Targeted inhibition of Nrf2 potentiates antitumor immunity and enhances the efficacy of immunotherapy in hepatocellular carcinoma

Yan Zhu; Maoxuan Liu; Xiaokai Fan; Yingying Xu; Xueling Diao; Jiacheng Bi; Xiaochun Wan; Yehuda G Assaraf; Hang Fai Kwok; Liang Chen

doi:10.1136/jitc-2024-010841

. 2026 Mar 24;14(3):e010841. doi: 10.1136/jitc-2024-010841

Targeted inhibition of Nrf2 potentiates antitumor immunity and enhances the efficacy of immunotherapy in hepatocellular carcinoma

Yan Zhu ^1,^2,⁰, Maoxuan Liu ^3,⁰, Xiaokai Fan ¹, Yingying Xu ¹, Xueling Diao ¹, Jiacheng Bi ⁴, Xiaochun Wan ⁴, Yehuda G Assaraf ⁵, Hang Fai Kwok ^2,^*, Liang Chen ^1,^3,^*

PMCID: PMC13034291 PMID: 41876134

Abstract

Background

Immune checkpoint inhibitors (ICIs) and chimeric antigen receptor T-cell (CAR-T) immunotherapies have revolutionized the treatment of hepatocellular carcinoma (HCC). However, the frequent emergence of treatment resistance significantly limits the clinical efficacy of HCC immunotherapy. The molecular mechanisms underlying therapy resistance remain poorly understood.

Methods

To delineate the immune impact of nuclear factor erythroid 2-related factor 2 (Nrf2) inhibition, we integrated allograft tumor models with bulk and single-cell RNA sequencing analyses. Biochemical assays were performed to investigate the mechanisms underlying Nrf2 inhibition in immune resistance. The combined activity of Nrf2 inhibition with anti-programmed death-1 (PD-1) antibody and CAR-T cell therapy was also explored in vivo.

Results

We show that brusatol (BRU), a specific inhibitor of Nrf2, an emerging regulator of the tumor immune microenvironment, potentiates antitumor immunity in HCC mouse models. Mechanistically, inhibition of Nrf2 downregulates surface programmed death ligand-1 (PD-L1) expression via transcriptional repression in tumor cells, while upregulating major histocompatibility complex (MHC)-I expression via nuclear factor kappa-light-chain-enhancer of activated B cells activation. Inhibition of Nrf2 in tumor cells enhances the activation of immune-related signaling pathways and promotes CD8⁺ T-cell infiltration into tumor tissues. Furthermore, inhibition of Nrf2 with BRU significantly enhances the efficacy of PD-1 antibody and CAR-T cells against HCC in vivo, indicating that therapeutic targeting of Nrf2 in HCC cells sensitizes them to ICIs and CAR-T immunotherapies.

Conclusions

Our findings offer a novel strategy to enhance HCC immunotherapy by blocking Nrf2, which has the potential to address the low response rates observed with current HCC immunotherapies.

Keywords: Hepatocellular Carcinoma, Immunotherapy

WHAT IS ALREADY KNOWN ON THIS TOPIC

Tumor immune resistance has become a significant obstacle to effective hepatocellular carcinoma (HCC) treatment. Several studies have confirmed that nuclear factor erythroid 2-related factor 2 (Nrf2) inhibits effective immune surveillance and response in HCC. Nrf2 decreases the cellular ROS level to evade the tumor-killing effects of immune cells (eg, natural killer cells and cytotoxic T lymphocytes). Besides, Nrf2 activation increases the expression of immunosuppressive cytokines (eg, interleukin-10 and transforming growth afctor (TGF)-β), which leads to the enhanced expression of programmed death ligand-1 (PD-L1) on tumor cells and resistance to immune checkpoint inhibitors therapy. Nrf2 knockdown with specific shRNA leads to programmed death-1 (PD-1)/PD-L1 inhibition and reducing tumor growth in melanoma. Nrf2 gain-of-function mutation results in lower STING expression and reduces infiltration of peripheral immune cells, thereby enhancing the immune escape in HCC.

WHAT THIS STUDY ADDS

Our study confirmed that inhibiting Nrf2 in HCC cells promotes antitumor immunity and elucidated the underlying mechanisms. Mechanistically, Nrf2 inhibition downregulates PD-L1 expression at the transcriptional level. Additionally, for the first time, we uncovered that Nrf2 inhibition increases the phosphorylated status of the p65 subunit, thereby enhancing the major histocompatibility complex-I signaling pathway. We also demonstrated that Nrf2 inhibition (via specific small molecular inhibitor) boosts the therapeutic effects of anti-PD-1 antibody and chimeric antigen receptor-T therapy in mouse models of HCC.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Our study confirms that Nrf2 inhibition in tumor cells is beneficial to antitumor immunity and further reveals the underlying mechanisms. Our study provides new insights and solutions for addressing clinical issues related to anti-PD-1 immunotherapy resistance and offers a new combination strategy for T-cell-based immunotherapy.

Introduction

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with high mortality rates and increasing incidence worldwide.¹ Immune checkpoint inhibitors (ICIs), one of the most effective immunotherapies, have revolutionized the management of HCC in the past few years.² However, despite the marked success of ICIs therapeutics in HCC, only 20% of patients with HCC benefit from ICIs therapy. In addition, some patients develop immune resistance after successful ICIs therapy, which has become a primary impediment for HCC immunotherapy.³ Due to the short application time of immunotherapy in HCC treatment, the mechanisms underlying immunotherapy resistance have not been fully revealed. Further exploration of the mechanisms underlying immunotherapy resistance and development of new therapeutic strategies to surmount this resistance is critical to improve the clinical efficacy of immunotherapy in HCC.

The potential causes of immune resistance to ICIs in patients with HCC are intricate and variable. For example, impaired immune cell antigen recognition and presentation, abnormal immunosuppressive cell activation and proliferation with increased inhibitory cytokines and chemokines, as well as impaired antitumor immune cell proliferation and function in the complex tumor microenvironment (TME), all contribute to the development of immune resistance.³ The programmed death ligand-1/programmed death-1 (PD-L1/PD-1) signaling pathway plays a significant role in tumor immunosuppression, which can inhibit the activation of T lymphocytes and enhance tumor immune tolerance, thereby allowing tumors to evade the immune system.⁴ Elevated PD-L1 levels on HCC cells have been identified as a predictor of recurrence in patients with HCC.⁵ Further exploration of the regulatory mechanisms of PD-L1 in HCC is of great importance to HCC immunotherapy.

The transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) is regarded as one of the main orchestrators of the cellular antioxidant response. Recent studies have revealed that Nrf2 activation alleviates tumor progression6,8 and metastasis,⁹ and contributes to resistance to chemotherapy and radiotherapy.^{10 11} Among the hallmarks of cancer, metabolism and immune evasion represent one of the most intertwined partners.^{12 13} Accumulating evidence has revealed that aberrant Nrf2 expression influences the tumor immune microenvironment (TIME).¹⁴ In advanced lung squamous cell carcinoma (LUSC), Nrf2 affects efficacy outcomes associated with PD-L1 and tumor mutational burden status.¹⁵ Hyperactivation of the Nrf2 antioxidant pathway is responsible for diminished immune responses in Keap1-mutant lung cancer.¹⁶ Moreover, targeted inhibition of Nrf2 has been demonstrated to be an alternative strategy of PD-1/PD-L1 inhibition to activate infiltration of T cells and subsequently inhibiting melanoma growth.¹⁷ However, whether directly inhibiting Nrf2 in tumor cells could potentiate the antitumor immunity and sensitivity to immunotherapy in HCC remains incompletely understood.

Solid tumors often downregulate the major histocompatibility complex class I (MHC-I) to reduce the recognition by, and cytotoxicity of CD8⁺ T cells, thereby evading antitumor immunity.¹⁸ Loss of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) influences the expression of MHC-I molecules or their associated antigen presentation pathway genes in some cancers and therefore affects the response to immunotherapy.¹⁹ In contrast, activation of NF-κB upregulated MHC-I antigen presentation and improved immunotherapy response in tumor cells.²⁰ Importantly, Nrf2 and NF-κB are key regulators of cellular oxidative stress and inflammation. Previous research has confirmed the crosstalk between these two central players. Nrf2 deficiency induced an increasingly aggressive inflammation by leading to the activation of NF-κB and downstream pro-inflammatory cytokines.²¹ However, whether Nrf2 could influence the expression of MHC-I in tumor cells remains unknown.

In this study, we demonstrate that a specific inhibitor of Nrf2, brusatol (BRU), enhances the efficacy of antitumor immunity against HCC. Mechanistically, Nrf2 inhibition decreases PD-L1 expression in tumor cells at the transcriptional level and upregulates MHC-I expression via activating NF-κB in HCC. We further evaluate the addition of BRU to boost the efficacy of anti-PD-1 therapy and chimeric antigen receptor (CAR)-T therapy as a potentially efficacious combination strategy for HCC immunotherapy.

Results

The antitumor activity of Nrf2 inhibition is closely associated with the immune response

Preliminary analysis of gene function in tumor tissues based on patient cohort survival outcomes serves as an effective strategy for inferring gene roles. Accordingly, we performed Kaplan-Meier survival analysis to evaluate the association between Nrf2 expression and overall survival in patients with HCC, stratified by high or low abundance of CD8⁺ T cells. For an efficient statistical analysis, we mainly employed The cancer genome atlas liver hepatocellular carcinoma (TCGA-LIHC) RNA sequencing (RNA-seq) data. As these data used in this study were derived from bulk RNA-seq of tumor tissues, the expression profiles represent signals from mixed cell populations. To accurately examine the combined effect of tumor-cell-specific Nrf2 expression and CD8⁺ T cells on patient prognosis, we first corrected Nrf2 expression values based on tumor purity, thereby obtaining a more specific measure of Nrf2 levels within tumor cells. For estimating the relative abundance of CD8⁺ T cells, we employed two main approaches: one based on the expression level of the CD8A gene, and the other using deconvolution algorithms to infer cellular proportions, allowing us to classify patients into high-abundance and low-abundance groups. To enhance the robustness of our findings and mitigate limitations associated with any single method, we applied three widely used deconvolution algorithms—TIMER,²² xCell,²³ and CIBERSORT²⁴—to comprehensively estimate the relative abundance of CD8⁺ T cells in the TME (figure 1A). The results showed that regardless of whether CD8⁺ T-cell abundance was defined by CD8A expression or by deconvolution algorithms, patients with high CD8⁺ T-cell abundance and high Nrf2 expression exhibited a significantly worse prognosis compared with those with low Nrf2 expression in the same subgroup (figure 1B). In contrast, when patients were not stratified by CD8⁺ T-cell abundance, the impact of Nrf2 expression on survival was not statistically significant, and the hazard ratio (HR) was lower than that observed in the stratified analysis (online supplemental figure S1A). These findings suggest a specific functional interplay between Nrf2 and CD8⁺ T cells within the TME characterized by high CD8⁺ T-cell infiltration, indicating Nrf2 has potential association between antitumor immunity response and Nrf2 levels in HCC. To further investigate the role of Nrf2 inhibition in antitumor immunity, BRU—a well-established specific Nrf2 inhibitor,²⁵ was selected as the pharmacological inhibitor to regulate the functional opening of Nrf2. We compared the antitumor activity of Nrf2 inhibition between immunocompetent and immune-deficient mice in a Hepa1-6 HCC allograft mouse model. For the immune-deficient mice, we chose the Rag1^−/− mice, which lack mature T cells and B cells,²⁶ to determine whether the observed antitumor effects require adaptive immune system, especially T-cell immunity. Tumor-bearing mice were treated with 2 mg/kg BRU²⁵ via intraperitoneal injection every 2 days, while an equal concentration of the solvent dimethyl sulfoxide (DMSO) (1%) was used in the control group (figure 1C). We found that a significant tumor regression was only observed in the immunocompetent mice but not in the immune-deficient mice after BRU treatment (figure 1D,E,F). To further delineate the tumor inhibitory effects of BRU in mice with different levels of immunity, tumor inhibition rate (TIR) was calculated to compare the antitumor activity.²⁷ The BRU-treated immunocompetent group achieved an effective TIR of up to 46% compared with the immune-deficient mice group, which failed to elicit any measurable antitumor response (figure 1G). No significant difference was found in the body weight of mice under BRU treatment, indicating that BRU did not cause severe side effects (online supplemental figure S1B). The above results confirm that the antitumor activity of Nrf2 inhibition is closely associated with immune response.

Nrf2 inhibition enhances antitumor immunity by upregulating immune response genes, increasing immune cell infiltration, and boosting CTLs activity

To explore the mechanism underlying the antitumor immunity of BRU treatment, we performed bulk RNA-seq on tumor tissues from BRU-treated and control mice. Differential gene expression (DEG) analysis of the pre-processed bulk RNA-seq data revealed that the BRU-treated group exhibited significant upregulation of several immune effector genes, including Gzmb, Gzma, Gzme, Tnn, Nos2, Saa3, Cxcl12, Chil3, and Cxcl2, which are associated with tumor cell cytotoxicity (figure 2A). Remarkably, Gene ontology biological processes (GOBP) enrichment analysis revealed that the BRU-treated group was enriched in pathways such as regulation of epithelial cell proliferation, angiogenesis, epithelial-to-mesenchymal transition, cell killing, T-cell activation involved in immune response, T cell-mediated immunity, and granzyme-mediated programmed cell death signaling (figure 2B). Cytotoxic T lymphocytes (CTLs) use the granzyme family of cytolytic serine proteases to elicit cell death of pathogen-infected and malignant cells.²⁸ Granzymes play a pivotal role in immune regulation by modulating the survival of activated lymphocytes.²⁹ The upregulation and enrichment of the granzyme-mediated programmed cell death signaling pathway highlight the critical role of the granzyme family in BRU-mediated antitumor immunity.^{30 31} These findings also suggest an intense and concentrated immune response within the TME following BRU treatment. Gene set enrichment analysis (GSEA) further confirmed the preferential activation of these pathways (figure 2C), supporting the notion that BRU orchestrates a multifaceted immunomodulatory response by simultaneously enhancing cytotoxic mechanisms and suppressing tumor cell proliferation.

To confirm the inhibitory effects of BRU on Nrf2 expression in tumor tissues, we initially used immunohistochemistry analysis to monitor Nrf2 expression levels. Expectedly, markedly reduced Nrf2 levels were observed in the BRU-treated group (figure 2D). As abovementioned, Nrf2 was previously found to regulate PD-L1 expression in malignant melanoma.¹⁷ We therefore examined whether Nrf2 could also regulate PD-L1 expression in HCC tissues. Using immunohistochemical (IHC) analysis, we observed decreased expression levels of PD-L1 in the BRU-treated group (figure 2D), suggesting that BRU significantly reduced Nrf2 expression in tumor tissues and may thereby contribute to the subsequent suppression of PD-L1 (figure 2D).

Since antitumor immunity is accompanied by apoptosis in tumor tissues,³² we determined the levels of active cleaved caspase-3 (Active CCA3).³³ BRU markedly elevated active CCA3 in immunocompetent mice, whereas it had no significant impact on immunodeficient mice (figure 2E). CD8⁺ CTLs, the major effector cell of antitumor immunity, eliminate cancer cells by secreting granzyme B (GzmB), a central cue of apoptosis.²⁹ Therefore, the CD8⁺ CTLs population and CTLs activity was examined by measuring GzmB release. We found that BRU treatment tumors increased the CD8⁺ CTLs population and total GzmB release compared with the control group (figure 2F). Consistently, multiplex CD8⁺ CTLs and TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling) immunofluorescence (IF) analysis showed BRU-induced TUNEL signals concentrated in CD8⁺-enriched regions in immunocompetent mice, with minimal increase in immunodeficient hosts, supporting CTL-mediated rather than an intrinsic apoptotic effect induced by BRU (online supplemental figure S2A).

We further examined the spatial correlation between CD8⁺ T-cell recruitment and PD-L1 expression using multiplex IF (online supplemental figure S2B). In BRU-treated tumors, we observed dense infiltration of CD8⁺ T cells in close proximity to tumor cells. Importantly, these adjacent tumor cells maintained low expression levels of both Nrf2 and PD-L1, in contrast to the expected PD-L1 upregulation typically induced by Tumor infiltrating lymphocytes (TILs)-derived interferon (IFN)-γ.³⁴ To further quantify this regulatory relationship, we performed a correlation analysis based on the fluorescence intensity of the immunostained biomarkers. Notably, among the parameters analyzed, only the expression levels of Nrf2 and PD-L1 exhibited a strongly significant positive correlation (online supplemental figure S2C). This robust statistical association confirms that PD-L1 protein abundance is tightly synchronized with Nrf2 status within the tumor tissue, reinforcing the direct dependency of PD-L1 on Nrf2.

Furthermore, the immune cells from the tumor tissue were isolated and analyzed; we found that BRU treatment significantly increased the fraction of infiltrating CD8⁺ T cells (figure 2G) with single-cell level GzmB expression also increasing after BRU treatment (figure 2H). To confirm that these cells were actively undergoing degranulation, a prerequisite for target cell killing, we assessed the surface expression of CD107a. Flow cytometric analysis revealed a marked elevation of CD107a on CD8⁺ T cells in the BRU-treated group (figure 2H). Furthermore, these cells exhibited enhanced production of IFN-γ (figure 2H). Collectively, these findings demonstrate that BRU treatment induces a fully functional cytotoxic phenotype in CD8⁺ T cells, characterized by increased granule content, active degranulation, and cytokine secretion. BRU did not significantly change the status of other immune cell infiltration, although BRU treatment increased the percentage of M1 type macrophages (figure 2I,J). These findings indicate that Nrf2 inhibition instigated by BRU enhances immune response within the TME and augments CTLs activity, thereby enhancing its therapeutic antitumor effects.

BRU treatment reshapes the tumor immune microenvironment and enhances immune activation

To further investigate changes in the immune microenvironment in tumor tissues in BRU-treated mice, we used CD45⁺ magnetic bead sorting to isolate cells from dissociated tumor tissues and performed single-cell RNA sequencing (scRNA-seq) on the sorted cells. After dimension reduction and clustering, which revealed that both the BRU-treated and control groups contained nine major cell types within the tumor tissues: CD8⁺ T cell, M1 macrophages, neutrophils, M2 macrophages, mitochondrial hyperactive macrophages, regulatory T cells, natural killer (NK) cells, B cells, and plasmacytoid dendritic cell (DC) (figure 3A), which were expressed their characteristic marker genes (online supplemental figure S3A). We next analyzed the changes in cell type composition and proportions between the BRU-treated and control groups. Notably, the number and proportion of CD8⁺ T cells was significantly increased in the BRU-treated group compared with the control group (figure 3B). Further analysis of gene expression differences in CD8⁺ T cells between the two groups showed that BRU treatment led to the upregulation of genes such as Gzmb and Ifng (figure 3C), which are critical for promoting cytotoxic activity. To validate the transcriptional upregulation of effector genes observed in our scRNA-seq data, we analyzed the protein levels of key cytotoxic cytokines in freshly isolated TILs. Flow cytometric analysis confirmed that, in addition to the elevated GzmB levels (figure 2H, left panel), BRU treatment significantly increased the frequency of IFN-γ-producing CD8⁺ T cells compared with the control group (figure 2H, middle panel). These results confirm that the transcriptional activation induced by Nrf2 inhibition translates into a functional cytotoxic phenotype in tumor-infiltrating CD8⁺ T cells. GOBP analysis of the genes upregulated in CD8⁺ T cells from the BRU-treated group revealed enrichment in pathways related to regulation of cell killing, immune response to tumor cells, positive regulation of immune effector processes, immune response-activating cell surface receptor signaling, type II IFN production, and granzyme-mediated programmed cell death signaling (figure 3D). By comparing pathway activation levels between the BRU-treated and control groups, we observed a significant upregulation of these pathways in the BRU-treated group (figure 3E,F, online supplemental figure S3B–E), especially in immune response to tumor cells (figure 3E) and the granzyme-mediated programmed cell death signaling pathway (figure 3F). Further subcluster analysis identified four main CD8⁺ T-cell subsets: effector CD8⁺ T cells (Ccl5-hi), proliferating CD8⁺ T cells, activated/stressed CD8⁺ T cells, and Tcf7⁺ progenitor-like CD8⁺ T cells (figure 3G), which expressed their corresponding biomarker genes (online supplemental figure S3F). Comparing their relative abundances, we found that BRU treatment increased the proportions of effector CD8⁺ T cells (Ccl5-hi), proliferating CD8⁺ T cells, and activated/stressed CD8⁺ T-cell subsets (figure 3H). Moreover, effector CD8⁺ T cells (Ccl5-hi) in the BRU-treated group showed significantly elevated activity in pathways critical for tumor cell killing, including cytotoxic functions, MHC-I antigen presentation, pan-IFN response, and antigen processing and presentation, compared with controls (figure 3I). These findings indicate that BRU treatment robustly enhances CD8⁺ T-cell immune activation, amplifies the functional activity of specific subsets, and promotes tumor-cell-killing capacity within the TIME.

Nrf2 inhibition attenuates PD-L1 expression at the transcriptional level in cancer cells

To further confirm that BRU regulates PD-L1 expression in HCC tumor cells via inhibition of Nrf2 and explore the underlying mechanism of action, we investigated the association between Nrf2 inhibition and PD-L1 using in vitro cell models. We first used a stable CMV (cytomegalovirus)-driven PD-L1 overexpression HeLa cell line (online supplemental figure S4A). Immunoblotting confirmed that BRU treatment effectively reduced endogenous Nrf2 levels, validating the functional activity of the drug in this model (online supplemental figure S4A). Despite the constitutive CMV promoter, cell surface PD-L1 expression was significantly reduced after BRU treatment (online supplemental figure S4B). Consistently, BRU treatment reversed the IFN-γ-induced PD-L1 upregulation in the plasma membrane in a dose-dependent manner (figure 4A). Next, we explore the time course of the inhibitory effect of BRU on PD-L1 expression. To exclude the possibility of spontaneous protein fluctuation, we compared Hepa1-6 cells treated with IFN-γ alone vs those treated with IFN-γ combined with BRU. While Nrf2 and PD-L1 protein levels remained stable or were slightly induced in the presence of IFN-γ alone, the addition of BRU led to a reduction in both proteins (figure 4B). This confirms that the observed downregulation of PD-L1 is specifically driven by BRU-mediated Nrf2 suppression rather than time-dependent variation. The IFN-γ-induced PD-L1 upregulation was also reversed at the messenger RNA (mRNA) levels (figure 4E).

We then constructed stable Nrf2-knockdown (KD) Huh7 cell lines (online supplemental figure S4C) and studied PD-L1 expression; PD-L1 expression in Nrf2-KD cells was significantly decreased compared with vehicle cells (figure 4C). In stable Nrf2-knockdown Huh7 cells, BRU did not further reduce PD-L1 levels compared with vehicle, consistent with a requirement for Nrf2 to sustain PD-L1 expression (online supplemental figure S4D). Importantly, on stimulation with IFN-γ, the induction of PD-L1 was markedly blunted in Nrf2-KD cells compared with vehicle controls (online supplemental figure S4E). This parallel evidence further substantiates that the BRU-mediated decrease in PD-L1 protein is dependent on Nrf2 status. Conversely, ectopic overexpression of Nrf2 increased PD-L1 expression (figure 4D). To verify that BRU-mediated PD-L1 suppression is functionally dependent on Nrf2, we performed a rescue experiment. While BRU treatment reduced PD-L1 levels in vector-transfected control cells, this reduction was significantly attenuated by ectopic Nrf2 overexpression. Although BRU still caused a partial decrease, Nrf2-overexpressing cells sustained markedly higher PD-L1 levels compared with the vector control (online supplemental figure S4F). Combined with our knockdown findings, these findings confirm that BRU suppresses PD-L1 primarily by targeting Nrf2. Consequently, both genetic depletion and pharmacological inhibition of Nrf2 result in a marked decrease in PD-L1 surface expression, thereby exerting antitumor effects.

As Nrf2 is a transcription factor, it might regulate the expression of PD-L1 at a transcriptional level.¹⁷ Therefore, we used the dual-luciferase assay via insertion of the promoter sequence of PD-L1 in the pGL4 luciferase reporter plasmid. Following treatment with BRU, we observed a significant decrease in the relative luciferase activity, indicating that BRU can suppress the expression of PD-L1 at the transcriptional level in a dose-dependent manner (figure 4F). To further validate that Nrf2 inhibition suppresses PD-L1 expression at the transcriptional level, we used a stable Nrf2-KD Huh7 cell line. Our findings revealed a significant decrease in the relative luciferase activity in the Nrf2-KD cell lines, indicating that inhibition of Nrf2 expression leads to transcriptional repression of PD-L1 gene expression (figure 4G). To exclude off-target effects of BRU, we used independent Nrf2 pathway inhibitors, Luteolin and ML385, to corroborate our above findings.35,37 In Hepa1-6 cells, luteolin reduced Nrf2 expression and concordantly decreased PD-L1 abundance (online supplemental figure S4G). Following treatment with luteolin, we also observed a significant decrease in the relative luciferase activity, indicating that luteolin can suppress the expression of PD-L1 at the transcriptional level in a dose-dependent manner (online supplemental figure S4I). Consistently, treatment with the chemically distinct Nrf2 inhibitor ML385 consistently induced a dose-dependent reduction in both Nrf2 and PD-L1 protein levels (online supplemental figure S4H), and similarly suppressed PD-L1 promoter activity as indicated by the dual-luciferase reporter assay (online supplemental figure S4J). These collective data demonstrate that PD-L1 downregulation is Nrf2-dependent rather than an off-target artifact of BRU.

To further validate the clinical relevance and potential applications of our research findings, we analyzed the sample data of patients with HCC in the TCGA database. Consistent with our current findings, Nrf2 expression levels were positively correlated with PD-L1 expression (online supplemental figure S4KK). Taken together, Nrf2 inhibition suppresses the expression of PD-L1 at the transcriptional level, thereby exerting an antitumor immunity effect.

Nrf2 inhibition upregulates MHC-I expression via NF-κB activation in HCC cells

Tumor-associated antigens (TAAs) must be processed before being presented to CTLs through MHC-I. Antigen recognition leads to the activation of the immune response by CTLs.³⁸ However, clinical data has shown that immune escape often occurs in HCC due to a lower expression of MHC-I, although the underlying mechanism remains unknown.³⁹ Moreover, it has been demonstrated that upregulation of MHC-I sensitizes cancer cells to T cell-dependent killing and augments immune checkpoint blockade efficacy.⁴⁰ Considering the importance of MHC-I in TAAs presentation, we sought to investigate whether inhibition of Nrf2 would influence the expression of MHC-I in HCC. Further analysis of MHC-I-mediated antigen processing and presentation pathway was also upregulated in BRU-treated tumor tissues, suggesting an association between Nrf2 and MHC-I (figure 5A). Real-time PCR analysis revealed that BRU treatment increased mRNA levels of several components in the MHC-I pathway, including TAPBP, TAP1, HLA-A, HLA-B, and B2M (figure 5B). In addition, either BRU treatment or tumor cell-specific depletion of Nrf2, elevated cell surface MHC-I expression level, as revealed by flow cytometric analysis (figure 5C,D). We then explored the molecular mechanism underlying the Nrf2 inhibition-dependent increase in MHC-I expression in tumor cells. Previous studies have shown that depletion of endogenous NF-κB significantly decreases MHC-I levels in colon cancer cells.¹⁸ Furthermore, Nrf2 and NF-κB are important regulators of oxidative defense and inflammation and do crosstalk with each other.²¹ We therefore hypothesized that Nrf2 inhibition could mediate NF-κB activation to increase MHC-I expression. Consistent with our hypothesis, either inhibition of Nrf2 or depletion of Nrf2 activates NF-κB expression (phosphorylation of p65) (figure 5E,F). Similar results could be observed in the murine HCC cell line (online supplemental figure S5A). Based on these mechanisms, we used lentivirus to construct a p65-KD Huh7 cell line (online supplemental figure S5B). KD of p65 in Huh7 cells reversed MHC-I upregulation induced by Nrf2 inhibition (figure 5G). BRU treatment had no apparent effect on mRNA levels of components in the MHC-I pathway in p65-KD cells (figure 5H). To directly link Nrf2 inhibition to NF-κB-driven MHC-I upregulation, we performed chromatin immunoprecipitation followed by quantitative polymerase chain reaction (ChIP-qPCR) in BRU-treated Huh7 cells. BRU treatment increased p65 occupancy at the HLA-A and B2M promoter regions in Huh7 cells (figure 5I). These results suggest that Nrf2 inhibition leads to NF-κB activation and subsequent MHC-I upregulation by directly binding to HLA-A and B2M promoter region. To further confirm the association between Nrf2 and MHC-I in clinical specimens, the HCC RNA-seq data in the TCGA database were analyzed, and a negative correlation was observed (online supplemental figure S5C). Together, Nrf2 inhibition upregulates MHC-I expression via activation of p65 in HCC cells.

Nrf2 inhibition potentiates the efficacy of PD-1 antibody against HCC in vivo

Our findings have shown that either gene-specific KD or pharmacological inhibition of Nrf2, significantly downregulated PD-L1 expression at the transcription level and upregulated the MHC-I signaling pathway via NF-κB activation. Furthermore, Nrf2 inhibition upregulated immune-related pathway expression to boost the host antitumor immunity and reshape the TIME. Based on the above findings, we hypothesized that inhibition of Nrf2 may sensitize HCC tumors to anti-PD-1 immunotherapy. Mice were treated with BRU and PD-1 antibody (figure 6A); we found that this combination treatment displayed a significantly stronger antitumor effect compared with the individual treatment groups (figure 6B). The tumor weight in the combination treatment group was significantly reduced compared with the individual treatment groups (figure 6C). Tumor growth in the combination treatment group underwent stronger growth inhibition compared with the individual treatment groups without altering the body weight of mice (figure 6D and online supplemental figure S6C). Furthermore, the immune cells from the tumor tissue were isolated and analyzed; we found that the combination treatment significantly increased tumor-infiltrating CD3⁺ T and CD8⁺ T cells (figure 6E). We also analyzed the surface expression of both PD-L1 and MHC-I in the tumor cells derived from mice tumor tissues. Consistent with the above observation, the combination treatment groups showed lower cell surface PD-L1 levels (figure 6F) as well as higher cell surface MHC-I levels (figure 6G), in comparison with the PD-1 antibody treatment group, as shown by flow cytometric analysis. Similar to the experiments described above (figure 2E,F), we consistently observed increased apoptosis level (ie, active CCA3), a significant increase in tumor infiltration by CD8⁺ T cells and GzmB release in the combination treatment group compared with the single treatment group, based on the multiplex immunofluorescence staining (figure 6H,I).

To provide a more comprehensive immune landscape, we also determined the status of other infiltrating immune cell types in the tumor tissues. The combination treatment groups increased NK cells and DCs relative to either monotherapy and also elevated macrophage abundance (online supplemental figure S6A). In both monotherapies, M1-like macrophages were significantly enriched relative to control; in the combination group the fraction of M1 increased but without attaining statistical significance. M2-like macrophages showed no significant differences among groups (online supplemental figure S6B).

Apart from the antibody therapy, we also explored the combination treatment effects of BMS-8, a novel small molecule inhibitor of the PD-1/PD-L1 interaction, along with BRU in the allograft tumor model (figure 7A). The combination treatment group displayed stronger antitumor activity compared with the individual treatment group (figure 7B). Tumor growth in the combination treatment group underwent stronger growth inhibition compared with the individual treatment groups (figure 7C).

To test whether Nrf2 status modulates PD-1 blockade, we generated stable Nrf2-knockdown (shNrf2) Hepa1-6 single-cell-derived clones (online supplemental figure S6D) and constructed the allograft tumor model (figure 7D). The shNrf2 group displayed an attenuated tumor growth compared with the vehicle (shNC) group, and the anti-PD-1 activity was significantly more effective in the shNrf2 than in the shNC group (figure 7E,F). This indicated that genetic suppression of Nrf2 enhances the therapeutic efficacy of PD-1 blockade in this HCC model, thereby confirming that therapeutic efficacy of BRU is highly dependent on Nrf2. In conclusion, the combination of Nrf2 inhibition with the PD-1/PD-L1 blocking therapy, significantly enhanced the infiltration and activity of CD8⁺ T cells within the tumor tissue and therefore suppressed tumor growth in vivo.

Nrf2 inhibition promotes the efficacy of CAR-T cells against HCC in vivo

Considering the functions of Nrf2 inhibition in avoiding immune escape that was mentioned above, we sought to study whether BRU could potentiate CAR-T cells, another T cell-based immunotherapy, to kill HCC cells in vivo. We established the B-NDG mouse model using human CD19 CAR-T targeting CD19-overexpressing Huh7 cells (Huh7-CD19-OE) to evaluate how BRU modulated CAR-T-mediated cytotoxicity in vivo. Although CD19 is not a clinical target in HCC, this engineered system served as a well-established proof-of-concept to validate the sensitizing efficacy of BRU. Tumor-bearing B-NDG mice were treated with 2 mg/kg BRU via intraperitoneal injection and CD19 CAR-T cells by intravenous injection (figure 8A). BRU treatment combined with the CAR-T cells significantly repressed tumor growth, suggesting that BRU increased CAR-T cell-mediated killing of HCC cancer cells (figure 8B,C). The TILs in the tumor tissues were isolated and analyzed, showing that the populations of CD3⁺ T cells were significantly increased in the combination treatment group (figure 8D). Consistently, immunohistology analysis also showed a higher population of CD3⁺ T cells in the combination treatment group (figure 8E). Furthermore, there were no differences in body weight of B-NDG mice across the different groups (online supplemental figure S7A). Histopathology analysis of internal organs including liver, spleen, lung, and kidney showed that the combination treatment with CAR-T and BRU had no deleterious side effects on mice (online supplemental figure S7B). Long-term safety profiling in the above cohorts showed no biochemical evidence of hepatotoxicity or renal injury across the treatment arms (online supplemental figure S7C–L). Consistent with the aforementioned mechanistic findings, the combination of BRU with CAR-T therapy significantly increased the CD8⁺ CTLs population, active CCA3 levels, and GzmB secretion within tumor tissues (figure 8F,G). Taken altogether, Nrf2 inhibition potentiates CAR-T cells to kill HCC cells in vivo.

Discussion

BRU, a bruceolide from the seeds of Brucea javanica, has been recognized as a specific and potent Nrf2 inhibitor. Mechanistically, BRU selectively reduces Nrf2 protein levels by enhancing its ubiquitination and degradation.²⁵ Therefore, we selected BRU as the pharmacological Nrf2 inhibitor to explore the function of Nrf2 in antitumor immunity.

Nrf2 plays a key role in immunosuppression in the TIME.⁴¹ Recent studies have reported immune-related functions of Nrf2 in T cells. Nrf2 deficiency in T cells, promotes antitumor responses and results in an enhanced tumor rejection in the ROS-rich TME.⁴² On the other hand, Nrf2 activation in human cytotoxic lymphocytes (including NK cells, TILs and CAR-T) could be used to enhance the efficacy of adoptive cell therapy during oxidative stress.⁴³ However, a limited number of studies focused on the immune-related role of Nrf2 in tumor cells. In human KEAP1 mutant non-small cell lung carcinoma, higher levels of Nrf2 are often associated with low T-cell infiltration and unfavorable responses to immunotherapy.⁴⁴ Recent research has confirmed that the Nrf2 gain-of-function mutation results in lower STING expression and reduces infiltration of peripheral immune cells, thereby evading immune surveillance in HCC.⁴⁵ Here, our study confirmed that Nrf2 inhibition in tumor cells is beneficial to antitumor immunity and provided a novel mechanism of action as well.

Given that BRU is a small molecule, it could not be excluded that BRU may influence other targets, in addition to Nrf2. Therefore, apart from pharmacological inhibition of Nrf2 with BRU in our study, we also constructed the Nrf2-KD cell lines, which further validated the role of Nrf2 in our study. Although BRU is widely used to inhibit the Nrf2 axis, it can also attenuate protein synthesis and thereby affect multiple short-lived proteins.^{46 47} Our luteolin and ML385 experiments mitigate this concern by reproducing PD-L1 suppression with independent Nrf2-pathway inhibitors, strengthening the conclusion that PD-L1 regulation in our models is Nrf2-dependent (online supplemental figure S4G–J). However, BRU presents toxicity that cannot be overlooked; notably, it reduces Nrf2 activity in primary human hepatocytes, posing potential safety risks for clinical application.⁴⁸ In this respect, severe side effects of BRU have been observed through early phase clinical studies. Therefore, optimizing BRU specificity and potency to Nrf2 is warranted to reduce adverse effects and improve efficacy, which is currently in urgent need for future clinical applications.⁴⁹ Beyond Nrf2 inhibition, BRU downregulates c-Myc and globally suppresses protein synthesis^{46 50}; bioinformatic predictions identify up to 464 candidate targets.⁵¹ Thus, its activity presumably reflects Nrf2-independent mechanisms, with apparently inevitable off-target effects. We observed that BRU markedly elevated active CCA3 in immunocompetent mice but had no significant effect in immunodeficient mice (figure 2E). Furthermore, BRU-induced TUNEL signals concentrated in CD8⁺-enriched regions in immunocompetent mice, with minimal increase in immunodeficient hosts (online supplemental figure S2A), supporting CTL-mediated rather than BRU-intrinsic apoptosis. However, tumor-intrinsic apoptosis cannot be fully excluded; exploring BRU effects on CD8⁺ T-cell depletion in animal studies is proposed as next steps.

Antigen presentation failure is a key factor leading to the resistance of HCC to ICIs.³ The reduction of MHC-I expression by tumor cells has been closely associated with cold tumors and resistance to immunotherapy.⁵² Fatty acid synthase inhibition attenuates palmitoylation of MHC-I, which leads to its lysosomal degradation and therefore increases MHC-I levels in HCC cells and increases antigen-specific CD8⁺ T-cell cytotoxicity.⁵³ For the first time, we uncovered herein that Nrf2 inhibition could increase the phosphorylated status of the p65 subunit, thereby upregulating the MHC-I signaling pathway. However, a more specific and in-depth mechanism of action needs to be further investigated, which may lay the foundation for the development of more effective strategies to avoid immune escape by upregulating MHC-I in the future. Patients with resistance to anti-cytotoxic T-lymphocyte associated protein 4 (CTLA-4) and anti-PD-1 checkpoint blockade therapy have been found to have reduced expression of NLRC5-dependent MHC-I and CD8⁺ T-cell genes in melanoma.⁵⁴ Environmental transforming growth factor (TGF)-β plays a role in immune evasion and resistance to PD-1 inhibitors by reducing T-cell infiltration and decreasing MHC-I expression in solid tumors.⁵⁵ Inhibiting Nrf2 holds significant potential when combined with these strategies to enhance the response to immunotherapy in solid tumors.

In HCC, both tumor and immune cells exhibit elevated levels of PD-1 and/or PD-L1, which is associated with an increasingly immunosuppressive environment and a poorer prognosis.⁵⁶ For most patients with HCC, the PD-1/PD-L1 pathway is not the sole limiting factor for antitumor immunity. Merely blocking the PD-1/PD-L1 axis is insufficient to elicit a robust antitumor immune response; therefore, combination therapy might be a more effective approach.⁵⁷ Evidence also has shown that Nrf2 pathway activation negatively impacts the sensitivity of atezolizumab-based anti-PD-L1 therapy in LUSC.¹⁵ Based on the mechanisms we explored, we sought to investigate whether Nrf2 inhibition could sensitize HCC cells to ICIs immunotherapy. We found that Nrf2 inhibition with BRU significantly enhanced the effects of anti-PD-1 therapy with decreasing tumor burden and increased CTL activity in a murine HCC model. When we explored the infiltration status of other immune cells in the combination therapy, we noticed the increase in NK cells and DCs in the combination group relative to either monotherapy and also elevated macrophage abundance (online supplemental figure S6A). In both monotherapies, M1-like macrophages were significantly enriched relative to control; in the combination group, the fraction of M1 increased but without attaining statistical significance (online supplemental figure S6B). While we emphasize the leading role of increased CD8⁺ T-cell infiltration in the combination group (figure 6E), one cannot exclude contributions from other immune compartments. NK cells would recruit DCs to promote antitumor immunity; specifically, NK cells are known to secrete chemokines such as CCL5 and XCL1, which are crucial for recruiting conventional type 1 DCs into the TME to initiate the cancer-immunity cycle.^{58 59} Furthermore, PD-L1 on DCs restrains T-cell activation, also suggesting a potential role of DCs here.⁶⁰ As professional antigen-presenting cells, DCs are essential for cross-priming CD8⁺ T cells.⁶¹ Nrf2 inhibition has been reported to facilitate DC maturation and antigen presentation; thus, the elevated DC population likely boosts the initial activation and recruitment of cytotoxic T cells.⁶² Macrophages support CTLs by supplying CXCL9/10, which are necessary for robust responses to checkpoint inhibitors.⁶³ Nrf2 activation is often associated with the polarization of macrophages towards an immunosuppressive M2 phenotype.⁶⁴ By inhibiting Nrf2, BRU may instigate a shift towards pro-inflammatory M1 macrophages, thereby reversing immunosuppression and restoring T-cell function. Thus, the collective increases we observe in NK cells, DCs, and macrophages may provide a mechanistic basis for other immune modalities which are involved in our combination models. Our study provides new insights and solutions for addressing clinical issues related to anti-PD-1 immunotherapy resistance. Future studies are warranted to extend the present findings to other cancer types, and other ICI therapies, such as anti-CTLA-4.

CAR-T therapy has emerged as a promising avenue for the treatment of HCC. However, several major challenges, including an immunosuppressive environment within the tumor and exhaustion, significantly limit the therapeutic efficacy of CAR-T immunotherapy in patients with HCC.⁶⁵ Studies have shown that disruption of PD-1 enhanced the in vivo antitumor activity of CAR-T cells against HCC, improved the persistence and infiltration of CAR-T cells in NSG mice bearing the tumor.⁶⁶ Therefore, we investigated whether Nrf2 inhibition could sensitize HCC cells to CAR-T therapy in vivo. The results confirmed that Nrf2 inhibition could promote CAR-T cells to kill HCC cells in vivo without causing untoward toxicity in mice. Our study provides a new combination therapeutic strategy by which Nrf2 inhibition may sensitize HCC cells to immunotherapy, that of ICIs and CAR-T therapies in particular. Our approach is based on T-cell tumor immunotherapy strategies. Currently, there are also ICIs based on NK cells and macrophages in development.^{67 68} Nrf2 inhibition could be combined with ICIs immunotherapy strategies based on other immune cells, given their different mechanisms of action. Our research may also provide a new combination strategy for immunotherapies, in addition to T-cell-based immunotherapy, which can be further investigated in the future.

While our study provides a compelling preclinical rationale for targeting the Nrf2/PD-L1 axis, we acknowledge the gap between murine models and clinical practice. The TME in patients is far more complex and heterogeneous than in the Hepa1-6 mouse model used herein. Furthermore, although BRU served as an effective pharmacological tool in this study, its clinical safety profile, optimal dosing regimen, and potential off-target toxicities in humans remain to be fully characterized. Therefore, rigorous future clinical validation is warranted to determine whether the synergistic efficacy of BRU and anti-PD-1 observed in mice can be successfully translated to patients with HCC.

In conclusion, our current study illustrates for the first time the antitumor immunity functions and specific molecular mechanisms of Nrf2 inhibition in HCC cells in vitro and in vivo (figure 9). Nrf2 inhibition downregulates PD-L1 expression at the transcription level and upregulates MHC-I expression via NF-κB activation. In addition, we also demonstrated that therapeutic targeting of Nrf2 significantly enhances the efficacy of anti-PD-1 therapy or CAR-T therapy against HCC-bearing mice. Thus, Nrf2 inhibition emerges as a promising combination strategy with immunotherapies, which has the potential to address the low response and frequent resistance to immunotherapy in HCC.

Methods

Plasmids and drugs

Lentiviral vectors expressing Nrf2 shRNAs were purchased from Sigma: Nrf2 (TRCN0000273494 and TRCN0000284999). Plasmid pcDNA3.1-Flag-Nrf2 was purchased from Addgene (#36971). Lentiviral vectors expressing p65 shRNAs⁶⁹ (Human) were constructed in our laboratory. BRU, luteolin, ML385 was obtained from MCE (MCE, Monmouth, New Jersey, USA).

Antibodies

Primary antibodies against the following proteins were obtained from Cell Signaling Technology: Nrf2 (#12721, 1:1000 for WB, 1:200 for IHC, 1:200 for IF), Anti-rat IgG, Alexa Fluor 488 (#4416S, 1:500 for IF), PD-L1 (#13684, 1:1000 for WB; #64988, 1:200 for IF, 1:50 for IHC), NF-κB p65 (#8242, 1:1000), Phospho-NF-κB p65 (#3033, 1:1000), Cleaved Caspase-3 (#9664, 1:200); from Beyotime: Nrf2 (#AF7623, 1:1000 for WB), PD-L1 (#AF7710, 1:1000 for WB); from Proteintech: Cy3-conjugated Affinipure Goat Anti-Rabbit IgG(H+L) (#SA00009-2, 1:200), GAPDH (#10494-1-AP, 1:8000); from AiFang Biology: CD8 (#AFRM0004, 1:200 for IF), Granzyme B (#AFRM0352, 1:200 for IF); from BioLegend: anti-mouse CD45 (#103137, #103138, #103154), anti-mouse CD3ε (#100306, #100216), anti-mouse CD4 (#100451), anti-mouse CD8α (#100722, #100792), anti-human/mouse Granzyme B (#372204, #396408, Isotype ctrl #400141), anti-mouse IFN-γ (#505830, Isotype ctrl #400429), anti-mouse CD107a (#121612, Isotype ctrl #400507), anti-mouse CD274 (#124308, 1:100), anti-mouse CD25 (#102063), anti-mouse F4/80 (#123162), anti-mouse/human CD11b (#101257), anti-mouse CD86 (#105032), anti-mouse Gr-1 (#108416), anti-mouse CD11c (#117328) and anti-human HLA-A2 (#343307); from BD Biosciences (anti-mouse): CD206 (#568273), FoxP3 (#562996).

Cell culture and treatment

Hepa1-6, Huh7 and HeLa cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM, Viva cell), both with 5% CO₂ at 37℃ and supplemented with 10% fetal bovine serum (FBS, HyClone) and 1% penicillin and streptomycin. BRU was added to the complete medium at the indicated concentrations.

Quantitative real-time PCR

Total RNA extraction of the cells was extracted using TRIzol (Invitrogen) and 1 µg RNA was reverse transcribed by the First Strand cDNA Synthesis Kit (Takara). Quantitative RT-PCR was performed using SYBR Green PCR Master Mix (Yeasen) in the ABI 7300 Detection System (Applied Biosystems), using the primers related to PD-L1 and all MHC-I pathway genes⁷⁰ described in the online supplemental table 1.

Immunoblotting

Cells were lysed in sodium dodecyl sulfate (SDS) lysis buffer (Beyotime), mixed in loading buffer, and then boiled for 20 min. The samples were then resolved with sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and analyzed by western blot.

Immunocytochemistry

Place the climbing slides in a 24-well plate and wash them with 400 µL of complete culture medium to ensure they adhere tightly to the bottom. Plate the cells, ensuring the density does not exceed 20,000 cells per well. After processing the cells, collect the slides. First, fix the cells with 4% paraformaldehyde for 15 min, then wash with PBS two times for 5 min each time. Permeabilize the cells with 0.1% Triton-PBS for 15 min, followed by two 5-min washes with PBS. Block with 3% bovine serum albumin (BSA) at room temperature for 30–40 min. Incubate with the primary antibody (diluted in 3% BSA) at room temperature in the dark for 2 hours, followed by three washes with PBS for 5 min each. Incubate with the secondary antibody (diluted in 5% BSA) and 4’,6‑Diamidino‑2‑Phenylindole (DAPI) at room temperature in the dark for 1 hour, then wash three times with PBS for 5 min each. Cover the slide and store it at 4°C.

Immunohistochemistry

IHC staining was performed as follows. Formalin-fixed, paraffin-embedded tissue slides were dewaxed with xylene and rehydrated by a graded series of alcohols, followed by antigen retrieval and peroxidase activity blockade. Then, blocking the tissue slides with 5% BSA for 90 min was performed. Incubation was carried out at 4°C overnight with the primary antibody. Primary antibodies included: anti-Nrf2 polyclonal antibody (1:200, CST), anti-PD-L1 polyclonal antibody (1:50, CST). The anti-rabbit/mouse HRP-conjugate was dripped onto the tissue to cover it completely and then incubated at room temperature for 30 min. Signals were detected using diaminobenzidine (DAB) detection kit (#PK10006, Proteintech). For paired comparisons, pictures were selected at matched anatomical positions on consecutive serial sections. For IHC quantification, we performed background subtraction (ImageJ) prior to DAB intensity measurement, applied an identical threshold across all images, and used a constant DAB color development time for all sections.

Immunofluorescence

Dewaxing the paraffin-embedded tissue slides was conducted as described above and antigen retrieval was performed. Blocking the tissue slides with 2% BSA for 90 min. Incubation was carried out at 4°C in the dark overnight with the primary antibody. Primary antibodies included: anti-cleaved caspase-3 (1:200, CST), anti-CD8 (AiFang Biology, 1:200 for IF), anti-GzmB (AiFang Biology, 1:200 for IF). Incubation with the secondary antibody was carried out at room temperature for 90 min. Hoechst was used to stain the nuclei at room temperature for 10 min. Slides were mounted with medium containing anti-fade reagent and sealed with a coverslip using nail polish.

Tumor allograft mouse models

5 weeks old female C57BL/6J, 5 weeks old female RAG1^−/− mice, 6–8 weeks old female B-NDG mice were raised in specific pathogen-free conditions and were housed with a 12 hours light/dark schedule at 25±1°C and were fed an autoclaved chow diet and water ad libitum. The mice were randomly divided into groups before injection. Tumor volume was calculated by using the formula: length×width²/2 (mm³). At the endpoint of experiments, the mice were sacrificed under anesthesia, and the tumor samples were then collected for further analysis. All animal experiments were undertaken in accordance with relevant guidelines and regulations and were approved by the Institutional Animal Care and Use Committee at Shenzhen Institute of Advanced Technology, ID: SIAT-IACUC-190715-YYS-CL-A0779.

Isolation of immune cells from tumor tissues

The tumors were excised, weighed and then cut into approximately 1 mm³ tissue pieces. These tissue pieces were digested at 37°C in a shaking incubator for 1 hour, after which the digestion was stopped on ice and the tissue was ground using a 70 µm mesh with PBS added to a total volume of 15 mL. Digestion buffer contains: Collagenase I (C0130, 50 mg/mL for 1000X); Collagenase IV (Sigma, C5138, 50 mg/mL for 1000X); DNase I (Takara, TKR-2270A, 5000X). Centrifugation of the cell suspension was performed at 1,060×g for 10 min at 4°C to remove the supernatant. Then the cells were layered on 70% and 42% Percoll solutions and centrifuged 1,260×g for 30 min at room temperature. The middle layer containing the cells was then collected, followed by washing with PBS and cell counting. Finally, the cells were incubated with antibodies and prepared for flow cytometry analysis following the exemplifying gating strategy for analyzing (online supplemental figure S8). IFN-γ and CD107a staining: single-cell suspensions were stimulated with BD Pharmingen Leukocyte Activation Cocktail kit (#550583) for 4 hours prior to surface staining. Following surface staining, cells were permeabilized with the eBioscience Foxp3/Transcription Factor Staining Buffer Set (#00-5523-00) for GzmB and IFN-γ staining. Gating strategies were confirmed using fluorescence minus one (FMO) and isotype controls (online supplemental figure S8). The expression level of GzmB in CD8⁺ T cells was quantified based on the mean fluorescence intensity (MFI) of the APC signal. The “Relative MFI” was calculated by normalizing the MFI of each sample to the average MFI of the control group within the same experimental batch.

CAR plasmid construction and lentiviral package

The CD19-targeting FMC63 single‑chain variable fragment (scFv) was synthesized (Genewiz) and fused to a CAR backbone comprising a human CD8a hinge spacer and transmembrane domain, 4–1BB costimulatory domain, and CD3ζ. The entire coding sequence of the CAR expression molecule was cloned into the lentiviral vector pWPXLd (Addgene). For recombinant lentivirus packaging, the lentiviral plasmids were co-transfected into HEK293T cells with the packaging plasmids psPAX2 and pMD2.G (Addgene) at a ratio of 5:3:2. Lentivirus was harvested 48 hours after transfection.

Generation of CAR-T cells

The CAR-expressing lentiviral vectors were transduced into human primary T cells as previously described, with some modifications.⁷¹ T cells were isolated from peripheral blood mononuclear cells obtained from healthy donors and activated with Dynabeads CD3/CD28 (Thermo Fisher Scientific) at a 1:1 ratio and then cultured in Corning KBM 581 serum-free medium containing interleukin-2 (50 U/mL, Novoprotein). After 24 hours, activated T cells were infected with the lentiviral particles. Seven days after stimulation, the beads were removed. The percentage of CD19 CAR⁺ cells was used to calculate transduction efficiency using flow cytometry.

Analysis of patients with hepatocellular carcinoma bulk RNA sequencing data

The patients with HCC bulk RNA-seq data were acquired from TCGA-LIHC cohort using the following link:

https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-LIHC.htseq_fpkm.tsv.gz;

the data have been normalized by fragments per kilobase million (FPKM) method and transformed by logarithm. After acquiring data, we first change the data to raw FPKM value by this formulation:

m = 2^{k} - 1

Where $k$ is the downloaded expression matrix, $m$ is the adjusted raw FPKM expression matrix. The initial data includes 424 patients, then basic data filtering and cleaning were performed first to remove adjacent normal samples, metastatic samples, and samples without clinical data, finally including 362 samples. The Spearman correlation method was mainly used for calculating the relationship of two variables. The MHC-I related pathway enrichment scores of TCGA-LIHC patients were analyzed using GSVA analysis with GSVA (V.1.52.3) package.

Survival analysis

The effect of gene expression level and cell infiltration on patient survival was mainly analyzed and plotted using the survival (V.3.7.0) and survminer (V.0.4.9) packages. The immunedeconv (V.2.1.0) is a deconvolution method integration package, which was used for estimating tumor purity and CD8⁺ T-cell abundance in TCGA-LIHC (HCC) samples. The Nrf2 expression level was corrected for tumor purity to infer its expression specifically in the tumor cell compartment by the following formula:

E_{c o r r e c t e d} = m a x (0, \frac{E_{r a w} - c \times (1 - p)}{p})

where $E_{corrected}$ is the corrected Nrf2 expression level, $E_{raw}$ is the original Nrf2 expression level, $p$ is tumor purity, and $c$ is the baseline expression level, which was defined by the following formula:

c=\begin{cases} median\left (E_{normal}\right),\ if\ exsits\ in\ normal\ samples\\min\left (E_{tumor}\right)\end{cases}

in our analysis, we selected paratumor normal samples in the TCGA-LIHC cohort as baseline expression level. To analyze the impact of Nrf2 on patient survival prognosis under the influence of CD8⁺ T-cell abundance levels, we first divided patients into high and low CD8⁺ T-cell abundance groups based on their CD8A expression levels or inferred CD8⁺ T-cell abundance. We then performed survival analysis stratified by Nrf2 expression within each CD8⁺ T-cell abundance group to assess its impact under different immune contexts. For comparison, the same analysis was conducted on the entire cohort without CD8⁺ T-cell stratification to evaluate the overall relationship between Nrf2 expression and patient survival. The ggsurvplot function was used to plot the results, and the p value was tested by log-rank test.

Analysis of mouse tumor tissues’ bulk RNA-seq data

For the bulk RNA-seq data from eight mouse tumor tissues (BRU-treated sample 1, BRU-treated sample 2, BRU-treated sample 3, BRU-treated sample 4, control sample 1, control sample 2, control sample 3, and control sample 4), the raw fastq files were quantified using fastqc (V.0.12.1.) and employing trimmomatic (V.0.27) to filter low quality reads. The index of the mouse reference genome was built using HISAT2 (V.2.1.0), and paired-end clean reads were aligned to the reference genome. Then, featureCounts (V.2.0.5) was used for counting reads and acquiring the raw counts. Then we used the Combat_seq method in the sva package (V.3.52.0) to eliminate batch effects among eight samples obtained from two separate sequencing runs. Specifically, BRU-treated sample 1, BRU-treated sample 2, control sample 1, and control sample 2 were collected during the first sequencing run, while BRU-treated sample 3, BRU-treated sample 4, control sample 3, and control sample 4 were collected during the second run. After correcting for batch effects, we applied DESeq2 (V.1.44.0) to calculate DEGs between the BRU-treated and control groups. Genes were considered significantly upregulated or downregulated in the BRU-treated group if their log2 fold change (log2FC) ≥1 or ≤−1, and their adjusted p value≤0.05. We then selected the upregulated genes in the BRU group and performed GOBP enrichment analysis using the ClusterProfiler (V.4.12.6) package. Only pathways with a p value≤0.05 were considered significantly enriched in the BRU-treated group. Additionally, we ranked all genes by log2FC in descending order and used ClusterProfiler to conduct GSEA to identify pathways enriched in the BRU-treated group compared with the control group.

Analysis of mouse tumor tissues single-cell RNA sequencing data

For the scRNA-seq data, we began by processing the raw data using DNBC4 tools (V.2.1.3), then using the Read10X function in the Seurat (V.4.4.0) package. To identify and filter doublets, we calculated the likelihood of doublets using the scDblFinder (V.1.18.0) package with its default parameters. After removing doublets, we integrated the cleaned data and created a Seurat object using the CreateSeuratObject function.

Next, we filtered out cells with mitochondrial gene expression proportions greater than 20%, cells expressing fewer than 700 genes, and cells with total counts below 700 or above 30,000. After completing basic quality control, we normalized the data using SCTransform in Seurat and corrected for mitochondrial gene expression with percent.mt. Dimensionality reduction and clustering were performed using RunPCA, RunUMAP, FindNeighbors, and FindClusters, with the clustering resolution set to 0.1. We used the ScType based on its GitHub tutorial (https://github.com/IanevskiAleksandr/sc-type), AI assistant DeepSeek and marker genes associated with known cell types to annotate the identified cell clusters. For analyzing the proportion of each cell type in different sample groups (BRU-treated and control), we categorized cells based on their sample origin and calculated the relative proportions of different cell types within each group to compare the changes in cell type composition between the BRU-treated and control groups. For differences in gene expression in CD8⁺ T cells between the BRU-treated and control groups, we used the FindAllMarkers function in Seurat. Genes were considered significantly upregulated or downregulated in the BRU-treated group if their adjusted p value≤0.05 and average log2FC ≥0.25 or ≤−0.25. GOBP enrichment analysis was then conducted for genes upregulated in the BRU-treated group.

To assess pathway activity, we used AUCell (V.1.26.0), a widely used tool for evaluating pathway intensities in scRNA-seq data. Pathway activity was calculated for each cell, and comparisons were made between BRU-treated and control groups to determine whether pathways were differentially activated and, overall, whether they were upregulated in the BRU-treated group.

To obtain a higher-resolution characterization of CD8⁺ T-cell subsets, we extracted the CD8⁺ T-cell population and reperformed SCTransform, RunPCA, RunUMAP, FindNeighbors, and FindClusters to identify finer subpopulations. Subsequently, the proportion of each CD8⁺ T-cell subpopulation relative to total cells was compared across control and BRU-treated groups. We then applied AUCell to calculate pathway activity scores for each subpopulation in different groups. Differential activity between groups was assessed using the Wilcoxon rank-sum test, with p values adjusted via the Benjamini-Hochberg method. Fold changes were calculated as the ratio of the mean score in the BRU-treated group to that in the control group. A fold change >1 combined with an adjusted p value ≤0.05 was considered indicative of significant upregulation of the corresponding pathway in the BRU-treated group.

Statistical analysis

Two groups were compared using the two-tailed Student’s t-test and Wilcoxon rank-sum test. Variable correlation analysis was used by Spearman correlation test. Statistical analyses were performed using GraphPad Prism V.8.0 (GraphPad Software) and R V.4.1.0. The p value or adjusted p value<0.05 was considered significant.

Supplementary material

online supplemental file 1

jitc-14-3-s001.pdf^{(2.7MB, pdf)}

DOI: 10.1136/jitc-2024-010841

Footnotes

Funding: This study was supported by Grants 2023YFA0914900 (to LC) from National Key Research and Development Program of China, 32570840 (to LC) from Natural Science Foundation of China, SGDX20220530111004031 (to LC) from Shenzhen Science and Technology Innovation Commission, the Science and Technology Development Fund of Macau SAR (File no. 0069/2025/AFJ), the University of Macau (UM) - Dr Stanley Ho Medical Development Foundation “Set Sail for New Horizons, Create the Future” Grant 2024 (File no. SHMDF-VSEP/2024/002), and the UM Multi-Year Research Grant General Research Grant (File no. MYRG-GRG-2025-0067-FHS).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Ethics approval: All the studies involving human subjects were approved by the Institutional Review Board at Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences (approved ID: SIAT-IRB-190715-H0363) with written informed consent obtained from participants and conducted in accordance with the international ethical guidelines for biomedical research involving human subjects.

Data availability free text: All data relevant to the study are included in the article or uploaded as supplementary information. The sequencing data reported in this paper have been deposited in the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2021) in National Genomics Data Center (Nucleic Acids Res 2022), China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA-Human: HRA025246) which are publicly accessible at https://ngdc.cncb.ac.cn/gsa-human. The corresponding processing codes and data is available in the GitHub repository (https://github.com/BruDrugAnalysisProject/BRU_CTRL_bulk_scRNAseq_data_analysis).

Data availability statement

Data are available upon reasonable request.

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Associated Data

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

Supplementary Materials

online supplemental file 1

jitc-14-3-s001.pdf^{(2.7MB, pdf)}

DOI: 10.1136/jitc-2024-010841

Data Availability Statement

Data are available upon reasonable request.

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PERMALINK

Targeted inhibition of Nrf2 potentiates antitumor immunity and enhances the efficacy of immunotherapy in hepatocellular carcinoma

Yan Zhu

Maoxuan Liu

Xiaokai Fan

Yingying Xu

Xueling Diao

Jiacheng Bi

Xiaochun Wan

Yehuda G Assaraf

Hang Fai Kwok

Liang Chen

Abstract

Background

Methods

Results

Conclusions

WHAT IS ALREADY KNOWN ON THIS TOPIC

WHAT THIS STUDY ADDS

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Introduction

Results

The antitumor activity of Nrf2 inhibition is closely associated with the immune response

Nrf2 inhibition enhances antitumor immunity by upregulating immune response genes, increasing immune cell infiltration, and boosting CTLs activity

BRU treatment reshapes the tumor immune microenvironment and enhances immune activation

Nrf2 inhibition attenuates PD-L1 expression at the transcriptional level in cancer cells

Nrf2 inhibition upregulates MHC-I expression via NF-κB activation in HCC cells

Nrf2 inhibition potentiates the efficacy of PD-1 antibody against HCC in vivo

Nrf2 inhibition promotes the efficacy of CAR-T cells against HCC in vivo

Discussion

Methods

Plasmids and drugs

Antibodies

Cell culture and treatment

Quantitative real-time PCR

Immunoblotting

Immunocytochemistry

Immunohistochemistry

Immunofluorescence

Tumor allograft mouse models

Isolation of immune cells from tumor tissues

CAR plasmid construction and lentiviral package

Generation of CAR-T cells

Analysis of patients with hepatocellular carcinoma bulk RNA sequencing data

Survival analysis

Analysis of mouse tumor tissues’ bulk RNA-seq data

Analysis of mouse tumor tissues single-cell RNA sequencing data

Statistical analysis

Supplementary material

Footnotes

Data availability statement

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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