future studies.

In conclusion, our study illuminates the potential of targeting of PD-L1-specific TAMs using oHSV, offering a foundation for the development of CAR-directed OVs to overcome resistance in tumors. The successful clinical translation of this strategy could address a significant unmet need for cancer patients who are unresponsive to current immunotherapies or oHSV treatments.

MATERIALS AND METHODS

Animals

BALB/c-Nude mice (D000521), BALB/cJGpt (N000020), Cxcl9^fl/fl mice (T052171), and C57BL/6JGpt (N000013) mice were sourced from GemPharmatech. OT-1 TCR transgenic mice (003831), Batf3^−/− mice (013755), and LysM^Cre mice (004781) were obtained from The Jackson Laboratory. Cd274-KO (NM-KO-18044) and Sting-KO mice (NM-KO-2105967) were provided by the Shanghai Model Organisms Center. Cd274^fl/fl mice were obtained from Jizhou Zhang’s laboratory. LysM^Cre mice were crossed with Cxcl9^fl/fl mice to generate myeloid-specific Cxcl9 knockout mice (Cxcl9^fl/fl LysM^Cre), with sex-matched Cxcl9^fl/fl littermates serving as wild-type (WT) controls. The following primers were used: primer 1 (forward) TGCCTTCTTGGCGTAGGTATTG, primer 2 (reverse) ATTCACGTGGACTGAAGTCAGCC. Similarly, LysM^Cre mice were crossed with Cd274^fl/fl mice to create myeloid-specific Cd274 knockout mice (Cd274^fl/fl LysM^Cre), with sex-matched Cd274^fl/fl littermates as WT controls. The following primers were used: primer 1 (forward) TCCTGTTTCCCACCTGCTGCTTCAG, primer 2 (reverse) TCTGCAACGTCTGCCTGGAGAAGAC. Female mice aged 6–10 weeks were used in the study. All mice were maintained under pathogen-free conditions, adhering to a 12-hour dark/light cycle and standard temperature and humidity (22 ± 2°C and 55 ± 5%, respectively). Tumor measurement were performed by investigators blinded to treatment allocation. Tumor size was measured using a digital caliper, and tumor volume was calculated using the formula: volume = (width)² × length/2, where length represents the largest tumor diameter and width represents the perpendicular tumor diameter. Humane endpoints were defined as a progressively growing tumor reaching 17 mm in its longest dimension, tumor ulceration or necrosis, or any other condition requiring euthanasia according to the animal protocol approved by the Institutional Animal Care and Use Committee at Xiamen University (XMULAC20210129).

Cell culture

293 T (CRL-3216), U-2 OS (HTB-96), B16-F10 (CRL-6475), EMT-6 (CRL-2755), EO771 (CRL-3461), LTPA (CRL-2389), YUMM1.7 (CRL-3362), 4 T1 (CRL-2539), and CT26.WT (CRL-2638) cells were purchased from the American Type Culture Collection (ATCC). MB49 were sourced from MeisenCTCC (CTCC-400-0344). MC38 and GL261 cells were obtained from Jian Qiao’s laboratory. Jurkat-Lucia NFAT cells were obtained from InvivoGen (jktl-nfat). B16-F10, MB49, EO771, 293 T, U-2 OS, GL261, and MC38 cell lines were cultured in DMEM supplemented with 10% fetal bovine serum (FBS), 1 × GlutaMax, and 100 U/ml penicillin–streptomycin. CT26.WT and 4 T1 cells were cultured in RPMI-1640 medium supplemented with 10% FBS, 1 × GlutaMax, and 100 U/ml penicillin–streptomycin. LTPA cells were cultured in EMEM medium supplemented with 10% FBS, 1 × GlutaMax, and 100 U/ml penicillin–streptomycin. YUMM1.7 cells were cultured in DMEM: F-12 medium supplemented with 10% FBS, 1 × non-essential amino acids solution, and 100 U/ml penicillin–streptomycin. Jurkat-Lucia™ NFAT cells were cultured in IMDM medium supplemented with 10% FBS, 1 × GlutaMax, and 100 U/ml penicillin–streptomycin. EMT-6 cells were cultured in Waymouth’s MB 752/1 medium supplemented with 15% FBS, 1 × GlutaMax, and 100 U/ml penicillin–streptomycin. All cell lines were regularly tested for mycoplasma contamination sing the LookOut Mycoplasma PCR Detection Kit (Sigma–Aldrich, MP0035). Primary bone marrow-derived macrophages (BMDMs) and bone marrow-derived dendritic cells (BMDCs) were obtained from C57BL/6 mice using protocols described below. Primary mouse T cells were purified from splenocytes using a mouse CD8⁺ T cell isolation kit (STEMCELL, 19853). PBMCs were cultured in RPMI 1640 medium supplemented with 20% FBS and 100 U/ml penicillin-streptomycin.

Constructs

To construct the shuttle vector PUC57-P0 for oHSV recombination, we introduced both a 959 bp DNA sequence upstream and a 412 bp DNA sequence downstream of the RL2 gene’s initiation and termination codons, respectively, into the PUC57 vector (Sangon, B522201). The dICP0 transfer vector plasmid was created by incorporating a gene cassette containing a cytomegalovirus (CMV) promoter, a cDNA for eGFP protein expression, and an SV40 polyA sequence into the PUC57-P0 plasmid using NcoI restriction sites. Similarly, to assemble the PUC57-gD vector for gD recombination, an 829 bp DNA segment upstream and an 817 bp DNA segment downstream of the US6 gene’s initiation and termination codons were inserted into a PUC57 vector. The chimeric gene sequence for a mouse PD-L1 nanobody (αPD-L1) (47) fused to gD (gD-αPD-L1) was synthesized by integrating the αPD-L1 cDNA in replace of the gD coding region (26–50 amino acids) alongside a G₄S linker sequence. The gD^αPD-L1 transfer vector plasmid was created by inserting a gene cassette containing a CMV promoter, the gD-αPD-L1 sequence, and an SV40 polyA sequence into the PUC57-gD plasmid using the restriction enzyme sites PstI. Mouse PD-L1, human Nectin-1, human HVEM, OVA and the luc gene were synthesized by GENEWIZ and cloned into the Lenti-Puro vector (48) with a puromycin selection marker. The cDNA encoding for the extracellular domain (ECD) of PD-L1 and the αPD-L1 sequence were synthesized and separately cloned into the pCMV6 expression vector (OriGene, PS100001), each tagged with a C-terminal hIgG or His tag, respectively. To generate αAPC cells, a chimeric gene sequence combining the anti-human CD3 (OKT3) single-chain variable fragment (scFv) with the human CD28 transmembrane domain was synthesized and inserted into the Lenti-Puro vector, which included a puromycin selection cassette.

CRISPR–Cas9-mediated PD-L1 deletion was performed as previously described (48). Guide RNAs targeting mouse PD-L1 (gRNA#1 sequence: GTATGGCAGCAACGTCACGA, gRNA#2 sequence: GCTTGCGTTAGTGGTGTACT) were cloned into LentiCRISPR v2 (Addgene, 52961).

Stable cell lines

The B16-F10-luc and GL261-luc cell lines were transduced using lentiviruses produced in 293 T cells using packaging plasmids pMD2.G (Addgene, 12259) and psPAX2 (Addgene, 12260), along with a lentiviral vector encoding the firefly luciferase gene (luc). The B16-F10-lucM cell line, derived from the murine parental B16-F10-luc line, exhibited high metastatic capacity. It was isolated from a metastatic lung nodule that arose in the lung metastasis model (C57BL/6 J background) after intravenous injection of B16-F10-luc cells. Stable expression of PD-L1, Nectin-1, HVEM or the tumor antigen ovalbumin (OVA) in B16-F10 tumor cells was achieved using lentiviruses containing the respective genes. PD-L1 knockout in tumor cells was established using lentiviruses with specific sgRNAs, followed by single-cell cloning. The αAPC cells, derived from 293 T cells, were generated by infecting 293 T cells with lentiviruses encoding a membrane-associated OKT3 scFv.

Virus construction

Recombinant viruses were generated using a previously described cell-based recombination method. (49) The ICP0-null virus, oHSV-gD^WT, was developed in our laboratory by replacing both copies of the ICP0 coding sequences with the eGFP gene (49, 50). oHSV-gD^αPD-L1, derived from the oHSV-gD^WT backbone, features a modification at the N terminus of gD, with αPD-L1 fused to the gD domain spanning amino acids 51–394. Virus titers were quantified on U-2 OS monolayers employing a standard plaque assay (51). UV-inactivated viruses were prepared using a UV Stratalinker 2400 instrument (Stratagene) set to 360 mJ/cm² for five minutes, a duration proven adequate for complete viral inactivation (21).All experiments involving recombinant attenuated HSV-1 were conducted under BSL-2 practices.

Protein purification

Expi293F cells (Gibco, A14527) were transfected with plasmids encoding individual proteins and maintained at 37°C for six days. αPD-L1 was purified from mammalian cell supernatants using a HisTrap HP purification column (Cytiva, 17524801) using the C-terminal His tag on the PD-L1 nanobody. PD-L1-hIgG was purified from mammalian cell supernatants using a HiTrap Protein G HP antibody purification column (Cytiva, 17040501) using the C-terminal hIgG tag on the extracellular domain of PD-L1.

αPD-L1 functional assays

The blocking activity of αPD-L1 was assessed using a blocking chemiluminescence immunoassay (CEIA). Briefly, 96-well plates were coated with 100 ng/well of mouse PD-1 Fc chimera protein (BPS bioscience, 71116), followed by blocking nonspecific binding with PBS containing 5% BSA. gD^αPD-L1 samples were initially diluted from 2.1 × 10⁹ PFU/ml in PBS containing 20% CBS and then subjected to two-fold serial dilutions across eight gradients. Subsequently, each dilution, along with 100 ng/well of biotinylated mouse PD-L1-hIgG (BPS bioscience, 71119), was added to the wells and incubated for 1 hour before washing, reaction, and detection steps. Signal detection was performed with a chemiluminescence reader (Berthold) following the manufacturer’s protocol. The inhibitory ratio was defined as: % inhibitory = 100 × [1 − (average value for each dilution / average value for the control)]. Data were analyzed using nonlinear dose-response regression analysis with GraphPad Prism software. The bioactivity of αPD-L1 was evaluated using a reporter gene assay. A total of 1 × 10⁴ αAPC cells and 5 × 10³ Jurkat-Lucia™ NFAT cells were seeded into wells, followed by the addition of viruses or specified proteins to the culture systems. After 24 hours of co-culture, luciferase activity was quantified using QUANTI-Luc reagent (InvivoGen, rep-qlc2).

Immunofluorescence and immunohistochemistry

For cellular staining, cells were seeded in CellCarrier 96-well microplates (PerkinElmer) at a density of 1,000 cells per well and incubated for 24 hours. The immunostaining process included washing the cells with PBS, fixing them in 4% paraformaldehyde for 20 minutes at room temperature, and blocking with 10% normal goat serum in PBST buffer for 30 minutes at room temperature. Subsequently, the cells were incubated overnight at 4°C with PD-L1-hIgG (BPS bioscience, 71119), followed by incubation with DyLight 650-labeled secondary antibodies (ThermoFisher, SA5–10137) at room temperature for 45 minutes. Finally, the nuclei were counterstained with DAPI, and images were captured using a Leica TCS SP8 X confocal fluorescence microscope with a 100× objective lens. For staining formalin-fixed, paraffin-embedded (FFPE) sections of 4–6 μm thickness, deparaffinization, rehydration, and antigen retrieval were performed. The slides were stained with the indicated antibodies, followed by subsequent antibody detection using an OPAL 6-PLEX manual detection kit (AKOYA, NEL811001KT). Corresponding fluorophores and spectral DAPI were applied following the manufacturer’s instructions. Images of the stained slides were captured using a LEICA DM6B microscope with LAS X software as well as the Pannoramic 250 Flash III scanner (3DHISTECH) with Pannoramic Scanner software. The images were subsequently cropped and analyzed using SlideViewer software and its QuantCenter feature.

Flow cytometry analysis

To examine cell-surface PD-L1 expression, mouse tumor cells were treated with varying concentrations of IFN-γ (R&D Systems, 485-MI-100) or IFN-β (R&D Systems, 8234-MB-010) for 24 hours to induce PD-L1 expression and subsequently stained with APC-labeled anti-PD-L1 antibodies (Biolegend, 124312) for 30 minutes on ice. Membrane-bound proteins were detected using appropriate fluorescein-conjugated antibodies for 30 minutes on ice. For analysis of the number and function of tumor-infiltrating lymphocytes (TILs), tumors were injected intratumorally with the virus in two doses administered every two days, and were harvested two days following the final treatment. Tumor tissues were then digested and processed as previously described (21) and subjected to flow cytometry analysis using the following gating strategy to define cell populations: CD4⁺ T cells (CD45⁺ CD4⁺), CD8⁺ T cells (CD45⁺ CD8⁺), IFN-γ⁺ CD4⁺ T cells (IFN-γ⁺ CD45⁺ CD4⁺), GZMB⁺ CD4⁺ T cells (GZMB⁺ CD45⁺ CD4⁺), IFN-γ⁺ CD8⁺ T cells (IFN-γ⁺ CD45⁺ CD8⁺), GZMB⁺ CD8⁺ T cells (GZMB⁺ CD45⁺ CD8⁺), CD8⁺ Tem cells (CD44⁺ CD62L⁻ CD8⁺), CXCR3⁺ CD8⁺ T cells (CXCR3⁺ CD8⁺), macrophages in the spleen (CD45⁺ CD11b⁺ F4/80⁺), TAMs in the tumor (CD45⁺ CD11b⁺ F4/80⁺), PD-L1⁺ TAMs (CD45⁺ CD11b⁺ CD68⁺ PD-L1⁺), and CXCL9⁺ TAMs (CD45⁺ CD11b⁺ F4/80⁺ CXCL9⁺) (table S2). The cell suspensions were stained with Zombie Aqua™ Fixable Viability Kit (BioLegend, 423102) for 10 minutes at 4°C. Fc receptors were then blocked using anti-CD16/32 (BD Biosciences, 553141) for 15 minutes at 4°C. Subsequently, cell surface proteins were stained with the appropriate antibodies for 30 minutes at 4°C. Following permeabilization and fixation (BD Biosciences, 555028), intracellular proteins were stained 30 minutes at 4°C. After washing with PBS, samples were analyzed using a BD LSRFortessa™ X-20 flow cytometer. Flow-cytometry gating was performed blinded to treatment allocation.

Attachment assay

The attachment assay was conducted on B16-F10 cells seeded in 6-well plates. Tumor cells were pre-treated with 250 pg/ml of IFN-γ (R&D Systems, 485-MI-100) or IFN-β (R&D Systems, 8234-MB-010) for 24 hours to induce PD-L1 expression. Both the cells and viruses were pre-chilled at 4°C for 15 minutes prior to co-incubation for 30 minutes at 4°C. The B16-F10 cells were then washed five times with PBS to remove unbound viruses, and subsequently analyzed by flow cytometry using anti-gD antibodies (4A3) (52).

Cell cytotoxicity assays and high-content screening microscopy

Each of the specified cell lines was seeded at 5,000 cells per well in 96-well plates using 100 μl of complete medium and cultured in triplicate. The cells were exposed to different infectious doses of viruses, a predefined multiplicity of infection (MOI), or predefined concentrations of IFN-α (R&D Systems, 12100–1), IFN-β (R&D Systems, 8234-MB-010), IFN-γ (R&D Systems, 485-MI-100), anti-IFNAR-1 antibody (BioXCell, BE0241), HVEM protein (Sinobiological, 10334-H08H), and Nectin-1 protein (Sinobiological, 11611-H08H). Cell viability was assessed three days post-infection using a CCK8 assay (MedChemExpress, HY-K0301), with optical absorbance measured at 450 nm via a microplate reader (Thermo Fisher Scientific). The effective concentration 50 (EC₅₀), indicating the dose required to eliminate 50% of the cell population, was determined through nonlinear, dose-response regression analysis using GraphPad Prism software. For confocal microscopy imaging, cells were plated in CellCarrier 96-well microplates (PerkinElmer) at a density of 10,000 cells per well, cultured for 12 hours, and subsequently infected with oHSV at the specified MOI and/or subjected to varying treatments. Two days after infection, images of cells were acquired with the Opera Phenix Plus High-Content Screening System (PerkinElmer).

Immunoblots

Cell lysates were prepared using RIPA lysis buffer supplemented with protease inhibitor cocktails (MedChemExpress, HY-K0011) and then subjected to SDS-polyacrylamide gel electrophoresis (SDS–PAGE). Following transfer to nitrocellulose membranes, the proteins were probed with specific primary antibodies followed by horseradish peroxidase (HRP)-conjugated secondary antibodies (Abcam, ab97265 or ab97225). The following primary antibodies were used: ICP0 (Santa Cruz, sc-53070), gH (Virusys Corporation, H1A258–100), 4A3 (52), and β-actin (Proteintech, 60008–1-Ig). Membrane visualization was conducted using the Fusion FX SPECTRA system (VILBER).

Cytokine analysis

High-plex Luminex assays were used to measure cytokines in cell culture supernatants with the ProcartaPlex mouse cytokine & chemokine panel (Invitrogen, EPX360–26092-901) on a Luminex 200 instrument system. For cytokine analysis, tumor homogenates were prepared by immersing tumors in 1 ml of PBS and then mechanically disrupting them with a gentleMACS tissue dissociator. Bone marrow-derived macrophages (BMDMs) were treated with either the oHSV or inhibitors, including C-176, Fludarabine, and R406, obtained from MedChemExpress (HY-112906, HY-B0069, HY-12067). The concentrations of CXCL9 and CXCL10 in mouse tumors or cell culture supernatants were measured using the CXCL9/MIG Quantikine ELISA Kit (R&D Systems, MCX900) and the CXCL10/IP-10/CRG-2 DuoSet ELISA Kit (R&D Systems, DY466–05), respectively. Similarly, the concentrations of IFN-α, IFN-β, and IFN-γ in mouse tumors or cell culture supernatants were determined using the IFN-α Quantikine ELISA Kit (R&D Systems, MFNAS0), IFN-β Quantikine ELISA Kit (R&D Systems, MIFNB0), and IFN-γ Quantikine ELISA Kit (R&D Systems, MIF00), respectively.

Cell separation assays

CD8⁺ OT-1 T cells were isolated from mouse spleen single-cell suspensions using a mouse CD8⁺ T cell isolation kit (STEMCELL, 19853). Similarly, CD11b⁺ cells were isolated from mouse tumors or spleen single-cell suspensions by first employing a dead cell removal kit (STEMCELL, 17899), followed by a mouse CD11b positive selection kit (STEMCELL, 18970). The samples were then seeded in 24-well plates and infected with viruses at specified MOI. Cell infectivity was assessed two days post-infection using flow cytometry.

Mouse procedures

In subcutaneous tumor models, 5 × 10⁵ tumor cells suspended in 100 μl of PBS were inoculated subcutaneously into the right flank of the specified mice and allowed to establish for seven days. Once tumors reached the indicated volume 70–110 mm³, mice were were randomized into treatment groups and injected intratumorally with oHSV at a dose of 3 × 10⁷ PFU, followed by additional injections on days 2, 4, and 6, or on days 3 and 6 after the initial treatment, unless otherwise indicated. Specific treatment schedules are shown in the corresponding experimental schemes.

For generating BMDMs, bone marrow from the femurs and tibias of C57BL/6 WT, Sting-KO or Cd274-KO mice was harvested and cultured in macrophage medium composed of RPMI 1640 supplemented with 10% FBS, 1 × GlutaMax, 100 U/ml penicillin–streptomycin, and 20 ng/ml recombinant mouse M-CSF (R&D Systems, 416-ML-050). To generate BMDCs, bone marrow was harvested and cultured in a medium consisting of RPMI 1640 supplemented with 10% FBS, 1 × GlutaMax, 100 U/ml penicillin-streptomycin, 25 ng/ml recombinant mouse GM-CSF (Sino Biological, 51048-MNAH), and 10 ng/ml recombinant mouse IL-4 (R&D Systems, 404-ML-025). After seven days of induction, 25 ng/ml recombinant mouse TNF-α (Novoprotein, CF09) was added to the culture medium for an additional two days. In co-implantation experiments involving BMDMs or BMDCs, the cells were pre-treated for 24 hours with either a vehicle or oHSV viruses at an MOI of 10 PFU. After washing, they were mixed with 1 × 10⁵ B16-F10 or MC38 cells in a 1:2.5 ratio.

Lymphocyte trafficking was inhibited by intravenous injection of 50 μg of FTY720 (MedChemExpress, HY-12005) one day prior to tumor inoculation, with continued treatment every two days for six days. Immune cells were depleted by intraperitoneally injecting 200 μg of each depleting antibody (and their respective control antibodies) two days before virus treatment. The following antibodies were used: Ly6G (Leinco, L280), DCIR2 (Leinco, D112), CSF-1R (Leinco, C2169), NK1.1 (Leinco, N123), CD8a (BioXCell, BE0004–1) and CD4 (Leinco, BE0003–1). This regimen was continued every two days for a total of eight days. In vivo depletion of CXCL9/10 was accomplished by pre-treating mice with 10 mg/kg of anti-CXCL9 (BioXCell, BE0309) and anti-CXCR3 (BioXCell, BE0249) or control antibodies (BioXCell, BE0091) two days before virus treatment, with continued treatment every two days for eight days.

In experiments combining oHSV and immune checkpoint therapy, B16-F10 tumor-bearing mice received an intratumoral injection of oHSV at a dose of 3 × 10⁷ PFU, along with an intravenous injection of 200 μg of either anti-PD-1 (Leinco, P362) or anti-CTLA-4 (Leinco, C2855) antibodies. This treatment was followed by additional injections on days 2 and 4 after the initial treatment.

In experiments combining oHSV and T cell therapy, B16-F10-OVA tumor-bearing mice received an intratumoral injection of oHSV at a dose of 3 × 10⁷ PFU, followed by a repeat dose on day 4 post-treatment. 1 × 10⁶ OT-1 T cells in 500 μl of PBS were then adoptively transferred into the mice two days after virus treatment, with a repeat injection on day 4.

For the lung metastasis model, 5 × 10⁵ B16-F10-lucM cells suspended in 500 μL of PBS were injected intravenously into the tail veins of C57BL/6 mice and allowed to establish for 5 days. The virus was administered intravenously at a dose of 3 × 10⁷ PFU, with additional doses given on days 2, 4, and 6 after the initial treatment. Tumor growth was monitored using a bioluminescence imaging system (PerkinElmer IVIS Lumina II).

Blood cell analysis

In BALB/c mice, a strain susceptible to HSV (53), the virus was administered intravenously at a dose of 5 × 10⁷ PFU in 0.5 ml. Blood samples were collected on days 0, 1, 3, 5, and 7 post-initial treatment, resulting in five collections, using plastic K2EDTA tubes. Analysis of white blood cells (WBC), platelets (PLT), lymphocytes, red blood cells (RBC), hemoglobin (HGB), monocytes, and granulocytes was conducted using the Mindray Hematology Analyzer BC-30 Vet, following the manufacturer’s guidelines.

Serum chemistry

Blood samples were collected on days 0, 1, 3, 5, and 7 after the initial treatment, resulting in five collections stored in plastic tubes. Following centrifugation, the sera were aliquoted and immediately stored at −80°C for subsequent batch processing. The analyses of creatine kinase (CK), creatinine (CREA), urea, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were performed using the Mindray BS-200 Analyzer with the appropriate detection kits, following the manufacturer’s guidelines.

Single-cell RNA (scRNA) sequencing

The tumors were excised and homogenized using a gentleMACS tissue dissociator with a Tumor Dissociation Kit (Miltenyi, 130–096-730) for mice. The resulting cell mixture was filtered through a 70-μm cell strainer to obtain a single-cell suspension. Following centrifugation, the supernatant was discarded, and the pellet was resuspended in 1 ml of cold PBS supplemented with 2% FBS. The cell suspensions were stained with 7-AAD (Invitrogen, L34957) and APC/Cyanine7-labeled anti-mouse CD45 antibodies (Biolegend, 109824). Subsequently, fluorescence-activated cell sorting (FACS) was employed to isolate CD45⁺ cells, ensuring a cell viability exceeded 90%. These sorted cells were then prepared for single-cell RNA sequencing (scRNA-seq) using the Chromium Next GEM Single Cell 3′ Kit v3.1, following the manufacturer’s protocols. Approximately 10,000 cells were loaded onto a chip to produce the Gel Beads-in-Emulsions, followed by reverse transcription, amplification of complementary DNA, and library preparation. Quantification and size determination of the sequencing library were conducted using Qubit and Qsep100 analyzers, respectively. Sequencing was performed on an Illumina NovaSeq 6000 system, generating paired-end reads of 150 bp.

Bioinformatic analysis

RNA-seq data from pan-cancer samples were obtained from The Cancer Genome Atlas (TCGA) database. For each TCGA cancer type, immune cell fractions were estimated using the CIBERSORT algorithm (version 1.03). Macrophage scores were extracted and compared between tumor and normal groups using the rank-sum test implemented in ggplot2. Differences in immune infiltration were visualized with heat maps generated by ComplexHeatmap. To assess the prognostic significance of macrophage infiltration, macrophage scores were categorized into high and low groups based on the optimal cutoff determined by the surv_cutpoint function from the survminer package. Cox univariate analysis was then performed using the coxph function from the survival package. Only cancer types with hazard ratios (HR) > 1, P-values <0.05, and finite confidence intervals for HR and HR 95% CI were included in the forest plot. Immune infiltration analyses of tissue samples were conducted using the CIBERSORT and GSVA packages. The surv_cutpoint function from the survminer determined optimal cutoffs for grouping based on CIBERSORT macrophage scores and CD274 gene expression. Survival curves were then plotted for groups with high and low levels of PD-L1 and macrophage infiltration.

Macrophage populations in scRNA-seq data were quantified by calculating the fractions of CD68-positive macrophages in each sample. These fractions were compared between responder (R) and non-responder (NR) lesions using a bar plot, with the y-axis representing proportions and group labels displayed below. Statistical significance was evaluated using the Wilcoxon rank-sum test, with sample sizes annotated for each group. For multiple comparisons, a false discovery rate (FDR) correction was applied (q < 0.05). In bulk RNA-seq data, macrophage abundance was estimated using computational deconvolution with CIBERSORTx and the LM22 immune signature matrix. For cross-validation, macrophage-specific marker genes were aggregated into a metagene score (mean log2[TPM + 1]) and correlated with CIBERSORTx outputs (Pearson’s r > 0.7 in pilot analyses). TPM-normalized counts were used for cross-sample comparisons, and limma’s batch correction was applied to account for technical variability. After normalization, macrophage fractions were calculated for each sample and compared between responder (R) and non-responder (NR) groups. Inter-group comparisons were performed using Wilcoxon rank-sum tests with Benjamini-Hochberg FDR correction for multiple comparisons (q < 0.05 considered significant).

scRNA-seq data analysis

The generation of the scRNA-seq matrix commenced with the conversion of bcl files to fastq format using bcl2fastq version 2.20. This was followed by read demultiplexing and mapping to the mouse reference genome (mm10) using CellRanger (10× Genomics), which also corrected cell barcodes and unique molecular identifiers (UMIs), and calculated expression counts, thereby producing a single-cell expression matrix. The raw matrix was subsequently imported into Seurat for advanced analysis. Specifically, the raw UMI matrix was processed to exclude genes detected in fewer than three cells and cells with fewer than 300 genes. For quality control, the top and bottom 1% of cells based on nFeature and the top 1% of cells based on percent.mt were removed to eliminate doublets and cell debris.

For dimensional reduction, the ‘NormalizeData’ function was used to normalize the matrix, in which UMI counts for each gene were divided by the total UMI counts in each cell and multiplied by a scale factor of 1000, followed by a natural-log transformation with the addition of a pseudo count of 1 for each gene. Based on the normalized expression matrix, the 2,000 most variable genes were identified for each sample using the ‘FindVariableFeatures’ function with the ‘vst’ method. Prior to principal component analysis (PCA), the gene expression matrices from each sample were merged into a single gene expression matrix for all cells. The ‘ScaleData’ function was then used to scale and center the gene expression matrix after regressing out the heterogeneity associated with mitochondrial contamination. PCA was performed on the selected variable genes to identify the top 50 principal components using the ‘RunPCA’ function of Seurat. Substantial variability between cells from different samples was observed, reflecting a combination of technical and biological variations. These batch effects can sometimes cause cells to cluster based on sample heterogeneity rather than cell types or states. Unsupervised linear dimensionality reduction was performed using PCA, selecting the top 50 PCs alongside parameters of 30 perplexity and 0.7 resolution to delineate cell clusters through a shared nearest neighbor algorithm. The resolution parameter was adjusted to 0.5 for distinguishing T cell subsets and to 1 for Macrophage subsets, aiming for a more refined analysis. For data visualization, Uniform Manifold Approximation and Projection (UMAP) and t-SNE (t-distributed stochastic neighbor embedding) were employed. T cells were classified into ten subsets: effector memory CD8⁺ T (CD8⁺ Tem) cells, follicular helper CD4⁺ T (CD4⁺ Tfh) cells, proliferative CD8⁺ T (CD8⁺ Tprol) cells, stem cell-like memory CD8⁺ T (CD8⁺ Tsm-like) cells, exhausted CD8⁺ T (CD8⁺ Tex) cells, double-negative T (dNT) cells, naïve CD8⁺ T (CD8⁺ Tn) cells, regulatory CD4⁺ T (Treg) cells, stress response CD8⁺ T (CD8⁺ Tstr) cells, and activated CD8⁺ T (CD8⁺ Tact) cells. Macrophages were classified into eight subsets: CXCL9/CXCL10-enriched TAMs (CXCL9-TAMs), heat shock protein-enriched TAMs (Hsp-TAMs), proangiogenic TAMs (Angio-TAMs), inflammatory cytokine-enriched TAMs (Inflam-TAMs), resident-tissue macrophage-like TAMs (RTM-TAMs), proliferating TAMs (Prolif-TAMs), lipid-associated TAMs (LA-TAMs), and immune regulatory TAMs (Reg-TAMs) (22, 23).

To identify differentially expressed genes, the Seurat package’s functions, FindAllMarkers and FindMarkers, were used to discern differences between two cell populations, employing the two-sided Wilcoxon test as the default statistical method. Cluster-specific gene expressions were determined using the dplyr. To assess cell proportion comparisons, the relative abundance of each cell type across various groups was analyzed using the single-cell Deconvolution (scDC) algorithm. The analysis incorporated bias-corrected and accelerated (BCa) bootstrapping, specified by the parameters ‘calCI_method = BCa, nboot = 1,000’.

To calculate the immune-inhibitory score, normalized data were used to determine the average expression of a specific gene set in distinct single cells. An immune-inhibitory gene list was obtained from the Gene Ontology (GO) database (table S1). Subsequently, the average expression of these immune-inhibitory genes across each cell population was calculated to determine each cell population’s immune-inhibitory score.

GO enrichment analysis was conducted on differentially expressed genes using Metascape, a comprehensive and user-friendly web-based portal (https://metascape.org/) that integrates multiple databases. The findings were visualized through heat maps or dot plots created using the ggplot2.

Cell-cell interactions within the TME were analyzed using CellChat to decipher the interaction patterns among various cell populations. The initial steps involved computing the overall interactions between pairs of cell types within the TME, followed by separate analyses of interactions in gD^WT-treated and gD^αPD-L1-treated tumors. Subsequently, disparities in interaction strengths and ligand-receptor (L-R) pairs between the two cell populations were assessed. These findings were visualized using circle plots, chord diagrams, and scatter plots. In circle plots, the width of the lines indicates the signal intensity, with the line color matching that of the signal initiator. Chord diagrams feature edge colors consistent with the signaling initiators, and edge thickness reflects the interaction strength; a thicker edge signifies a stronger signal. The inner bars, thinner by comparison, represent the signal recipients and are colored to correspond with the respective outer bars.

Statistical analysis

Statistical analyses were performed using GraphPad Prism 9 software. Exact P values are presented in all graphs. Differences a P value below 0.05 were considered significant (*P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; NS = not significant). To evaluate variances in tumor growth, a repeated measures ANOVA was utilized for multiple comparisons. Survival analysis of the mice was assessed using log-rank tests. Repetitions of animal experiments are specified in the corresponding figure legends. For other experiments, comparisons between two groups were performed using unpaired two-sided Student’s t tests. Differences among three or more independent groups were assessed using one-way analysis of variance (ANOVA). The relationship between receptor expression levels and the cytotoxic effect of oHSV on specific mouse tumor cell lines was evaluated using Spearman’s correlation test.

Acknowledgments

Graphical diagram and schematics were created with BioRender and Adobe Illustrator.

Funding:

This research received funding from the Distinguished Young Scientists Grant of the Fujian Provincial Natural Science Foundation awarded to C.H. (2026D021), the National Natural Science Foundation of China with grants awarded to C.H. (82373286), N.X. (81991491) and C.L. (32100732), and the Scientific Research Foundation of the National Innovation Platform for Industry-Education Integration in Vaccine Research, with a grant awarded to C.L. (2023XAKJ0101008).

Author contributions:

C.L., S.L., R.L., W.T., Y.T., and C.F. conducted research, analyzed data and wrote the manuscript. W.T., C.L., and Y.R. were responsible for the bioinformatic analyses. Y.Q., L.L., and Y.L. contributed to the research and data interpretation. N.W. and Y.L. carried out histopathology analyses. X.H. prepared recombinant proteins. J.Z. undertook the statistical analyses. C.L., C.H., and N.X. were in charge of study design, data interpretation, research supervision, manuscript writing, and coordination of the project.

Competing interests:

C.H., C.L., S.L., R.L., C.F., J.Z., and N.X. are inventors on a patent related to glycoprotein D-modified herpes simplex virus vectors (patent numbers 202510453585.0), filed by Xiamen University. The other authors declare no competing interests.

Data, code, and materials availability:

Single-cell transcriptomic data from tumors treated with gD^WT and gD^αPD-L1 have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE272424. To compare immune-inhibitory scores across different immune cells, raw scRNA-seq data were obtained from GSE151091, GSE215120, and GSE139829. To compare PD-L1 expression across different human immune cell populations, raw scRNA-seq data were obtained from GSE215120. Additionally, raw scRNA-seq data from B16-F10 and GL261 tumors were sourced from GSE160132 and GSE222192. To assess TAM abundance in human samples, patients treated with PD-1 monotherapy (αPD-1) or combination therapy (αPD-1 + chemotherapy) with available response data were selected. Three scRNA-seq datasets (GSE120575, GSE207422, and GSE205506) and two bulk RNA-seq datasets (PRJEB23709 and GSE145996) were analyzed. All data and code needed to evaluate and reproduce the results in the paper are present in the paper and/or the Supplementary Materials. Generated materials in this study, including recombinant gD^WT and gD^αPD-L1 vectors, transfer plasmids, and engineered cell lines or cell materials, can be provided by C.H. pending scientific review and a completed material transfer agreement through Xiamen University. Requests for these materials should be submitted to: huangchenghao@xmu.edu.cn.

Supplementary Materials

This PDF file includes:

Figs. S1 to S16

Tables S1 and S2

sciadv.aef6767_sm.pdf^{(12.2MB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figs. S1 to S16

Tables S1 and S2

sciadv.aef6767_sm.pdf^{(12.2MB, pdf)}

Data Availability Statement

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PERMALINK

Rejuvenating endogenous antitumor immunity via a chimeric receptor-engineered oncolytic virus targeting tumor-associated macrophages

Chaolong Lin

Shaopeng Li

Rui Lou

Wenzhong Teng

Yang Tian

Chenxi Feng

Naizhen Wang

Yipeng Rao

Yaning Qin

Lu Li

Xiaoxuan Huang

Yisen Lin

Jun Zhang

Ningshao Xia

Chenghao Huang

Roles

Abstract

INTRODUCTION

RESULTS

PD-L1-positive TAMs are associated with poorer outcomes in cancers and serve as ideal targets for oHSV

Fig. 1. Intratumoral TAMs expressing high levels of inhibitory receptors are associated with poor cancer prognosis.

Generation of a PD-L1-directed CAR oHSV enabling specific infection of PD-L1-positive cells

Fig. 2. Generation of a PD-L1-targeted CAR-oHSV enabling the selective infection of PD-L1-positive target cells.

Retargeting oHSV to PD-L1 broadens its viral tropism and amplifies its oncolytic efficacy

Fig. 3. gDαPD-L1 repurposes PD-L1 as an alternative viral entry receptor to infect tumor cells regardless of initial susceptibility.

PD-L1 upregulation on tumor cells can be shielded by cis interaction with αPD-L1 CAR

gDαPD-L1 induces potent antitumor responses and augments effector T cell functionality

Fig. 4. Treatment with gDαPD-L1 enhances T cell activation and improves antitumor efficacy.

gDαPD-L1 directly targets PD-L1-positive TAMs and initiates tumor regression

Fig. 5. gDαPD-L1 targets TAMs via the PD-L1 receptor to promote robust antitumor immune responses.

gDαPD-L1 reprograms TAMs towards a pro-inflammatory phenotype

Fig. 6. gDαPD-L1 reprograms TAMs into a pro-inflammatory CXCL9-positive phenotype and enhances antigen presentation.

gDαPD-L1 promotes TAM immune activation via STING-dependent CXCL9/CXCL10 signaling

Fig. 7. gDαPD-L1 stimulates STING-dependent production of CXCL9 and CXCL10 in TAMs, enhancing cancer immunotherapy.

gDαPD-L1 sensitizes tumors to cancer immunotherapy and exhibits a favorable safety profile

Fig. 8. gDαPD-L1 exhibits a favorable safety profile and sensitizes tumors to cancer immunotherapy.

DISCUSSION

MATERIALS AND METHODS

Animals

Cell culture

Constructs

Stable cell lines

Virus construction

Protein purification

αPD-L1 functional assays

Immunofluorescence and immunohistochemistry

Flow cytometry analysis

Attachment assay

Cell cytotoxicity assays and high-content screening microscopy

Immunoblots

Cytokine analysis

Cell separation assays

Mouse procedures

Blood cell analysis

Serum chemistry

Single-cell RNA (scRNA) sequencing

Bioinformatic analysis

scRNA-seq data analysis

Statistical analysis

Acknowledgments

Funding:

Author contributions:

Competing interests:

Data, code, and materials availability:

Supplementary Materials

This PDF file includes:

REFERENCES

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Fig. 3. gD^αPD-L1 repurposes PD-L1 as an alternative viral entry receptor to infect tumor cells regardless of initial susceptibility.

gD^αPD-L1 induces potent antitumor responses and augments effector T cell functionality

Fig. 4. Treatment with gD^αPD-L1 enhances T cell activation and improves antitumor efficacy.

gD^αPD-L1 directly targets PD-L1-positive TAMs and initiates tumor regression

Fig. 5. gD^αPD-L1 targets TAMs via the PD-L1 receptor to promote robust antitumor immune responses.

gD^αPD-L1 reprograms TAMs towards a pro-inflammatory phenotype

Fig. 6. gD^αPD-L1 reprograms TAMs into a pro-inflammatory CXCL9-positive phenotype and enhances antigen presentation.

gD^αPD-L1 promotes TAM immune activation via STING-dependent CXCL9/CXCL10 signaling

Fig. 7. gD^αPD-L1 stimulates STING-dependent production of CXCL9 and CXCL10 in TAMs, enhancing cancer immunotherapy.

gD^αPD-L1 sensitizes tumors to cancer immunotherapy and exhibits a favorable safety profile

Fig. 8. gD^αPD-L1 exhibits a favorable safety profile and sensitizes tumors to cancer immunotherapy.