Gene mutation analysis method and gene mutation analysis system

Abstract

This gene mutation analysis method comprises: a preparation step for simultaneously extracting DNA and RNA from a common patient sample, and generating a DNA-derived sample and an RNA-derived sample from each of the extracted DNA and RNA; and an analysis processing step for performing gene mutation analysis processing on the generated DNA-derived sample and RNA-derived sample.

Description

Gene mutation analysis method and gene mutation analysis system

[0001] The present invention relates to a gene mutation analysis method and a gene mutation analysis system.

[0002] In recent years, personalized medicine has become popular, in which the base sequence of genes from patient samples is analyzed, and the causes of disease are investigated based on the analysis results to select the optimal treatment plan for the patient. Gene panel testing, which uses next-generation sequencers to comprehensively analyze mutations occurring in the genes of a sample, is expected to play an important role in this type of personalized medicine. Gene mutations that can be analyzed are classified into germline mutations and somatic mutations.

[0003] Generally, the procedures for gene panel testing are roughly divided into a sequencing step (determining the base sequence) using a next-generation sequencer and a data analysis step (analyzing gene mutations using a data analyzer). In the sequencing step, nucleic acids are extracted from a specimen obtained in advance from the patient and further fragmented to prepare samples. Libraries are then prepared from the prepared samples, and the prepared libraries are sequenced to obtain sequence data (base sequence data) for the samples in the libraries. In the data analysis step, the obtained sequence data is compared with pre-prepared reference data to obtain gene mutation information, and the obtained information is output to the user (a medical professional or specialist who investigates the cause of disease, etc.).

[0004] For example, Patent Document 1 describes an analytical method in which genetic mutations are analyzed from base sequence data of a nucleic acid sample from a patient specimen and an analysis report including the analysis results is output, in which the user can select the presentation format of the analysis report as appropriate.

[0005] Patent No. 6953586

[0006] In a gene panel test, DNA (deoxyribonucleic acid) and RNA (ribonucleic acid) can be analyzed. Therefore, in the data analysis step, if the nucleic acid sample is a DNA sample, an analysis result for the DNA sample is obtained, and if the nucleic acid sample is an RNA sample, an analysis result for the RNA sample is obtained.

[0007] However, the analysis results of only one of the DNA and RNA samples cannot determine whether the obtained mutation information affects the protein, while the analysis results of only the other RNA sample can identify factors that affect the protein but cannot determine the cause. For example, in the case of diseases such as cancer, information related to protein abnormalities is important to clarify the cause of the disease, but Patent Document 1 does not propose any method for efficiently obtaining analysis results of both DNA sample sequence data and RNA sample sequence data. Therefore, the conventional analysis method described in Patent Document 1 has the problem that it is not always easy to analyze the cause of the disease.

[0008] An object of the present invention is to provide a gene mutation analysis method and a gene mutation analysis system that can improve the efficiency of disease causal analysis based on gene mutation information while maintaining accuracy.

[0009] One aspect of the gene mutation analysis method according to the present invention includes a preparatory step of simultaneously extracting DNA and RNA from a common patient specimen and generating a DNA-derived sample and an RNA-derived sample from the extracted DNA and RNA, respectively; and an analytical step of performing gene mutation analysis on the generated DNA-derived sample and RNA-derived sample.

[0010] Another aspect of the gene mutation analysis method according to the present invention includes: a preparatory step of simultaneously extracting DNA and RNA from a common patient specimen and generating a DNA-derived sample and an RNA-derived sample from the extracted DNA and RNA, respectively; a sequencing step of simultaneously sequencing the generated DNA-derived sample and RNA-derived sample to obtain sequence data; and a data analysis step of simultaneously analyzing the sequence data obtained for each of the DNA-derived sample and the RNA-derived sample to obtain DNA mutation information and RNA abnormality information for the patient specimen.

[0011] One aspect of the gene mutation analysis system according to the present invention is a gene mutation analysis system used in the gene mutation analysis method described above, comprising: a next-generation sequencer that performs the sequencing step; and a data analysis device that performs the data analysis step.

[0012] According to the present invention, it is possible to improve the efficiency of disease causal analysis based on gene mutation information while ensuring accuracy.

[0013] FIG. 1 is a diagram schematically illustrating the configuration of a gene mutation analysis system according to an embodiment of the present invention. FIG. 2 is a block diagram illustrating the internal configuration of the data analysis device shown in FIG. 1. FIG. 3 is a diagram illustrating an example of an ID list. FIG. 4 is a flowchart illustrating the processing steps of a gene mutation analysis method executed in a gene mutation analysis system according to an embodiment of the present invention. FIG. 5 is a diagram illustrating an example of a test request screen. FIG. 6 is a diagram illustrating the sample preparation step shown in FIG. 4, and is a schematic diagram illustrating a cut surface of an FFPE sample. FIG. 7 is a diagram illustrating the sequencing step shown in FIG. 4, and is a schematic diagram illustrating sample placement on a well plate. FIG. 8 is a flowchart illustrating the mutation information simultaneous acquisition step shown in FIG. 4, particularly the processing steps of the analysis pipeline. FIG. 9 is a schematic diagram illustrating alignment shown in FIG. 8.

[0014] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0015] Fig. 1 is a diagram showing a schematic configuration of a gene mutation analysis system according to an embodiment of the present invention, and Fig. 2 is a block diagram showing the internal configuration of a data analysis device shown in Fig. 1.

[0016] In this embodiment, as shown in FIG. 1 , a genetic mutation analysis system 100 is installed in a testing institution that receives a genetic panel testing request from a medical institution and performs genetic panel testing, including genetic mutation analysis (described below). The medical institution's information system 200 includes a terminal device 220, such as a personal computer, and an electronic medical record system (not shown). The request from the medical institution includes an analysis target sample S and information regarding the genetic panel testing request (hereinafter simply referred to as "request information"). A genetic panel testing is requested of the testing institution by a medical professional, such as a pathologist, clinical laboratory physician, or attending physician, using the terminal device 220. The analysis target sample S is collected from a patient, placed in a container, and delivered from the medical institution to the testing institution in a packaged state, such as a box, by mail or the like.

[0017] The request information includes, for example, patient information, specimen information, and attending physician information. The patient information includes the patient's identification information (patient identification ID), date of birth, and gender. The specimen information includes, for example, the type of cancer, specimen identification number, and blood collection date. The attending physician information includes the facility name and facility code indicating the requesting medical institution, as well as the name of the attending physician.

[0018] The request information is transmitted, for example, from the terminal device 220 to the gene mutation analysis system 100 (more specifically, the data analysis device 130, described below) via a wireless or wired network. If the patient identification information and specimen identification number already registered in the medical institution's electronic medical record system or the like exist as barcoded information, the request information is preferably provided from the medical institution to the testing institution in the form of an ID list L (see FIG. 3 ) that lists these barcodes. The ID list L includes a list of barcodes as well as character strings of the request information displayed as text or an image. The ID list L may be an electronic file provided via a network, or may be a document packaged together with the sample S to be analyzed.

[0019] The gene mutation analysis system 100 according to this embodiment includes a next-generation sequencer 110, a sequence data storage device 120, a data analysis device 130, and a terminal device 140 for receiving test requests.

[0020] The next-generation sequencer 110 is a device that performs sequencing on a pre-prepared nucleic acid sample. The sequence data storage device 120 is, for example, a database server that internally stores output data (sequence data, etc.) from the next-generation sequencer 110 as a database and outputs the stored data to the data analysis device 130 in response to a request from the data analysis device 130. The data analysis device 130 is, for example, a computer device such as a personal computer or supercomputer that performs data analysis on data acquired from the sequence data storage device 120 and outputs the analysis results as a report R to an external device (e.g., a terminal device 220 in a medical institution's information system 200). The next-generation sequencer 110 and the sequence data storage device 120 are communicatively connected to each other via a wired or wireless line, and the sequence data storage device 120 and the data analysis device 130 are communicatively connected to each other via a wired or wireless line. Note that the data analysis device 130 may have a cluster configuration including multiple clustered computer devices, as shown in the figure, or may have a configuration in which some computer devices are connected via a network such as the Internet. The terminal device 140 may be a computer device having an input unit such as a keyboard, a display unit such as an LCD display, a control unit including a CPU (Central Processing Unit), memory, storage, etc., and a communication unit capable of sending and receiving data with external devices.

[0021] The data analysis device 130 includes a control unit 131 , an operation input unit 132 , a display unit 133 , a first interface unit 134 , and a second interface unit 135 .

[0022] The operation input unit 132 receives user operations to instruct data acquisition from the sequence data storage device 120, data analysis of the acquired data, or output of analysis results to an external device, and inputs the instructions to the control unit 131. The operation input unit 132 is, for example, a keyboard, a mouse, a touch panel input device, a scanner, a barcode scanner, etc. The operation input unit 132 is also used to input request information.

[0023] The display unit 133 displays a setting screen that displays setting items required for data analysis, an analysis result screen that displays the results of data analysis, etc. The display unit 133 is, for example, a liquid crystal display. The display unit 133 may be a touch panel display device equipped with a touch panel input device that functions as the operation input unit 132.

[0024] The first interface 134 and the second interface 135 are input / output interfaces that mediate data communication between the data analysis device 130 and other devices. The input / output interfaces may be wired or wireless. The first interface 134 communicatively connects the data analysis device 130 to the sequence data storage device 120, and the second interface 135 communicatively connects the data analysis device 130 to an external device. Here, the external device is typically a computer configured to output a report R of the analysis results to a medical professional or a patient.

[0025] The control unit 131 controls the overall operation of the data analysis device 130. The control unit 131 includes a processor 131a, a memory 131b, and a storage 131c. The processor 131a is an arithmetic processing unit configured with a hardware processor such as a CPU. It reads various control programs and setting data stored in the storage 131c, stores them in the memory 131b, and executes the programs to realize various functions of the data analysis device 130, particularly functions required to execute each step of the gene mutation analysis method described below. The memory 131b is a storage medium configured with, for example, RAM (Random Access Memory), and provides working memory space for the processor 131a and stores temporary data. The memory 131b may include not only volatile memory but also nonvolatile memory. The storage 131c is a storage medium configured with, for example, ROM (Read Only Memory), and stores various control programs and data executed by the processor 131a. The storage 131c is an example of a non-transitory computer-readable storage medium. The various control programs may be downloaded from the outside to the data analysis device 130 via the first interface 134, the second interface 135, or another input / output interface not shown, and stored in the storage 131c.

[0026] FIG. 4 is a flowchart illustrating the processing steps of the gene mutation analysis method executed by the gene mutation analysis system 100.

[0027] In this embodiment, as shown in FIG. 4, the gene mutation analysis method includes a sequencing process (steps S1 to S3) that is mainly performed by the next-generation sequencer 110, and a data analysis process (steps S4 to S6) that is mainly performed by the control unit 131 of the data analysis device 130 (hereinafter simply referred to as the "data analysis device 130").

[0028] To begin sample preparation, samples (the aforementioned analysis target samples S) are received from the medical institution requesting the test. The request information provided by the medical institution during this process must be entered accurately. Accurate unique ID information identifying patients and samples is particularly important to prevent mix-ups between patients and samples. At the medical institution, for example, a written ID list L is scanned with a barcode scanner, and the request information, including the ID information, is entered into the terminal device 220. The request information can then be transmitted to the testing institution's terminal device 140 by the terminal device 220 performing a transmission process. If the ID list L is a printed document or image file, the terminal device 140 may use OCR (Optical Character Recognition) to automatically acquire the request information. If the ID list L is an electronic file, the terminal device 140 may read the file using a system installed in the terminal device 140, and the request information may then be displayed on the test request screen (see FIG. 5 ) displayed on the terminal device 140. Automatic acquisition of request information enables accurate information to be obtained from the medical institution, reducing the risk of misidentification of sample information during reception.

[0029] After receiving the sample, sample preparation is performed in step S1 (sample preparation process). The sample preparation process includes (step S11) extracting DNA and RNA (e.g., messenger RNA (mRNA)) from a formalin-fixed, paraffin-embedded (FFPE) specimen of the patient's tumor tissue, and (step S12) synthesizing complementary DNA (cDNA) from the RNA. In step S11, DNA is also extracted separately from the patient's non-tumor cells (whole blood). In this case, genetic mutations can be detected with high accuracy by data analysis using both the tumor and non-tumor specimens, i.e., matched pair analysis. In step S11, DNA may also be extracted separately from the patient's non-tumor cells, which enables detection of germline mutations in addition to somatic mutations. Furthermore, matched pair analysis using both the tumor and non-tumor specimens enables detection of somatic and germline mutations with higher accuracy. While whole blood can be used as the non-tumor cells, this is not limiting. An FFPE specimen from a patient is an example of a sample S to be analyzed.

[0030] In the above step S11, conventionally known techniques can be applied to extract DNA from the FFPE sample and extract RNA from the FFPE sample, and therefore detailed explanations thereof will be omitted here. However, the gene mutation analysis method according to the present embodiment differs from conventionally known techniques in that DNA extraction and RNA extraction are performed simultaneously.

[0031] In particular, in this embodiment, the FFPE sample from which DNA is extracted in step S11 and the FFPE sample from which RNA is extracted are treated as a common FFPE sample, thereby enabling simultaneous extraction of DNA and RNA.

[0032] As described above, in this embodiment, DNA extraction and RNA extraction can be performed simultaneously, which shortens processing time compared to when DNA extraction and RNA extraction are performed separately, prevents mixing up samples from different patients, and reduces the time and labor required to manage samples and extracted samples from the same patient.

[0033] Here, the FFPE specimen being common means the following: (1) As a specific example, the specimen block from which the FFPE specimen for DNA extraction is cut is the same as the specimen block from which the FFPE specimen for RNA extraction is cut. (2) As another specific example, when the specimen block is cut into a plurality of small blocks, the small blocks from which the FFPE specimen for DNA extraction is cut are the same as the small blocks from which the FFPE specimen for RNA extraction is cut. (3) As a more preferred specific example, the FFPE specimen for DNA extraction and the FFPE specimen for RNA extraction are adjacent sections, such as adjacent sections. (4) As an even more preferred specific example, the FFPE specimen for DNA extraction and the FFPE specimen for RNA extraction are the same. For example, as shown in Figure 6, a FFPE specimen block of a patient's tumor tissue may contain a mixture of multiple different genomically abnormal cells (in the example shown in Figure 6, first, second, and third genomically abnormal cells). In such cases, there is a possibility that differences (heterogeneity) in the mutation information obtained as a result of the sequencing process and data analysis process may occur between FFPE sections obtained by slicing the FFPE specimen block at each of the cutting positions CP1, CP2, and CP3. In this embodiment, by extracting DNA and RNA from all of the multiple FFPE sections, the FFPE sections from which DNA is extracted and the FFPE sections from which RNA is extracted can be identified, thereby more reliably suppressing the effects of heterogeneity within the specimen block and enabling more accurate acquisition of mutation information.

[0034] That is, in this embodiment, it is possible to achieve a reduction in processing time by improving efficiency while ensuring accuracy.

[0035] The simultaneous extraction of DNA and RNA described above refers to the simultaneous extraction of DNA (tumor DNA) and RNA from a common specimen, which is tumor tissue. In the case of the separate extraction of DNA (non-tumor DNA) from non-tumor cells, the specimen itself to be subjected to the extraction process is separate from the tumor tissue. Therefore, the extraction of non-tumor DNA is preferably performed in parallel with the extraction of tumor DNA and RNA from the tumor tissue specimen, but this does not necessarily have to be simultaneous.

[0036] In the sample preparation process (step S1), tumor DNA, RNA, and non-tumor DNA are extracted, and then the quality of the extracted tumor DNA, RNA, and non-tumor DNA is checked before proceeding to step S2. The quality checked includes, for example, the amount of nucleic acid and the degree of nucleic acid degradation. If the quality does not meet the desired level, the sample preparation process is performed again.

[0037] Next, in step S2, a library is prepared (library preparation step). The library preparation step includes (step S21) fragmenting DNA and cDNA to lengths appropriate for sequencing using ultrasound or other methods, (step S22) adding artificial sequences (adapters) to both ends of each DNA fragment and each cDNA fragment, and (step S23) sorting the samples prepared in step S22 into DNA and RNA origins, and then recovering all DNA fragments and all cDNA fragments containing specific sequences by adsorption with DNA probes and cDNA probes (capture method), or amplifying DNA or cDNA fragments containing specific sequences using PCR (polymerase chain reaction). The artificial sequences added in step S22 include a sequence primer required to initiate the extension reaction, an index primer for identifying individual patients, and a flow cell binding primer for binding the DNA or cDNA fragments to the flow cell. In the following description, the DNA fragments and cDNA fragments to which the various artificial sequences have been added will be referred to as "DNA-derived samples" and "RNA-derived samples," respectively. The principles of fragmentation of DNA and cDNA, addition of artificial sequences to the fragments, and adsorption, recovery, and amplification of fragments containing specific sequences are well-known techniques, and therefore will not be described in detail here.

[0038] The DNA-derived samples obtained in the library preparation process (step S2) include "tumor DNA-derived samples" derived from DNA from tumor tissue, and "non-tumor DNA-derived samples" derived from DNA from non-tumor tissue.

[0039] Furthermore, in the library preparation process (step S2), library preparation is performed not only on DNA and cDNA obtained from patient samples, but also on DNA from commercially available clinical samples containing known sequences or artificially constructed samples containing known sequences (hereinafter referred to as "control samples"), and on cDNA obtained from RNA from the control samples. As a result of these library preparations, libraries containing samples derived from the DNA of the control samples and libraries containing samples derived from the RNA of the control samples are generated, respectively. Examples of control samples include, but are not limited to, commercially available clinical samples and artificially constructed samples. Furthermore, control samples can be introduced in any of the steps included in the sample preparation process (step S1), library preparation process (step S2), and sequencing execution process (step S3) in the sequencing process. Introducing control samples containing known sequences and processing them simultaneously with patient-derived samples in each step of the sequencing process improves the objective reliability of each step of the test.

[0040] In the library preparation process (step S2), index primers that can identify individual patients are assigned, so in this embodiment, samples obtained from specimens (tumor tissues) of not only one patient but multiple patients can be subjected to analytical processing all at once.

[0041] In this embodiment, in step S23, the corresponding derived samples are concentrated according to the type of probe used. As an example of concentration, tumor DNA-derived samples from multiple patients (hereinafter referred to as "tumor DNA-derived samples from multiple patients") are concentrated together in a common tube, RNA-derived samples from multiple patients (hereinafter referred to as "RNA-derived samples from multiple patients") are concentrated in a common tube, and non-tumor DNA-derived samples from multiple patients are concentrated in a common tube. Thus, in this embodiment, as a result of the library preparation step (step S2), three separate tubes are prepared, including a tube for concentrating tumor DNA-derived samples from multiple patients, a tube for concentrating RNA-derived samples from multiple patients, and a tube for concentrating non-tumor DNA-derived samples from multiple patients.

[0042] Prior to the concentration, tubes 154 containing library a of tumor DNA-derived samples from a first patient, library b of RNA-derived samples from the first patient, library c of non-tumor DNA-derived samples from the first patient, library d of tumor DNA-derived samples from a second patient, library e of RNA-derived samples from the second patient, library f of non-tumor DNA-derived samples from the second patient, library g of DNA-derived samples from a control specimen, and library h of RNA-derived samples from a control specimen are arranged in separate wells 151 in columns A to H of a common well plate 150 (see FIG. 7 ). The contents of the tubes 154 arranged in wells 151 in columns A, D, and G are concentrated in a common tube, the contents of the tubes 154 arranged in wells 151 in columns B, E, and H are concentrated in a common tube, and the contents of the tubes 154 arranged in wells 151 in columns D, F, and G are concentrated in a common tube. This results in the three separate tubes described above. In this way, by arranging multiple tubes 154 with different contents in a common well plate 150 in a manner that allows each to be identified, it is possible to achieve both efficient concentration work and reduced risk of mix-up.

[0043] In the library preparation step (step S2), quality checks are performed after each of the libraries a-h is generated and after each of the libraries a-h is concentrated in multiple batches. The quality checked for each of the generated libraries a-h is, for example, the amount of nucleic acid. Furthermore, the quality checked for the concentration results of the libraries a-h is, for example, the concentration of nucleic acid. If the quality does not meet the desired level, the process returns to step S1, and the sample preparation step is performed again.

[0044] Next, in step S3, sequencing is performed by the next-generation sequencer 110. In this embodiment, the base sequence of each sample is determined by PCR reaction and SBS (Sequence by Synthesis) method, but the specific method of base sequence determination is not limited to this. The PCR reaction of each sample and the SBS method are conventionally known, and detailed description thereof will be omitted here.

[0045] In this embodiment, the next-generation sequencer 110 simultaneously sequences the DNA-derived sample and the RNA-derived sample (sequencing execution step), thereby making it possible to simultaneously obtain DNA-derived sequence data and RNA-derived sequence data.

[0046] The next-generation sequencer 110 outputs the acquired DNA-derived sequence data and RNA-derived sequence data together with supplementary information such as the test accession number to the sequence data storage device 120 and stores them in the sequence data storage device 120 .

[0047] Next, in step S4, the data analysis device 130 simultaneously analyzes the DNA-derived sequence data and the RNA-derived sequence data using an analysis pipeline to simultaneously acquire DNA mutation information and RNA abnormality information (mutation information simultaneous acquisition process). Here, the analysis pipeline is a program constructed to continuously execute the processes required for analyzing the DNA-derived sequence data and the RNA-derived sequence data. In this embodiment, the analysis pipeline executes the series of processing steps shown in the flowchart of FIG. 8. Specifically, it includes the following steps S41 to S43. In FIG. 8, the DNA analysis pipeline is an analysis pipeline for DNA-derived sequence data, and the RNA analysis pipeline is an analysis pipeline for RNA-derived sequence data.

[0048] Step S41 is a process of obtaining the read sequence indicated in the total DNA-derived sequence data (hereinafter referred to as the "DNA read sequence SDNA") and the read sequence indicated in the total RNA-derived sequence data (hereinafter referred to as the "RNA read sequence SRNA").

[0049] Step S42 is a process of aligning all acquired DNA read sequences SDNA and RNA read sequences SRNA to a reference genome sequence SREF. The reference genome sequence SREF used for aligning the DNA read sequences SDNA and RNA read sequences SRNA can be selected according to each analysis. In this embodiment, all DNA read sequences SDNA and all RNA read sequences SRNA are aligned to a common reference genome sequence SREF (see FIG. 9 . In FIG. 9 , the DNA read sequences SDNA and the RNA read sequences SRNA are distinguished from each other by different hatching). Alignment is also performed using a reference sequence created independently based on the common reference genome sequence SREF according to the analysis. Here, a common reference genome sequence refers to citing nucleic acid sequence data serving as a reference for sequence analysis from a common database. By using this common reference genome sequence SREF, the mutation detection conditions for all DNA read sequences SDNA and all RNA read sequences SRNA can be matched, thereby improving the reliability when comparing the results of both analyses later.

[0050] Furthermore, using a common reference genome sequence for DNA analysis and RNA analysis not only prevents discrepancies between the reference genome sequences used in DNA analysis and RNA analysis and improves the efficiency of update and verification work, but also reduces data volume. The database to be cited may be the entire gene sequence database registered and managed by a public institution such as the National Center for Biotechnology Information (NCBI), or a portion of it. Furthermore, a database collected and curated by a testing institution performing testing and analysis may be used in conjunction with the database of the public institution.

[0051] In this embodiment, the mutation detection process performed in step S43 detects mutations such as single-base substitutions, insertions, deletions, and copy number abnormalities from the DNA read sequence SDNA, and detects mutations such as fusion genes and gene expression levels from the RNA read sequence SRNA. Thus, the mutation detection process in this embodiment can simultaneously obtain DNA mutation information and RNA abnormality information. Since conventionally known methods can be used to detect each type of mutation, detailed descriptions thereof will be omitted here.

[0052] The DNA mutation information and RNA abnormality information obtained in step S43 are output on a screen or in writing. In step S44, a mutation information analysis process is performed to compare the output DNA mutation information and RNA abnormality information and perform error checks, etc.

[0053] Incidentally, "simultaneously analyzing DNA-derived sequence data and RNA-derived sequence data" refers to analyzing DNA-derived sequence data and RNA-derived sequence data in parallel in the data analysis device 130. Specific examples of "simultaneously analyzing" include, for example, (1) starting both analyses at the same time, (2) starting each analysis so that the analysis time period of one analysis that takes a longer time is included in the analysis time period of the other analysis, (3) starting each analysis so that the predicted completion time of one analysis that takes a longer time matches the completion time of the other analysis, and (4) giving priority to one analysis that takes a longer time.

[0054] Furthermore, when analyzing multiple samples in parallel, the latency within the analysis can be reduced by assigning a priority to each sample, thereby reducing the influence of other samples, and as a result, the time required for analysis of each sample can be reduced.

[0055] By performing simultaneous analysis, the time required to complete the analysis of both DNA-derived and RNA-derived sequence data can be reduced, thereby significantly shortening the waiting time for subsequent steps that use the results of both analyses.

[0056] Furthermore, by simultaneously analyzing both DNA-derived sequence data and RNA-derived sequence data, and separating repetitive processing and processing for different subjects in each analysis and distributing the processing in parallel across multiple computers forming a cluster of the data analysis device 130, the time required for the overall analysis can be further reduced. For example, the time required can be reduced by dividing the analysis of DNA-derived sequence data and the analysis of RNA-derived sequence data into separate computers and performing parallel processing. In addition, in the analysis of DNA-derived sequence data, the time required can be further reduced by dividing the analysis of tumor DNA-derived sequence data and non-tumor DNA-derived sequence data from the same patient into separate computers and performing parallel processing. The time required can also be reduced when analyzing samples from multiple patients.

[0057] In step S5, the data analysis device 130 stores the acquired DNA mutation information and RNA abnormality information in the storage 131c. In step S6, when necessary, the data analysis device 130 reads the DNA mutation information and RNA abnormality information from the storage 131c and outputs them to an external device. The acquired DNA mutation information and RNA abnormality information do not have to be stored in the storage 131c built into the data analysis device 130, but may be stored in, for example, an external server device (or a cloud server device). In any case, storing the acquired DNA mutation information and RNA abnormality information in the same location facilitates centralized data management of the gene mutation analysis results for the DNA and RNA of the same patient, and facilitates the creation of a report R that integrates the gene mutation analysis results for the DNA and RNA, thereby improving the efficiency of genetic panel testing. If centralized data management is possible, the data storage location does not have to be the same location, but may be multiple devices linked by a database.

[0058] As described above, the gene mutation analysis method according to this embodiment includes a preparatory step of simultaneously extracting DNA and RNA from a common patient specimen and generating DNA-derived samples and RNA-derived samples from the extracted DNA and RNA, respectively, and an analytical step of performing gene mutation analysis on the generated DNA-derived samples and RNA-derived samples. This enables simultaneous data analysis of DNA-derived sequence data and RNA-derived sequence data. Therefore, DNA mutation information and RNA abnormality information for a patient specimen can be collected substantially simultaneously. Therefore, as described above, while ensuring accuracy, the waiting time between each step for each specimen can be minimized, improving the efficiency of the entire test.

[0059] More specifically, the gene mutation analysis method according to this embodiment includes a preparation step of simultaneously extracting DNA and RNA from a common patient specimen and generating DNA-derived samples and RNA-derived samples from the extracted DNA and RNA, respectively; a sequencing step of simultaneously sequencing the generated DNA-derived samples and RNA-derived samples using a next-generation sequencer to obtain sequence data; and a data analysis step of simultaneously analyzing the sequence data obtained for the DNA-derived samples and the RNA-derived samples using a data analyzer to obtain DNA mutation information and RNA abnormality information for the patient specimen. This method can suppress the effects of heterogeneity to ensure analytical accuracy, and can significantly reduce the time required for the sequencing and data analysis steps compared to conventional analytical methods in which DNA and RNA data analysis was performed separately. Therefore, the DNA mutation information and RNA abnormality information can be provided to users (healthcare professionals and experts) in a consolidated manner, allowing the users to begin their analysis promptly.

[0060] Furthermore, since DNA mutation information and RNA abnormality information for the same patient can be provided to the user in one place, the user can easily compare DNA mutation information and RNA abnormality information to determine what factors influence protein abnormalities in cancer and other conditions, and what causes these factors. For example, for an "ALK translocation tumor," which can be identified using only DNA-derived sequence data, by comparing the analysis results of DNA-derived sequence data with the analysis results of RNA-derived sequence data, it becomes possible to determine, for example, that "ALK translocation tumors are EML4 fusion gene tumors." This facilitated comparison can improve the efficiency of causal analysis of disease based on gene mutation information. Furthermore, comparative studies that include information on germline mutations in addition to somatic mutations are also possible.

[0061] Although the embodiments of the present invention have been specifically described above, the present invention is not limited to the above-described specific embodiments. Various modifications and changes to the specific examples described in the above embodiments are possible within the scope of the gist of the present invention as defined in the claims.

[0062] Although the nucleic acid species analyzed by the gene mutation analysis method according to the above embodiment are DNA and mRNA, the present invention is not limited to these nucleic acid species. Furthermore, although the tumor type analyzed by the gene mutation analysis method according to the present embodiment is solid cancer in general, the present invention is not limited to these tumor types. Furthermore, although the sample type analyzed by the gene mutation analysis method according to the present embodiment is FFPE, the present invention is not limited to this. As long as the sample is collected from a patient (mainly including cells from the test site), it does not have to be FFPE. Furthermore, although the sequencing step is performed by a next-generation sequencer 110 in the present embodiment, the present invention is not limited to this. Other base sequence analysis methods, such as Sanger sequencing or PCR, can also be used.

[0063] The disclosures of the specification, drawings and abstract contained in Japanese Patent Application No. 2023-103518, filed on June 23, 2023, are incorporated herein by reference in their entirety.

[0064] The present invention is useful as a gene mutation analysis method and a gene mutation analysis system that can improve the efficiency of disease causal analysis based on gene mutation information while ensuring accuracy.

[0065] 100 Gene mutation analysis system 110 Next-generation sequencer 120 Sequence data storage device 130 Data analysis device 131 Control unit 131a Processor 131b Memory 131c Storage 132 Operation input unit 133 Display unit 134 First interface unit 135 Second interface unit 140 Terminal device 150 Well plate 151 Well 154 Tube 200 Medical institution information system 220 Terminal device L ID list R Report S Sample to be analyzed SREF Reference genome sequence SDNA DNA read sequence SRNA RNA read sequence

Claims

1. A gene mutation analysis method comprising: a preparatory step of simultaneously extracting DNA and RNA from a common patient specimen and producing a DNA-derived sample and an RNA-derived sample from the extracted DNA and RNA, respectively; and an analytical processing step of performing gene mutation analysis processing on the produced DNA-derived sample and RNA-derived sample.

2. The gene mutation analysis method according to claim 1, wherein the analytical processing step includes a sequencing step of simultaneously sequencing the DNA-derived sample and the RNA-derived sample using a next-generation sequencer to obtain sequence data.

3. The gene mutation analysis method according to claim 1, wherein the analysis processing step includes a data analysis step of simultaneously analyzing sequence data obtained for each of the DNA-derived sample and the RNA-derived sample using a data analysis device to obtain DNA mutation information and RNA abnormality information for the patient specimen.

4. A method for analyzing gene mutations, comprising: a preparatory step of simultaneously extracting DNA and RNA from a common patient specimen and generating a DNA-derived sample and an RNA-derived sample from the extracted DNA and RNA, respectively; a sequencing step of simultaneously sequencing the generated DNA-derived sample and RNA-derived sample to obtain sequence data; and a data analysis step of simultaneously analyzing the sequence data obtained for each of the DNA-derived sample and the RNA-derived sample to obtain DNA mutation information and RNA abnormality information for the patient specimen.

5. The method for analyzing gene mutations according to claim 3, wherein the data analysis step includes collating the DNA-derived sample and the RNA-derived sample with common reference genome sequence data.

6. The method for analyzing gene mutations according to claim 4, wherein the data analysis step includes collating the DNA-derived sample and the RNA-derived sample with common reference genome sequence data.

7. The gene mutation analysis method according to claim 3, wherein the data analysis step stores the acquired DNA mutation information and RNA abnormality information in the same storage device.

8. The gene mutation analysis method according to claim 4, wherein the data analysis step includes storing the acquired DNA mutation information and RNA abnormality information in the same storage device.

9. The method for analyzing gene mutations according to claim 1, wherein the common patient specimen is a common section of a formalin-fixed, paraffin-embedded specimen of patient tissue.

10. The method for analyzing gene mutations according to claim 4, wherein the common patient specimen is a common section of a formalin-fixed, paraffin-embedded specimen of patient tissue.

11. The gene mutation analysis method according to claim 1, wherein the analysis target of the gene mutation analysis process in the analysis process step is a somatic mutation and / or a germline mutation.

12. A gene mutation analysis system for use in the gene mutation analysis method according to claim 4, comprising: a next-generation sequencer that executes the sequencing step; and a data analysis device that executes the data analysis step.

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