Drug system for targeting tumor-associated macrophages as well as preparation method and application of drug system

Abstract

The invention relates to the technical field of pharmaceutical preparations, in particular to a drug system for targeting tumor-associated macrophages as well as a preparation method and application of the drug system. Bioinformatics screening finds that Dicer is closely related to M2 polarization and poor prognosis of tumor-related macrophages in tumor liver metastasis. In-vivo and in-vitro experiments find that the Dicer in the macrophages is knocked down, so that M2 type macrophages can be reprogrammed into M1 type macrophages, and the proliferation of colon cancer cells is inhibited. By constructing a Dicer1siRNA delivery system targeting TAMs and applying the Dicer1siRNA delivery system to CRLM mouse treatment, a result shows that through targeted regulation of Dicer expression in M2 type TAMs, a CRLM tumor immune microenvironment can be regulated, an immunosuppression state can be improved, tumor progression can be finally inhibited, and a new thought is provided for CRLM treatment in the future.

Description

Technical Field

[0001] The present invention relates to the technical field of pharmaceutical preparations, and in particular to a pharmaceutical system targeting tumor-associated macrophages, and a preparation method and application thereof. Background Art

[0002] Metastasis is the main cause of death from colorectal cancer (CRC), among which liver metastasis (CRLM) is the most common. Despite the rapid development of chemotherapy, molecular targeted therapy and immunotherapy, CRLM patients often respond poorly to the above treatments due to their special liver microenvironment and immune tolerance characteristics, and their survival prognosis is extremely poor. In recent years, more and more studies have shown that tumor-associated macrophages (TAMs) play a key role in the occurrence and development, distant metastasis and treatment response of CRC. Therefore, reshaping the tumor immune microenvironment by targeting and regulating TAMs may be a potential new strategy to inhibit tumor progression and improve disease prognosis.

[0003] Although small molecule drugs and monoclonal antibodies targeting TAMs have achieved good therapeutic effects in various tumor animal models, the clinical application effect is not good. In addition, factors such as unclear TAMs-specific targets in CRLM, poor drug targeting, and the non-drugability of potential targets further limit the clinical application of related drugs in CRLM. Compared with traditional small molecule and antibody drugs, nucleic acid drugs have the advantages of simple design, short R&D cycle, strong targeting specificity, wide therapeutic field and long-term effect. They have received more and more attention in the treatment of genetic diseases, tumors, viral infections and other diseases. However, the problem of nucleic acid delivery has always been one of the bottlenecks of nucleic acid drug therapy. Although non-viral nucleic acid drug carriers represented by lipid nanoparticles (LNPs) have been widely studied, most LNPs are taken up by hepatocytes in vivo and lack extrahepatic tissue and cell selectivity. Summary of the invention

[0004] In view of this, the present invention provides a drug system targeting tumor-associated macrophages, and a preparation method and application thereof. The present invention combined Bulk transcriptome and single-cell sequencing analysis to find that Dicer is closely related to the polarization of tumor-associated macrophages M2 and poor prognosis in tumor liver metastasis. In vivo and in vitro experiments found that knocking down Dicer in macrophages reprogrammed M2 macrophages to M1, inhibiting the proliferation of colon cancer cells. By constructing a Dicer1 siRNA delivery system targeting TAMs and applying it to the treatment of CRLM mice, it was found that targeted regulation of Dicer expression in M2 TAMs can regulate the CRLM tumor immune microenvironment, improve the immunosuppressive state, and ultimately inhibit tumor progression, providing a new idea for the future treatment of CRLM.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

[0006] The present invention provides the use of Dicer as a marker in the preparation of products for diagnosing, preventing and / or treating tumor liver metastasis.

[0007] The present invention also provides the use of Dicer as a target in the preparation of products for preventing and / or treating tumor liver metastasis.

[0008] In some specific embodiments of the present invention, the tumor comprises colorectal cancer, breast cancer, bile duct cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, pancreatic cancer, prostate cancer or sarcoma.

[0009] The present invention also provides an application of knocking down Dicer in promoting the reprogramming of M2 macrophages into M1 macrophages.

[0010] The present invention also provides siRNA for knocking down Dicer expression, including:

[0011] The sense strand has the nucleotide sequence shown in SEQ ID NO: 30; the antisense strand has the nucleotide sequence shown in SEQ ID NO: 31; or

[0012] The sense strand has the nucleotide sequence shown in SEQ ID NO:32; the antisense strand has the nucleotide sequence shown in SEQ ID NO:33; or

[0013] The sense strand has the nucleotide sequence shown in SEQ ID NO:34; the antisense strand has the nucleotide sequence shown in SEQ ID NO:35.

[0014] The present invention also provides a drug system targeting M2 macrophages, including LNP modified with M2pep and encapsulating siRNA to obtain the drug system siRNA@M2pep-LNP.

[0015] In some specific embodiments of the present invention, the siRNA comprises:

[0016] The sense strand has the nucleotide sequence shown in SEQ ID NO: 30; the antisense strand has the nucleotide sequence shown in SEQ ID NO: 31; or

[0017] The sense strand has the nucleotide sequence shown in SEQ ID NO:32; the antisense strand has the nucleotide sequence shown in SEQ ID NO:33; or

[0018] The sense strand has the nucleotide sequence shown in SEQ ID NO:34; the antisense strand has the nucleotide sequence shown in SEQ ID NO:35.

[0019] The present invention also provides a method for preparing the drug system, comprising the following steps:

[0020] Step 1, dissolving Dlin-MC3-DMA, DSPC, Cholesterol, DMG-PEG2000, and DSPE-PEG2000-M2pep in anhydrous ethanol solution to obtain a lipid solution of Dlin-MC3-DMA containing M2pep;

[0021] Dissolve siRNA in sodium citrate buffer to obtain siRNA buffer;

[0022] Step 2: Mix the lipid solution and the siRNA buffer solution, and allow the lipids to self-assemble to form the drug system siRNA@M2pep-LNP encapsulating siRNA.

[0023] In some specific embodiments of the present invention, the mass ratio of the siRNA to the Dlin-MC3-DMA includes (2.5-30) μg:1 mg; the molar ratio of the DSPE-PEG2000-M2pep to the DMG-PEG2000 includes (1:1)-(1.5:0.5).

[0024] In some specific embodiments of the present invention, the mass ratio of the siRNA to the Dlin-MC3-DMA comprises 10 μg:1 mg.

[0025] In some specific embodiments of the present invention, the molar ratio of the DSPE-PEG2000-M2pep to the DMG-PEG2000 is 1:1.

[0026] In some specific embodiments of the present invention, the concentration of the sodium citrate buffer is 20 mM and the pH value is 4.

[0027] The present invention also provides the use of any of the following in the preparation of a drug for preventing and / or treating tumor liver metastasis:

[0028] (I), the siRNA; and / or

[0029] (II), the drug system; and / or

[0030] (III) The drug system obtained by the preparation method.

[0031] In some specific embodiments of the present invention, the application comprises:

[0032] (I) promoting the reprogramming of M2 macrophages into M1 macrophages; and / or

[0033] (II), up-regulating the expression of IL-1β, IL-6, and IL-12; and / or

[0034] (III), down-regulating the expression of IL-10, TGF-β1, and Mgl1; and / or

[0035] (IV) Increase CD8 in the tumor microenvironment + T cell count; and / or

[0036] (V) Inhibit the proliferation of colon cancer cell CT26.

[0037] The present invention provides the following beneficial effects:

[0038] (1) TAMs play a key role in the development and metastasis of CRC, but the key regulatory molecules of their functions and phenotypes in CRLM are still not very clear. This study used bioinformatics analysis, screening, and in vivo and in vitro experimental verification to show that Dicer is an important molecule regulating the M2 polarization of TAMs in CRLM, and knocking down Dicer expression can reprogram M2 macrophages to M1.

[0039] (2) Although the development of drugs targeting TAMs is becoming a hot area in tumor immunotherapy, how to effectively, safely and targetedly regulate key molecules in TAMs has always been a research focus and difficulty. This study successfully constructed an in vivo siRNA delivery system (M2pep-LNP) targeting M2 TAMs based on a peptide modification method. The use of this delivery system to encapsulate siDicer1 can achieve the in vivo reprogramming of M2 TAMs, reshape the tumor suppressive immune microenvironment, and thereby inhibit the progression of CRLM. This result lays a theoretical foundation for the future treatment of CRLM using Dicer in M2 TAMs as a target. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0041] Figure 1 Figure 2 shows the relationship between macrophage M2 polarization level and tumor liver metastasis explored by combining bulk transcriptome and single-cell sequencing; A shows that the M2 polarization level of macrophages in pan-cancer patient liver metastasis samples (LM) (n=179) is higher than that in non-liver metastasis samples (Non-LM) (n=143); B shows that macrophages are divided into 5 subgroups (C1-C5) by annotating and classifying single-cell samples of tumor tissues of CRLM patients (n=5818); C shows the comparison of M2 polarization levels of different macrophage subgroups; D shows the schematic diagram of the distribution of M2 polarization states of different macrophage subgroups; E shows genes related to macrophage M2 polarization in the single-cell dataset of CRLM patients (GSE164522); F shows genes related to macrophage M2 polarization in the bulk sequencing dataset of tumor tissues of pan-cancer patient liver metastasis (MET-500); LM: liver metastasis, Non-LM: non-liver metastasis, Mac: macrophage, scRNA: single-cell RNA, *** P < 0.001;

[0042] Figure 2 Figure 2 shows the exploration of macrophage M2 polarization genes associated with CRC prognosis; A shows a Venn diagram showing the intersection of macrophage M2 polarization-related genes in the pan-cancer liver metastasis sample Bulk transcriptome sequencing dataset (MET-500) and the CRLM patient single-cell sequencing dataset (GSE164522); BC shows the use of meta-analysis to explore the correlation between 13 genes and CRC recurrence survival prognosis in 6 cohorts (GSE39582, GSE14333, GSE41258, GSE72970, TCGA-COAD, TCGA-READ); Mac / Macro: macrophage;

[0043] Figure 3 DICER1 is highly expressed in M2 macrophages in tumors and affects CRC prognosis; A shows the expression level of DICER1 among different immune cells in the single-cell sequencing dataset of CRLM patients (GSE164522); B shows the expression of DICER1 in different macrophage populations (C1-C5) in the single-cell dataset of CRLM patients; C shows the correlation between DICER1 expression and macrophage M2 polarization in the bulk transcriptome of pan-cancer patients with liver metastasis (MET-500); DE shows the relationship between DICER1 expression and CRC recurrence and survival in the bulk transcriptome sequencing datasets of different CRC patients (GSE72970 and GSE14333); CD4Tconv: CD4 helper T cells; Treg: regulatory T cells;

[0044] Figure 4 Figure 4 shows the relationship between Dicer expression and TAMs phenotype in CRLM; A shows the phenotype and distribution of TAMs in liver metastasis tissues of CRLM patients; left: typical image of tissue immunofluorescence staining; right: comparison of the number of M1 and M2 TAMs in tumor tissues, scale: 25μm; BC shows the difference in Dicer expression in TAMs with different polarization states in tumor tissues; B shows a typical immunofluorescence schematic diagram; C shows a statistical analysis of the expression levels of Dicer in the two TAMs; scale: 50μm; D shows the phenotype and distribution of TAMs in liver metastasis tissues of CRLM mouse models; left: typical image of immunofluorescence staining; right: comparison of the number of M1 and M2 TAMs in tumor tissues; EF shows the expression of Dicer in TAMs with different polarization states in tumor tissues; E shows a typical immunofluorescence schematic diagram; F shows a statistical analysis of the expression levels of Dicer in the two TAMs; scale: 50μm; M1 TAMs are CD86 + Cells (human / mouse), M2 TAMs are CD163 + Cells (human) or CD206 + Cells (mouse); dotted line is the boundary between tumor and normal tissue, red ★ is the tumor area, blue ★ is the normal tissue area; TAMs: tumor-associated macrophages; Student's ttest was used to compare the two groups, and the data are expressed as Mean±SD; * P < 0.05; ** P < 0.01; *** P < 0.001;

[0045] Figure 5 Flow cytometry was used to verify the purity of BMDM induced by L929 in vitro; CD11b was detected after bone marrow cells were induced in complete medium containing 30% L929 supernatant for 7 days + F4 / 80 + Cell ratio;

[0046] Figure 6 Figure 4 shows the relationship between Dicer expression and macrophage phenotype; macrophages (RAW264.7 and BMDM) were induced into M1 and M2 types by LPS and IL-4, respectively; qPCR was used to detect the expression levels of Dicer1, IL-12 and IL-10 mRNA in macrophages with different polarization states (A: RAW264.7; B: BMDM); Western blotting was used to analyze the expression level of Dicer protein in macrophages with different polarization states (C); ANOVA was used for statistical analysis, and the results were corrected by Tukey, and the data were expressed as Mean±SD; compared with M0 macrophages (PBS group), * P<0.05, **P<0.01, *** P < 0.001;

[0047] Figure 7 Figure 2 shows that knocking down Dicer affects macrophage proliferation; lentivirus was used to construct RAW264.7 stable cell lines (Dicer-KD1 and Dicer-KD2) with Dicer knockdown, A shows the proliferation of Dicer-KD RAW264.7 cells detected by CCK-8; B shows the expression level of apoptosis-related protein cleaved caspase-3 in Dicer-KD RAW264.7 by Western blotting; C shows the apoptosis of RAW264.7 cells with Dicer knockdown by flow cytometry; D shows the statistical analysis of the proportions of different cell cycles; E shows the typical flow cytometric graphs of different cell cycles; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; compared with the control (Vector), * P<0.05, ** P<0.01, *** P < 0.001;

[0048] Figure 8 The protein expression levels of related factors in Dicer-knocked macrophages were detected by Western blotting. Macrophages were induced into M2 macrophages after 24 hours of IL-4 stimulation. A shows the protein expression levels of IL-10 and IL-1β in Dicer-knocked RAW264.7 cells. B shows the protein expression levels of IL-10 and IL-1β in Dicer-knocked BMDM cells by Western blotting.

[0049] Fig. 9 The mRNA expression levels of macrophage-related factors detected by qPCR were shown; after macrophages were stimulated with IL-4 for 24 hours and induced into M2 macrophages, the mRNA expression levels of macrophage-related cytokines detected by qPCR were detected by Dicer knockdown (A: RAW264.7, B: BMDM); multiple t-tests were used for statistical analysis, and the results were corrected by Bonferroni, and the data were expressed as Mean±SD; compared with the control, * P<0.05, ** P<0.01, *** P < 0.001;

[0050] Fig.10Figure 2 shows the flow cytometry analysis of the levels of surface markers of macrophages with Dicer knockdown; after macrophages were stimulated with IL-4 for 24 hours, the expression of macrophage-related markers CD206 and CD86 were detected by flow cytometry; AB shows the flow cytometry analysis of the expression of surface markers of RAW264.7 cells with Dicer knockdown; A shows the typical flow cytogram of Vector and Dicer-KD groups; B shows the statistical analysis of CD206 and CD86 positive cells; CD shows the flow cytometry analysis of the expression of surface markers of BMDM cells with Dicer knockdown; C shows the typical flow cytogram of siNC and siDicer1 groups; D shows the statistical analysis of CD206 and CD86 positive cells; multiple t-tests were used for statistical analysis, the results were corrected by Bonferroni, and the data were expressed as Mean±SD; compared with the control (Vector), * P<0.05, ** P < 0.01;

[0051] Fig.11 The results show that Dicer-KD RAW264.7 inhibits the proliferation of CT26 cells; after Vector and Dicer-KD RAW264.7 were stimulated with IL-4 for 24 hours, they were added to the upper chamber of the transwell and co-cultured with CT26 cells. After 48 hours, CCK-8 was used to detect the proliferation of CT26 cells at 2h (D0), 24h (D1), 48h (D2), and 72h (D3); A shows the co-culture pattern; B shows the proliferation of CT26 cells at different time points; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; *** P < 0.001;

[0052] Fig.12 Figure 4 shows that Dicer-KD RAW264.7 inhibits the growth of CT26 subcutaneous tumors. After 24 hours of stimulation with IL-4, Vector and Dicer-KD RAW264.7 cells were mixed with CT26 cells and co-injected subcutaneously. The size of the subcutaneous tumor was observed every 3 days (A). When the tumor grew to the observation endpoint, the mice were killed and the tumors were photographed (B) and weighed (C) (n=5). D shows typical histochemical images of Ki67 and CD206 in subcutaneous tumor tissues; scale 50μm; EF shows quantitative analysis of Ki67 and CD206 immunohistochemical staining using ImageJ (n=3); student's t test was used for statistical analysis, and the data are expressed as Mean±SD. * P < 0.05;

[0053] Fig.13Figure 1 shows the optimization of siRNA@LNP preparation conditions; different RNA / MC3 mass ratios (μg / mg) were used to prepare LNP; DLS analysis of the particle size (A), PDI (B) and potential (C) of different LNPs; data are expressed as Mean±SD;

[0054] Fig.14 The optimized preparation conditions of siRNA@M2pep-LNP were shown; siRNA@M2pep-LNP was prepared with different RNA / MC3 mass ratios (μg / mg); DLS was used to analyze the particle size (A), PDI (B) and potential (C) of different M2pep-LNPs; the data were expressed as Mean±SD;

[0055] Fig.15 The results show the uptake of different M2pep-LNPs by M2 BMDM; three different DiI-labeled M2pep-LNPs were prepared according to the molar ratio of DSPE-PEG2000-M2pep / DMG-PEG2000, which were defined as M2pep-LNP1, M2pep-LNP2 and M2pep-LNP3 respectively; IL-4 was added after BMDM was successfully induced, and DiI@M2pep-LNP was added and incubated for 1 hour after 24 hours of stimulation, and the uptake difference of different M2pep-LNPs by M2 BMDM was observed under an inverted fluorescence microscope; A shows a typical fluorescence image; scale: 50μm; B shows the comparison of the average fluorescence intensity of DiI between different groups; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; * P<0.05, ** P<0.01, *** P < 0.001;

[0056] Fig.16 Figure 2 shows the characterization and stability of nanoparticles; A shows the morphology of nanoparticles observed by electron microscopy and the particle size distribution measured by DLS; scale: 100 nm; BD shows the changes in particle size (B), PDI (C) and potential (D) of nanoparticles under 4°C storage conditions; data are expressed as Mean±SD;

[0057] Fig.17 The uptake of nanoparticles by BMDM was observed by fluorescence microscopy; LPS and IL-4 were used to induce BMDM into M1 and M2 types, respectively, and then DiI-labeled LNP and M2pep-LNP were added and incubated for 1 hour; the difference in the uptake of two nanoparticles by BMDM in different polarization states was observed by inverted fluorescence microscopy; A shows a typical fluorescence image, scale: 50μm; B shows the comparison of the average fluorescence intensity of DiI in different groups; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; ***P<0.001; IntDen: total fluorescence intensity;

[0058] Fig.18 The uptake of nanoparticles by RAW264.7 was observed by fluorescence microscopy; LPS and IL-4 were used to induce RAW264.7 to M1 and M2 types, respectively, and then DiI-labeled LNP and M2pep-LNP were added and incubated for 1 hour; the uptake ability of RAW264.7 in different polarization states to the two nanoparticles was observed by inverted fluorescence microscopy; A shows a typical fluorescence image, scale: 50μm; B shows the comparison of the average fluorescence intensity of DiI in different groups; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; ** P<0.01; IntDen: total fluorescence intensity;

[0059] Fig.19 Figure 2 shows the observation of nanoparticle uptake by RAW264.7 by flow cytometry; LPS and IL-4 were used to induce RAW264.7 to M1 and M2 types, respectively, and then DiI-labeled LNP and M2pep-LNP were added and incubated for 1 hour; flow cytometry was used to observe the difference in the uptake ability of RAW264.7 in different polarization states for the two nanoparticles; A shows a typical flow cytometry image; B shows the analysis of the average fluorescence intensity of DiI in different groups; C shows the statistical analysis using ANOVA, the results were corrected by Tukey, and the data were expressed as Mean±SD; *** P<0.001; MFI: mean fluorescence intensity;

[0060] Fig. 20 The figure shows the flow cytometry detection of the uptake of different nanoparticles by M2 TAMs and spleen macrophages in vitro of CRLM mice; the CRLM mouse model was established, liver metastases and spleen were isolated, and single cell suspensions were prepared respectively, and then co-incubated with DiD-labeled LNP and M2pep-LNP; flow cytometry was used to observe the difference in the uptake of the two nanoparticles by different cells; A shows the typical flow cytometric images and statistical analysis of the DiD fluorescence intensity of different nanoparticles in M2 TAMs; B shows the typical flow cytometric images and statistical analysis of the DiD fluorescence intensity of different nanoparticles in M2 spleen macrophages; the student's t test was used for statistical analysis, and the data were expressed as Mean±SD; * P < 0.05;

[0061] Fig.21The ability of different nanoparticles to deliver siRNA to BMDM was observed by fluorescence microscopy; BMDM was induced to M1 and M2 by LPS and IL-4, respectively, and then different nanoparticles loaded with FAM-Si were added for co-culture to observe the expression of FAM among BMDM in each group; A shows a typical fluorescence image, scale: 50μm; B shows the analysis of the mean fluorescence intensity of FAM; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; ** P<0.01; IntDen: total fluorescence intensity;

[0062] Fig. 22 The flow cytometry analysis of the ability of different nanoparticles to deliver siRNA to BMDM was shown; BMDM were induced to M1 and M2 types by LPS and IL-4, respectively, and then different nanoparticles loaded with FAM-Si were added for co-culture, and the FAM expression between BMDM in each group was analyzed; AB shows the flow cytometric graphs of FAM fluorescence intensity; C shows the comparison of the mean fluorescence intensity of FAM; ANOVA was used for statistical analysis, and the results were corrected by Tukey, and the data were expressed as Mean±SD; *** P<0.001; MFI: mean fluorescence intensity;

[0063] Fig.23 Figure 2 shows the flow cytometry detection of the ability of different nanoparticles to deliver siRNA to fibroblasts and colon cancer cells; different nanoparticles loaded with FAM-Si were co-incubated with fibroblasts (3T3) and colon cancer cells (CT26), and the FAM expression between each group of cells was observed; AB shows the typical flow cytometric graphs and statistical analysis of the FAM fluorescence intensity in 3T3 cells transfected with different nanoparticles; CD shows the typical flow cytometric graphs and statistical analysis of the FAM fluorescence intensity in CT26 cells transfected with different nanoparticles; the student's t test was used for statistical analysis, and the data were expressed as Mean±SD; * P<0.05; MFI: mean fluorescence intensity;

[0064] Fig.24 The organ distribution characteristics of nanoparticles in CRLM mice were detected by the small animal in vivo optical imaging system. A CRLM mouse model was established, and DiR-labeled LNP and M2pep-LNP were injected into the tail vein. The average fluorescence intensity of the liver area of ​​mice at different time points [(p / s / cm 2 / sr) / (μW / cm 2 )]; A shows the distribution of nanoparticles in the liver of mice; B shows the comparison of the average fluorescence intensity of DiR in the liver of mice; multiple t-tests were used for statistical analysis, the results were corrected by Bonferroni, and the data were expressed as Mean±SD; * P < 0.05;

[0065] Fig.25 The distribution characteristics of nanoparticles in the isolated organs of CRLM mice were detected by the small animal in vivo optical imaging system (8 hours); the CRLM mouse model was established, and DiR-labeled LNP and M2pep-LNP were injected through the tail vein to observe the average fluorescence intensity of each isolated organ of the mouse at the 8-hour time point [(p / s / cm 2 / sr) / (μW / cm 2 )]; A shows the comparison of the average fluorescence intensity of DiR in each organ; B shows the typical image of the distribution of DiR-labeled nanoparticles in each organ (upper left: spleen; lower left: heart; center: liver; upper right: kidney; lower right: lung); multiple t-tests were used for statistical analysis, and the results were corrected by Bonferroni, and the data were expressed as Mean±SD. * P < 0.05;

[0066] Fig.26 The distribution characteristics of nanoparticles in the isolated organs of CRLM mice were detected by the small animal in vivo optical imaging system (12 hours); the CRLM mouse model was established, and DiR-labeled LNP and M2pep-LNP were injected through the tail vein to observe the average fluorescence intensity of each isolated organ of the mouse at the 24-hour time point [(p / s / cm 2 / sr) / (μW / cm 2 )]; A shows the comparison of the average fluorescence intensity of DiR in each organ; B shows a typical image of the distribution of DiR-labeled nanoparticles (upper left: spleen; lower left: heart; center: liver; upper right: kidney; lower right: lung); multiple t-tests were used for statistical analysis, and the results were corrected by Bonferroni, and the data were expressed as Mean±SD. * P < 0.05;

[0067] Fig. 27 The distribution characteristics of nanoparticles in the organs of unmodeled mice were detected by the in vivo optical imaging system of small animals. DiR-labeled LNP and M2pep-LNP were injected into the tail vein to observe the average fluorescence intensity of the mouse liver at different time points [(p / s / cm 2 / sr) / (μW / cm 2 )]; mice were killed 24 hours later, and the average fluorescence intensity of DiR on each isolated organ was detected; A shows the distribution image of nanoparticles in the liver area of ​​mice; B shows the comparison of the average fluorescence intensity of DiR in the liver area of ​​mice; C shows the comparison of the average fluorescence intensity of DiR in each isolated organ; D shows a typical image of the distribution of DiR-labeled nanoparticles in isolated organs (upper left: spleen; lower left: heart; center: liver; upper right: kidney; lower right: lung); multiple t-tests were used for statistical analysis, and the results were corrected by Bonferroni, and the data were expressed as Mean±SD;

[0068] Fig.28 The results showed that different nanoparticles targeted M2 TAMs in CRLM lesions. A CRLM mouse model was prepared, and Cy3-Si-loaded LNPs and M2pep-LNPs were injected via the tail vein. Six hours later, Cy3 + Cells were analyzed; A shows flow cytometry analysis of Cy3 + Cell ratio; multiple t-test was used for statistical analysis, and the results were corrected by Bonferroni; B shows the difference between different types of Cy3 + Typical flow cytometry of cells; C shows a typical fluorescence image of Cy3-Si expression in liver metastasis TAMs by immunofluorescence analysis; scale bar: 20 μm; D shows the Cy3 + Statistical analysis of TAMs: Student's t test was used for statistical analysis, and the data were expressed as Mean ± SD. * P < 0.05;

[0069] Fig.29 The figure shows the effect of siDicer1 nanoparticles on M2 BMDM reprogramming; A shows qPCR detection of Dicer1, IL-12 and IL-10 mRNA expression levels; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; B shows Western blotting to detect Dicer, IL-10 and IL-1β expression levels; * P<0.05, ** P<0.01, *** P < 0.001;

[0070] Fig.30 Figure 2 shows the therapeutic effect of siDicer1 nanoparticles on CRLM; wherein, A shows a schematic diagram of the time points of modeling, drug administration and in vivo optical imaging of small animals; B shows the changes in tumors of CRLM mice during treatment; CD shows the comparison of tumor growth in different treatment groups (4 mice in each group of siNC@LNP and siNC@M2pep-LNP, 7 mice in each group of siDicer1@LNP and siDicer1@M2pep-LNP); E shows the comparison of liver weight / body weight of mice in different treatment groups; FG shows HE staining of the liver of mice in different treatment groups, and ImageJ software analysis of the percentage of liver area occupied by tumors (F) (4 mice in each group) and typical HE staining images of each group (G), scale: 1 mm; H shows the survival curve analysis of mice in different treatment groups (6 mice in each group); I shows the expression levels of Dicer and IL-10 in liver metastasis tissues of mice in different treatment groups (3 mice in each group); multiple t-tests were used for statistical analysis, and the results were corrected by Bonferroni, and the data were expressed as Mean±SD; * P<0.05,** P<0.01, *** P < 0.001;

[0071] Fig.31 Shows the gating strategy for myeloid cells in mouse liver metastasis tissue;

[0072] Fig.32 The gating strategy of lymphocytes in liver metastasis tissue of mice is shown;

[0073] Fig.33 The effect of siDicer1 nanoparticles on the immune microenvironment of liver metastases in CRLM mice was shown; flow cytometry was used to analyze the number of various immune cells in the tumor immune microenvironment; ANOVA was used for statistical analysis, and the results were corrected by Tukey, and the data were expressed as Mean±SD; * P<0.05, ** P<0.01, *** P < 0.001;

[0074] Fig.34 The effect of siDicer1 nanoparticles on the immune microenvironment of the spleen in CRLM mice was shown; flow cytometry was used to analyze the proportions of various immune cells in the spleen; ANOVA was used for statistical analysis, and the results were corrected by Tukey, and the data were expressed as Mean±SD; * P<0.05, ** P<0.01, *** P < 0.001;

[0075] Fig.35 Figure 2 shows immunofluorescence staining of liver metastasis tissues in CRLM mice treated with siDicer1 nanoparticles; A shows CD8 + T cells, CD86 + M1 TAMs and CD206 + Representative images of immunofluorescence staining of M2 TAMs in liver metastasis tissues of mice in each group; Scale bar: 50 μm; B shows the statistical analysis of immune cells in liver metastasis tissues of mice in each group; ANOVA was used for statistical analysis, and the results were corrected by Tukey, and the data were expressed as Mean±SD; * P<0.05, ** P<0.01, *** P < 0.001;

[0076] Fig.36The figure shows that macrophage scavengers weaken the therapeutic effect of siDicer1 nanoparticles on CRLM; A shows a schematic diagram of the time points of modeling, drug administration and in vivo optical imaging of small animals; B shows the tumor changes of CRLM mice during the treatment process; C shows the comparison of tumor growth in different treatment groups (3 mice in the PBS+siNC@M2pep-LNP group, 4 mice in each of the PBS+siDicer1@M2pep-LNP and Clodro+siDicer1@M2pep-LNP groups); D shows the survival curve analysis of mice in different treatment groups (5 mice in each group); E shows HE staining of the liver of mice in different treatment groups, scale: 1mm; F ​​shows the percentage statistics of the liver area occupied by the tumor; G shows the comparison of liver weight / body weight of mice in different treatment groups; multiple t-tests were used for statistical analysis, the results were corrected by Bonferroni, and the data were expressed as Mean±SD; * P<0.05, ** P<0.01, *** P < 0.001;

[0077] Fig.37 The results showed that macrophage scavengers antagonized the reprogramming effect of siDicer1 nanoparticles on TAMs; Fig.35 The experiment was performed as shown in A; A shows a typical flow cytometric analysis of the number of macrophages in liver tumor tissues of mice in each group after treatment; B shows a comparison of the number of macrophages in mice in each group; CF shows the number of immune cells in liver tumor tissues of mice in each group by immunofluorescence analysis; C shows the number of total TAMs cells; D shows the number of M1 TAMs cells; E shows the number of CD8 + T cell number; F shows typical immunofluorescence staining images of mice in each group; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; * P<0.05, ** P<0.01, *** P < 0.001;

[0078] Fig.38 The figure shows the biosafety of nanoparticles; A shows the HE results of major organs after nanoparticle treatment; scale: 100 μm; BE shows the liver and kidney function results after nanoparticle treatment; ANOVA was used for statistical analysis, and the results were corrected by Tukey, and the data were expressed as Mean ± SD; ALT: alanine aminotransferase; AST: serum aspartate aminotransferase; BUN: blood urea nitrogen; SCr: serum creatinine;

[0079] Fig.39The figure shows the screening of downstream miRNAs for siDicer1@M2pep-LNP-regulated macrophage reprogramming; BMDM was induced to M2 type by IL-4, and miRNA sequencing was performed after 48 hours of treatment with siDicer1@M2pep-LNP; A shows the differential miRNA volcano map; screening conditions: |log2(FC)|>0.5 and P<0.05; B shows the intersection of differentially expressed miRNAs and highly expressed miRNAs in macrophages (ER0000000235), and the miRNAs with |log2(FC)|>1 and P<0.05 were screened; CD shows the verification of the screened candidate miRNAs in Dicer-knocked-down M2 BMDM and RAW264.7 cells; multiple t-tests were used for statistical analysis, the results were corrected by Bonferroni, and the data were expressed as Mean±SD; * P<0.05, ** P<0.01, *** P < 0.001;

[0080] Fig.40 Figure 4 shows the prediction of miRNA downstream targets and KEGG pathway enrichment; A shows the prediction of target genes of miR-148a-3p and miR-1981-5p using miRmap and microT; BC shows the KEGG pathway enrichment of miR-148a-3p and miR-1981-5p target genes;

[0081] Fig.41 The effects of miR-148a-3p and miR-1981-5p on BMDM phenotype were shown; BMDM were induced to M2 type by IL-4, and miRNA mimics or inhibitors were added to stimulate for 48 hours; A shows the overexpression / knockdown verification of miRNA mimics and inhibitors; B shows the effects of miRNA mimics or inhibitors on cytokines and Akt signaling pathways in M2 BMDM; ANOVA was used for statistical analysis, and the results were corrected by Tukey, and the data were expressed as Mean±SDzais; ** P<0.01, *** P < 0.001;

[0082] Fig.42The effects of miR-148a-3p and miR-1981-5p on the phenotype of RAW264.7 were shown; RAW264.7 was induced to M2 type by IL-4, and miRNA mimics or inhibitors were added to stimulate for 48 hours; A shows the overexpression / knockdown verification of miRNA mimics and inhibitors; B shows the effects of miRNA mimics or inhibitors on the cytokine and Akt signaling pathways of M2 type RAW264.7; ANOVA was used for statistical analysis, the results were corrected by Tukey, and the data were expressed as Mean±SD; *** P < 0.001;

[0083] Fig.43 Figure 3 shows the effect of miR-148a-3p and miR-1981-5p mimics on the phenotype of Dicer-KD RAW264.7. Dicer-KD RAW264.7 was induced to M2 type by IL-4, and miR-148a-3p mimics (A) and miR-1981-5p mimics (B) were added for stimulation for 48 hours. The expression levels of macrophage-related cytokines were detected by qPCR. Multiple t-tests were used for statistical analysis, and the results were corrected by Bonferroni. The data are expressed as Mean±SD. * P<0.05, ** P<0.01, *** P<0.001. DETAILED DESCRIPTION

[0084] The present invention discloses the use of Dicer as a marker in the preparation of products for detecting tumor liver metastasis. Those skilled in the art can refer to the content of this article and appropriately improve the process parameters to achieve it. It should be particularly noted that all similar substitutions and modifications are obvious to those skilled in the art, and they are all considered to be included in the present invention. The methods and applications of the present invention have been described through preferred embodiments, and relevant personnel can obviously modify or appropriately change and combine the methods and applications described herein without departing from the content, spirit and scope of the present invention to implement and apply the technology of the present invention.

[0085] The present invention targets the dilemma of poor treatment effect and poor prognosis of CRLM patients, as well as the important role of M2 TAMs in the occurrence and development of CRLM, screens out the key regulatory molecules of M2 TAMs in CRLM, and constructs a nucleic acid drug delivery system targeting M2 TAMs. By targeting and silencing the expression of M2 TAMs-related genes, the tumor immune microenvironment is reshaped, in order to provide a new potential molecular target for the treatment of CRLM. By modifying the surface groups of LNP, it is given tissue, organ and cell targeting.

[0086] The present invention found through bioinformatics analysis that compared with non-liver metastases in pan-cancer patients, TAMs M2 polarization increased in liver metastases; further, it was found that high expression of the DICER1 gene was significantly associated with TAMs M2 polarization and poor prognosis in CRLM patients. The liver metastatic lesions of CRLM patients and mouse models were rich in M2 TAMs, and the Dicer protein expression in M2 TAMs was significantly higher than that in M1.

[0087] The present invention found through in vitro cell experiments that compared with M0 (unpolarized) macrophages, Dicer1 mRNA and protein expression in M1 macrophages decreased, while expression in M2 macrophages increased. Knocking down Dicer in macrophages did not affect macrophage apoptosis, but caused cells to undergo G0 / G1 phase arrest. In addition, knocking down Dicer in macrophages reprogrammed M2 macrophages to M1, inhibiting the proliferation of colon cancer cells.

[0088] The present invention successfully prepared siRNA@LNP and siRNA@M2pep-LNP that meet the in vivo and in vitro delivery conditions. Compared with unmodified LNP, M2pep modification can increase the RNA delivery efficiency and targeting of LNP to M2 macrophages / TAMs; small animal in vivo imaging analysis found that compared with LNP, M2pep-LNP was more significantly enriched in liver metastases in tumor-bearing mice. In vitro experiments found that siDicer1@M2pep-LNP had a better knockdown efficiency of Dicer protein in M2 macrophages than siDicer1@LNP.

[0089] In the CRLM mouse model, the siDicer1@M2pep-LNP of the present invention showed a more excellent anti-tumor effect; the expression of Dicer and IL-10 proteins in tumor tissues was reduced, the M2 type TAMs were reduced, and the M1 type TAMs and CD8 + The number of T cells increased. After using macrophage scavengers and then giving the above drugs, it was found that the tumor inhibition effect of siDicer1@M2pep-LNP was weakened.

[0090] The present invention uses miRNA sequencing and qPCR verification, and the results show that miR-148a-3p and miR-1981-5p may be potential targets for Dicer to regulate macrophage phenotypes. Further functional verification of the above two miRNAs using miRNA mimics and inhibitors revealed that miR-148a-3p and miR-1981-5p may reprogram M2 macrophages by regulating the Akt signaling pathway.

[0091] The mouse CRC cell line CT26, mouse monocyte macrophage cell line RAW264.7, human embryonic kidney cell 293T and mouse fibroblast L929 selected in the present invention are all derived from the American Type Culture Collection (ATCC) cell bank. The 6-8 week old Babl / c mice used in this study were purchased from Beijing Weitong Lihua Experimental Animal Co., Ltd. Babl / c mice were raised in an SPF-level environment in the experimental animal center of our hospital. The ethics of experimental animals were reviewed and approved by the Animal Ethics Committee of our hospital. The liver tissue sections of CRLM patients used in this study were from the Department of Pathology of the Second Affiliated Hospital of Zhejiang University. The samples were reviewed by the hospital clinical ethics review and the patient's informed consent was obtained before collection.

[0092] The primer sequences of the genes are shown in the following table:

[0093] Table 1 Primer sequences of genes

[0094]

[0095] Table 2 Main reagents and consumables

[0096]

[0097]

[0098] Unless otherwise specified, the raw materials and reagents used in the application of Dicer provided by the present invention as a marker in the preparation of products for detecting tumor liver metastasis can all be purchased from the market.

[0099] The present invention will be further described below in conjunction with embodiments:

[0100] Example 1 Bioinformatics Analysis

[0101] 1. Increased M2 polarization levels of macrophages in liver metastases

[0102] In the pan-cancer patient bulk transcriptome sequencing dataset (MET500), the CIBERSORT and MCPcounter algorithms were used to calculate the M2 polarization level of macrophages in the samples. The results showed that compared with patients without liver metastasis, the M2 polarization level of macrophages in the lesions of patients with liver metastasis was significantly increased ( Figure 1 In the CRLM single cell dataset (GSE164522), 5818 macrophages were divided into five groups (C1-C5) by resolution = 0.1 ( Figure 1 Middle B); The M2 polarization gene set was used to perform GSVA scoring on all macrophages. The GSVA score of the C5 cluster cells was significantly lower than that of the other four clusters (C1-C4). Based on this, the macrophages were divided into a high M2 score group and a low M2 score group ( Figure 1 CD). Further differential analysis of the expressed genes of the cells was performed, and a total of 516 genes were found to be positively correlated with the macrophage M2 score using min.pct=0.15&logfc.threshold=0.15&P.value<0.01 as the screening conditions ( Figure 1 Middle E). In the above pan-cancer liver metastasis sample Bulk transcriptome sequencing dataset (MET500), by analyzing the genes related to macrophage M2 polarization, 1355 genes related to M2 polarization were obtained with P.value<0.01&cor>0.15 as the screening criteria ( Figure 1 Middle F).

[0103] 2. Explore macrophage M2 polarization genes associated with CRC prognosis

[0104] like Figure 2 As shown in A, a cross-analysis of the above two M2 polarization-related gene datasets (MET-500 and GSE164522) was performed through a Venn diagram, and a total of 13 common genes were found, namely RNF13, CD9, ELL2, PGD, B3GNT5, ABHD5, GNPDA1, TMEM251, WIPI1, CREG1, TFRC, DICER1, and SLIRP. Subsequently, we performed Cox regression analysis of recurrence survival of these genes in 6 CRC Bulk transcriptome datasets (Table 3). The expression of the above genes was standardized according to the monocyte / macrophage content. Due to the possible heterogeneity of different cohorts, we performed a meta-analysis on these 13 genes and found that the four genes, DICER1, CD9, RNF13 and CREG1, were closely related to the recurrence survival status of CRC (P<0.05, Figure 2 In B), we found that the DICER1 gene was the most correlated with CRC recurrence and survival among all genes ( Figure 2 Middle C).

[0105] Table 3 Cox regression analysis of 13 genes for recurrence and survival in 6 CRC cohorts

[0106]

[0107]

[0108] 3. DICER1 is highly expressed in M2 macrophages in tumors and affects the prognosis of CRC

[0109] To identify the expression of DICER1 in different cells, we annotated all single cells from CRLM patients and found that DICER1 was highly expressed in macrophages ( Figure 3Middle A). We further used the pan-cancer liver metastasis bulk transcriptome sequencing dataset (MET500) ( Figure 3 Middle B) and CRLM single-cell sequencing dataset (GSE164522) ( Figure 3 In C), it was found that DICER1 expression was closely related to macrophage M2 polarization. Analysis of the CRC Bulk transcriptome dataset showed that in GSE72970 and GSE14333, the standardized DICER1 expression was closely related to CRC recurrence survival (P<0.05) ( Figure 3 middle DE).

[0110] Example 2 Inducing different polarization states of macrophages

[0111] 1. Culture of mouse bone marrow-derived macrophages (BMDM)

[0112] When L929 cells were cultured to 70-80% density, fresh medium was replaced. After 48 hours of continuous culture, the supernatant was collected, filtered through a 0.2 μm filter membrane to remove cells and cell debris, and aliquoted and stored at -80°C for future use.

[0113] In this study, 6-8 week old Babl / c mice were used to extract BMDM. The mice were killed and their femurs and tibias and fibulas were dissected to ensure the integrity of the bones. Incisions were made at both ends of the bone marrow cavity, and the bone marrow cavity was repeatedly rinsed with DMEM complete medium. The collected bone marrow cells were centrifuged at 4°C and 1000rpm for 5 minutes, and the supernatant was discarded. The obtained cell pellet was lysed with red blood cell lysis fluid for 5 minutes, the cells were collected by centrifugation, and washed once with PBS. The cells were resuspended in DMEM complete medium containing 30% L929 cell supernatant and cultured at 37°C and 5% CO2 for 7 days to induce differentiation. During the culture process, the culture medium was replaced every two days, and the cell morphology was observed regularly under an optical microscope. To verify whether the cells have successfully differentiated into macrophages, flow cytometry was used for identification (CD11b and F4 / 80). As Figure 5 As shown, after 7 days of L929 supernatant induction, almost all bone marrow cells were induced to CD11b + F4 / 80 + Macrophages.

[0114] 2. Macrophage polarization induction

[0115] In this study, LPS and IL-4 were used to induce macrophage polarization into M1 and M2 types, respectively. The specific scheme is as follows:

[0116] RAW264.7 cells were plated in advance, and after the cell confluence reached 50-60%, LPS (200 ng / mL) or IL-4 (20 ng / mL) was added for stimulation. The medium was changed after 24 hours to induce M1 or M2 macrophages.

[0117] After BMDM was successfully induced, they were replated and stimulated with LPS (100 ng / mL) or IL-4 (10 ng / mL). The medium was changed after 24 hours to induce M1 or M2 macrophages.

[0118] 3. Reverse transcription-real-time fluorescence quantitative PCR (Quantitative real-time PCR, qPCR)

[0119] Total RNA was extracted using the TRIzol kit (Thermo Fisher, USA). The RNA concentration and purity were determined using a Nanodrop2000 UV spectrophotometer, and the RNA samples were stored at -80°C for future use.

[0120] The RNA was reverse transcribed using HiScript IIQ RT SuperMix for qPCR (+gDNA wiper) kit (Vazyme). The reverse transcription product was subjected to qPCR using ChamQ Universal SYBR qPCR Master Mix kit (Vazyme). After the experiment, the data were calculated and analyzed based on the CT value of the gene.

[0121] 4. Western Blot

[0122] The protein sample was loaded at 20-30ug / well. At the beginning, the electrophoresis was maintained at 60V constant voltage. When the bromophenol blue indicator reached the separation gel interface, it was adjusted to 100V constant voltage to continue separation for a suitable time. The PVDF membrane was soaked in methanol for more than 15 seconds. The sandwich method was used for wet transfer, with a constant current of 250mA, and the transfer time was adjusted according to the size of the protein. After the transfer, 5% BSA was blocked at room temperature for 1 hour. After the blocking was completed, the PVDF membrane was placed in the pre-prepared primary antibody diluent, and the antibody was diluted in advance according to the antibody instructions (1:1000) using the antibody diluent. After ensuring full coverage, it was incubated at 4°C overnight (about 8 hours). After the incubation was completed, it was washed 3 times at room temperature with TBST solution for 10 minutes each time. The PVDF membrane was placed in the pre-prepared secondary antibody diluent, incubated at room temperature for 2 hours, and washed 3 times for 10 minutes each time. The ultrasensitive ECL chemiluminescence kit (Suzhou Xinsaimei Biotechnology Co., Ltd.) was used for exposure. The image was saved for later processing.

[0123] Example 3 Knockdown of Macrophage Dicer

[0124] 1. siRNA transfection of cells: One day before transfection, cells were evenly plated in a well plate so that the density of cells was 40-50% on the day of transfection; siRNA transfection was performed according to the instructions of Lipofectamine RNAiMAX (Thermo Fisher, USA). Cells were collected 48-72 hours later for subsequent detection.

[0125] 2. Construction of Dicer knockdown (KD) macrophage cell line using CRISPR-Cas9 technology

[0126] A. Targeting the gene sequence of mouse Dicer1, two different sequences were designed according to the sgRNA sequence design principle, synthesized by Jima Biotech (Shanghai) Co., Ltd. and linked into the Lenti CRISPR V2 vector. The packaging plasmids psPAX2 and pMD2.G were constructed by Jima Biotech (Shanghai) Co., Ltd.

[0127] B. Lentivirus packaging: Mix packaging plasmid psPAX2, auxiliary plasmid pMD2.G and lentivirus plasmid in a certain ratio (mass ratio 4:3:1). Transfect 293T cells according to the operating instructions of Lipofectamine 3000 (Thermo Fisher, USA). Within 48 to 72 hours after transfection, collect the culture supernatant containing viral particles. Filter through a 0.45 μm pore size filter to remove cell debris; concentrate the viral supernatant according to the instructions of the GMLPCTM Lentivirus Concentration Kit.

[0128] C. The cell density of RAW264.7 was about 30%. Lentivirus was added for infection. After 48 hours of culture, puromycin was added for resistance screening. The culture medium was replaced every 48 hours. After several rounds of screening, a monoclonal cell Dicer-KDRAW264.7 stable transfected cell line was obtained.

[0129] 3. CCK-8 cell proliferation assay

[0130] A. Before the experiment, the cells were digested and counted. They were seeded in 96-well plates at a density of 3,000 cells per well. Four time points (2, 24, 48, and 72 hours) were set up in the experiment to monitor the proliferation ability of the cells.

[0131] B. When testing at each predetermined time point, first remove the old culture medium in the well to ensure that the residual liquid is drained as much as possible. Perform cell proliferation testing according to the instructions of the Cell Proliferation and Toxicity Detection Kit (CCK-8) (Dalian Meilun Biotechnology Co., Ltd.).

[0132] 4. Western blotting to detect the expression of apoptotic proteins in cells

[0133] The experimental operation was the same as that of protein immunoblotting in Example 2.

[0134] 5. Flow cytometry to detect cell apoptosis and cell cycle

[0135] Apoptosis detection:

[0136] Digestion of cells: When the cells were cultured to an appropriate density, EDTA-free trypsin was added to digest the cells, the cells were collected by centrifugation, and resuspended in PBS. Cell apoptosis was detected using the Annexin V-FITC / PI apoptosis kit (Lianke Biotechnology). Data were analyzed using CytExpert software.

[0137] Cell cycle detection:

[0138] The collected cells were subjected to cell cycle detection according to the Cell Cycle Staining Kit (Lianke Biotech). The lowest loading speed was selected for loading. Flowjo was used to analyze the changes in the cell cycle.

[0139] 6. Flow cytometry to detect macrophage phenotype

[0140] Collect cells and stain with surface antibodies: adjust the cell concentration to 2×10 7 / mL. Set up blank control, single staining control and experimental tube. Consult the antibody instructions, add appropriate antibodies according to the instructions, add 0.3-1μL antibody (surface staining) to every 50μL cell suspension, stain at 4℃ in the dark for 30 minutes, add cell staining buffer to neutralize, centrifuge at 1000rpm for 5 minutes, and discard the supernatant; after staining, add appropriate amount of PBS to resuspend and transfer to flow tube, and detect on Beckman flow cytometer. CytExpert software analyzes the expression of CD206 and CD86 on the surface of macrophages.

[0141] Example 4 In vivo tumor inhibition effect of Dicer-KD macrophages

[0142] 1. Subcutaneous co-injection of macrophages and colon cancer cells into mice

[0143] (1) 4-6 week old Babl / c mice were housed in an SPF animal room 3 days in advance to acclimate to the environment. On the day of the experiment, the skin of the mice at the inoculation site was prepared.

[0144] (2) CT26 cells, VectorRAW264.7 cells, and Dicer-KD RAW264.7 cells were cultured until the logarithmic growth phase. When the cell confluence reached 80% to 90%, the cells were digested with trypsin and collected. The obtained cells were washed three times with PBS and resuspended to prepare a cell suspension. The cells were counted using Countstar and a concentration of 1×106 The cell suspension was kept on ice throughout the whole process.

[0145] (3) Take 300 μL of CT26 cell suspension and mix with 300 μL of Vector RAW264.7 and 300 μL of Dicer-KD RAW264.7 cell suspensions, respectively, to obtain 600 μL of CT26 / Vector RAW264.7 mixed cell suspension and CT26 / Dicer-KD RAW264.7 mixed cell suspension, and inoculate 100 μL per mouse into the right armpit. Grouping: CT26+Vector RAW264.7 group and CT26+Dicer-KD RAW264.7 group, 5 mice in each group.

[0146] (4) After tumor cells are inoculated, a bulge will form under the mouse's skin. The bulge will gradually decrease over time and reach its minimum value around the 5th day. At this time, the size of the mouse's subcutaneous tumor will be measured and recorded. When measuring the tumor, use a vernier caliper to gently clamp the tumor and record the long diameter (L, mm) and short diameter (W, mm) of the tumor. Tumor volume (V, mm 3 )The calculation formula is as follows: V = L × W 2 / 2. When the tumor diameter reaches 1.5cm and the volume reaches 1500~2000mm 3 The experiment was terminated if ulcers, infection or continuous bleeding occurred on the tumor surface.

[0147] (5) After the last day of observation, the mice were killed by dislocation of the neck and the tumor tissues were obtained by dissection. The tumor tissues were divided into two parts, one was frozen in a -80°C refrigerator, and the other was fixed in 4% paraformaldehyde.

[0148] 2. Hemi-splenectomy mouse liver metastasis model

[0149] After 6-8 week old Babl / c mice were adaptively raised for 3 days, the left abdomen of the mice was shaved and depilatory cream was used to remove hair. On the day of surgery, CT26-luc cells in the logarithmic growth phase were digested with trypsin and their density was adjusted to 5×10 5 / 100μL, placed on ice for use. Use sterile surgical scissors to make an incision about 1cm long in the epidermis and peritoneum below the left rib, expose the spleen and gently lift the spleen out of the abdominal cavity; use medical absorbable sutures to ligate the spleen in half and then cut off the spleen along the right side. Flatten the left spleen and insert the needle about 1cm along the spleen, slowly inject 100μL of cell suspension, and press the needle eye with alcohol cotton balls for 2 minutes. After ligating the splenic blood vessels, separate the left half of the spleen, retract the right half of the spleen, and suture the wound with medical sutures. After disinfecting the incision, place the mouse on a 37℃ warming blanket and wait for it to recover. 3 to 5 days after injection, the mouse was intraperitoneally injected with luciferase substrate, and the mouse was anesthetized with an air anesthesia machine. The IVIS small animal in vivo imaging system was used to monitor the growth of liver metastases in the mouse.

[0150] 4. Tissue Immunofluorescence Staining

[0151] (1) Dewaxing to water: Place the slides in xylene I and II for 15 minutes, then in anhydrous ethanol I and II for 5 minutes, dry them, and then wash them with distilled water;

[0152] (2) Antigen repair: Place the slide in antigen repair buffer and set the microwave oven to medium heat for 8 minutes, off heat for 8 minutes, and medium-low heat for 7 minutes. Be careful to prevent the slide from drying during the repair process. After cooling, gently wash with PBS 3 times, 5 minutes each time;

[0153] (3) BSA blocking: After the slices are slightly dried, use a tissue pen to draw a circle around the tissue, and evenly cover the tissue with 3% BSA, and block at room temperature for 30 minutes;

[0154] (4) Primary antibody incubation: remove the blocking solution, add the primary antibody dilution solution (according to the recommended concentration of the antibody), and place in a humidified box at 4°C overnight;

[0155] (5) Fluorescent secondary antibody incubation: After removing the primary antibody diluent, wash gently three times for 5 minutes each time, then prepare the secondary antibody diluent (according to the recommended concentration of the antibody) and incubate at room temperature for 1 hour;

[0156] (6) Nuclear staining and sealing: After removing the secondary antibody diluent, wash gently three times for 5 minutes each time, add DAPI working solution to the sample, incubate at room temperature in the dark for 10 minutes; wash three times with TBST for 5 minutes each time; add anti-fluorescence attenuation sealing agent, observe and collect images under a fluorescence microscope.

[0157] 5. Immunohistochemistry

[0158] (1) Sectioning, baking, dewaxing, antigen repair, peroxidase blocking, and blocking steps are the same as above;

[0159] (2) Primary antibody incubation: remove the blocking solution, add the primary antibody dilution solution (according to the recommended concentration of the antibody), and place in a humidified box at 4°C overnight;

[0160] (3) Secondary antibody incubation: After removing the primary antibody diluent, gently wash three times for 5 minutes each time, then add the secondary antibody dilution (HRP labeled) corresponding to the primary antibody (according to the recommended concentration of the antibody) and incubate at room temperature for 50 minutes.

[0161] (4) DAB color development: After removing the secondary antibody dilution solution, gently wash three times, 5 minutes each time, and then prepare fresh DAB color development solution. After the reaction time is appropriate, stop the color development;

[0162] (5) Restain with hematoxylin for 1 to 2 minutes until the nucleus turns blue. Differentiate with 1% hydrochloric acid alcohol for a few seconds, rinse with tap water, turn blue with ammonia water, and rinse with running water.

[0163] (6) Dehydration and sealing: 75% alcohol for 6 minutes → 85% alcohol for 6 minutes → anhydrous ethanol I for 6 minutes → anhydrous ethanol II for 6 minutes → xylene I for 7 minutes → xylene II for 5 minutes. After the above steps are completed, the slides are dehydrated and transparent, sealed with neutral gum, and examined under a microscope.

[0164] Preparation Example 1 Preparation of Nanoparticles (LNP and M2pep-LNP)

[0165] (1) Preparation of LNP lipid solution: Dlin-MC3-DMA, DSPC, Cholesterol, and DMG-PEG2000 were dissolved in an appropriate amount of anhydrous ethanol solution at a molar ratio of 50:10:30:8.5:1.5 to obtain a lipid solution with a final concentration of Dlin-MC3-DMA of 2 mg / mL.

[0166] (2) Preparation of M2pep-LNP lipid solution: Dlin-MC3-DMA, DSPC, Cholesterol, DMG-PEG2000, and DSPE-PEG2000-M2pep were dissolved in anhydrous ethanol solution at a molar ratio of 50:10:38:1.0:1.0 to obtain a lipid solution containing M2pep with a final concentration of Dlin-MC3-DMA of 2 mg / mL.

[0167] (3) Preparation of siRNA buffer: Prepare sodium citrate dihydrate / citric acid buffer solution (pH = 4, 20 mM), dissolve an appropriate amount of siRNA (the mass ratio of siRNA to Dlin-MC3-DMA (μg / mg) is 10:1) in the citric acid buffer to obtain a siRNA buffer with a final concentration of 20 μg / mL.

[0168] (4) Microfluidic device setup: Connect the microfluidic chip to the syringe pump. Adjust the flow rate and flow rate of the syringe pump to ensure that the lipid solution and siRNA buffer are mixed at an appropriate rate. The lipid solution flow rate is 114 μL / min, and the siRNA buffer flow rate is 684 μL / min; the lipid solution flow rate is 333.3 μL / min, and the siRNA buffer flow rate is 2.0 mL / min.

[0169] (5) Synthesis of LNP and M2pep-LNP: Start the syringe pump and inject lipid solution and siRNA buffer into the microfluidic chip on both sides. In the chip, the two solutions are quickly mixed, and by controlling the flow rate, the lipids self-assemble to form siRNA-encapsulated nanoparticles siDicer1@LNP and siDicer1@M2pep-LNP.

[0170] (6) Collection and purification of LNP and M2pep-LNP: To remove unencapsulated drugs and excess lipids and organic solvents, the effluent was added to a dialysis tube with a MWCO of 3.5-5kD and dialyzed in sufficient PBS for about 6-8 hours. The dialyzate was added to an ultrafiltration tube with a MWCO of 100kDa and centrifuged at 3,500g for 10 minutes to concentrate the liquid.

[0171] Preparation Example 2 Preparation of DiI / DiR / DiD labeled nanoparticles

[0172] In order to facilitate the detection of cell uptake of nanoparticles by inverted fluorescence microscopy and / or flow cytometry, we prepared DiI / DiR / DiD labeled nanoparticles. The preparation method refers to Preparation Example 1, using microfluidic technology, and the process is: weigh an appropriate amount of DiI / DiR / DiD dye and dissolve it in anhydrous ethanol to obtain a working solution with a final concentration of 30μM. Take an appropriate amount of the above working solution and add it to the LNP and M2pep-LNP lipid solutions prepared in (1) and (2) of Preparation Example 1 to obtain a lipid solution containing DiI / DiR / DiD with a final concentration of 5μM, and then prepare DiI / DiR / DiD labeled LNP and M2pep-LNP according to the microfluidic technology described in Preparation Example 1. The obtained nanoparticles are dialyzed with a dialysis tube, concentrated with an ultrafiltration tube, and placed at 4°C for use. The preparation process must be kept away from light throughout.

[0173] Example 5 Nanoparticle Characterization

[0174] (1) Particle size and potential: The nanoparticle solution prepared in Preparation Example 1 was diluted to an appropriate concentration, and the particle size distribution and potential were measured using a Malvern nano-ZS Zetasizer (Malvern Instruments Ltd.) dynamic light scattering (DLS).

[0175] (2) Cryo-electron microscopy observation of nanoparticle morphology:

[0176] The prepared nanoparticles were concentrated to an appropriate concentration using an ultrafiltration tube to ensure the formation of a monolayer of particles on the electron microscope grid. The electron microscope grid was then cleaned using a plasma cleaner to remove surface contaminants; an appropriate amount of nanoparticle suspension was carefully dripped onto the electron microscope grid, and the edge of the grid was gently touched with filter paper to remove excess liquid, leaving a thin layer of sample liquid; the grid with the sample was quickly immersed in liquid nitrogen to ultra-rapidly freeze the sample to prevent ice crystal formation; the sample was loaded into the cryo-EM sample holder under low temperature conditions; the appropriate acceleration voltage, electron beam intensity and focus were set on the cryo-EM (Talos F200C 200kV), and images at different angles were collected.

[0177] (3) RNA encapsulation efficiency determination:

[0178] According to Quant-iT TM RiboGreen TM Calculate the LNP encapsulation efficiency according to the RNA reagent instructions.

[0179] Example 6 Cellular uptake of different nanoparticles

[0180] (1) The method described in Example 4 was used to prepare a hemi-splenectomized mouse liver metastasis model;

[0181] (2) Preparation of single cell suspension of liver metastasis: Take liver metastasis, cut it into pieces with scissors, resuspend it in RPMI-1640 medium containing 5% FBS and 0.5 mg / mL IV collagenase, and place it in a 37°C shaker for digestion for 30 minutes. Then filter it with a 70μm sterile cell filter to obtain a single cell suspension of tumor tissue. Centrifuge the cell suspension for 5 minutes (4°C, 2000rpm), discard the supernatant, add 5mL of red blood cell lysis buffer, lyse for 10 minutes, and centrifuge at 50g for 5 minutes to precipitate liver cells. Collect the supernatant and centrifuge it again for 5 minutes (4°C, 2000rpm), collect the cell precipitate, and resuspend it with an appropriate amount of PBS for later use.

[0182] (3) Preparation of spleen single cell suspension: Place the spleen on a 70 μm cell strainer and gently crush it with the back of a syringe to allow the cells to pass through the strainer into a collection tube containing PBS. Centrifuge at 2000 rpm at 4°C for 5 minutes, resuspend the cell suspension with an appropriate amount of red blood cell lysis buffer to remove red blood cells. Centrifuge again and resuspend the cell pellet with an appropriate amount of PBS.

[0183] (4) Co-incubation of DiD-labeled nanoparticles with single cell suspension: DiD@LNP and DiD@M2pep-LNP prepared in Preparation Example 2 were added to tumor single cell suspension and spleen single cell suspension, respectively (final DiD concentration was 1 μM), mixed thoroughly, incubated at room temperature in the dark for 2 hours, centrifuged at 2000 rpm for 5 minutes at 4°C, washed 3 times with PBS, resuspended and stained with flow cytometry surface antibodies (zombie NIR, CD45, CD11b, F4 / 80, CD206) (same method as above), resuspended in PBS and analyzed by flow cytometry. CytExpert software was used to analyze the expression of M2 macrophages (CD45 + CD11b + F4 / 80 + CD206 + ) Mean fluorescence intensity of DiD.

[0184] (5) Observation under an inverted fluorescence microscope: Plate RAW264.7, BMDM and other cells in advance to ensure that the cell density reaches 80% when the DiI-labeled LNP or M2pep-LNP prepared in Preparation Example 2 is added. RAW264.7 and BMDM are induced into macrophages of different polarization states by adding LPS or IL-4 according to the experimental design. Take an appropriate amount of the above nanoparticles and add them to the well plate (final concentration is 1 μM DiI), incubate for 1 hour, discard the culture medium, wash 3 times with PBS, add Hoechst 33342 working solution and incubate at 37°C in the dark for 10 minutes. Then wash gently with PBS 3 times, and observe the cell uptake of nanoparticles under an inverted fluorescence microscope. The operation must be kept away from light throughout the process. The obtained image is analyzed for the average fluorescence intensity using ImageJ.

[0185] (6) Flow cytometry: Cells were plated and treated in the same manner as above. After treatment, the cells were digested with trypsin, centrifuged at 800 rpm for 5 minutes, washed once with PBS, resuspended, and transferred to a flow cytometry tube for analysis. The entire operation process must be protected from light. CytExpert software was used to analyze the intracellular mean fluorescence intensity.

[0186] Example 7 Detection of siRNA transfection efficiency of different nanoparticles

[0187] (1) Observation under an inverted fluorescence microscope: Plate RAW264.7, BMDM and other cells in advance to ensure that the cell density reaches 60-70% when the nanoparticles are added. Prepare nanoparticles encapsulated with FAM-Si (FAM-siNC (FAM-Si) synthesized by Jima Biotechnology (Shanghai) Co., Ltd.) using the same method as in Preparation Example 1. Take an appropriate amount of FAM-Si@LNP and FAM-Si@M2pep-LNP and add them to the well plate, with a final siRNA concentration of 4 μg / mL. Incubate at 37°C, 5% CO2 in the dark for 8 hours, discard the culture medium, wash with PBS three times, add Hoechst 33342 working solution, and incubate at 37°C, 5% CO2 in the dark for 10 minutes. Wash gently twice with PBS, and observe the expression of FAM-Si in the cells using an inverted fluorescence microscope. The operation process must be kept away from light. The obtained image was analyzed for average fluorescence intensity using ImageJ.

[0188] (2) Flow cytometry: Cells were plated and treated in the same manner as above. After treatment, the cells were digested with trypsin, centrifuged at 800 rpm for 5 minutes, washed once with PBS, resuspended, transferred to a flow cytometry tube, and analyzed by flow cytometry. The operation process must be protected from light. CytExpert software was used to analyze the intracellular FAM mean fluorescence intensity.

[0189] Example 8 In vivo imaging of small animals to investigate the organ distribution of nanoparticles

[0190] A hemi-splenectomy liver metastasis mouse model was prepared according to the method in Example 4. Ten days after inoculation, the tumor formation of the mice was observed by IVIS, and the mice with successful modeling were divided into two groups, with 6 mice in each group. On the day of the experiment, 200μL DiR@LNP or DiR@M2pep-LNP (DiR-eq. 30μmol / mouse) prepared in Preparation Example 2 was injected into the tumor-bearing mice through the tail vein, and the real-time distribution of the nanoparticles in the liver area of ​​the mice was detected by IVIS at 2 hours, 8 hours, 12 hours and 24 hours. Half of the mice were killed after the imaging was completed at the 8-hour time point, and the heart, liver, spleen, lungs and kidneys were removed and imaged again in vitro. The remaining half of the mice were killed after completing 24 hours of living imaging, and each organ was imaged in vitro again. Living -4.5 software was used to quantitatively analyze the fluorescence intensity of DiR in different tissues.

[0191] At the same time, we further observed the distribution of nanoparticles in normal mice and divided the normal mice into two groups, 3 in each group. 200μL DiR@LNP or DiR@M2pep-LNP (DiR-eq. 30μmol / mouse) was injected into the mice through the tail vein, and the distribution of nanoparticles in the liver area of ​​the mice was detected by IVIS at 2 hours, 8 hours, 12 hours and 24 hours. After 24 hours of completion of the test, the mice were killed, and their hearts, livers, spleens, lungs and kidneys were dissected and subjected to in vitro imaging again. Living -4.5 software was used to quantitatively analyze the fluorescence intensity of DiR in different tissues.

[0192] Example 9 Immunofluorescence and flow cytometry to detect the cellular distribution of nanoparticles

[0193] Cy3-labeled Cy3-Si@LNP and Cy3-Si@M2pep-LNP were prepared according to the method of Preparation Example 1. A hemi-splenectomy liver metastasis mouse model was established according to the method in Example 4, and the tumor growth of the mice was detected by IVIS. After successful tumor bearing, the mice were divided into two groups, with 5 mice in each group. On the day of the experiment, 200 μL of Cy3-Si@LNP or Cy3-Si@M2pep-LNP (siRNA-eq. 0.75 mg / kg per mouse) was injected into the tumor-bearing mice through the tail vein. After 6 hours of administration, the mice were killed and the liver was removed. Wash with pre-cooled PBS to remove blood and other impurities. The liver tissue was divided into two parts, one for the preparation of frozen sections and immunofluorescence detection, and the other for the preparation of single cell suspension and subsequent flow cytometry analysis.

[0194] (1) Immunofluorescence detection: Pour an appropriate amount of OCT complex into a pre-cooled mold, place the liver tissue in the center of the mold and cover it with a layer of OCT complex, and immediately put the mold into liquid nitrogen for quick freezing until the OCT is completely solidified. Transfer the embedded liver tissue to a cryostat. Slice the tissue into 8 μm slices at -20°C in a dark environment. Collect the cut tissue slices on an adhesive slide and place them in a -80°C refrigerator in a dark environment for later use. When used, take the slide out of the -80°C refrigerator and equilibrate at room temperature in the dark for 15 minutes. Wash the slides with PBST three times for 5 minutes each. Incubate with 0.5% TritenX-100 (PBST configuration) at room temperature for 20 minutes for permeabilization. After gently washing with PBST three times, block with PBST solution containing 5% FBS for 1 hour to reduce background signals. Incubate with F4 / 80 fluorescent primary antibody (1:200 dilution) at room temperature in the dark for 2 hours, and wash with PBST three times for 5 minutes each. Then use DAPI anti-fluorescence quenching sealing solution to seal the slide. Cover with a cover slip and seal with nail polish. Observe under a fluorescence microscope F4 / 80 + Cy3 + The number of cells.

[0195] (2) Flow cytometry analysis: Prepare a single cell suspension of liver metastases (same method as above). Wash the obtained single cell suspension twice with cell staining buffer, count the cells, add Fc blocking antibody (anti-mouse CD16 / 32), and incubate on ice for 5 minutes to block the nonspecific binding of the antibody. Dilute the flow cytometry antibody according to the antibody manual with cell staining buffer and incubate with the cells at room temperature for 30 minutes (the flow cytometry antibody staining method is the same as above). Wash 3 times with PBS, resuspend, and detect on the machine. CytExpert software was used to analyze the expression of Cy3 in different cells.

[0196] Example 10 Flow cytometry detection of liver metastases and spleen immune cells

[0197] The preparation method of CRLM mouse model was the same as that in Example 4. Tumor growth was monitored by IVIS 3 days after modeling, and the mice with successful modeling were divided into 4 groups, with 7 mice in each group: siNC@LNP group, siNC@M2pep-LNP group, siDicer1@LNP group and siDicer1@M2pep-LNP group. Each mouse was injected with 200 μL of drug-containing solution (siRNA-eq. 0.75 mg / kg per mouse) through the tail vein. The drug was administered once every two days for a total of 3 times. The mice were killed 48 hours after the last administration, and the liver tumor tissue and spleen of the mice were dissected to prepare a single cell suspension (the preparation method is the same as in Example 6).

[0198] (1) Extraction of immune cells from liver metastasis tissue: First, prepare Percoll separation solutions of different concentrations. First, mix 9 parts of Percoll separation solution with 1 part of 10×PBS to achieve physiological osmotic pressure. At this time, the solution is 100% Percoll, the density is 1.127, and the millimolecular osmotic pressure concentration is 290mOsmol / kg. Prepare Percoll separation solutions of different densities according to the following formula: a1×N+a2×(YN)=a3×Y. Where a1 is the density of the isotonic Percoll stock solution (about 1.127), a2 is the density of the isotonic PBS (about 1.000), a3 is the density of the required separation solution, N is the volume of the required separation Percoll stock solution, and Y is the total volume of the required separation solution.

[0199] After preparing the required Percoll separation solution of different densities, first resuspend the cells with 4mL 40% Percoll separation solution, and carefully and slowly spread the cell suspension on top of 4mL 70% Percoll separation solution (add slowly to the wall, do not disturb the interface layer). Adjust the centrifuge's lifting and lowering speed to the lowest, and centrifuge (15°C, 750g, 22 minutes). After the centrifugation, carefully aspirate the cell layer suspended between the 40% and 70% Percoll separation solutions, which are the immune cells in the tissue. Neutralize the cell suspension with pre-cooled cell staining buffer and centrifuge (4°C, 2000rpm, 5 minutes), discard the supernatant, add 1mL red blood cell lysis solution, resuspend, and place at room temperature for 5 minutes. Then neutralize and centrifuge with pre-cooled cell staining buffer (4°C, 2000rpm, 5 minutes), and discard the supernatant. Finally, resuspend the cells with PBS, dilute and count, and place on ice for later use.

[0200] (2) Extraction of spleen immune cells: Place the spleen on a 70 μm cell strainer and gently crush it with the back of a syringe to allow the cells to pass through the strainer into a collection tube containing PBS. Centrifuge at 2000 rpm at 4°C for 5 minutes, resuspend the cells with red blood cell lysis buffer, let stand at room temperature for 5 minutes, and centrifuge again. Resuspend the cell pellet with an appropriate amount of PBS, dilute and count, and place on ice for later use.

[0201] (3) Staining steps: Count the single cell suspension and adjust the cell concentration, add 0.3 μL of live / dead dye, stain at room temperature and away from light for 30 minutes, then add cell staining buffer to stop, centrifuge at 4°C 2000rpm for 5 minutes, and discard the supernatant. Add cell surface antibody (0.3-1 μL / 50 μL), stain at room temperature and away from light for 30 minutes, add cell staining buffer to stop, centrifuge and discard the supernatant. Add 100 μL of fixative, fix at room temperature and away from light for 50 minutes, add 100 μL of permeabilization solution, centrifuge and discard the supernatant, and resuspend the cells with permeabilization solution. Add intracellular factor antibody (0.5-2 μL / 50 μL), stain at room temperature and away from light for 50 minutes. After staining, centrifuge at 4°C 1000rpm for 5 minutes, discard the supernatant, wash once with PBS, centrifuge and discard the supernatant, add 400 μL of PBS and transfer to the flow tube, and detect on the machine. The multicolor flow strategy is as follows: M1 TAMs: CD11b + Gr-1-F4 / 80 + CD86 + ; M2 TAMs: CD11b + Gr-1-F4 / 80 + CD206 + ;CD8+T cells:CD3 + CD8 + ;CD4+T cells:CD3 + CD4 + ; Th1 cells: CD3+ CD4 + GATA3 + ; Th2 cells: CD3 + CD4 + T-bet + ; Treg cells: CD3 + CD4 + CD25 + Foxp3 + ;MDSCs:CD11b + Gr-1 + ; DCs:CD11b + CD11c +

[0202] Example 11 In vivo anti-tumor study

[0203] To evaluate the antitumor effect of the nanoparticles, mice bearing CRLM were divided into different treatment groups and intravenously injected with LNPs or M2pep-LNPs (0.75 mg / kg) encapsulating siDicer1 or siNC. After intraperitoneal injection of D-luciferin (10 mg / mL, 200 μL), tumor growth was monitored by IVIS imaging. After imaging was completed on day 12, all mice were euthanized and body weight and liver weight were recorded. The main organs (heart, liver, spleen, lung, and kidney) were washed with pre-cooled PBS and fixed in 4% paraformaldehyde solution for pathological staining. Whole blood was collected for biochemical analysis. For survival curve analysis, mice were monitored daily and monitoring was stopped if any of the following conditions were met: weight gain or loss of more than 10% within 1 week, or signs of distress such as dehydration, inactivity, or lethargy.

[0204] In the macrophage clearance experiment, CRLM model mice were divided into 3 groups and intraperitoneally injected with macrophage clearing agent clodronate liposomes (1.4 mg / 20 g body weight) (40335ES10, YEASEN) or an equal amount of PBS-liposomes twice a week. At the same time, nanoparticles siDicer1@M2pep-LNP or its control siNC@M2pep-LNP were administered as planned. Tumor growth and survival curves were monitored as described above. Flow cytometry and immunofluorescence analysis were used to evaluate the macrophage clearance effect and changes in immune cells in liver metastasis.

[0205] Example 12 Safety Evaluation of siDicer1 Nanoparticles

[0206] 1. Blood biochemical test

[0207] The peripheral blood of mice was collected into sodium heparin blood collection tubes, and the liver and kidney function indicators were detected using VITROS 5600 biochemical immune integrated analyzer.

[0208] 2. Hematoxylin-Eosin Staining (HE)

[0209] (1) Dewaxing of paraffin tissue to water: Place the sections in xylene I for 15 minutes → xylene II for 15 minutes → anhydrous ethanol I for 5 minutes → anhydrous ethanol II for 5 minutes → 95% alcohol for 5 minutes → 90% alcohol for 5 minutes → 80% alcohol for 5 minutes → 70% alcohol for 5 minutes → wash with distilled water.

[0210] (2) Hematoxylin staining of cell nuclei: The sections were placed in hematoxylin for 5 minutes, washed with tap water, differentiated with 1% hydrochloric acid alcohol for a few seconds, rinsed with tap water, blued with 1% ammonia water, and rinsed with running water.

[0211] (3) Eosin staining of cytoplasm: Place the sections in eosin staining solution for 5 minutes.

[0212] (4) Dehydration and sealing: Place the slices in 95% alcohol II for 15 minutes → anhydrous ethanol I for 10 minutes → anhydrous ethanol II for 10 minutes → xylene I for 10 minutes → xylene II for 10 minutes to dehydrate and make them transparent. Take the slices out of xylene and let them dry slightly, then seal the slices with neutral gum. Observe under a microscope after sealing.

[0213] Example 13 miRNA sequencing method

[0214] (1) Sample preparation: After 24 hours of IL-4 stimulation, the induced BMDM was added with siNC@M2pep-LNP and siDicer1@M2pep-LNP (siRNA-eq. 4 μg / mL) prepared in Preparation Example 1, and the cells were collected after culturing at 37°C 5% CO2 for 48 hours to extract total RNA. The total RNA was extracted using the TRIZOL method, and the steps were the same as those in Example 2. The total RNA was sent to Novogene Bioinformatics Technology Co., Ltd. (Beijing) for miRNA sequencing.

[0215] (2) The specific steps for library construction and sequencing are as follows:

[0216] ① Sample quality detection: a. Sequencing error rate distribution check; b. Summary of raw sequencing data quality; c. Sequencing data filtering; d. sRNA length screening; e. Public and unique sequence analysis library construction, quality control and sequencing.

[0217] ②Library construction and sequencing: After the sample is qualified, total RNA is used as input material and NEB Multiplex Small RNA Library Prep Set for (NEB E7300L) to generate sequencing libraries. Briefly, 3' and 5' adapters are first connected to the 3' and 5' ends of small RNA (sRNA), respectively. Then the first-strand cDNA is synthesized by hybridization with the reverse transcription primer. Double-stranded cDNA libraries are generated by PCR enrichment. After purification and size selection, libraries with insert fragments between 18 and 40 bp are ready for SE50 sequencing on the Illumina sequencing platform. Then, the library quality is evaluated on the Agilent 5400 system and quantified by qPCR. Qualified libraries are sequenced on the Illumina platform using the SE50 strategy based on the effective library concentration and the required data volume.

[0218] (3) Bioinformatics analysis process:

[0219] ① Quality control: First, the raw data in fastq format were processed by customized Perl and Python scripts. In this step, clean data were finally obtained by removing reads containing poly-N, 5' adapter contaminants, no 3' adapter or inserted tags containing poly A / T / G / C, and low quality; at the same time, the Q20, Q30 and GC content of the raw data were calculated; then a certain range of lengths were selected from the clean reads for downstream analysis.

[0220] ② Read mapping to the reference sequence: Use the Bowtie tool to map the sRNA tags to the reference sequence and analyze their expression and distribution on the reference sequence.

[0221] ③ Alignment of known miRNAs: The mapped sRNA tags were used to search for known miRNAs. Using the miRBase20.0 database as a reference, the modified miRDeep2 and srna-tools-cli software were used to obtain potential miRNAs and draw secondary structures. Custom scripts were used to obtain miRNA counts, as well as base preferences at the first position of miRNAs of a specific length and base preferences at each position of all identified miRNAs.

[0222] ④ Label removal: To remove labels from protein-coding genes, repetitive sequences, rRNA, tRNA, snRNA, and snoRNA, sRNA labels were mapped to RepeatMasker, Rfam database, or the data of the specified species itself.

[0223] ⑤ Prediction of new miRNAs: Predict new miRNAs using the hairpin structure features of miRNA precursors. By exploring secondary structures, Dicer cleavage sites, and sRNA tags, miREvo and mirdeep2 software are used to predict new miRNAs for the minimum free energy not annotated in the above steps. Custom scripts are also used to obtain miRNA counts, as well as the first position of a specific length and the base preference of each position of all identified miRNAs.

[0224] ⑥ sRNA annotation summary: Comprehensively analyze all alignments and annotations obtained previously. In previous alignments and annotations, some sRNA tags may be mapped to multiple categories. In order to map each unique sRNA to only one annotation, we follow the following rules (priority from large to small): known miRNA>rRNA>tRNA>snRNA>snoRNA>repeat>gene>NAT-siRNA>gene>new miRNA>ta-siRNA. The total rRNA ratio is used as a sample quality indicator. It is generally believed that the total rRNA ratio of high-quality samples should be less than 60% in plant samples and less than 40% in animal samples.

[0225] ⑦ miRNA editing analysis: The 2nd to 8th positions of mature miRNA are highly conserved and are called the seed region. The target of miRNA may vary with the change of nucleotides in this region. In our analysis process, miRNAs with possible base editing are detected by aligning all sRNA tags with mature miRNAs (allowing one mismatch).

[0226] ⑧ miRNA family analysis: Explore the occurrence of miRNA families identified in samples in other species. In our analysis process, known miRNAs use miFam.dat to search for families; new miRNA precursors are submitted to Rfam to search for Rfam families.

[0227] ⑨Target gene prediction: miRNA target gene prediction is performed through miRmap and microT, and the intersection is taken as the final targeting result.

[0228] ⑩ miRNA quantification: miRNA expression levels were estimated by transcripts per million (TPM). Normalized expression formula: Normalized expression = mapped read counts / total reads*1,000,000.

[0229] Differential expression of miRNAs: For samples with biological replicates, differential expression analysis between two conditions / groups was performed using the DESeq R package.

[0230] KEGG enrichment analysis was performed using clusterProfiler software.

[0231] Example 14 miRNA reverse transcription

[0232] The miRNA 1st Strand cDNA Synthesis Kit (by stem-loop) from Novagen Biotech was used to reverse the miRNA. The primer design was based on the Novagen primer design software miRNA Design to design the reverse transcription primer sequence:

[0233] mmu-miR-1981-5p (SEQ ID NO:15): 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACGCCACG-3'

[0234] mmu-miR-148a-3p (SEQ ID NO:16): 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACACAAAG-3'

[0235] mmu-miR-146b-5p (SEQ ID NO:17): 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAGCCTA-3'

[0236] mmu-miR-30a-5p (SEQ ID NO:18): 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTTCCA-3'

[0237] mmu-miR-30d-5p (SEQ ID NO:19): 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTTCCA-3'

[0238] Example 15 miRNA qPCR

[0239] The miRNA Universal SYBR qPCR Master Mix from Novazonics was used for miRNA real-time fluorescence quantitative PCR.

[0240] miRNA forward primer:

[0241] mmu-miR-1981-5p (SEQ ID NO:20): 5'-CGGTAAAGGCTGGGCTTAGA-3'

[0242] mmu-miR-148a-3p (SEQ ID NO:21): 5'-GCGCGTCAGTGCACTACAGAA-3'

[0243] mmu-miR-146b-5p (SEQ ID NO:22): 5'-CGCGTGAGAACTGAATTCCA-3'

[0244] mmu-miR-30a-5p (SEQ ID NO:23): 5'-CGCGTGTAAAACATCCTCGAC-3'

[0245] mmu-miR-30d-5p (SEQ ID NO:24): 5'-GCGTGTAAACATCCCCGAC-3'

[0246] Example 16 Synthesis of miRNA mimics and inhibitors and cell transfection

[0247] The miRNA mimics / inhibitor / NC sequence was synthesized by Guangzhou Ruibo Biotechnology Co., Ltd. The final concentration of mimics was 50 nM, and the final concentration of inhibitor was 100 nM. Lipofectamine RNAiMAX was used for transfection, and the steps were the same as in Example 3. Cells were collected 48 hours after transfection for total RNA or protein extraction. Western blotting analysis was then performed.

[0248] Effect Example 1: M2 TAMs are enriched and highly express Dicer in CRLM lesions

[0249] Immunofluorescence detection was performed on liver tissue samples of three CRLM patients and three CRLM mouse models constructed in Example 4, and M1 and M2 TAMs were marked with CD86 and CD163 (human) / CD206 (mouse), respectively. Figure 4 As shown in A and D, the liver metastatic lesions of CRLM patients and mouse models are rich in TAMs, and the vast majority are M2 TAMs (human: CD163 + Cells, mouse: CD206 + In contrast, there are more M1 macrophages (CD86 + cell).

[0250] ImageJ software was used to gate the M1 and M2 TAMs in the lesion area and analyze the difference in Dicer protein expression between them. The results showed that regardless of CRLM patients ( Figure 4 BC) or mouse model ( Figure 4 (EF) The Dicer fluorescence intensity in M2 TAMs within the lesion was significantly higher than that in M1 TAMs (P<0.05; P<0.01).

[0251] Effect Example 2 Dicer expression is associated with different polarization states of macrophages

[0252] RAW264.7 and BMDM cells were induced into M1 and M2 macrophages according to the method of Example 2, and characterized by the pro-inflammatory cytokine IL-12 and the anti-inflammatory cytokine IL-10. On this basis, we used qPCR to measure the mRNA levels of Dicer1, IL-12 and IL-10 in macrophages of different polarization states. The results showed that compared with M0 (unpolarized) macrophages (RAW264.7 and BMDM), the mRNA expression levels of Dicer1 and IL-10 in M1 macrophages were reduced, and the mRNA expression level of IL-12 was increased ( Figure 6 In M2 macrophages, the expression levels of Dicer1 and IL-10 mRNA increased, and the expression level of IL-12 mRNA decreased ( Figure 6 (middle AB).

[0253] Western blotting results also showed that compared with M0 macrophages (RAW264.7 and BMDM), Dicer protein expression was decreased in M1 macrophages and increased in M2 macrophages ( Figure 6 Middle C).

[0254] Effect Example 3 Knockdown of Dicer affects macrophage proliferation

[0255] To clarify the effect of Dicer on macrophage growth, we used the CRISPR-Cas9 system to construct a Dicer knockdown (Knockdown, KD) stable macrophage cell line (Dicer-KD RAW264.7). The specific experimental method is the same as Example 3. First, CRISPR-Cas9 lentiviral plasmids with different sgRNA sequences were designed and constructed, and the negative control sgRNA sequence was used as the control group.

[0256] The genomic sequences targeted by sgRNA are as follows:

[0257] sgRNA1 (SEQ ID NO:25): 5'-AGAACCCGAGAATTGCCTGA-3'

[0258] sgRNA2 (SEQ ID NO:26): 5'-AGGTACGTATTACTCAGTAG-3'

[0259] After being successfully packaged into lentivirus, RAW264.7 was transfected. After drug resistance screening, monoclonal cells were finally selected and expanded for culture. Figure 7 As shown in Figure A, CCK-8 results showed that the proliferation of Dicer-KDRAW264.7 was significantly slower than that of the control (Vector). However, the results of Western blotting showed that the expression of apoptosis-related protein cleaved caspase-3 in cells did not increase significantly ( Figure 7 In addition, flow cytometry analysis did not reveal that Dicer knockdown significantly increased the number of apoptotic cells ( Figure 7 C). Based on this, we speculated that Dicer may affect the proliferation of RAW264.7 cells by regulating the cell cycle. By flow cytometry analysis, we found that compared with the control (Vector), Dicer-KD RAW264.7 cells underwent G0 / G1 phase arrest, which was manifested by an increase in the G0 / G1 phase ratio and a decrease in the S and G2 / M phase ratios ( Figure 7 Effect Example 4: Knockdown of Dicer to reprogram M2 macrophages

[0260] To further clarify the effect of Dicer expression on the functional phenotype of macrophages, the methods in Examples 2 and 3 were used to first stimulate Vector and Dicer-KD RAW264.7 cells with IL-4 for 24 hours. Western blotting results showed that compared with Vector, Dicer-KD RAW264.7 cells had increased expression of the pro-inflammatory factor IL-1β and decreased expression of the anti-inflammatory factor IL-10 ( Figure 8 (A).

[0261] From the results of cell proliferation and western blotting, we found that the effects of the two sgRNAs on RAW264.7 were basically the same, but the effect of sgRNA2 was more obvious. Therefore, the Dicer-KD macrophages described below are cell lines knocked down by sgRNA2. After 24 hours of stimulation of Vector and Dicer-KD RAW264.7 cells with IL-4, qPCR results showed that knocking down Dicer could significantly increase the mRNA levels of M1 macrophage-related factors IL-6, IL-12, and IL-1β, and reduce the mRNA levels of M2 macrophage-related cytokines IL-10, TGF-β1, and Mgl1 ( Fig. 9 Flow cytometry results showed that compared with Vector, the expression of CD206 in Dicer-KD RAW264.7 cells was decreased, and the expression of CD86 was increased ( Fig.10 (middle AB).

[0262] Subsequently, we verified the function of Dicer in primary macrophages (BMDM). After BMDM was successfully induced, IL-4 was added for 24 hours, and Dicer1 siRNA was transfected using Lipofectamine RNAiMAX. Western blotting results showed that Dicer1 siRNA successfully knocked down the expression of Dicer protein in BMDM ( Figure 8 Middle B); and compared with the control (siNC), knockdown of Dicer increased the expression of the pro-inflammatory factor IL-1β and decreased the expression of the anti-inflammatory factor IL-10 in BMDM ( Figure 8 (middle B).

[0263] The siRNA sequence of the mouse Dicer1 gene used in this study was synthesized by Genema Biotechnology (Shanghai) Co., Ltd. The sequence is as follows:

[0264] Negative control (SEQ ID NO: 27): 5'-TTCTCCGAACGTGTCACGTTT-3' (sense strand)

[0265] Negative control (SEQ ID NO: 28): 5'-ACGTGACACGTTCGGAGAATT-3' (antisense strand)

[0266] Dicer1-siRNA-1 (SEQ ID NO: 29): 5'-GGUGCUCCCAGUAAUCAAATT-3' (sense strand)

[0267] Dicer1-siRNA-1 (SEQ ID NO: 30): 5'-UUUGAUUACUGGGAGCACCTT-3' (antisense strand)

[0268] Dicer1-siRNA-2 (SEQ ID NO: 31): 5'-GGGAAAGAGACUGUUAAAUTT-3' (sense strand)

[0269] Dicer1-siRNA-2 (SEQ ID NO: 32): 5'-AUUUAACAGUCUCUUUCCCTT-3' (antisense strand)

[0270] Dicer1-siRNA-3 (SEQ ID NO: 33): 5'-GAGCGCCGAUCUCUAAUUATT-3' (sense strand)

[0271] Dicer1-siRNA-3 (SEQ ID NO: 34): 5'-UAAUUAGAGAUCGGCGCUCTT-3' (antisense strand) Due to the reasons of the sequence list making software, "U" was replaced by "T" when making the sequence list. The specific sequence information shall be subject to the description in the manual.

[0272] Since the knockdown efficiency of siDicer1-3 is better than that of siDicer1-1 and siDicer1-2, siDicer1-3 will be selected for subsequent experiments (represented by siDicer1). qPCR results showed that knockdown of Dicer in M2 BMDMs could significantly increase the mRNA levels of pro-inflammatory factors IL-6, IL-12, and IL-1β, and reduce the mRNA levels of anti-inflammatory factors IL-10, TGF-β1, and Mgl1 ( Fig. 9 B). Flow cytometry results showed that compared with the control (siNC), knockdown of Dicer significantly reduced the expression of CD206 on M2 BMDM and increased the expression of CD86 ( Fig.10 Effect Example 5: Antitumor Effect of Dicer-KD Macrophages in Vivo and in Vitro

[0273] 1. In vitro tumor inhibition effect of Dicer-KD macrophages

[0274] To preliminarily determine whether Dicer knockdown macrophages can inhibit the growth of colon cancer cells, CT26 cells were plated in advance in the lower chamber of the transwell co-culture chamber (24-well plate), with 100,000 cells plated per well. After the colon cancer cells adhered to the wall, macrophages stimulated with IL-4 for 24 hours were plated in the upper chamber of the co-culture chamber, with 100,000 cells plated per well, and cultured in DMEM complete medium for 48 hours. CT26 cells were digested and re-plated in 96-well plates, and the proliferation of colon cancer cells was detected by CCK-8 ( Fig.11 A). As follows Fig.11 As shown in B, compared with the control group (Vector+CT26), the proliferation ability of CT26 cells in the Dicer-KD+CT26 group was significantly weakened (P<0.001).

[0275] 2. In vivo tumor inhibition effect of Dicer-KD macrophages

[0276] The IL-4-stimulated Vector and Dicer-KD RAW264.7 cells were mixed with CT26 cells and injected subcutaneously using the method of Example 4. The results showed that compared with the control group (Vector+CT26), the subcutaneous tumor growth of mice in the Dicer-KD+CT26 group was slower ( Fig.12AC) (P<0.05). The immunohistochemical results showed that compared with the control group (Vector+CT26), the Ki67 and CD206 scores in the subcutaneous tumor tissues of mice in the Dicer-KD+CT26 group were reduced ( Fig.12 (in DF).

[0277] Effect Example 6 Construction of LNPs that can target M2 TAMs (M2pep-LNP)

[0278] The long circulation ability of nanoparticles in the blood circulation is closely related to the particle size of the nanoparticles. Studies have shown that nanoparticles with a particle size greater than 500nm do not have an enhanced permeability and retention effect (EPR) and are easily cleared by macrophages in the blood; while nanoparticles with a particle size greater than 1μm will be retained in the capillaries of the liver and lungs; but nanoparticles that are too small (such as less than 10nm) are easily metabolized by the kidneys and have almost no selectivity for lesions and cells, so nanoparticles of 10 to 500nm are considered to be the particle size range that will produce a relatively good EPR effect.

[0279] First, in order to prepare suitable siRNA@LNP, we kept the flow rate and flow rate of the liquid in the microfluidic chip unchanged, adjusted the mass ratio of siRNA and Dlin-MC3-DMA (RNA / MC3, μg / mg), and characterized the prepared nanoparticles using the method in Example 5. The results showed that when RNA / MC3 was in the range of 2.5 to 30, the particle size of siRNA@LNP was in the range of 150 to 210 nm, and the PDI was in the range of 0.1 to 0.3, the potential was negative ( Fig.13 (in AC).

[0280] In order to further clarify the optimal synthesis conditions of M2pep-LNP within the above concentration range, we synthesized M2pep-LNP according to the three ratios of RNA / MC3 of 10, 20 and 30, while keeping the molar ratio of DSPE-PEG-M2pep to DMG-PEG2000 at 1:1. DLS results showed that the particle size of the three nanoparticles was between 150 and 300 nm, but the nanoparticle size of RNA / MC3=10 was the smallest ( Fig.14 The Zetapotential results showed that the potential of the nanoparticles with RNA / MC3=30 was significantly reduced ( Fig.14 Therefore, considering comprehensively, we selected RNA / MC3=10 to prepare siRNA@LNP and siRNA@M2pep-LNP.

[0281] Subsequently, we further explored the effects of different DSPE-PEG2000-M2pep / DMG-PEG2000 molar ratios (1:1, 0.5:1.5, 1.5:0.5) on the targeting of M2pep-LNP (M2pep-LNP was defined as 1, 2, and 3, respectively). The prepared DiI@M2pep-LNP was co-incubated with M2 BMDM for 1 hour (stimulated with IL-4 for 24 hours). Fluorescence microscopy results showed that compared with M2pep-LNP2 and 3, M2pep-LNP1 was internalized more by M2 BMDM, increasing by 1.5 times and 2.3 times, respectively (P < 0.05) ( Fig.15 AB), indicating that when the molar ratio of DSPE-PEG2000-M2pep to DMG-PEG2000 in the lipid solution is 1:1, the prepared M2pep-LNP has the best targeting effect on M2 macrophages.

[0282] We then observed the stability of the nanoparticles at 4°C. Fig.16 As shown in Figures AD, the particle size and PDI of the prepared nanoparticles changed little within 3 days, and the potential did not change significantly, showing good stability.

[0283] In order to intuitively understand the morphology of the nanoparticles, we used cryo-electron microscopy to observe their morphological characteristics under an electron microscope. The results showed that the prepared nanoparticles were spherical, uniform in morphology, and the particle size was basically consistent with the results measured by DLS. The surface modification of LNP with M2pep did not significantly affect the morphology and particle size of LNP ( Fig.16 (A).

[0284] The loading capacity of nanoparticles is an important property of drug delivery systems, and is of great significance for the selection of drug delivery methods and dosage conversion. In this paper, Ribogreen Assay was used to detect and calculate the RNA encapsulation efficiency in nanoparticles. The results showed that the encapsulation efficiencies of the prepared siRNA@LNP and siRNA@M2pep-LNP were 94±0.11% and 95±0.12%, respectively.

[0285] Effect Example 7: In vitro verification of nanoparticle uptake by macrophages in different polarization states

[0286] In order to determine whether M2pep-LNP exhibits a stronger targeting effect on M2 macrophages, we used the method of Example 6 to induce BMDM into M1 and M2 macrophages with LPS and IL-4, respectively. Then, appropriate amounts of DiI-labeled LNP and M2pep-LNP (DiI final concentration 1 μM) prepared in Preparation Example 2 were added, and fluorescence microscopy showed that there was no significant difference in DiI fluorescence intensity between LNP and M2pep-LNP in M1 BMDM (P>0.05); however, in M2 BMDM, compared with LNP, M2pep-LNP was more taken up by cells, increasing by nearly 2 times (P<0.001) ( Fig.17 (middle AB).

[0287] In the RAW264.7 cell line, we used the same method to induce it into M1 and M2 macrophages, and observed the uptake of nanoparticles by macrophages in different polarization states under fluorescence microscopy after co-culture with DiI-labeled nanoparticles. Fig.18 As shown in Figures AB, compared with LNP, M2pep-LNP was more absorbed by M2-type RAW264.7 cells, increasing by nearly 1.7 times (P<0.01); while there was no significant difference in the uptake of the two nanoparticles by M1-type RAW264.7 cells (P>0.05).

[0288] Flow cytometry was further used to analyze the uptake of the two nanoparticles by RAW264.7 cells in different polarization states. The results were consistent with the fluorescence microscopy results: compared with LNP, M2pep-modified LNP was more uptaken by M2-type RAW264.7 cells ( Fig.19 (in AC).

[0289] Effect Example 8 Uptake of different nanoparticles by M2 TAMs and spleen macrophages in vitro

[0290] To further clarify whether M2pep-LNP has good targeting to M2 TAMs and M2 macrophages in the spleen of CRLM mice, we constructed a liver metastasis mouse model and prepared single cell suspensions of liver metastasis tissues and spleen tissues. Using the method of Example 6, they were co-incubated with DiD@LNP and DiD@M2pep-LNP prepared in Preparation Example 2, respectively. Flow cytometry was used to analyze the M2 TAMs and M2 macrophages in the spleen (CD11b + F4 / 80 + CD206 + ) for the uptake of the two nanoparticles. The results are as follows Fig. 20As shown in Figures AB, compared with the LNP group, the DiD fluorescence intensity in M2 TAMs and spleen M2 macrophages in the M2pep-LNP group was higher (P<0.05). Effect Example 9 In vitro verification of the ability of different nanoparticles to deliver siRNA to macrophages

[0291] The process by which cells engulf LNPs and release RNA, thereby allowing RNA to exert its effects within the cell, is quite complex. LNPs first interact with the cell membrane. This interaction may be mediated by specific receptors, or may be due to the high affinity of the lipid composition of LNPs to the cell membrane. After LNPs are internalized by cells, endosomes containing LNPs are formed, which fuse with early endosomes and develop into late endosomes or lysosomes, and the pH value in the endosomes decreases. Subsequently, the LNPs rupture or structural reorganization occurs, and the RNA in the LNPs is released and escapes into the cytoplasm, thereby exerting physiological functions. Therefore, in order to further verify the difference in siRNA delivery efficiency between the two LNPs, we encapsulated FAM-labeled siRNA in LNPs and M2pep-LNPs. The specific operating method is the same as in Example 7, and M1 and M2 BMDMs are transfected respectively. As shown in FIG. Fig.21 As shown in Figures AB, fluorescence microscopy revealed no significant difference in the FAM fluorescence intensity of the two nanoparticles in M1 BMDM (P>0.05), while in M2 BMDM, the intracellular FAM fluorescence intensity of M2pep-LNP-transfected cells was significantly higher than that of LNP, increasing by nearly 4 times (P<0.01). In M2 BMDM, we further used flow cytometry to analyze the differences in siRNA delivery capabilities of different nanoparticles, and the results were consistent with the fluorescence microscopy results. Fig. 22 As shown in center AC, the FAM fluorescence intensity in M2 BMDMs transfected with M2pep-LNP was higher than that with LNP (P<0.001).

[0292] Effect Example 10 Distribution of Nanoparticles in Mice

[0293] First, after we successfully constructed the CRLM mouse model, we injected two nanoparticles labeled with DiR through the tail vein, and observed the DiR fluorescence intensity of the mouse liver at 2 hours, 8 hours, 12 hours and 24 hours by IVIS. The specific operation was the same as in Example 8. The results showed that from 2 hours to the end of the 24-hour observation, the average DiR fluorescence intensity in the liver of the mice in the M2pep-LNP group was higher than that in the LNP group (8 hours P < 0.05) ( Fig.24 After 8 hours and 24 hours of observation, some mice were killed and their hearts, livers, spleens, lungs, and kidneys were removed for in vitro live imaging. The results showed that at 8 hours ( Fig.25 AB) and 24 hours ( Fig.26At the two time points (center AB), the average fluorescence intensity of DiR in the liver of metastatic tumors in the M2pep-LNP group was higher than that in the LNP group (all P<0.05), indicating that M2pep modification can increase the enrichment of LNP in the liver of metastatic tumors.

[0294] In unmodeled mice, we used the same method to observe the distribution of the two nanoparticles in vivo at different time points. The results showed that there was no statistical difference in the average fluorescence intensity of DiR in the liver area between the M2pep-LNP group and the LNP group at each time point (all P>0.05) ( Fig. 27 After 24 hours of imaging, the organs were dissected and IVIS also did not find significant differences in the organ distribution of the two nanoparticles (all P>0.05) ( Fig. 27 Medium CD).

[0295] Effect Example 11 Distribution of Nanoparticles in TAMs of Mouse CRLM Lesions

[0296] After the CRLM mouse model was successfully constructed, the mice were divided into two groups: Cy3-Si@LNP and Cy3-Si@M2pep-LNP. The mice were killed 6 hours after administration, and the liver tumor tissue was taken to prepare a tumor single cell suspension. The expression level of Cy3 in different cell subpopulations in the tumor tissue was analyzed by flow cytometry. The specific operation method was the same as Example 9. The results showed that 28.80±4.93% of macrophages in the LNP group expressed Cy3, which was significantly lower than that in the M2pep-LNP group (53.09±12.88%) (P<0.05) ( Fig.28 AB). CD206 was further used to label M2 TAMs. The results showed that 34.39±3.88% of M2 TAMs in the LNP group expressed Cy3, while the expression in the M2pep-LNP group was as high as 61.44±12.85%, with a significant difference between the two groups (P<0.05) ( Fig.28 AB). Cy3 expression in DCs and T cells was relatively low, and there was no statistical difference between the two groups (P>0.05) ( Fig.28 IF detection was performed on liver tissue to analyze the expression of Cy3 in TAMs of tumor tissue. The results also showed that Cy3 in the M2pep-LNP group + The proportion of TAMs was significantly increased compared with the LNP group (55.63±12.61% vs. 29.10±10.09%, P<0.05) Fig.28 CD), indicating that M2pep-LNP has targeting effect on M2 TAMs.

[0297] Effect Example 12: siDicer1 nanoparticles reprogram M2 macrophages in vitro

[0298] To further clarify the silencing efficiency of siDicer1 nanoparticles on target genes and the reprogramming effect of macrophages, we co-incubated the nanoparticles prepared in Preparation Example 1 with M2 BMDM. Fig.29 As shown in Figures AB, both nanoparticles can significantly reduce the expression levels of Dicer1 mRNA and protein in macrophages, and the knockdown efficiency of siDicer1@M2pep-LNP is significantly better than that of siDicer1@LNP (P<0.001). At the same time, we also found that both nanoparticles can increase the expression of proinflammatory factors IL-12 and IL-1β, and reduce the expression of IL-10 ( Fig.29 (middle AB).

[0299] Effect Example 13: siDicer1 Nanoparticles Inhibit CRLM Growth

[0300] as follows Fig.30 As shown in A, 3 days after the establishment of CRLM model in mice, the tumor-bearing mice were divided into 4 groups: siNC@LNP, siNC@M2pep-LNP, siDicer1@LNP and siDicer1@M2pep-LNP. The tumor inhibition experiment started on the 3rd day after modeling (the modeling time was recorded as day -3). Each tumor-bearing mouse was injected with 200 μL of drug-containing solution (siRNA-eq. 0.75 mg / kg per mouse) through the tail vein, and drug treatment was given on D0, D2 and D4, respectively. On the 0th day, 4th day, 8th day and 12th day of the first administration, the growth of liver metastases in mice was indirectly observed by IVIS. The survival status of mice was recorded every day, and the animals were judged to be dead when any of the following conditions occurred in the mice: animal death or severe ascites, tumor burden exceeding 10% of body weight or rapid loss of 15-20% of the original body weight. All mice were killed after imaging was completed on the 12th day, and the body weight and liver weight of the mice were weighed. The main organs (heart, liver, spleen, lung, and kidney) were washed with pre-cooled PBS and then immersed in 4% paraformaldehyde solution for pathological staining. Whole blood was collected from mice for blood biochemical detection.

[0301] Tumor growth was monitored by small animal in vivo imaging. The results showed that the tumors in the two groups of mice given siNC@LNP and siNC@M2pep-LNP grew rapidly, increasing by 20 times and 14 times respectively on the 12th day; while the tumors in the siDicer1@LNP and siDicer1@M2pep-LNP groups grew slowly (increasing by 4.4 times and 1.4 times respectively), and siDicer1@M2pep-LNP had a better tumor inhibition effect ( Fig.30 Compared with other treatment groups, the relative liver weight of tumor-bearing mice in the siDicer1@M2pep-LNP group was the lowest (10.96±2.61%) ( Fig.30HE showed that the liver metastases in the siNC@LNP and siNC@M2pep-LNP groups were diffuse, occupying 54.59±22.64% and 56.12±20.84% ​​of the liver, respectively, while the tumor size and range in the siDicer1 nanoparticle group, especially the siDicer1@M2pep-LNP group, were significantly reduced (20.80±2.87% in the siDicer1@LNP group and 8.25±5.71% in the siDicer1@M2pep-LNP group) ( Fig.30 FG in the middle). Overall survival analysis showed that compared with siNC@LNP, the siDicer1@LNP group and siDicer1@M2pep-LNP treatment significantly increased the median survival days of tumor-bearing mice (by 2.5 and 5.5 days, respectively) ( Fig.30 The above results suggest that targeted silencing of the Dicer1 gene in M2 TAMs can significantly inhibit tumor growth in tumor-bearing mice and prolong the survival of mice.

[0302] After the tumor inhibition experiment, we selected tumor nodules with larger size from each group, extracted tissue proteins and performed western blot analysis. The results showed that siDicer1 nanoparticles could significantly reduce the expression of Dicer and anti-inflammatory factor IL-10 in tumor tissues, especially in the siDicer1@M2pep-LNP group ( Fig.30 Middle I).

[0303] Effect example 14 siDicer1@M2pep-LNP reshapes the tumor immune microenvironment by reprogramming M2 TAMs

[0304] To further explore whether siDicer1 nanoparticles inhibit CRLM growth by reprogramming M2 TAMs and reshaping the tumor immunosuppressive microenvironment, we used flow cytometry to detect the number of macrophages, MDSCs, DCs, and T cell subsets in the tumor immune microenvironment and spleen. The following figure shows the gating strategy for flow cytometry analysis ( Fig.31 and Fig.32 ). According to the method in Example 10, liver metastases and spleen immune cells were detected by flow cytometry.

[0305] as follows Fig.33 As shown in the figure, flow cytometry results showed that the number of M2 TAMs in liver metastasis tissues was significantly reduced after siDicer1@M2pep-LNP treatment, and the number of M1 TAMs and CD8 + The number of T cells increased significantly, but did not affect the total number of macrophages, DCs, MDSCs, and total CD4 +In addition, we also analyzed the spleen immune microenvironment, and the results were similar to those of the liver tumor immune microenvironment. siDicer1 nanoparticles, especially siDicer1@M2pep-LNP, could significantly reduce the number of M2 macrophages and Treg cells, and increase the number of M1 macrophages and CD8 + T cell counts, but not total macrophages, DCs, MDSCs, total CD4 + There was no significant effect on T cell numbers ( Fig.34 ).

[0306] as follows Fig.35 As shown in the figure, tissue immunofluorescence results showed that the number of M2 TAMs in liver metastasis tissues was significantly reduced after siDicer1@M2pep-LNP treatment, while the number of M1 TAMs and CD8 + The number of T cells increased significantly, which was consistent with the flow cytometry results.

[0307] Effect Example 15 The anti-tumor effect of siDicer1@M2pep-LNP in CRLM is largely dependent on macrophages

[0308] To clarify whether the antitumor effect of siDicer1 nanoparticles is partially dependent on the macrophage phenotype switch mediated by Dicer1 targeted silencing, CRLM model mice were treated with in vivo macrophage depletion twice a week and received different treatments according to the schedule ( Fig.36 In vivo imaging and survival curve analysis showed that the antitumor effect mediated by siDicer1@M2pep-LNP was greatly attenuated in CRLM mice treated with macrophage depletion, as manifested by increased tumor growth and shortened survival time compared with the PBS+siDicer1@M2pep-LNP group ( Fig.36 Liver tissue weight and HE staining also showed that macrophage depletion therapy increased the tumor size and range of CRLM model mice during siDicer1@M2pep-LNP treatment. Flow cytometry and immunofluorescence staining results confirmed that F4 / 80 in the liver metastases of mice receiving macrophage depletion therapy + Macrophages did decrease ( Fig.37 AC, F). In addition, we observed that M1-like macrophages and CD8 + T cell infiltration is low ( Fig.36Taken together, our data suggest that the antitumor effect of siDicer1@M2pep-LNP in CRLM is at least partly achieved by reprogramming M2 TAMs in the TME.

[0309] Effect Example 16 Safety Evaluation of siDicer1 Nanoparticles

[0310] The potential toxicity of nanoparticles remains a major concern for clinical translation. HE staining of the important organs (heart, spleen, lung, and kidney) of four groups of mice was performed to evaluate whether the nanoparticles could cause histological damage. The results showed that neither siDicer1@LNP nor siDicer1@M2pep-LNP had any damage to the major organs ( Fig.38 The liver function [alanine aminotransferase (ALT) and serum aspartate aminotransferase (AST)] and renal function [blood urea nitrogen (BUN) and creatinine (Cre)] of mice were tested, and the results showed that there was no significant change in the above indicators in all treatment groups ( Fig.38 The results suggest that the siRNA delivery system targeting Dicer1 gene does not cause obvious toxic side effects and has good biocompatibility.

[0311] Effect Example 17 miRNA sequencing and candidate miRNA screening and verification

[0312] According to the method of Example 13, we performed miRNA sequencing analysis on Dicer knockdown M2 BMDM. Fig.39 As shown in the volcano plot in Figure A, we obtained a total of 74 up-regulated genes and 55 down-regulated genes using |log2(FC)|>0.5 and P<0.05 as the screening criteria. According to the macrophage miRNA expression abundance dataset in the MiRbase database (ER0000000235), we intersected the miRNAs highly expressed in macrophages with the 55 down-regulated miRNAs screened previously; the screened miRNAs were further narrowed down using |log2(FC)|>1 and P<0.05 as the criteria, and finally 5 candidate miRNAs (miR-148a-3p, miR-146a-5p, miR-30a-5p, miR-30d-5p, miR-1981-5p) were obtained ( Fig.39 (middle B).

[0313] These five miRNAs were validated by miRNA qPCR in Dicer-KD M2 BMDM and RAW264.7 cells. The results showed that miR-148a-3p and miR-1981-5p changed consistently in both cells. Knockdown of Dicer could significantly downregulate the expression levels of miR-148a-3p and miR-1981-5p in macrophages ( Fig.39 CD), suggesting that they may be potential targets of Dicer-regulated macrophage reprogramming.

[0314] We predicted the target genes of these two miRNAs in the miRmap and microT databases, and took the intersection of the prediction results of the two databases. The results showed that miR-148a-3p and miR-1981-5p regulated 158 and 143 target genes, respectively ( Fig.40 The KEGG pathway enrichment was performed on these 158 and 143 genes, and the results showed that the Akt signaling pathway was the most significantly enriched signaling pathway among the potential target genes of the two miRNAs ( Fig.40 Chinese BC).

[0315] Effect example 18 miR-148a-3p and miR-1981-5p regulate Akt signaling pathway to reprogram M2 macrophages

[0316] Based on this, we designed corresponding mimics and inhibitors for miR-148a-3p and miR-1981-5p sequences. In IL-4-stimulated BMDM and RAW264.7 cells, we found that both miR-148a-3p and miR-1981-5 inhibitors could significantly reduce the expression of the anti-inflammatory factor IL-10, increase the expression of the pro-inflammatory factor IL-1β, and down-regulate the expression of p-Akt. In contrast, both miR-148a-3p and miR-1981-5p mimics could significantly increase the expression of the anti-inflammatory factor IL-10, reduce the expression of the pro-inflammatory factor IL-1β, and increase the expression of p-Akt ( Fig.41 AB and Fig.42 On this basis, we further complemented miR-148a-3p and miR-1981-5p mimics in IL-4-stimulated Dicer-KD RAW264.7. qPCR results showed that the expression of pro-inflammatory factors in macrophages was reduced, while the expression of anti-inflammatory factors was increased ( Fig.43 The above results indicate that miR-148a-3p and miR-1981-5p may be one of the targets of Dicer in regulating macrophage reprogramming, and their reduced expression may promote macrophage polarization to M1 type by inhibiting Akt signaling pathway.

[0317] Comparative Example 1: In vitro verification of the ability of different nanoparticles to deliver siRNA to fibroblasts and colon cancer cells

[0318] To analyze the efficiency of siRNA delivery of M2pep-modified LNP to other cells in tumor tissue, we selected fibroblast NIH 3T3 cells and colon cancer cells CT26 as research objects. Fibroblasts are an important component of TME and can directly interact with nanoparticles, thereby affecting the distribution of nanoparticles. The specific operation method is the same as Example 7. In this study, we found that compared with LNP, the FAM fluorescence intensity of M2pep-LNP in 3T3 cells was significantly weakened (P<0.05) ( Fig.23 AB); however, there was no significant difference in the FAM fluorescence intensity of the two nanoparticles in CT26 cells (P>0.05) ( Fig.23 Medium CD).

[0319] By fluorescently labeling M2pep-LNP or siRNA, the targeting properties of the nanoparticles in vivo and in vitro were analyzed. The results showed that M2pep modification could significantly increase the targeting of LNP to M2 macrophages and TAMs, but would not affect the distribution of LNP in colon cancer cells, DCs and T cells.

[0320] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. Use of Dicer as a marker in the preparation of products for the diagnosis, prevention and / or treatment of tumor liver metastasis.

2. Application of Dicer as a target in the preparation of products for preventing and / or treating tumor liver metastasis.

3. Application of Dicer knockdown in promoting the reprogramming of M2 macrophages into M1 macrophages.

4. siRNA for knocking down Dicer expression, characterized in that include: The sense strand has the nucleotide sequence shown in SEQ ID NO: 29; the antisense strand has the nucleotide sequence shown in SEQ ID NO: 30; or The sense strand has the nucleotide sequence shown in SEQ ID NO:31; the antisense strand has the nucleotide sequence shown in SEQ ID NO:32; or The sense strand has the nucleotide sequence shown in SEQ ID NO:33; the antisense strand has the nucleotide sequence shown in SEQ ID NO:

34.

5. A drug system targeting M2 macrophages, characterized in that: The method includes encapsulating siRNA in LNP modified by M2pep to obtain the drug system siRNA@M2pep-LNP.

6. The drug system according to claim 5, characterized in that The siRNA comprises: The sense strand has the nucleotide sequence shown in SEQ ID NO: 29; the antisense strand has the nucleotide sequence shown in SEQ ID NO: 30; or The sense strand has the nucleotide sequence shown in SEQ ID NO:31; the antisense strand has the nucleotide sequence shown in SEQ ID NO:32; or The sense strand has the nucleotide sequence shown in SEQ ID NO:33; the antisense strand has the nucleotide sequence shown in SEQ ID NO:

34.

7. The method for preparing the pharmaceutical system according to claim 5 or 6, characterized in that: The steps include: Step 1, dissolving Dlin-MC3-DMA, DSPC, Cholesterol, DMG-PEG2000, and DSPE-PEG2000-M2pep in anhydrous ethanol solution to obtain a lipid solution of Dlin-MC3-DMA containing M2pep; Dissolve siRNA in sodium citrate buffer to obtain siRNA buffer; Step 2: Mix the lipid solution and the siRNA buffer solution, and allow the lipids to self-assemble to form the drug system siRNA@M2pep-LNP encapsulating siRNA.

8. The preparation method according to claim 7, characterized in that: The mass ratio of the siRNA to the Dlin-MC3-DMA includes (2.5-30) μg:1 mg; the molar ratio of the DSPE-PEG2000-M2pep to the DMG-PEG2000 includes (1:1)-(1.5:0.5).

9. Use of any of the following in the preparation of a drug for preventing and / or treating tumor liver metastasis: (I), the siRNA as claimed in claim 4; and / or (II), a pharmaceutical system as claimed in claim 5 or 6; and / or (III) A pharmaceutical system prepared by the preparation method according to claim 7 or 8.

10. The use according to claim 9, characterized in that The applications include: (I) promoting the reprogramming of M2 macrophages into M1 macrophages; and / or (II), up-regulating the expression of IL-1β, IL-6, and IL-12; and / or (III), down-regulating the expression of IL-10, TGF-β1, and Mgl1; and / or (IV) Increase CD8 in the tumor microenvironment + T cell count; and / or (V) Inhibit the proliferation of colon cancer cell CT26.

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