Inhibiting B cells enhances the efficacy of STING agonism or immune checkpoint blockade in hepatocellular carcinoma

Liu, Xin; Liu, Zelong; Zhu, Chengzhan; Kobayashi, Tatsuya; Lei, Pin-Ji; Shi, Yue; Yuan, Dandan; Wang, Jianguo; Li, Min; Matsui, Aya; Mafra, Kassiana; Ando, Tomofumi; Kojo, Ken; Schleinhege, Rieke; Miyazaki, Kento; Huang, Peigen; Kuang, Ming; Bod, Lloyd; Duda, Dan G.

doi:10.1038/s41467-025-66581-3

Download PDF

Article
Open access
Published: 08 December 2025

Inhibiting B cells enhances the efficacy of STING agonism or immune checkpoint blockade in hepatocellular carcinoma

Nature Communications volume 16, Article number: 10416 (2025) Cite this article

7295 Accesses
1 Citations
21 Altmetric
Metrics details

Subjects

Abstract

Most patients with hepatocellular carcinoma (HCC) develop resistance to immune checkpoint blockade (ICB) or STING agonists despite their immune-stimulating activities. Here, we identify increased intratumoral B-cell infiltration as a mediator of acquired resistance. In HCC models with liver fibrosis in male mice, anti-PD-1 ICB or the STING agonist BMS-986301 increase intratumoral B-cell infiltration, circulating IL-10, and TIM-1⁺ B-cells, promoting tertiary lymphoid structure formation. B-cell depletion combined with ICB or STING agonism improves survival, and STING agonism inhibits distant metastasis. In addition, co-targeting STING and TIM-1 enhances B-cell differentiation and antigen presentation, reduces intratumoral TIM-1⁺ B-cells, and increases CD86 and MHC class II expression, thereby augmenting CD8⁺ T-cell-mediated anti-tumor immunity. These findings reveal that B-cells contribute to ICB and STING therapy resistance in HCC, and that B-cell depletion or TIM-1 blockade can overcome acquired resistance to these immunotherapies.

Angiogenesis and immune checkpoint dual blockade in combination with radiotherapy for treatment of solid cancers: opportunities and challenges

Article Open access 10 July 2021

Targeting tumor-intrinsic BCL9 reverses immunotherapy resistance by eliciting macrophage-mediated phagocytosis and antigen presentation

Article Open access 17 November 2025

Targeting AXL induces tumor-intrinsic immunogenic response in tyrosine kinase inhibitor-resistant liver cancer

Article Open access 03 February 2024

Introduction

Hepatocellular carcinoma (HCC) is one of the most common malignancies and a leading cause of cancer-related mortality worldwide, representing a major global healthcare challenge with increasing incidence and mortality^1,2,3. The majority of HCC development occurs in patients with underlying liver disease, mostly because of hepatitis B or C virus infection, while non-alcoholic steatohepatitis associated with metabolic syndrome or diabetes mellitus is becoming a dominant risk factor in Western countries^4,5. Although surgical and locoregional treatments are becoming more widely available globally, it is estimated that ~50–60% of patients with HCC will eventually receive systemic therapies^1,6. Systemic therapies have been the mainstay of treatment of advanced HCC for almost two decades⁷. The successes of the phase III trials of combination therapy based on immune checkpoint blockade (ICB) (anti-PD-L1 with anti-VEGF in the IMbrave150 study and anti-PD-L1 with anti-CTLA-4 in the HIMALAYA study) have transformed systemic therapy for HCC^8,9. Despite this progress, more than 70% of the patients with advanced HCC do not respond to current ICBs, and most suffer from disease progression. Enhancing immunotherapy approaches by targeting the immunosuppressive tumor microenvironment (TME) of HCC remains an urgent need.

As key components of adaptive immunity, T lymphocytes play a well-established role in tumor responses to ICB¹⁰. However, the contribution of B lymphocytes to this process remains less understood, with most insights emerging only in the past decade¹¹. Within the TME, B cells can exhibit a broad spectrum of cell states and mediate innate and adaptive immune responses^12,13. Their antigen-presenting ability enables them to generate co-stimulatory or co-inhibitory signals and release cytokines and chemokines, modulating the behavior of other cells, such as effector T cells^12,13. Tumor-infiltrating B cells may exert both pro-tumor and anti-tumor effects depending on their phenotypes and TME composition. The formation of tertiary lymphoid structures (TLS) with B-cell follicles in cancer tissues, including HCC, indicates the crucial role of B cells and TLS in mediating anti-tumor immunity^14,15,16,17. Conversely, regulatory B cells (Bregs) inhibit immune responses to maintain immune homeostasis and promote tumor progression^18,19. Reports suggest that certain B-cell subsets and antibody specificities could contribute to cancer relapse and metastasis^20,21. Our recent study uncovered a B-cell population that expands during tumor progression, marked by the surface receptor T-cell immunoglobulin and mucin domain 1 (TIM-1) and other T-cell checkpoint receptors, indicating that TIM-1 marks a subset of activated B cells expressing co-inhibitory molecules and IL-10. This B cell subset significantly impairs anti-tumor T cell responses in multiple murine cancer models²². These findings underscore the need to further elucidate the roles of specific B-cell subpopulations and cell states in immunotherapy resistance in HCC.

A pathway identified as critical for the innate immune system and anti-tumor immunity is the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling^23,24. STING proteins, located in the endoplasmic reticulum, facilitate innate immune signaling by inducing the expression of type I interferons (IFNs) and pro-inflammatory cytokines upon sensing cytosolic double-strand DNA^25,26,27. Mechanistically, the binding of STING agonist to STING recruits TANK-binding kinase 1 and interferon regulatory factor 3, leading to the production of type I IFNs and pro-inflammatory cytokines, which results in the maturation, migration, and activation of dendritic cells, T cells, and natural killer (NK) cells^28,29,30,31. STING agonist agents are actively being evaluated in pre-clinical and clinical studies as enhancers of anti-tumor immune responses. However, while modulating STING has shown promise against primary and metastatic cancers in pre-clinical studies, STING agonists have demonstrated limited anti-tumor efficacy in the clinical trials conducted so far, even when combined with PD-1/PD-L1 ICB^32,33,34. This underscores the need to counteract immunosuppressive factors within the TME when employing STING agonists. Notably, STING activation has been shown to induce regulatory B cells that impair NK cell function in pancreatic cancer³⁵, suggesting a potential immunosuppressive role for Bregs in limiting STING-mediated anti-tumor immunity. However, the precise mechanisms remain incompletely understood, and these mechanisms are entirely unknown in HCC, restricting the development of effective combination strategies despite the promising activity of STING agonists in preclinical models^36,37.

Since the discovery of STING, a range of natural and synthetic STING agonists have undergone evaluation in pre-clinical and clinical settings for different tumor types³⁸. The notable pre-clinical anti-tumor effects of STING agonists have led to the development of multiple pharmacologic classes of agents, including cyclic dinucleotides, non-cyclic dinucleotides, bacterial vectors, and other unique STING agonists^28,38,39. Currently, several STING agonists, such as ADU-S100/MIW815, E7766, and GSK3745417, have been approved for clinical trials in treating solid tumors or lymphoma^28,40. However, some have been terminated because no substantial anti-tumor activity was observed in humans. The challenge of delivering STING agonists into the cytosol has led to the predominant use of intratumoral injections for administration in clinical trials. This approach enables precise tumor targeting, achieving high local concentrations with reduced systemic distribution and toxicity. Nonetheless, it brings specific challenges for further application in HCC treatment, such as the risks of bleeding and needle tract implantation⁴¹.

BMS-986301 is a STING agonist undergoing clinical trials as a systemic treatment using intramuscular injections, either alone or in combination with nivolumab and ipilimumab, for advanced solid cancers resistant to checkpoint inhibitor therapy (NCT03956680). Preliminary results have demonstrated that BMS-986301 monotherapy achieved over 90% complete regression in murine models of colorectal cancer, exhibiting lower toxicity towards CD8⁺ T cells and less inhibition of their proliferation compared to ADU-S100.

In this study, we evaluate the efficacy of STING agonism in murine models of HCC with underlying liver damage, which mimics the presentation of human disease. Our findings demonstrate the role of B cells in STING agonist or ICB-based HCC treatment and offer insights into overcoming resistance to such therapies. By harnessing B-cell-mediated immunity, particularly by identifying specific targets on B cells, we can amplify the efficacy of existing HCC immunotherapies. This approach also opens avenues for treating tumors previously unresponsive to treatment with STING agonists alone, providing a promising strategy for enhancing HCC management.

Results

ICB immunotherapy drives B-cell infiltration in murine HCC

To objectively assess changes in intratumoral immune cell populations following ICB, we integrated seven bulk RNA-seq datasets of murine liver cancer from our previous studies^{42,43,44,45,46}. Using an anti-PD-1 antibody as the primary treatment, principal component analysis (PCA) revealed significant transcriptional shifts in response to ICB (Fig. 1a, b). Immune deconvolution revealed a significant increase in two major immune populations following treatment: CD8⁺ T cells, as expected and previously reported^44,45, and more notably, B cells among non-tumor cell populations (Fig. 1c, d). Multiple immune profiling approaches consistently identified this expansion, with large effect sizes quantified using Cohen’s d across various methods (Fig. 1c). Notably, the increase in B cells post-ICB treatment was further validated through multiple deconvolution techniques, underscoring the robustness of these findings (Fig. 1e). As ICB immunotherapy triggers adaptive immune responses, our findings indicate that the increased B cell infiltration is associated with the activation of adaptive immunity, highlighting its potential role in the response to immunotherapy.

**Fig. 1: ICB immunotherapy increased B-cell infiltration.**

To investigate whether the expanded B-cell populations differ between PD-1 blockade and STING agonism, we performed deconvolution analysis using bulk RNA-seq data to estimate B-cell subtype proportions. The results showed no significant differences in the predicted enrichment scores of B-cell subtypes between the two treatment groups in both the HCA-1 and RIL-175 murine HCC models (Supplementary Fig. 1a). In addition, the expression of representative marker genes for these B-cell subsets was also comparable between the two groups (Supplementary Fig. 1b).

STING agonist treatment enhances B-cell infiltration in HCC

Next, to understand the alterations in the TME following the activation of innate immunity, we investigated the effects of enhancing anti-tumor immunity by using a STING agonist (BMS-986301) in the ICB-responsive RIL-175 murine HCC model in C57Bl/6 mice. First, to determine its optimal dosing, mice with established tumors and underlying liver damage received 2 intramuscular injections of STING agonist at varying doses: 0.67, 1.33, 2.00, 2.67, and 3.33 mg/kg, administered weekly. We monitored the changes in body weight as a measure of toxicity and tumor growth delay by ultrasound imaging. All doses led to body weight loss in some mice, notably one week after the treatment, yet all mice recovered to their normal weight shortly thereafter (Supplementary Fig. 2a). Doses higher than 2 mg/kg were associated with improved therapeutic outcomes, manifesting as delayed tumor growth and extended survival compared to lower doses (Supplementary Fig. 2b, c). Given the potential risk of high doses of the STING agonist inducing T cell apoptosis and adverse effects⁴⁷, we selected the 2 mg/kg weekly dose that showed anti-HCC activity without limiting toxicity in mice with liver damage for further testing of the efficacy and safety of the treatment.

Next, we tested the efficacy of the STING agonist in a highly metastatic and ICB-resistant murine HCC model (orthotopic HCA-1 grafted in C3H mice)⁴⁴. Weekly administration of the STING agonist for two doses of 2 mg/kg induced a transient growth delay but did not increase median OS in this model (Fig. 2a and Supplementary Fig. 2d). Flow cytometric analysis of the tumor tissues from a separate time-matched cohort showed that the proportion of tumor-infiltrating B cells was significantly higher after STING agonism (Fig. 2b, c and Supplementary Fig. 2e). We conducted bulk RNA-sequencing (RNA-seq) analysis on tumor tissue samples collected on day 10 post-treatment to investigate the alterations within the TME that may mediate immunosuppression. The analysis revealed an upregulation of B-cell-related pathways in the STING agonist-treated group compared to the control group (Supplementary Fig. 3a). These upregulated pathways included FCGR3A-mediated IL10 synthesis, CD22-mediated BCR regulation, and signaling by the B cell receptor (Supplementary Fig. 3b, c), motivating us to focus on the enrichment of B cells. Using the bioinformatic tool xCell, which is designed to perform cell type enrichment analysis from gene expression signature⁴⁸, we found that the enrichment score of total B cells increased after STING agonist treatment compared to the control group, with memory B cells showing the most increase (Fig. 2d and Supplementary Fig. 4). The increased B-cell infiltration was also confirmed by IF, which showed a significant increase in B-cell proportion after STING agonist treatment (p = 0.0008) (Fig. 2e, f).

**Fig. 2: B cells are enriched after STING agonist treatment in orthotopic HCA-1 and RIL-175 murine HCCs.**

To examine the effect of STING agonism in an autochthonous murine HCC model, we administered CCl₄ for 12 weeks after tail-vein injection of Cre-expressing adenovirus (adeno-Cre) in Stk4^−/−Stk3^F/− (Mst1^−/−Mst2^F/−) mice to induce HCC development concomitant with liver fibrosis⁴⁹. A single dose of STING agonist produced a non-significant tumor growth delay (Supplementary Fig. 5a, b); immunofluorescence analysis of tumor tissues showed a trend toward increased B-cell infiltration after STING agonist-treatment versus control (Supplementary Fig. 5c, d).

STING agonist treatment promotes vascular normalization and enhances T-cell infiltration in murine HCC

Next, we tested the effects of STING agonism in the orthotopic RIL-175 murine HCC model in C57Bl/6 mice with liver damage, which responds to anti-PD-1 therapy⁴⁴. We found that treatment with the STING agonist alone increased the number of B-cell aggregates compared to the control group after just one dose (Supplementary Fig. 6a, b), indicating a rapid functional reprogramming of B-cells after the treatment. We performed staining using CD3 and B220, identifying TLS-like structures in tumors from the STING agonist treatment group, particularly on day 12 (Fig. 2g, h). Most of these TLS-like structures were located in the peritumoral area, with very few observed within the intratumoral region (Supplementary Fig. 6c). To further characterize the TLS-like structures observed in STING agonist-treated mice, we performed staining for CD21, peripheral node addressin (PNAd), and IL-10 on murine RIL-175 HCC tissue sections. Our analysis identified B220^–CD21⁺ cells, suggesting the presence of follicular dendritic cells, but only minimal expression of PNAd and IL-10 in these areas (Supplementary Fig. 6d), suggesting that the induced TLS-like structures are likely in an immature or intermediate state. Moreover, we found that STING agonist treatment significantly increased the total and pericyte-covered microvessel density (Supplementary Fig. 7a, b), and the intratumoral infiltration by CD4⁺ and CD8⁺ T-cells in the RIL-175 model (Supplementary Fig. 7c). These data demonstrate that the STING agonist treatment promotes vascular normalization and enhances T-cell infiltration.

B-cell depletion increases the therapeutic benefits of immunotherapy in an ICB-resistant murine HCC model

Given that increased B-cell infiltration during ICB treatment may indicate both pro-tumor and anti-tumor effects, we next performed B-cell depletion experiments in combination with ICB treatment. In the anti-PD-1-resistant orthotopic HCA-1 murine HCC model, we tested the treatment efficacy of B cell depletion combined with dual PD-1/VEGFR2 blockade (Fig. 3a). The combination of dual anti-PD-1/VEGFR2 and B-cell depletion showed superior tumor growth delay (Fig. 3b and Supplementary Fig. 8a), and significantly longer overall survival (OS) than other groups (Fig. 3c). No obvious adverse effects were observed as the body weight remained stable during the treatment period, and no differences in lung metastasis were found among the treatment groups (Supplementary Fig. 8b, c). The efficiency of B-cell depletion was confirmed by flow cytometry analysis of blood samples collected on day 12 and by immunofluorescence staining of tumor tissues (Supplementary Fig. 8d–f). These results indicate that the increase in intratumoral B cells after ICB immunotherapy has a predominantly immunosuppressive function in an immunotherapy-resistant murine HCC model.

**Fig. 3: B cell depletion enhances the anti-tumor efficacy of immunotherapy and decreases metastasis in the murine HCA-1 HCC model.**

To investigate the role of the increased B cell infiltration after STING agonist therapy, we conducted a survival study in mice with or without B-cell depletion by anti-CD19 and anti-B220 antibodies in HCA-1 murine HCC-bearing mice with underlying liver damage (Fig. 3d). To sustain the tumor growth delay effect seen with 2 doses of STING agonist, we administered a third weekly dose in this cohort. Mice with established orthotopic tumors were randomized to treatment with (1) IgG control, (2) STING agonist with IgG, (3) STING agonist with anti-CD19 and anti-B220 antibodies for B cell depletion. We found that STING agonist combined with B-cell depletion effectively delayed tumor growth and significantly prolonged survival without limiting toxicities (STINGa + aCD19/aB220 versus STINGa + IgG, HR = 0.38, p = 0.02, log-rank test) (Fig. 3e, f and Supplementary Fig. 9a). These data demonstrate that the increased B-cell infiltration has an immunosuppressive role and limits the survival benefit of STING agonism. The lungs are the most common site of HCC metastatic colonization, accounting for 51% of all extrahepatic metastases, one of the key factors affecting its prognosis^50,51,52. The HCA-1 model is highly prone to lung metastasis^44,53. Therefore, we also measured the lung metastases in the survival experiment and found lung metastasis incidence was the lowest in the STING agonist with B-cell depletion group (Fig. 3g). When we evaluated the lung metastatic burden by enumerating metastatic nodules, we found it significantly reduced in the group that received a combination of STING agonist and anti-CD19/anti-B220 B-cell depletion than other groups (Fig. 3h). Moreover, pleural effusions were lowest in the STING agonist with the B-cell depletion group (Supplementary Fig. 9b). However, ascites and peritoneal metastasis incidence were comparable between the treatment groups at the terminal endpoint (Supplementary Fig. 9c, d). H&E staining results showed that the STING agonist potently inhibited metastasis, and the addition of B-cell depletion further enhanced this ability, showing the enhanced effect of STING agonist and B-cell depletion in the control of HCC metastasis (Supplementary Fig. 9e). This effect of STING agonism is remarkable, as none of the anti-VEGF-based combinations or anti-PD1 treatments have shown anti-metastatic effects in clinical studies or preclinical models of HCC.

Combining STING agonism, ICB, and B-cell depletion eradicates tumor growth and prevents relapse in an ICB-responsive HCC model

Since B-cell depletion overcame resistance in both STING agonist-treated and ICB-treated HCA-1 models individually, we next investigated its impact in a more potent setting combining STING agonism with dual PD-1/VEGFR2 blockade (Fig. 4a). Strikingly, tumor growth was completely eradicated in this model, with all mice receiving the full combination treatment (STING agonist + anti-PD-1/anti-VEGFR2 + anti-CD19/anti-B220) achieving complete responses (Fig. 4b–d). Moreover, rechallenging long-term survivors by implanting RIL-175 HCC cells into a different liver lobe resulted in no tumor growth, whereas tumors developed in age-matched control mice (Fig. 4e, f). These findings suggest that B-cell infiltration counteracts the therapeutic efficacy of STING agonism and dual PD-1/VEGFR2 blockade, potentially through immunosuppressive mechanisms. Notably, B-cell depletion significantly enhances tumor regression and leads to complete responses, indicating its role in overcoming resistance. Furthermore, the absence of tumor regrowth upon rechallenge highlights the establishment of durable anti-HCC immunological memory in this model.

**Fig. 4: B cell depletion enhances STING agonism with dual PD-1/VEGFR2 blockade in the RIL-175 murine HCC model.**

To explore whether VEGFR2 inhibition alters B-cell abundance or polarization when combined with PD-1 blockade, we performed additional flow cytometry analyses of RIL-175 murine HCC tissues. Mice were assigned to four different treatment groups: (1) IgG control, (2) anti-VEGFR2, (3) anti-PD-1, and (4) combination of anti-VEGFR2 and anti-PD-1. All treatments were administered once every three days, and tumors were harvested on day 10 after treatment initiation. Our results showed that the addition of anti-VEGFR2 did not affect overall B cell abundance. TIM-1⁺ B cells were increased only in the anti-PD-1-containing groups. Notably, B cells from the dual anti-PD-1 and anti-VEGFR2 group exhibited elevated IL-10 and PD-L1 expression (Supplementary Fig. 10a–e). These findings suggest that while VEGFR2 blockade does not change B-cell numbers, its combination with PD-1 blockade may enhance B-cell polarization toward a more immunosuppressive phenotype.

We also performed an additional cohort using the RIL-175 model in which mice were treated with either control IgG or anti-CD19/anti-B220 therapy. The results showed that B-cell depletion by dual anti-CD19/anti-B220 did not affect tumor growth or overall survival (Supplementary Fig. 11a, b). These findings indicate that while B-cell depletion alone has no therapeutic effect, its combination with STING agonist and dual anti-PD-1/VEGFR2 therapy further improves survival. To understand the potential impact of fibrosis on B cells, we performed an additional cohort study in the HCA-1 murine HCC model with four groups: (1) non-fibrosis + IgG, (2) non-fibrosis + anti-CD19/anti-B220, (3) fibrosis + IgG, and (4) fibrosis + anti-CD19/anti-B220. The results showed that mice with a fibrotic background had worse survival outcomes, as those treated with IgG in the fibrosis group exhibited significantly shorter survival compared with the non-fibrosis group. However, within both the fibrosis and non-fibrosis settings, there were no survival differences between B-cell-depleted mice (anti-CD19/anti-B220) and IgG controls (Supplementary Fig. 11c, d), also indicating that B-cell depletion alone does not affect survival.

TIM-1 expression is upregulated after STING agonist treatment in HCA-1 murine HCC

Given that B-cell infiltration in HCCs following immunotherapy may contribute to resistance, we analyzed the expression profiles of genes associated with B-cell regulatory functions using bulk RNA-sequencing data from HCC tissues in control and STING agonist-treated mice. This analysis revealed increased expression of regulatory Breg markers, including Havcr1, Il10, Il12a, and Ebi3, in HCA-1 HCC samples from STING agonist-treated mice (Fig. 5a). Based on these markers, we computed a “Breg score” using ssGSEA method⁵⁴, which was significantly higher in the tumor from STING agonist-treated group (Fig. 5b). Notably, Havcr1, which encodes the immune checkpoint TIM-1, was also upregulated in STING agonist-treated tumors compared to controls (Fig. 5c), suggesting an enrichment of TIM-1⁺ B cells following treatment. Furthermore, STING agonist-treated mice exhibited significantly higher plasma IL-10 levels, which may support the immunosuppressive role of infiltrating B cells in this context (Fig. 5d). In contrast, the same group displayed lower plasma levels of IFN-γ, IL-1β, and IL-2, indicating a reduction in pro-inflammatory cytokines (Supplementary Fig. 12).

**Fig. 5: Higher TIM-1 expression in HCA-1 murine HCC after STING agonist treatment than control.**

To further investigate the role of STING agonism and TIM-1 signaling in B cells, we isolated B cells from mouse spleens and treated them in vitro with IgG, STING agonist, anti-TIM-1 blocking antibodies, or their combination. After 72 h, RNA was extracted for transcriptomic analysis (Fig. 5e). The PCA showed a distinct transcriptional shift in STING agonist-treated B cells compared to the PBS control, with anti-TIM-1 treatment further enhancing this shift (Fig. 5f). Pathway enrichment analysis revealed that the combination of STING agonism and TIM-1 blockade promoted B-cell differentiation, including germinal center B-cell formation (Fig. 5g), and enhanced antigen processing and presentation (Supplementary Fig. 13). These findings demonstrate that this combination therapy reprograms B cells, potentially altering their function within the TME.

To examine the cytokine production capacity of TIM-1⁺ B cells, we analyzed publicly available single-cell RNA-seq and spatial transcriptomic data from patients with HCC treated with neoadjuvant anti-PD-1 therapy and from murine B cells^55,56,57. In these datasets, TIM-1⁺ B cells were found to express IL10 and IL35 (encoded by IL12A and EBI3) (Supplementary Fig. 14a, b). Notably, IL10⁺ Bregs did not universally express TIM-1, indicating that TIM-1⁺ B cells represent only a subset of the broader Breg population. Consistent with this, we detected colocalization of B-cell markers (CD79A, CD79B) with HAVCR1 (encoding TIM-1) in spatial transcriptomic data, and it was significantly higher in responders compared with non-responders (Supplementary Fig. 14c, d), supporting our finding that immune-activating therapies such as STING agonists or PD-1 blockade can simultaneously induce TIM-1⁺ B cells, which may act to restrain anti-tumor immunity. However, colocalization between HAVCR1 and IL10 transcripts was not detected in spatial transcriptomic data (Supplementary Fig. 14c), which is likely attributable to the known technical difficulty of detecting cytokine transcripts at the single-cell level.

A combination of STING agonism and TIM-1 ICB is effective in an ICB-resistant murine HCC model

We conducted a survival experiment to test the efficacy of TIM-1 blockade in the context of STING agonism in the orthotopic anti-PD1-resistant HCA-1 model. Tumor-bearing mice received 15 days of treatment with (1) IgG control, (2) STING agonist with IgG, (3) anti-TIM-1 antibody, or (4) STING agonist with anti-TIM-1 antibody (Supplementary Fig. 15a). We found a significantly longer growth delay and median OS in the STING agonist/anti-TIM-1 combination group (Fig. 6a, b). Lung metastatic burden was also lowest in the combination group, in line with the anti-metastatic activity of STING agonism with B-cell targeting (Fig. 6c, d and Supplementary Fig. 15b). Thus, combining STING agonism with TIM-1 blockade is a potentially effective treatment approach in anti-PD-1-resistant HCC.

Fig. 6: Combination treatment of STING agonism and TIM-1 blockade reprograms B cell function, induces more IFNγ+CD8+ T cells, and improves anti-tumor benefit. — **Fig. 6: Combination treatment of STING agonism and TIM-1 blockade reprograms B cell function, induces more IFNγ⁺CD8⁺ T cells, and improves anti-tumor benefit.**

Next, to investigate how the combination of a STING agonist and anti-TIM-1 antibody reprograms the immune TME of HCC, we conducted a time-matched cohort study using the HCA-1 model in mice with liver damage. Mice with established tumors were randomized to treatment with (1) IgG control, (2) STING agonist with IgG, (3) anti-TIM-1 antibody, and (4) STING agonist with anti-TIM-1 antibody. Tumor samples were collected on day 35 post-treatment to ensure sufficient material for flow cytometry analysis (Supplementary Fig. 15c). Flow cytometry revealed that the STING agonist alone significantly increased B-cell infiltration, while adding TIM-1 blockade reduced the B-cell frequency (Fig. 6e, f). TIM-1⁺ B cells were significantly elevated in the STING agonist group, and the addition of TIM-1 blockade prevented this increase (Fig. 6g, h). Among B cells, the proportions of MHC-II⁺ and CD86⁺ B cells were higher in groups treated with the anti-TIM-1 antibody (Fig. 6i, j), indicating an enhanced antigen-presenting capacity. Functionally, the combination treatment led to a significant increase in IFNγ⁺CD8⁺ T cells (Fig. 6k), further supporting the anti-tumor immune reprogramming of the TME of HCC induced by this therapeutic approach. In addition, we conducted co-staining of TIM-1 and B220 in the HCA-1 murine HCC model to examine the distribution of TIM-1⁺ B cells. Consistent with the flow cytometry results, only a limited number of TIM-1⁺B220⁺ cells were detected in the tissues overall. Notably, TIM-1⁺B220⁺ cells tended to be localized more frequently in the peritumor regions after STING agonist-treatment compared to controls (p = 0.081), and no differences were observed within TLS-like structures or intratumor areas (Supplementary Fig. 15d, e).

TIM-1 and a B-cell signature are associated with survival in human HCC

To examine whether the expression levels of the TIM-1⁺ B-cell signature (271 genes) correlate with survival in patients with HCC, we used these genes to stratify the patients with HCC from The Cancer Genome Atlas (TCGA) cohort into two groups of high and low scores based on the median. We found that this signature was significantly associated with the overall survival of these patients (Fig. 6l), and that the expression level of the HAVCR1 gene alone was significantly associated with survival (Supplementary Fig. 16a). Moreover, we found that the expression levels of TIM-1⁺ B-cell signature and STING pathway signature (54 genes) were directly correlated (Fig. 6m), further supporting the mechanistic link between the STING pathway activation and TIM-1⁺ B cells identified in HCC models.

To explore the role of B cells in acquired resistance to immunotherapy in patients, we analyzed a single-cell RNA-seq dataset reported from a neoadjuvant clinical trial of anti-PD-1 ICB for HCC⁵⁶. The data revealed that both T cells and B cells were significantly more enriched in ICB responders than non-responders (Supplementary Fig. 16b), consistent with a role for these populations in modulating the balance between immune activation and suppression. Further analysis of cell-cell interactions revealed that ICB-non-responders had greater overall intercellular communication, with enrichment of immunosuppressive interactions such as CLEC2C-KLRB1 and HLA-E-CD94:NKG2A, particularly involving B cells with NK cells and other immune subsets (Supplementary Fig. 16c, d). Naive and memory B cells were examined from patients classified as ICB responders or non-responders (Supplementary Fig. 17a, b). Differential gene expression analysis revealed that pathways associated with immune responses, including adaptive immune response, immune effector processes, and antigen processing and presentation, were enriched among the upregulated genes in responders (Supplementary Fig. 17c–e). Among the significant differences in immune responses between responder and non-responder patients with HCC, the scores for antigen processing and presentation, as well as B-cell activation, were significantly higher in the responder group (Supplementary Fig. 17f, g), suggesting that functional activation of B cells is a critical target for ICB treatment efficacy. Finally, antigen-presentation markers (CD40, CD74, HLA-DMA, HLA-DMB) were expressed at higher levels in TIM-1-negative B cells compared with TIM-1-positive B cells (Supplementary Fig. 17h), suggesting that TIM-1⁺ B cells are less specialized for antigen presentation but may instead contribute to immunosuppression.

Discussion

ICB immunotherapy with PD1/PD-L1 blockers has transformed HCC treatment. However, inherent or acquired immunotherapy resistance remains a significant challenge, and the mechanisms driving resistance remain poorly understood. We studied resistance to ICB and STING agonism-based immunotherapy in well-characterized murine HCC models, which revealed a surprising mechanism of treatment resistance mediated by infiltrating B cells. We also show that targeting B-cell-mediated immunosuppression in HCC can prevent the acquired resistance to ICB and STING agonist therapy in murine HCC and identify the immune checkpoint TIM-1 as a target for HCC treatment (Fig. 7). As an immune checkpoint molecule on immunosuppressive B-cells, TIM-1 holds promise for guiding the development of combination therapies that enhance the efficacy of STING agonists, offering new hope for the immunotherapy of HCC.

**Fig. 7: Targeting B cells enhances STING agonism in HCC.**

STING agonism showed potent activation of anti-tumor immunity but rapidly increased the infiltration by B-cells in the murine HCC tumor tissue, particularly in the immunotherapy-resistant HCA-1 model. Considering the pleiotropic roles of B-cells in cancer progression, we used the depletion of B-cells to clarify their predominant role in this treatment setting. The overall depletion of B-cells significantly enhanced the efficacy of STING agonism, including when combined with STING agonist and anti-PD-1 therapy, demonstrating the predominantly immunosuppressive role of B-cell populations during immunotherapy in HCC. This discovery points to B-cells as potential targets for overcoming immunotherapy resistance. Indeed, combining STING agonism, dual anti-PD-1/VEGFR2 therapy, and B-cell depletion led to HCC eradication in all mice and immunological memory responses. Although no significant differences in the phenotypes of B cells infiltrating after ICB versus STING agonist treatment were observed in our current dataset, higher-resolution approaches may uncover more subtle differences, particularly given the distinct mechanisms of action of the two agents. Approaches to specifically target immunosuppressive B-cells in HCC still need to be developed. We show here that combining ICB using antibodies blocking TIM-1, an immune checkpoint expressed on immunosuppressive and tumor-promoting B-cells²², significantly improves survival in ICB-resistant murine HCC.

Lung metastasis is the most common form of distant dissemination in liver cancer patients and is associated with treatment resistance and poor outcomes^50,51,52. A recent study showed that STING activity increases in metastatic progenitors re-entering the cell cycle⁵⁸. In contrast, another study showed that persistent activation of STING leads to desensitization and rewiring of downstream signaling, which impedes effective anti-tumor immunity and may instead facilitate cancer metastasis⁵⁹. We found that combining a STING agonist with B-cell depletion significantly reduced the incidence of lung metastases, lung metastatic burden, and pleural effusion. Moreover, combining anti-TIM-1 ICB treatment with a STING agonist also inhibited lung metastasis, offering a strategy to improve outcomes in metastatic HCC.

Of note, we found an increased formation of B-cell aggregates and TLS-like structures in HCC tissues from STING agonist-treated mice. The function of the B cells in the TLS-like structures in HCC may explain the conflicting data on the association between TLSs and outcomes in patients with cancer, as our results show that B-cells promoted immunosuppression after immunotherapy. The balance between positive and negative feedback from different T cell subsets is believed to govern the functionality of tumor-associated TLS, with Bregs potentially contributing to additional negative feedback⁶⁰. Interestingly, IL-10-producing Bregs in TLS-like aggregates in patients with breast cancer are associated with shorter metastasis-free survival⁶¹. Further studies in HCC are needed to dissect the pro- versus anti-tumor roles of TLS to better understand their impact on tumor progression and therapeutic response. Given the lack of Breg-specific markers⁶², our finding of TIM-1 as a target to prevent or convert the Breg phenotype may represent a more promising approach than depletion. Prior in vivo studies strongly support the role of TIM-1 in regulating IL-10 production by Bregs. Specifically, TIM-1 is preferentially expressed on B cells rather than T cells in mice, and TIM-1 deficiency markedly impairs IL-10 production in Bregs^63,64,65,66. These findings suggest that TIM-1⁺ B cells, although rare, represent an immunoregulatory subset with the potential to contribute to IL-10-mediated suppression in the tumor microenvironment. Our previous work also demonstrated that the anti-tumor efficacy of anti-TIM-1 antibody treatment was abolished in Cd19^Cre/+×Havcr1^fl/fl mice, indicating that TIM-1 expression on B cells is required for therapeutic benefit across tumor contexts. By contrast, TIM-1 deletion in T cells (Cd4^Cre/+ × Havcr1^fl/fl) had no impact on tumor progression in the same models²². Together with independent studies reporting that TIM-1 is predominantly expressed on B cells rather than T cells in mice^63,65, these findings suggest that the observed effects are largely mediated by B cells and that off-target effects on T cells are minimal. While the TIM-1-dependent suppression of T-cell responses by B cells reflects a fundamental immunoregulatory mechanism that extends beyond specific tumor types, it needs further validation as a therapeutic target across additional cancer contexts.

Agonists activating the STING pathway have shown modest anti-cancer efficacy in clinical trials so far^28,38,39, and ICB-based therapy is ineffective in most patients with HCC. Despite potently activating anti-tumor immunity, resistance to STING agonists and ICB occurs frequently and rapidly, mediated by immunosuppressive mechanisms. Our study showed that B cells are a major source of therapy resistance under both innate and acquired immune response activated by STING agonist and ICB treatment, and identified that combining STING agonist with B-cell targeting and anti-TIM-1 ICB can improve the treatment response in murine HCC. As B cells represent a heterogeneous population whose functions vary with developmental stage, activation status, and tumor microenvironment, the translational implications of B-cell depletion strategies remain to be defined. Future studies involving human samples, particularly with single-cell resolution, will be critical to delineate the roles of distinct B cell subsets in mediating clinical responses.

Overall, our findings reveal a critical role for B cells in shaping the immune TME and influencing immunotherapy outcomes in HCC. While STING agonists and ICB alone have shown limited efficacy, targeting B-cell-mediated immunosuppression could enhance anti-tumor immunity. More broadly, our study underscores the role of B cells in hindering immunotherapy responses. By dissecting these mechanisms and functional states of B cells, we provide a foundation for combination strategies to reprogram the TME and improve the efficacy of ICB, STING agonism, and other immunotherapies in HCC.

Methods

Study approval

The study was approved by the Institutional Animal Care and Use Committee (IACUC) at Massachusetts General Hospital (MGH) under ethical approval ID 2020N000023, complying with all relevant ethical regulations.

Cells and culture conditions

We used 2 murine HCC cell lines: HCA-1 from C3H mice, established in our laboratory^49,67, and RIL-175 (a p53/Hras mutant HCC cell line from C57Bl/6 mice, a kind gift from Dr. Tim Greten, NIH)⁶⁸. HCA-1 was maintained in Dulbecco’s Modified Essential Medium (DMEM) (ThermoFisher, USA) with 10% fetal bovine serum (FBS) (Hyclone, SH30071.03) and 1% penicillin-streptomycin (Gibco #15070063) in 5% CO₂ at 37 °C. RIL-175 was maintained in DMEM with 20% FBS and 1% penicillin-streptomycin in 5% CO₂ at 37 °C. All cells used for experiments were passaged less than 5 times and were authenticated before in vivo use. Mycoplasma contamination was routinely performed before in vivo studies for all cell lines using MycoAlert Mycoplasma Detection Kit (Lonza #LT07-318), and all tested negative. No genetic manipulations were performed for the cells used in this study. B cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS), 100 U/mL penicillin–streptomycin, 2 mM L-glutamine, 1.5 mM sodium pyruvate, 1× non-essential amino acids, 10 mM HEPES, and 0.05 mM 2-mercaptoethanol.

Animal studies

Animal experiments were performed in the animal facility of Massachusetts General Hospital under specific pathogen-free conditions. The animals were kept under a standard 12-h light/12-h dark cycle, at a controlled ambient temperature of ~20–24 °C and relative humidity of 40–60%. Food and water were provided ad libitum. All animal experiments were performed under the IACUC at MGH-approved protocol (2020N000023). Studies complied with all guidelines outlined regarding animal research in the IACUC Policies and Guidance of MGH Research Institute. Euthanasia was performed per protocol on animals when tumor size exceeded 2000 mm³, tumor length was ≥13 mm as measured by ultrasound, body weight loss exceeded 20%, the body condition score reached 1, or when other health conditions met the euthanasia criteria according to the MGH IACUC guideline.

Orthotopic HCC mouse models

In the therapeutic studies, orthotopic HCCs were induced by intrahepatic injection of HCA-1 cells in syngeneic male C3H mice, while RIL-175 cells were implanted in syngeneic male C57Bl/6 mice. The mice were purchased from the MGH Center for Comparative Medicine. Six-to-8-week-old male mice were used for experiments. The HCC model under liver damage was performed as described previously⁴⁹. To induce liver damage, 100 μl of 20% carbon tetrachloride (CCl4) (Sigma-Aldrich #289116) was administered orally for 6 weeks. After one week of recovery, the suspensions of the murine HCC cells mixed with Matrigel (Corning #354234) in a 1:1 volume ratio were injected into the subcapsular region of the liver parenchyma using 0.5 ml syringes with 28-gauge needles. To prevent leakage of tumor cells from the injection sites, the injection volume was controlled to 10 μl (10⁶ cells in 10 μl per mouse). In addition, a steady and slow injection was performed to minimize leakage of the injected cell suspension further. After withdrawing the needle, the injection site was covered with Surgifoam (Ethicon #1972) for 5 min to reduce bleeding and potential backflow. Carbon tetrachloride (CCl4) is administered for 12 weeks after tail-vein injection of Cre-expressing adenovirus (adeno-Cre) in Stk4^−/−Stk3^F/− (also known as Mst1^−/−Mst2^F/−) mice to induce HCC concomitantly with liver fibrosis^49,69. Treatments were initiated in mice with established tumors when the tumors reached 5 mm in diameter, measured by high-frequency ultrasound imaging. Tumor growth and treatment response were also monitored by ultrasound imaging. Primary tumor size was controlled by the experimental endpoint defined in the animal protocol (tumor length ≥13 mm as measured by ultrasound).

Imaging of orthotopic HCC

Tumor growth and treatment response were monitored by high-frequency ultrasound imaging. For the longitudinal evaluation of tumor growth, we used an ultrasound device (Vevo 2100, VisualSonics) equipped with specific probes for small-animal imaging weekly. Imaging to assess tumor growth longitudinally was conducted noninvasively under isoflurane anesthesia. The ultrasound measurement was discontinued upon the demise of over 50% of the mice in a treatment group, and the health status of the mice was monitored to recover from the anesthesia.

Treatments

BMS provided STING agonist BMS-986301. Mouse anti-CD19 (clone 1D3), anti-B220 (clone RA3.3A1/6.1), anti-TIM-1 (clone 3B3), anti-PD1 (clone RMP1-14), and anti-VEGFR2 (clone DC101) were purchased from BioXCell (Lebanon, NH). The STING agonist was administered by intramuscular (i.m.) injection (2 mg/kg, weekly, 2-3 doses). Anti-CD19 and anti-B220 depleting antibodies (10 mg/kg, every 5 days for 3 weeks), anti-TIM-1 blocking antibodies antibody (10 mg/kg, every 5 days for 20 days), and anti-PD1 and anti-VEGFR2 blocking antibodies were administered by intraperitoneal (i.p.) injections (anti-PD1: 10 mg/kg, anti-VEGFR2: 20 mg/kg, every 3 days for 21 days). Corresponding isotypes of IgG were administered i.p. at the same frequency as the other antibodies. B-cell depletion was validated by flow cytometry analysis of peripheral blood mononuclear cells collected 5 days after the last antibody dose.

Immunofluorescence

Six-µm-thick frozen sections of murine HCC tissue were prepared for immunofluorescence (IF). We used an anti-CD31 antibody (Millipore, clone 2G8) to identify endothelial cells, an anti-α-SMA antibody (Sigma, clone 1A4) to identify perivascular cells, anti-CD3 (Abcam #ab135372), anti-CD8 (CST, #98941) and anti-CD4 (Abcam, #ab288724) antibodies for T cells staining, and anti-CD19 (Abcam #ab245235, Proteintech #65290-1-Ig) and anti-B220 (R&D #MAB1217) antibodies for B cells staining. Anti-TIM-1 (Abcam #ab316854), anti-IL-10 (Abcam, #ab313401), anti-CD21 (Abcam, #ab318999), and anti-PNAd (BioLegend, #120805) were used for co-staining with anti-B220. All primary antibodies were diluted 1:200 in PBS. All secondary antibodies were purchased from Jackson ImmunoResearch (West Grove, PA, USA). Frozen sections from OCT-embedded tissue blocks were washed with PBS and treated with normal donkey serum (Jackson ImmunoResearch #017000121) for blocking. Primary antibodies were applied overnight at 4 °C, followed by the reaction with corresponding secondary antibodies for 1 h at room temperature. Analysis was performed in random fields in the tumor tissues under ×400 magnification using a laser-scanning confocal microscope (Olympus, FV-1000). Whole-slide scanning was conducted using Zeiss Axio Scan Z1. Data were analyzed using ImageJ (US NIH) and QuPath software⁷⁰.

Lung preparation

Complete lungs were dissected at the hilum from the pulmonary trunk of the heart and immediately immersed in Bouin’s fluid (Electron Microscopy Sciences, #15990-01) for 24 h for the long-term experiment. Lung metastatic burden was assessed by enumerating metastatic nodules on the surface of the lung.

H&E staining

Five-μm-thick sections of murine HCA-1 lung metastatic tissues were deparaffinized in xylene for 5 min × 2 times, rehydrated using a graded alcohol series, and placed in a citrate buffer at 97 °C for 20 min for antigen retrieval. After hydration, hematoxylin was applied for 2 min to stain cell nuclei, followed by a brief rinse in water. Eosin (Sigma-Aldrich #102439) was applied for 1 min to stain the cytoplasm. After mounting the slides, images were taken using a bright-field microscope (Olympus, BX40) under ×40 magnification by a Canon camera. Data were analyzed using QuPath software⁷⁰. 3 regions were randomly selected for each sample for statistical analysis.

RNA sequencing

Total RNA was extracted from the HCC tissues using Qiagen kits. RNA sequencing (RNA-seq) was performed on Illumina Novaseq at the MIT BioMicro Center (Cambridge, MA). FastQC was performed for the quality control of RNA-seq raw data. After quality control, the low-quality bases and adaptor contamination were removed by Cutadapt. The quality of clean yield data was examined again by FastQC software. Next, the clean data were aligned to the mouse reference genome mm39 by STAR. After data mapping, samtools and featureCounts were used to count the number of reads aligned to the gene features. DESeq2 identified the differentially expressed genes. Differentially expressed genes were annotated using REACTOME databases, and the cell type enrichment analysis was performed using the xCell package⁴⁸. The scores calculated by xCell are comparable across samples but not across cell types. The scores calculated by xCell are comparable across samples but not across cell types. For the multi-cohort RNA sequencing analysis, the data were obtained and integrated from our previously published studies^{42,43,44,45,46}; after the batch effect removal by the sva package, the normalized data were used for the cell type deconvolution by the immunedeconv package. To demonstrate the effect size of the cell type score calculated by different methods in immunedeconv, Cohen’s d value was applied to measure the differences of each cell type between the immunoactivator and control groups. The network plot of enriched pathways was performed by the clusterProfiler package. Single-sample gene set enrichment analysis (ssGSEA) was used to calculate the Breg score based on the markers⁵⁴. TCGA data analyses were performed with the log-rank Mantel-Cox test using the web server GEPIA2⁷¹, based on TCGA liver hepatocellular carcinoma (TCGA-LIHC) data.

Single-cell RNA-sequencing and spatial transcriptomic data analysis

Single-cell RNA-seq (scRNA-seq) data were processed following the Seurat package tutorial. Signature scores were computed using the AddModuleScore function, and cell-cell interactions between B cells and other cell populations were examined using the CellChat package according to its standard workflow⁷². Spatial transcriptomic data from HCC clinical samples were analyzed with Seurat. Colocalization was defined as a spot with non-zero expression of both HAVCR1 and either CD79A or CD79B. Spatial images were generated using the SpatialFeaturePlot function.

Flow cytometry analysis

Harvested cells were washed with the buffer and stained with the cell surface antibodies. Anti-mouse CD16/32 antibody (clone 93, Biolegend, San Diego, California, USA) was added for FcR blockade and incubated for 5 min at room temperature; 7-amino-actinomycin D or zombie UV was added for live/dead staining. After another washing step, antibodies for cell phenotyping were added, and cells were incubated for 30 min at room temperature. The monoclonal antibodies used for flow cytometry analysis were specific for CD45 (BioLegend, 30-F11), CD3 (BioLegend, 17A2), CD19 (BioLegend, 1D3/CD19), B220 (BioLegend, RA3-6B2), CD11b (BioLegend, M1/70), CD80 (BioLegend, 16-10A1), IL-10 (BioLegend, JES5-16E3), TIM-1 (BD Biosciences, RMT1-4), PD-L1 (BioLegend, 10F.9G2), MHC II (BioLegend, M5/114.15.2), CD11c (BioLegend, N418), CD86 (BioLegend, GL-1), CD8a (BioLegend, 53-6.7), CD4 (BioLegend, GK1.5), and IFN-γ (BioLegend, XMG1.2). These antibodies were diluted 1:200 in buffer.

Cytokine analysis

Mouse plasma samples were assayed in duplicate using the MSD V-PLEX proinflammatory panel 1 mouse kit, a highly sensitive multiplex enzyme-linked immunosorbent assay (ELISA) for quantitatively measuring 10 cytokines: IFN-γ, interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p70, CXCL1, and tumor necrosis factor (TNF)-α from a single small sample volume (25 μl) using electrochemiluminescence-based detection (MesoScale Discovery, Gaithersburg, MD).

Statistical analysis

Mann–Whitney U test was utilized to compare two groups with quantitative variables. When the experimental cohort includes more than two groups, including quantitative variables, one-way ANOVA with Tukey’s multiple comparisons test was applied unless specified in the figure legends. The Kaplan–Meier method generated survival curves underlying the Log-Rank test and Cox proportional hazard model. The hazard ratio (HR) and 95% CI were calculated for statistical survival analyses for murine models. All analyses were performed using GraphPad Prism 9 (v.9.5.1, GraphPad Software, MA, USA) or R (v.4.3.3), and data were presented as mean values ± SD. The significant difference between experimental groups was determined when p-values were less than 0.05.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The RNA-sequencing data from this study are deposited in the Gene Expression Omnibus (GEO) under accession numbers GSE301030, GSE301138, GSE301139, and GSE301140. The publicly available scRNA-seq data from patients with HCC treated with neoadjuvant anti-PD-1 therapy were obtained from the GEO database with an accession number of GSE206325. The spatial transcriptomic data of HCC samples treated with neoadjuvant anti-PD-1 were obtained from Mendeley Data (https://doi.org/10.17632/skrx2fz79n.1). The publicly available scRNA-seq data on murine B cells were obtained from the GEO database with an accession number of GSE174739. The publicly available TCGA liver hepatocellular carcinoma (TCGA-LIHC) data were obtained from the Broad GDAC Firehose. The remaining data are available within the Article, Supplementary Information, or Source Data file. Source data are provided with this paper.

Code availability

The custom code used for analysis in this study is deposited in a GitHub repository (https://github.com/Lewisen-Liu/HCC_B_cell)⁷³.

References

Llovet, J. M. et al. Immunotherapies for hepatocellular carcinoma. Nat. Rev. Clin. Oncol. 19, 151–172 (2022).
Article PubMed CAS Google Scholar
Villanueva, A. Hepatocellular carcinoma. N. Engl. J. Med. 380, 1450–1462 (2019).
Article PubMed CAS Google Scholar
Vogel, A., Meyer, T., Sapisochin, G., Salem, R. & Saborowski, A. Hepatocellular carcinoma. Lancet 400, 1345–1362 (2022).
Article PubMed CAS Google Scholar
Llovet, J. M. et al. Hepatocellular carcinoma. Nat. Rev. Dis. Prim. 7, 6 (2021).
Article PubMed Google Scholar
Rumgay, H. et al. Global burden of primary liver cancer in 2020 and predictions to 2040. J. Hepatol. 77, 1598–1606 (2022).
Article PubMed PubMed Central Google Scholar
Llovet, J. M., Montal, R., Sia, D. & Finn, R. S. Molecular therapies and precision medicine for hepatocellular carcinoma. Nat. Rev. Clin. Oncol. 15, 599–616 (2018).
Article PubMed PubMed Central Google Scholar
Yang, X. et al. Precision treatment in advanced hepatocellular carcinoma. Cancer Cell 42, 180–197 (2024).
Article PubMed CAS Google Scholar
Abou-Alfa, G. K. et al. Tremelimumab plus durvalumab in unresectable hepatocellular carcinoma. NEJM Evid. 1, EVIDoa2100070 (2022).
Article PubMed Google Scholar
Finn, R. S. et al. Atezolizumab plus bevacizumab in unresectable hepatocellular carcinoma. N. Engl. J. Med. 382, 1894–1905 (2020).
Article PubMed CAS Google Scholar
Pardoll, D. M. The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer 12, 252–264 (2012).
Article PubMed PubMed Central CAS Google Scholar
Sharonov, G. V., Serebrovskaya, E. O., Yuzhakova, D. V., Britanova, O. V. & Chudakov, D. M. B cells, plasma cells and antibody repertoires in the tumour microenvironment. Nat. Rev. Immunol. 20, 294–307 (2020).
Article PubMed CAS Google Scholar
Cyster, J. G. & Allen, C. D. C. B cell responses: cell interaction dynamics and decisions. Cell 177, 524–540 (2019).
Article PubMed PubMed Central CAS Google Scholar
Downs-Canner, S. M., Meier, J., Vincent, B. G. & Serody, J. S. B cell function in the tumor microenvironment. Annu. Rev. Immunol. 40, 169–193 (2022).
Article PubMed CAS Google Scholar
Cabrita, R. et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature 577, 561–565 (2020).
Article ADS PubMed CAS Google Scholar
Calderaro, J. et al. Intra-tumoral tertiary lymphoid structures are associated with a low risk of early recurrence of hepatocellular carcinoma. J. Hepatol. 70, 58–65 (2019).
Article PubMed Google Scholar
Helmink, B. A. et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature 577, 549–555 (2020).
Article ADS PubMed PubMed Central CAS Google Scholar
Petitprez, F. et al. B cells are associated with survival and immunotherapy response in sarcoma. Nature 577, 556–560 (2020).
Article ADS PubMed CAS Google Scholar
Michaud, D., Steward, C. R., Mirlekar, B. & Pylayeva-Gupta, Y. Regulatory B cells in cancer. Immunol. Rev. 299, 74–92 (2021).
Article PubMed CAS Google Scholar
Xiao, X. et al. PD-1hi identifies a novel regulatory B-cell population in human hepatoma that promotes disease progression. Cancer Discov. 6, 546–559 (2016).
Article PubMed CAS Google Scholar
Shalapour, S. et al. Immunosuppressive plasma cells impede T-cell-dependent immunogenic chemotherapy. Nature 521, 94–98 (2015).
Article ADS PubMed PubMed Central CAS Google Scholar
Shalapour, S. et al. Inflammation-induced IgA+ cells dismantle anti-liver cancer immunity. Nature 551, 340–345 (2017).
Article ADS PubMed PubMed Central CAS Google Scholar
Bod, L. et al. B-cell-specific checkpoint molecules that regulate anti-tumour immunity. Nature 619, 348–356 (2023).
Article ADS PubMed PubMed Central CAS Google Scholar
Ablasser A., Chen Z. J. cGAS in action: Expanding roles in immunity and inflammation. Science 363, eaat8657 (2019).
Kong, X. et al. STING as an emerging therapeutic target for drug discovery: Perspectives from the global patent landscape. J. Adv. Res. 44, 119–133 (2023).
Article ADS PubMed CAS Google Scholar
Ishikawa, H. & Barber, G. N. STING is an endoplasmic reticulum adaptor that facilitates innate immune signalling. Nature 455, 674–678 (2008).
Article ADS PubMed PubMed Central CAS Google Scholar
Sun, L., Wu, J., Du, F., Chen, X. & Chen, Z. J. Cyclic GMP-AMP synthase is a cytosolic DNA sensor that activates the type I interferon pathway. Science 339, 786–791 (2013).
Article ADS PubMed CAS Google Scholar
Wu, J. et al. Cyclic GMP-AMP is an endogenous second messenger in innate immune signaling by cytosolic DNA. Science 339, 826–830 (2013).
Article ADS PubMed CAS Google Scholar
Huang, C. et al. Overcoming challenges in the delivery of STING agonists for cancer immunotherapy: A comprehensive review of strategies and future perspectives. Mater. Today Bio 23, 100839 (2023).
Article PubMed PubMed Central CAS Google Scholar
Li, T. & Chen, Z. J. The cGAS-cGAMP-STING pathway connects DNA damage to inflammation, senescence, and cancer. J. Exp. Med. 215, 1287–1299 (2018).
Article PubMed PubMed Central CAS Google Scholar
Marcus, A. et al. Tumor-derived cGAMP triggers a STING-mediated interferon response in non-tumor cells to activate the NK cell response. Immunity 49, 754–763.e754 (2018).
Article PubMed PubMed Central CAS Google Scholar
Zhang, C. et al. Structural basis of STING binding with and phosphorylation by TBK1. Nature 567, 394–398 (2019).
Article ADS PubMed PubMed Central CAS Google Scholar
Luke, J. J. et al. Phase I study of SYNB1891, an engineered E. coli nissle strain expressing STING agonist, with and without atezolizumab in advanced malignancies. Clin. Cancer Res. 29, 2435–2444 (2023).
Article PubMed PubMed Central CAS Google Scholar
Meric-Bernstam, F. et al. Phase I dose-escalation trial of MIW815 (ADU-S100), an intratumoral STING agonist, in patients with advanced/metastatic solid tumors or lymphomas. Clin. Cancer Res. 28, 677–688 (2022).
Article PubMed CAS Google Scholar
Meric-Bernstam, F. et al. Combination of the STING agonist MIW815 (ADU-S100) and PD-1 inhibitor spartalizumab in advanced/metastatic solid tumors or lymphomas: an open-label, multicenter, phase Ib study. Clin. Cancer Res. 29, 110–121 (2023).
Article PubMed PubMed Central CAS Google Scholar
Li, S. et al. STING-induced regulatory B cells compromise NK function in cancer immunity. Nature 610, 373–380 (2022).
Article ADS PubMed PubMed Central CAS Google Scholar
Flood, B. A., Higgs, E. F., Li, S., Luke, J. J. & Gajewski, T. F. STING pathway agonism as a cancer therapeutic. Immunol. Rev. 290, 24–38 (2019).
Article PubMed PubMed Central CAS Google Scholar
Galon, J. & Bruni, D. Approaches to treat immune hot, altered and cold tumours with combination immunotherapies. Nat. Rev. Drug Discov. 18, 197–218 (2019).
Article PubMed CAS Google Scholar
Amouzegar, A., Chelvanambi, M., Filderman, J. N., Storkus, W. J., Luke, J. J. STING agonists as cancer therapeutics. Cancers 13, 2695 (2021).
Samson, N. & Ablasser, A. The cGAS-STING pathway and cancer. Nat. Cancer 3, 1452–1463 (2022).
Article PubMed CAS Google Scholar
Jiang, M. et al. cGAS-STING, an important pathway in cancer immunotherapy. J. Hematol. Oncol. 13, 81 (2020).
Article PubMed PubMed Central CAS Google Scholar
Zhou, J. et al. Guidelines for the diagnosis and treatment of hepatocellular carcinoma (2019 edition). Liver Cancer 9, 682–720 (2020).
Article PubMed PubMed Central Google Scholar
Chen, J. et al. Reprogramming the intrahepatic cholangiocarcinoma immune microenvironment by chemotherapy and CTLA-4 blockade enhances anti-PD-1 therapy. Cancer Immunol. Res. 12, 400–412 (2024).
Article PubMed PubMed Central CAS Google Scholar
Morita, S. et al. Combination CXCR4 and PD1 blockade enhances intratumoral dendritic cell activation and immune responses against hepatocellular carcinoma. Cancer Immunol. Res. 13, 162–170 (2024).
Shigeta, K. et al. Dual programmed death receptor-1 and vascular endothelial growth factor receptor-2 blockade promotes vascular normalization and enhances antitumor immune responses in hepatocellular carcinoma. Hepatology 71, 1247–1261 (2020).
Article PubMed CAS Google Scholar
Shigeta, K. et al. Regorafenib combined with PD1 blockade increases CD8 T-cell infiltration by inducing CXCL10 expression in hepatocellular carcinoma. J. Immunother. Cancer 8, e001435 (2020).
Xiao, Y. et al. Combining p53 mRNA nanotherapy with immune checkpoint blockade reprograms the immune microenvironment for effective cancer therapy. Nat. Commun. 13, 758 (2022).
Article ADS PubMed PubMed Central CAS Google Scholar
Gulen, M. F. et al. Signalling strength determines proapoptotic functions of STING. Nat. Commun. 8, 427 (2017).
Article ADS PubMed PubMed Central Google Scholar
Aran, D., Hu, Z. & Butte, A. J. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 18, 220 (2017).
Article PubMed PubMed Central Google Scholar
Reiberger, T. et al. An orthotopic mouse model of hepatocellular carcinoma with underlying liver cirrhosis. Nat. Protoc. 10, 1264–1274 (2015).
Article PubMed PubMed Central CAS Google Scholar
Katyal, S. et al. Extrahepatic metastases of hepatocellular carcinoma. Radiology 216, 698–703 (2000).
Article PubMed CAS Google Scholar
Ou, L., Lu, G., Cao, M. & Hu, M. Lung metastases after liver cancer resection cured by immunotherapy: case report and literature review. Anticancer Drugs 34, e1–e8 (2023).
Article PubMed CAS Google Scholar
Wu, C., Ren, X. & Zhang, Q. Incidence, risk factors, and prognosis in patients with primary hepatocellular carcinoma and lung metastasis: a population-based study. Cancer Manag Res. 11, 2759–2768 (2019).
Article PubMed PubMed Central Google Scholar
Chen, Y. et al. Differential effects of sorafenib on liver versus tumor fibrosis mediated by stromal-derived factor 1 alpha/C-X-C receptor type 4 axis and myeloid differentiation antigen-positive myeloid cell infiltration in mice. Hepatology 59, 1435–1447 (2014).
Article PubMed CAS Google Scholar
Barbie, D. A. et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature 462, 108–112 (2009).
Article ADS PubMed PubMed Central CAS Google Scholar
Liu, Y. et al. Identification of a tumour immune barrier in the HCC microenvironment that determines the efficacy of immunotherapy. J. Hepatol. 78, 770–782 (2023).
Article PubMed CAS Google Scholar
Magen, A. et al. Intratumoral dendritic cell-CD4(+) T helper cell niches enable CD8(+) T cell differentiation following PD-1 blockade in hepatocellular carcinoma. Nat. Med. 29, 1389–1399 (2023).
Article ADS PubMed PubMed Central CAS Google Scholar
Yang, S. Y. et al. Characterization of organ-specific regulatory B cells using single-cell RNA sequencing. Front. Immunol. 12, 711980 (2021).
Article PubMed PubMed Central CAS Google Scholar
Hu, J. et al. STING inhibits the reactivation of dormant metastasis in lung adenocarcinoma. Nature 616, 806–813 (2023).
Article ADS PubMed PubMed Central CAS Google Scholar
Li, J. et al. Non-cell-autonomous cancer progression from chromosomal instability. Nature 620, 1080–1088 (2023).
Article ADS PubMed PubMed Central CAS Google Scholar
Laumont, C. M. & Nelson, B. H. B cells in the tumor microenvironment: Multi-faceted organizers, regulators, and effectors of anti-tumor immunity. Cancer Cell 41, 466–489 (2023).
Article PubMed CAS Google Scholar
Ishigami, E. et al. Coexistence of regulatory B cells and regulatory T cells in tumor-infiltrating lymphocyte aggregates is a prognostic factor in patients with breast cancer. Breast Cancer 26, 180–189 (2019).
Article PubMed Google Scholar
Bodogai, M. et al. Anti-CD20 antibody promotes cancer escape via enrichment of tumor-evoked regulatory B cells expressing low levels of CD20 and CD137L. Cancer Res. 73, 2127–2138 (2013).
Article PubMed PubMed Central CAS Google Scholar
Ding, Q. et al. Regulatory B cells are identified by expression of TIM-1 and can be induced through TIM-1 ligation to promote tolerance in mice. J. Clin. Invest 121, 3645–3656 (2011).
Article PubMed PubMed Central CAS Google Scholar
Xiao, S. et al. Defect in regulatory B-cell function and development of systemic autoimmunity in T-cell Ig mucin 1 (Tim-1) mucin domain-mutant mice. Proc. Natl. Acad. Sci. USA 109, 12105–12110 (2012).
Article ADS PubMed PubMed Central CAS Google Scholar
Xiao, S., Brooks, C. R., Sobel, R. A. & Kuchroo, V. K. Tim-1 is essential for induction and maintenance of IL-10 in regulatory B cells and their regulation of tissue inflammation. J. Immunol. 194, 1602–1608 (2015).
Article PubMed CAS Google Scholar
Xiao, S. et al. Checkpoint receptor TIGIT expressed on Tim-1(+) B cells regulates tissue inflammation. Cell Rep. 32, 107892 (2020).
Article PubMed PubMed Central CAS Google Scholar
Tofilon, P. J., Basic, I. & Milas, L. Prediction of in vivo tumor response to chemotherapeutic agents by the in vitro sister chromatid exchange assay. Cancer Res. 45, 2025–2030 (1985).
PubMed CAS Google Scholar
Kapanadze, T. et al. Regulation of accumulation and function of myeloid derived suppressor cells in different murine models of hepatocellular carcinoma. J. Hepatol. 59, 1007–1013 (2013).
Article PubMed PubMed Central CAS Google Scholar
Zhou, D. et al. Mst1 and Mst2 maintain hepatocyte quiescence and suppress hepatocellular carcinoma development through inactivation of the Yap1 oncogene. Cancer Cell 16, 425–438 (2009).
Article PubMed PubMed Central CAS Google Scholar
Bankhead, P. et al. QuPath: open source software for digital pathology image analysis. Sci. Rep. 7, 16878 (2017).
Article ADS PubMed PubMed Central Google Scholar
Tang, Z., Kang, B., Li, C., Chen, T. & Zhang, Z. GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res. 47, W556–W560 (2019).
Article PubMed PubMed Central CAS Google Scholar
Jin, S., Plikus, M. V. & Nie, Q. CellChat for systematic analysis of cell-cell communication from single-cell transcriptomics. Nat. Protoc. 20, 180–219 (2025).
Article PubMed CAS Google Scholar
Liu, X. & Duda, D. Inhibiting B cells enhances efficacy of STING agonism or immune checkpoint blockade in hepatocellular carcinoma. Zenodo https://doi.org/10.5281/zenodo.17448321 (2025).

Download references

Acknowledgements

This study was supported by a sponsored research agreement with Bristol Myers Squibb (BMS). D.G.D.’s research is supported by National Institutes of Health (NIH) grants R01CA260857, R01CA254351, R01CA247441, R03CA256764, and P01CA261669, Department of Defense PRCRP grants W81XWH-19-1-0284 and W81XWH-21-1-0738, and a Katz Investigator Award. L.B. was supported by grants from the Cancer Research Institute (CRI), the Bridge project, the Lung Cancer Research Foundation (LCRF), the Torrey Coast Foundation, and the Massachusetts General Hospital (MGH) Transformative Scholars Program and Krantz Family Quantum award. The authors sincerely thank M. Duquette, A. Khachatryan, C. Smith, H. Taniguchi, and S. Roberge (all MGH) for technical support.

Author information

Xin Liu, Zelong Liu & Yue Shi
Present address: The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
Chengzhan Zhu
Present address: Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
Dandan Yuan
Present address: Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
Jianguo Wang
Present address: Zhejiang Provincial People’s Hospital, Hangzhou Medical College, Hangzhou, China
Min Li
Present address: The First Affiliated Hospital of Anhui Medical University, Hefei, China
Aya Matsui
Present address: Kanazawa University Institute of Medical, Pharmaceutical and Health Sciences Faculty of Medicine, Kanazawa, Japan
Dan G. Duda
Present address: Transplant Oncology and Therapeutics Program, Department of Surgery, Houston Methodist Academic Institute, Houston, TX, USA
These authors contributed equally: Xin Liu, Zelong Liu, Chengzhan Zhu.
These authors jointly supervised this work: Lloyd Bod, Dan G. Duda.

Authors and Affiliations

Edwin L. Steele Laboratories for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
Xin Liu, Zelong Liu, Chengzhan Zhu, Tatsuya Kobayashi, Pin-Ji Lei, Yue Shi, Dandan Yuan, Jianguo Wang, Min Li, Aya Matsui, Tomofumi Ando, Ken Kojo, Rieke Schleinhege, Kento Miyazaki, Peigen Huang & Dan G. Duda
Center for Immunology and Inflammatory Diseases and Krantz Family Center for Cancer Research, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
Kassiana Mafra & Lloyd Bod
Center of Hepato-Pancreato-Biliary Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
Ming Kuang
Broad Institute of MIT and Harvard, Cambridge, MA, USA
Lloyd Bod

Authors

Xin Liu
View author publications
Search author on:PubMed Google Scholar
Zelong Liu
View author publications
Search author on:PubMed Google Scholar
Chengzhan Zhu
View author publications
Search author on:PubMed Google Scholar
Tatsuya Kobayashi
View author publications
Search author on:PubMed Google Scholar
Pin-Ji Lei
View author publications
Search author on:PubMed Google Scholar
Yue Shi
View author publications
Search author on:PubMed Google Scholar
Dandan Yuan
View author publications
Search author on:PubMed Google Scholar
Jianguo Wang
View author publications
Search author on:PubMed Google Scholar
Min Li
View author publications
Search author on:PubMed Google Scholar
Aya Matsui
View author publications
Search author on:PubMed Google Scholar
Kassiana Mafra
View author publications
Search author on:PubMed Google Scholar
Tomofumi Ando
View author publications
Search author on:PubMed Google Scholar
Ken Kojo
View author publications
Search author on:PubMed Google Scholar
Rieke Schleinhege
View author publications
Search author on:PubMed Google Scholar
Kento Miyazaki
View author publications
Search author on:PubMed Google Scholar
Peigen Huang
View author publications
Search author on:PubMed Google Scholar
Ming Kuang
View author publications
Search author on:PubMed Google Scholar
Lloyd Bod
View author publications
Search author on:PubMed Google Scholar
Dan G. Duda
View author publications
Search author on:PubMed Google Scholar

Contributions

D.G.D. conceived the study, obtained funding, and supervised the project. X.L., Z.L., C.Z., T.K., P.L., Y.S., D.Y., J.W., M.L., A.M., K.Ma., T.A., K.K., R.S., K.Mi., and P.H. performed the experiments and analyzed data. X.L. performed bioinformatic analyses and wrote the manuscript. M.K. provided funding support. L.B. co-supervised the study. D.G.D. and X.L. drafted the manuscript, and all authors edited and approved the manuscript.

Corresponding author

Correspondence to Dan G. Duda.

Ethics declarations

Competing interests

D.G.D. reports research grants from Bayer, Exelixis, and Surface Oncology, outside the submitted work. The other authors reported no disclosures.

Peer review

Peer review information

Nature Communications thanks Chuanlin Ding and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information (download PDF )

Reporting Summary (download PDF )

Transparent Peer Review file (download PDF )

Source data

Source data (download XLSX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Liu, X., Liu, Z., Zhu, C. et al. Inhibiting B cells enhances the efficacy of STING agonism or immune checkpoint blockade in hepatocellular carcinoma. Nat Commun 16, 10416 (2025). https://doi.org/10.1038/s41467-025-66581-3

Download citation

Received: 11 April 2025
Accepted: 11 November 2025
Published: 08 December 2025
Version of record: 08 December 2025
DOI: https://doi.org/10.1038/s41467-025-66581-3