Method and device for discovering target antigens for chimeric antigen receptors

Abstract

The method for discovering a target antigen for a chimeric antigen receptor of the present invention includes the steps of: acquiring gene expression information of tumor cells on a single-cell basis using an analysis device; extracting candidate antigen genes having expression levels equal to or greater than a threshold value from among the genes using the analysis device; determining all gene combinations that can constitute the candidate antigen genes; and determining target gene combinations in which at least one gene included in the gene combinations is expressed.

Description

[Technical field]

[0001] The technology described below relates to a technique for discovering antigens for chimeric antigen receptors (CARs). [Background technology]

[0002] Anti-cancer immune cell therapy is a treatment technique that uses T cells cultured outside the body to eliminate tumor cells. Chimeric antigen receptors are designed with a binding site that recognizes an antigen and binds it to the active domain inside the T cell. CAR-T is a T cell therapy that applies chimeric antigen receptors to T cells. Meanwhile, CAR-NK is a cell therapy that applies chimeric antigen receptors to NK (Natural Killer) cells. Summary of the Invention [Problem to be solved by the invention]

[0003] For CAR-T and CAR-NK, it is very important to find an effective target antigen. In finding a target antigen, the key indicators are the coverage of the antigen to act on multiple tumor cells and the specificity of the antigen to act only on tumor cells while minimizing the cytotoxicity to normal cells.

[0004] The technology described below aims to provide a technique for discovering target antigens that chimeric antigen receptors bind to in order to treat specific tumors. [Means for solving the problem]

[0005] The method for discovering a target antigen for a chimeric antigen receptor includes the steps of: an analysis device acquiring gene expression information of a tumor cell in a single cell unit; an analysis device extracting candidate antigen genes having an expression level equal to or higher than a threshold value from among the genes; an analysis device determining gene combinations that can be constituted by the candidate antigen genes; an analysis device determining a target gene combination in which at least one gene included in the gene combinations is expressed; and an analysis device determining at least one of the target gene combinations as a gene combination for the target antigen.

[0006] The analysis device for designing a chimeric antigen receptor includes an input device for receiving gene expression data of a sample tumor cell on a single cell basis, a storage device for storing a program for determining an antigen to be recognized by a chimeric antigen receptor using gene expression information of the tumor cell, and a calculation device for determining a target gene combination or target genes for a target antigen of the sample tumor cell recognized by the chimeric antigen receptor in a gene combination that can be constructed from a plurality of genes among genes of candidate antigens determined by the gene expression data. Effect of the Invention

[0007] The technology described below aims to discover antigens with broad spectrum and high specificity in the design of chimeric antigen receptors. [Brief description of the drawings]

[0008] [Figure 1] Examples of antigen expression patterns in single cells and cell populations.

[0009] [Diagram 2] This is an example of a target antigen mining system for chimeric antigen receptors.

[0010] [Diagram 3] 1 is an example of a flow chart for the target antigen mining process for a chimeric antigen receptor.

[0011] [Figure 4] 1 is another example of a flowchart for the process of mining target antigens for chimeric antigen receptors.

[0012] [Diagram 5] 1 is yet another example of a flow chart for the process of discovering target antigens for chimeric antigen receptors.

[0013] [Figure 6] This is an example of the process by which an analytical device discovers a target antigen.

[0014] [Figure 7] These are experimental results showing gene expression patterns in tumor cells and normal cells for colon cancer samples and lung cancer samples.

[0015] [Figure 8] These are experimental results for gene combinations in which one or more genes are expressed in lung cancer samples.

[0016] [Figure 9] These are experimental results for gene combinations in which one or more genes are expressed in colon cancer samples.

[0017] [Figure 10] These are experimental results for gene combinations in which two or more genes are simultaneously expressed in lung cancer samples.

[0018] [Figure 11] These are experimental results for gene combinations in which two or more genes are simultaneously expressed in colon cancer samples.

[0019] [Figure 12] These are experimental results for tumor cell-specific gene combinations in lung cancer samples.

[0020] [Figure 13]These are experimental results for tumor cell-specific gene combinations in colon cancer samples.

[0021] [Figure 14] This is an example of an analytical device that detects antigens for chimeric antigen receptors. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] The technology described below can be modified in various ways and can have various embodiments, and a specific embodiment will be described in detail with reference to the drawings. However, this does not limit the technology described below to a specific embodiment, and it should be understood that the technology described below includes all modifications, equivalents, and alternatives included in the spirit and technical scope of the technology described below.

[0023] Terms such as first, second, A, and B are used to describe various components, but the components are not limited by the terms, and are used only to distinguish one component from another. For example, a first component may be named a second component, and similarly, a second component may be named a first component, without departing from the scope of the technology described below. The term "and / or" includes a combination of multiple associated listed items or any item among multiple associated listed items.

[0024] In the terms used in this specification, the singular term "a" or "an" should be understood to include the plural term unless the context clearly dictates otherwise, and terms such as "comprise" or "comprise" should be understood to mean the presence of a stated feature, number, step, operation, component, part, or combination thereof, but not to exclude the presence or possible addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0025] Before describing the drawings in detail, it should be made clear that the components in this specification are merely classified according to the main function of each component. That is, two or more components described below may be combined into one component, or one component may be divided into two or more components according to more specific functions. Furthermore, each of the components described below may additionally perform some or all of the functions of the other components in addition to its own main function, and some of the main functions of each component may be exclusively performed by the other components.

[0026] Additionally, in performing a method or method of operation, each step of the method may be performed differently from the order specified, unless the context clearly dictates otherwise, i.e., each step may be performed identically to the order specified, substantially simultaneously, or in the reverse order.

[0027] The terms used in the description will be explained below.

[0028] An antigen is a substance that induces an immune response.

[0029] Hereinafter, an antigen is a site that a chimeric antigen receptor recognizes in a tumor cell. The antigen may be, but is not limited to, tumor-specific antigens (TSAs) that are not expressed in normal cells but are expressed only in tumor cells, or tumor-associated antigens (TAAs) that are also expressed in normal cells but undergo antigenic changes during the canceration process of cells and are expressed at a particularly high frequency in cancer cells.

[0030] Chimeric antigen receptors mainly utilize single-chain variable fragments (scFv). Therefore, antigens can include proteins, sugar chains, glycolipids, etc. expressed on the surface of tumor cells.

[0031] Hereinafter, a target antigen is defined as a target that a chimeric antigen receptor recognizes for the purpose of killing tumor cells. The techniques described below are for discovering target antigens.

[0032] By sample is meant a single cell or multiple cells, cell fragments, body fluids, etc. taken from an individual to be analysed.

[0033] Genetic data or genetic information refers to genetic information calculated by analyzing a sample. For example, genetic data may include base sequences obtained from deoxyribonucleic acid (DNA), ribonucleic acid (RNA) or protein from cells, tissues, etc., gene expression data, genetic variations from standard genetic data, DNA methylation, etc. In the following description, genetic data of cells mainly refers to information related to antigens expressed on the cell surface. Therefore, genetic data may include information such as genome, transcriptome, proteome, etc. In other words, genetic data refers to data that can confirm the degree of expression of a specific gene (especially antigen expression on the cell surface) regardless of type. It is assumed that genetic data is digital data that can be processed by a computer device.

[0034] Figure 1 shows examples of antigen expression patterns in single cells and cell populations.

[0035] FIG. 1(A) and FIG. 1(B) illustrate the state in which a single antigen is expressed in tumor cells. In FIG. 1(A) and FIG. 1(B), the single antigen is antigen 1. FIG. 1(A) is an example of observing expression at the single cell level, and FIG. 1(B) is an example of observing expression in a cell population. Referring to FIG. 1(A), antigen 1 has 100% coverage in a single cell. Referring to FIG. 1(B), antigen 1 has 4 / 7 coverage in a cell population. Therefore, if CAR-T is designed with a chimeric antigen receptor that recognizes antigen 1 that has been confirmed to be expressed based on the results of FIG. 1(B), the CAR-T will attack only a specific clone in tumor cells and will not be able to eliminate other clones in which the antigen is not expressed. Of course, the same is true for CART-NK.

[0036] FIG. 1(C) and FIG. 1(D) illustrate a state in which multiple antigens are expressed in tumor cells. In FIG. 1(A) and FIG. 1(B), the multiple antigens are antigen 1 and antigen 2. FIG. 1(C) is an example of observing expression at the single cell level, and FIG. 1(D) is an example of observing expression in a cell population. Referring to FIG. 1(C), antigen 1 and antigen 2 have 100% coverage on a single cell. Referring to FIG. 1(D), antigen 1 and antigen 2 have 4 / 7 coverage on a cell population. Therefore, if CAR-T is designed with a chimeric antigen receptor that recognizes antigen 1 or antigen 2 that has been confirmed to be expressed based on the results of FIG. 1(D), the chimeric antigen receptor cell will attack only a specific clone in tumor cells and will not be able to eliminate other clones in which the antigen is not expressed. Of course, the same is true for CART-NK.

[0037] In conclusion, if antigen expression is not verified based on a single cell but is instead determined based on population expression as in the conventional method, it is difficult to design a chimeric antigen receptor with a wide range of activity. In order to design a chimeric antigen receptor with a wide range of activity and high specificity, it is important to discover an effective target antigen. A new methodology for discovering target antigens is described below.

[0038] Fig. 2 is an example of a system 100 for mining target antigens for chimeric antigen receptors. Analytical devices 130 and 140 are devices for mining target antigens for chimeric antigen receptors. In Fig. 1, the analytical devices are shown in the form of a server 130 and a computer terminal 140. The server 130 may provide a service for mining target antigens on a network. The computer terminal 140 may be connected to a network or may be an individual device for mining target antigens. Meanwhile, the analytical devices 130 and 140 may be embodied in various forms.

[0039] The genetic analysis device 110 analyzes a sample to generate genetic data of the sample. The genetic data DB 120 can store and manage the generated genetic data. The genetic data may include the gene sequence of the sample, gene expression information, etc. The genetic data includes expression information of antigen genes on the surface of tumor cells. The genetic data includes information on the expression level of antigen genes. Meanwhile, each of the multiple genes corresponds to one antigen.

[0040] The genetic data DB 120 may be a public DB that contains the results of experiments conducted by many researchers. Alternatively, the genetic data DB 120 may contain genetic data for samples from specific patients. In this case, the analyzers 130 and 140 may discover antigens that are customized for each patient.

[0041] The analysis devices 130 and 140 analyze the genetic data to find target antigens for the chimeric antigen receptors. The process by which the analysis devices 130 and 140 find target antigens will be described later.

[0042] The users 10 and 20 can check the results of target antigen discovery for a specific tumor or a specific patient. The user 10 can connect to the server 130 through a user terminal (PC, smartphone, etc.) and check the analysis results performed by the server 130. The user 20 can check the results of target antigen discovery through a computer terminal 140 that he or she uses.

[0043] FIG. 3 is an example of a flow chart for a process 200 of mining target antigens for chimeric antigen receptors.

[0044] The analyzer obtains gene expression information of sample tumor cells (S210). Here, the sample may be samples collected from multiple individuals for a specific tumor (e.g., lung cancer), or the sample may be cells taken from a specific patient. The analyzer may also obtain gene expression information of normal cells of the sample (S210). The information on the normal cells may be used to evaluate specificity. Here, the tumor cells and normal cells may be cells obtained from a diverse cell population rather than a single clone.

[0045] The genetic data of tumor cells and / or normal cells collected by the analysis device is called source data. The source data includes gene expression information of individual cells through single cell analysis. The tumor cells included in the source data can be called a tumor cell group. The normal cells included in the source data can be called a normal cell group.

[0046] The analysis device can filter valid data from the source data (S220). The analysis device can select genes of candidate antigens from the source data (S220). The candidate antigens correspond to antigens that are a population for discovering target antigens. The genes of candidate antigens refer to genes that are directly or indirectly involved in the expression of the antigen. Genes involved in the expression of candidate antigens can be named candidate genes. Also, a collection of genes involved in the expression of each candidate antigen can be named candidate gene group.

[0047] Various criteria may be used for selecting candidate genes. (i) The analysis device may select genes expressed at a certain percentage or more of cells included in a tumor cell group based on a tumor cell group as candidate genes. For example, the analysis device may select genes for antigens expressed at 1% or more in the tumor cell group as candidate genes. (ii) The analysis device may select genes with a certain difference in expression pattern between tumor cells and normal cells as candidate genes. For example, the analysis device may analyze differential expression genes (DEG) and select genes that are differentially expressed in tumor cells compared to normal cells as candidate genes. The analysis device may select genes whose expression level in tumor cells is greater than that in normal cells by a reference value or more as candidate genes. (iii) Furthermore, the analysis device may select candidate genes by combining the criteria (i) and (ii). For example, the analysis device may select genes that are differentially expressed at a certain level in tumor cells from among genes for antigens expressed at 1% or more in the tumor cell group as candidate genes.

[0048] The analyzer determines all possible combinations of candidate genes based on the filtered candidate antigen genes (candidate genes) (S230). The analyzer can determine all possible combinations depending on the number of mathematical cases. Alternatively, the analyzer can determine possible gene combinations based on genes that are actually expressed simultaneously, taking into account the gene expression relationship.

[0049] The analysis device checks whether at least one gene included in each gene combination is expressed in tumor cells at a reference rate or higher. The analysis device determines a target gene combination based on the rate (action range) of cells expressing at least one gene included in the combination among all tumor cells (S240). For example, if tumor cells expressing at least one gene included in the combination account for 60% or more of all tumor cells, the analysis device can determine the combination as the target gene combination. The target gene combination includes genes involved in the expression of a target antigen recognized by a chimeric antigen receptor. At least one gene included in the gene combination is involved in the expression of one target antigen.

[0050] The analyzer determines a final gene combination for the target antigen from the target gene combinations (S250). (i) The analyzer can determine at least one gene combination that ranks high among the target gene combinations based on the action range as the final gene combination. (ii) The analyzer can determine at least one gene combination whose action range in normal cells is equal to or lower than a reference value among a plurality of gene combinations that rank high among the target gene combinations based on the action range as the final gene combination.

[0051] In Fig. 3, the analyzer finds target antigens based on at least one antigen expressed in tumor cells. That is, if even one gene in a gene combination has an action range in tumor cells that is greater than a reference value, the analyzer may determine that the gene is involved in an effective candidate antigen. In other words, if even one antigen is expressed in tumor cells at a certain rate or more, the analyzer determines that the antigen is a target antigen.

[0052] FIG. 4 is another example of a flow chart for a process 300 of mining target antigens for chimeric antigen receptors.

[0053] The analyzer obtains gene expression information of sample tumor cells (S310). Here, the samples may be samples collected from multiple individuals for a particular tumor (e.g., lung cancer), or the samples may be cells taken from a particular patient. The analyzer may also obtain gene expression information of normal cells of the sample (S310). The information on the normal cells may be used to evaluate specificity. Here, the tumor cells and normal cells may be cells obtained from a diverse cell population rather than a single clone.

[0054] The analysis device can filter valid data from the source data (S320).The analysis device can select genes of candidate antigens (candidate genes) from the source data (S320).

[0055] Various criteria may be used for selecting candidate genes. (i) The analysis device may select genes expressed at a certain percentage or more of cells included in a tumor cell group based on a tumor cell group as candidate genes. For example, the analysis device may select genes for antigens expressed at 1% or more in a tumor cell group as candidate genes. (ii) The analysis device may select genes with a certain difference in expression pattern between tumor cells and normal cells as candidate genes. For example, the analysis device may perform DEG analysis to select genes that are differentially expressed in tumor cells compared to normal cells as candidate genes. The analysis device may select genes whose expression level in tumor cells is greater than that in normal cells by a reference value or more as candidate genes. (iii) Furthermore, the analysis device may select candidate genes by combining the criteria (i) and (ii). For example, the analysis device may select genes that are differentially expressed at a certain level in tumor cells as candidate genes from among genes for antigens expressed at 1% or more in a tumor cell group.

[0056] The analyzer determines all possible combinations of candidate genes based on the filtered candidate antigen genes (candidate genes) (S330). The analyzer can determine all possible combinations mathematically depending on the number of cases. Alternatively, the analyzer can determine possible gene combinations based on genes that are actually expressed simultaneously, taking into account the gene expression relationship.

[0057] The analysis device checks whether the genes included in each gene combination are expressed in tumor cells at a reference rate or more. The analysis device determines a target gene combination based on the rate (action range) of cells expressing the genes included in the combination among all tumor cells (S340). For example, if the tumor cells expressing the genes included in the combination account for 60% or more of all tumor cells, the analysis device can determine the combination as the target gene combination. The target gene combination includes genes involved in the expression of a target antigen recognized by a chimeric antigen receptor. The genes included in the gene combination are involved in the expression of one target antigen. The genes may also be involved in the expression of one antigen. However, it is assumed here that the genes express different antigens from each other.

[0058] The analyzer determines a final gene combination for the target antigen from the target gene combinations (S350). (i) The analyzer can determine at least one gene combination that ranks high among the target gene combinations based on the action range as the final gene combination. (ii) The analyzer can determine at least one gene combination, the action range of which in normal cells is equal to or lower than a reference value, among a plurality of gene combinations that rank high among the target gene combinations based on the action range as the final gene combination.

[0059] In Fig. 4, the analyzer finds target antigens based on multiple antigens expressed in tumor cells. That is, when multiple genes in a gene combination have an action range in tumor cells that is greater than a reference value, the analyzer can determine that the multiple genes are involved in different candidate antigens.

[0060] FIG. 5 is another example of a flow chart for a process 400 of mining target antigens for a chimeric antigen receptor.

[0061] The analyzer obtains gene expression information of sample tumor cells (S410). Here, the samples may be samples collected from multiple individuals for a particular tumor (e.g., lung cancer), or the samples may be cells taken from a particular patient. The analyzer may also obtain gene expression information of normal cells of the sample (S410). The information on the normal cells may be used to evaluate specificity. Here, the tumor cells and normal cells may be cells obtained from a diverse cell population rather than a single clone.

[0062] The analysis device can filter valid data from the source data (S420).The analysis device can screen genes of candidate antigens in the source data (S420).

[0063] Various criteria may be used for selecting candidate genes. (i) The analysis device may select genes expressed at a certain percentage or more of cells included in a tumor cell group based on a tumor cell group as candidate genes. For example, the analysis device may select genes for antigens expressed at 1% or more in a tumor cell group as candidate genes. (ii) The analysis device may select genes with a certain difference in expression pattern between tumor cells and normal cells as candidate genes. For example, the analysis device may perform DEG analysis to select genes that are differentially expressed in tumor cells compared to normal cells as candidate genes. The analysis device may select genes whose expression level in tumor cells is greater than that in normal cells by a reference value or more as candidate genes. (iii) Furthermore, the analysis device may select candidate genes by combining the criteria (i) and (ii). For example, the analysis device may select genes that are differentially expressed at a certain level in tumor cells as candidate genes from among genes for antigens expressed at 1% or more in a tumor cell group.

[0064] The analyzer determines positive candidate genes and negative candidate genes from the genes of the candidate antigens (S430). A positive candidate gene means a gene related to an antigen that is specifically expressed in tumor cells or is highly expressed in tumor cells. (i) The analyzer can select, from among the genes of the candidate antigens, a gene whose range of action in tumor cells is equal to or exceeds a reference value as a positive candidate gene. (ii) Alternatively, the analyzer can select, from among the genes of the candidate antigens, a gene that is expressed in a number of tumor cells equal to or exceeds a reference value as a positive candidate gene.

[0065] When the analysis device determines a positive candidate gene, the analysis device determines at least one negative candidate gene for the positive candidate gene. To this end, the analysis device must hold information on the expression correlation between genes. That is, gene correlation information means information on whether the expression of a specific gene promotes or inhibits the expression of at least one other gene. The analysis device can grasp the correlation information between genes by using transcript information. A negative candidate gene is a gene whose expression pattern has a negative relationship with a positive candidate gene. That is, a negative candidate gene is a gene whose expression amount decreases when a positive candidate gene is expressed in a large amount. The analysis device can determine a negative candidate gene whose expression pattern has a negative relationship with the determined positive candidate gene. The analysis device can also determine multiple negative candidate genes for one positive candidate gene.

[0066] The analysis device determines all possible gene combinations consisting of positive candidate genes and negative candidate genes (S440). The analysis device can determine all possible combinations depending on the number of mathematical cases. Alternatively, the analysis device can determine possible gene combinations by targeting genes that are actually expressed simultaneously, taking into account the expression relationship of genes.

[0067] The analyzer checks whether at least one gene included in each gene combination is expressed in tumor cells at a reference rate or higher. The analyzer can determine a target gene combination based on the rate (range of action) of cells expressing at least one gene included in the combination in total tumor cells (S450). Furthermore, the analyzer can determine a target gene combination based on the expression rate of genes that inhibit the chimeric antigen receptor in normal cells (S450).

[0068] Some examples of the analysis device determining the target gene combination will be described below. (i) The analysis device may determine the combination as the target gene combination if the tumor cells expressing at least one positive candidate gene included in the combination account for 60% or more of the total tumor cells (this is merely an example of a reference value). (ii) The analysis device may determine the combination as the target gene combination if the tumor cells expressing at least one negative candidate gene included in the combination account for less than 10% of the total tumor cells. (iii) The analysis device may determine the combination as the target gene combination if the ratio of normal cells expressing the negative gene among normal cells expressing at least one positive candidate gene included in the combination is 60% or more. In this case, when a chimeric antigen receptor binds to the antigen of the negative gene during the production of CAR-T or CAR-NK cells, it must be designed to inhibit the immune response, so such a negative gene can be called an immune inhibitory gene, which can play a role in minimizing damage to normal cells. (iv) The analysis device may determine the combination as the first target gene combination if the tumor cells expressing at least one positive candidate gene included in the combination account for 60% or more of the total tumor cells. Thereafter, the analysis device may again determine a final target gene combination using the primary target gene combination as a population. For example, the analysis device may determine a secondary target gene combination in which, among normal cells expressing at least one positive candidate gene included in each combination, normal cells expressing an immune inhibitory gene account for 60% or more of the normal cells. The secondary target gene combination may be the final target gene combination.

[0069] The analyzer determines a final gene combination for the target antigen from among the target gene combinations (S46). (i) The analyzer can determine at least one gene combination that ranks high among the target gene combinations based on the action range as the final gene combination. (ii) The analyzer can determine at least one gene combination whose action range in normal cells is equal to or lower than a reference value among a plurality of gene combinations that rank high among the target gene combinations based on the action range as the final gene combination.

[0070] 6 is an example of a process 500 in which an analysis device discovers a target antigen. The gene data DB stores gene expression information of tumor cells. The gene data DB may store gene expression information of normal cells. The gene data DB may also store information on expression correlations between genes.

[0071] The analysis device can receive input of tumor information desired to be analyzed (S510). The tumor information can include tumor type, clinical information, patient information, etc. (i) The tumor information can define a specific tumor with a specific clinical condition. The clinical information can include the race of the sample, the sex of the sample, the age of the sample, the tumor progression state (early, middle, end, etc.), the anatomical site from which the sample was extracted, etc. In this case, the tumor information defines a specific tumor with a specific clinical condition. (ii) The tumor information can also define a specific tumor for a specific patient.

[0072] The analysis device can input or receive source data corresponding to the tumor information input from the gene data DB (S520).

[0073] The analysis device can select candidate antigen genes from the source data (S530). Gene filtering of the candidate antigen genes is as described above. Meanwhile, the process of selecting candidate genes can be omitted.

[0074] The analysis device constructs possible gene combinations using the selected genes or genes transferred from the gene data DB. Thereafter, the analysis device can select a target gene combination for each possible gene combination based on the scope of action of the genes included in the combination (S540). Alternatively, the analysis device can select a target gene combination for each possible gene combination based on the specificity of the genes included in the combination (S540). The process of determining the target gene combination is as shown in Figures 3 to 5. The analysis device can select the target gene combination itself or a more effective specific gene combination from among the target gene combinations as the gene combination or genes of the final target antigen (S540).

[0075] The analytical device can then transmit the final target antigen information for the chimeric antigen receptor to another object, or can design a recognition site for the chimeric antigen receptor that recognizes the final target antigen (S550).

[0076] Hereinafter, the in silico experimental process and results for the process of discovering target antigens based on actual gene data will be described.

[0077] The source data was prepared by collecting the following data: The researchers used protein analysis data from mass spectrometry for 41 cell types during the experiment, transcriptome data from 610 tumor cell lines, 2,769 tumor cell membrane protein genes extracted from the human surfaceome resource constructed through machine learning (Bausch-Fluck et al. PNAS, 2018), protein and transcriptome data for 375 tumor cell lines (Nusinow et al. Cell, 2020), and 1,421 cell membrane protein genes extracted from the Gene Ontology database. The source data includes 3,687 unique genes and their expression information.

[0078] The researchers targeted lung cancer and colorectal cancer for their analysis. Using LUAD and LUSC in lung cancer as the criteria, the researchers selected 498 genes that were differentially expressed in tumor cells from among genes present in tumor cells and normal cells. Using COAD and READ in colorectal cancer as the criteria, the researchers also selected 315 genes that were differentially expressed in tumor cells from among genes present in tumor cells and normal cells.

[0079] The single-cell transcriptome data for lung cancer were from 58 samples from 44 patients. The transcriptome data for colon cancer were from 33 samples from 23 patients. Tumor epithelial cells were isolated through single-cell transcriptome analysis techniques, and the remaining immune cells were considered as normal cells. The lung cancer cells consisted of 165,511 tumor cells and 42,995 normal cells, and the colon cancer cells consisted of 47,285 tumor cells and 16,404 normal cells.

[0080] In the following, all processes described as being performed by a "researcher" refer to processes performed by a researcher using an "analysis device," which is a computer device.

[0081] The researchers first filtered candidate antigen genes from the source data. They selected genes that showed a minimum gene expression (cell coverage) of 1% or more in tumor cells through single cell analysis. They also selected genes that showed a difference in expression value itself above the reference value through DEG analysis between normal cells and tumor cells. Ultimately, the researchers derived 163 genes in lung cancer and 110 genes in colon cancer. Figure 7 shows the experimental results of gene expression patterns of tumor cells and normal cells for colon cancer samples and lung cancer samples. Figure 7 shows the results of t-SNE (Stochastic Neighbor Embedding), which represents gene expression patterns in a reduced dimension. Figure 7 (A) shows the expression patterns of 163 lung cancer genes. The left side of Figure 7 (A) shows the expression difference between tumor cells and normal cells based on all genes, and the right side shows the expression difference based on specific genes. Figure 7 (B) shows the expression patterns of 110 genes. The left side of FIG. 7(B) shows the expression difference between tumor cells and normal cells based on all genes, and the right side shows the expression difference based on specific genes.

[0082] The researchers selected 70 genes with a tumor cell coverage of 10% or more out of 163 lung cancer genes, excluding the CLDN4 (93.5%) gene, which has a tumor cell coverage of 90% or more. The researchers determined 2,415 gene combinations using the 70 genes. For each gene combination, the researchers converted the presence or absence of gene expression in a single cell unit in which at least one gene included in the combination is expressed into binary information. The researchers selected 253 combinations with a tumor cell coverage of 60% or more. Figure 8 shows the experimental results for gene combinations that express one or more genes in lung cancer samples. Figure 8 (A) shows the expression rate of 253 gene combinations in tumor cells and normal cells. Figure 8 (B) shows gene combinations with a relatively high coverage in tumor cells, and the top combinations with a coverage of 80% or more are displayed in dotted boxes. In this case, the analyzer can select the gene combination with the highest coverage in tumor cells from the top combinations as the final antigen candidate. In addition, the analysis device can select a gene combination that has a high action range in tumor cells and a low action range in normal cells as a final antigen candidate. In summary, the analysis device can select a final antigen candidate based on at least one of the action range in tumor cells and the action range in normal cells.

[0083] The researcher selected genes with a tumor cell coverage of 10% or more from among 110 colon cancer genes. The researcher used the selected genes to determine 2,278 gene combinations. The researcher converted the presence or absence of gene expression in a single cell unit in which at least one of the genes included in the combination was expressed for each gene combination into binary information. The researcher selected 248 combinations with a tumor cell coverage of 60% or more. Figure 9 shows the experimental results for gene combinations in which at least one gene is expressed in a colon cancer sample. Figure 9 (A) shows the expression rate of 248 gene combinations in tumor cells and normal cells. Figure 9 (B) shows gene combinations with a relatively high coverage in tumor cells, and the top combinations with a coverage of 80% or more are displayed in dotted boxes. In this case, the analysis device can select the gene combination with the highest coverage in tumor cells from among the top combinations as the final antigen candidate. The analysis device can also select the gene combination with a low coverage in normal cells from among the gene combinations with a high coverage in tumor cells as the final antigen candidate. In summary, the analytical device can select final antigen candidates based on at least one of the following criteria: range of activity in tumor cells and range of activity in normal cells.

[0084] The researchers selected 163 lung cancer genes that have a tumor cell coverage of 10% or more. The researchers used the selected genes to determine 2,415 gene combinations. For each gene combination, the researchers converted the presence or absence of gene expression in a single cell unit in which two or more genes included in the combination are simultaneously expressed into binary information. The researchers selected 589 combinations in which the tumor cell coverage is 10% or more. Figure 10 shows the experimental results for gene combinations in which two or more genes are simultaneously expressed in lung cancer samples. Figure 10 (A) shows the expression rate of 589 gene combinations in tumor cells and normal cells. Figure 10 (B) shows gene combinations with a relatively high coverage in tumor cells, and the top combinations with a coverage of 50% or more are displayed in dotted boxes. In this case, the analyzer can select the gene combination with the highest coverage in tumor cells from the top combinations as the final antigen candidate. The analyzer can also select the gene combination with a low coverage in normal cells from among the gene combinations with a high coverage in tumor cells as the final antigen candidate. The analysis device may also select a gene combination having a high correlation between two or more co-expressed genes as a final antigen candidate. In summary, the analysis device may select a final antigen candidate based on at least one of the range of action in tumor cells, the range of action in normal cells, and the expression relationship between genes.

[0085] The researchers selected 110 colon cancer genes that have a tumor cell coverage of 10% or more. The researchers used the selected genes to determine 2,278 gene combinations. For each gene combination, the researchers converted the presence or absence of gene expression in a single cell unit in which two or more genes included in the combination are simultaneously expressed into binary information. The researchers selected 537 combinations that have a tumor cell coverage of 10% or more. Figure 11 shows the experimental results for gene combinations in which two or more genes are simultaneously expressed in colon cancer samples. Figure 11 (A) shows the expression rate of 537 gene combinations in tumor cells and normal cells. Figure 11 (B) shows gene combinations with a relatively high coverage in tumor cells, and the top combinations with a coverage of 50% or more are displayed in dotted boxes. In this case, the analyzer can select the gene combination with the highest coverage in tumor cells from among the top combinations as the final antigen candidate. The analysis device may also select a gene combination that has a low action range in normal cells from among gene combinations that have a high action range in tumor cells as a final antigen candidate. The analysis device may also select a gene combination that has a high expression correlation between two or more co-expressed genes as a final antigen candidate. In summary, the analysis device can select a final antigen candidate based on at least one of the action range in tumor cells, the action range in normal cells, and the expression correlation between genes.

[0086] The researchers used transcript sequence data from 10,459 individuals obtained from the TCGA DB to calculate the co-expression index between gene combinations in tumors. The researchers derived possible combinations for the six major candidate genes (positive candidate genes) selected from lung cancer and colon cancer, respectively, and genes with negative correlations (negative candidate genes). The researchers used the protection rate to evaluate the specificity of the chimeric antigen receptor. The protection rate refers to the proportion of normal cells expressing tumor cell-specific genes (positive genes) that also express immune inhibitory genes (negative genes) that have an inhibitory effect on the chimeric antigen receptor. In this case, when the chimeric antigen receptor binds to the antigen of the inhibitory gene during the production of CAR-T or CAR-NK cells, it must be designed to inhibit the immune response, which can serve to minimize damage to normal cells. The inhibitory genes may be based on the results of the researchers' own experiments or on results that have already been studied based on the characteristics of the chimeric antigen receptor.

[0087] The researchers selected major positive candidate genes for lung cancer. The major positive candidate genes were selected based on the range of action in tumor cells, and consisted of six genes with a wide range of action. The researchers also selected negative candidate genes whose expression patterns were negatively related to each positive candidate gene. More than one negative candidate gene can be selected for each positive candidate gene. The researchers selected 462 combinations with a range of action in tumor cells of 60% or more for all possible gene combinations of the selected positive candidate genes and negative candidate genes.

[0088] FIG. 12 shows the results of an experiment on tumor cell-specific gene combinations in lung cancer samples. FIG. 12 (A) shows the expression ratios of 462 gene combinations in tumor cells and normal cells. FIG. 12 (B) displays gene combinations with a relatively wide range of action on tumor cells. FIG. 12 (B) shows values ​​for the items of the range of action in tumor cells (tumor coverage), the range of action in normal cells (normal coverage), the protection rate, and the expression correlation (TCGA correlation) of genes belonging to the gene combination. In this case, the analysis device can select gene combinations with a range of action in tumor cells higher than a certain value as final antigen candidates. The analysis device may also select gene combinations with a range of action in normal cells lower than a certain value as final antigen candidates from gene combinations with a high range of action in tumor cells. The analysis device may also select gene combinations with a high inhibition rate higher than a certain value as final antigen candidates from gene combinations with a high range of action in tumor cells. The analysis device may also select gene combinations with a high expression correlation between positive candidate genes and negative candidate genes as final antigen candidates. In summary, the analytical device can select final antigen candidates by comprehensively considering the range of activity in tumor cells, the range of activity in normal cells, the inhibition rate, and the expression relationship between genes.

[0089] The researchers selected major positive candidate genes for colon cancer. The major positive candidate genes were selected based on the extent of action in tumor cells, and consisted of six genes with high action ranges. The researchers also selected negative candidate genes whose expression patterns were negatively related to each positive candidate gene. More than one negative candidate gene can be selected for each positive candidate gene. The researchers selected 449 combinations with an action range of 40% or more in tumor cells for all possible gene combinations of the selected positive candidate genes and negative candidate genes.

[0090] FIG. 13 shows the results of an experiment on tumor cell-specific gene combinations in colon cancer samples. FIG. 13 (A) shows the expression ratio of 462 gene combinations in tumor cells and normal cells. FIG. 13 (B) displays gene combinations with a relatively wide range of action on tumor cells. FIG. 13 (B) shows values ​​for the items of the range of action in tumor cells (tumor coverage), the range of action in normal cells (normal coverage), the protection rate, and the expression correlation (TCGA correlation) of genes belonging to the gene combination. In this case, the analyzer can select gene combinations with a range of action in tumor cells higher than a certain value as final antigen candidates. The analyzer can also select gene combinations with a range of action in normal cells lower than a certain value from among gene combinations with a high range of action in tumor cells as final antigen candidates. The analyzer can also select gene combinations with a high inhibition rate from among gene combinations with a high range of action in tumor cells as final antigen candidates. The analyzer can also select gene combinations with a high expression correlation between positive candidate genes and negative candidate genes as final antigen candidates. In summary, the analytical device can select final antigen candidates by comprehensively considering the range of activity in tumor cells, the range of activity in normal cells, the inhibition rate, and the expression relationship between genes.

[0091] FIG. 14 is an example for an analytical device 600 for discovering antigens for chimeric antigen receptors.

[0092] The analytical device 600 corresponds to the analytical device (130 or 140) in Fig. 1. The analytical device 600 discovers a target antigen that is recognized by a chimeric antigen receptor.

[0093] The analysis device 600 may be physically embodied in various forms. For example, the analysis device 600 may have the form of a computer device such as a PC, a network server, a chip set dedicated to data processing, etc. The computer device may include a mobile device such as a smart device.

[0094] The analysis device 600 may include a storage device 610 , a memory 620 , a processing device 630 , an interface device 640 , a communication device 650 , and an output device 660 .

[0095] The storage device 610 stores a program for determining an antigen recognized by a chimeric antigen receptor using gene expression information of tumor cells. The program can determine an antigen recognized by a chimeric antigen receptor by using gene expression information of normal cells as well as tumor cells. The storage device 610 can also store programs or source codes required for data processing. The storage device 610 can also store input gene data and / or tumor information required for analysis.

[0096] The memory 620 may store data and information generated in the process of the analysis device 600 analyzing genetic data.

[0097] The interface device 640 is a device that receives certain commands and data from the outside. The interface device 640 can receive genetic data from a physically connected input device or an external storage device. The interface device 640 can receive gene expression data of tumor cells and normal cells of a sample on a single cell basis. The interface device 640 can also receive inputs of analysis criteria, tumor information, etc.

[0098] The communication device 650 refers to a configuration for receiving and transmitting certain information through a wired or wireless network. The communication device 650 may receive genetic data from an external object. The communication device 650 may receive gene expression data of tumor cells and normal cells of a sample on a single cell basis. The communication device 650 may transmit target antigen-related information, which is an analysis result, to an external object.

[0099] The communication device 650 to the interface device 640 are devices that receive certain data or commands from the outside. The communication device 650 to the interface device 640 can be called input devices.

[0100] The output device 660 is a device that outputs certain information. The output device 660 can output an interface required for the data processing process, an analysis result, and the like.

[0101] The computing device 630 can use the program stored in the storage device 610 to analyze the gene data and discover target antigens.

[0102] The computing device 630 can select genes of candidate antigens (candidate genes) from the source data. The criteria and process for selecting the candidate genes are as described above.

[0103] The computing device 630 can determine all initial gene combinations that can be configured by multiple genes among genes of the candidate antigens. The computing device 630 can determine a target gene combination linked to the target antigen from the initial gene combination. In addition, the computing device 630 can select an optimal final gene combination or genes when there are multiple gene combinations in the target gene combination.

[0104] The computing device 630 may select a combination in which the proportion (action range) of cells expressing at least one gene included in the initial gene combination among tumor cells is equal to or greater than a reference value as a target gene combination.

[0105] The computing device 630 may select a combination in which the ratio (action range) of cells expressing a plurality of genes included in the initial gene combination among tumor cells is equal to or greater than a reference value as a target gene combination.

[0106] The computing device 630 may determine a positive candidate gene based on the ratio of cells expressed in tumor cells or the number of cells expressed in tumor cells among genes of the candidate antigen. The computing device 630 may determine a negative candidate gene whose expression pattern has an inverse relationship with the positive candidate gene.

[0107] The calculation device 630 can determine all gene combinations that can be constituted by positive candidate genes and negative candidate genes as the initial gene combinations.

[0108] The computing device 630 detects whether a ratio of cells expressing at least one of the positive candidate genes included in the specific combination among the tumor cells is equal to or greater than a reference value,

[0109] The target gene combination can be determined as a combination in which the proportion of normal cells expressing an inhibitory gene that inhibits the recognition or binding of the antigen associated with the positive candidate gene to the chimeric antigen receptor among normal cells expressing at least one positive candidate gene is equal to or higher than a standard value.

[0110] The computing device 630 may be a device such as a processor, AP, or a chip with an embedded program that processes data and performs certain operations.

[0111] In addition, the method for discovering a target antigen for a chimeric antigen receptor as described above may be embodied in a program (or application) including an executable algorithm that can be executed by a computer. The program may be provided by being stored in a transitory or non-transitory computer readable medium.

[0112] The term "non-transitory readable medium" refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short moment, such as a register, cache, memory, etc. In particular, the above-mentioned various applications or programs may be stored and provided in a non-transitory readable medium, such as a CD, a DVD, a hard disk, a Blu-ray disk, a USB, a memory card, a ROM (read-only memory), a PROM (programmable read only memory), an EPROM (Erasable PROM, EPROM), an EEPROM (Electrically EPROM), or a flash memory.

[0113] The temporary readable medium refers to various types of RAM such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous DRAM (Synclink DRAM, SLDRAM), and direct Rambus RAM (DRRAM).

[0114] The present embodiment and the drawings attached to this specification merely clearly show a part of the technical ideas contained in the above-mentioned technology, and it is self-evident that all modified examples and specific embodiments that a person skilled in the art can easily deduce within the scope of the technical ideas contained in the specification and drawings of the above-mentioned technology are included in the scope of the above-mentioned technology.

Claims

1. The analysis device acquires gene expression information of tumor cells on a single-cell basis; extracting candidate antigen genes having expression levels equal to or greater than a threshold value from among the genes by the analysis device; the analysis device determining possible gene combinations of genes for the candidate antigens; The analysis device determines a target gene combination in which at least one gene included in the gene combination is expressed; and The analysis device includes a step of determining at least one combination of the target gene combinations as a gene combination for a target antigen, the at least one gene is a gene for an antigen of the tumor cell that is recognized by a chimeric antigen receptor; The method for discovering a target antigen for a chimeric antigen receptor, wherein the target gene combination is a gene combination in which a ratio of cells expressing at least one of the genes among the tumor cells is equal to or greater than a reference value.

2. The method for discovering target antigens for chimeric antigen receptors according to claim 1, characterized in that the analysis device extracts genes of the tumor cells that are expressed in a proportion of the tumor cells equal to or greater than a reference value as genes of the candidate antigens.

3. The method for discovering target antigens for chimeric antigen receptors according to claim 1, characterized in that the analysis device extracts genes of the tumor cells whose expression level difference between normal cells and the tumor cells is equal to or greater than a reference value as genes of the candidate antigens.

4. The analysis device determines the target gene combination in which a plurality of genes included in the gene combination are expressed, The method of claim 1, wherein the target gene combination is a gene combination in which a ratio of cells in which the plurality of genes are simultaneously expressed among the tumor cells is equal to or greater than a reference value.

5. The method for discovering a target antigen for a chimeric antigen receptor according to claim 4, wherein the plurality of genes are involved in the expression of different antigens.

6. The analysis device acquires gene expression information of tumor cells on a single-cell basis; extracting candidate antigen genes having expression levels equal to or greater than a threshold value from among the genes by the analysis device; determining a positive candidate gene based on a ratio of cells expressing the candidate antigen genes in the tumor cells or a number of cells expressing the candidate antigen genes in the tumor cells; determining, by the analysis device, negative candidate genes among the genes of the candidate antigens, the expression pattern of which is inversely related to the positive candidate genes; the analysis device determining possible gene combinations of the positive candidate genes and the negative candidate genes; determining a target gene combination for an antigen recognized by a chimeric antigen receptor from among the gene combinations based on a ratio of cells expressing at least one positive candidate gene included in the gene combination among the tumor cells and a ratio of cells expressing at least one negative candidate gene among the negative candidate genes that inhibit an immune response of a chimeric antigen receptor cell to an antigen generated by the expression of the at least one positive candidate gene among the normal cells; and The method for discovering a target antigen for a chimeric antigen receptor, comprising the step of: determining, by the analysis device, at least one combination of the target gene combinations as a gene combination for the target antigen.

7. The method for discovering target antigens for chimeric antigen receptors according to claim 6, characterized in that the analysis device extracts genes of the tumor cells that are expressed in a proportion of the tumor cells equal to or greater than a reference value as genes of the candidate antigens.

8. The method for discovering target antigens for chimeric antigen receptors according to claim 6, characterized in that the analysis device extracts genes of the tumor cells whose expression level difference between normal cells and the tumor cells is equal to or greater than a reference value as genes of the candidate antigens.

9. The analysis device detects that a ratio of tumor cells expressing at least one of the positive candidate genes included in the specific combination among the tumor cells is equal to or greater than a reference value, The method for discovering a target antigen for a chimeric antigen receptor according to claim 6, characterized in that the specific combination in which a ratio of normal cells expressing an inhibitory gene that inhibits an immune reaction between the antigen and the chimeric antigen receptor due to the positive candidate gene among normal cells expressing at least one positive candidate gene is equal to or greater than a reference value is determined as the target gene combination.

10. The method for discovering target antigens for chimeric antigen receptors according to claim 6, wherein the positive candidate genes are involved in the expression of different antigens.

11. an input device for receiving input of gene expression data of tumor cells of a sample on a single cell basis; A storage device for storing a program for determining an antigen recognized by a chimeric antigen receptor using gene expression information of a tumor cell; and A computing device that determines a target gene combination or target genes for a target antigen of the tumor cell of the sample that is recognized by a chimeric antigen receptor in a gene combination that can be configured by a plurality of genes among genes of the candidate antigens determined by the gene expression data, The target gene combination is characterized in that a proportion of cells expressing at least one gene included in the target gene combination among the tumor cells is equal to or greater than a reference value.

12. The analytical device for designing a chimeric antigen receptor according to claim 11, wherein the gene of the candidate antigen is a gene whose proportion of cells expressed in the tumor cells among genes of the tumor cells is equal to or greater than a first reference value.

13. The analytical device for designing a chimeric antigen receptor according to claim 11, wherein the candidate antigen gene is a gene of the tumor cell whose difference in expression level between a normal cell and the tumor cell is equal to or greater than a reference value.

14. 13. The analytical device for designing a chimeric antigen receptor according to claim 12, wherein a ratio of cells expressed in the tumor cells among the genes of the candidate antigens is equal to or greater than a second reference value, and the second reference value is higher than the first reference value.

15. The analytical device for designing a chimeric antigen receptor according to claim 11, wherein the target gene combination is a ratio of cells expressing at least a plurality of genes included in the target gene combination among the tumor cells that is equal to or greater than a reference value.

16. The input device further receives input of gene expression data of normal cells of the sample; The computing device includes: determining positive candidate genes and negative candidate genes having an inverse relationship in expression pattern to the positive candidate genes based on the ratio of cells expressing the candidate antigen genes in the tumor cells or the number of cells expressing the candidate antigen genes in the tumor cells; The analytical device for designing a chimeric antigen receptor according to claim 11, wherein all gene combinations that can be constituted by the positive candidate genes and the negative candidate genes are determined as the target gene combination.

17. The computing device includes: The proportion of cells expressing at least one of the positive candidate genes included in the specific combination among the tumor cells is equal to or greater than a reference value; Among normal cells expressing the at least one positive candidate gene, the ratio of normal cells expressing an inhibitory gene that inhibits recognition or binding of an antigen associated with the positive candidate gene to a chimeric antigen receptor is equal to or greater than a reference value. The analytical device for designing a chimeric antigen receptor according to claim 16, wherein the specific combination is determined as the target gene combination.

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