Hyperactive mevalonate (MVA) metabolic activity is often observed in cancer cells, and blockade of this pathway inhibits tumor cell lipid synthesis and cell growth and enhances tumor immunogenicity. How tumor cell MVA metabolic blockade promotes antitumor immune responses, however, remains unclear. Here we show that inhibition of the MVA metabolic pathway in tumor cells elicits type 1 classical dendritic cells (cDC1)–mediated tumor recognition and antigen cross-presentation for antitumor immunity. Mechanistically, MVA blockade disrupted prenylation of the small GTPase Rac1 and induced cancer cell actin filament exposure, which was recognized by CLEC9A, a C-lectin receptor specifically expressed on cDC1s, in turn activating antitumor T cells. MVA pathway blockade or Rac1 knockdown in tumor cells induced CD8+ T-cell-mediated antitumor immunity in immunocompetent mice but not in Batf3−/− mice lacking CLEC9A+ dendritic cells. These findings demonstrate tumor MVA metabolic blockade stimulates a cDC1 response through CLEC9A-mediated immune recognition of tumor cell cytoskeleton, illustrating a new immune surveillance mechanism by which dendritic cells monitor tumor metabolic dysregulation and providing insight into how MVA pathway inhibition may potentiate anticancer immunity.

Significance:

These findings suggest that mevalonate blockade in cancer cells disrupts Rac1 prenylation to increase recognition and cross-presentation by conventional dendritic cells, suggesting this axis as a potential target for cancer immunotherapy.

The mevalonate (MVA) metabolic pathway produces sterols and isoprenoids that are essential for tumor growth and is often dysregulated in cancer through aberrant cell signaling. Multiple oncogenic signaling pathways can deregulate the MVA pathway for enhanced cell survival and growth. In turn, hyperactive MVA pathway is often observed in cancer cells for regulating the downstream propagation of many cell signals as well as providing essential building blocks for continued tumor cell proliferation (1). The dependence of MVA pathway in cancer cells establishes a tumor vulnerability that can be therapeutically targeted to induce cancer cell death (2). Blockade of MVA metabolic pathway by statin drugs targeting 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), a key step-limiting enzyme of MVA pathway, is commonly used in clinic for lowering blood cholesterol level and may also interfere with cellular protein isoprenylation (1, 3). Importantly, statin use has been associated with prolonged cancer patient survival, but the underlying mechanism is still not completely understood (4). Interestingly, immune system may monitor dysregulated MVA metabolic activity in tumor cells. For example, innate-like γδT cells may recognize isopentenyl pyrophosphate, a metabolic intermediate released from cancer cells of hyperactive MVA pathway, as a phosphoantigen and suppress cancer cell growth (5). On the other hand, inhibition of protein geranylgeranylation enhance expression of MHC-I and costimulatory molecule CD86/CD80 on tumor cells to facilitate T-cell recognition and killing (6). However, whether and how dendritic cells enforce surveillance over cancer MVA metabolic blockade to engage antitumor immune response is largely unclear.

Cancer immunotherapy have achieved tremendous success on treating multiple types of cancers (7), and combinational therapy with conventional chemotherapy or targeted therapy further improved immunotherapeutic efficacy (8). The initiation of antitumor immune response requires immune recognition of tumor (9). Antigen presenting cells, mainly dendritic cells (DC), recognize tumor antigens expressed on tumor cells and process them and presented to T or B cells for adaptive immunity against cancer. In addition to antigen recognition, dendritic cells also sense so-called pathogen-associated molecular patterns (PAMP) or danger-associated molecular patterns (DAMP) derived from pathogens or tumor cells via innate immune receptors and activate a plethora of signaling pathways to promote DC maturation and antigen presentation, thereby bridging innate immunity and adaptive immunity (9). Certain therapeutic interventions, including some specific chemotherapy, radiotherapy, molecular targeted therapy, and so on, could kill tumor cells and increase antigen exposure and stimulate immune recognition of tumor cells. Under such circumstance, tumor cells undergo immunogenic cell death (ICD), which was featured by the release of DAMPs accompanied with tumor cell death (10, 11). Many DAMPs such as ATP, calreticulin (CRT), and HMGB1, which locate inside the healthy cells, were released extracellularly as “danger signals,” binding to innate immune receptors on antigen presenting cells and activate them through inflammatory pathways (12). On the other hand, some DAMPs such as actin filament (F-actin) from necrotic cells would activate a specific c-type lectin receptor, CLEC9A, on a subset of DCs called type I conventional DCs (cDC1), and facilitate intracellular antigen routing and processing to promote antigen cross-presentation without eliciting inflammatory response (13, 14). Whether MVA metabolic blockade in tumor cells can act as a “danger signal” to antigen presenting cells is unknown.

We previously set up an adapted in vitro antigen presentation assay to screen ICD-inducing drugs from a FDA-approved drug library (15). In this assay, we chose a low-immunogenic B16-OVA cell line that can only activate T cells in the presence of dendritic cells and identified six statin drugs that could inhibit tumor MVA pathway and promote tumor cell-induced immune activation. Here, we further validate that pharmacologic or genetic inhibition of MVA pathway induces ICD of tumor cells. We find that blockade of protein prenylation, specifically, RAC1 geranylgeranylation, but not cholesterol synthesis, mediates tumor MVA metabolic inhibition-induced immune activation. Defective RAC1 geranylgeranylation induces tumor cell actin filament exposure, which is recognized by CLEC9A receptor on cDC1 and promote tumor antigen cross-presentation and subsequent antitumor immune response. Therefore, our studies reveal that conventional dendritic cells may sense tumor MVA metabolism blockade through CLEC9A-mediated immune recognition of tumor cell cytoskeleton, thus illustrate a new mechanism by which immune cells monitor tumor metabolic dysregulation, and how MVA pathway inhibition may potentiate anticancer immunity.

Cell lines culture

The B16 and HEK293 cell lines were obtained from ATCC. MC38 cells was kindly gifted by Dr. Yang Xuanming at Shanghai Jiaotong University, Shanghi, China. B16-OVA cells were constructed by stably expressing ovalbumin (OVA) cDNA on B16 cells. The PDAC murine pancreatic cancer cell line was derived from a spontaneous pancreatic cancer tissue of a K-rasG12D; p53R172H; Pdx1-Cre mouse (16). B3Z hybridoma cells were kindly gifted by Dr. Nilabh Shastri from the University of California. All cell lines were tested as being Mycoplasma free once a month and were not passaged for more than 3 months. All cells were maintained with either DMEM (Invitrogen) or RPMI1640 (Invitrogen) supplemented with 10% FBS and 1% penicillin–streptomycin in a humidified incubator at 37°C and 5% CO2.

Primary cells culture

BMDCs were generated by isolating bone marrow cells from 6- to 8-week-old female mice and cultured with GMCSF and IL4 (Peprotech, 315-03, 214-14, 20 ng/mL) or with FLT3L (Peprotech, 250-31L, 100 ng/mL). The culture media was refreshed every 2 days and BMDCs were used 7 days after culture. CD8+ OT-I T cells were isolated from the spleen and lymph nodes of 8-week-old OT-I mice using MagniSort Mouse CD8 T-Cell Enrichment Kit (Thermo Fisher Scientific, 8804-4622-74). BMDCs and OT-I T cells were both cultured in RPMI1640 (Gibco, 11875–176) supplemented with 10% FBS, 1% penicillin–streptomycin and 55 μmol/L 2-mercaptoethanol (Gibco, 21985023). BMDCs were also supplemented with MEM Nonessential Amino Acid (Gibco, 11140050), HEPES (Gibco, 15630130), and sodium pyruvate (Gibco, 11360070) in a humidified incubator at 37°C and 5% CO2.

Reagents and mice

DMSO (D2650), chlorophenol red β-d-galactopyranoside (220588), cholesterol (C8667), and GGPP (G6025) were from Sigma-Aldrich. Pitavastatin, simvastatin, fluvastatin, lovastatin, pravastatin, and atorvastatin were all from MicroSource Discovery System Inc. GGTI-298 (C4057) and FTI-277 (B5842) were from Apexbio Inc. Zaragozic acid A (sc-391058) was from Santa Cruz Biotechnology. Six to 8-week-old female C57BL/6J (B6) mice were purchased from the Vital River Laboratory. OT-I mice and Batf3−/− mice were obtained from The Jackson Laboratory. All the mice were maintained under specific pathogen-free conditions and all the animal procedures were approved by the Institutional Animal Care and Use Committee of Sun Yat-sen University.

LacZ and Gaussia luciferase reporter assay

The procedures for lacZ activity measurement were performed according to a previously described protocol (17). Briefly, B3Z T cells in the cell culture plate were lysed by 50 μL LacZ lysis buffer and were freeze-thawed, followed by adding with 50 μL PBS containing 0.5% bovine serum albumin and 100 μL substrate solution (1 mg/mL chlorophenol red β-d-galactopyranoside) dissolved in β-galactosidase buffer. The plate was incubated at 37°C for 5–10 hours until color development reached a proper level, followed by color intensity reading at 590 nm using a microtiter plate reader.

For Gaussia luciferase activity measurement, 50 μL culture medium from tumor cells expressing HMGB1-Gaussia luciferase reporter vector (HMGB1-Gluc) were collected to measure luciferase activity by using the Renilla Luciferase Assay System (Promega, E2820) according to the manufacturer's instructions.

Construction of Rac1-CAAX B16-OVA cells

The expression vector of pCDH-3×Flag-2-T2A-puro-WT mRac1 and pCDH-3×Flag-2-T2A-puro-WT mRac-1 CAAX were synthesized by Synbio Technology. The Rac1 knockdown B16-OVA cells were infected by lentivirus expressing WT or CAAX mRac1. The expression of RAC1 protein was validated by Western blot analysis.

Detection of cell death and apoptosis, surface CRT staining

B16-OVA tumor cells were seeded in 24-well multiple plates, then treated with specific reagents for an indicated time point(s). Tumor cell apoptosis was assessed by Annexin V–Propidium Iodide Apoptosis Detection Kit (BD Biosciences, 556547). Tumor cells were stained with CRT (Abcam, ab2907) and subsequently stained with Alexa Fluor-488 conjugated secondary antibody (Cell Signaling Technology, #4412) followed by flow cytometry (BD-LSRFortessaX-20) and analyzed using FlowJo 10.0.

F-actin staining and immunofluorescence

F-actin was stained using Rhodamine-Phalloidin Reagent (PHDR1, Cytoskeleton, Inc.). Cells were washed with PBS and fixed 15 minutes with 4% formaldehyde (Sigma-Aldrich). Fixed cells were permeabilized for 10 minutes using 0.1% Triton and washed three times with PBS. F-actin was stained for 1 hour with phalloidin dye diluted in PBS (100 nmol/L). For immunofluorescence, cells were blocked with 3% BSA in PBS for 30 minutes after fixation and permeabilization. Then cells were incubated with RAC1 antibody in PBS containing 3% BSA at 4°C overnight. After three times wash by PBS, cells were incubated with FITC-conjugated secondary antibody (Cell Signaling Technology, #4408). Nuclei were stained in Parallel using 100 nmol/L DAPI (C1002, Beyotime). After cells were washed three times with PBS, pictures were obtained using the Confocal Microscope (LSM880, ZEISS).

T cells activation and in vitro T-cell cytotoxic assay

B16-OVA tumor cells were treated with specific reagents for an indicated time point(s). Treated tumor cells were then cocultured with BMDC and T cells (B3Z T or OT-I cells) at a ratio of 1:1:5 for additional indicated time point(s). The LacZ activity was performed as described previously. Secretion of IL2 and IFNγ were measured by ELISA Kits (eBioscience, 88-7024-88; 88-7314-22). T cells were stained with fluorescence-labeled antibodies against CD8α (eBioscience, 11-0081-82), CD69 (Biolegend, 104514), followed by analysis on flow cytometry (BD-LSRFortessaX-20).

For detecting T-cell cytotoxic effect, the LDH release was measured by CytoTox96 Non-Radioactive Cytotoxicity Assay Kit (Promega, G1780). The procedure was performed following the kits' instructions. Briefly, LDH is a cytosolic soluble enzyme that will leak into culture medium when cells undergo cell death. Then the enzyme activity in the medium was quantified by a colorimetrical assay to reflect the cytotoxic effect of T cells. The percentage cytotoxicity was calculated in the formula: Percent cytotoxicity (%) = 100 × (OD490 of coculture experiment − OD490 of target cells − OD490 of effective cells − OD490 of culture media)/OD490 of whole cell lysis.

In vitro antigen presentation assay

B16-OVA tumor cells were treated with specific reagents for an indicated time point(s). Treated tumor cells were then cocultured with BMDCs at a ratio of 1:1 for 24 hours. Cells were harvested and were stained with antibodies against CD11c (61-0114-82, eBioscience), H2kb-SIINFEKL (17-5743-80, eBioscience), MHC-II (11-5321-82, eBioscience). Fluorescence data were acquired on a flow cytometry (BD-LSRFortessaX-20) and analyzed using FlowJo 10.0.

Tumor growth, treatment, and analysis

For the immunization experiments, 5 ×105 B16-OVA cells, either freeze-thawed six times in liquid nitrogen, or treated with 100 μg/mL Cisplatin, were inoculated subcutaneously into the ventral right flank of B6 mice. Seven days later, 2 × 105 live B16-OVA cells were inoculated into the dorsal right flank, and the tumor growth was monitored. For bilateral tumor inoculation experiments, lovastatin- or DMSO-treated PDAC or MC38 cells (1 × 106), B16-OVA cells (5 × 105) were inoculated subcutaneously into the dorsal right flank of B6 mice, whereas the opposite site was inoculated by untreated WT PDAC or MC38 cells (1 × 106), B16-OVA cells (2 × 105). Similarly, shRac1 or shScr B16-OVA cells (5 × 105) were inoculated subcutaneously into the dorsal right flank of B6 mice, whereas the opposite site was inoculated by untreated live WT B16-OVA cells (2 × 105). The tumor volume was calculated as 0.5 × tumor length × (tumor width)2, where the longer dimension was considered as the tumor length. For CD8+ T-cell depletion animal experiments, the mice were treated with anti-mouse CD8α (BioXCell, Clone 53-6.7, BE0004-1) or IgG isotype control (BioXCell, Clone 2A3, BE0089) on day −1, 3, and 7 since B16-OVA cell inoculation. For in vivo CLEC9A+ DC blocking experiments, B6 mice were treated with anti-mouse CLEC9A (Leinco Technologies Inc., Clone 1F6, I-2020) or isotype control IgG on day 0, 3, and 7 since tumor inoculation. For immunophenotyping analysis of tumor microenvironment, B16-OVA cells (5 × 105) or MC38 (1 × 106) tumor cells were subcutaneously injected into the dorsal right flank of B6 mice. Tumors were allowed to grow for 5 days and lovastatin (dissolved in 30% PEG400 + 0.5% Tween 80 + 5% propylene glycol) or vehicle was administered by intratumorally injection (0.75 mg/mouse) at day 5. For analysis of immune cells populations, mouse tumors were dissociated by gentle MACS (Miltenyi Biotec) and filtered through 70 μm cell strainers to generate single-cell suspensions, then stained with antibodies against CD45 (eBioscience, 48-0451-82), CD8 (eBioscience, 11-0081-82), IFNγ (eBioscience, 25-7311-82) for T-cell analysis, stained with CD11c (eBioscience, 11-0114-82), CD103 (BD Biosciences, 562772) for DC analysis. Fluorescence data were acquired on a flow cytometry (BD-LSRFortessaX-20) and analyzed using FlowJo 10.0.

Analysis of cancer patient data

MVAGGPP score was a signature of MVA pathway genes expression involved in GGPP synthesis, which is consist of HMGCR, MVK, PMVK, MVD, FDPS, and GGPS1. The calculation of MVAGGPP score were executed by GSVA package in R. The immune cells infiltration levels were conducted by TIMER 2.0 (http://timer.cistrome.org/; ref. 18). Immune estimation of CD8+ T cells, dendritic cells, and cytotoxicity score were calculated by MCPCOUNTER algorithm. Level of activated dendritic cells and immune score were calculated by XCELL algorithm. For overall survival (OS) analysis, The Cancer Genome Atlas (TCGA) tumor patients were divided into four groups based on RAC1 expression and MVAGGPP score, or RAC1 and CLEC9A expression. The median of gene expression was used as cut-off value to divide patients into different groups.

Quantification and statistical analysis

All results are expressed as the mean ± SEM. Unpaired two tailed Student t test was used for comparison of two groups. One-way ANOVA was used for comparison within multiple groups. Two-way ANOVA was performed when both time and treatment were compared or when two types of treatment involved. Comparisons of animal vaccine experiment were analyzed by log-rank (Mantel–Cox) test. Data were analyzed using GraphPad Prism 6. Statistical significance was defined as *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Inhibition of tumor MVA pathway activates antitumor immunity

We previously screened a small library of FDA-approved drugs for their potential for inducing ICD of tumor cells via an adapted antigen presentation assay (15). In this assay, B16-OVA mouse melanoma cells were treated by drugs for 24 hours, followed by co-culture with bone marrow-derived dendritic cells (BMDC) and B3Z T cells (a OVA-specific CD8+ T-cell hybridoma), and the T-cell activation was measured by IL2 promoter-driven LacZ reporter gene activity (Fig. 1A). In addition to a few chemotherapeutic drugs, we found that B16-OVA mouse melanoma cells treated with six types of statins all significantly activated the IL2-driven LacZ reporter gene in B3Z T cells in the presence of DCs (as antigen-presenting cells), whereas dead cells by freeze-thawing could not activate B3Z T cells (Fig. 1B). Notably, B16-OVA cells did not directly activate T cells without DCs in this experimental setting (Supplementary Fig. S1A), which allow us to evaluate DC-mediated cross-presentation of tumor antigen from tumor cells with different treatments. In line with this finding, specific knockdown of HMGCR enzyme, the metabolic target of statin drugs, by Hmgcr-specific siRNAs in B16-OVA cells also activates IL2 reporter in T cells (Fig. 1C; Supplementary Fig. S1B). Statin treatment on Hmgcr-knockdown B16-OVA cells could not further activate LacZ reporter activity in B3Z cells in the presence of DCs, confirming that statins enhanced immunogenicity of tumor cells by targeting HMGCR (Supplementary Fig. S1C). Consistent with the increased LacZ activity on B3Z T cells, the supernatant levels of cytokines IL2 and IFNγ significantly increased in primary OT-I T cells (CD8+ T cells that specifically recognize OVA antigen) cocultured with BMDCs and tumor cells pretreated with statins (Fig. 1D and E) or Hmgcr-specific siRNAs (Fig. 1F and G). Meanwhile, the proportion of T cells expressing the activation marker CD69 also significantly increased after coculture (Fig. 1H and I). We next checked the cytotoxic killing effect of OT-I cells over B16-OVA cells by measuring the lactate dehydrogenase (LDH) released from membrane-damaged B16-OVA cells induced by T-cell killing. LDH assay showed that cytotoxic killing effect of OT-I cells was also increased over B16-OVA cells pretreated with HMGCR inhibition by statins or siRNAs (Fig. 1J and K). Thus, inhibition of MVA metabolic pathway on tumor cells promotes dendritic cells-mediated activation of CD8+ T cells in vitro. To further validate the immunogenicity-inducing effect of statins in vivo, we inoculated B6 mice with B16-OVA cells pretreated with lovastatin or freeze-thawed cells on the right flank (in situ), and live untreated tumor cells on the left flank (abscopal; Fig. 1L). As expected, both lovastatin and freeze-thawed treatment inhibited in situ tumor growth from inoculation, but only lovastatin pretreated tumor cells inhibited the tumor growth on the opposite flank (Fig. 1M and N). Similar results were observed on MC38 or PDAC tumor models (Supplementary Figs. S1K–S1N). As another line of evidence for ICD-inducing effect of HMGCR inhibition, statin treatment or siRNAs targeting Hmgcr upregulated cell surface expression of CRT, an important ICD marker that serve as “eat-me” signal for tumor immune recognition (Supplementary Figs. S1D and S1E), and significantly increased cell death (Supplementary Figs. S1F and S1G). It has been reported that statins mainly induced apoptosis (2), whereas cells undergoing necroptosis was considered more immunogenic than those of apoptosis (19). Interestingly, blockade of apoptosis by a pan-caspase inhibitor (Z-VAD-FMK), but not necroptosis inhibitor (necrostatin1), inhibited statin-treated tumor cells-induced IL2 production by T cells (Supplementary Fig. S1H). It is therefore likely that the dying cell-released immunogenic signals, rather than the way cells undergoing death, determine the cell immunogenicity induced by statin. Statins also induced release of HMGB1, another putative ICD marker, in PDAC (a mouse pancreatic cancer cell line) and MC38 cells (a mouse colon cancer cell line) (Supplementary Figs. S1I and S1J). Furthermore, intratumor injection of lovastatin significantly inhibited tumor growth on MC38 tumor-bearing mice (Supplementary Fig. S1O) accompanied with markedly increased tumor infiltration level of CD8+ T cells (Supplementary Fig. S1P), indicating the involvement of CD8+ T cells in MVA pathway inhibition-induced tumor suppression in vivo. These results suggest that MVA pathway inhibition by statins or Hmgcr knockdown induce tumor cells undergoing ICD, which may in turn activate dendritic cell and CD8+ T-cell-mediated antitumor immunity.

Figure 1.

Inhibition of MVA pathway in tumor cells induces antigen specific CD8+ T-cell activation. A, Schematic illustration of LacZ assay reflecting the IL2 promoter-driven reporter gene activation of B3Z cells by BMDCs primed with B16-OVA cells pretreated with drugs or siRNAs. B and C, LacZ reporter activity was measured as a marker for B3Z T-cell activation. B16-OVA cells were treated with drugs for 16 hours or Hmgcr siRNAs for 48 hours, then cocultured with BMDC and B3Z T cells for 24 hours. The freeze-thawed cells were used as a negative control. DI, B16-OVA cells were pretreated with HMGCR inhibitors for 16 hours (D, E, and H) or Hmgcr siRNAs for 48 hours (F, G, and I), then cocultured with BMDC and OT-I for 24 hours, the production of IL2 and IFNγ was measured by ELISA (EG), and the activation status of OT-I cells was determined by CD69 expression by FACS (H and I). J and K, The cytotoxic effect of OT-I was measured by LDH release of B16-OVA cells after cocultured with BMDC and OT-I for 6 hours. L, Schematic illustration of bilateral tumor inoculation experiment to show different tumor cells inoculated in situ and untreated live tumor cells inoculated on abscopal site. M and N, B16-OVA cells were treated with freeze-thawed procedure or lovastatin, then injected on the left flank of B6 mice. Live untreated (NT) B16-OVA cells were inoculated on the opposite flank. The tumor growth was recorded for both sides. Data in BK are shown as mean ± SEM of three independent experiments. Bilateral tumor volume is shown as mean ± SEM; n = 6 per group. *, P < 0.05, **, P < 0.01, ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Dunnett posttest (BK), by two-way ANOVA with Sidak posttest (M and N).

Figure 1.

Inhibition of MVA pathway in tumor cells induces antigen specific CD8+ T-cell activation. A, Schematic illustration of LacZ assay reflecting the IL2 promoter-driven reporter gene activation of B3Z cells by BMDCs primed with B16-OVA cells pretreated with drugs or siRNAs. B and C, LacZ reporter activity was measured as a marker for B3Z T-cell activation. B16-OVA cells were treated with drugs for 16 hours or Hmgcr siRNAs for 48 hours, then cocultured with BMDC and B3Z T cells for 24 hours. The freeze-thawed cells were used as a negative control. DI, B16-OVA cells were pretreated with HMGCR inhibitors for 16 hours (D, E, and H) or Hmgcr siRNAs for 48 hours (F, G, and I), then cocultured with BMDC and OT-I for 24 hours, the production of IL2 and IFNγ was measured by ELISA (EG), and the activation status of OT-I cells was determined by CD69 expression by FACS (H and I). J and K, The cytotoxic effect of OT-I was measured by LDH release of B16-OVA cells after cocultured with BMDC and OT-I for 6 hours. L, Schematic illustration of bilateral tumor inoculation experiment to show different tumor cells inoculated in situ and untreated live tumor cells inoculated on abscopal site. M and N, B16-OVA cells were treated with freeze-thawed procedure or lovastatin, then injected on the left flank of B6 mice. Live untreated (NT) B16-OVA cells were inoculated on the opposite flank. The tumor growth was recorded for both sides. Data in BK are shown as mean ± SEM of three independent experiments. Bilateral tumor volume is shown as mean ± SEM; n = 6 per group. *, P < 0.05, **, P < 0.01, ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Dunnett posttest (BK), by two-way ANOVA with Sidak posttest (M and N).

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Geranylgeranyl pyrophosphate depletion mediates MVA pathway inhibition-induced tumor cell immunogenicity

MVA pathway bifurcates from the production of Farnesyl pyrophosphate (FPP), one goes into the process of cholesterol synthesis and another one is responsible for the production of geranylgeranyl pyrophosphate (GGPP; ref. 1). To delineate which pathway is responsible for the immunogenicity change, we used zaragozic acid A, the inhibitor of squalene synthase, to specifically suppress the synthesis of cholesterol from FPP (Fig. 2A). However, treatment of zaragozic acid A on B16-OVA cells did not enhance T-cell activation (Fig. 2B and C), suggesting that blockade of cholesterol synthesis is unlikely the main cue for enhanced tumor immunogenicity. We next focus on the biological function of GGPP. GGPP and FPP serve as substrates for geranylgeranyl transferases I/II (GGTase I/II) and farnesyl transferase (FTase), respectively, which are responsible for protein isoprenylation (20). Interestingly, pretreatment of tumor cells with GGTase I inhibitor GGTI-298, but not FTase inhibitor FTI-277, activated T cells (Fig. 2B and C), indicating that blockade of GGPP synthesis may induce tumor immunogenicity. Consistently, inhibition of geranylgeranylation by GGTI-298 also induced upregulation of ICD markers, such as CRT membrane translocation and HMGB1 secretion by tumor cells, and increased cell death (Supplementary Figs. S2A–S2C). Furthermore, tumor cells treated with siRNA knocking down Ggps1 gene encoding geranylgeranyl pyrophosphate synthase (Supplementary Fig. S2D), the enzyme responsible for synthesis of GGPP from FPP, also activated IL2 and IFNγ production by T cells (Fig. 2D and E). Importantly, supplement of GGPP, but not cholesterol, reversed T-cell activation induced by B16-OVA cells pretreated with statins (Fig. 2F and G) or Hmgcr siRNAs (Fig. 2H and I). GGPP supplement also reversed the membrane translocation of CRT or the secretion of HMGB1 by statins-treated tumor cells, whereas cholesterol supplement did not (Fig. 2J and K). Thus, we identified GGPP depletion as the specific metabolic intervention that mediates the ICD-inducing effect of MVA pathway inhibition.

Figure 2.

Geranylgeranyl pyrophosphate depletion mediates MVA pathway inhibition-induced tumor cell immunogenicity. A, Overview of the MVA metabolic pathway and the inhibitors used are shown. B and C, B16-OVA cells were treated with GGTI-298 (10 μmol/L), FTI-277 (20 μmol/L), or zaragozic acid A (5 μmol/L) for 24 hours, followed by coculture with BMDCs and OT-I for 24 hours. The production of IL2 (B) and IFNγ (C) was measured by ELISA. D and E,Ggps1 siRNA-treated B16-OVA cells were cocultured with BMDCs and OT-I for 24 hours. The production of IL2 and IFNγ was measured by ELISA. FI, Statins-treated (F and G) or Hmgcr siRNA-treated (H and I) B16-OVA cells were supplemented with GGPP (2 μmol/L) or cholesterol (10 μmol/L) for 24 hours, followed by coculture with BMDC and OT-I for 24 hours. The production of IL2 and IFNγ was measured by ELISA. J, The surface expression of CRT on B16-OVA cells treated with HMGCR inhibitors with supplement of GGPP or cholesterol was detected by FACS. K, MC38 (HMGB1-Gluc), and PDAC (HMGB1-Gluc) cells were treated with statins supplied with GGPP or cholesterol for 24 hours, and HMGB1-Gluc luciferase activity was measured. Data in BM are shown as mean ± SEM of three independent experiments. ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Dunnett posttest (BE), by one-way ANOVA with Turkey posttest (J), or by two-way ANOVA with Dunnett posttest (FI and K).

Figure 2.

Geranylgeranyl pyrophosphate depletion mediates MVA pathway inhibition-induced tumor cell immunogenicity. A, Overview of the MVA metabolic pathway and the inhibitors used are shown. B and C, B16-OVA cells were treated with GGTI-298 (10 μmol/L), FTI-277 (20 μmol/L), or zaragozic acid A (5 μmol/L) for 24 hours, followed by coculture with BMDCs and OT-I for 24 hours. The production of IL2 (B) and IFNγ (C) was measured by ELISA. D and E,Ggps1 siRNA-treated B16-OVA cells were cocultured with BMDCs and OT-I for 24 hours. The production of IL2 and IFNγ was measured by ELISA. FI, Statins-treated (F and G) or Hmgcr siRNA-treated (H and I) B16-OVA cells were supplemented with GGPP (2 μmol/L) or cholesterol (10 μmol/L) for 24 hours, followed by coculture with BMDC and OT-I for 24 hours. The production of IL2 and IFNγ was measured by ELISA. J, The surface expression of CRT on B16-OVA cells treated with HMGCR inhibitors with supplement of GGPP or cholesterol was detected by FACS. K, MC38 (HMGB1-Gluc), and PDAC (HMGB1-Gluc) cells were treated with statins supplied with GGPP or cholesterol for 24 hours, and HMGB1-Gluc luciferase activity was measured. Data in BM are shown as mean ± SEM of three independent experiments. ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Dunnett posttest (BE), by one-way ANOVA with Turkey posttest (J), or by two-way ANOVA with Dunnett posttest (FI and K).

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Rac1 inhibition in tumor cells activates antitumor immunity

The immunogenic effect of GGTI-298 on tumor cells indicated that global loss of protein geranylgeranylation is responsible for enhanced tumor immunogenicity. We next tried to pinpoint the downstream targets of GGTase that mediates the enhanced immunogenicity. First, we used siRNA to specifically knockdown GGTase I (Pggt1b) or GGTase II (Rabggtb), which are responsible for the modification of RAS and RHO, or RAB GTPase subfamily members (Supplementary Figs. S2E and S2F). Knockdown of GGTase II in tumor cells did not promote OT-I T-cell activation, nor CRT membrane translocation (Fig. 3A; Supplementary Fig. S2H). In contrast, specific knockdown of GGTase I in tumor cells promoted T-cell activation, reflected by increased IL2 and IFNγ production (Fig. 3A; Supplementary Fig. S2G). These results suggest that the GGTase I, but not GGTase II, plays a major role in MVA inhibition-enhanced immunogenicity. We next focused on downstream GTPases whose geranylgeranylation were mediated by GGTase I and designed a small siRNA library targeting individual small GTPase family genes, and confirmed the knockdown effect by qPCR (Supplementary Fig. S3A; Supplementary Table S1). After transfection by different siRNAs targeting individual genes for 48 hours, B16-OVA cells were then cocultured with BMDCs and OT-I T cells for 24 hours, and the levels of IL2 (Fig. 3B) and IFNγ (Supplementary Fig. S3B) production was measured as the readout for T-cell activation. Among the eight small GTPases, Rac1 knockdown in tumor cells markedly increased IL2 production by T cells, and fluvastatin treatment or siHmgcr could not further increase IL2 level (Fig. 3C; Supplementary Fig. S3C), suggesting that Rac1 depletion is largely responsible for MVA pathway inhibition-induced tumor immunogenicity. To confirm if the screening results were not limited to B16 cell line, we repeated the siRNA screening on MC38-OVA cells and measured cross presentation activity of DCs after MC38-OVA tumor cell priming. After transfection by different siRNAs targeting individual genes for 48 hours, MC38-OVA cells were then cocultured with BMDCs for 24 hours, and the surface level of MHCI/OVA peptide (H2Kb-SIINFEKL) complex on BMDCs was measured as the readout for antigen cross-presentation from tumor cells. Among the eight small GTPases, Rac1 knockdown in tumor cells markedly increased H2Kb-SIINFEKL level on BMDCs (Supplementary Fig. S3D), confirming that Rac1 knockdown also increased MC38 immunogenicity. Consistently, B16-OVA cells expressing shRNA targeting Rac1 showed upregulated surface expression of CRT, HMGB1 release and increased cell death (Supplementary Figs. S3E–S3I). Fluvastatin treatment on Rac1 knockdown cells could not further increase levels of IL2 and IFNγ from activated T cells (Supplementary Figs. S3J and S3K). To determine the in vivo effect of the tumor immunogenicity elicited by Rac1 knockdown, we treated B16-OVA cells expressing Rac1-specific or scramble shRNA (shRac1 or shScr) with cisplatin to make tumor cell vaccines, then injected the treated cells into the right flank of B6 mice, and rechallenged mice with live B16-OVA cells 7 days later. Thirty days after rechallenge, nearly 90% of mice immunized with shRac1 tumor cell vaccines remained tumor-free, whereas only 25% of the mice that vaccinated with shScr tumor cells were tumor-free (Fig. 3D). To further corroborate such finding, we inoculated shRac1- or shScr-expressing B16-OVA cells on the right dorsal flank of B6 mice while injecting live wild-type (WT) B16-OVA cells on the opposite dorsal flank at the same time. Consistent with lower in vitro cell survival (Supplementary Fig. S3L), Rac1 knockdown inhibited the in situ tumor growth from shRac1-expressing B16-OVA cells (Fig. 3E). Furthermore, it also slowed down the WT B16-OVA tumor growth on the opposite flank (Fig. 3F), which mimics the antitumor immunity-mediated abscopal effect of irradiation therapy. Indeed, CD8+ T cells are required for such abscopal antitumor efficacy of Rac1 knockdown, as pretreatment of mice with an anti-CD8 depletion antibody abolished Rac1 knockdown-induced both in situ and abscopal B16-OVA tumor growth inhibition (Fig. 3G and H). In contrast, shScr-expressing B16-OVA cells had no effect on either in situ or abscopal tumor growth (Fig. 3E and F). These results together pinpointed RAC1 as a key protein for maintaining tumor cell viability as well as low immunogenicity.

Figure 3.

Rac1 depletion in tumor cells activates antitumor immunity. A, B16-OVA cells were transfected with siRNA targeting different GGTases for 48 hours and then cocultured with BMDCs and OT-I for 24 hours. The production of IL2 was measured by ELISA. B, B16-OVA cells were transfected with siRNA targeting different GTPases for 48 hours and then cocultured with BMDCs and OT-I for 24 hours. The production of IL2 was measured by ELISA. C, B16-OVA cells were transfected with siRNA targeting different GTPases, followed by treatment with fluvastatin for another 16 hours, and then cocultured with BMDCs and OT-I for 24 hours. The production of IL2 was measured by ELISA. D, B16-OVA cells were pretreated with Rac1 knockdown plus cisplatin, freeze-thawed, or cisplatin only, followed by subcutaneous inoculation in B6 mice as tumor cell vaccines (n = 8 per group), and PBS group with no vaccine administered. After 7 days, mice were rechallenged with live WT B16-OVA cells. The diagram shows the percentage of tumor-free mice 30 days after rechallenge. E, Growth curve of in situ tumors from shRac1 B16-OVA cells or shScr B16-OVA cells inoculation on the left flank on B6 mice. F, Growth curve of abscopal tumors from untreated WT B16-OVA cells inoculation on the right flank of B6 mice in E. G and H, Mice were injected with CD8α depletion antibody or isotype antibody on day −1, 3, and 7 since B16-OVA tumor inoculation. Bilateral tumor volume is shown as mean ± SEM, n = 6 per group. Data in AC are shown as mean ± SEM of three independent experiments. **, P < 0.01; ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Dunnett posttest (A and B), by two-way ANOVA with Sidak posttest (C), or with Dunnett posttest (EH), or by log-rank (Mantel–Cox) test (D).

Figure 3.

Rac1 depletion in tumor cells activates antitumor immunity. A, B16-OVA cells were transfected with siRNA targeting different GGTases for 48 hours and then cocultured with BMDCs and OT-I for 24 hours. The production of IL2 was measured by ELISA. B, B16-OVA cells were transfected with siRNA targeting different GTPases for 48 hours and then cocultured with BMDCs and OT-I for 24 hours. The production of IL2 was measured by ELISA. C, B16-OVA cells were transfected with siRNA targeting different GTPases, followed by treatment with fluvastatin for another 16 hours, and then cocultured with BMDCs and OT-I for 24 hours. The production of IL2 was measured by ELISA. D, B16-OVA cells were pretreated with Rac1 knockdown plus cisplatin, freeze-thawed, or cisplatin only, followed by subcutaneous inoculation in B6 mice as tumor cell vaccines (n = 8 per group), and PBS group with no vaccine administered. After 7 days, mice were rechallenged with live WT B16-OVA cells. The diagram shows the percentage of tumor-free mice 30 days after rechallenge. E, Growth curve of in situ tumors from shRac1 B16-OVA cells or shScr B16-OVA cells inoculation on the left flank on B6 mice. F, Growth curve of abscopal tumors from untreated WT B16-OVA cells inoculation on the right flank of B6 mice in E. G and H, Mice were injected with CD8α depletion antibody or isotype antibody on day −1, 3, and 7 since B16-OVA tumor inoculation. Bilateral tumor volume is shown as mean ± SEM, n = 6 per group. Data in AC are shown as mean ± SEM of three independent experiments. **, P < 0.01; ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Dunnett posttest (A and B), by two-way ANOVA with Sidak posttest (C), or with Dunnett posttest (EH), or by log-rank (Mantel–Cox) test (D).

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Defective RAC1 geranylgeranylation is responsible for enhanced tumor immunogenicity induced by MVA pathway blockade

Previous reports showed that geranylgeranylation is required for membrane association of RAS and RHO family protein members (20, 21). Consistently, statins or GGTI treatment reduced RAC1 amount in membrane fraction whereas the supplement of GGPP rescue the statin-reduced membrane expression of RAC1 (Fig. 4A). Most small GTPases contain a carboxyl-terminal CAAX motif (C is cysteine, A is often an aliphatic amino acid, and X is any amino acid) where the cysteine residue is modified by geranylgeranylation (21, 22). To determine the role of RAC1geranylgeranylation in tumor cell immunogenicity, we re-introduced WT Rac1 or a geranylgeranylation-deficient Rac1 mutant (CAAX motif deleted, CAAX) in shRac1-B16-OVA cells (Fig. 4B and C). WT Rac1 expression rescued the cell growth to normal level, but Rac1-CAAX mutant re-introduction did not rescue the cell growth defect (Fig. 4D). In vitro T-cell co-culture experiment demonstrated that shRac1-B16-OVA cells expressing WT Rac1, but not CAAX mutant, reversed T-cell activation (Fig. 4E–H). Blockade of either protein geranylgeranylation by GGTI-298 (Fig. 4E and F), or MVA metabolic pathway by fluvastatin (Fig. 4G and H) on Rac1-CAAX-B16-OVA cells, could not further induce IL2 or IFNγ by T cells. Moreover, supplement of GGPP on Rac1-CAAX-B16-OVA cells could no longer lower the T-cell activation (Fig. 4G and H). In line with these in vitro findings, Rac1 knockdown significantly inhibited B16-OVA tumor growth in vivo, accompanied with increased tumor infiltration of IFNγ+CD8+ T cells. Re-expression of WT Rac1, but not CAAX mutant, reversed the tumor growth inhibition and T-cell infiltration (Fig. 4I–K). Interestingly, we also observed a similar trend of change in intratumor CD103+CD11c+ cell population (generally considered cDC1 subtype dendritic cells), indicating enhanced antigen presentation in B16-OVA tumors when Rac1 geranylgeranylation was blocked (Fig. 4L). Altogether, we identified that defective RAC1 geranylgeranylation played a major role in mediating MVA pathway inhibition-induced tumor immunogenicity.

Figure 4.

Defective RAC1 geranylgeranylation is responsible for MVA pathway blockade-induced tumor immunogenicity. A, Membrane and cytosolic RAC1 protein in B16-OVA cells after GGTI or statins with or without GGPP treatment. B, The schematic diagram illustrating the geranylgeranylation-defective Rac1 mutant with CAAX motif deletion. C, The re-expression of WT-Rac1 or CAAXRac1 in shRac1-B16-OVA cells detected by Western blot analysis. D, Cell survival detected by CCK-8 assay of shRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1.E and F, shRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 were treated with GGTI, followed by coculture with BMDCs and OT-I for 24 hours. The production of IL2 (E) and IFNγ (F) was measured by ELISA. G and H, The production of IL2 (G) and IFNγ (H) by OT-I was measured as in E and F, except tumor cells were pretreated with fluvastatin. I and J, Tumor growth curve (I) and tumor weight (J) of tumors formed on B6 mice inoculated with B16-OVA cells of different Rac1 status. K and L, The infiltration level of IFNγ+ CD8+ T cells (K) or CD103+ CD11c+ cells (L) in tumors of J. Tumors were harvested on day 14. Tumor volume is shown as mean ± SEM; n = 4 for shScr+ev and shRac1+WT groups; n = 5 for shRac1+ev and shRac1+CAAX groups. Data in DH are shown as mean ± SEM of three independent experiments. Data in K and L are shown as mean ± SEM of three mice per group. *, P < 0.05, ***, P < 0.001, n.s., nonsignificant, P > 0.05 by two-way ANOVA with Dunnett posttest (D and I), with Sidak posttest (E and F), or with Turkey posttest (G and H), by one-way ANOVA with Dunnett posttest (JL).

Figure 4.

Defective RAC1 geranylgeranylation is responsible for MVA pathway blockade-induced tumor immunogenicity. A, Membrane and cytosolic RAC1 protein in B16-OVA cells after GGTI or statins with or without GGPP treatment. B, The schematic diagram illustrating the geranylgeranylation-defective Rac1 mutant with CAAX motif deletion. C, The re-expression of WT-Rac1 or CAAXRac1 in shRac1-B16-OVA cells detected by Western blot analysis. D, Cell survival detected by CCK-8 assay of shRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1.E and F, shRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 were treated with GGTI, followed by coculture with BMDCs and OT-I for 24 hours. The production of IL2 (E) and IFNγ (F) was measured by ELISA. G and H, The production of IL2 (G) and IFNγ (H) by OT-I was measured as in E and F, except tumor cells were pretreated with fluvastatin. I and J, Tumor growth curve (I) and tumor weight (J) of tumors formed on B6 mice inoculated with B16-OVA cells of different Rac1 status. K and L, The infiltration level of IFNγ+ CD8+ T cells (K) or CD103+ CD11c+ cells (L) in tumors of J. Tumors were harvested on day 14. Tumor volume is shown as mean ± SEM; n = 4 for shScr+ev and shRac1+WT groups; n = 5 for shRac1+ev and shRac1+CAAX groups. Data in DH are shown as mean ± SEM of three independent experiments. Data in K and L are shown as mean ± SEM of three mice per group. *, P < 0.05, ***, P < 0.001, n.s., nonsignificant, P > 0.05 by two-way ANOVA with Dunnett posttest (D and I), with Sidak posttest (E and F), or with Turkey posttest (G and H), by one-way ANOVA with Dunnett posttest (JL).

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CLEC9A on conventional DCs recognize tumor cells with MVA pathway inhibition

Early studies showed that statins could increase tumor immunogenicity by upregulating MHC-I and CD80/CD86 expression on melanoma cells (6). However, tumor cells could not directly stimulate T cells in our coculture system, and dendritic cells were required for processing and presenting OVA antigen from B16-OVA cells to activate T cells. Therefore, we focused on dendritic cells for the molecular features related to their cross-presentation capacity. As expected, the surface expression of MHC class I-bound SIINFEKL (OVA epitope peptide) complex (Supplementary Figs. S4A–S4E) and MHC II on BMDCs both increased (Supplementary Figs. S4F–S4J) after cocultured with MVA pathway-inhibited B16-OVA cells, suggesting the enhanced antigen presenting function of BMDCs. In line with the in vitro findings, intratumor levels of cDC1 population also significantly increased when Rac1 geranylgeranylation was blocked in B16-OVA tumor cells (Fig. 4L). The cDC1s are often considered the most powerful antigen presenting cell populations in vivo, partly due to the specific expression of a pattern recognition receptor called CLEC9A (also known as DNGR-1), which is able to promote antigen cross presentation via recognizing F-actin from necrotic cells with damaged cytoskeleton (13, 14, 23). As membrane-associated RAC1 is known to maintain cytoskeleton homeostasis (24, 25), Rac1 knockdown markedly disrupted tumor cell cytoskeleton reflected by F-actin reduction (Fig. 5A), which was also observed on statin- or GGTI-treated cells (Supplementary Fig. S5A). We next reasoned whether CLEC9A on cDC1 would recognize exposed cytoskeleton from Rac1-blocked tumor cells and promote antigen presentation. As GMCSF cultured bone marrow cells are mainly myeloid DCs with low percentage of CLEC9A+ population, we then tested FLT3L-induced BMDCs (for cDC1 enrichment) for the coculture experiment, and such DCs also induced T-cell activation when cocultured with tumor cells deficient in WT Rac1 expression (Fig. 5C and D). Strikingly, knockdown of Clec9a on FLT3L-induced DCs (Fig. 5B), or on GM-CSF-induced DCs, abrogated the activation of OT-I T cells by shRac1-B16-OVA tumor cells with or without CAAX mutant expression (Fig. 5C and D; Supplementary Fig. S5G), or B16-OVA cells pretreated with statins or GGTI (Supplementary Figs. S5B, S5C, and S5F). Consistent with these data, surface expression of MHC class I-bound SIINFEKL epitope complex on DCs, another marker of OVA antigen presentation by DCs, was suppressed by Clec9a knockdown when cocultured with tumor cells with Rac1 knockdown, CAAX mutant expression (Fig. 5E and F), or statins or GGTI pretreatments (Supplementary Figs. S5D and S5E). Recognition of F-actin from necrotic cells by CLEC9A leads to SYK phosphorylation and subsequent routing of cross-presentation pathway in dendritic cells (23, 26). Consistently, the level of SYK phosphorylation markedly increased in BMDCs after coculture with Rac1 knockdown or CAAX mutant expressing B16-OVA cells (Fig. 5G), or B16-OVA cells pretreated with statins or GGTI (Fig. 5H). But such phosphorylation was inhibited by Clec9a knockdown in DCs (Fig. 5H). These results illustrated that CLEC9A/SYK signaling in dendritic cells mediated the recognition of MVA pathway-blocked tumor cells and subsequent antigen cross-presentation for CD8+ T-cell activation.

Figure 5.

CLEC9A on cDCs mediates the immune recognition of MVA pathway-inhibited tumor cells. A, Fluorescent staining and quantification of cytoskeleton by rhodamine-phallodin on ShRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1. B, Knockdown of Clec9a on BMDCs by RNAi and CLEC9A expression on Batf3−/− BMDCs was validated by Western blot analysis. C and D, OT-I activation by ShRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 detected by the secretion of IL2 (C) and IFNγ (D) after coculturing with BMDCs pretreated with siScr or siClec9a siRNAs. E and F, ShRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 were cocultured with BMDCs pretreated with siScr or siClec9a, then the surface expression of H-2Kb-SIINFEKL was determined by FACS. G and H, Phosphorylation levels of SYK in DCs after coculture with B16-OVA cells were determined by Western blot analysis. Data in A are shown as mean ± SEM of phalloidin mean fluorescence intensity (MFI) from six random 1,000× high power field. Data in C, D, and F are shown as mean ± SEM of three independent experiments. ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Turkey posttest (A), by two-way ANOVA with Dunnett posttest (C, D, and F).

Figure 5.

CLEC9A on cDCs mediates the immune recognition of MVA pathway-inhibited tumor cells. A, Fluorescent staining and quantification of cytoskeleton by rhodamine-phallodin on ShRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1. B, Knockdown of Clec9a on BMDCs by RNAi and CLEC9A expression on Batf3−/− BMDCs was validated by Western blot analysis. C and D, OT-I activation by ShRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 detected by the secretion of IL2 (C) and IFNγ (D) after coculturing with BMDCs pretreated with siScr or siClec9a siRNAs. E and F, ShRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 were cocultured with BMDCs pretreated with siScr or siClec9a, then the surface expression of H-2Kb-SIINFEKL was determined by FACS. G and H, Phosphorylation levels of SYK in DCs after coculture with B16-OVA cells were determined by Western blot analysis. Data in A are shown as mean ± SEM of phalloidin mean fluorescence intensity (MFI) from six random 1,000× high power field. Data in C, D, and F are shown as mean ± SEM of three independent experiments. ***, P < 0.001; n.s., nonsignificant, P > 0.05 by one-way ANOVA with Turkey posttest (A), by two-way ANOVA with Dunnett posttest (C, D, and F).

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CLEC9A+ DCs are required for the in vivo tumor immunogenicity induced by MVA pathway inhibition

To further confirm whether cross-presentation was involved in MVA pathway inhibition-induced immune activation, we cultured FLT3L-induced BMDCs from WT and Basic Leucine Zipper ATF-Like Transcription Factor 3 knockout (Batf3−/−) mice, which lack of CLEC9A+ DCs (27, 28), and used them as antigen presenting cells for OT-I T cell activation. Batf3 deficiency in FLT3L-induced DCs significantly impaired T-cell activation by tumor cells pretreated with statins, Hmgcr knockdown or protein geranylgeranylation inhibition by GGTI (Fig. 6A; Supplementary Figs. S6A and S6B). Similarly, Rac1 knockdown or CAAX mutant expression in B16-OVA cells induced lower levels of T-cell activation when cocultured with Batf3−/− DCs comparing with that with WT DCs (Fig. 6B; Supplementary Fig. S6C). In vivo, we performed bilateral tumor inoculation experiments on Batf3−/− mice as previously performed on WT mice in Fig. 3 (left flank with shRac1-B16-OVA cells, and right flank with WT B16-OVA cells). Rac1 knockdown inhibited in situ tumor growth on Batf3−/− mice as on WT mice (Fig. 6C; Supplementary Fig. S6D). However, the abscopal tumor inhibition effect observed on WT mice was almost completely abolished on Batf3−/− mice (Fig. 6D; Supplementary Fig. S6E). We also generated Rac1-knockdown MC38 cells and performed similar experiment and observed similar effect for in situ and abscopal MC38 tumor growth on WT mice. Differ from B16-OVA tumor, both in situ and abscopal MC38 tumor growth was accelerated on Batf3−/− mice, which was likely due to different tumor microenvironment and sensitivity to residual cDC1 activity in Batf3−/− mice of MC38 tumor model (Supplementary Figs. S6F–S6I). To directly examine the role of CLEC9A+ DCs in tumor growth control, we pretreated mice with a CLEC9A blocking antibody to block CLEC9A+ DC function, and then inoculated different tumor cells on both flanks. In line with the tumor growth results on Batf3−/− mice, antibody blocking of CLEC9A did not affect in situ tumor growth inhibition by RAC1 knockdown (Fig. 6E) but abrogated the abscopal WT tumor growth inhibition by in situ shRac1-expressing tumor cell inoculation (Fig. 6F). Consistent with the defective SYK signaling in Clec9a knockdown DCs, SYK phopsphorylation induced by tumor cells pretreated with statins, GGTI, or Rac1 CAAX mutant-expressing tumor cells were also abrogated on Batf3−/− BMDCs, on which CLEC9A expression was largely absent (Fig. 6G and H). Overall, the in vitro and in vivo evidence illustrated that MVA metabolism blockade in tumor cells promote CLEC9A+ DCs-mediated tumor recognition and antigen cross-presentation to enhance antitumor immunity (Fig. 6I).

Figure 6.

CLEC9A+ DCs mediate the in vivo tumor immunogenicity induced by MVA pathway inhibition. A and B,In vitro OT-I activation experiments detecting the secretion of IL2 after coculture with HMGCR inhibitors treated (A), shRac1 or CAAXRac1 expressing B16-OVA cells (B) together with DCs from WT or Batf3−/− mice. C, Tumor growth curve of shRac1 B16-OVA cells or shScr B16-OVA cells inoculated in situ on Batf3−/−mice (n = 6 for each group). D, Tumor growth curve of live, untreated B16-OVA cells inoculated on the opposite site of Batf3−/−mice in C. E, Mice were injected with an anti-CLEC9A blocking antibody (400 μg/mouse) or isotype control antibody on days 0, 3, and 7 since B16-OVA tumor inoculation (arrows), and growth curves of in situ tumors from shRac1-expressing or shScr-expressing B16-OVA cells inoculation on the left flank on B6 mice were recorded. F, Growth curves of abscopal tumors from untreated WT B16-OVA cells inoculation on the right flank of B6 mice are shown in E. G and H, Phosphorylation levels of SYK in DCs after coculture with B16-OVA cells pretreated with statins or GGTI-298 treated (G), or with shRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 (H). I, Schematic illustration of the molecular mechanism mediating MVA pathway blockade-induced antitumor immunity. Bilateral tumor volume is shown as mean ± SEM; n = 6 per group in C and D; n = 5 per group in E and F. Data in A and B are shown as mean ± SEM of three independent experiments. **, P < 0.01; ***, P < 0.001; n.s., nonsignificant, P > 0.05 by two-way ANOVA with Sidak posttest (AF).

Figure 6.

CLEC9A+ DCs mediate the in vivo tumor immunogenicity induced by MVA pathway inhibition. A and B,In vitro OT-I activation experiments detecting the secretion of IL2 after coculture with HMGCR inhibitors treated (A), shRac1 or CAAXRac1 expressing B16-OVA cells (B) together with DCs from WT or Batf3−/− mice. C, Tumor growth curve of shRac1 B16-OVA cells or shScr B16-OVA cells inoculated in situ on Batf3−/−mice (n = 6 for each group). D, Tumor growth curve of live, untreated B16-OVA cells inoculated on the opposite site of Batf3−/−mice in C. E, Mice were injected with an anti-CLEC9A blocking antibody (400 μg/mouse) or isotype control antibody on days 0, 3, and 7 since B16-OVA tumor inoculation (arrows), and growth curves of in situ tumors from shRac1-expressing or shScr-expressing B16-OVA cells inoculation on the left flank on B6 mice were recorded. F, Growth curves of abscopal tumors from untreated WT B16-OVA cells inoculation on the right flank of B6 mice are shown in E. G and H, Phosphorylation levels of SYK in DCs after coculture with B16-OVA cells pretreated with statins or GGTI-298 treated (G), or with shRac1-B16-OVA cells with re-expression of WT-Rac1 or CAAXRac1 (H). I, Schematic illustration of the molecular mechanism mediating MVA pathway blockade-induced antitumor immunity. Bilateral tumor volume is shown as mean ± SEM; n = 6 per group in C and D; n = 5 per group in E and F. Data in A and B are shown as mean ± SEM of three independent experiments. **, P < 0.01; ***, P < 0.001; n.s., nonsignificant, P > 0.05 by two-way ANOVA with Sidak posttest (AF).

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MVAGGPPpathway–RAC1–CLEC9A axis is associated with antitumor immune signature and OS of patients with cancer

The in vitro and in vivo mouse studies demonstrated that inhibition of GGPP synthesis by MVA pathway blockade could interfere with RAC1 geranylgeranylation, thereby activated CLEC9A+ dendritic cells to activate CD8+ T cells-mediated antitumor immunity. To explore the biological significance of our work on patients with cancer, we explored the relationship between GGPP synthesis or RAC1 expression and immune microenvironment on TCGA cancer patient samples by TIMER 2.0 (http://timer.cistrome.org; ref. 18). We transformed the expression of MVA pathway genes responsible for GGPP synthesis as a signature shown as MVAGGPP score. We found that patients with skin cutaneous melanoma (SKCM) with low MVAGGPP score or low RAC1 level showed higher infiltration level of CD8+ T cells and higher cytotoxicity score (Fig. 7A, B, F, and G), higher infiltration levels of dendritic cells and activated dendritic cells (Fig. 7C, D, H, and I), and higher immune score (Fig. 7E and J), indicating that inhibition of tumor GGPP synthesis or low RAC1 expression could remodel tumor immune microenvironment towards an immune-stimulating direction. On the other hand, our preclinical work demonstrated the role of CLEC9A+ DC on sensing MVA pathway or RAC1 inhibition in tumor cells and promoting antitumor immunity. Correspondingly, we examined the effect of GGPP synthesis, RAC1 expression and CLEC9A expression on prognosis of patients with cancer. We classified the patients into four groups based on GGPP score (or Rac1 expression level) and the CLEC9A expression level. OS was significantly better in the patients with low MVAGGPP score (or low RAC1 expression) and high CLEC9a expression compared with those with high MVAGGPP (or high Rac1 expression) and low CLEC9A expression (P < 0.001, Fig. 7K and L). Similar trends were observed in patients with pancreatic adenocarcinoma (PAAD; Supplementary Figs. S7A–S7L). Together these data are in line with the preclinical findings, that the MVAGGPP–RAC1–CLEC9A axis regulates tumor immune microenvironment and promotes antitumor immunity.

Figure 7.

MVAGGPP pathway-RAC1-CLEC9A axis in tumors is associated with antitumor immune markers and OS of patients with cancer. AE and FJ, Infiltration levels of CD8+ T cells, dendritic cells, and activated dendritic cells, and cytotoxicity score or immune score of patients with SKCM from TCGA database were compared between two groups with high or low MVAGGPP score (AE) or RAC1 expression (FG). K and L, OS of patients with SKCM from TCGA database was compared between groups with different level of CLEC9A and MVAGGPP score (K) or RAC1 expression (L). Data of gene expression and OS in AL were from patients with SKCM of TCGA datasets. Immune estimation of CD8+ T cells, dendritic cells, and cytotoxicity score were calculated by MCPCOUNTER algorithm. Level of activated dendritic cells and immune score were calculated by XCELL algorithm. The MVAGGPP score was calculated by GSVA. P values were calculated by unpaired one-tailed Student t test (AJ), or by log-rank test (KL).

Figure 7.

MVAGGPP pathway-RAC1-CLEC9A axis in tumors is associated with antitumor immune markers and OS of patients with cancer. AE and FJ, Infiltration levels of CD8+ T cells, dendritic cells, and activated dendritic cells, and cytotoxicity score or immune score of patients with SKCM from TCGA database were compared between two groups with high or low MVAGGPP score (AE) or RAC1 expression (FG). K and L, OS of patients with SKCM from TCGA database was compared between groups with different level of CLEC9A and MVAGGPP score (K) or RAC1 expression (L). Data of gene expression and OS in AL were from patients with SKCM of TCGA datasets. Immune estimation of CD8+ T cells, dendritic cells, and cytotoxicity score were calculated by MCPCOUNTER algorithm. Level of activated dendritic cells and immune score were calculated by XCELL algorithm. The MVAGGPP score was calculated by GSVA. P values were calculated by unpaired one-tailed Student t test (AJ), or by log-rank test (KL).

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It is well accepted that reprogrammed metabolism plays essential role on tumor immune microenvironment remodeling (29, 30). Immune cells may in turn monitor abnormal metabolic activities in premalignant or malignant cells as well. How adaptive immunity may sense the blockade of tumor MVA metabolism and promote antitumor immunity has not been well understood. Our work demonstrates that cDC1s may sense tumor MVA metabolic blockade through CLEC9A-mediated immune recognition of tumor cell cytoskeleton and activate tumor-specific T-cell response. Thus, our work illustrates a new mechanism by which immune cells monitor tumor metabolic dysfunction, and how MVA pathway intervention may potentiate anticancer immunity through disrupting Rac1-regulated cytoskeleton.

The dependence of MVA pathway in cancer cells establishes a tumor vulnerability that can be therapeutically targeted to improve outcomes for cancer patients. Interestingly, several studies revealed that deregulation of the downstream protein prenylation, rather than cholesterol synthesis, is responsible for MVA pathway inhibition-induced antitumor effect (31–33). Small GTPases including Ras, Rho, and Rab family proteins require prenylation for membrane association and transducing downstream signals for cancer cell proliferation, migration, and resistance to apoptosis (20). The GTPase undergoing geranylgeranylation responsible for tumor immunogenicity we identified is RAC1, which is known for regulating cytoskeletal organization together with RHOA and CDC42. We did not include RAS family proteins in our screening because they mainly undergo farnesylation instead of geranylgeranylation (20), and the inhibition of farnesylation did not improve tumor immunogenicity in our study. Interestingly, small GTPases protein geranylgeranylation is also critical for adipocyte browning, and ablation of GGTase I leads to reduced F-actin and YAP/TAZ-mediated thermogenic function in adipocytes, highlighting the importance of protein prenylation in modulating systemic metabolism through regulating cytoskeleton (34). In another study, myeloid-specific GGTase I deficiency in mice caused inflammation and arthritis, and such phenotype was alleviated by heterozygous Rac1 deletion, but not by Rhoa or Cdc42 deletion (35). Thus, RAC1 may have unique effects involved in cytoskeleton regulation and immune regulation. Our study not only confirmed the critical role of RAC1 in cancer cell survival, but also put forward the potential role of RAC1 inhibition in antitumor immune activation. The RAC1 inhibitors ZIN69391 and EHop-016 reduced RAC1 activation levels, and inhibition of RAC1 effector impaired cytoskeleton reorganization through blocking p21-activated kinase (PAK) activation (36, 37). Interestingly, PAK4 inhibition is reported to improve PD-1 blockade immunotherapy by increasing intratumor immune cell infiltration (38). These results suggest a great potential for RAC1 selective inhibitors for cancer treatment in combination with immunotherapy, and the specific combination strategy merits further study.

Antitumor immunity requires “antigenicity” to provide the first signal and guarantees the specificity of immune reactions and “adjuvanticity” to determine the characteristics and magnitude of disturbance in immune homeostasis triggered by innate signaling, accompanied by various forms of inflammation (10, 39, 40). We propose that on one hand, cellular demise induced by MVA metabolic blockade foster the “adjuvanticity” of cancer cells by eliciting secretion or exposure of certain DAMPs, which can be detected by innate immune receptors on immune cells and orchestrate antitumor immune reactions in the tumor microenvironment. On the other hand, the blockade of MVA metabolic pathway depletes intracellular GGPP that is required for RAC1 geranylgeranylation. It is the defective RAC1 geranylgeranylation that induce the exposure of tumor F-actin, which was detected by CLEC9A receptor on cDC1 cells. The subsequent cross-presentation of tumor antigen by DCs contributes to the improvement of “antigenicity” required for antitumor immunity. Thus, targeting MVA pathway may boost both “adjuvanticity” and “antigenicity” of tumor cells to enhance tumor immunogenicity. A recent report showed that MVA pathway inhibitors may have strong adjuvant effect for cancer vaccine by decreasing the prenylation of Rab5 on DCs, thereby resulting in enhanced antigen presentation and T-cell activation (41). As Rab5 prenylation is mediated by GGTase II, and GGTase II knockdown on B16-OVA cells did not enhance immunogenicity, we did not include Rab5 in our siRNA screening. Thus, prenylation blockade on different cell types may have various effects. As tumor microenvironment is a mixture of multiple types of cells including cancer cells and immune cells, our study suggested that clinical benefit of statins administration on cancer patients may be a combined result from enhanced tumor cell immunogenicity and elevated antigen presenting function of dendritic cells by MVA pathway inhibition. It is worth noting that BATF3 deficiency in host mice was able to accelerate the in situ tumor growth of Rac1-knockdown MC38 tumor but not that of Rac1-knockdown B16-OVA tumor. This discrepancy likely reflects the intrinsic differences in tumor sensitivity to the residual cDC1 cells or dynamic immune microenvironment changes between B16-OVA and MC38 tumor models, which was also observed in a recent study (42).

In DCs, CLEC9A diverts cell cargo into a recycling endosome compartment that facilitates cross-presentation, but not DC activation (43). Interestingly, upon sensing F-actin, CLEC9A restricts innate inflammation tissue injury to limit excessive immunopathology because of its restricted expression to one DC subset-cDC1s, and its ability to restrict infiltration of neutrophils, another innate immune cell subset that are often considered tumor-promoting (44). Thereby, treatment based on CLEC9A can circumvent excessive tissue damage by avoiding nonspecific inflammation. Interestingly, several studies have exploited targeting CLEC9A for efficient antigen presentation for tumor vaccine enhancement (43, 45–47). Delivery of antigen to DCs via CLEC9A in vivo leads to a cytotoxic T lymphocyte response that actively suppresses tumor lung metastases in a B16 mouse melanoma model (48). Of note, CLEC9A routing did not activate dendritic cells, and adjuvant was still required for efficacious tumor inhibition by the CLEC9A-targeting vaccine. MVA pathway blockade in tumor cells, on one side promote the release of prototype DAMPs such as CRT and HMGB1, and on another side elicit cytoskeleton exposure, which promote CLEC9A-mediated immune recognition and antigen cross presentation. Thus, targeting tumor MVA pathway-regulated protein prenylation may provide an ideal approach to boost in situ antitumor immunity in a therapeutic setting via serving as both CLEC9A-targeting and immune adjuvant purpose. Future studies are warranted to test the in vivo efficacy of such combination therapy.

X. Xia reports grants from National Key R&D Program of China, The National Natural Science Foundation of China, The Guangdong Innovative and Entrepreneurial Research Team Program, and Fundamental Research Funds for the Central Universities during the conduct of the study. No disclosures were reported by the other authors.

F. Xu: Conceptualization, data curation, investigation, methodology, writing–original draft. Z. Wang: Conceptualization, investigation, methodology. H. Zhang: Investigation. J. Chen: Methodology. X. Wang: Investigation, methodology. L. Cui: Investigation, methodology. C. Xie: Investigation, methodology. M. Li: Investigation, methodology. F. Wang: Data curation, formal analysis. P. Zhou: Resources. J. Liu: Resources. P. Huang: Resources. X. Xia: Conceptualization, resources, formal analysis, supervision, writing–review and editing. X. Xia: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, project administration, writing–review and editing.

The results shown here are in part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga. This work was supported by the grants from National Key R&D Program of China (2018YFC1313300/2018YFC1313304), the National Natural Science Foundation of China (grants 82073140, 81773051, 81803005, 81972692), the Guangdong Innovative and Entrepreneurial Research Team Program (2016ZT06S638), and Fundamental Research Funds for the Central Universities (20ykzd22, 19ykpy191). The datasets generated and/or analyzed during the current study are available at Research Data Deposit public platform (www.researchdata.org.cn), with the approval number of RDDB2021001634.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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Supplementary data