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May  2023
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Chang Wei Qing Decoction enhances the anti-tumor effect of PD-1 inhibitor therapy by regulating the immune microenvironment and gut microbiota in colorectal cancer

  • The anti-tumor effect of anti-PD-1 antibody has long been shown to be strongly related to the tumor immune microenvironment (TIME). This study aimed to mechanistically assess whether Chang Wei Qing (CWQ) Decoction can enhance the anti-tumor effect of PD-1 inhibitor therapy. PD-1 inhibitor therapy showed the significant anti-tumor effect in patients with mismatch repair-deficient/microsatellite instability-high (dMMR/MSI-H) colorectal cancer (CRC), rather than those with mismatch repair-proficient/microsatellite stable (pMMR/MSS) CRC. Hence, immunofluorescence double-label staining was utilized to explore the difference in the TIME between dMMR/MSI-H and pMMR/MSS CRC patients. Flow cytometry was used to analyze T-lymphocytes in tumors from mice. Western blot was used to measure the expression of PD-L1 protein in mouse tumors. The intestinal mucosal barrier of mice was evaluated by hematoxylin-eosin staining and immunohistochemistry. 16S rRNA-gene sequencing was used to examine the structure of the gut microbiota in mice. Subsequently, Spearman’s correlation analysis was used to analyze the relationship between the gut microbiota and tumor-infiltrating T-lymphocytes. The results showed that dMMR/MSI-H CRC patients had more CD8+ T cells and higher expression of PD-1 and PD-L1 proteins. In vivo, CWQ enhanced the anti-tumor effect of anti-PD-1 antibody and increased the infiltration of CD8+ and PD-1+CD8+ T cells in tumors. Additionally, the combination of CWQ with anti-PD-1 antibody resulted in lower inflammation in the intestinal mucosa than that induced by anti-PD-1 antibody alone. CWQ and anti-PD-1 antibody co-treatment upregulated PD-L1 protein and reduced the abundance of Bacteroides in the gut microbiota but increased the abundance of Akkermansia, Firmicutes, and Actinobacteria. Additionally, the proportion of infiltrated CD8+PD-1+, CD8+, and CD3+ T cells were found to be positively correlated with the abundance of Akkermansia. Accordingly, CWQ may modulate the TIME by modifying the gut microbiota and consequently enhance the anti-tumor effect of PD-1 inhibitor therapy.
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Chang Wei Qing Decoction enhances the anti-tumor effect of PD-1 inhibitor therapy by regulating the immune microenvironment and gut microbiota in colorectal cancer

    Corresponding author: E-mails: lan701206@163.com (SHI Xiaolan); liuhui79@shutcm.edu.cn (LIU Hui); dengwanli2631@shutcm.edu.cn (DENG Wanli)
  • 1. Department of Oncology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200062, China
  • 2. Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

Abstract: The anti-tumor effect of anti-PD-1 antibody has long been shown to be strongly related to the tumor immune microenvironment (TIME). This study aimed to mechanistically assess whether Chang Wei Qing (CWQ) Decoction can enhance the anti-tumor effect of PD-1 inhibitor therapy. PD-1 inhibitor therapy showed the significant anti-tumor effect in patients with mismatch repair-deficient/microsatellite instability-high (dMMR/MSI-H) colorectal cancer (CRC), rather than those with mismatch repair-proficient/microsatellite stable (pMMR/MSS) CRC. Hence, immunofluorescence double-label staining was utilized to explore the difference in the TIME between dMMR/MSI-H and pMMR/MSS CRC patients. Flow cytometry was used to analyze T-lymphocytes in tumors from mice. Western blot was used to measure the expression of PD-L1 protein in mouse tumors. The intestinal mucosal barrier of mice was evaluated by hematoxylin-eosin staining and immunohistochemistry. 16S rRNA-gene sequencing was used to examine the structure of the gut microbiota in mice. Subsequently, Spearman’s correlation analysis was used to analyze the relationship between the gut microbiota and tumor-infiltrating T-lymphocytes. The results showed that dMMR/MSI-H CRC patients had more CD8+ T cells and higher expression of PD-1 and PD-L1 proteins. In vivo, CWQ enhanced the anti-tumor effect of anti-PD-1 antibody and increased the infiltration of CD8+ and PD-1+CD8+ T cells in tumors. Additionally, the combination of CWQ with anti-PD-1 antibody resulted in lower inflammation in the intestinal mucosa than that induced by anti-PD-1 antibody alone. CWQ and anti-PD-1 antibody co-treatment upregulated PD-L1 protein and reduced the abundance of Bacteroides in the gut microbiota but increased the abundance of Akkermansia, Firmicutes, and Actinobacteria. Additionally, the proportion of infiltrated CD8+PD-1+, CD8+, and CD3+ T cells were found to be positively correlated with the abundance of Akkermansia. Accordingly, CWQ may modulate the TIME by modifying the gut microbiota and consequently enhance the anti-tumor effect of PD-1 inhibitor therapy.

    • Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide [1-3]. Chemotherapy, radiotherapy, and targeted therapy are the main strategies for the treatment of advanced CRC. However, adverse reactions and acquired pharmacological resistance limit the efficacy of these treatments and restrict the potential improvement in overall survival in CRC [4].

      Recent advances have demonstrated that therapies based on immune checkpoint inhibitors (ICIs), such as PD-1 inhibitor therapy, are highly effective against most of solid tumors [5]. While only 10%−15% of CRC patients with microsatellite instability-high (dMMR/MSI-H) tumors were approved by the FDA for receiving PD-1 inhibitor therapy [6-7]. Furthermore, PD-1 inhibitor therapy was largely ineffective in CRC patients with mismatch repair-proficient/microsatellite stable (pMMR/MSS) tumors [8-9]. Therefore, it is crucial to augment the efficacy of PD-1 inhibitor therapy.

      The tumor immune microenvironment (TIME) consists of the immunological components within tumors and comprises innate immune cells, adaptive immune cells, extracellular immune factors, and cell-surface molecules. The TIME has long been shown to be strongly related to the anti-tumor effect of PD-1 inhibitor therapy [10-11]. Notably, promoting the infiltration of T-lymphocytes into tumor tissues can enhance the efficacy of PD-1 inhibitor therapy [12-13]. Thus, strategies that increase the number of T-lymphocytes in CRC tumors are needed.

      In recent years, the gut microbiota has attracted much attention due to its extensive biological roles, including affecting host immunity. It has been found that the gut microbiota can recruit T-lymphocytes into colorectal tumor tissues [14]. For example, Akkermansia increased the number of CCR9+ CXCR3+ CD4+ and CD8+ T cells in the tumor microenvironment to improve the efficacy of PD-1 inhibitor therapy [15]. Chang Wei Qing Decoction (CWQ) is a traditional Chinese medicine herbal formula, consisting of Astragalus root, Codonopsis, Atractylodes, Polyporus umbellatus, Coix seed, Fructus akebiae, Sargent gloryvine and Wild grapevine. Astragalus root and Codonopsis nourish qi and invigorate the spleen. Atractylodes, Polyporus umbellatus, and Coix seed dry dampness. Fructus akebiae, Sargent gloryvine and Wild grapevine clear heat and eliminate toxins. CWQ has long been employed clinically to treat cancer. In our previous studies, CWQ reduced the toxicity and adverse effects of radiotherapy and chemotherapy for advanced CRC, modified the gut microbiota, and improved host immune function [16-17]. Here, we investigated mechanistically whether CWQ can augment the efficacy of PD-1 inhibitor therapy through the gut microbiota in CRC.

    Material and Methods
    • Dulbecco’s modified Eagle’s medium (DMEM), trypsin, fetal bovine serum (FBS), PerCP-Cyanine5.5 (Lot #2017819), CD279 (PD-1), BV421 (Lot #9014528), Fixable Viability Dye eFluor™ 780 (Lot 2229096), FITC (Lot 2037887), and the monoclonal antibodies against CD45 (30-F11) (Lot 2026515), CD3e (145-2C11), PE-Cyanine7 (Lot 2114130), CD4 (RM4-5), and CD8a (53-6.7) were obtained from eBioscience, Inc. (San Diego, CA, USA).

    • A total of 20 CRC patients who underwent surgry in Putuo Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from January 2018 to January 2021 were selected, including 10 patients with dMMR/MSI-H genotype, and the other 10 patients with pMMR/MSS genotype, and the corresponding specimens were collected. There were statistical differences in baseline data between the two groups (P > 0.05), indicating that the two groups were comparable (Table 1).

      pMMR/MSSdMMR/MSI-HP-value
      Gender 0.371
      Men 6 4
      Women 4 6
      Average age 70.1 72 0.784
      Degree of differentiation 0.607
      Low 1 1
      Low-medium 2 4
      Medium 7 5
      Lymph node metastasis 0.639
      Yes 3 4
      No 7 6
      Histological type 0.606
      Adenocarcinoma 8 7
      Mucinous adenocarcinoma 2 3
      Distant metastasis 0.531
      Yes 1 2
      No 9 8
      Staging 0.644
      Phase I 0 1
      Phase II 7 5
      Phase III 2 2
      Phase IV 1 2

      Table 1.  Summary of demographic information

      This study was approved by the Ethics Committee of Putuo District Central Hospital, Shanghai University of Traditional Chinese Medicine (Approval ID: 2019-691-46-01).

    • To explore the distributions of CD8+ and CD4+ T cells and the expression of PD-1 and PD-L1 proteins in CRC tumors, double immunofluorescence staining was performed on specimens from the CRC patients. All the specimens were fixed in 4% formalin, then paraffin-embedded and sectioned. The slices were incubated with one of the following primary antibodies at the indicated dilutions: human CD4 antibody (1 : 200, R&D), anti-CD8 alpha (1 : 100, Abcam), PD-L1 (E1L3N®) XP® rabbit mAb (1 : 200, CST), and PD-1 (D4W2J) XP rabbit mAb (1 : 200, CST). Then, they were incubated with the corresponding secondary antibodies. The sections were finally stained with DAPI at 37 °C for 10 min and then photographed by a fully automated scanner. The images were visualized by the CaseViewer software, and the expression of the analyzed proteins in different sub-types of tumors were analyzed by Image Pro Plus 6.0.

    • CWQ Formula comprised 30 g raw Astragalus root, 15 g Codonopsis, 15 g Atractylodes, 24 g Polyporus umbellatus, 30 g Coix seed, 24 g Fructus akebiae, 30 g Sargentgloryvine, and 30 g Wild grapevine. These herbs were boiled in distilled water and the resultant decoction was concentrated into granules (prepared by Tianjiang Pharmaceutical Co., Ltd., Jiangyin, China). Then, the granules were dissolved in distilled water to achieve a concentration of 2.574 g·mL−1 and stored at 4 °C.

      Anti-PD-1 antibody (11430), a kind of PD-1 inhibitors, was purchased from Xinda Biopharmaceutical Co. (Suzhou, China), diluted in PBS to achieve a concentration of 0.5 mg·mL−1 and then stored at 4 °C.

    • MC38 mouse colon cancer cell line was obtained from the Shanghai Institute of Cell Research (Shanghai, China) and cultured in DMEM with 10% FBS at 37 °C in an atmosphere of 95% air and 5% CO2.

    • Specific-pathogen–free female C57BL/6 mice (5 weeks old, 18.0 ± 2.0 g, n = 24) were purchased from Shanghai SLAC Laboratory Animal Co. The experimental protocol was approved by the Animal Experimentation Ethics Committee of Shanghai University of Traditional Chinese Medicine (Approval number: PZSHUTCM201023005).

      The mice were acclimated for one week prior to the study. Subsequently, MC38 cells (1.0 × 107 cells/mouse) were subcutaneously transplanted into the right axillary region of each mouse and allowed to form tumors for about one week. Tumor formation was observed daily until the surface area of the tumor reached 25 mm2. Then, the mice were randomly assigned to the following four groups (n = 6): a Control group (0.2 mL normal saline i.g. and 0.2 mL normal saline i.v.), a CWQ group (0.2 mL CWQ i.g. and 0.2 mL normal saline i.v. ), an anti-PD-1 antibody group (0.2 mL of the anti-PD-1 antibody i.v. and 0.2 mL normal saline i.g.), and a CWQ combined with anti-PD-1 antibody group (0.2 mL CWQ i.g. and 0.2 mL of the anti-PD-1 antibody i.v.). The mice were treated with CWQ daily for 18 days, and the anti-PD-1 antibody was administered on days 5, 10, and 15. The mice were sacrificed four days after the last intravenous injection of the anti-PD-1 antibody.

    • Tumor samples from the mice were placed in PBS at 4 °C, minced and fully digested. The digest was then filtered to obtain a single-cell suspension, before centrifugation at 500 g for 5 min. The pellet was resuspended in FACS buffer to achieve a concentration of 2 × 106 cells/mL. Then, 100 μL of the cell suspension was incubated with an antibody against the Fc receptor at 20–30 °C for 10 min to block non-specific antibody binding. The cells were then incubated with fluorescent-labeled antibodies against CD45, CD3, CD4, CD8, and PD-1 at 20−30 °C for 30 min. Next, 2−3 mL FACS buffer was added per sample, and the cells were washed with PBS, followed by centrifugation at 250 g for 5 min. The pellet was resuspended in 100 μL FACS buffer, and the ratios of CD3+, CD4+, CD8+, and PD-1+ CD8+ T cells were assessed by flow cytometry. The results were analyzed by the FlowJo X software (VX 0.7).

    • Tumor samples from the mice were homogenized in the RIPA lysis buffer (Biyuntian Biotechnology Co., Ltd., Shanghai, China) containing protease and protein-phosphatase inhibitors. A BCA protein quantification kit (Biyuntian Biotechnology Co., Ltd., Shanghai, China) was used to determine the total protein concentration of each homogenate. The homogenates comprising 50 μg of total protein were subjected to Tris-glycine SDS PAGE (10%), and the separated proteins were transferred onto nitrocellulose membrane. Then, the membrane was blocked with 5% BSA (Biyuntian Biotechnology Co., Ltd., Shanghai, China) in TBST at 37 °C for 2 h and incubated overnight at 4 °C with the following antibodies (at the indicated dilutions): anti-PD-L1 (Proteintech, 1 : 2000), anti-STAT3 (CST, 1 : 1000), anti-EIF-2α (CST, 1 : 1000), anti-p-EIF-2α (CST, 1 : 1000), anti-GAPDH (CST, 1 : 2000), and anti-β-actin (CST, 1 : 2000). The next day, the membrane was incubated with the corresponding secondary antibodies (CST, 1 : 2000) at 37 °C for 2 h. Target protein bands were developed using an enhanced chemiluminescence kit [Sangon Biotech (Shanghai) Co.] and then scanned using an Amersham Imager 600. The relative protein amounts were determined by the ImageJ software.

    • The intestinal tissue 4 cm above the anus was removed from mice. Subsequently, 1 cm of the dissected tissue was washed with ice-cold saline and then fixed with 10% formalin, embedded in paraffin, sectioned, and finally stained with hematoxylin-eosin (H&E) or Sirius red (to evaluate collagen deposition). The sections were dehydrated using ethanol in gradient concentrations followed by incubation in xylene. The samples were mounted and then observed under a light microscope (Olympus, Tokyo, Japan).

      For immunohistochemistry, the intestinal tissue sections were de-paraffinized, followed by an antigen-retrieval process by heating in 10 mmol·L−1 citrate buffer (pH 9.0), before treatment with 3% hydrogen peroxide. The mouse anti-ZO-1 (Abcam, USA), mouse anti-Occludin (CST, USA), and anti-Claudin (Abcam, USA) antibodies were applied at the dilutions of 1 : 500, 1 : 200, and 1 : 250, respectively. Then, the corresponding horseradish-peroxidase–conjugated secondary antibodies were applied, and the targeted antigens were detected using 3,3′-diaminobenzidine tetrahydrochloride under a light microscope (Olympus, Tokyo, Japan).

    • The perianal regions of five randomly selected mice per group were disinfected, and the mice were induced to defecate through abdominal massage. Two-to-four pieces of feces were aseptically collected using forceps into sterile lyophilization tubes, immediately placed in liquid nitrogen, and then stored at −80 °C.

    • Fecal samples were collected from the mice on day 18 of the drug intervention and then kept at 80 °C for 16S rRNA-gene sequencing. The total genomic DNA of the fecal microbiota was extracted from 20 samples (n = 5) by the E.Z.N.A.® soil DNA Kit (Omega Bio-tek, Norcross, GA, U.S.), according to the manufacturer’s instructions. The extracted DNA was separated on a 2% agarose gel, and the DNA concentration and purity were evaluated on a NanoDrop 2000 UV-vis spectrophotometer (Thermo Scientific, Wilmington, USA). The hypervariable region V3–V4 of the bacterial 16S rRNA gene was amplified using primer pairs 338F and 806R in an ABI GeneAmp® 9700 polymerase chain reaction (PCR) thermocycler (ABI, CA, USA). The thermocycler conditions were described as follows: initial denaturation at 95 °C for 3 min, followed by 27 cycles of denaturing at 95 °C for 30 s, annealing at 55 °C for 30 s and extension at 72 °C for 45 s, and single extension at 72 °C for 10 min, and ending at 4 °C. The PCR products were run on a 2% agarose gel. The corresponding amplicons were extracted from the gel using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA), according to the manufacturer’s instructions and then quantified using Quantus™ Fluorometer (Promega, USA). The reactions were performed in triplicate.

      The purified amplicons were pooled in equimolar and then paired-end-sequenced in an Illumina MiSeq PE300 platform/NovaSeq PE250 platform (Illumina, San Diego, USA) by Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) according to the standard protocols.

      Operational taxonomic units (OTUs) with 97% similarity cutoff were clustered using UPARSE version 7.1 [18-19], and then chimeric sequences were identified and removed. The taxonomy of each OTU representative sequence was analyzed using RDP Classifier version 2.2 [20] against the 16S rRNA database (eg. Silva v138), with a confidence threshold of 0.7.

    • Statistical analysis was performed using SPSS 25.0 (IBM Corp., Armonk, NY, USA). The normally distributed data of any given two groups and those of more than two groups were compared using t-tests and one-way ANOVA, respectively. Data that were not normally distributed were compared using rank-sum tests. Values with P < 0.05 were considered statistically significant. Graphs were prepared using GraphPad Prism 8 (GraphPad Software Inc., San Diego, CA, USA).

    Results
    • We investigated the tumor microenvironment in dMMR/MSI-H and pMMR/MSS CRC patients through double immunofluorescence staining to detect CD8+ and CD4+ T cells in tumor tissues. The results showed that the number of CD8+ and CD4+ T cells in the dMMR/MSI-H CRC group was significantly higher than that in the pMMR/MSS CRC group (both P < 0.05). Panoramic views of the tumor sections revealed that CD8+ and CD4+ T cells were widely scattered throughout the dMMR/MSI-H CRC group in significantly more amounts than the pMMR/MSS CRC group, where these cells were mainly located at the edges (Figs. 1A1C).

      Figure 1.  Differences in the tumor microenvironment between dMMR/MSI-H and pMMR/MSS CRC patients. (A) Green, red, and blue signals reflect CD8+ T cells, CD4+ T cells, and the nuclei, respectively. Comparison of the number of (B) CD8+ and (C) CD4+ T cells between the dMMR/MSI-H and pMMR/MSS CRC groups. (D) Green, red, and blue signals reflect PD-L1 and PD-1 proteins, and the nuclei respectively. (E) Comparison of PD-L1 protein expression between the dMMR/MSI-H and pMMR/MSS CRC groups. (F) Comparison of PD-1 protein expression between the dMMR/MSI-H and pMMR/MSS CRC groups. Data are shown as the mean ± SD ( n = 10), **P < 0.01, and ***P < 0.001 vs the dMMR/MSI-H CRC group

    • The expression of PD-1 and PD-L1 proteins in the dMMR/MSI-H and pMMR/MSS CRC groups were assessed through double immunofluorescence staining. These two proteins were co-localized in the dMMR/MSI-H CRC group and bound to each other (Figs. 1D1F). Additionally, their expression was significantly higher in the dMMR/MSI-H CRC group than that in the pMMR/MSS CRC group (both P < 0.01). Panorama mapping revealed that both PD-1 and PD-L1 proteins were widely distributed in the dMMR/MSI-H CRC group, whereas in the pMMR/MSS CRC group, they were mainly located at the margins of the tumor. Notably, their distribution pattern was similar to those of CD8+ and CD4+ T cells.

    • We investigated the effect of CWQ in combination with anti-PD-1 antibody on the growth of CRC cells subcutaneously transplanted in mice. Compared with the Control group, tumor volume (Fig. 2B) and weight (Fig. 2C) significantly decreased in the three treatment groups (P < 0.05). The results indicated that although the tumor growth was inhibited in the three treatment groups, only the combinatorial therapy exhibited significantly inhibitory effect.

      Figure 2.  Effect of the combinatorial therapy with CWQ and anti-PD-1 antibody on CRC tumor formation and the expression of related proteins in a mouse xenotransplantation model. (A) CRC mice tumors from different groups (n = 6) for 19 days. (B) Tumor volumes of the mice treated with CWQ (2.574 g·mL−1), anti-PD-1 antibody (5 mg·kg−1), CWQ (2.574 g·mL−1), or normal saline.*P < 0.05 vs the Control group, #P < 0.05 vs the anti-PD-1 antibody group. (C) Tumor weights in each group,*P < 0.05 vs the Control group. (D and E) Effect of CWQ and anti-PD-1 antibody on the expression of PD-L1, STAT3, HMGB-1, EIF-α and p-EIF-α proteins in CRC tumors. **P < 0.01 vs the Control group, ##P < 0.01, and ###P < 0.001 vs the combination group. Data are presented as the mean ± SD

    • To explore the mechanism by which the combination of CWQ and anti-PD-1 antibody inhibited tumor growth, we first examined the STAT3/PD-L1 signaling pathway and immunogenic cancer cell death (ICD) in mice tumors, which are considered to influence the anti-tumor effect of PD-1 inhibitor therapy [21, 22]. Compared with the Control group, STAT3 and EIF-α proteins were upregulated in the CWQ and combination groups, while p-EIF-α was upregulated in the anti-PD-1 antibody group and combination groups but PD-L1 protein was significantly upregulated only in the combination group (Figs. 2D2E). Furthermore, the levels of HMGBM-1 did not change in any groups. These findings suggested that CWQ combined with anti-PD-1 antibody significantly upregulated PD-L1 protein in tumor tissues, whereas either CWQ or anti-PD-1 antibody alone did not. Studies have shown that STAT3 can promote the expression of PD-L1 protein [21], but in our study, PD-L1 protein was only highly expressed in the combination group, and the underlying mechnism involved needs further exploration.

    • To further explore the effect of CWQ and anti-PD-1 antibody in the TIME, we detected the proportion of tumor-infiltrating lymphocytes (TILs) in tumor tissues. Compared with the control group, the proportion of CD3+ T cells in the tumors tissue increased in the three treatment groups, and significantly increases were found in the CWQ group alone (P < 0.05, Figs. 3A and 3D). Furthermore, the proportion of CD8+ T cells significantly increased in the CWQ and combination groups (P < 0.05 and P < 0.01, respectively). Compared with the Control group, the combination group prsented a decreased the proportion of CD4+ T cells (P < 0.05), rather than the CWQ group and the anti-PD-1 antibody group (Figs. 3B, 3E and 3F), and the proportion of PD-1+ CD8+ T cells in the tumors significantly increased in the CWQ, anti-PD-1 antibody, and combination groups (all P < 0.05) (Figs. 3C and 3G). These findings indicated that CWQ upregulated the infiltration of CD3+, CD8+, and PD-1+ CD8+ T cells in the TIME.

      Figure 3.  Effect of the combinatorial therapy with CWQ and anti-PD-1 antibody on the tumor immune microenvironment in the mouse xenotransplantation model of CRC. The proportions of (A and D) CD3+ T cells, (B, E, F) CD8+ and CD4+ T cells, and (C and G) PD-1+ CD8+ T cells in the tumors from the four groups. Data are presented as the mean ± SD (n = 6). *P < 0.05 and **P < 0.01 vs the Control group, ##P < 0.01 vs the CWQ group

    • To observe the effect of CWQ on the intestinal mucosal barrier of mice, the colons of mice in the four groups were evaluated by H&E staining and immunohistochemical analysis. The colonic mucosa structure was intact in the Control and CWQ groups, and the intestinal villi were neatly arranged without any defects (Fig. 4A). However, in the anti-PD-1 antibody group, inflammatory cell infiltration, hyperemia, and edema, depletion of goblet cells, and colonic villi were sparse, with obvious rupture and atrophy. Interestingly, the colonic villi were atrophied but neatly arranged, but no villus defects or inflammatory changes were observed in the combination group. Thus, CWQ appeared to inhibit inflammation, restore the intestinal villus structure, and improve the intestinal mucosal barrier.

      Figure 4.  Effect of the combinatorial therapy with CWQ and anti-PD-1 antibody on the intestinal barrier in the mouse xenotransplantation model of CRC. (A) The histomorphology of the colonic mucosa after drug intervention in the four groups. 1. Inflammatory-cell infiltration; 2. Hyperemia and edema; 3. Sparse colonic villi; 4. Depleted goblet cells; 5. Ruptured colonic villi; and 6. Atrophied colonic villi. The expression of (B) Claudin, (C) Occludin, and (D) ZO-1 proteins in the colonic mucosa in the four groups after drug intervention

      As shown in Figs. 4B4D, the levels of Claudin, Occludin, and ZO-1 proteins almost did not decrease in the CWQ group compared with the Control group, but were reduced in the anti-PD-1 antibody group. The levels of these proteins in the anti-PD-1 antibody group were slightly lower than those in the Control and CWQ groups, but higher than those in the combination group. These findings suggested that PD-1 inhibitor therapy exerted adverse effects on the intestinal mucosal barrier and that these effects were suppressed by CWQ.

    • According to the results from gel electrophoresis and rarefaction curves, the gut microbiota data from the mouse fecal samples were sufficient for subsequent analysis (Supplementary Figs. 1A–1C). To prove the regulatory effect of CWQ on the gut microbiota, principal components analysis (PCA) was utilized to analyze the difference between the Control group and the other groups. The results demonstrated that the CWQ group shared a similar microbial community structure with the combination group, but clearly different from that of the Control group (Fig. 5A). Thus, CWQ changed the microbial community structure. Then, the gut bacterial composition of the four groups was analyzed by plotting Venn diagrams to show the number of taxa that were the same and unique in each group. There were 250 identical OTUs in the four groups, and the number of specific OTUs in the Control, CWQ, anti-PD-1 antibody, and combination groups were 16, 19, 15, and 23, respectively (Fig. 5B). Then, the diversity and abundance of the microbial communities were assessed by analyzing the alpha diversity. According to the Shannon and Simpson indices, the gut microbiota was significantly more diverse in the combination group than in the control group (Supplementary Fig. 1D). Furthermore, at the phylum level (Fig. 5C), the community composition histograms showed a reduced abundance of Desulfobacterota and Bacteroidota in the CWQ, anti-PD-1 antibody, and combination groups compared with the Control group. In contrast, the abundance of Firmicutes, Actinobacteria, and Verrucomicrobiota increased, especially in the combination group. Then, using a heatmap, the abundance of the bacterial genera was compared among the groups (Fig. 5D). We found that in addition to the obvious changes in the abundance of the above-mentioned bacteria, the abundance of other bacteria were also different among the four groups. For example, the abundance of Akkermansia and unclassified_f_Eggerthellaceae increased in the CWQ and the anti-PD-1 antibody groups, especially in the combination group. We also observed that the abundance of Aerococcus largely increased in the anti-PD-1 antibody group, and the abundance of Marvinbryantia decreased in the combination group, compared with the Control group. Finally, we performed high-dimensional class comparisons through linear discriminant analysis of effect size (LEfSe) and consequently found that Erysipelotrichaceae, Dubosiella, Verrucomicrobiota, Akkermansia, and g_unclassified_f_Eggerthellaceae increased in the combination group (Fig. 5E).

      Figure 5.  Effect of the combinatorial therapy with CWQ and anti-PD-1 antibody on the gut microbiota in the mouse xenotransplantation model of CRC. (A) Principal components analysis at the OTU level in the four groups. (B) The number of gut bacterial taxa at the OTU level per group. (C) The composition of the gut microbiota at the phylum level per group. (D) Heatmap showing the species abundance at the genus level per group. (E) LEfSe showing the differences in fecal microbial taxa for the four groups. Dot size is proportional to the abundance of the corresponding taxon

    • To explore the regulatory effect of the drug on the gut microbiota, we first analyzed the differentially abundant bacteria in the four groups using the Kruskal-Wallis H test bar plot. Lactobacillus, Dubosiella, Staphylococcus, Candidatus_Saccharimonas, Rikenellaceae_RC9_gut_group, Mavinbryantia, Bacteroides, and Akkermansia were the differentially abundant bacteria among the four groups (Fig.6A). Then, we used the Wilcoxon rank-sum test to identify the differentially abundant bacterial genera between the Control and CWQ groups. As shown in the bar plot in Fig. 6B, Lactobacillus and Dubosiella were significantly enriched in the CWQ group compared with the Control group. Compared with the Control group, the differentially abundant bacteria of Dubosiella, Akkermansia, and unclassified_f_Eggerthellaceae were riched, while Lactobacillus and Bacteroides were reduced in the combination group (Fig. 6C). We further investigated the relationship between the T-lymphocytes in the tumor microenvironment and the gut microbiota. Spearman’s correlation analysis was used to analyze the association between bacterial genera and CD3+, CD4+, CD8+, and CD8+ PD-1+ T cells. The results showed that CD4+ T cells were positively correlated with the abundance of Lactobacillus, but negatively correlated with that of Akkermansia. CD8+ PD-1+, CD8+, and CD3+ T cells were positively correlated with the abundance of Akkermansia and unclassified_f_Eggerthellaceae, but negatively correlated with that of Lactobacillus (Fig. 6D).

      Figure 6.  Differentially expressed bacteria in different groups and the relationship between the gut microbiota and the tumor-infiltrating T-lymphocytes. (A) Differentially expressed bacterial genera in the four groups. Differentially abundant bacterial genera in the mice treated with (B) CWQ, and (C) a combination of CWQ and anti-PD-1 antibody, compared with the Control group. (D) The relationship between the gut microbiota and the T-lymphocytes in tumor microenvironment

    Discussion
    • Many clinical trials have shown that PD-1 inhibitor therapy exhibit significant anti-tumor effect on dMMR/MSI-H CRC, but the results in pMMR/MSS CRC are disappointing [23]. In the 2016 annual meeting of the American Society of Clinical Oncology, a clinical study on the efficacy of PD-1 inhibitor therapy in CRC reported that 28 CRC patients with dMMR/MSI-H had a response rate of 50% and a disease control rate of 89%, whereas none of the 18 CRC patients with pMMR/MSS had a response [24]. Based on this observation, further research indicated that there were more TILs in dMMR/MSI-H CRC than in pMMR/MSS CRC [25-27]. Furthermore, 45% of dMMR/MSI-H CRC patients had higher immune scores (the immune score was determined by the density of CD3+ T cells and CD8+ T cells in tumors), in contrast to only 21% in pMMR/MSS patients [28] and the expression of PD-1 and PD-L1 protein significantly increased in dMMR/MSI-H CRC, compared with pMMR/MSS CRC (18% vs 2%, and 50% vs 13%, respectively) [29]. Therefore, it is generally believed that the anti-tumor effect of PD-1 inhibitor therapy on CRC are closely related to the TIME.

      The TIME plays a crucial role in the development of malignant tumors [30]. The specific killer lymphocytes in the tumor microenvironment are called TILs [31], which mainly consist of T, B, and NK cells, and their expression greatly increase after tumorigenesis. Most of TILs are CD3-positive and mainly comprise CD4+ and CD8+ T cells, among which CD8+ T cytotoxic T-lymphocytes can directly kill tumor cells [32].

      In the current study, we found the higher infiltration of CD8+ T cell and expression of PD-1 and PD-L1 proteins in dMMR/MSI-H CRC tumors than in pMMR/MSS CRC tumors. Thus, the tumor microenvironment of dMMR/MSI-H CRC, which has a better response to PD-1 inhibitor therapy than pMMR/MSS CRC, appears to be more immunocompetent than that in pMMR/MSS CRC [33]. Interestingly, we observed that the most of CD8+ and CD4+ T cells were located at the edges of pMMR/MSS CRC tumors (marginal infiltration) and did not infiltrate the center of the tumors, unlike those in the dMMR/MSI-H CRC tumors. Thus, tumors can escape from being recognized and are killed by immune cells by reducing the TILs. Accordingly, we proposed to find a way to increase the number of CD8+ T cells and the expression of PD-1 and PD-L1 proteins in tumor tissues, and increase the immunocompetence of the tumor microenvironment from “cold” to “hot”, ultimately allowing more pMMR/MSS CRC patients to benefit from PD-1 inhibitor therapy.

      As previously shown, CWQ improved host immune response, and thus we investigated whether CWQ enhanced the TILs. To this end, we established a MC38 cell xenograft tumor model for drug intervention. The results indicated that the tumor volume was significantly smaller in the combination group than that in the Control group. These findings showed that both the CWQ and the anti-PD-1 antibody groups exerted anti-tumor effect and showed synergism. Then we found that CWQ decreased the number of CD4+ T cells and significantly increased the number of CD8+ , CD3+ , and PD-1+ CD8+ T cells in tumors. Moreover, we assume the decrease in the number of CD4+ T cells is attributed to a decrease in the sub-population of regulatory T cells (Tregs). The PD-1+ CD8+ T cells, a type of CD8+ T cells expressing PD-1 protein, was strongly predictive for response in cancer patients treated with PD-1 blockade [34]. Therefore, we confirmed that CWQ enhanced the infiltration of CD3+, CD8+, and PD-1+ CD8+ T cells in tumor tissues, thereby increasing the immunocompetence of the TIME. However, the underlying mechanism needs to be elucidated.

      We first examined the changes in the expression of HMGB-1, EIF-α, and p-EIF-α proteins to demonstrate the presence of ICD. ICD elicited potent adaptive immune responses against tumor-associated antigens by exposing tumor-derived specific antigens to T cells, thereby generating an anticancer immune response [35]. However, we did not find any significant change in the expression of the above-mentioned proteins, and there was almost less ICD development. PD-L1, a kind of surface protein, is widely expressed in T cells, B cells, DCs and cancer cells, which binds to PD-1 to assists cancer cells in immune escape. Interestingly, recent studies have found that upregulating the expression of PD-L1 potein will turn cold tumors into hot tumors, which lead to better efficacy in immunotherapy [36]. We found that only PD-L1 protein was highly expressed in the combination group, whereas STAT3 protein was upregulated both in the CWQ and combination groups. Thus, we thought that additional factors regulated the expression of PD-L1 protein.

      The gut microbiota has been recognized to modulate host immunity. For instance, transplantation of the gut microbiota from patients with a good response to anti-PD-1 immunotherapy to germ-free mice increased the infiltration of CD8+ T cells and upregulated PD-L1 potein in the TIME [37]. Thus, we hypothesized that the upregulated expression of PD-L1 protein in the combination group, compared with the Control group, was due to a change in the gut microbiota. Additionally, the gut microbiota can recruit T cells to the tumor microenvironment in CRC by upregulating chemokines [38] and activate tumor-killing T-cell subsets [39]. Therefore, the gut microbiota of the mice in the four groups were characterized by 16s RNA gene sequencing to determine the microbiota changes that may affect the TIME.

      We found that Akkermansia, a strictly anaerobic commensal bacterium from the phylum Verrucomicrobia and typically closely associated with the protective mucous lining of the human intestine [40], increased in the CWQ, anti-PD-1 antibody and combination groups. Thus, we speculated that the increased abundance of Akkermansia in the combination group alleviated the inflammation and improved the intestinal mucosal barrier. A significantly higher level of Akkermansia showed a good response after PD-1 inhibitor therapy [41]. In this experiment, the combination group showed a higher level of Akkermansia with a smaller tumor volume, and the anti-tumor efficacy of PD-1 inhibitor therapy was positively correlated with the level of Akkermansia, consistent with current research. Additionally, Akkermansia was reported to decrease the percentage of Tregs among the total tumor-infiltrating CD4+ T cells [42]. In the current study, we also observed that the proportion of CD4+ T cells decreased in the combination group, which may be caused by Akkermansia. Meanwhile, the results from Spearman's correlation analysis showed that Akkermansia was positively correlated with the proportions of CD8+ and PD-1+ CD8+ T cells in CRC tumors. This conclusion is in line with results from other studies. For example, Akkermansia muciniphila-derived extracellular vesicles increased the number of GZMB+ CD8+ and IFN-γ+ CD8+ T cells in vitro [43]. We have reason to believe that this phenomenon of TIL changes in the TIME is currently related to the gut microbiota.

      We also found that CWQ and anti-PD-1 antibody alone or in combination, significantly decreased the abundance of Bacteroidota in the gut microbiota but significantly increased the abundance of Firmicutes, Actinobacteria, and Verrucomicrobiota. A recent study has reported that Bacteroidota are enriched in patients unresponsive to PD-1 inhibitor therapy, and bacteria from the Actinobacteria and Firmicutes phyla are associated with a favorable response [37, 44]. We speculate that decreasing the abundance of Bacteroidota and increasing the abundance of Firmicutes and Actinobacteria may elevate the response rate to PD-1 inhibitor therapy.

      The above-mentioned results indicate that CWQ alters the gut microbiota. It increases the abundance of beneficial bacteria that promote immunocompetence, while decreasing those associated with immunosuppression. Consequently, the immune response induced by PD-1 inhibitor therapy may augmented by CWQ.

    Conclusions
    • In this work, we first compare the TIME between pMMR/MSS and dMMR/MSI-H CRC patients and find that the poor anti-tumor effect of PD-1 inhibitor therapy may result from low infiltration of CD8+ T cells in tumor tissues. Then we demonstrate that CWQ increases the infiltration of CD3+ and CD8+ T cells in the TIME, and the combination of CWQ with anti-PD-1 antibody upregulates PD-L1 protein in the TIME and modifies some gut microbiome associated with TILs cells, such as Akkermansia. Thus, CWQ may enhance the anti-tumor effect of the PD-1 inhibitor therapy by modifying the gut microbiota to increasing the recruitment of TILs to the TIME (Fig.7).

      Figure 7.  Schematic diagram showing the mechanism by which CWQ enhances the anti-tumor effect of PD-1 inhibitor therapy. CWQ increases the tumor infiltration of CD8+ and PD-1+ CD8+ T cells and modifies the gut microbiota which may be associated with TILs, thereby enhancing the anti-tumor effect of PD-1 inhibitor therapy in CRC

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