Drug repositioning support system and drug repositioning support method

Abstract

Target genes are identified with high accuracy and the effectiveness of drugs is evaluated. [Solution] The system acquires a dataset consisting of gene expression data of samples belonging to one of two groups, references a pathway database to generate a gene network representing the interactions of multiple genes, selects one gene from the multiple genes, traces the gene network downstream starting from the selected gene to extract a path, calculates a path score by performing enrichment analysis using as input a list of genes included in the path and the dataset, ranks the multiple genes based on the path scores of the multiple genes to generate a ranked gene list, and calculates a drug score by performing enrichment analysis using as input a list of genes that are targets of drugs stored in a drug database and the ranked gene list.

Description

[Technical Field]

[0001] The present invention relates to a technology for supporting drug repositioning. [Background technology]

[0002] Drug repositioning is a development method to find a new drug effective against a different disease from an existing drug that is effective against a certain disease. It is attracting attention because the cost, time, and risk involved are significantly lower than those of new drug development.

[0003] Accurately identifying target genes for specific diseases is crucial to identifying new therapeutic uses for existing drugs. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Heonjong Han, Sangyoung Lee, and Insuk Lee, “NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets”, Mol. Cells 2019; 42(8): 579-588 Summary of the Invention [Problem to be solved by the invention]

[0005] Traditionally, target genes have been selected based on the difference in gene expression between disease samples and normal samples. A method described in Non-Patent Document 1 is also known. Non-Patent Document 1 describes a method for selecting target genes based on a modified gene ranking that takes gene networks into account.

[0006] An object of the present invention is to provide an analytical method for identifying target genes with high accuracy and evaluating the effectiveness of drugs. [Means for solving the problem]

[0007] A representative example of the invention disclosed in this application is as follows. a drug repositioning support system including a processor, a storage device connected to the processor, and a network interface connected to the processor, and accessible to a pathway database for managing pathways representing interactions between genes and a drug database for managing a list of genes targeted by drugs; the processor acquires a dataset consisting of gene expression data including information on the expression levels of a plurality of genes in samples belonging to one of two groups, refers to the pathway database, and generates a directed graph representing the interactions of the plurality of genes as a gene network; selects one gene from the plurality of genes; extracts a path by tracing the gene network downstream from the selected gene; performs enrichment analysis using the list of genes included in the path and the dataset to calculate an enrichment score of the path as a path score; ranks the plurality of genes based on the path score of each of the plurality of genes to generate a ranked gene list; performs enrichment analysis using the list of genes targeted by the drug stored in the drug database and the ranked gene list to calculate an enrichment score of the drug as a drug score; and outputs the drug score. [Effects of the Invention]

[0008] According to the present invention, it is possible to select target genes with high accuracy and evaluate the effectiveness of drugs. Objects, configurations and effects other than those described above will become clear from the following explanation of the examples. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 illustrates an example of a system configuration according to a first embodiment. [Figure 2] FIG. 1 is a diagram showing an example of the hardware configuration of a computer that constitutes the drug repositioning support system of Example 1. [Figure 3] FIG. 1 is a diagram showing an example of a pathway managed in the pathway DB of Example 1. [Figure 4] FIG. 2 is a diagram showing an example of a data structure of a medicine DB according to the first embodiment. [Figure 5] 1 is a flowchart illustrating an example of processing executed by the drug repositioning support system of the first embodiment. [Figure 6] FIG. 10 is a diagram illustrating an example of a method for calculating a path score according to the first embodiment. [Figure 7] FIG. 10 is a diagram showing an example of a method for calculating a drug score in Example 1. [Figure 8] FIG. 1 is a diagram showing an example of a drug evaluation result generated by the drug repositioning support system of Example 1. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, the present invention should not be construed as being limited to the description of the embodiments shown below. Those skilled in the art will readily understand that the specific configuration can be changed without departing from the spirit or intent of the present invention.

[0011] In the configuration of the invention described below, the same or similar configurations or functions are denoted by the same reference numerals, and redundant explanations will be omitted.

[0012] In this specification, the terms "first," "second," "third," etc. are used to identify components and do not necessarily limit the number or order. [Example]

[0013] Fig. 1 is a diagram showing an example of the system configuration of Example 1. Fig. 2 is a diagram showing an example of the hardware configuration of a computer constituting the drug repositioning support system 100 of Example 1. Fig. 3 is a diagram showing an example of a pathway managed in the pathway DB of Example 1. Fig. 4 is a diagram showing an example of the data structure of the drug DB of Example 1.

[0014] The system is composed of a drug repositioning support system 100, a pathway DB 110, and a drug DB 111. The pathway DB 110 and the drug DB 111 are publicly available databases. The drug repositioning support system 100 is connected to the pathway DB 110 and the drug DB 111 via a network so that they can be accessed.

[0015] The drug repositioning support system 100 is configured from a computer 200 as shown in Fig. 2. The computer 200 has a processor 201, a main memory device 202, a secondary memory device 203, and a network interface 204. The hardware elements are connected to each other via a bus 205.

[0016] The processor 201 executes a program stored in the main memory device 202. The processor 201 executes processing in accordance with the program, thereby operating as a functional unit (module) that realizes a specific function. In the following description, when a processing is described using a functional unit as the subject, it indicates that the processor 201 is executing a program that realizes the functional unit.

[0017] The main storage device 202 is a memory or the like, and stores programs executed by the processor 201 and information used by the programs. The main storage device 202 is also used as a work area.

[0018] The secondary storage device 203 is a large-capacity storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The programs and information stored in the main storage device 202 may be stored in the secondary storage device 203. In this case, the processor 201 reads the programs and information from the secondary storage device 203 and loads them into the main storage device 202.

[0019] The network interface 204 is an interface for connecting to a network.

[0020] The computer 200 may have input devices such as a keyboard, a mouse, and a touch panel, as well as an output device such as a display.

[0021] The pathway DB 110 is a database that manages pathways that represent interactions between genes. As shown in Figure 3, a pathway is expressed as a directed graph consisting of nodes that represent genes and edges that represent interactions. The pathway DB 110 stores, for example, information about the nodes and information about the edges.

[0022] The drug DB 111 is a database for managing target genes of existing drugs. For example, as shown in Fig. 4, the drug DB 111 stores a table 400 for storing entries each consisting of a drug 401 and a gene 402. The drug 401 is a field for storing the name of an existing drug, etc. The gene 402 is a field for storing the target gene of an existing drug.

[0023] The drug repositioning support system 100 includes a gene network construction unit 101, a path evaluation unit 102, a ranking determination unit 103, and a drug evaluation unit 104. Regarding the functional units included in the drug repositioning support system 100, multiple functional units may be combined into one functional unit, or one functional unit may be divided into multiple functional units for each function.

[0024] Fig. 5 is a flowchart illustrating an example of processing executed by the drug repositioning support system 100 of Example 1. Fig. 6 is a diagram illustrating an example of a method for calculating a pass score of Example 1. Fig. 7 is a diagram illustrating an example of a method for calculating a drug score of Example 1. Fig. 8 is a diagram illustrating an example of a drug evaluation result generated by the drug repositioning support system 100 of Example 1.

[0025] When the drug repositioning support system 100 receives an execution instruction together with the gene expression dataset 120, it starts the process described below.

[0026] The gene expression dataset 120 is a dataset consisting of gene expression data that stores the expression levels of multiple genes in a single sample or statistical values ​​calculated from the expression levels. The gene expression dataset 120 includes gene expression data for two groups: patients with a certain disease and healthy individuals.

[0027] The gene network constructor 101 refers to the pathway DB 110 and generates a gene network made up of genes included in the data of the gene expression dataset 120 (step S101). Like pathways, the gene network is represented as a directed graph.

[0028] The path evaluation unit 102 selects one gene from among the genes included in the gene network (step S102). In this embodiment, genes are selected in order from the upstream of the gene network. If the gene network has the shape shown in Figure 3, genes are selected in order from GENE1 or GENE2.

[0029] The path evaluation unit 102 extracts paths by tracing downstream genes in the gene network starting from the selected gene (step S103). For example, if GENE4 is selected as the selected gene in the gene network shown in Figure 3, a path consisting of GENE5 and GENE6 and a path consisting of GENE7 and GENE8 are extracted.

[0030] The path evaluation unit 102 calculates the enrichment score of the gene list corresponding to the path as a path score by performing GSEA (Gene SET Enrichment Analysis) using the gene expression dataset 120 and the gene set corresponding to the path (step S104). Specifically, the path score is calculated in the following procedure.

[0031] (S104-1) The path evaluation unit 102 generates a first ranked gene list by ranking the genes included in the gene expression data based on their differential expression levels.

[0032] (S104-2) The path evaluation unit 102 calculates the enrichment score of the gene set corresponding to each path as a path score using the first-ranked gene list. In Figure 6, the gene set corresponding to path 1 has a higher path score than the gene set corresponding to path 2. Note that the first-ranked gene list shown in Figure 6 arranges genes from the left in descending order of differential expression level.

[0033] (S104-3) The path evaluation unit 102 stores the maximum value among the path scores of each path and the selected gene in association with each other in the work area.

[0034] Genes that are functionally important for a particular disease process are thought to not only exhibit dysregulation themselves, but also tend to cause significant dysregulation of downstream genes within a functional gene network. In this example, genes are scored taking into account differences in the expression of downstream genes. When multiple paths exist, adopting the maximum path score allows for accurate estimation of genes that may cause significant dysregulation of downstream genes. Non-Patent Document 1 takes into account neighboring genes and does not perform scoring based on the aforementioned hypothesis.

[0035] The path evaluation unit 102 determines whether or not the processing has been completed for all genes included in the gene network (step S105).

[0036] If the process has not been completed for all genes included in the gene network, the path evaluation unit 102 returns to step S102 and executes the same process.

[0037] When the processing is completed for all genes included in the gene network, the ranking unit 103 generates a second ranked gene list by ranking the genes based on the path scores (step S106).

[0038] The drug evaluation unit 104 executes GSEA using the drug DB 111 and the second ranked gene list to calculate the drug score of each drug, which is the enrichment score of the list of genes targeted by each drug (step S107). In Figure 7, the gene set corresponding to drug 1 has a higher path score than the gene set corresponding to drug 2. Note that the second ranked gene list shown in Figure 7 arranges genes from the left in descending order of path score.

[0039] The drug evaluation unit 104 generates and outputs a drug evaluation result including data associating drugs with drug scores (step S108). The drug evaluation result is, for example, a list as shown in FIG.

[0040] The present invention is not limited to the above-described embodiments, but includes various modifications. For example, the above-described embodiments are provided to explain the present invention in detail, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, some of the configurations of each embodiment can be added to, deleted from, or replaced with other configurations.

[0041] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The present invention can also be realized by software program code that implements the functions of the embodiments. In this case, a storage medium on which the program code is recorded is provided to a computer, and a processor included in the computer reads the program code stored in the storage medium. In this case, the program code itself read from the storage medium implements the functions of the above-described embodiments, and the program code itself and the storage medium on which it is stored constitute the present invention. Examples of storage media for providing such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, solid-state drives (SSDs), optical disks, magneto-optical disks, CD-Rs, magnetic tapes, non-volatile memory cards, and ROMs.

[0042] Furthermore, the program code that realizes the functions described in this embodiment can be implemented in a wide range of program or script languages, such as assembler, C / C++, perl, Shell, PHP, Python, and Java (registered trademark).

[0043] Furthermore, the program code of the software that realizes the functions of the embodiments may be distributed via a network and stored in a storage means such as a computer's hard disk or memory, or in a storage medium such as a CD-RW or CD-R, and the processor of the computer may read and execute the program code stored in the storage means or storage medium.

[0044] In the above-described embodiment, the control lines and information lines are shown as those considered necessary for the explanation, and not all control lines and information lines are necessarily shown in the product. All components may be interconnected. [Explanation of symbols]

[0045] 100 Drug Repositioning Support System 101 Gene Network Construction Department 102 Path Evaluation Unit 103 Ranking Division 104 Drug Evaluation Department 110 Pathway DB 111 Drug DB 120 gene expression datasets 200 calculator 201 processor 202 Main storage 203 Secondary storage device 204 Network Interface 205 Bus

Claims

1. A drug repositioning support system, comprising: a processor, a storage device connected to the processor, and a network interface connected to the processor; a pathway database for managing pathways representing interactions between genes and a drug database for managing a list of genes targeted by drugs; The processor: obtaining a dataset consisting of gene expression data containing information on the expression levels of multiple genes in samples belonging to either of the two groups; generating a directed graph representing interactions of the plurality of genes as a gene network by referring to the pathway database; selecting one gene from the plurality of genes, tracing the gene network downstream from the selected gene as a starting point to extract a path, and performing enrichment analysis using the list of genes included in the path and the dataset to calculate an enrichment score of the path as a path score; ranking the plurality of genes based on the path score of each of the plurality of genes to generate a ranked gene list; calculating an enrichment score of the drug as a drug score by performing an enrichment analysis using the list of genes targeted by the drug stored in the drug database and the ranked gene list; A drug repositioning support system that outputs the drug score.

2. The drug repositioning support system according to claim 1, The drug repositioning support system is characterized in that, when there are two or more paths for the selected gene, the processor generates the ranked gene list using the largest path score.

3. A computer-implemented drug repositioning support method, comprising: The computer a processor, a storage device connected to the processor, and a network interface connected to the processor; a pathway database for managing pathways representing interactions between genes and a drug database for managing a list of genes targeted by drugs; The drug repositioning assistance method a first step in which the processor acquires a dataset consisting of gene expression data containing information on the expression levels of a plurality of genes in samples belonging to either of two groups; a second step in which the processor refers to the pathway database and generates a directed graph representing interactions between the plurality of genes as a gene network; a third step in which the processor selects one gene from the plurality of genes, traces the gene network downstream starting from the selected gene to extract a path, and performs enrichment analysis using the list of genes included in the path and the dataset to calculate an enrichment score of the path as a path score; a fourth step in which the processor ranks the plurality of genes based on the path score of each of the plurality of genes to generate a ranked gene list; a fifth step in which the processor performs enrichment analysis using the list of genes targeted by the drug stored in the drug database and the ranked gene list to calculate an enrichment score of the drug as a drug score; A drug repositioning support method comprising: a sixth step in which the processor outputs the drug score.

4. The drug repositioning assistance method according to claim 3, The drug repositioning support method is characterized in that the fourth step includes a step in which the processor generates the ranked gene list using the largest path score if there are two or more paths for the selected gene.

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