Dihydroartemisinin increased the abundance of Akkermansia muciniphila by YAP1 depression that sensitizes hepatocellular carcinoma to anti-PD-1 immunotherapy

Abstract

The effect of anti-programmed cell death 1 (anti-PD-1) immunotherapy is limited in patients with hepatocellular carcinoma (HCC). Yes-associated protein 1 (YAP1) expression increased in liver tumor cells in early HCC, and Akkermansia muciniphila abundance decreased in the colon. The response to anti-PD-1 treatment is associated with A. muciniphila abundance in many tumors. However, the interaction between A. muciniphila abundance and YAP1 expression remains unclear in HCC. Here, anti-PD-1 treatment decreased A. muciniphila abundance in the colon, but increased YAP1 expression in the tumor cells by mice with liver tumors in situ. Mechanistically, hepatocyte-specific Yap1 knockout (Yap1^LKO) maintained bile acid homeostasis in the liver, resulting in an increased abundance of A. muciniphila in the colon. Yap1 knockout enhanced anti-PD-1 efficacy. Therefore, YAP1 inhibition is a potential target for increasing A. muciniphila abundance to promote anti-PD-1 efficacy in liver tumors. Dihydroartemisinin (DHA), acting as YAP1 inhibitor, increased A. muciniphila abundance to sensitize anti-PD-1 therapy. A. muciniphila by gavage increased the number and activation of CD8⁺ T cells in liver tumor niches during DHA treatment or combination with anti-PD-1. Our findings suggested that the combination anti-PD-1 with DHA is an effective strategy for liver tumor treatment.

Keywords

hepatocellular carcinoma / YAP1 / Akkermansia muciniphila / anti-PD-1 / dihydroartemisinin / bile acid

1 Introduction

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death and the sixth most frequently diagnosed cancer worldwide [1]. Programmed cell death protein-1 (PD-1)-targeted immunotherapy has shown promising results in many tumors. However, the response rate is only 15%–20% during anti-PD-1 therapy in patients with HCC [2–4].

Akkermansia muciniphila is a gram-negative, anaerobic bacterium that has probiotic properties. The abundance of A. muciniphila is considerably lower in patients with early HCC [5]. Increased abundance of A. muciniphila sensitized anti-PD-1 therapy in patients with tumors (including HCC) [6–9]. A. muciniphila treatment turned poor responders to anti-PD-1 therapy into responders [7].

Yes-associated protein 1 (YAP1), a key effector molecule of the Hippo pathway, promoted tumor development [10]. The activation and overexpression of YAP1 were the early events in HCC [11,12]. Disruption of YAP reduced tumor growth, enhanced the immune response, and sensitized tumor cells to anti-PD-1 therapy [13]. However, the relationship between A. muciniphila and YAP1 during anti-PD-1 therapy is unclear.

Bile acids are the final products of cholesterol metabolism and link the intestine and the liver through the enterohepatic circulation. Studies have shown that bile acids affect A. muciniphila [14–16], participate in the regulation of gut microbiota, and activate YAP1 to promote the occurrence of HCC [17].

Dihydroartemisinin (DHA), an Artemisia annua derivative, is an antimalarial drug approved by the U.S. Food and Drug Administration (FDA). Increasing pieces of evidence have shown that DHA exerts antitumor effect [18,19], which may be related to its modulation of immune cell infiltration and chemokine secretion.

In this study, we found that anti-PD-1 treatment increased YAP1 expression in the liver tumor cells and decreased the abundance of A. muciniphila in the colon of mice with liver tumors. Mechanistically, the inhibition of A. muciniphila abundance by YAP1 was associated with bile acid homeostasis in the liver. DHA reduced the YAP1 expression and increased A. muciniphila abundance to sensitize animals to anti-PD-1 therapy in mice with liver tumors. A. muciniphila increased the number and activation of CD8⁺ T cells in liver tumor niches during the combination of DHA and anti-PD-1 or DHA treatment alone.

2 Materials and methods

2.1 Animal experiment

The protocol was approved by the Ethics Committee for Animal Experiment of Hebei University of Chinese Medicine (Shijiazhuang, China) with permit numbers DWLL2018051 and DWLL202203064. Male mice (Vital River Laboratory Animal Technology Co. Ltd., Beijing) were housed in a specific pathogen-free facility at a temperature of 22 °C–24 °C and had a 12 h light-dark cycle with free access to water and food. Genetically engineered albumin-cre mice were purchased from Guangzhou Cyagen Biosciences (Guangzhou, China). Yap1^flox/flox (Yap1^Flox) mice with a loxP-flanked Yap1 allele on a C57BL/6 background were generated. Albumin-cre mice were crossed with Yap1^flox/flox mice to produce Yap1 ^LKO mice.

2.2 DEN/TCPOBOP-induced HCC model in mice

The HCC model was established as previously described [20]. Three-week-old male mice were injected intraperitoneally with 25 mg/kg bodyweight N-nitrosodiethylamine (DEN). Starting at 5 weeks of age, the mice received 10 consecutive biweekly injections with a dose of 3 mg/kg bodyweight TCPOBOP. The mice in the anti-PD-1 (BioXcell, USA) group were injected intraperitoneally with anti-PD-1 (10 mg/kg, dissolved in saline) once every 3 days for 2–3 weeks [21,22]. The mice in the DHA (Tci, Tokyo, Japan) group were injected intraperitoneally with DHA (25 mg/kg, dissolved in DMSO) once daily for five consecutive days per week for 2–3 weeks [23,24]. The mice in the DHA combined with anti-PD-1 (DHA + anti-PD-1) group were intraperitoneally injected with anti-PD-1 (10 mg/kg, dissolved in saline) and DHA (25 mg/kg, dissolved in DMSO) for 2–3 weeks. The mice in the control group were intraperitoneally injected with DMSO (0.1%, dissolved in saline).

2.3 Antibiotic solution induced the reduction of A. muciniphila in the colon in mice

The mice were given an antibiotic solution (ATB, streptomycin (5 mg/mL), ampicillin (1 mg/mL), and vancomycin (0.25 mg/mL) added to sterile drinking water) for two weeks [6]. The solution and bottles were changed three times and once per week, respectively.

2.4 Hepa1-6 cells induced the heterotopic tumor model in C57BL/6 mice

The model with reduced A. muciniphila was established in accordance with method 3 in four-week-old C57BL/6 mice. Hepa1-6 cells (PWE-MU008, Suzhou Meilun Biotechnology) were injected subcutaneously in mice. Tumours were palpable (7 days’ post injection), and DHA or anti-PD-1 + DHA were injected for two weeks [22,23]. The mice stopped drinking the antibiotic solution and were gavaged with 100 µL of suspension containing 1 × 10⁸ A. muciniphila or normal saline for two weeks [6]. The length and width of the tumors were measured every 72 h by using a digital caliper. Tumor volume was calculated as V (mm³) = width² (mm²) × length (mm) × 0.5. Tumors were weighed on a fine scale (FA224, Sunny Hengping Instrument, China).

2.5 Western blot

Proteins were extracted from tissue by using a columnar protein extraction kit (Yamei Biotechnology, Shanghai, China). The extracted proteins were transferred to polyvinylidene difluoride membranes and blocked with 5% milk to prevent nonspecific binding. The membranes were then incubated overnight at 4 °C with primary antibodies (rabbit anti-YAP1 monoclonal antibody (14074, CST, 1: 1000) and rabbit anti-GAPDH polyclonal antibody (ab0037, Abways, 1:5000) and secondary antibody (goat anti-rabbit IgG-HRP (ZB-2301, ZSGB-BIO, 1:5000)) for 2 h at room temperature. The bands were detected by using an ECL detection system (Vilber, Fusion FX5 Spectra, France). The band intensity was measured by using Image-Pro Plus v6.0 software (Media Cybernetics, USA).

2.6 Haematoxylin and eosin (H&E) staining and immunohistochemistry

Mouse liver tissue was fixed in 4% paraformaldehyde and paraffin embedded, cut into 5 µm sections, and stained with H&E. The pathological images were obtained by using a microscope (Leica DM2500, Germany). For immunostaining, the sections were repaired using high-pressure heating and incubated overnight at 4 °C with primary antibodies (rabbit anti-YAP1 monoclonal antibody (14074, CST, 1:200), Ki-67 (12202S, CST, 1: 300) or CD8α (#98941, CST, 1:300)) and secondary antibody (goat anti-rabbit IgG) for 20 min at room temperature. DAB chromogenic solution was used for 3 min (ZLI-9017, ZSGB-BIO, Beijing, China) to visualize the cells, and cells stained tan were considered positive.

2.7 Bacterial strain

The strain of A. muciniphila (ATCC^®BAA-835™, 70012048) was obtained from the American Type Culture Collection (ATCC) and grown in an anaerobic jar at 37 °C. A. muciniphila was cultured in brain heart infusion broth (BHI, Land Bridge Technology, 190701, Beijing, China) supplemented with 0.5% (w/v) hog gastric mucin (Type III, Sigma, SLCCC7713) and 0.05% (w/v) cysteine (Tianjin, China) [25].

2.8 Faecal 16S rRNA sequencing

The genomic DNA of samples was extracted by using the CTAB or SDS method. The DNA of the samples was diluted to 1 ng/μL with sterile water. Purified DNA from different samples was used as a template to amplify the V3–4 region of 16S rRNA with specific primers. Polymerase chain reactions (PCRs) were performed with Phusion® High-Fidelity PCR Master Mix with GC Buffer (New England Biolabs). PCR products were detected by electrophoresis on a 2% agarose gel. The samples were mixed in equal amounts in accordance with the concentration of PCR products. PCR products were detected by 2% agarose gel electrophoresis, and the target bands were recovered after full mixing. A TruSeq DNA PCR-free Sample Preparation Kit was used for library construction. The constructed library was quantified by Qubit and Q-PCR. A HiSeq2500 PE250 was used for machine sequencing after the library was qualified. Sequencing was completed by Suzhou Smartnuclide. Co. Ltd.

2.9 Quantitative PCR

Faecal DNA was extracted by using a Stool Genomic DNA Extraction Kit (Solarbio). The specific primers AM1 (5′-CAGCACGTGAAGGTGGGGAC-3′) and AM2 (5′-CCTTGCGGTTGGCTTCAGAT-3′) were used for the detection of A. muciniphila species as described by Collado et al. [26]. The total bacterial primers were UniF340 (5′-ACTCCTACGGGAGGCAGCAGT-3′) and UniR514 (5′-ATTACCGCGGCTGCTGGC-3′) [27]. The amplification reactions were conducted in a total volume of 20 µL, containing 1 µL of DNA sample, 10 µL SYBR Green (TIANGEN), and 0.3 µm each primer. Real-time PCR was performed by using a two-step PCR procedure. Assay results were calculated by using the manufacturer’s software as signal threshold cycle values. The 2^–ΔΔCT method was used to represent the mRNA fold change.

2.10 Quantification of bile acid metabolism substances by liquid chromatography–mass spectrometry (LC–MS)

An appropriate amount of sample was placed in an EP tube, methanol was accurately added, and the samples were vortically oscillated. Glass beads were then added and oscillated, and the above operations were repeated at least twice. The supernatant was added with methanol to mix, and vortex oscillation was performed after ultrasonic treatment at room temperature and centrifugation. The supernatant was filtered through a membrane, and the filtrate was added to the flask. The sample was analyzed by using LC–MS with an ACQUITY UPLC BEH C18 column (American Waters Corporation), using a 5 μL sample size and a column temperature of 40 °C. The chromatography was performed by using a gradient of formic acid water (phase A) and acetonitrile (phase B). The LC–MS detection was completed by Suzhou Smartnuclide Co. Ltd.

2.11 Measurement of inlammatory cytokines

IL-2, IL-10, TNF-α, and IFN-γ were measured by using ELISA kits (ml002295, ml037873, ml002095, and ml002277) from mlbio (Shanghai, China) according to the manufacturer’s instructions.

2.12 Flow cytometry

An appropriate amount of blood was collected in anticoagulant tube, and the spleen was placed in trypsin for 30 min and filtered through a cell strainer. The samples were then incubated with Anti-Mouse FITC-labeled CD3ε (AM003E0201, MultiSciences Biotech, China) and PE-labeled CD8α (AM008A0204, MultiSciences Biotech, China) for 20 min at room temperature. Lysing Buffer (555899, BD Biosciences) was added to the samples, and the samples were tested by using a BD FACSAria^TM Fusion machine.

2.13 Statistical analysis

Data analysis were performed by using GraphPad Prism 8 and SPSS 25.0 statistics software. Each sample was repeated at least three times, and the data were presented as mean ± SD. Comparison between two groups with normal distribution was performed by using t-test. One-way ANOVA was used when three or more groups were included. P < 0.05 was considered statistically significant.

3 Results

3.1 DHA increased the abundance of A. muciniphila during anti-PD-1 treatment in mice with liver tumors

Our previous research showed that the combination of anti-PD-1 and DHA (mark as DHA + anti-PD-1) reduced the tumor volumes than anti-PD-1 or DHA treatment alone in vivo [23]. Consistent with this, the maximal size of tumors was lower in the DHA + anti-PD-1 (3.89 ± 0.6 mm) group than the anti-PD-1 (6.31 ± 0.68 mm) or DHA (5.95 ± 1.05 mm) group (Fig.1) in C57BL/6 mice with liver tumors induced by DEN/TCPOBOP (Fig.1). The DHA + anti-PD-1 group reduced the tumor numbers more than either DHA or anti-PD-1 alone (Fig.1). These results suggested that DHA promoted the efficacy of anti-PD-1 treatment in mice with liver tumors.

The balanced gut microbiota promoted the effect of anti-PD-1 immunotherapy in HCC [9]. Therefore, colon microbiota was analyzed by 16S rRNA sequencing from normal mice and treated mice with liver tumors in situ. The sequence amount was reasonable (Fig. S1). Venn diagram showed that the common operational taxonomic units (OTUs) of DHA and normal group accounted for 73.69% of the DHA group, and the common OTUs of anti-PD-1 and normal group accounted for 53.65% of the anti-PD-1 group (Fig.1). The data revealed that the colon bacterial composition in DHA group was more similar to that in the normal group. The abundance of unidentified_Ruminococcaceae and Akkermansia decreased, whereas Alloprevotella increased in the anti-PD-1 group compared with the normal group (Fig.1). However, the abundance of three genera in the DHA group were close to that in the normal group. Akkermansia was changed obviously in each group. Akkermansia abundance was increased with DHA treatment, but decreased by anti-PD-1 compared with the DMSO group (Fig.1 and 1F). The combination of anti-PD-1 and DHA group significantly enriched Akkermansia abundance compared with the anti-PD-1 or DHA group alone (Fig.1 and 1F). These results showed that DHA increased the abundance of Akkermansia during anti-PD-1 treatment.

We examined the promoting effect of DHA on A. muciniphila abundance by using a heterotopic tumor model bearing with Hepa1-6 cells (Fig.2). The sequence amount was reasonable (Fig. S2). Venn diagram showed that a total of 2382 OTUs were identified, including 592 in DMSO group, 1115 in DHA group, 1025 in anti-PD-1 group, and 769 in DHA + anti-PD-1 group (Fig.2). These results suggested that the DHA group contained the most abundant species in the four groups. The result of the top 20 species in abundance showed that A. muciniphila was enriched in the DHA + anti-PD-1 group compared with the other three groups, which was consistent with the results of the mice with liver tumors in situ (Fig.2). The abundance of A. muciniphila in the DHA group was higher than that in the DMSO and anti-PD-1 groups (Fig.2). Microbiota composition in the four groups was different by β-diversity analysis (Fig.2). Verrucomicrobiota and Akkermansia were predominant in the DHA + anti-PD-1 group (Fig.2), and Firmicutes, Alloprevotella, and Erysipelotrichales were predominant in the anti-PD-1 group. These results indicated that DHA increased the abundance of A. muciniphila in tumor-bearing mice during anti-PD-1 treatment.

3.2 A. muciniphila ameliorated the tumor immunosuppressive microenvironment in the combination of anti-PD-1 and DHA treatment

High abundance of A. muciniphila promotes anti-PD-1 treatment in patients with HCC [9].

To explore the effect of A. muciniphila in the combination of DHA and anti-PD-1, we used ATB to reduce the abundance of A. muciniphila in the heterotopic tumor model with Hepa1-6 cells (Fig.3). The abundance of A. muciniphila in the colon was significantly lower in the ATB group than in the sterile water group, as determined by solid culture under anaerobic conditions and real-time PCR (Fig.3 and S3). After stopping ATB treatment, we administered A. muciniphila or sterile water by oral gavage and intraperitoneally injected with the combination of DHA and anti-PD-1 in the tumor-bearing mice. No significant difference was observed in the body weight between the two groups (Fig. S4). The weight and volume of tumors were decreased in the A. muciniphila + DHA + anti-PD-1 group compared with the sterile water + DHA + anti-PD-1 group (Fig.3 and 3D). These data indicated that the antitumor effect may be enhanced by the effect of A. muciniphila during the combination of DHA and anti-PD-1 treatment.

One study reported that A. muciniphila blunted tumor growth through the modulation of CD8⁺ T cell number and activation in colitis-associated colorectal cancer [28]. CD8⁺ T cell numbers were not different in blood and spleen as determined by flow cytometry (Fig.3 and 3F), but were increased in the liver tumor microenvironment as determined by immunohistochemistry in the A. muciniphila + DHA + anti-PD-1 group compared with the sterile water + DHA + anti-PD-1 group (Fig.3 and 3H). We further tested CD8⁺ T cell activation in the tumors. The concentration of IL-2, IFN-γ, and TNF-α in the liver tumors did not change after the oral administration of A. muciniphila during the combination of DHA and anti-PD-1 treatment (Fig.3). However, the level of inhibitory cytokines IL-10 was decreased in the A. muciniphila + DHA + anti-PD-1 group (2693.49 ± 578.36 pg/g) compared with the sterile water + DHA + anti-PD-1 group (3399.71 ± 273.93 pg/g) (Fig.3). The combination of A. muciniphila, DHA, and anti-PD-1 treatment increased CD8⁺ T cell numbers and downregulated IL-10 levels in the liver tumor microenvironment.

3.3 YAP1 decreased the abundance of A. muciniphila

In our previous study, we found that DHA inhibited YAP1 expression in liver tumor cells [23,24] and increased the abundance of A. muciniphila in the colon, as shown in Fig.1 and Fig.1. To explore the relationship between A. muciniphila and YAP1 expression, we induced liver tumors in Yap1^LKO and Yap1^Flox mice using DEN/TCPOBOP (Fig.4). The abundance of total bacteria was the same at 7, 11, 15, 19, and 23 weeks in the feces of Yap1^LKO and Yap1^Flox mice with liver tumors, as determined by real-time PCR assay (Fig.4). However, A. muciniphila abundance was increased at the above five points in Yap1^LKO mice compared with Yap1^Flox mice (Fig.4). These results suggested that hepatocyte-specific Yap1 knockout increased A. muciniphila abundance during the liver tumorigenesis and development in mice.

Further, Yap1^LKO and Yap1^Flox mice without liver tumors were given water containing ATB to reduce A. muciniphila in the colon, followed by gavage of A. muciniphila for two weeks (Fig.4). The abundance of A. muciniphila was higher in Yap1^LKO mice than in Yap1^Flox mice, and the total bacteria in the feces were not different between the two groups (Fig.4). Shannon’s index showed that the bacterial diversity in Yap1^LKO mice was higher than that in Yap1^Flox mice with liver tumors, as determined by 16S rRNA sequencing (Fig.4). The bacterial phyla Firmicutes and Bacteroidota, which accounted for up to 90% of abundance on average, were the predominant populations in the two groups (Fig.4). At the genus level, Akkermansia abundance in Yap1^LKO mice was higher than that in Yap1^Flox mice among the top 10 species (Fig.4). The bacteria composition in the two groups was significantly different by β-diversity analysis (P = 0.026, Fig.4). Further, LefSe analysis revealed that the Yap1^LKO group was characterized by A. muciniphila (a representative of the Verrucomicrobiota) and Clostridia_UCG_014 (a member of the Firmicutes), but Desulfovibrionaceae (a member of the Proteobacteria) and Muribaculaceae (a member of the Bacteroidota) were considered the key species in the Yap1^Flox group with liver tumors in situ (Fig.4). These results indicated that YAP1 decreased the abundance of A. muciniphila in mice with or without liver tumors.

3.4 Decreased abundance of A. muciniphila in the colon by YAP1 related to bile acid metabolism

Bile salts inhibited A. muciniphila growth in vitro [14] and activated YAP1 to promote liver carcinogenesis [17]. To explore whether A. muciniphila inhibition by YAP1 was related to bile acid metabolism, we tested bile acid components in the liver, serum, and colonic contents from Yap1^Flox and Yap1^LKO mice with liver tumors by LC–MS-based metabolomic analysis (Fig.5). Thirty-eight bile acids components were detected, and the data of bile acids from liver samples were reliable based on a principal component analysis (Fig.5). Ten bile acids were significantly different between Yap1^Flox and Yap1^LKO mice in the liver, with Yap1 knockout resulting in a reduction in the bile acid components. These components were ranked in descending order of decrease as taurohyodeoxycholic acid sodium salt (THDCA) + tauroursodeoxycholic acid sodium salt (TUDCA) > taurochenodeoxycholic acid (TCDCA) > taurocholic acid sodium salt (TCA) > tauro-α-muricholic acid sodium salt (T-alpha-MCA) > tauro-β-muricholic acid sodium salt (T-beta-MCA) > norcholic acid (NorCA) > sodium glycocholate hydrate (GCA) > cholic acid (CA) in the liver (Fig.5 and 5D). Conversely, taurodeoxycholic acid sodium salt (TDCA) and 7,12-diketolithocholic acid (7,12-diketoLCA) were increased.

Five bile acids were different between the two groups in the colon contents. TDCA, β-ursodeoxycholic acid (β-UDCA), glycodeoxycholic acid sodium salt (GDCA), and 23-nordeoxycholic acid (NorDCA) were decreased in Yap1^LKO mice, but THDCA + TUDCA was increased (Fig.5). Four bile acids were different between the two groups in the serum. GCA, T-alpha-MCA, CA, and NorCA were decreased in Yap1^LKO mice compared with Yap1^Flox mice (Fig.5). These results suggested that Yap1 knockdown mainly affected the metabolism of hepatic bile acids.

Interestingly, TCDCA, GCA, CA, TDCA, and GDCA were reported to inhibit the growth of A. muciniphila in vitro [14]. We analyzed the correlation between gut microbiota composition and liver bile acid components. Twenty-five pairs of microbial and bile acid combinations were positively correlated, whereas 30 pairs were negatively correlated at the phylum level. Six pairs had positive correlations, including Armatimonadota and 6-ketoLCA, Bdellovibrionota and 6-ketoLCA, Fusobacteriota and TLCA, Fusobacteriota and T-alpha-MCA, Bacteroidota and TCA, and Proteobacteria and NorCA. Six negative pairs were Verrucomicrobiota and TCDCA, Verrucomicrobiota and TLCA, Fusobacteriota and 7,12-diketoLCA, Armatimonadota and TCA, Bdellovibrionota and TCA, and GAL15 and TCA (Fig.5). These results showed that Yap1 knockout in hepatocyte induced the balanced gut microbiota composition and bile acid homeostasis. At the species level, A. muciniphila was positively correlated with 7-ketoLCA and beta-CA but negatively correlated with TLCA, THDCA + TUDCA and TCDCA (Fig. S5). Hepatocyte-specific Yap1 knockout elevated A. muciniphila abundance, which was related to the incomplete hepatic metabolism of bile acids.

3.5 DHA depressed YAP1 expression, leading to the increased abundance of A. muciniphila

Our previous study showed that DHA inhibited YAP1 expression in liver tumor cells in vivo [23,24] and increased the abundance of A. muciniphila in the intestine (Fig.1 and 1F). Further investigation was performed to determine whether DHA increased the abundance of A. muciniphila by inhibiting YAP1 expression in Yap1^LKO and Yap1^Flox mice with liver tumors induced by DEN/TCPOBOP (Fig.6). The abundance of A. muciniphila displayed a 6.40-fold enhancement in Yap1^LKO mice compared with Yap1^Flox mice by real-time PCR in the DMSO group, suggesting that YAP1 inhibited A. muciniphila abundance (Fig.6). Similarly, DHA increased the abundance of A. muciniphila and was estimated to be 8.50-fold higher than that in the DMSO group in Yap1^Flox mice. However, DHA increased A. muciniphila abundance by only 1.50-fold in Yap1^LKO mice compared with the DMSO group. These results showed that DHA increased the abundance of A. muciniphila, which depended on YAP1 expression in the hepatocyte in mice with liver tumors (Fig.6). Recently, our group reported that DHA depressed the CA and CDCA levels of liver tissue in Yap1^LKO mice with liver tumors [24]. To examine the changes of bile acid metabolites in the colonic contents after the combination of A. muciniphila and DHA (marked as A. muciniphila + DHA), the mouse heterotopic tumor model with Hepa1-6 cells was intraperitoneally injected with DHA or DMSO after drinking ATB water and gavaged with A. muciniphila or sterile water (Fig.6). The LC–MS results showed that DHA treatment reduced β-UDCA and HDCA in the colonic contents, and A. muciniphila decreased NorDCA and increased UCA (Fig.6–6F). β-UDCA decreased in the colonic contents of Yap1^LKO mice (Fig.5). These results suggested that the combination of A. muciniphila and DHA regulated bile acid homeostasis in the colon of C57BL/6 mice with heterotopic tumors.

3.6 A. muciniphila increased CD8⁺ T cell numbers in spleen and tumor niche during DHA treatment

We explored whether A. muciniphila promoted the antitumor effect of DHA. A. muciniphila reduced the weight and volume of tumors (Fig.7 and 7C) compared with the group treated with sterile water during DHA treatment by heterotopic tumor mice loading with Hepa1-6 cells (Fig.7). No significant difference was observed in the body weight between the two groups (Fig. S6). The result showed that A. muciniphila promoted the antitumor effect of DHA. A. muciniphila increased CD8⁺ T cell numbers in the spleen but not in the blood (Fig.7 and 7E) by FCM. A. muciniphila increased CD8⁺ T cell numbers (Fig.7 and 7G) and the content of IFN-γ in liver tumor niches (Fig.7). However, IL-2, IL-10, and TNF-α did not change in DHA treatment in tumor niches (Fig.7). These results suggested that A. muciniphila enhanced the antitumor effect of DHA in relation to the increased numbers of CD8⁺ T cells in the spleen and tumor niches and CD8⁺ T cell activation in tumor niches.

3.7 Hepatocyte-specific Yap1 knockout increased the abundance of A. muciniphila and promoted anti-PD-1 effect in mice with liver tumors

Anti-PD-1 treatment enhanced YAP1 expression (Fig.8) and decreased A. muciniphila abundance in mice with liver tumors (Fig.1–1F). We observed the effect of YAP1 inhibition on anti-PD-1 therapy in mice with liver tumors (Fig.8). The tumor numbers and Ki-67 expression level were reduced, but the tumor sizes showed no significant difference in the anti-PD-1 group compared with the normal saline group in Yap1^Flox mice, suggesting that anti-PD-1 inhibited tumor growth (Fig.8–8E). In Yap1^LKO mice, the tumor numbers, Ki-67 expression level, and liver/body weight decreased in the anti-PD-1 group compared with the normal saline group (Fig.8–8E). Interestingly, anti-PD-1 treatment significantly reduced the tumor numbers and size, and Ki-67 expression level in Yap1^LKO mice compared with Yap1^Flox mice. These results suggested that hepatocyte-specific Yap1 knockout improved the effect of anti-PD-1 treatment on mice with liver tumors.

Anti-PD-1 increased the expression level of YAP1 protein in the liver tumors from Yap1^Flox and Yap1^LKO mice (Fig.8). The abundance of A. muciniphila displayed 0.30-fold after anti-PD-1 treatment in Yap1^Flox and Yap1^LKO mice with tumors in liver compared with the normal saline group. These results showed that anti-PD-1 decreased A. muciniphila abundance in Yap1^LKO and Yap1^Flox mice. However, the abundance of A. muciniphila in Yap1^LKO mice was 2.00-fold higher than that in Yap1^Flox mice after anti-PD-1 treatment (Fig.8). The result showed that hepatocyte-specific Yap1 knockout increased the abundance of A. muciniphila in the colon during anti-PD-1 treatment in mice with liver tumors.

4 Discussion

YAP1 expression increased in liver tumor cells in early HCC, in which A. muciniphila abundance was also decreased. A. muciniphila elevated the response rate to anti-PD-1 therapy. However, the relationship between YAP1 expression in the liver and the abundance of A. muciniphila in the colon is unclear in HCC. Here, we first showed that anti-PD-1 treatment decreased the abundance of A. muciniphila in the colon and increased the expression level of YAP1 in liver tumor cells. Secondly, YAP1 in liver tumor cells inhibited the abundance of A. muciniphila associated with bile acid metabolism. Thirdly, DHA increased the abundance of A. muciniphila by YAP1 inhibition leading to enhance anti-PD-1 therapeutic efficacy in mice with liver tumors (Fig.9). Therefore, the combination of anti-PD-1 and DHA, a potential YAP1 inhibitor, is a good strategy in HCC.

In this study, we first demonstrated that DHA, an artemisinin derivative, increased the abundance of A. muciniphila in the colon by YAP1 depression in liver tumor cells through Yap1^LKO and Yap1^Flox mice with tumors in situ. Similarly, artesunate and 5-desmethylsinensetin, two derivatives of artemisinin, inhibited the expression and activation of YAP1 in the human uveal melanoma C918 cells and breast cancer cells [29,30]. DHA promoted anti-PD-1 therapeutic efficacy in association with the increased abundance of A. muciniphila in the colon. Some studies showed that the increased abundance of A. muciniphila was beneficial for anti-PD-1 therapy on patients with HCC, non-small cell lung cancer, melanoma, renal cell carcinoma, and colitis-associated cancer in clinical trials [6–9,28,31,32]. Fecal microbiota transplantation or oral gavages of A. muciniphila were used to restore the immunotherapy response and increase the antitumor effect of anti-PD-1 [8,33,34]. Here, we proposed a promising strategy to reverse the imbalance in A. muciniphila homeostasis by YAP1 depression via DHA, a drug approved by the U.S. FDA. Furthermore, we confirmed that A. muciniphila by oral gavage elevated the antitumor effect of DHA in heterotopic tumor mice. Unlike our study, some papers reported that the increased abundance of A. muciniphila promoted the development in esophageal adenocarcinoma [35], colonic [36], and colorectal tumors [37,38]. The abundance of A. muciniphila may have dual activities in regulating tumor or immune cells [39]. Mechanistically, we clarified that A. muciniphila by oral gavage increased the number and activation of CD8⁺ T cells in liver tumor niches during the combination of DHA and anti-PD-1 or DHA treatment alone. Accordingly, one study showed that A. muciniphila inhibited tumorigenesis by expanding CD8⁺ T cells in the colon and activating CD8⁺ T cells in the mesenteric lymph nodes [28]. Other studies reported that A. muciniphila-derived extracellular vesicles (Akk-EVs) increased the number of IFN-γ⁺ CD8⁺ T cells and decreased the prostate tumor burden in mice [40]. The effects of A. muciniphila in the subcutaneous liver tumor model imply a system effect in our study. Consistent with this, one study reported that oral gavages of A. muciniphila induced dendritic cells to secrete IL-12 in mice with xenograft MCA-205 sarcoma [6]. Therefore, we suggested that the antitumor effect of A. muciniphila was related to the regulation of systemic immunity during anti-PD-1 treatment in mice with xenograft Hepa1-6 cells.

Recently, we reported that DHA depressed the content of CA and CDCA in liver tissue of Yap1^LKO mice with liver tumors [24]. In this study, we found that hepatocyte-specific Yap1 knockout decreased the content of TCDCA and TCA in the liver and the GCA content in the serum from mice with liver tumors. Similarly, YAP1 regulated some genes involved in bile acid metabolism [41]. CDCA activated YAP1 in the liver cells to promote HCC [17], whereas TUDCA inhibited YAP1 to reduce the formation of HCC [42], suggesting that bile acids regulated YAP1 activation in HCC. TCDCA, GCA, and TCA are conjugated primary bile acids synthesized from CA and CDCA in the liver. The levels of TCDCA, GCA, and TCA increased in the liver and serum of patients with HCC [43]. Specifically, TCDCA inhibited the gene expression of tumor suppressors in HepG2 cells [44,45]. The content of GCA in the serum is positively correlated with HCC occurrence and development [46–48]. Here, Yap1 knockout alleviated the accumulation of bile acids in the liver (such as TCDCA, GCA, and TCA) and serum (such as GCA), and inhibited the development of liver tumors.

Furthermore, Yap1 knockout increased the abundance of A. muciniphila in the colon. A. muciniphila is abundant in the colon [49], in which primary bile acids are converted to secondary bile acids [50]. Some bile acids (GDCA, TDCA, TCDCA, GCA, CA and GCDCA) inhibited the growth of A. muciniphila in the culture medium in vitro [14]. In this study, the decrease in bile acids by Yap1 knockout might be related to the increased abundance of A. muciniphila in the colon contents. However, we did not observe the reduction of TCDCA, GCA, and TCA in the colon contents. Furthermore, bile acids of ileum and colon significantly increased, but bile acids of liver and serum changed slightly after gavage of A. muciniphila in mice [51]. Therefore, hepatocyte-specific Yap1 knockout maintained the homeostasis of bile acids in the liver, resulting in an increased abundance of A. muciniphila in the colon contents.

5 Conclusions

Anti-PD-1 treatment increased YAP1 expression in the liver and decreased the abundance of A. muciniphila in the colon in liver tumor-bearing mice. Hepatocyte-specific Yap1 knockout increased the abundance of A. muciniphila during anti-PD-1, leading to increased sensitivity to the treatment. YAP1 inhibited the abundance of A. muciniphila in the colon, which was associated to bile acid homeostasis in the liver. We first reported that DHA increased the abundance of A. muciniphila by YAP1 suppression, eventually improving the efficacy of anti-PD-1 on liver tumors. Therefore, we proposed combining DHA with anti-PD-1 as a strategy in liver tumor treatment.

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