Application of Blauria coccoides bacteria and metabolite UDP-galactose thereof in treatment of pancreatic cancer
By using Blautia coccoides and its metabolite UDP-galactose, combined with immune checkpoint inhibitors, the problem of immunosuppressive tumor microenvironment in pancreatic cancer treatment was solved, and effective treatment and survival rate for pancreatic cancer was achieved.
Patent Information
- Application Number
- CN202411842820.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-13
- Publication Date
- 2025-04-04
AI Technical Summary
The prior art is difficult to effectively treat pancreatic cancer, especially in improving the efficacy of immunotherapy, mainly due to the immunosuppressive tumor microenvironment in pancreatic tumors.
Blautia coccoides and its metabolite UDP-galactose, alone or in combination with immune checkpoint inhibitors (such as PD-1 inhibitors) are used to prepare drugs for the treatment of pancreatic cancer.
By reshaping the intestinal microbiota and its metabolite, Blautia coccoides and its metabolite UDP-galactose can effectively block and reverse the progress of pancreatic cancer, and cooperate with PD-1 monoclonal antibody to improve survival, providing a new therapeutic direction.
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Figure CN119745929A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to application of Blautia coccoides bacteria and its metabolite UDP-galactose in treating pancreatic cancer, belonging to the technical field of biomedicine. Background Art
[0002] Pancreatic cancer is a deadly and aggressive disease, among which pancreatic ductal adenocarcinoma (PDAC) is the main tumor type of pancreatic cancer, accounting for about 80%-90% (hereinafter referred to as pancreatic cancer). Most patients have progressed to the advanced stage when they are discovered, and the 5-year overall survival rate is only 9%. Pancreatic cancer is expected to become the third leading cause of cancer death in 2025. At present, the main treatment strategies for pancreatic cancer include surgery and chemotherapy. However, only 20% of patients are surgically resectable, and chemoradiotherapy is usually accompanied by a large number of adverse reactions and drug resistance. In recent years, the emergence of immune checkpoint inhibitors (ICIs) represented by PD-1 / PD-L1 inhibitors has marked a therapeutic renaissance in the field of tumors. However, immunotherapy has little effect on alleviating pancreatic cancer, which is mainly due to the presence of a highly immunosuppressive tumor microenvironment (TME) in pancreatic tumors, which is characterized by dense fibrotic stroma, immunosuppressive cell infiltration, including the most prominent tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), and a small number of CD8+T cells that kill cancer cells. These features suggest that strategies to shift the TME from an immunosuppressive to a more immune-activated state could halt pancreatic cancer progression and improve the efficacy of immunotherapy.
[0003] At present, a large number of studies have confirmed that the microbiota and its metabolites affect the occurrence, development and treatment of pancreatic cancer by mediating inflammation and regulating immune microcircles. For example, studies have shown that intestinal bacteria can induce innate and adaptive immunosuppression by activating Toll-like receptors, promoting the progression of PDAC. Studies have found that long-term survivors (LTS) of pancreatic cancer show unique tumor microbiome characteristics. Fecal transplant studies from humans to mice have shown that bacterial communities from LTS have anti-tumor effects. In addition to directly participating in the occurrence and development of cancer, the microbiota can also reshape the metabolism of the host and tumor, induce cell damage, and regulate tumor immunity. Trimethylamine oxide (TMAO) is a product converted by intestinal bacterial enzymes from choline in the diet. A recent study showed that TMAO can drive anti-tumor immunity to inhibit pancreatic cancer progression by inducing the immunostimulatory phenotype of macrophages and enhancing the function of effector T cells, and improve the immunotherapy efficacy of PD-1 monoclonal antibodies. In addition, tryptophan-derived microbial metabolites activate aromatic hydrocarbon receptors in tumor-associated macrophages to inhibit anti-tumor immunity in pancreatic cancer. Taken together, these results suggest that the gut microbiota and its metabolites can inhibit pancreatic cancer progression and improve its therapeutic response by altering the tumor immune microenvironment.
[0004] However, to date, no specific microbiota and metabolites have been used in the clinic to treat pancreatic cancer. Therefore, remodeling the intestinal microbiota and its metabolites may become a potential therapeutic target for pancreatic cancer, which is of great significance. Summary of the invention
[0005] The purpose of the present invention is: in view of the deficiencies of the prior art, the present invention provides the use of Blautia coccoides bacteria and its metabolite UDP-galactose in the treatment of pancreatic cancer, and provides an effective therapeutic drug for pancreatic cancer.
[0006] In order to achieve the above object, the present invention adopts the following technical solutions:
[0007] In a first aspect, the present invention provides the use of Blautia coccoides and / or its metabolite UDP-galactose, or Blautia coccoides and / or its metabolite UDP-galactose combined with an immune checkpoint inhibitor in the preparation of a medicament for treating pancreatic cancer.
[0008] Preferably, the drug comprises an active ingredient and a pharmaceutically acceptable excipient, wherein the active ingredient comprises Blautia coccoides and / or its metabolite UDP-galactose.
[0009] Preferably, the active ingredient also includes an immune checkpoint inhibitor.
[0010] Preferably, the immune checkpoint inhibitor is a PD-1 inhibitor and / or a PD-L1 inhibitor.
[0011] In a second aspect, the present invention provides a pharmaceutical composition, comprising an active ingredient and a pharmaceutically acceptable excipient, wherein the active ingredient comprises Blautia coccoides and / or its metabolite UDP-galactose.
[0012] Preferably, the immune checkpoint inhibitor is a PD-1 inhibitor and / or a PD-L1 inhibitor.
[0013] In a third aspect, the present invention provides a use of a product for detecting Blautia coccoides and / or its metabolite UDP-galactose in the preparation of a product for diagnosis, staging and / or prognosis of pancreatic cancer.
[0014] Compared with the prior art, the present invention has the following beneficial effects:
[0015] (1) The present invention first discovered that the abundance of Blautia coccoides and its metabolite UDP-galactose is closely related to the occurrence and development of pancreatic cancer; the present invention first confirmed the blocking and reversing effects of Blautia coccoides and its metabolite UDP-galactose on the progression of pancreatic cancer using an in situ pancreatic cancer model in mice;
[0016] (2) The present invention proposes and verifies for the first time that Blautia coccoides and its metabolite UDP-galactose can cooperate with PD-1 monoclonal antibody to treat pancreatic cancer and improve the survival rate; the present invention provides a new direction for the treatment of pancreatic cancer and has good application prospects and application value. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 The relationship between the abundance of Blautia coccoides and UDP-galactose and the progression of pancreatic cancer is shown; A is the absolute quantification of Blautia coccoides in the feces of pancreatic cancer patients with TNM stage I / II (n=29) and stage III / IV (n=27); B is the level of UDP-galactose in the serum of pancreatic cancer patients with TNM stage I / II (n=25) and stage III / IV (n=24); C is the spearman correlation analysis of Blautia coccoides abundance and CA199 level; D is the spearman correlation analysis of UDP-galactose content and CA199 level.
[0018] Figure 2 The results show that Blautia coccoides inhibits the development of pancreatic cancer; wherein A is the tumor size of orthotopic pancreatic cancer in mice three weeks after oral administration of Blautia coccoides (n=5); B is the tumor weight of orthotopic pancreatic cancer in mice three weeks after oral administration of Blautia coccoides (n=5).
[0019] Figure 3 The UDP-galactose content in the supernatant of Blautia coccoides incubated with PBS or D-galactose for 48 h (n=3), indicating that Blautia coccoides can produce UDP-galactose through substrate metabolism.
[0020] Figure 4 The results showed that UDP-galactose inhibits the development of pancreatic cancer; A is the tumor size of subcutaneous tumors in mice after oral gavage of 100 mg / kg, 150 mg / kg, and 200 mg / kg UDP-galactose for three weeks (n=4); B is the tumor volume of subcutaneous tumors in mice within three weeks after oral gavage of 100 mg / kg, 150 mg / kg, and 200 mg / kg UDP-galactose (n=4).
[0021] Figure 5 The results show that Blautia coccoides and UDP-galactose synergistically promote the PD-1 monoclonal antibody in the treatment of pancreatic cancer; wherein, A is the tumor weight measurement in mice with pancreatic cancer orthotopic tumors that received PD-1 monoclonal antibody, PD-1 monoclonal antibody combined with Blautia Coccoides or UDP-galactose (n=5); B is the Kaplan-Meier analysis of the survival of the three groups of mice (n=5). DETAILED DESCRIPTION
[0022] In order to make the present invention more clearly understood, preferred embodiments are described in detail below with reference to the accompanying drawings.
[0023] The experimental methods in the following examples without specifying specific conditions were carried out according to conventional methods and conditions, or selected according to the product instructions; the materials, reagents, etc. used were conventional commercially available products unless otherwise specified.
[0024] Previously, we collected feces and serum from 50 healthy controls and 50 patients with pathological diagnosis of pancreatic cancer, and performed metagenomic and targeted metabolomics sequencing, respectively. The results showed that the abundance of Blautia coccoides in pancreatic cancer patients was significantly lower than that in healthy controls. High-throughput targeted metabolomics showed that compared with normal controls, 53 metabolites in the serum of pancreatic cancer patients were reduced. Spearman correlation analysis was performed between these 53 metabolites and Blautia coccoides, and Metorigin data was used to predict whether these metabolites might be of bacterial origin. It was found that UDP-galactose (Uridinediphosphate galactose) was closely related to Blautia coccoides and showed a decrease in pancreatic cancer patients.
[0025] Therefore, the present invention aims to explore the therapeutic effect of Blautia coccoides and its metabolite UDP-galactose on pancreatic cancer.
[0026] Example
[0027] 1. Materials
[0028] 1.1 Clinical tissue specimens
[0029] The stool and blood samples used in the present invention were all from pancreatic cancer patients diagnosed by Zhongshan Hospital Affiliated to Fudan University. The present invention has been approved by the Ethics Committee of Zhongshan Hospital Affiliated to Fudan University, and all patients signed informed consent forms.
[0030] 1.2 Cells and Animals
[0031] The animal experiments used in the present invention followed the procedures approved by the Institutional Animal Care and Use Committee (IACUC) of Zhongshan Hospital of Fudan University. Male C57BL / 6J mice used in the experiments, aged 8 to 12 weeks, were purchased from Vital River Company (Shanghai, China).
[0032] The KPC cells used in the present invention were purchased from Shanghai Model Organisms Corporation (serial number: NM-YD04-TG01).
[0033] 1.3qRT-PCR Primers
[0034] The primers of the present invention were all synthesized by Shanghai Shenggong Biotechnology Co., Ltd.
[0035] Table 1 qRT-PCR primer sequence information
[0036] Gene Forward primer (5'-3') Reverse primer (3'-5') B. coccoides CGGTACCTGACTAAGAAGC AGTTTCATTCTTGCGAACG 16S TCCTACGGGAGGCAGCAGT GGACTACCAGGGTATCTA
[0037] 1.4 Instruments
[0038] Table 2 Experimental instrument information
[0039]
[0040]
[0041] 1.5 Reagents and consumables
[0042] Table 3 Reagents and consumables information
[0043]
[0044]
[0045] 2. Methods
[0046] 2.1 Mouse model construction
[0047] The present invention established an orthotopic pancreatic cancer model and a subcutaneous tumor model in mice. For the orthotopic tumor model, we injected 1×10 6 Pdx1-Cre, LSL-KRASG12D, LSL-Trp53R172H / + (KPC) cells were orthotopically injected into the pancreas of each mouse and mixed with PBS to form a 25 μL cell suspension. One week later, tumor growth was observed using IVIS in vivo imaging. Three weeks after modeling, mice were euthanized to evaluate tumor growth and immune microenvironment. For subcutaneous tumor models, 50 μL of 2×10 5A KPC cell suspension was subcutaneously injected into each mouse, and the length (L) and width (W) were measured by calipers, and the tumor volume was calculated as 0.5LW^2. Three weeks after modeling, the mice were euthanized to evaluate tumor growth and immune microenvironment.
[0048] 2.2 In vivo experiments in mice
[0049] In the oral gavage experiment, mice were gavaged with 1×10 9 The mice were treated with 100 / 150 / 200 mg / kg of UDP-galactose in 200 μl of PBS until the end of the study. The control mice were given the same volume of PBS.
[0050] For PD-1 monoclonal antibody treatment, mice were injected intraperitoneally with 200 μg of anti-PD-1 antibody three times a week until the end of the study. The control group was given the same volume of IgG1 isotype (IgG1 isotype control antibody).
[0051] 2.2 Cell culture
[0052] KPC cell line used DMEM medium supplemented with 10% fetal bovine serum and 100 U / ml penicillin and streptomycin antibiotics.
[0053] 2.3 Blautia coccoides culture
[0054] Blautia coccoides strains were routinely cultured in an anaerobic sterilized ATCC 272 medium (containing basic soy peptone supplemented with yeast extract, L-cysteine·HCl, heparin, and vitamin K1) at 37°C in an anaerobic chamber with an atmosphere of 10% H 2 , 10% CO 2 and 80% N 2 All manipulations with Blautia coccoides were performed in an anaerobic chamber, with media and reagents pre-deoxygenated for at least 48 h.
[0055] 2.4 Flow cytometry
[0056] Tumor tissue or spleen was removed and minced, and then the tissue was digested with type IV collagenase and DNase I. The digestion solution consisted of 1640 medium containing 2% fetal bovine serum, 0.5mg / ml type IV collagenase, and 200U / ml DNase I. 500 microliters of digestion solution was added for every 300 mg of tissue, and it was placed on a shaker at 37°C for digestion for 1-2 hours. The digestion was terminated with FACS buffer (containing 1% fetal bovine serum, 2M EDTA, 50mL PBS), and then filtered through a 70-micron mesh to collect the single-cell suspension for later use. The blocking solution was prepared by mixing CD16 / 32 antibody with FACS buffer at a ratio of 1:200 and incubated at room temperature for 10 minutes to block the Fc region of the antibody and its receptor on the cells. After washing the cells, incubate with specific flow antibodies and live / dead dye in the dark at 4°C for 30 minutes. To evaluate the cytokine profile of immune cells, T cells were stimulated with 100 ng / ml PMA, 1 μg / ml ionomycin, and 10 μg / ml Brefeldin A for 4 h at 37°C in the dark. After surface staining, 200 μl of fixation and permeabilization solution was added to each sample to fix and permeabilize the cells, incubated for 30 min at room temperature in the dark, and then stained with intracellular or nuclear fluorescent antibodies. Incubation was performed at room temperature for 30 min. After filtering through a 70 μm mesh, flow cytometric analysis was performed. Samples were analyzed on a BD Fortessa X20 flow cytometer.
[0057] 2.5 Metagenomic sequencing
[0058] Total DNA was extracted from various samples using the magnetic bead-based soil and feces genomic DNA extraction kit from Tiangen Biotechnology (Beijing) Co., Ltd. and analyzed by agarose gel electrophoresis and The quality of the DNA was checked by using a 2.0 fluorometer. The qualified DNA was sonicated into 350 bp fragments for Illumina library construction and Ultra TMDNA library preparation kit. The library was sequenced on the Illumina Novaseq 6000 platform, generating 150 bp paired-end reads. All bioinformatic analyses were performed by Shanghai Meiji Biotechnology Co., Ltd. The raw data were quality controlled using fastp, and potential host contamination was removed using BWA. Metagenomic assembly was performed using MEGAHIT, and contigs larger than 800 bp were retained. Gene prediction and abundance analysis were performed using Prodigal and CD-HIT software, and a non-redundant gene catalog with 95% identity and 90% coverage was generated. Clean reads were aligned to the non-redundant gene catalog using Bowtie2, and gene abundance (TPM) was calculated based on the number of reads and gene length. Representative sequences were selected from the non-redundant gene catalog and compared to the NCBI NR database using BLASTP (version 2.2.28+) with an e-value cutoff of 1e-5 for taxonomic annotation. For alignment against the Kyoto Encyclopedia of Genes and Genomes database (KEGG), BLASTP (version 2.2.28+) was used with an e-value cutoff of 1e-5.
[0059] 2.6 High-throughput targeted metabolome sequencing
[0060] To extract metabolites from the samples, 400 μL of cold methanol / acetonitrile (1:1, volume ratio) extraction solvent was added to remove proteins and extract metabolites, and then vortexed thoroughly to mix. For absolute quantification of metabolites, stock solutions of stable isotope internal standards were simultaneously added to the extraction solvent. The mixture was collected into a new centrifuge tube and centrifuged at 14,000 g for 20 min at 4 °C to collect the supernatant. The supernatant was dried in a vacuum centrifuge. For LC-MS analysis, the samples were re-dissolved in 100 μL of acetonitrile / water (1:1, volume ratio) solvent and centrifuged at 14,000 g for 15 min at 4 °C, and the supernatant was injected. The analysis was performed using UHPLC (1290 Infinity LC, Agilent Technologies) coupled to SCIEX QTRAP MS (6500+, Sciex) at Shanghai Applied Protein Technology Co., Ltd. Analytes were separated on HILIC (Waters UPLC BEH Amide column, 2.1 mm × 100 mm, 1.7 μm) and C18 column (Waters UPLC BEH 2.1 × 100 mm, 1.7 μm). For HILIC separation, the column temperature was set at 35°C; the injection volume was 2 μL. Mobile phase A: 90% H2O + 2M ammonium acetate + 10% acetonitrile, mobile phase B: 0.4% formic acid in acetonitrile. A gradient was then initiated at a flow rate of 300 μL / min (5% B at 0-1 min, 80% B at 3-4 min, 70% B at 6 min, 50% B at 10-15.5 min, 85% B at 15.6-23 min). For RPLC separation, the column temperature was set at 40°C and the injection volume was 2 μL. Mobile phase A: 5 mM ammonium acetate in water, mobile phase B: 99.5% acetonitrile. Then a gradient was started at a flow rate of 400 μl / min (5% B at 0 min, 60% B at 5 min, 100% B at 11-13 min, 5% B at 13.1-16 min). The samples were kept at 4°C during the entire analysis.
[0061] 6500+QTRAP (AB SCIEX) was performed in positive and negative polarity switching mode. ESI positive polarity source conditions were as follows: source temperature: 580°C; ion source gas 1 (GS1): 45; ion source gas 2 (GS2): 60; curtain gas (CUR): 35; ion spray voltage (IS): +4500V; ESI negative polarity source conditions were as follows: source temperature: 580°C; ion source gas 1 (GS1): 45; ion source gas 2 (GS2): 60; curtain gas (CUR): 35; ion spray voltage (IS): -4500V. MRM method was used for mass spectrometry quantitative data acquisition. MRM ion pairs are shown in the attached file. A polling quality control (QC) sample was set in the sample queue to evaluate the stability and repeatability of the system. Quantitative data were processed using MultiQuant or Analyst. QCs were processed together with biological samples. Metabolite coefficient of variation (CV) in QC was less than 30% indicating reproducible measurement.
[0062] After and normalization, the processed data was imported before being uploaded into SIMCA-P (version 14.1, Umetrics, Umea, Sweden), where it was subjected to multivariate data analysis, including Pareto-scaling principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The robustness of the model was assessed using 7-fold cross-validation and response permutation tests. The variable importance projection (VIP) value of each variable in the OPLS-DA model was calculated to indicate its contribution to the classification. Significance was determined using an unpaired Student's t-test. p < 0.05 was considered statistically significant.
[0063] 2.7 Fecal RNA extraction
[0064] 1) Take 20 mg of mouse colonic fecal tissue frozen at -80℃ on ice and transfer it to a 1.5 ml RNase-free centrifuge tube. Add 500 μl RNA easy solution and shake vigorously or pipette to fully lyse the sample.
[0065] 2) Add 2 / 5 volume of RNase-free ddH 2 O (use 200μl for every 500μl RNA-easy), mix by inverting, and let stand at room temperature for 5min. Centrifuge at 11,200rpm (12,000×g) for 15min at room temperature. Remove the centrifuge tube and transfer the upper aqueous phase to a new centrifuge tube. Add an equal volume of isopropanol, mix by inverting, and let stand at room temperature for 10min. Centrifuge at 11,200rpm (12,000×g) for 10min at room temperature and discard the supernatant. Add 500μl 75% ethanol (RNase-free ddHO). 2O), suspend the precipitate, and turn it upside down several times. Centrifuge at 9,100rpm (8,000×g) for 3min at room temperature and discard the supernatant. After the precipitate is dried, dissolve it in an appropriate amount of RNase-free ddH2O and quantify it using an ultra-micro spectrophotometer. The A260 / A280 ratio between 1.8-2.0 indicates that the RNA purity is qualified. Then store it in a -80℃ refrigerator for use.
[0066] 2.8 Reverse transcription
[0067] In this example, the reverse transcription experiment used the ABScript II cDNA First-Strand Synthesis Kit from Ibotek, and the specific composition was formulated as follows:
[0068] Table 4 Reverse transcription system composition
[0069]
[0070]
[0071] After the configuration is completed, place it in the gradient PCR instrument and set the reverse transcription program as follows:
[0072] Table 5 Reverse transcription program settings
[0073] temperature time 42℃ 60 minutes 80℃ 5 minutes 4℃ ∞
[0074] After reverse transcription, the cDNA samples were stored in a -80°C refrigerator for later use.
[0075] 2.9 Real-time fluorescence quantitative PCR
[0076] In this example, the real-time fluorescence quantitative PCR experiment was performed using Yeason Hieff Universal Blue qPCR SYBR Master Mix Kit, the specific composition is as follows:
[0077] Table 6 qRT-PCR system composition
[0078]
[0079] Each sample was set up with 3 technical replicates, and the system was prepared in a 96-well PCR microplate and tested in a fluorescent quantitative PCR instrument. The reaction procedure was as follows:
[0080] Table 7 qRT-PCR program settings
[0081]
[0082]
[0083] The sample used GAPDH as the internal reference, and the 2-ΔΔCt method was used to evaluate the expression level of mRNA. Where ΔCt = Ct (target mRNA) - Ct (internal reference), ΔΔCt = ΔCt n -ΔCt 1 (n is the sample number).
[0084] 3. Data Analysis
[0085] All data are expressed as mean ± standard error (SEM). Statistical analysis was performed using SPSS20.0 software. When comparing two groups of data, a normal distribution test was performed first, followed by the Student's t test. If normal distribution or homogeneity of variance was not satisfied, the Mann-Whitney U test was used to compare the two groups. When the experimental design involved comparisons of more than two groups, a normal distribution test was performed first, followed by analysis of variance (ANOVA) to compare differences between groups, and the least significant difference (LSD) test was used for multiple comparisons between pairs. If normal distribution or homogeneity of variance was not satisfied, the Kruskal-Wallis test was used to compare differences between groups, and the Hodges-Lehmann test was used for multiple comparisons between pairs. A p value of less than 0.05 was considered statistically significant. P values are indicated by *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001.
[0086] 4. Implementation plan and results
[0087] 4.1 Blautia coccoides and UDP-galactose abundance are associated with the occurrence and development of pancreatic cancer
[0088] To observe the relationship between Blautia coccoides and UDP-galactose and the progression of pancreatic cancer, we conducted quantitative analysis of Blautia coccoides and UDP-galactose in the feces and serum of 60 patients with pancreatic cancer at different stages. We found that the levels of Blautia coccoides and UDP-galactose were significantly higher in patients with TNM stage I / II than in patients with III / IV ( Figure 1 AB). Since CA199 is currently the main diagnostic and prognostic indicator for pancreatic cancer, we further analyzed the correlation between the abundance of Blautia coccoides and UDP-galactose and CA199 levels and found that both were significantly negatively correlated with CA199 ( Figure 1 CD). These results indicate that the abundance of Blautia coccoides and UDP-galactose decreases during the development and progression of pancreatic cancer.
[0089] 4.2 Blautia coccoides and its derived metabolite UDP-galactose effectively inhibit the progression of pancreatic cancer
[0090] To clarify the therapeutic effect of Blautia coccoides on pancreatic cancer, we used a mouse pancreatic orthotopic tumor model and administered 1×10 9 After three weeks of continuous intragastric administration, the tumors in the Blautia coccoides treatment group were significantly reduced compared with the control group ( Figure 2 ). To verify that UDP-galactose is a derivative metabolite of Blautia coccoides, we conducted an incubation experiment between Blautia coccoides and D-galactose, the substrate of UDP-galactose. The results showed that after the addition of D-galactose, the UDP-galactose content in the Blautia coccoides bacterial solution increased significantly ( Figure 3 ), indicating that UDP-galactose can be metabolized by Blautia coccoides. Next, we used the pancreatic cancer subcutaneous tumor experiment to explore the inhibitory effect of oral administration of different concentrations of UDP-galactose on pancreatic cancer and found that the inhibitory effect on pancreatic cancer was most significant at a concentration of 200 mg / kg ( Figure 4 ). This indicates that Blautia coccoides and its derived metabolite UDP-galactose can effectively inhibit the occurrence and development of pancreatic cancer.
[0091] 4.3 Blautia coccoides and its metabolite UDP-galactose synergistically promote the therapeutic efficacy of PD-1 monoclonal antibody in pancreatic cancer
[0092] Since pancreatic cancer is currently poorly sensitive to PD-1 monoclonal antibody treatment, we further explored whether Blautiacoccoides and its derived metabolite UDP-galactose can sensitize the efficacy of PD-1 monoclonal antibodies in pancreatic cancer. We used a mouse pancreatic orthotopic tumor model and gave oral gavage and PD-1 monoclonal antibody treatment on the day of tumor inoculation, both three times a week. After three weeks of treatment, we found that the effect of PD-1 monoclonal antibody alone on pancreatic cancer was minimal, while Blautia coccoides or UDP-galactose combined with PD-1 monoclonal antibody significantly sensitized the tumor inhibitory effect of PD-1 monoclonal antibody and increased the survival rate of mice ( Figure 5 ). This indicates that Blautia coccoides and UDP-galactose have a synergistic effect with PD-1 monoclonal antibody in pancreatic cancer.
[0093] The above description is only a preferred embodiment of the present invention and is not any formal or substantial limitation of the present invention. It should be pointed out that a person skilled in the art can make several improvements and supplements without departing from the present invention, and these improvements and supplements should also be regarded as the protection scope of the present invention.
Claims
1. Use of Blautia coccoides and / or its metabolite UDP-galactose, or Blautia coccoides and / or its metabolite UDP-galactose combined with immune checkpoint inhibitors in the preparation of a drug for the treatment of pancreatic cancer.
2. The use according to claim 1, characterized in that The medicine comprises an active ingredient and pharmaceutically acceptable excipients, wherein the active ingredient comprises Blautia coccoides bacteria and / or its metabolite UDP-galactose.
3. The use according to claim 1, characterized in that The active ingredients also include immune checkpoint inhibitors.
4. The use according to claim 3, characterized in that The immune checkpoint inhibitor is a PD-1 inhibitor and / or a PD-L1 inhibitor.
5. A pharmaceutical composition, characterized in that The pharmaceutical composition comprises an active ingredient and pharmaceutically acceptable excipients, wherein the active ingredient comprises Blautia coccoides bacteria and / or its metabolite UDP-galactose.
6. The pharmaceutical composition according to claim 5, characterized in that The immune checkpoint inhibitor is a PD-1 inhibitor and / or a PD-L1 inhibitor.
7. Use of a product for detecting Blautia coccoides and / or its metabolite UDP-galactose in the preparation of a product for diagnosis, staging and / or prognosis of pancreatic cancer.