A method for screening CRISPR libraries of multidimensional immune stress in breast cancer

Abstract

The present invention discloses two sets of CRISPR libraries (MiTCL-L, 2796 genes; MiTCL-S, 273 genes), uses a variety of different immunodeficient mice for high-throughput screening, and finds key genes that play an immune escape role in the microenvironment of triple-negative breast cancer (TNBC), laying an important theoretical and experimental foundation for the discovery of new immunotherapy targets, which is conducive to breakthroughs in the immunotherapy of triple-negative breast cancer. The candidate genes screened and discovered by the present invention include the confirmed immune heterogeneity star genes LAG3 and CD38, confirming the reliability of the screening platform.

Description

Technical Field

[0001] The present invention relates to the field of tumor treatment, and in particular to a method for screening a multi-dimensional immune pressure CRISPR library for breast cancer. Background Art

[0002] The most concerned topic in cancer treatment is tumor immunotherapy, among which immune checkpoint blockade is the most successful. However, immune checkpoint blockade cannot achieve sustained clinical response in most patients, and tumor cells can express more other genes to regulate their escape or resistance to tumor immunity. Therefore, it is necessary to explore other immunotherapy targets and treatment strategies in the tumor immune process.

[0003] Triple-negative breast cancer (TNBC) is one of the difficulties in breast cancer treatment today because of its lack of effective therapeutic targets. As a new treatment for TNBC, immunotherapy has shown good application prospects, but at the same time it also has challenges such as single target and limited efficacy. Although immunotherapy drugs have been approved in the field of triple-negative breast cancer, there are still many clinical problems that need to be solved. For example, although the expression of PD-L1 has been used as a biomarker to predict the efficacy of immune checkpoint inhibitors, there are still concerns in conventional clinical trials: PD-L1 is a dynamic marker and its expression may change over time; some patients who test positive for PD-L1 may not respond to treatment, while other patients who test negative may still respond. In addition, monotherapy targeting PD-1 / PD-L1 is not effective in breast cancer, which may indicate the presence of other key molecules in breast cancer that mediate immune escape.

[0004] Therefore, clinically, it is necessary to discover new tumor immune targets specific to triple-negative breast cancer and develop targeted targeted therapy strategies in order to achieve greater breakthroughs in the immunotherapy of triple-negative breast cancer. By constructing different CRISPR-Cas9 library high-throughput library screening platforms, genes related to tumor immunity can be systematically and comprehensively screened to fully explore potential targets for tumor treatment. Summary of the invention

[0005] To overcome the above problems, the present invention uses a multi-dimensional immune pressure mouse model to carry out two rounds of CRISPR library screening, mainly using the different immune microenvironments of normal (Balb / c, complete immune system) and various immunodeficient mice (NPG, T cell, B cell, NK cell deficiency; CB-17Scid, T cell, B cell deficiency; Balb / c-nude mice, T cell deficiency) for transplanted tumors (4T1 cells introduced with MiTCL library) Different immune pressures, screening and discovering key molecules that can regulate tumor immune escape.

[0006] Specifically, the first aspect of the present invention provides an sgRNA library, wherein the sgRNA library is MiTCL-L and / or MiTCL-S; the MiTCL-L comprises sgRNAs targeting 2796 genes selected from Table 1, and the MiTCL-S comprises sgRNAs targeting 273 genes selected from Table 2.

[0007] In certain embodiments, the target sequence of MiTCL-L is selected from Table 1.

[0008] In certain embodiments, the target sequence of MiTCL-S is selected from Table 2.

[0009] The second aspect of the present invention provides the use of the sgRNA library described in the first aspect of the present invention in screening tumor immunity-related genes.

[0010] The third aspect of the present invention provides the use of the sgRNA library described in the first aspect of the present invention in preparing a kit for screening tumor immunity-related genes.

[0011] The fourth aspect of the present invention provides a method for screening a multi-dimensional immune pressure CRISPR library for breast cancer, the method comprising the following steps: a) construction of a MiTCL-L plasmid library; b) using the MiTCL-L library to perform a first round of CRISPR screening based on different immune pressure mouse models; c) using bioinformatics to analyze the screening results of the MiTCL-L immune library, and identifying candidate genes related to immune escape and immune surveillance of triple-negative breast cancer; d) based on the screening results of the MiTCL-L library, performing a second round of screening of the MiTCL-S plasmid library; e) a second round of immune screening based on the MiTCL-S library; f) using bioinformatics to analyze the screening results of the MiTCL-S immune library, and identifying genes related to immune escape.

[0012] In certain embodiments, the construction of the MiTCL-L plasmid library in step a) uses the MiTCL-L sgRNA library described in the first aspect of the present invention.

[0013] In certain embodiments, in step a), the sgRNA is connected to the lentiGuide-Puro plasmid and amplified to form a MiTCL-L plasmid library.

[0014] In certain embodiments, in the step b), the Cas9 gene is introduced into 4T1 cells using a lentivirus, and after screening positive cells, the MiTCL-L library packaged by the lentivirus is introduced, and then the positive mixed library cells are screened; the positive mixed library cells are divided into 9 parts: 3 parts of cells are baseline cells on day 0, and genomic DNA is immediately extracted; 3 parts of cells are inoculated into immune-perfect Balb / c mice, and 3 parts of cells are inoculated into severely immune-deficient NPG mice.

[0015] In certain embodiments, in step c), the DNA of the baseline cells and the DNA of the transplanted tumor are amplified, purified and sequenced using a nested PCR scheme, and the MAGeCK algorithm is used to calculate and compare the distribution of sgRNA in the baseline cells before injection and the collected tumor tissue cells, and the β value of each gene in the tumor tissue cells compared with the baseline cells is calculated; the β value of each gene is calculated by the maximum likelihood estimation (MLE) module in the MAGeCK algorithm, and the δ value of each gene in the Balb / c versus NPG screening is calculated; a group of candidate genes related to triple-negative breast cancer immune escape and immune surveillance are identified based on the β value and δ value.

[0016] In certain embodiments, in step d), the construction of the MiTCL-S plasmid library uses the MiTCL-S sgRNA library described in the first aspect of the present invention.

[0017] In certain embodiments, in step e), four types of mice with different immunodeficiencies are selected and injected with 4T1-Cas9 cells infected with the MiTCL-S library to construct a breast cancer transplant tumor model, and tumor growth is observed and genomic DNA of tumor tissue is extracted for next-generation sequencing.

[0018] In certain embodiments, step f) includes performing MAGeCK algorithm analysis on the second-generation sequencing results to calculate the δ value of each gene in the MiTCL-S library under 6 different immune pressure screenings, namely (1) T, B, NK cell screening, (2) T, B cell screening, (3) T cell screening, (4) B cell screening, (5) B, NK cell screening and (6) NK cell screening, and using the transcriptome data of the TNBC cohort in FUSCC to analyze the expression of the genes in the MiTCL-S library in TNBC tumor tissues, and comprehensively combining the δ value and transcriptome data to screen out immune escape-related genes in TNBC.

[0019] The beneficial effects of the present invention are:

[0020] This project constructed two sets of CRISPR libraries (MiTCL-L, 2796 genes; MiTCL-S, 273 genes), and used a variety of different immunodeficient mice for high-throughput screening to discover key genes that play an immune escape role in the TNBC microenvironment. The candidate genes screened and discovered by this method include the confirmed immune heterogeneity star genes LAG3 and CD38, confirming the reliability of the screening platform.

[0021] The CRISPR library screening method in this project revealed the key molecules that regulate tumor immune escape, laying an important theoretical and experimental foundation for the discovery of new immunotherapy targets, which is conducive to breakthroughs in the immunotherapy of triple-negative breast cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0023] Figure 1 The results of the initial round of CRISPR library screening based on the immune pressure model are shown. (A) Gene function distribution of the MiTCL-L library targeting 2796 mouse immune-related genes; (B) Mouse tumor growth curve and tumor weight of 4T1-Cas9 cells introduced with the MiTCL-L library; (C) Cumulative distribution curve of sgRNAs in the MiTCL-L library in different samples; (D) Scatter plot of the β value distribution of library genes; (E and F) β values ​​of H2-D1 (E) and Cd274 (F) under different immune pressure screening.

[0024] Figure 2 Figure 3 shows the results of the second round of CRISPR screening based on the immune pressure model. (A and B) Growth curves of four mouse transplanted tumors of 4T1-Cas9 cells introduced into the MiTCL-S library; (C) Cumulative distribution curve of sgRNAs of the MiTCL-S library in different samples; (D) Spearman correlation of different samples showed good heterogeneity between groups; (E) Box plot of the distribution of sgRNAs of the MiTCL-S library in different samples.

[0025] Figure 3 Comparison table of CRISPR library screening under multi-dimensional immune stress mouse model.

[0026] Figure 4 The results of the second round of CRISPR screening based on the immune pressure model are shown in Figure 1. (AF) Scatter plot of the δ values ​​of the MiTCL-S library enrichment comparison under 6 different immune screening pressures and the difference in TNBC transcriptome expression; (G) The δ values ​​of the genes with common differential changes under 6 immune screening pressures, dark colors represent δ>0, and light colors represent δ<0. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Unless otherwise defined, technical or scientific terms used herein shall have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs.

[0029] The following is an explanation of a breast cancer multi-dimensional immune pressure CRISPR library screening method of the present invention in conjunction with specific examples.

[0030] Example 1 Establishment of a CRISPR library screening platform for mouse immune genes (MiTCL-L) based on different immune stress mouse models

[0031] 1.1 Construction of a MiTCL-L library targeting 2796 mouse immune-related

[0032] Genes related to human diseases and the immune system were selected from the Mouse Genome Informatics (MGI), and 2796 genes were screened to form the Mouse immune Targeting CRISPR Library-Large (MiTCL-L) targeting mouse immune genes. The genes in the library are mainly enriched in cytokine and receptor pathways, Toll-like receptor pathways, NK cells, T cells, B cells, and antigen presentation pathways. Figure 1 A). Subsequently, referring to the mouse CRISPR knockout library (Pooled Library #73632, #73633, #73633-LV) of John & David on Addgene (http: / / www.addgene.org / ), 2796 genes were selected for this study, and each gene matched 4 sgRNAs, totaling 11184 sgRNAs to form the MiTCL-L immune library (Table 1). In addition, a negative control sgRNA that did not target any gene was set up. By customizing a DNA oligonucleotide mixed library containing a 20bp targeting sequence specific to sgRNA, the target sequence was inserted into the lentiGuide-Puro plasmid by Gibson Ligation, and then electroporated (GenePulser Xcell electroporator of BioRad) at 200 × The mixed library was obtained by colony amplification with a coverage of .

[0033] 1.2 Using the MiTCL-L library for the first round of CRISPR screening based on different immune stress mouse models

[0034] The mouse breast tumor 4T1 cells used in the first round of screening were derived from the breast tumor of BalB-c mice, so they have the characteristics of spontaneous tumor formation in BalB-c mice. The mice used in this project are (1) BalB-c mice: they have a complete immune system, with T cells, B cells, NK cells and other immune cells (such as monocytes, neutrophils, etc.); (2) NPG mice (NOD-PrkdcscidII2rgnull): the establishment of this mouse is through the gene homologous recombination technology on mouse embryonic stem cells, to establish the Il2rg (Interleukin-2 receptor gamma chain) gene knockout cell line of ES cells derived from C57B / 6 mice, and obtain Il2rg gene knockout mice. Its important characteristics are the lack of T cells, B cells, and NK cell activity in mice, and almost no rejection reaction to foreign cells or tissues.

[0035] First, 293T cells and packaging plasmids PAX2 (Addgene, 35002) and PMD2.G (Addgene, 12259) were used for lentiviral packaging, and the virus was collected and titered. The Cas9 gene was introduced into 4T1 cells at a low MOI using lentivirus, and positive cells were screened with blasticidin. Then, the MiTCL-L library virus was introduced by centrifugal infection (MOI = 0.5) and the positive mixed library baseline cells were screened with puromicin for 5 days. The positive mixed clone cells were divided into 9 parts: 3 cells were used as baseline cells on day 0, and genomic DNA was immediately extracted; 3 cells were inoculated into immune-perfect Balb / c mice, and 3 cells were inoculated into severely immune-deficient NPG mice. The tumor growth time was about 4 weeks. In vivo screening was performed with the help of the in vivo environment of mice.

[0036] The results showed that the tumor growth rate of immune-complete Balb / c mice was significantly slower than that of severely immune-deficient NPG mice ( Figure 1 B), and the tumor tissues were weighed at the end of the experiment, and it was also found that the tumors in Balb / c mice were smaller than those in NPG mice ( Figure 1 B) The above results suggest that a complete immune system has an inhibitory effect on tumor growth, and when the immune system is defective, the tumor grows rapidly.

[0037] 1.3 Analysis of MiTCL-L immune library screening results using bioinformatics

[0038] The DNA of the benchmark cells and the transplanted tumors was amplified, purified and sequenced using a nested PCR protocol, with a sequencing coverage depth of 500× for each sgRNA. For the data of CRISPR-Cas9 gene library screening, the quality of the library screening was first analyzed. The original FASTQ file generated by the illumina platform was analyzed by Geneious 7.0 (Biomatters Inc, Auckland) to obtain the number of reads for each sgRNA corresponding to each sample. The distribution of sgRNAs in benchmark cells and transplanted tumor samples was analyzed using the cumulative distribution function, and it was found that the sgRNAs in the benchmark cells had good uniformity, while differential loss / amplification of sgRNAs occurred in the transplanted tumor samples ( Figure 1 C), indicating that some sgRNAs were lost, while some were significantly enriched. In order to further analyze the impact of which sgRNAs were screened on cells, the MAGeCK algorithm was used to calculate and compare the distribution of sgRNAs in baseline cells before injection and collected tumor tissue cells, and the β value of each gene in tumor tissue cells compared with baseline cells was calculated. The β value of each gene was calculated by the maximum likelihood estimation (MLE) module in the MAGeCK algorithm, and the δ value of each gene in the Balb / c versus NPG screening was calculated. β>0 means that the distribution of sgRNAs corresponding to the gene increased after screening, and β<0 means a decrease. The larger the absolute value of β, the more important the gene is under this type of immune pressure screening ( Figure 1 D). Based on the comparison of β between Balb / c mice and NPG mice, the genes in quadrant I promote tumor growth in both the microenvironment of the immune system (Balb / c mice) and the severely immunodeficient (NPG mice), while the genes in quadrant III are involved in tumor growth suppression ( Figure 1 D). The genes in the second and fourth quadrants affect tumor growth through the immune environment. The genes in the fourth quadrant are involved in immune escape; the genes in the second quadrant are involved in immune surveillance ( Figure 1 D). The β values ​​of the gene in Balb / c mice and NPG mice were further compared, and the δ value (δ = β immunodeficiency low - β immunodeficiency high) was calculated to show the effect of the gene on tumor immune escape and immune surveillance. δ>0 means that the gene is involved in immune surveillance after screening, such as H2-D1 (MHC-Ⅰ) ( Figure 1 E); δ<0, indicating that the gene is involved in immune escape after screening, Cd274 (PD-L1), which can bind to PD-1 and inhibit T cell activation ( Figure 1 F).

[0039] Through the first round of MiTCL-L library screening based on different immune pressure mouse models, a group of candidate genes related to triple-negative breast cancer immune escape and immune surveillance can be identified, and then a second round of MiTCL-S library screening will be carried out around this immune gene set.

[0040] Example 2 Establishment of MiTCL-S library targeting key immune genes

[0041] 2.1 Preparation of MiTCL-S library for the second round of screening

[0042] According to the screening results of MiTCL-L library, the β value of each gene was calculated by the maximum likelihood estimation (MLE) module in the MAGeCK algorithm, and the δ value of each gene in the Balb / c versus NPG screening was calculated. According to the δ value, the top 8% genes with δ>0 and δ<0, as well as the middle part of the genes were selected as positive controls, totaling 273 genes, as the targeted genes of the Mouse immune Targeting CRISPR Library-Small (MiTCL-S) library. Subsequently, 10 sgRNAs were matched for each target gene, totaling 2730 sgRNAs, forming the MiTCL-S library (Table 2). At the same time, a negative control sgRNA that did not target any gene was set. The construction method of the library is similar to that of MiTCL-L.

[0043] 2.2 Second round of immune screening based on MiTCL-S library

[0044] In the second round of research, four mice with different immune deficiencies were selected, and the order of immunity from low to high was: NOD-PrkdcscidII2rgnull (T cell, B cell, NK cell deficiency) <CB-17Scid (T cell, B cell deficiency) <Balb / c-nude (T cell deficiency) <Balb / c (intact immune system). These mice with different immune characteristics were used for screening to discover key tumor immune regulatory factors. Consistent with the first round of screening methods, 4T1-Cas9 cells infected with the MiTCL-S library were injected in situ into the mammary pad to construct a breast cancer transplant tumor model, and tumor growth was observed ( Figure 2 A and Figure 2 B) Extract genomic DNA from tumor tissue for next-generation sequencing.

[0045] 2.3 Analysis of MiTCL-S immune library screening results using bioinformatics

[0046] In order to explore the changes of MiTCL-S library under different immune pressure screening, the changes in the number of sgRNA detected in different samples (plasmid, reference cells, and transplanted tumor tissues) were compared. The distribution of sgRNAs in reference cells and transplanted tumor samples was analyzed using the cumulative distribution function, and it was found that differential loss of sgRNAs occurred in transplanted tumor samples ( Figure 2 C). Spearman correlation analysis revealed that baseline cells had good repeatability, while xenograft tumors had greater variability ( Figure 2 D); The box plot also shows that some sgRNAs are lost during tumorigenesis, suggesting that the genes targeted by these sgRNAs may be key genes in the progression of triple-negative breast cancer ( Figure 2 E).

[0047] The MAGeCK algorithm was further used to analyze the results of the second-generation sequencing, and the four groups of mice were compared in pairs (the mice with stronger immunity were defined as the intervention group, and the mice with weaker immunity were defined as the control group). By comparing the four different groups of mice, different immune pressure screenings can be performed ( Figure 3 ): (1) T, B, NK cell screening; (2) T, B cell screening; (3) T cell screening; (4) B cell screening; (5) B, NK cell screening; (6) NK cell screening. The MAGeCK algorithm calculated the δ value of each gene in the MiTCL-S library under 6 different immune pressure screenings, and used the transcriptome data of the TNBC cohort in FUSCC to analyze the expression of MiTCL-S library genes in TNBC tumor tissues ( Figure 4 AF). Gene δ<0 indicates that the gene regulates tumor cells involved in immune escape, and the transcriptome data of triple-negative breast cancer were combined for comprehensive analysis. According to the δ value and FUSCC transcriptome analysis results, it was found that under the six immune screening pressures, many genes with δ<0 were expressed more in tumor tissues than in adjacent tissues (log2 FoldChange>0.5 compared with adjacent tissues) ( Figure 4 The dark dots in AF indicate that the expression of genes with different immune screening pressures was analyzed by intersection analysis. It was found that there were 11 genes with δ < 0 under six different immune screening pressures, and they were generally highly expressed in tumor tissues ( Figure 4 G), suggesting that these genes may be associated with immune escape in TNBC.

[0048] Among the 11 candidate genes screened, the negative regulatory effect of lymphocyte activation gene-3 (LAG3) on immunity has been widely reported. LAG3 is a member of the protein Ig superfamily and belongs to type 1 transmembrane protein. It is expressed on activated human NK cells, T cells, activated B cells and plasmacytoid dendritic cells. LAG3 binds to MHC class II with an affinity 100 times higher than that of CD4. LAG3 plays a negative regulatory role in T cell proliferation and activation. Targeting LAG3 has become a new strategy for tumor treatment. Targeting LAG3 can activate effector T cells and inhibit Treg suppressive activity, so this LAG3 with a dual mechanism of action has become an important target for checkpoint inhibition. At present, LAG3 inhibitors combined with paclitaxel have been proven to be effective in clinical trials for the first-line treatment of metastatic breast cancer. Another well-known gene screened out is CD38 (Cluster of Differentiation 38). CD38 is an important metabolic enzyme located on the cell surface. The enzymatic activity of CD38 is manifested by catalyzing the conversion of NAD+ into metabolites such as ADPR, cADPR, and NAM. Its products play an important role in the process of immune regulation. CD38 is highly expressed in non-solid tumors, especially multiple myeloma (MM), which makes CD38 one of the good targets for targeted therapy of non-solid tumors such as multiple myeloma and CLL. Johnson & Johnson has developed a CD38-mediated, cytolytic antibody drug with broad-spectrum killing activity. It can target and bind to the transmembrane extracellular enzyme CD38 molecules highly expressed on the surface of multiple myeloma and various solid tumor cells, inducing rapid death of tumor cells.

[0049] The above findings suggest that CRIPSR screening based on a multidimensional immune stress mouse model can effectively screen out key regulatory factors that are closely related to the immune regulation of triple-negative breast cancer.

[0050] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0051] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This description method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

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Claims

1. A sgRNA library, characterized in that The sgRNA library is MiTCL-L and / or MiTCL-S; the MiTCL-L comprises sgRNAs targeting 2796 genes in Table 1, and the MiTCL-S comprises sgRNAs targeting 273 genes in Table 2.

2. The sgRNA library according to claim 1, characterized in that The target sequence of MiTCL-L includes Table 1; the target sequence of MiTCL-S includes Table 2.

3. Use of the sgRNA library according to claim 1 or 2 in screening genes related to tumor immunity.

4. Use of the sgRNA library according to claim 1 or 2 in preparing a kit for screening genes related to tumor immunity.

5. A method for screening a CRISPR library for multi-dimensional immune stress in breast cancer, characterized in that: Screening is performed using the sgRNA library described in claim 1, and the method comprises the following steps: a) construction of a MiTCL-L plasmid library; b) using the MiTCL-L library to perform a first round of CRISPR screening based on different immune pressure mouse models; c) using bioinformatics to analyze the screening results of the MiTCL-L immune library and identify candidate genes related to immune escape and immune surveillance of triple-negative breast cancer; d) based on the screening results of the MiTCL-L library, preparing a MiTCL-S plasmid library for a second round of screening; e) a second round of immune screening based on the MiTCL-S library; f) using bioinformatics to analyze the screening results of the MiTCL-S immune library and identify genes related to immune escape.

6. The method according to claim 5, characterized in that The construction of the MiTCL-L plasmid library in step a) uses the MiTCL-L sgRNA library described in claim 1 or 2.

7. The method according to claim 5, characterized in that The sgRNA is connected to the lentiGuide-Puro plasmid and amplified to form a MiTCL-L plasmid library.

8. The method according to claim 5, characterized in that In the step b), the Cas9 gene is introduced into 4T1 cells using a lentivirus, and after screening positive cells, the MiTCL-L library packaged by the lentivirus is introduced, and then the positive mixed library cells are screened; the positive mixed library cells are divided into 9 parts: 3 parts of cells are baseline cells on day 0, and genomic DNA is immediately extracted; 3 parts of cells are inoculated into immune-perfect Balb / c mice, and 3 parts of cells are inoculated into severely immune-deficient NPG mice.

9. The method according to claim 5, characterized in that In the step c), the DNA of the baseline cells and the DNA of the transplanted tumor are amplified, purified and sequenced using a nested PCR scheme, and the MAGeCK algorithm is used to calculate and compare the distribution of sgRNA in the baseline cells before injection and the collected tumor tissue cells, and the β value of each gene in the tumor tissue cells compared with the baseline cells is calculated; the β value of each gene is calculated by the maximum likelihood estimation (MLE) module in the MAGeCK algorithm, and the δ value of each gene in the Balb / c versus NPG screening is calculated; a batch of candidate genes related to triple-negative breast cancer immune escape and immune surveillance are identified based on the β value and δ value.

10. The method according to claim 5, characterized in that In the step d), the construction of the MiTCL-S plasmid library uses the MiTCL-S sgRNA library according to claim 1 or 2.

11. The method according to claim 5, characterized in that In the step e), four types of mice with different immunodeficiencies were selected and injected with 4T1-Cas9 cells infected with the MiTCL-S library to construct a breast cancer transplant tumor model, and the tumor growth was observed and the genomic DNA of the tumor tissue was extracted for next-generation sequencing.

12. The method according to claim 5, characterized in that The step f) includes performing MAGeCK algorithm analysis on the second-generation sequencing results to calculate the δ value of each gene in the MiTCL-S library under 6 different immune pressure screenings, namely (1) T, B, NK cell screening, (2) T, B cell screening, (3) T cell screening, (4) B cell screening, (5) B, NK cell screening and (6) NK cell screening, and using the transcriptome data of the TNBC cohort in FUSCC to analyze the expression of the MiTCL-S library genes in TNBC tumor tissues, and comprehensively combining the δ value and transcriptome data to screen out immune escape-related genes in TNBC.

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