Use of gata3 inhibitor and pd1 inhibitor in preparation of drugs for treating breast cancer

Abstract

The application relates to application of a GATA3 inhibitor and a PD1 inhibitor in preparation of a drug for treating breast cancer and belongs to the technical field of biological medicines. The application discloses application of a GATA3 inhibitor and a PD1 inhibitor in preparation of a drug for treating breast cancer. GATA3 mediates transcriptional regulation of IFN beta by inhibiting enhancer activity of IFNB1, down-regulates a type I interferon signal channel, inhibits an MHC-I antigen presentation channel of breast cancer cells and secretion of a chemotactic factor CCL5, reduces immune recognition, and achieves the purpose of immune escape. The immunotherapy of the breast cancer treated by the GATA3 inhibitor combined with the PD1 inhibitor can effectively treat breast cancer mice, improve IFN beta level in the mice, promote an MHC-I antigen presentation channel of the mice, improve CCL5 level in the mice, improve CD8+ T cell level in a tumor immune microenvironment, thereby reducing tumor occurrence and inhibiting tumor growth.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to the application of GATA3 inhibitors and PD1 inhibitors in the preparation of drugs for treating breast cancer. Background Technology

[0002] Breast cancer (BC) is one of the most common cancers. Based on the expression of breast cancer cell surface receptors—estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2)—breast cancer can be classified into four molecular subtypes: luminal A, luminal B, HER2-positive, and triple-negative breast cancer (TNBC). Luminal A and luminal B, collectively known as hormone receptor (HR)-positive breast cancer, are the most common subtypes, accounting for approximately 75% of all cases.

[0003] Although the prognosis for early-stage HR-positive breast cancer patients with endocrine therapy is generally good, approximately 30%–40% experience systemic recurrence, and about 10% develop new metastatic breast cancer (MBC). Currently, HR-positive breast cancer with MBC (HR+MBC) is primarily treated with endocrine therapy and chemotherapy. Despite attempts at new treatments, patients gradually develop endocrine resistance over time, and almost all women with HR+MBC die from the disease. Therefore, significant efforts are still needed to explore new therapies, either alone or in combination, to reduce recurrence rates and improve overall survival. Currently, targeting immune checkpoints by blocking programmed cell death 1 (PD-1) and / or programmed cell death 1 ligand 1 (PD-L1) is one of the most promising cancer therapies and has been shown to improve progression-free survival in patients with TNBC. The KEYNOTE-012 trial was the first phase Ib trial to evaluate the role of the anti-PD-1 inhibitor pembrolizumab monotherapy in TNBC. The results showed an overall response rate (ORR) of 18.5% and a median duration of response of 17.9 weeks. The phase II KEYNOTE-086 trial showed an ORR of 21.4% for PD-L1 therapy. In a randomized phase II study of 88 HR+MBC patients investigating the efficacy of eribulin mesylate in combination with pembrolizumab, similar ORR and median progression-free survival (PFS) were observed in the PD-L1-positive subgroup, with no benefit observed from pembrolizumab. Studies suggest that HR-positive breast cancer patients are not very sensitive to immunotherapy. This may be because, compared to TNBC and HER2-positive breast cancer, HR-positive breast cancer exhibits less immune infiltration and fewer somatic mutations, making it less likely for tumor mutations to generate neoantigens, consistent with the characteristics of immunologically "immune desert tumors."

[0004] Researchers have conducted numerous trials in exploring immunotherapy for HR-positive breast cancer, while also revealing many drawbacks of combination therapies. The first study evaluating the efficacy of pembrolizumab in combination with palliative radiotherapy (RT) in HR+MBC patients was prematurely halted because the first eight patients failed to achieve an objective response, and there was no indication that the combination prolonged progression-free survival (PFS) or overall survival (OS). Adverse events (AEs) occurred in 87.5% of patients. Another report explored the benefit of CDK4 / 6i inhibitors for disease-free survival (DFS) in HR+MBC patients, as well as the adverse effects of using these drugs in combination with immune checkpoint inhibitors (ICIs). Although ICIs and CDK4 / 6i are known to have synergistic activity, the high incidence of side effects from this combination therapy, particularly interstitial lung disease and liver injury, led to the discontinuation of the study.

[0005] Therefore, from a clinical perspective, ICIs can only make progress as a treatment option for HR-positive breast cancer when combined with established treatments already used in the disease context or other drugs that enhance the immune response. Thus, to improve the efficacy of immunotherapy for luminal breast cancer and enhance patient prognosis, it is urgently necessary to conduct a detailed and comprehensive exploration of the immune characteristics of luminal breast cancer, identify new immune targets, and activate the tumor immune response.

[0006] The tumor microenvironment (TME) is the environment in which tumors develop and progress. It is a complex network system composed of immune cells, fibroblasts, adipocytes, and other cells, as well as the extracellular matrix (ECM) and various signaling molecules. During breast cancer progression, different components of the TME exert varying inhibitory or promoting effects on cancer cells. Luminal breast cancer contains a large proportion of natural killer (NK) cells and neutrophils, while the proportions of cytotoxic T cells, naive T cells, and memory T cells are relatively low. High abundance of tumor-associated macrophages (TAMs) 1 and 2 and Treg lymphocytes indicates a poor prognosis in luminal breast cancer. Furthermore, supporting cells in the luminal breast cancer TME also directly or indirectly promote cancer progression. The heterogeneity of immune-infiltrating cells in the luminal breast cancer tumor microenvironment and the complex relationship between tumor phenotype and supporting cells make the treatment of this disease even more challenging.

[0007] GATA-binding protein 3 (GATA3) is expressed in multiple tissues, including the breast. GATA3 plays a crucial role in maintaining the differentiation of mammary ductal epithelial cells. It not only regulates the growth and differentiation of normal breast tissue but is also closely related to the occurrence and development of breast cancer. Gene expression profiling studies show that GATA3 expression levels are high in luminal breast cancer, and GATA3 expression in breast tumors is highly correlated with estrogen receptor α (ESR1) expression. High GATA3 expression promotes tumorigenesis and cell proliferation in luminal breast cancer. Large-scale genome sequencing results indicate a high mutation frequency of GATA3 in luminal breast cancer, with 10%–15% of breast tumors carrying mutations in this gene. The high frequency of GATA3 mutations in breast cancer suggests they are driver mutations, and wild-type GATA3 luminal cases have a better prognosis than mutant cases; therefore, high levels of GATA3 gene mutations may have significant clinical implications. However, the specific mechanisms of GATA3's role in breast cancer immunity are not yet fully understood, and the contribution of GATA3 mutations to breast cancer immunity requires further investigation. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of the prior art and provide the application of GATA3 inhibitors and PD1 inhibitors in the preparation of drugs for treating breast cancer.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0010] In a first aspect, the present invention provides the use of GATA3 inhibitors and PD1 inhibitors in the preparation of drugs for treating breast cancer.

[0011] Immunotherapy that combines GATA3 inhibition with PD1 inhibitors is an effective treatment for breast cancer.

[0012] Furthermore, the breast cancer in question is luminal breast cancer.

[0013] Further, the GATA3 inhibitor is siRNA or shRNA, the nucleotide sequence of the siRNA is shown in SEQ ID NO: 1 and 2; the nucleotide sequence of the sense strand of the shRNA is shown in SEQ ID NO: 3, and the nucleotide sequence of the antisense strand is shown in SEQ ID NO: 4.

[0014] Furthermore, the GATA3 inhibitor promotes IFN-β expression.

[0015] Furthermore, the GATA3 inhibitor promotes the MHC-I antigen presentation pathway.

[0016] The MHC-I presentation pathway-related genes include at least one of HLA-A, HLA-B, HLA-C, HLA-F, HLA-G, B2M, TAP1, TAP2, TAPBP, ERAP1, ERAP2, PSMB8, and PSMB9.

[0017] Furthermore, the GATA3 inhibitor promotes CCL5 cytokine expression.

[0018] Furthermore, the GATA3 inhibitor increases the number of CD8+ T cells.

[0019] Secondly, the present invention provides a recombinant lentiviral packaging vector containing shRNA, wherein the nucleotide sequence of the sense strand of the shRNA is shown in SEQ ID NO: 3, and the nucleotide sequence of the antisense strand is shown in SEQ ID NO: 4.

[0020] Furthermore, in a specific embodiment of the present invention, taking the Plko.1-puro vector as an example, the shRNA is ligated to the EcoRI and AgeI restriction sites of the Plko.1-puro vector.

[0021] Thirdly, the present invention provides a recombinant cell containing shRNA, wherein the nucleotide sequence of the sense strand of the shRNA is shown in SEQ ID NO: 3, and the nucleotide sequence of the antisense strand is shown in SEQ ID NO: 4.

[0022] Fourthly, the present invention provides the use of the recombinant lentiviral packaging vector and / or the recombinant cells in the preparation of GATA3 gene inhibitors and / or drugs for treating breast cancer.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0024] GATA3 mediates the transcriptional regulation of IFNβ by inhibiting the enhancer activity of IFNB1, downregulating the type I interferon signaling pathway, thereby suppressing the MHC-I antigen presentation pathway and the secretion of the chemokine CCL5 in breast cancer cells, thus reducing immune recognition and ultimately achieving immune escape. Immunotherapy combining GATA3 inhibition with PD-1 inhibitors can effectively treat breast cancer mice, increasing IFNβ levels, promoting the MHC-I antigen presentation pathway, increasing CCL5 levels, and enhancing CD8+ T cell levels in the tumor immune microenvironment, thereby reducing tumorigenesis and inhibiting tumor growth. Attached Figure Description

[0025] Figure 1 This is a graph from Gene Set Enrichment Analysis (GSEA).

[0026] Figure 2 This study used qPCR to analyze genes involved in the processing and presentation of MHC-I protein antigens in cells. A represents MCF7 cells; B represents T47D cells.

[0027] Figure 3 The content of HLA-ABC+ cells in cells with GATA3 gene knockdown is shown. A is a flow cytometry plot of MCF7 cells; B is a barplot of MCF7 cells; C is a flow cytometry plot of T47D cells; and D is a barplot of T47D cells.

[0028] Figure 4 The expression levels of HLA-B, B2M, TAP1, and PSMB8 are shown in cells overexpressing the GATA3 gene (GATA3 WT) and GATA3 G335fs. A represents BT-549 cells; B represents MDA-MB-436 cells.

[0029] Figure 5The figures show the HLA-ABC+ cell content in cells overexpressing the GATA3 gene (GATA3 WT) and GATA3 G335fs. A is a flow cytometry plot of BT-549 cells; B is a barplot of BT-549 cells; C is a flow cytometry plot of MDA-MB-436 cells; and D is a barplot of MDA-MB-436 cells.

[0030] Figure 6 The expression levels of GATA3 and HLA-ABC+ in MCF7, T47D, BT-549 and MDA-MB-436 cells after GATA3 gene knockdown or overexpression were determined.

[0031] Figure 7 Enrichment of the Top signaling pathway after GATA3 knockout.

[0032] Figure 8 Heatmap of relative interferon expression after GATA3 gene knockdown in MCF7 and T47D cells.

[0033] Figure 9 The expression of CCL5, IFNL1, IFNL2, and IFNB1 mRNA in cells with and without GATA3 gene knockdown. A represents MCF7 cells; B represents T47D cells.

[0034] Figure 10 This image shows the mRNA expression of genes involved in the MHC-I antigen processing and presentation signaling pathway in cells with and without GATA3 knockout, treated with different supernatants. A represents MCF7 cells; B represents T47D cells.

[0035] Figure 11 The values ​​represent the HLA-ABC+ cell content in cells treated with different culture supernatants. A is a flow cytometry plot of MCF7 cells; B is a barplot of MCF7 cells; C is a flow cytometry plot of T47D cells; and D is a barplot of MCF7 cells.

[0036] Figure 12 These are representative images of HLA-ABC+ cell staining in cells treated with PBS, IFN-β, IFN-λ1, or IFN-λ2. A represents MCF7 cells; B represents T47D cells.

[0037] Figure 13 The expression levels of HLA-B, B2M, TAP1, and PSMB8 in cells treated with different cytokines (CCL5, IFN-β, IFN-λ1, or IFN-λ2) are shown. A represents MCF7 cells; B represents T47D cells.

[0038] Figure 14 The values ​​represent the HLA-ABC+ cell content in cells treated with PBS, IFN-β, IFN-λ1, or IFN-λ2. A is a flow cytometry plot of MCF7 cells; B is a barplot of MCF7 cells; C is a flow cytometry plot of T47D cells; and D is a barplot of T47D cells.

[0039] Figure 15 The expression of IFN-β in cells with GATA3 gene knockdown and overexpression was detected by ELISA. A represents MCF7 cells; B represents T47D cells; C represents BT-549 cells; and D represents MDA-MB-436 cells.

[0040] Figure 16 The figures show the HLA-ABC+ cell content in different cell types. A is a flow cytometry plot of MCF7 cells; B is a barplot of MCF7 cells; C is a flow cytometry plot of T47D cells; and D is a barplot of T47D cells.

[0041] Figure 17 Representative immunofluorescence images of different cell lines after GATA3 gene knockdown, IFN-β neutralizing antibody treatment, and HLA-ABC staining. A represents MCF7 cells; B represents T47D cells.

[0042] Figure 18 A barplot shows the CCL5 secretion in different cells under various conditions, including GATA3 knockdown, IFN-β treatment, and IFN-βNab treatment. A represents MCF7 cells; B represents T47D cells.

[0043] Figure 19 Use a barplot to show the migration of CD8+ T cells under different conditions.

[0044] Figure 20 The images show the CCL5 secretion of cells under different conditions, including GATA3 overexpression, IFN-β, and IFN-βNAb treatment, as measured by ELISA. A represents BT-549 cells; B represents MDA-MB-436 cells.

[0045] Figure 21 The expression level of CCL5 mRNA in cells treated with or without IFN-β is shown.

[0046] Figure 22 Data from CHIA-PET, ChIP-seq, and RNA-seq confirmed the binding of the GATA3 and REST-CoREST complex within the IFNB1 enhancer region.

[0047] Figure 23 A barplot was used to show the association between SNP (rs10964832 allele status) and IFNB1 mRNA expression. P-values ​​were calculated using the xx test. *P<0.05.

[0048] Figure 24 Analysis of luciferase reporter genes demonstrated the relationship between GATA3 WT and GATA3 G335fs and IFNB1 enhancer activity.

[0049] Figure 25 The heatmap image shows the colocalization signal between GATA3 and the REST / CoREST complex, with each row representing a GATA3 binding peak.

[0050] Figure 26 A barplot is used to show the effect of histone deacetylase inhibitors (HDACs) on the expression of IFNB1, HLA-A, and CCL5 mRNA in cells. A represents MCF7 cells; B represents T47D cells.

[0051] Figure 27 Luciferase reporter gene analysis was performed to show the relationship between GATA3 gene knockout and CCL5 promoter activity in cells. In this study, A represents T47D cells; B represents 293FT cells.

[0052] Figure 28 Western blot analysis confirmed the effects of IFN-β treatment or GATA3 changes on the NF-κB and STAT1 signaling pathways in different breast cancer cell lines. Specifically, A shows that IFN-β activated the NF-κB and STAT1 signaling pathways in MCF7 and T47D cells; B shows that GATA3 knockdown activated the NF-κB and STAT1 signaling pathways in MCF7 and T47D cells, while GATA3 overexpression inhibited the NF-κB and STAT1 signaling pathways in BT-549 and MDA-MB-436 cells; and C shows that IFN-βNAb inhibited the activation of the NF-κB and STAT1 signaling pathways induced by GATA3 knockdown.

[0053] Figure 29 This is a schematic diagram for preparing a mouse model.

[0054] Figure 30 To illustrate the differences in tumor-infiltrating CD8+ T cells, the following diagrams are used: A is a flow cytometry plot showing the differences in tumor-infiltrating CD8+ T cells; B is a barplot showing the relative number of CD3+CD8+ T cells in each group; C is the distribution of tumor-infiltrating CD8+ T effector cells; and D is a barplot showing the relative number of CD8+IFNγ+ T cells in each group.

[0055] Figure 31The data for each group of tumors are shown below. A represents images of tumors in each group; B represents a statistical graph of tumor weight in each group; C represents tumor growth curves in each group; D represents stable knockout of the GATA3 gene in 4T1 cells; and E represents a box plot showing the body weight of different groups.

[0056] Figure 32 Representative images of multiplex immunofluorescence staining of MHC-I (red), CD8 (yellow), and GATA3 (green) in different groups. Detailed Implementation

[0057] To better illustrate the purpose, technical solution, and advantages of this invention, the invention will be further described below with reference to specific embodiments. Unless otherwise specified, other materials and reagents used in the embodiments are commercially available.

[0058] Example 1: GATA3 inhibits luminal breast cancer antigen presentation

[0059] I. Experimental Methods

[0060] (I) Constructing plasmids

[0061] 1. Construct plasmids expressing wild-type GATA3 (GATA3 WT) and mutant GATA3 (G335fs MUT).

[0062] (1) Based on the GATA3 mRNA sequence (NCBI accession number: NM_001002295.1), the GATA3 p.G335fs mutant mRNA sequence (COSM number: COSM5214182), and the DNA sequence of the IFNB1 enhancer (chr9: 21094316-21097300), PCR primers were designed for reverse transcription and amplification to obtain the corresponding wild-type GATA3, mutant GATA3, and IFNB1 enhancer cDNA fragments. The cDNA fragments were analyzed by agarose gel electrophoresis to determine the size of the target fragments, and the fragments were excised and recovered.

[0063] (2) The three cDNA fragments from step (1) and the Plenti-puro plasmid vector were double-digested with EcoI and XbalI restriction enzymes at 37℃ for 2 hours to obtain the three digested cDNA fragments and plasmid vector fragments, which were then recovered by electrophoresis.

[0064] (3) Vector ligation: The three cDNA fragments digested in step (2) and the plasmid vector fragments were ligated using T4 DNA ligase to obtain three ligation products.

[0065] 2. Plasmid Transformation: Add 5 μL of the ligation product to 50 μL of competent cells, incubate on ice for 30 min, heat shock at 42℃ for 60 s, add 200 μL of antibiotic-free LB medium (lysate broth), and incubate at 37℃ in a shaker for 60 min to obtain bacterial culture. Briefly centrifuge the bacterial culture, remove the supernatant, and evenly spread the remaining competent cells on LB agar plates containing 50 μg / mL ampicillin. Incubate at 37℃ for 10–12 h to obtain single colonies. Pick 10 colonies and transfer them to 5 mL of LB medium containing ampicillin. Incubate at 37℃ in a shaker for 6 h and then sequence. Retain the strains with correct sequencing sequences for large-scale culture to extract plasmids and store at -20℃ for later use.

[0066] 3. Plasmid amplification and extraction

[0067] (1) The bacterial strain that was verified by sequencing in step 2 was added to 15 mL of LB medium containing ampicillin and cultured in a shaker at 37°C for 10–12 h to obtain a culture solution. The culture solution was centrifuged at 8000 × g at 4°C for 10 min, the precipitate was collected, and plasmids were extracted using an endotoxin-free plasmid extraction kit to obtain plasmids expressing wild-type GATA3, mutant GATA3, and IFNB1 enhancers (GATA3WT plasmid, G335fs MUT plasmid, and IFNB1 plasmid).

[0068] (II) Construction of transient expression cell lines

[0069] 1. Construct MCF7 cells and T47D cells with GATA3 knockdown.

[0070] (1) Cell preparation: One day in advance, MCF7 cells and T47D cells were seeded into 24-well plates and cultured until the cell density reached 70-90% on the second day.

[0071] (2) Take a sterile 1.5 mL EP tube, dilute 2 μL of transfection reagent siRNA-mate with 50 μL of Opti-MEM serum-reduced medium, add 1 μL of GATA3 siRNA, incubate for 10 min, and obtain transfection mixture 1;

[0072] Three siRNA sequences were used: SiNC (as a control): 5'-UAGGCGAAUCAUUUGUUCAAA-3'; SiGATA3-1: 5'-AACAUCGACGGUCAAGGCAAC-3' (SEQ ID NO: 1); and SiGATA3-2: 5'-AAGCCUAAACGCGAUGGAUAU-3' (SEQ ID NO: 2). SiGATA3-1 and SiGATA3-2 have different target sites, but both exhibit high silencing efficiency.

[0073] *Regarding SEQ ID NO: 1 and 2 in the sequence listing of this specification: According to the editing rules of WIPOSequence software, the nucleotide sequence must only contain the symbols listed in "WIPOST.26 Annex I Part 1". The base "t" is "u" in the RNA sequence. Therefore, SEQ ID NO: 1 and 2 in this specification are substantially the same as SEQ ID NO: 1 and 2 in the sequence listing.

[0074] (3) Slowly add the three transfection mixtures 1 from step (2) to the culture medium of MCF7 cells and T47D cells treated in step (1), shake gently, incubate at 37°C for 6 hours, then replace the culture medium with complete culture medium containing 10% (v / v) serum and continue culturing for 48 hours to obtain GATA3 knocked-down MCF7 cells and GATA3 knocked-down T47D cells and their corresponding control cells.

[0075] 2. Construct MDA-MB-436 cells and BT549 cells overexpressing GATA3.

[0076] (1) Cell preparation: One day in advance, MDA-MB-436 cells and BT549 cells were seeded into 24-well plates and cultured until the cell density reached 70-90% the next day.

[0077] (2) Take a sterile 1.5mL EP tube and add 50μL Opti-MEM and 1μL transfection reagent Lipofectamine 3000.

[0078] (3) Take a sterile 1.5mL EP tube, add 50μL Opti-MEM and 1μL transfection reagent Lipofectamine 3000, and add 500ng GATA3 WT plasmid or G335fs MUT plasmid.

[0079] (4) Mix the two tubes from steps (2) and (3) and incubate for 10 minutes to obtain transfection mixture 2.

[0080] (5) Slowly add the two transfection mixtures (corresponding to the two plasmids) from step (4) to the culture medium of MDA-MB-436 cells and BT549 cells treated in step (1), mix gently and evenly, incubate in a 37°C incubator for 6 hours, then replace the culture medium with complete culture medium and continue culturing for 48 hours to obtain MDA-MB-436 cells and BT549 cells overexpressing GATA3.

[0081] MDA-MB-436 cells or BT549 cells transfected with the blank Plenti-puro plasmid vector served as the EV control group, while MDA-MB-436 cells or BT549 cells not transfected with the plasmid vector served as the blank control group.

[0082] (III) qPCR detection of the expression of antigen presentation-related gene mRNA in cells after GATA3 knockdown or overexpression.

[0083] Total RNA was extracted from GATA3-knockdown MCF7 and T47D cells, and cDNA was obtained by reverse transcription as template DNA for real-time quantitative PCR (qPCR).

[0084] qPCR reaction system: 5.0 μL of 2×Taq Pro Universal SYBR qPCR Master Mix, 0.2 μL of forward primer (10 μM), 0.2 μL of forward primer (10 μM), and 0.3 μL of template DNA, with ddH2O added to a total PCR reaction volume of 10 μL. The qPCR primer sequences are shown in Table 1.

[0085] qPCR reaction conditions: 95℃, 30s, 1 cycle; 95℃, 10s, 60℃, 30s, 40 cycles. After the PCR reaction was completed, the resulting melting curves were verified and the results were analyzed.

[0086] Table 1

[0087] GAPDH GGAGCGAGATCCCTCCAAAAT GGCTGTTGTCATACTTCTCATGG GATA3 ACCACAACCACACTCTGGAGGA TCGGTTTCTGGTCTGGATGCCT HLA-A AGATACACCTGCCATGTGCAGC GATCACAGCTCCAAGGAGAACC HLA-B CTGCTGTGATGTGTAGGAGGAAG GCTGTGAGAGACACATCAGAGC HLA-C GGAGACACAGAAGTACAAGCGC ACATCCTCTGGAGGGTGTGAGA HLA-F GCTGCTGTGATGTGGAGGAAGA GTATGTTCGTGAGGCACAAGTGC HLA-G CTGCTGTGATGTGTAGGAGGAAG TCGCAGCCAATCATCCACTGGA B2M CCACTGAAAAAAGATGAGTATGCCT CCAATCCAAATGCGGCATCTTCA TAP1 GCAGTCAACTCCTGGACCACTA CAAGGTTCCCACTGCTTACAGC TAP2 ATGCCCTTCACAATAGCAGCGG CCAAAACTGCGAACGGTCTGCA TAPBP GAGCCTGTTCTCATCACCATGG GTAGGCAAAGCTCAAGTCCAGC ERAP1 CGAGGACCTGTGGAATAGCATG CATCTACAACCTCCTGACGCCA ERAP2 CTGTGACCTGAACCATGCTCCT TCCATCCTGCTGTTGTTGTCTGAGC PSMB8 CCTTACCTGCTTGGCACCATGT TTGGAGGCTGCCGACACTGAAA PSMB9 CGAGAGGACTTGTCTGCACATC CACCAATGGCAAAAGGCTGTCG

[0088] (iv) Flow cytometry detection of the expression of classical human leukocyte antigen class I (HLA-ABC+) in cells

[0089] 1. Count the GATA3-knockdown MCF7 and T47D cells, GATA3-overexpressing MDA-MB-436 and BT549 cells, and their corresponding control cells. Take 1×10⁻⁶ cells from each group. 5 Cells were plated and cultured for 48 hours.

[0090] 2. Digest the cells from step 1 with trypsin, centrifuge at 300g for 3.5 minutes, and collect the cells.

[0091] 3. Wash the cells from step 2 once with PBS (phosphate buffer), centrifuge at 300g for 3 minutes, and collect the cells.

[0092] 4. Separate blank tubes from the control cells. Add HLA-ABC + flow cytometry antibody to all tubes except the blank tubes. Incubate on ice in the dark for 15-20 min. Add PBS and shake to wash for 5 min. Wash twice. Centrifuge at 350g for 5 min and collect the cells.

[0093] 5. Resuspend the cells collected in step 4 in 500 μL PBS, add 5 μL 7-aminoactinomycin D (7-AAD), and incubate on ice in the dark for 5 min.

[0094] 6. On-machine testing.

[0095] II. Experimental Results

[0096] Knockdown of the GATA3 gene upregulates the expression of antigen presentation-related gene mRNA.

[0097] 1. For example Figure 1 As shown in the figure, the gene set enrichment analysis (GSEA) diagram shows that GATA3 expression significantly interferes with the processing and presentation signaling pathways of major histocompatibility complex class I (MHC-I) protein antigens.

[0098] 2. For example Figure 2 A (MCF7 cells) and Figure 2 As shown in B (T47D cells), qPCR analysis was performed on genes involved in the processing and presentation of MHC1 protein antigens in control cells (siNC) and GATA3 knockdown cells (siGATA3-1 and siGATA3-2). GATA3 knockdown upregulated the expression of HLA-A, HLA-B, HLA-C, HLA-F, HLA-G, B2M, TAP1, TAP2, TAPBP, ERAP1, ERAP2, PSMB8, and PSMB9.

[0099] 3. Figure 3 A (MCF7 cells) and Figure 3 Flow cytometry images of C(T47D cells) show the number of HLA-ABC+ cells in the control group (siNC) and the GATA3 knockdown cell groups (siGATA3-1 and siGATA3-2). Figure 3 B (MCF7 cells) and Figure 3 D(T47D cells) represents the relative proportion of HLA-ABC+ cells in the control group (siNC) and the GATA3 knockdown cell groups (siGATA3-1 and siGATA3-2), as summarized by Barplot. HLA-ABC+ expression is upregulated after GATA3 knockdown.

[0100] 4. Figure 4 A (BT-549 cells) and Figure 4B(MDA-MB-436 cells) shows the expression of HLA-B, B2M, TAP1, and PSMB8 in control (EV) and cells overexpressing the GATA3 gene (GATA3 WT) or GATA3 G335fs. GATA3 gene overexpression downregulated the expression of HLA-B, B2M, TAP1, and PSMB8.

[0101] 5. Figure 5 A (BT-549 cells) and Figure 5 C(MDA-MB-436 cells) is a flow cytometry image showing the content of HLA-ABC+ cells in control group (Blank, EV), cells overexpressing GATA3 (GATA3 WT), and cells expressing GATA3 G335fs. Figure 5 B (BT-549 cells) and Figure 5 D(MDA-MB-436 cells) represents the relative proportion of HLA-ABC+ cells in the control group (Blank, EV), cells overexpressing GATA3 (GATA3 WT), and cells expressing GATA3 G335fs, as summarized by Barplot. GATA3 gene overexpression reduces the number of HLA-ABC+ cells.

[0102] 6. Figure 6 The expression levels of GATA3 and HLA-ABC in MCF7, T47D, BT-549, and MDA-MB-436 cells after GATA3 gene knockdown (siGATA3-1, siGATA3-2) or overexpression (GATA3 WT and GATA3 MUT) were shown. HLA-ABC expression was upregulated after GATA3 gene knockdown; HLA-ABC expression was downregulated after GATA3 gene overexpression.

[0103] Example 2: GATA3 inhibits IFN-β-downregulation of MHC-I expression

[0104] I. Experimental Methods

[0105] (I) Enrichment of Top signaling pathways and relative expression of interferons

[0106] 1. RNA was extracted from MCF7 cells and T47D cells with GATA3 knockdown in Example 1 and from control cells, and sequenced.

[0107] 2. The RNA data from step 1 was mapped to the human genome hg38 using STAR (v2.7.11a). Gene expression levels were quantitatively analyzed using RSEM (v1.3.3). The gene counting matrix was input into the DESeq2 (v1.40.2) package, and differentially expressed gene analysis was performed using default parameters. Pathway enrichment analysis was performed on TCGA patients with immunosuppressive subtypes using fGSEA.

[0108] (II) qPCR detection of CCL5, IFNL1, IFNL2, and IFNB1 mRNA expression in GATA3-knockdown MCF7 and T47D cells and control group cells. The qPCR detection method was the same as in Example 1, and the primers used are shown in Table 2.

[0109] Table 2

[0110] IFNB1 CTTGGATTCCTACAAAGAAGCAGC TCCTCCTTCTGGAACTGCTGCA IFNL1 AACTGGGAAGGGCTGCCACATT GGAAGACAGGAGAGCTGCAACT IFNL2 TCGCTTCTGCTGAAGGACTGCA CCTCCAGAACCTTCAGCGTCAG CCL5 CCTGCTGCTTTGCCTACATTGC ACACACTTGGCGGTTCTTTCGG

[0111] (III) Treat cells with different culture supernatants and perform detection.

[0112] 1. Treatment of cells with different culture supernatants

[0113] (1) MCF7 and T47D cells with GATA3 knockdown and control cells were cultured for 48h, and 500μL of supernatant was taken and cultured for 48h in the same way as ordinary MCF7 and T47D cells without GATA3 knockdown.

[0114] 2. Cells treated with different culture supernatants were analyzed by flow cytometry, and the expression of antigen-presenting related gene mRNAs in the cells was detected by qPCR. The method was the same as in Example 1.

[0115] (iv) Treatment of cells with different cytokines and subsequent detection

[0116] 1. Cells treated with different cytokines

[0117] Undigested GATA3-free MCF7 and T47D were digested and centrifuged according to the method in Example 1. After counting, 1×10⁻⁶ ppm was added to each well. 5 Cells were seeded into plates, and after 6 hours, PBS, 50 ng / mL IFN-β, 50 ng / mL IFN-λ1, or 50 ng / mL IFN-λ2 cytokines were added, and the plates were incubated at 37°C for 48 hours.

[0118] 2. Flow cytometry was used to detect the expression of antigen-presenting related gene mRNAs in cells treated with different methods, and qPCR was used to detect the expression of antigen-presenting related genes mRNAs in the cells. The method was the same as in Example 1.

[0119] (V) Detection of IFN-β expression in different cells using double-antibody sandwich enzyme-linked immunosorbent assay (ELISA)

[0120] (1) Coating antigen: Add 50 μL of hIFN-βcapture antibody to each well of a 96-well plate, seal the plate, and incubate at room temperature overnight (10-12 h).

[0121] (2) Remove excess antibody from step (1), pour out all liquid from the wells, and invert the 96-well plate onto absorbent paper to dry.

[0122] (3) Add 200 μL of blocking buffer to each well treated in step (2) and place at 37°C for 2 hours.

[0123] (4) Discard the liquid in the well after treatment in step (3), and invert the 96-well plate onto absorbent paper to dry it.

[0124] (5) Prepare 10 ng / mL hIFN-β standard. Add Blank, D1-D7 standard 50 μL to the 96-well plate treated in step (4) (the concentrations of D1-D7 are 1000 pg / mL, 500 pg / mL, 250 pg / mL, 125 pg / mL, 62.5 pg / mL, 31 pg / mL and 15 pg / mL, respectively).

[0125] (6) Add 50 μL of sample (cells to be tested) diluted 10 times with Reagent deligent to the 96-well plate after the treatment in step (5).

[0126] (7) Add 50 μL of 30 ng / mL Lucia-conjugated detection antibody to the wells treated in step (6), seal the membrane, and incubate at 37°C for 2 h.

[0127] (8) Remove the liquid in the wells after step (7), and wash each well with 200 μL of wash buffer three times. On the last wash, pat the 96-well plate dry on absorbent paper.

[0128] (9) Add 50 μL of Quanti-luc4 to each well after the treatment in step (8). TM Reagent was detected using a 490mm microplate reader.

[0129] (10) Analyze the data and plot it.

[0130] (vi) IFN-β treatment of cells and subsequent detection

[0131] 1. MCF7 and T47D cells with knocked-down GATA3 and control cells were digested and centrifuged according to the method in Example 1. After counting, 1×10⁻⁶ cells were added to each well. 5 Cells were seeded into plates, and after 6 hours, groups were added with 50 ng / mL IFN-β and 50 ng / mL IFN-β neutralizing antibody (IFN-βNAb), respectively, and cultured in an incubator at 37°C for 48 hours.

[0132] 2. Flow cytometry was performed on cells with different cell treatments, using the same method as in Example 1. Multiplex immunofluorescence assays were also performed on cells with different cell treatments, as follows:

[0133] (1) Discard the culture medium in each group of cells, add 1 mL of PBS and wash 3 times on a shaker for 5 min each time.

[0134] (2) Add 200 μL of 4% (v / w) paraformaldehyde to each well in step (1), fix at room temperature for 15 min, add 1 mL of PBS, wash on a shaker for 5 min, and repeat the washing twice.

[0135] (3) Add 200 μL of 0.1% (v / v) Triton X-100 membrane rupture solution to each well in step (2), let stand at room temperature for 10 min, add 1 mL of PBS, wash on a shaker for 5 min, and repeat twice.

[0136] (4) Add 200 μL of 1% (v / v) BSA (bovine serum albumin) solution to each well in step (3), block at room temperature for 1 h, remove the BSA solution, add 100 μL of primary antibody to each well, and incubate at 4°C for 10-12 h.

[0137] (5) Recover the primary antibody from step (4), add 1 mL of PBS solution, wash 3 times on a shaker for 5 min each time, add 100 μL of the corresponding fluorescent secondary antibody to each well, and incubate at room temperature in the dark for 1 h.

[0138] (6) Add 1 mL of PBS solution to each well in step (5), wash 3 times on a shaker for 5 min each time, add 200 μL of 1% (v / v) BSA solution, block at room temperature for 1 h, add 100 μL of the second primary antibody to each well, and incubate at 4°C in the dark for 10-12 h.

[0139] (7) Repeat step (5), add 100 μL of 5 μg / mL 4',6-diamidinyl-2-phenylindole (DAPI), incubate in the dark for 5 min, add 1 mL of PBS solution to each well, and wash 3 times on a shaker for 5 min each time.

[0140] (8) Use a syringe to remove the slide after step (9) and let it air dry. Add 5 μL of mounting medium and let it stand for 10 minutes. Use a confocal microscope to take and save the images, keeping them away from light throughout the process.

[0141] II. Experimental Results

[0142] 1. Figure 7 Enrichment of the Top signaling pathway after GATA3 gene knockout. Figure 8Heatmap of relative interferon expression after GATA3 gene knockdown in MCF7 and T47D cells.

[0143] 2. MCF7 cells ( Figure 9 A) and T47D cells ( Figure 9 B) Expression of CCL5, IFNL1, IFNL2, and IFNB1 mRNA with or without GATA3 knockdown. GATA3 knockdown resulted in decreased expression levels of CCL5, IFNL1, IFNL2, and IFNB1 mRNA.

[0144] 3. MCF7 cells ( Figure 10 A) and T47D cells ( Figure 10 B) mRNA expression of genes involved in the processing and presentation of MHC class I antigens in cells treated with different supernatants, with or without GATA3 knockout. GATA3 knockdown led to upregulation of HLA-A, HLA-B, HLA-C, HLA-F, HLA-G, B2M, TAP1, TAP2, TAPBP, ERAP1, ERAP2, PSMB8, and PSMB9 expression.

[0145] 4. Figure 11 A (MCF7 cells) and Figure 11 C(T47D cells) is a flow cytometry plot showing the HLA-ABC+ cell content in cells treated with different culture supernatants. Figure 11 B (MCF7 cells) and Figure 11 D(T47D cells) represents the proportion of HLA-ABC+ cells in cells treated with different culture supernatants, as summarized by Barplot. Treatment with GATA3 gene knockdown cell supernatants increased both the content and proportion of HLA-ABC+ cells.

[0146] 5. Figure 12 MCF7 cells treated with PBS, IFN-β, IFN-λ1, or IFN-λ2 ( Figure 12 A) and T47D cells ( Figure 12 B) shows a representative image of HLA-ABC+ cell staining. It can be seen that the HLA-ABC+ cell content is increased in IFN-β treated MCF7 and T47D cells.

[0147] 6. Figure 13 This indicates MCF7 cells treated with different cytokines (CCL5, IFN-β, IFN-λ1, or IFN-λ2). Figure 13 A) and T47D cells ( Figure 13B) Expression levels of HLA-B, B2M, TAP1, and PSMB8. Cells treated with IFN-β showed higher expression levels of HLA-B, B2M, TAP1, and PSMB8.

[0148] 7. Figure 14 MCF7 cells treated with PBS, IFN-β, IFN-λ1, or IFN-λ2 ( Figure 14 A) and T47D cells ( Figure 14 C) Flow cytometry plot showing the content of HLA-ABC+ cells. Figure 14 B (MCF7 cells) and Figure 14 D(T47D cells) represents the HLA-ABC+ cell content in different cell types as summarized by Barplot. Cells treated with IFN-β have a higher HLA-ABC+ cell content.

[0149] 8. Figure 15 This indicates that ELISA detection was performed on MCF7 cells with GATA3 gene knockdown (siGATA3-1 and siGATA3-2) or overexpression (GATA3WT and GATA3 G335fs). Figure 15 A) T47D cells ( Figure 15 B), BT-549 cells ( Figure 15 C) and MDA-MB-436 cells ( Figure 15 D) IFN-β expression. Knockdown of GATA3 increased IFN-β expression; while overexpression of GATA3 decreased IFN-β expression.

[0150] 9. Figure 16 Flow cytometry analysis showed the expression of HLA-ABC+ in different groups. Figure 16 A is a flow cytometry image of MCF7 cells; Figure 16 B is a barplot of MCF7 cells; Figure 16 C is a flow cytometry image of T47D cells; Figure 16 D is a barplot of T47D cells. Treatment with IFN-β increased HLA-ABC+ expression, while treatment with the IFN-β neutralizing antibody decreased HLA-ABC+ expression.

[0151] 10. Figure 17 For MCF7 cells ( Figure 17 A) and T47D cells ( Figure 17B) Representative immunofluorescence images of GATA3 gene knockdown and HLA-ABC staining. Control group, siGATA3 cells, and cells treated with IFN-β neutralizing antibody, showing that IFN-β neutralizing antibody blocked the increase of MHC-I in GATA3 knockdown cells.

[0152] Example 3: Molecular mechanisms of GATA3-mediated immune evasion

[0153] I. Experimental Methods

[0154] (i) Following the method in Example 2, MCF7 and T47D cells with knockdown of GATA3, MDA-MB-436 and BT549 cells overexpressing GATA3, and their corresponding control cells were treated with IFN-β and IFN-β neutralizing antibody (IFN-βNAb). The capture antibody was replaced with CCL5 capture antibody, and CCL5 expression was detected by ELISA.

[0155] (II) Detection of CD8+ T cell migration in different cell types using CCL5

[0156] 1. Following the method in Example 2, MCF7 and T47D cells with GATA3 knockdown and their corresponding control cells were treated with 50 ng / mL CCL5 and 0.2 μg / mL CCL5 neutralizing antibody (CCL5 NAb).

[0157] 2. The migration rate of CD8+ T cells in each group was detected using a Transwell chamber.

[0158] (III) qPCR was used to detect the mRNA expression of CCL5 in ordinary MCF7 and T47D cells without GATA3 knockdown after treatment with different concentrations of IFN-β (10 ng / mL, 50 ng / mL, and 100 ng / mL). The IFN-β treatment method and qPCR method were the same as in Example 2.

[0159] (IV) Detection of the interaction between GATA3 and the IFNB1 enhancer or CCL5 promoter using luciferase reporter gene analysis. 1. Following the method in Example 1, different plasmids were transfected into 293FT cells to obtain different transfected cell groups. Each group was configured with 3 replicates to obtain 293FT cells transfected into different transfection groups. The different transfection groups are as follows:

[0160] PGL3-Basic+Plenti-puro, IFN-βEnhancer+Plenti-puro, IFN-βEnhancer+GATA3WT (plasmid constructed in Example 1), IFN-βEnhancer+GATA3 G335fs (plasmid constructed in Example 1); PGL3-Basic+Plenti-puro, CCL5 Promoter+GATA3 WT, CCL5 Promoter+GATA3 G335fs, CCL5 Promoter+GATA3 WT+IFN-β and CCL5 Promoter+GATA3 G335fs+IFN-β.

[0161] PGL3-Basic: A control plasmid containing the firefly luciferase reporter gene; IFN-βEnhancer (IFNB1 plasmid constructed in Example 1): An IFNB1 enhancer fragment inserted into the PGL3-Basic plasmid; Plenti-puro: A control plasmid used as the GATA3 WT plasmid and the GATA3 G335fs plasmid; CCL5 Promoter: A CCL5 promoter fragment (chromosome 17:35880361-35882361) inserted into the PGL3-Basic plasmid, constructed using the same method as in Example 1.

[0162] 2. Dual-fluorescence reporter gene detection

[0163] (1) Discard the culture medium of the transfected 293FT cells and wash the cells with 1 mL PBS.

[0164] (2) Add 50 μL of 1×Passive Lysis Buffer to each well in step (1) and lyse on a shaker for 30 min.

[0165] (3) Take 10 μL of the supernatant after step (2) and add it to a 96-well microplate. Add 100 μL of Luciferase Assay Reagent II and detect the luciferase reaction intensity after 2 seconds.

[0166] (4) After the detection in step (3) is completed, add 100 μL of Stop& to each well. Reagent, after 2 seconds, detect the intensity of the internal reference Renal luciferase reaction.

[0167] (5) Calculate the data and plot it.

[0168] (v) Analysis of differential protein and gene expression in cells

[0169] 1. ChIP-seq and Cut & Tag Data Analysis

[0170] ChIP-seq data from the MCF7 cell line were collected from the coding data. To identify most of the transcription factors associated with GATA3, colocalization analysis was performed using Beetools (v2.29.1) based on the GATA3 binding peak and peaks of other transcription factors, as well as the available histone modifiers encoded in the data. The top-ranked factors included REST, SIN3A, HDAC2, and COREST, and their raw sequence data were retrieved from coding databases, along with the ChIP-seq sequences of MCF7 and H3K4me1 of MCF7. CUT&Tag data for GATA3, H3K27ac, and H3K4me1 in MCF7 and T47D were also generated. ChIP and CUT&Tag data were aligned to the human genome GRCh38 using bowtie2 (v2.5.4). Repeated reads were then labeled using the Picard tool (v1.140). Peaks for each sample were retrieved using Macs2. The peaks were normalized to CPM (v3.5.1) using deeptools (v3.5.1). The identified peaks were annotated using ChIPseeker (v1.36.0).

[0171] 2. RNA-seq analysis and differentially expressed gene analysis

[0172] RNA-seq data were mapped to hg38 of the human genome using STAR (v2.7.11a) (Dobin et al., 2013).

[0173] Gene expression levels were quantitatively analyzed using RSEM (v1.3.3). The gene count matrix was input into DESeq2 (v1.40.2) for differentially expressed gene analysis using default parameters. Finally, visualization was performed using deeptools (v3.5.1).

[0174] (vi) Western blotting detection of HLA-ABC protein and NFκB and STAT1 signaling pathway protein expression after GATA3 gene knockdown or overexpression

[0175] 1. Extracting cell proteins

[0176] (1) Discard the culture medium of MCF7 and T47D cells with knockdown of GATA3, MDA-MB-436 and BT549 cells overexpressing GATA3, MCF7 and T47D cells treated with PBS, IFN-β, IFN-λ1 or IFN-λ2 respectively and their control cells, and wash the cells twice with 1 ml of pre-cooled 1× phosphate buffer (PBS) to obtain the washed cells.

[0177] (2) Add 250 μL of RIPA (Radio Immuno Precipitation Assay) buffer, 2.5 μL of 100× protease inhibitor and phosphatase inhibitor to the cells washed in step (1) to obtain a protein mixture.

[0178] (3) Scrape off the protein mixture from step (2) with a cell scraper, transfer it to a clean 1.5 mL centrifuge tube with a pipette, and lyse it at 4 °C for 35 min.

[0179] (4) Place the centrifuge tubes processed in step (3) in a centrifuge at 4°C and centrifuge at 12,000 rpm for 10 min. Collect the supernatant to obtain cell protein and store it in a refrigerator at -80°C.

[0180] 2. Perform Western blotting on the cell proteins extracted in step 1.

[0181] II. Experimental Results

[0182] Figure 18 To display MCF7 cells in a barplot ( Figure 18 A) and T47D cells ( Figure 18 B) CCL5 secretion under different conditions, including GATA3 knockdown, IFN-β treatment, and IFN-βNAb treatment. The expression level of CCL5 in cells treated with GATA3 knockdown and IFN-β was significantly higher than in other groups.

[0183] Figure 19 A barplot is used to show the migration of CD8+ T cells under different conditions. The migration of CD8+ T cells in the control group treated with CCL5 was significantly higher than that in other groups, followed by cells knocked down by GATA3.

[0184] Figure 20 BT-549 cells as measured by ELISA ( Figure 20 A) and MDA-MB-436 cells ( Figure 20 B) CCL5 secretion in cells under different conditions of GATA3 overexpression, IFN-β, and IFN-βNAb treatment. The expression level of CCL5 was significantly increased in cells treated with IFN-β.

[0185] Figure 21 The values ​​represent the CCL5 mRNA expression levels in cells treated with or without IFN-β. CCL5 mRNA expression levels increase with increasing IFN-β levels.

[0186] Figure 22Signals from CHIA-PET, ChIP-seq, and RNA-seq confirmed the binding of GATA3 and the REST / CoREST complex within the IFNB1 enhancer region.

[0187] Figure 23 Barplot shows the association between SNP (rs10964832 allele status) and IFNB1 mRNA expression.

[0188] Figure 24 Luciferase reporter gene analysis demonstrated that the GATA3 WT and GATA3 G335fs transcriptional repressors reduced the activity of the IFNB1 enhancer.

[0189] Figure 25 The heatmap image shows the colocalization signal between GATA3 and the REST / CoREST complex, with each row representing a GATA3 binding peak.

[0190] Figure 26 Barplot shows the effects of histone deacetylase inhibitors (HDACs), including Romidepsin IC20, Romidepsin IC50, Chidamide IC20, and Chidamide IC50, on MCF7 cells ( Figure 26 A) and T47D cells ( Figure 26 B) Effects on the expression of IFNB1, HLA-A, and CCL5 mRNA. HDAC significantly increased the expression levels of IFNB1, HLA-A, and CCL5 mRNA in cells.

[0191] Figure 27 Analysis of luciferase reporter genes showed that T47D cells ( Figure 27 A) and 293FT cells ( Figure 27 B) Transcriptional activation of the CCL5 promoter following GATA3 knockout.

[0192] Figure 28 Western blot analysis confirmed the activation of the NFκB and STAT1 signaling pathways in IFN-β-treated or GATA3-knockdown cells. Figure 28 A indicates that IFN-β activates the NF-κB and STAT1 signaling pathways in MCF7 and T47D cells; Figure 28 GATA3 knockdown on the surface of B cells activated the NF-κB and STAT1 signaling pathways in MCF7 and T47D cells, while GATA3 overexpression inhibited the NF-κB and STAT1 signaling pathways in BT-549 and MDA-MB-436 cells. Figure 28C indicates that IFN-βNAb inhibits the activation of the NF-κB and STAT1 signaling pathways induced by GATA3 knockdown.

[0193] Example 4: Mouse orthotopic tumor transplantation model and combined treatment

[0194] I. Experimental Methods

[0195] 1. Cell preparation

[0196] (1) Design shGATA3

[0197] Four shRNA sequences targeting the GATA3 gene were designed using the online tool (BLOCK-iT RNAi Designer). The shRNA sequences are shown in Table 3. The cells were transiently transfected into 4T1 cells (using the same method as step (II) in Example 1). The knockdown efficiency of GATA3 was verified by qPCR (the same method as in Example 1), and shRNA-1 with the highest gene knockdown efficiency was selected.

[0198] Table 3

[0199]

[0200] (2) Construction of shRNA vector

[0201] shGATA3-1 and shNC were cloned into the Plko.1-puro vector (at the EcoRI and AgeI restriction sites), respectively. The experimental steps were the same as in Example 1, and the shGATA3-1 Plko.1-puro plasmid and shNC Plko.1-puro plasmid were obtained.

[0202] (3) Virus packaging

[0203] The plasmids from step (2) were transfected into 293FT cells according to the method in Example 1. After 48 hours of transfection, the supernatant was transferred to a 15 mL centrifuge tube, filtered with a 0.45 μm filter, and lentivirus HIV-1 was aliquoted into each tube in 2 mL portions and stored in a freezer at -80°C.

[0204] (4) Constructing 4T1 stable strains

[0205] One day in advance, 4T1 cells were seeded into 24-well plates and cultured until the cell density reached 70-90% the next day. On the second day, 1 mL of the virus constructed in step (3) was transfected into 4T1 cells. After culturing at 37°C for 48 h, 1 μg / mL puromycin was added for further culture. The cells were screened for the drug until all untransfected 4T1 cells died. 4T1+Plko.1 (containing shNCPlko.1-puro plasmid) and 4T1+shGATA3 (containing shGATA3-1 Plko.1-puro plasmid) cells were harvested and passaged. 4T1+Plko.1 or 4T1+shGATA3 cells were passaged, digested, washed once with PBS, and then counted to achieve a cell density of 5 × 10⁻⁶ cells. 7 per mL.

[0206] 2. Vaccination and treatment

[0207] Concentration 5×10 7 Cells per ml were injected subcutaneously into mice at a rate of 100 μL per mouse. Tumor formation was observed in the mice; by day 6 after injection, the tumors had grown to approximately 100 mm. 3 Tumor volume and mouse weight were measured every other day, and mice were intraperitoneally injected with PB S, 100 μg / mL IFN-β, or 100 μg / mL anti-PD1 (PD1 monoclonal antibody, InVivoMAb anti-mousePD-1(CD279), brand: Bioxcell, catalog number: BE0146) according to their groups. IFN-β: on days 7, 9, and 11 after injection; anti-PD1: on days 6, 8, and 10 after injection.

[0208] The groups are shown in Table 1.

[0209] Table 4

[0210] 1 4T1-plko.1 10 PBS 2 4T1-shGATA3 10 PBS 3 4T1-plko.1 10 IFN-β 4 4T1-plko.1 10 Anti-PD-1 5 4T1-plko.1 10 IFN-β+Anti-PD-1 6 4T1-shGATA3 10 Anti-PD-1

[0211] 3. Tumor Removal and Result Analysis

[0212] Mice in each treatment group were sacrificed by carbon dioxide inhalation to obtain tumor tissue, adjacent normal tissue, and spleen. Mononuclear cells were isolated in vitro or tissue sections were prepared to assess the degree of invasion of different cell types and the expression of marker genes in the tumor tissue.

[0213] Tumor cells were extracted and subjected to flow cytometry experiments according to the method in Example 1. The antibody used was BrilliantViolet 510. TM anti-mouse CD8a, APC / Fire TM 750 anti-mouse CD3 and PE anti-mouse IFN-γ.

[0214] The tissue multiplex immunofluorescence method is as follows:

[0215] (1) Dewaxing: The tissue sections were baked at 65°C for 2 hours to obtain baked tissue sections; the baked tissue sections were then immersed in xylene I, II and III for 15 minutes each, and in anhydrous ethanol, 95% (v / v) ethanol, 85% (v / v) ethanol and 75% (v / v) ethanol for 5 minutes each to obtain rehydrated tissue sections.

[0216] (2) Antigen retrieval: Place the rehydrated tissue section from step (1) into a retrieval box filled with sodium citrate antigen retrieval solution and perform antigen retrieval treatment in a microwave oven; set the heat to medium for 8 minutes, stop heating for 8 minutes, then switch to medium-low heat for 7 minutes, and finally cool naturally. Wash with PBS three times, 5 minutes each time.

[0217] (3) Marking tissue: Gently shake the tissue slices after step (2) to dry them, and use a histological pen to draw the outer contour of the tissue.

[0218] (4) Inactivation of endogenous peroxidase: Add 100 μl of 3% (v / v) hydrogen peroxide to the tissue sections after treatment in step (3), incubate at room temperature in the dark for 20 min, wash with PBS for 5 min, and wash 3 times.

[0219] (5) Blocking: Gently shake the tissue slices after step (4) to dry them, drip goat serum into them, and block them at room temperature for 1 hour to obtain blocked tissue slices.

[0220] (6) Primary antibody incubation: Dilute GATA3 primary antibody with PBS (the volume ratio of GATA3 primary antibody to PBS is 1:200) to obtain diluted primary antibody; add 100 μl of diluted primary antibody to the tissue section after blocking in step (5) to cover the tissue, and incubate overnight at 4°C.

[0221] (7) Secondary antibody incubation: Wash the tissue sections treated in step (6) three times with PBS solution, 5 min each time. Add 50 μL of the corresponding species of secondary antibody (mouse / rabbit) at a ratio of 1:500. Incubate at room temperature for 1 h. Wash the sections three times with PBS, 5 min each time.

[0222] (8) Add iF594-TSA staining working solution: Gently shake the tissue sections after step (7) to dry, add 50 μL iF594-TSA staining working solution, block at room temperature in the dark for 10 min, and wash with TBST solution (Tris buffered saline containing Tween 20) three times, 5 min each time.

[0223] (9) Repeat steps (2)-(8).

[0224] (10) Nuclear counterstaining with DAPI: After the tissue sections treated in step (9) were dried, DAPI staining solution was added, and the sections were incubated at room temperature in the dark for 10 min. The sections were then washed three times with PBS for 5 min each time.

[0225] (11) Mounting: Dry the tissue sections after step (10) and add anti-fluorescence quenching agent to mount the sections.

[0226] (12) Take a picture and place the tissue sections processed in step (11) in a light-proof slide box. They can be stored at 4°C for 15 days.

[0227] II. Experimental Results

[0228] Figure 29 This is a schematic diagram for preparing a mouse model.

[0229] Figure 30 A is a flow cytometry image showing the differences in tumor-infiltrating CD8+ T cells. Figure 30 B is a barplot showing the relative number of CD3+CD8+ T cells in each group. Figure 30 C represents the distribution of tumor-infiltrating CD8+ T effector cells. Figure 30 D is a barplot showing the relative number of CD8+IFNγ+ T cells in each group.

[0230] Figure 31 A shows images of tumors in each group; Figure 31 B is a statistical chart of tumor weight in each group; Figure 31 C represents the tumor growth curves measured in each group. P-values ​​were calculated using the chi-square test. ***P < 0.001; Figure 31 D shows stable knockout of GATA3 in 4T1 cells; Figure 31 E is a box plot showing the weights of different groups.

[0231] Figure 32 Representative images showing MHC-I (red), CD8 (yellow), and GATA3 (green) staining.

[0232] Based on the above experimental results, immunotherapy combining GATA3 knockout with anti-PD1 or IFN-β with anti-PD1 showed the most effective anti-tumor effect, significantly increasing the expression of MHC-I and CD8+ T cells in mouse tumor tissues.

[0233] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. Application of GATA3 inhibitors and PD1 monoclonal antibodies in the preparation of drugs for treating triple-negative breast cancer; The GATA3 inhibitor is shRNA, and the nucleotide sequence of the sense strand of the shRNA is shown in SEQ ID NO: 3, and the nucleotide sequence of the antisense strand is shown in SEQ ID NO:

4.

2. The application according to claim 1, characterized in that, The GATA3 inhibitor promotes IFN-β expression.

3. The application according to claim 1, characterized in that, The GATA3 inhibitor promotes the MHC-I antigen presentation pathway.

4. The application according to claim 1, characterized in that, The GATA3 inhibitor promotes the expression of CCL5 cytokines.

5. The application according to claim 1, characterized in that, The GATA3 inhibitor increases the number of CD8+ T cells.

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