Application of GATA3 inhibitor and PD1 inhibitor in preparation of medicine for treating breast cancer

Abstract

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

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to the use of a GATA3 inhibitor and a PD1 inhibitor in the preparation of a drug for treating breast cancer. Background Art

[0002] Breast cancer (BC) is one of the most common cancers. According to the expression of surface receptors of breast cancer cells: estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor 2 (HER2), breast cancer can be divided into four molecular subtypes: luminal A, luminal B, HER2-positive and triple negative breast cancer (TNBC). Among them, luminal A and luminal B are collectively referred to as hormone receptor (HR)-positive breast cancer, which is the most common subtype, accounting for about 75% of the total.

[0003] Although patients with early-stage HR-positive breast cancer generally have a good prognosis after endocrine therapy, approximately 30% to 40% of patients will experience systemic recurrence, and approximately 10% of patients will present with new metastatic breast cancer (MBC). Currently, MBC with HR-positive breast cancer (HR+MBC) is mainly 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 will die from the disease. Therefore, a lot of effort is still needed to explore new therapies that can be used 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 is the first phase Ib trial to evaluate the role of the anti-PD-1 inhibitor pembrolizumab monotherapy in TNBC. The results showed that the overall response rate (ORR) was 18.5% and the median response time was 17.9 weeks. The Phase II KEYNOTE-086 trial showed that the ORR of PD-L1 was 21.4%; in a randomized Phase II study of 88 HR+MBC patients exploring the efficacy of the combination of Eribulin mesylate and pembrolizumab, similar ORR and median progression-free survival (PFS) were observed for the combination in the PD-L1-positive subgroup, and no benefit of pembrolizumab was observed. Studies have shown that patients with HR-positive breast cancer are not very sensitive to immunotherapy. The possible reason is that compared with TNBC and HER2-positive breast cancer, HR-positive breast cancer exhibits less immune infiltration and fewer somatic mutations, and tumor mutations are less likely to produce new antigens, which is consistent with the characteristics of "immune desert tumors" in immunology.

[0004] In the process of exploring immunotherapy for HR-positive breast cancer, researchers have conducted a large number of trials and exposed the drawbacks of many combination therapies. The first study designed to evaluate the efficacy of pembrolizumab combined with palliative radiotherapy (RT) in patients with HR+MBC was forced to stop early because none of the first 8 patients achieved an objective response and there was no evidence that the combination prolonged PFS or overall survival (OS). And adverse events (AEs) occurred in 87.5% of patients. There is also a report exploring the benefits of CDK4 / 6i inhibitors on disease-free survival (DFS) in patients with HR+MBC, as well as the adverse reactions of these drugs in combination with immune checkpoint inhibitors (ICIs). Although ICIs and CDK4 / 6i are known to have synergistic activity, the toxicity of this combination is too high, especially the high incidence of interstitial lung disease and liver injury, which led to the interruption of the test.

[0005] Therefore, clinically speaking, ICIs can only make progress as a treatment option for HR-positive breast cancer when combined with established treatments already used in this disease setting or other drugs that enhance immune responses. Therefore, in order to improve the immunotherapy effect of luminal breast cancer and improve patient prognosis, it is urgent to conduct a detailed and comprehensive exploration of the immune characteristics of luminal breast cancer, find new immune targets, and activate tumor immune responses.

[0006] Tumor microenvironment (TME) is the environment in which tumors occur and develop. It is a complex network system composed of cells such as immune cells, fibroblasts, adipocytes, extracellular matrix (ECM), and various signaling molecules. During the progression of breast cancer, different components in the TME will have different inhibitory or promoting effects on cancer cells. There is a large proportion of natural killer cells (NK) and neutrophils in luminal breast cancer, while the proportion of cytotoxic T cells and naive and memory T cells is low. High abundance of tumor-associated macrophages (TAM) 1 and 2 and Treg lymphocytes show poor prognosis in luminal breast cancer. In addition, supporting cells in the TME of luminal breast cancer also directly or indirectly promote cancer progression. The heterogeneity of immune infiltrating cells in the tumor microenvironment of luminal breast cancer and the complex relationship between tumor phenotype and supporting cells make the treatment of this disease more challenging.

[0007] GATA binding protein 3 (GATA3) is expressed in multiple tissues, including the breast. GATA3 plays a vital role in maintaining the differentiation of mammary luminal 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 have shown that GATA3 expression levels are high in luminal breast cancer, and the expression of GATA3 in breast tumors is highly correlated with the expression of estrogen receptor α (ESR1). High expression of GATA3 plays a role in promoting tumorigenesis and cell proliferation in luminal breast cancer. Large-scale genome sequencing results show that GATA3 mutation frequency is very high in luminal breast cancer, and 10% to 15% of breast tumors carry mutations in this gene. The high frequency of GATA3 mutations in breast cancer indicates that they are driver mutations, and the prognosis of luminal cases with wild-type GATA3 is better than that of mutant cases. Therefore, high levels of GATA3 gene mutations may be clinically important. However, the specific mechanism of action of GATA3 in breast cancer immunity is not fully understood, and the contribution of GATA3 mutations in breast cancer immunity needs to be further explored. Summary of the invention

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

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

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

[0011] Immunotherapy by inhibiting GATA3 combined with PD1 inhibitors for breast cancer is effective in treating breast cancer.

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

[0013] Furthermore, 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 the expression of CCL5 cytokine.

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

[0019] In a second aspect, the present invention provides a recombinant lentiviral packaging vector, wherein the recombinant lentiviral packaging vector contains shRNA, wherein the nucleotide sequence of the positive 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 connected to the EcoRI and AgeI restriction sites of the Plko.1-puro vector.

[0021] In a third aspect, the present invention provides a recombinant cell, wherein the recombinant cell contains 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] In a fourth aspect, the present invention provides use of the recombinant lentiviral packaging vector and / or the recombinant cell in the preparation of a GATA3 gene inhibitor and / or a drug for treating breast cancer.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] GATA3 mediates the transcriptional regulation of IFNβ by inhibiting the enhancer activity of IFNB1, downregulating the type I interferon signaling pathway, thereby inhibiting the MHC-I antigen presentation pathway and the secretion of chemokine CCL5 in breast cancer cells, thereby reducing immune recognition and ultimately achieving immune escape. Immunotherapy that inhibits GATA3 and combines PD1 inhibitors to treat breast cancer can effectively treat breast cancer mice, increase IFNβ levels in mice, promote the MHC-I antigen presentation pathway in mice, increase CCL5 levels in mice, and increase CD8+T cell levels in the tumor immune microenvironment, thereby reducing tumor occurrence and inhibiting tumor growth. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a gene set enrichment analysis (GSEA) diagram.

[0026] Figure 2 This is a qPCR analysis of genes involved in the processing and presentation of MHC-I protein antigens in cells. A is MCF7 cells; B is T47D cells.

[0027] Figure 3 The content of HLA-ABC+ cells in GATA3 gene knockdown cells. A is the flow cytometric graph of MCF7 cells; B is the barplot graph of MCF7 cells; C is the flow cytometric graph of T47D cells; and D is the barplot graph of T47D cells.

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

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

[0031] Figure 7 Top signaling pathway enrichment after GATA3 knockout.

[0032] Figure 8 The heat map of the relative expression of interferon after GATA3 gene knockdown in MCF7 cells and T47D cells.

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

[0034] Fig.10 The mRNA expression of genes involved in the MHC-I class antigen processing and presentation signaling pathway in cells treated with different supernatants with or without GATA3 knockout. A is MCF7 cells; B is T47D cells.

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

[0036] Fig.12 Representative images of HLA-ABC+ cell staining in cells treated with PBS, IFN-β, IFN-λ1, or IFN-λ2. A is MCF7 cells; B is T47D cells.

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

[0038] Fig.14 The content of HLA-ABC+ cells in cells treated with PBS, IFN-β, IFN-λ1 or IFN-λ2. A is the flow cytometry graph of MCF7 cells; B is the barplot graph of MCF7 cells; C is the flow cytometry graph of T47D cells; D is the barplot graph of T47D cells.

[0039] Fig.15 ELISA was used to detect the expression of IFN-β in cells with GATA3 gene knockdown and overexpression. A is MCF7 cells; B is T47D cells; C is BT-549 cells; and D is MDA-MB-436 cells.

[0040] Fig.16 The content of HLA-ABC+ cells in different cells. A is the flow cytometry graph of MCF7 cells; B is the barplot graph of MCF7 cells; C is the flow cytometry graph of T47D cells; D is the barplot graph of T47D cells.

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

[0042] Fig.18 Barplot shows the secretion of CCL5 in different cells under different conditions such as GATA3 knockdown, IFN-β treatment and IFN-β Nab treatment. A is MCF7 cells; B is T47D cells.

[0043] Fig.19 Barplot shows the migration of CD8+T cells under different conditions.

[0044] Fig. 20 The ELISA method was used to determine the secretion of CCL5 in cells under different conditions of GATA3 overexpression, IFN-β and IFN-βNAb treatment. A is BT-549 cells; B is MDA-MB-436 cells.

[0045] Fig.21 is the CCL5 mRNA expression level in cells treated or not treated with IFN-β.

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

[0047] Fig.23 Barplot showing the association between SNP (rs10964832 allele status) and IFNB1 mRNA expression. P value was calculated using xx test. *P<0.05.

[0048] Fig.24 Luciferase reporter gene analysis was used to demonstrate the association of GATA3 WT and GATA3 G335fs with IFNB1 enhancer activity.

[0049] Fig.25 The heat map image shows the co-localization signal between GATA3 and REST / CoREST complex, and each row represents a GATA3 binding peak.

[0050] Fig.26 Barplot shows the effect of histone deacetylase inhibitor (HDAC) on the expression of IFNB1, HLA-A and CCL5 mRNA in cells. A is MCF7 cells; B is T47D cells.

[0051] Fig. 27 Luciferase reporter gene analysis shows the relationship between GATA3 knockout and CCL5 promoter activity. A is T47D cells; B is 293FT cells.

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

[0053] Fig.29 Schematic diagram of the preparation of mouse model.

[0054] Fig.30 To show the differences in tumor-infiltrating CD8+T cells. A is a flow cytometry graph 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; D is a barplot showing the relative number of CD8+IFNγ+T cells in each group.

[0055] Fig.31The data of each group of tumors. A is the picture of each group of tumors; B is the statistical chart of tumor weight in each group; C is the growth curve of each group of tumors; D is the stable knockout of GATA3 gene in 4T1 cells; E is a box plot showing the weight of different groups.

[0056] Fig.32 Representative images of multiple immunofluorescence staining of MHC-I (red), CD8 (yellow) and GATA3 (green) in different groups. DETAILED DESCRIPTION

[0057] To better illustrate the purpose, technical solutions and advantages of the present invention, the present invention will be further described below in conjunction with specific examples. Other materials, reagents, etc. used in the examples, unless otherwise specified, can be obtained from commercial sources.

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

[0059] 1. Experimental Methods

[0060] (I) Construction of plasmid

[0061] 1. Construction of 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 IFNB1 enhancer DNA sequence (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, respectively. The cDNA fragments were analyzed by agarose gel electrophoresis to determine the size of the target fragment, and then the gel was cut and recovered.

[0063] (2) The three cDNA fragments and the Plenti-puro plasmid vector in step (1) were double-digested with EcoI and XbalI endonucleases at 37°C for 2 h to obtain the three cDNA fragments and plasmid vector fragments after digestion, and then recovered by electrophoresis.

[0064] (3) Vector ligation: Use T4 DNA ligase to ligate the three cDNA fragments and the plasmid vector fragment after enzyme digestion in step (2) to obtain three ligation products.

[0065] 2. Plasmid transformation: Take 5μL of the ligation product and add it to 50μL of competent cells, ice bath for 30min, heat shock at 42℃ for 60s, add 200μL of non-resistant LB medium (lysing broth medium), and culture it in a 37℃ shaker for 60min to obtain bacterial liquid. Instantly centrifuge the bacterial liquid, remove the supernatant, and evenly spread the remaining competent cells on an LB plate containing 50μg / mL ampicillin, and culture it at 37℃ for 10-12h to obtain monoclonal colonies. Pick 10 colonies to 5mL of LB medium containing ampicillin, culture it in a 37℃ shaker for 6h, and then sequence it; retain the strain with the correct sequencing sequence, carry out large-scale culture to extract the plasmid, and put it in a -20℃ refrigerator for standby use.

[0066] 3. Plasmid amplification and extraction

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

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

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

[0070] (1) Cell preparation: MCF7 cells and T47D cells were inoculated into 24-well plates one day in advance and cultured so that the cell density reached 70-90% on the next day;

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

[0072] There are three siRNA sequences: Si NC (as a control): 5'-UAGGCGAAUCAUUUGUUCAAA-3'; SiGATA3-1: 5'-AACAUCGACGGUCAAGGCAAC-3' (SEQ ID NO: 1); SiGATA3-2: 5'-AAGCCUAAACGCGAUGGAUAU-3' (SEQ ID NO: 2). SiGATA3-1 and SiGATA3-2 have different targets, but both have high silencing efficiency.

[0073] *Explanation on SEQ ID NO: 1 and 2 in the sequence listing of the 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", and the base "t" in the RNA sequence is "u", so SEQ ID NO: 1 and 2 in the specification of the present invention are substantially the same as SEQ ID NO: 1 and 2 in the sequence listing.

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

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

[0076] (1) Cell preparation: MDA-MB-436 cells and BT549 cells were inoculated into 24-well plates one day in advance and cultured so that the cell density reached 70-90% on the next day.

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

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

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

[0080] (5) Slowly add the two (corresponding to the two plasmids) transfection mixture 2 of step (4) to the culture medium of the MDA-MB-436 cells and BT549 cells treated in step (1), gently mix them evenly, incubate them in a 37° C. incubator for 6 hours, replace the culture medium with complete culture medium, and continue to culture for 48 hours to obtain MDA-MB-436 cells overexpressing GATA3 and BT549 cells overexpressing GATA3.

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

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

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

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

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

[0086] Table 1

[0087] Gene Upstream primer (5'-3') Downstream primer (5'-3') 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 MCF7 cells and T47D cells with GATA3 knockdown, the MDA-MB-436 cells and BT549 cells with GATA3 overexpression, and their corresponding control cells. Take 1×10 5 Cells were plated and cultured for 48 h.

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

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

[0092] 4. Separate a blank tube from the control cells, add HLA-ABC+ flow cytometry antibody to all tubes except the blank tube, 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 with 500 μL PBS, add 5 μL 7-aminoactinomycin D (7-AAD), and incubate on ice in the dark for 5 min.

[0094] 6. Test on the machine.

[0095] 2. Experimental Results

[0096] GATA3 gene knockdown upregulated the mRNA expression of genes related to antigen presentation.

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

[0098] 2. If Figure 2 A (MCF7 cells) and Figure 2 As shown in B (T47D cells), qPCR analysis of genes involved in MHCI protein antigen processing and presentation in control cells (siNC) and GATA3 gene knockdown cells (siGATA3-1 and siGATA3-2). GATA3 gene knockdown, HLA-A, HLA-B, HLA-C, HLA-F, HLA-G, B2M, TAP1, TAP2, TAPBP, ERAP1, ERAP2, PSMB8 and PSMB9 expression were upregulated.

[0099] 3. Figure 3 A (MCF7 cells) and Figure 3 C (T47D cells) Flow cytometry graphs showing the content of HLA-ABC+ cells in the control group (siNC) and GATA3 gene knockdown cell groups (siGATA3-1 and siGATA3-2). Figure 3 B (MCF7 cells) and Figure 3 D (T47D cells) is the relative proportion of HLA-ABC+ cells in the control group (siNC) and GATA3 gene knockdown cell groups (siGATA3-1 and siGATA3-2) summarized by Barplot. HLA-ABC+ expression was upregulated after GATA3 gene 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 the control group (EV) and cells overexpressing the GATA3 gene (GATA3 WT) or GATA3 G335fs. When the GATA3 gene was overexpressed, the expression of HLA-B, B2M, TAP1, and PSMB8 was downregulated.

[0101] 5. Figure 5 A (BT-549 cells) and Figure 5 C (MDA-MB-436 cells) is a flow cytometry graph showing the content of HLA-ABC+ cells in the control group (Blank, EV), cells overexpressing GATA3 (GATA3 WT) and GATA3 G335fs. Figure 5 B (BT-549 cells) and Figure 5 D (MDA-MB-436 cells) is a barplot summarizing the relative proportion of HLA-ABC+ cells in the control group (Blank, EV), cells overexpressing GATA3 (GATA3 WT) and GATA3 G335fs. When the GATA3 gene is overexpressed, the amount of HLA-ABC+ cells decreases.

[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). After GATA3 gene knockdown, the expression of HLA-B was upregulated; when GATA3 gene was overexpressed, the expression of HLA-B was downregulated.

[0103] Example 2 GATA3 downregulates MHC-I expression by inhibiting IFN-β

[0104] 1. Experimental Methods

[0105] (I) Top signaling pathway enrichment and relative expression of interferon

[0106] 1. Extract RNA from MCF7 cells and T47D cells with GATA3 knockdown in Example 1 and cells in the control group, and sequence them.

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

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

[0109] Table 2

[0110] Gene Upstream primer (5'-3') Downstream primer (5'-3') IFNB1 CTTGGATTCCTACAAAGAAGCAGC TCCTCCTTCTGGAACTGCTGCA IFNL1 AACTGGGAAGGGCTGCCACATT GGAAGACAGGAGAGCTGCAACT IFNL2 TCGCTTCTGCTGAAGGACTGCA CCTCCAGAACCTTCAGCGTCAG CCL5 CCTGCTGCTTTGCCTACATTGC ACACACTTGGCGGTTCTTTCGG

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

[0112] 1. Treat cells with different culture supernatants

[0113] (1) MCF7 and T47D cells with GATA3 knockdown and control cells were cultured for 48 h, and 500 μL of supernatant was taken and used to culture normal MCF7 and T47D cells without GATA3 knockdown for 48 h.

[0114] 2. The cells treated with different culture supernatants were subjected to flow cytometry detection, and qPCR was performed to detect the expression of antigen presentation-related gene mRNA in the cells, using the same method as in Example 1.

[0115] (IV) Treat cells with different cytokines and perform tests

[0116] 1. Treat cells with different cytokines

[0117] Ordinary MCF7 and T47D cells without GATA3 knockdown were digested and centrifuged according to the method of Example 1. After counting, 1×10 5 Cells were plated, and PBS, 50 ng / mL IFN-β, 50 ng / mL IFN-λ1 or 50 ng / mL IFN-λ2 cytokines were added 6 h later, and the cells were cultured in a 37°C incubator for 48 h.

[0118] 2. Flow cytometry was performed on cells treated with different cells, and qPCR was performed to detect the expression of mRNA of antigen presentation-related genes in the cells, using the same method as in Example 1.

[0119] (V) Double antibody sandwich enzyme-linked immunosorbent assay (ELISA) to detect the expression of IFN-β in different cells

[0120] (1) Antigen coating: Add 50 μL hIFN-β capture 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 the liquid in the wells, and invert the 96-well plate on absorbent paper and pat dry.

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

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

[0124] (5) Prepare 10 ng / mL hIFN-β standard, add Blank and 50 μL of D1-D7 standards (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) to the 96-well plate treated in step (4).

[0125] (6) Add 50 μL of the sample (cells to be tested) diluted 10 times with Reagent deligent to the 96-well plate treated 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 treated in step (7), wash each well with 200 μL Wash buffer, wash three times, and pat the 96-well plate dry on absorbent paper for the last wash.

[0128] (9) Add 50 μL Quanti-luc4 to each well after treatment in step (8). TM Reagent, detected by ELISA reader at 490mm.

[0129] (10) Analyze the data and draw graphs.

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

[0131] 1. The GATA3 knockdown MCF7 and T47D cells and control cells were digested and centrifuged according to the method of Example 1. After counting, 1×10 5 The cells were plated, and 6 hours later, 50 ng / mL IFN-β and 50 ng / mL IFN-β neutralizing antibody (IFN-βNAb) were added to the groups, and cultured in a 37°C incubator for 48 hours.

[0132] 2. Flow cytometry was performed on cells treated with different cells in the same manner as in Example 1. Multiple immunofluorescence experiments were performed on cells treated with different cells in the following manner:

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

[0134] (2) Add 200 μL of 4% (v / w) paraformaldehyde to each well of 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 permeabilization 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 of 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 to 12 h.

[0137] (5) Recover the primary antibody in step (4), add 1 mL of PBS solution, wash on a shaker three times, 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 of step (5), wash on a shaker three times, 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 to 12 h.

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

[0140] (8) Use a syringe to remove the slide treated in step (9) and air dry it, add 5 μL of mounting medium, and let it stand for 10 minutes. Use a confocal microscope to capture and save images, and protect from light throughout the process.

[0141] 2. Experimental Results

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

[0143] 2. MCF7 cells ( Fig. 9 A) and T47D cells ( Fig. 9 B) Expression of CCL5, IFNL1, IFNL2, and IFNB1 mRNA in the presence or absence of GATA3 knockdown. The expression of CCL5, IFNL1, IFNL2, and IFNB1 mRNA decreased after GATA3 knockdown.

[0144] 3. MCF7 cells ( Fig.10 A) and T47D cells ( Fig.10 B) mRNA expression of genes involved in the MHC class I antigen processing and presentation signaling pathway in cells treated with different supernatants with or without GATA3 knockdown. When GATA3 was knocked down, HLA-A, HLA-B, HLA-C, HLA-F, HLA-G, B2M, TAP1, TAP2, TAPBP, ERAP1, ERAP2, PSMB8, and PSMB9 were upregulated.

[0145] 4. Fig.11 A (MCF7 cells) and Fig.11 C (T47D cells) is a flow cytometry graph showing the HLA-ABC+ cell content in cells treated with different culture supernatants. Fig.11 B (MCF7 cells) and Fig.11 D (T47D cells) is a barplot summarizing the proportion of HLA-ABC+ cells in cells treated with different culture supernatants. The HLA-ABC+ content and proportion increased after treatment with the supernatant of GATA3 knockdown cells.

[0146] 5. Fig.12 MCF7 cells treated with PBS, IFN-β, IFN-λ1 or IFN-λ2 ( Fig.12 A) and T47D cells ( Fig.12 Representative images of HLA-ABC+ cell staining in B). As can be seen, the HLA-ABC+ cell content of MCF7 cells and T47D cells treated with IFN-β increased.

[0147] 6. Fig.13 represents MCF7 cells treated with different cytokines (CCL5, IFN-β, IFN-λ1 or IFN-λ2) ( Fig.13 A) and T47D cells ( Fig.13B) Expression of HLA-B, B2M, TAP1 and PSMB8 in IFN-β treated cells. The expression of HLA-B, B2M, TAP1 and PSMB8 was higher in cells treated with IFN-β.

[0148] 7. Fig.14 MCF7 cells treated with PBS, IFN-β, IFN-λ1 or IFN-λ2 ( Fig.14 A) and T47D cells ( Fig.14 C) Flow cytometry graph showing the content of HLA-ABC+ cells. Fig.14 B (MCF7 cells) and Fig.14 D (T47D cells) is a barplot summarizing the content of HLA-ABC+ cells in different cells. The content of HLA-ABC+ cells in cells treated with IFN-β is higher.

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

[0150] 9. Fig.16 Flow cytometric analysis is shown to show the expression of HLA-ABC+ in different groups. Fig.16 A is the flow cytometry image of MCF7 cells; Fig.16 B is a barplot of MCF7 cells; Fig.16 C is the flow cytometry image of T47D cells; Fig.16 D is a barplot of T47D cells. After IFN-β treatment, the expression of HLA-ABC+ increased, while after IFN-β neutralizing antibody treatment, the expression of HLA-ABC+ decreased.

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

[0152] Example 3 Molecular Mechanism of GATA3-Mediated Immune Escape

[0153] 1. Experimental Methods

[0154] (A) According to the method of Example 2, GATA3 knockdown MCF7 and T47D cells, GATA3 overexpressing MDA-MB-436 and BT549 cells 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 the expression of CCL5 was detected by ELISA.

[0155] (II) Using CCL5 to detect the migration of CD8+T cells in different cells

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

[0157] 2. Use transwell chamber to detect the migration amount of CD8+T cells in each group of cells

[0158] (III) qPCR was used to detect the mRNA expression of CCL5 after treating ordinary MCF7 and T47D cells without knockdown of GATA3 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 those in Example 2.

[0159] (IV) Luciferase reporter gene analysis to detect the interaction between GATA3 and IFNB1 enhancer or CCL5 promoter 1. According to the method of Example 1, different plasmids were transfected into 293FT cells to obtain different transfected cell groups. Three replicate wells were set in each group to obtain 293FT cells transfected with different transfection groups. The different transfection groups were:

[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 with a firefly luciferase reporter gene; IFN-βEnhancer (IFNB1 plasmid constructed in Example 1): an IFNB1 enhancer fragment is inserted into the PGL3-Basic plasmid; Plenti-puro: a control plasmid for the GATA3 WT plasmid and the GATA3 G335fs plasmid; CCL5 Promoter: a CCL5 promoter fragment (chromosome 17:35880361-35882361) is inserted into the PGL3-Basic plasmid, and the construction method is the same 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 of 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 treated in step (2) and add it to a 96-well ELISA plate, add 100 μL of Luciferase Assay Reagent II (luciferase assay reagent), and detect the luciferase reaction intensity after 2 seconds.

[0166] (4) After step (3), add 100 μL Stop & Reagent, and the reaction intensity of the internal reference Renilla luciferase was detected after 2s.

[0167] (5) Calculate the data and draw a graph.

[0168] (V) Analysis of differential expression of proteins and genes in cells

[0169] 1. ChIP-seq and Cut&Tag data analysis

[0170] ChIP-seq data of MCF7 cell line were collected from ENCODE data. To find most related transcription factors of GATA3, colocalization analysis was performed based on the binding peaks of GATA3 and the peaks of other transcription factors and histone modifiers available in ENCODE using Beetools (v2.29.1). The top ranked factors included REST, SIN3A, HDAC2 and COREST, and their raw sequence data were then retrieved from ENCODE database, along with the ChIP-seq sequences of MCF7 and H3K4me1 of MCF7. Meanwhile, CUT&Tag data of GATA3, H3K27ac and H3K4me1 in MCF7 and T47D were newly generated. ChIP and CUT&Tag data were aligned to human genome GRCh38 by bowtie2 (v2.5.4). Duplicate reads were next labeled using Picard tool (v1.140). Peaks were called for each sample using Macs2 [Macs2]. Normalization to CPM (v3.5.1) was performed by deeptools (v3.5.1). 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 the human genome hg38 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) and differentially expressed gene analysis was performed using default parameters. Finally, deeptools (v3.5.1) was used for visualization.

[0174] (VI) Western Blotting to detect the expression of HLA-ABC proteins and NFκB and STAT1 signaling pathway proteins after GATA3 gene knockdown or overexpression

[0175] 1. Extract cell protein

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

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

[0178] (3) Use a cell scraper to scrape off the protein mixture in step (2), transfer it to a clean 1.5 mL centrifuge tube using a pipette, and lyse it in a 4°C refrigerator for 35 min.

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

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

[0181] 2. Experimental Results

[0182] Fig.18 Barplot showing MCF7 cells ( Fig.18 A) and T47D cells ( Fig.18 B) CCL5 secretion under different conditions such as GATA3 knockdown, IFN-β treatment and IFN-β NAb treatment. The expression of CCL5 in cells treated with GATA3 knockdown and IFN-β was significantly higher than that in other groups.

[0183] Fig.19 Barplot shows the migration of CD8+T cells under different conditions. The migration of CD8+T cells in the CCL5-treated control group was significantly higher than that in other groups, followed by cells with GATA3 knockdown.

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

[0185] Fig.21 is the expression level of CCL5 mRNA in cells treated or not treated with IFN-β. As the IFN-β content increases, the expression level of CCL5 mRNA in cells increases.

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

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

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

[0189] Fig.25 The heat map image shows the co-localization signal between GATA3 and REST / CoREST complex, and each row represents a GATA3 binding peak.

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

[0191] Fig. 27 Luciferase reporter gene analysis showed that T47D cells ( Fig. 27 A) and 293FT cells ( Fig. 27 B) Transcriptional activation of CCL5 promoter after GATA3 knockdown.

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

[0193] Example 4 Orthotopic transplantation tumor model in mice and combined therapy

[0194] 1. Experimental Methods

[0195] 1. Cell Preparation

[0196] (1) Design of shGATA3

[0197] Four groups of shRNA sequences targeting the GATA3 gene were designed using an online tool (BLOCK-iT RNAi Designer). The shRNA sequences are shown in Table 3, and 4T1 cells were transiently transfected (the method is the same as step (ii) of Example 1), and the GATA3 knockdown efficiency was verified by qPCR (the same as 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, and the experimental steps were the same as those in Example 1 to obtain the shGATA3-1 Plko.1-puro plasmid and the shNC Plko.1-puro plasmid.

[0202] (3) Virus packaging

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

[0204] (4) Construction of 4T1 stable transgenic strain

[0205] One day in advance, 4T1 cells were inoculated in a 24-well plate and cultured so that the cell density reached 70-90% on the next day; on the next day, 1 mL of the virus constructed in step (3) was transfected into the 4T1 cells, and after culturing at 37°C for 48 h, 1 μg / mL puromycin was added and continued to be cultured, and drug screening was performed until all 4T1 cells not transfected with the virus died. Harvest and passage 4T1+Plko.1 (containing shNCPlko.1-puro plasmid) and 4T1+shGATA3 cells (containing shGATA3-1 Plko.1-puro plasmid). Subculture 4T1+Plko.1 or 4T1+shGATA3 cells, digest the cells, wash once with PBS, and then count the cells to make the cell density reach 5×10 7 Pieces / mL.

[0206] 2. Vaccination and treatment

[0207] The concentration was 5×10 7 The cells were injected into the subcutaneous tissue of mice at a volume of 100 μL per mouse. The tumor formation in the mice was observed. On the sixth day after the injection, the tumor grew to about 100 mm. 3 The tumor volume and mouse body weight were measured every other day, and PBS, 100 μg / mL IFN-β or 100 μg / mL anti-PD1 (PD1 monoclonal antibody, InVivoMAb anti-mousePD-1 (CD279), brand: Bioxcell, catalog number: BE0146) were intraperitoneally injected according to the groups. IFN-β: 7th, 9th and 11th days after injection, anti-PD1: 6th, 8th and 10th days after injection.

[0208] The groups are shown in Table 1

[0209] Table 4

[0210] Grouping name quantity treat 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 killed by carbon dioxide inhalation, and tumor tissues, paracancerous tissues and spleen were obtained. Mononuclear cells were isolated in vitro or tissue sections were made to evaluate the infiltration degree of different cell types in tumor tissues and the expression of marker genes.

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

[0214] Tissue multiplex immunofluorescence method is as follows:

[0215] (1) Dewaxing: Bake the tissue sections at 65°C for 2 h to obtain baked tissue sections; soak the baked tissue sections in xylene I, II, and III one by one, each for 15 min, and soak them in anhydrous ethanol, 95% (v / v) ethanol, 85% (v / v) ethanol, and 75% (v / v) ethanol for 5 min each to obtain rehydrated tissue sections.

[0216] (2) Antigen repair: Place the rehydrated tissue sections from step (1) into a repair box filled with sodium citrate antigen repair solution and perform antigen repair 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 for 3 times with shaking, 5 minutes each time.

[0217] (3) Marking tissue: Gently shake dry the tissue slices processed in step (2), and use a tissue pen to circle the outer contour of the tissue.

[0218] (4) Inactivation of endogenous peroxidase: 100 μl of 3% (v / v) hydrogen peroxide was added to the tissue sections treated in step (3), incubated at room temperature in the dark for 20 min, and washed with PBS for 5 min, for three times.

[0219] (5) Blocking: The tissue sections treated in step (4) were gently shaken dry, and goat serum was added and blocked at room temperature for 1 h to obtain blocked tissue sections.

[0220] (6) Primary antibody incubation: dilute the GATA3 primary antibody with PBS (the volume ratio of the GATA3 primary antibody to PBS is 1:200) to obtain the diluted primary antibody; drip 100 μl of the diluted primary antibody onto the blocked tissue section in step (5), cover the tissue, and incubate in a 4°C refrigerator overnight.

[0221] (7) Secondary antibody incubation: Wash the tissue sections treated in step (6) with PBS solution by shaking for 3 times, each time for 5 min, then add 50 μL of the secondary antibody of the corresponding species (mouse / rabbit) at a ratio of 1:500, incubate at room temperature for 1 h, and wash with PBS by shaking for 3 times, each time for 5 min.

[0222] (8) Adding iF594-TSA staining working solution: Gently shake dry the tissue sections treated in step (7), add 50 μl of 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) for 3 times, 5 min each time.

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

[0224] (10) Counterstaining of cell nuclei with DAPI: Dry the tissue sections treated in step (9), add DAPI staining solution, incubate at room temperature in the dark for 10 min, and wash with PBS for 3 times with shaking, 5 min each time.

[0225] (11) Sealing: Spin dry the tissue slices treated in step (10), and add an anti-fluorescence quenching agent to seal the slices.

[0226] (12) Take photos and place the tissue sections processed in step (11) in a light-proof section box at 4°C for 15 days.

[0227] 2. Experimental Results

[0228] Fig.29 Schematic diagram of the preparation of mouse model.

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

[0230] Fig.31 A is the tumor picture of each group; Fig.31 B is the statistical graph of tumor weight in each group; Fig.31 C is the tumor growth curve of each group. P value was calculated using xx test. ***P<0.001; Fig.31 D shows stable knockout of GATA3 in 4T1 cells; Fig.31 E is a box plot showing the body weight of different groups.

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

[0232] Based on the above experimental results, immunotherapy with GATA3 knockout combined with anti-PD1 or IFN-β combined 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 solution of the present invention rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. Application of GATA3 inhibitors and PD1 inhibitors in the preparation of drugs for the treatment of breast cancer.

2. The use according to claim 1, characterized in that: The breast cancer is luminal breast cancer.

3. The use according to claim 1, characterized in that: 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.

4. The use according to claim 1, characterized in that: The GATA3 inhibitor promotes IFN-β expression.

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

6. The use according to claim 1, characterized in that: The GATA3 inhibitor promotes CCL5 cytokine expression.

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

8. A recombinant lentiviral packaging vector, characterized in that: The recombinant lentiviral packaging vector contains shRNA, the nucleotide sequence of the positive 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.

9. A recombinant cell, characterized in that The recombinant cell contains shRNA, 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.

10. Use of the recombinant lentiviral packaging vector according to claim 8 and / or the recombinant cell according to claim 9 in the preparation of a GATA3 inhibitor and / or a drug for treating breast cancer.

Images