CN114267410A - Method, device and storage medium for determining the state of a tumor mutational burden - Google Patents
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Abstract
Embodiments of the present disclosure relate to methods, electronic devices, and storage media for determining a state of tumor mutational burden, and relate to the field of biological information. According to the method, sequencing data for the gene combination and the length of the capture region of the gene combination are obtained, the sequencing data being associated with a tumor sample of the target object, the tumor sample being associated with a target tumor type; determining a first tumor mutation burden based on the sequencing data and length; obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with a target tumor type; determining, for each full exon sequencing result, a second tumor mutation burden in the capture region of the gene combination based on the full exon sequencing result and the length; and determining a status of the tumor mutation burden of the subject based on the first tumor mutation burden and a plurality of second tumor mutation burdens associated with the plurality of whole exon sequencing results. This enables the determination of the state of tumor mutation load for gene combinations and tumor types.
Description
Technical Field
Embodiments of the present disclosure relate generally to the field of biological information, and more particularly, to methods, electronic devices, and computer storage media for determining a state of tumor mutational burden.
Background
Tumor Mutation Burden (TMB) refers to the total number of point mutations and insertion/deletion mutations occurring per megabase in the coding region of an exon in the genome of a Tumor cell. Tumor mutational burden was originally used as a biomarker for predicting efficacy when treating patients with advanced melanoma with Ipilimumab (Ipilimumab) or Tremelimumab (Tremelimumab). However, with the increase of research, the tumor mutation load is found to have corresponding curative effect prediction effect in other cancer species (such as non-small cell lung cancer, head and neck squamous cell cancer, small cell lung cancer, urinary epithelial cancer and the like). Thus, tumor mutation burden is becoming an independent biomarker for the efficacy of PD-1/PD-L1 and CTLA-4 inhibitors. On day 16/6/2020, the U.S. Food and Drug Administration (FDA) approved the use of Pabollizumab alone for the treatment of adult and pediatric solid Tumor patients with unresectable or metastatic Tumor tissue samples with High Mutation loads (TMB-H) of > 10 mutations/Mb (megabase). High throughput Sequencing (NGS) has been widely used for cancer diagnosis and drug administration, and F1CDx estimates the tumor mutation load by detecting 324 gene combination (panel) mutations.
Disclosure of Invention
A method, electronic device, and computer storage medium for determining a state of tumor mutational burden are provided, which enable determination of a state of tumor mutational burden for a combination of genes and a tumor type.
According to a first aspect of the present disclosure, a method for determining the status of a tumor mutational burden is provided. The method comprises the following steps: obtaining sequencing data for the gene combination and a length of a capture region of the gene combination, the sequencing data being associated with a tumor sample of the target object, the tumor sample being associated with a target tumor type; determining a first tumor mutation burden based on the sequencing data and the length of the capture region of the gene combination; obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with a target tumor type; determining, for each full exon sequencing result of the plurality of full exon sequencing results, a second tumor mutation burden in the capture region of the combination of genes based on the full exon sequencing result and the length of the capture region of the combination of genes; and determining a status of the tumor mutation burden of the subject based on the first tumor mutation burden and a plurality of second tumor mutation burdens associated with the plurality of whole exon sequencing results.
According to a second aspect of the present disclosure, an electronic device is provided. The electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method according to the first aspect of the disclosure.
In a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements a method according to the first aspect of the present disclosure.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements.
FIG. 1 is a schematic block diagram of an information processing environment 100 in accordance with an embodiment of the present disclosure.
Fig. 2 is a schematic diagram of a method 200 for determining a status of a tumor mutational burden, according to an embodiment of the present disclosure.
Fig. 3 is a schematic diagram of a method 300 for determining a state of tumor mutational burden of a target subject, according to an embodiment of the present disclosure.
Fig. 4 is a graph 400 comparing tumor mutation load distribution of gene combination sequencing and whole exon sequencing according to embodiments of the disclosure.
Fig. 5 is a schematic block diagram of an electronic device for implementing a method for determining a state of tumor mutational burden according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The term "include" and variations thereof as used herein is meant to be inclusive in an open-ended manner, i.e., "including but not limited to". Unless specifically stated otherwise, the term "or" means "and/or". The term "based on" means "based at least in part on". The terms "one example embodiment" and "one embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
As described above, F1CDx was evaluated for the magnitude of tumor mutation burden by detecting mutations in 324 gene combinations (panel). However, many tumor sequencing companies have introduced their own gene combination sequencing products, and most tumor patients use non-F1 CDx combination products for gene detection. Since there is no uniform criterion for the threshold of tumor mutation burden, many clinical trials use different thresholds, such as 10/Mb for F1CDx, and 102 mutations for KEYNOTE-012. Furthermore, the number of genes included in each gene combination is different, which also causes a change in the threshold value. Therefore, there is a need for a scheme that can judge the status of tumor mutation load of gene combination products of different companies.
In addition, most of the detection products have threshold values which do not distinguish cancer species, and the distribution of the tumor mutation load is inconsistent among different cancer species, so that the tumor mutation load of different cancer species is not easy to evaluate by using a unified standard. Also, traditional approaches neglect the impact of population problems on the threshold of tumor mutational burden.
To address, at least in part, one or more of the above problems, as well as other potential problems, example embodiments of the present disclosure propose a scheme for determining the status of a tumor mutational burden. In this approach, sequencing data for a gene combination and a length of a capture region for the gene combination are obtained, the sequencing data being associated with a tumor sample of the target subject, the tumor sample being associated with a target tumor type; determining a first tumor mutation burden based on the sequencing data and the length of the capture region of the gene combination; obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with a target tumor type; determining, for each full exon sequencing result of the plurality of full exon sequencing results, a second tumor mutation burden in the capture region of the combination of genes based on the full exon sequencing result and the length of the capture region of the combination of genes; and determining a status of the tumor mutation burden of the subject based on the first tumor mutation burden and a plurality of second tumor mutation burdens associated with the plurality of whole exon sequencing results.
According to aspects of the present disclosure, by obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with a target tumor type and determining a second tumor mutation burden summarized by capture regions of a combination of genes for each whole exon sequencing result, a status of the tumor mutation burden for the target subject can be determined based on the plurality of second tumor mutation burdens associated with the plurality of whole exon sequencing results, thereby enabling a status of the tumor mutation burden to be determined for the combination of genes and the tumor type.
Hereinafter, specific examples of the present scheme will be described in more detail with reference to the accompanying drawings.
FIG. 1 shows a schematic block diagram of an information processing environment 100 in accordance with embodiments of the present disclosure. The information processing environment 100 may include an electronic device 110.
The electronic device 110 includes, for example, but is not limited to, a personal computer, desktop computer, laptop computer, smart phone, personal digital assistant, server, and the like.
The information processing environment 100 can also include sequencing data 120 for combinations of genes. The sequencing data 120 is associated with a tumor sample of the target subject. The tumor sample is associated with a target tumor type. The object includes, for example, a person. The target tumor type may include a variety of suitable tumor types.
The information processing environment 100 may also include a length 130 of the capture region of the gene combination, a plurality of full exon sequencing results 140 for a plurality of subjects (1-n subjects, n being greater than or equal to 0) associated with the target tumor type, and a state 150 of tumor mutational burden for the target subject.
The electronics 110 are configured to obtain sequencing data 120 for the gene combination and a length 130 of a capture region of the gene combination, the sequencing data 120 being associated with a tumor sample of the target subject, the tumor sample being associated with a target tumor type; determining a first tumor mutation burden based on the sequencing data 120 and the length 130 of the capture region of the gene combination; obtaining a plurality of whole exon sequencing results 140 for a plurality of subjects associated with a target tumor type; determining a second tumor mutation burden in the capture region of the combination of genes based on the full exon sequencing results and the length 130 of the capture region of the combination of genes for each full exon sequencing result of the plurality of full exon sequencing results 140; and determining a status of tumor mutational burden of the subject of interest based on the first tumor mutational burden and a plurality of second tumor mutational burdens associated with the plurality of full exon sequencing results 150.
Thus, by obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with a target tumor type and determining a second tumor mutation burden summarized by capture regions of a combination of genes for each whole exon sequencing result, a status of the tumor mutation burden for the target subject can be determined based on the plurality of second tumor mutation burdens associated with the plurality of whole exon sequencing results, thereby enabling a status of the tumor mutation burden to be determined for the combination of genes and the tumor type.
Fig. 2 shows a flow diagram of a method 200 for determining a state of tumor mutational burden, according to an embodiment of the present disclosure. For example, the method 200 may be performed by the electronic device 110 as shown in fig. 1. It should be understood that method 200 may also include additional blocks not shown and/or may omit blocks shown, as the scope of the present disclosure is not limited in this respect.
At block 202, the electronic device 110 obtains sequencing data 120 for the gene combination and the length 130 of the capture region of the gene combination, the sequencing data 120 being associated with a tumor sample of the target subject, the tumor sample being associated with the target tumor type.
It is understood that the length of the capture region of a gene combination refers to the number of bases included in the gene combination, e.g., in megabases Mb.
At block 204, the electronic device 110 determines a first tumor mutation burden based on the sequencing data 120 and the length 130 of the capture region of the gene combination.
Specifically, the electronic device 110 can determine, based on the sequencing data 120, a first number of mutations having a variant allele frequency greater than a predetermined number. The predetermined value includes, for example, but is not limited to, 5%.
Subsequently, the electronic device 110 can determine a first tumor mutation burden based on the first number of mutations having a variant allele frequency greater than a predetermined value and the length 130 of the capture region of the gene combination. For example, a first tumor mutation burden is determined by dividing a first number of mutations having a variant allele frequency greater than a predetermined number by the length of the capture region of the gene combination.
It should be understood that mutations in the sequencing data include synonymous mutations and non-synonymous mutations. Non-synonymous mutations may include point mutations and insertion/deletion mutations.
At block 206, the electronic device 110 obtains a plurality of full exon sequencing results 140 for a plurality of objects associated with the target tumor type.
In some embodiments, the electronic device 110 may obtain a plurality of sets of full exon sequencing results for a plurality of sets of objects associated with a plurality of tumor types, the plurality of tumor types including a target tumor type. For example, the electronic device 110 can obtain, from the database, a plurality of sets of full exon sequencing results for a plurality of sets of objects associated with a plurality of tumor types. The database may be stored in the electronic device 110 or may be communicatively coupled to the electronic device 110. Multiple tumor types include, for example, but are not limited to, brain glioma, colorectal carcinoma, hepatocellular carcinoma, glioblastoma, lung adenocarcinoma, soft tissue sarcoma, gastric carcinoma, cholangiocarcinoma, breast cancer, medulloblastoma, pancreatic carcinoma, non-small cell lung carcinoma, renal carcinoma, esophageal carcinoma, head and neck tumors, non-hodgkin's lymphoma, and the like.
Subsequently, the electronic device 110 can obtain a plurality of full exon sequencing results 140 for a plurality of subjects associated with the target tumor type from the plurality of full exon sequencing result sets.
It is understood that mutations in the whole exon sequencing results include only non-synonymous mutations. Non-synonymous mutations may include point mutations and insertion/deletion mutations.
In some embodiments, the plurality of object sets belong to the same population as the target object. The same population includes, for example, but is not limited to, Chinese.
In other embodiments, the plurality of object sets are associated with a plurality of ethnic groups, the plurality of objects belonging to the same ethnic group as the target object.
Thus, the state of tumor mutation burden of the target object can be determined in consideration of the results of sequencing a plurality of whole exons of a plurality of objects belonging to the same population as the target object.
At block 208, the electronic device 110 determines, for each full exon sequencing result of the plurality of full exon sequencing results, a second tumor mutation burden in the capture region of the gene combination based on the full exon sequencing result and the length 130 of the capture region of the gene combination.
Specifically, the electronic device 110 can determine a second number of mutations in the capture region of the gene combination having a variant allele frequency greater than a predetermined number based on the full exon sequencing results.
Subsequently, the electronic device 110 can determine a second tumor mutation burden in the capture region of the combination of genes based on a second number of mutations in the capture region of the combination of genes having a variant allele frequency greater than a predetermined number and a length of the capture region of the combination of genes. For example, a second tumor mutation burden in the capture region of the gene combination is determined by dividing a second number of mutations in the capture region of the gene combination having a variant allele frequency greater than a predetermined value by the length of the capture region of the gene combination.
At block 210, the electronic device 110 determines a status of the tumor mutation burden of the target subject based on the first tumor mutation burden and a plurality of second tumor mutation burdens associated with the plurality of full exon sequencing results.
Thus, by obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with a target tumor type and determining a second tumor mutation burden summarized by capture regions of a combination of genes for each whole exon sequencing result, a status of the tumor mutation burden for the target subject can be determined based on the plurality of second tumor mutation burdens associated with the plurality of whole exon sequencing results, thereby enabling a status of the tumor mutation burden to be determined for the combination of genes and the tumor type.
Fig. 3 shows a flow chart of a method 300 for determining a state of tumor mutational burden of a target subject according to an embodiment of the present disclosure. For example, the method 300 may be performed by the electronic device 110 as shown in fig. 1. It should be understood that method 300 may also include additional blocks not shown and/or may omit blocks shown, as the scope of the disclosure is not limited in this respect.
At block 302, the electronic device 110 determines a predetermined quantile of the plurality of second tumor mutational burden as a threshold for the tumor mutational burden associated with the target tumor type.
The predetermined quantiles include, for example, but are not limited to, the upper tertile. For example, a plurality of second tumor mutational burden may be ranked from high to low, generating a ranking result, and determining an upper third place in the ranking result as a threshold for tumor mutational burden.
At block 304, the electronic device 110 determines whether the first tumor mutational burden is greater than a threshold.
If the electronic device 110 determines at block 304 that the first tumor mutational burden is greater than the threshold, then at block 306 it is determined that the status of the tumor mutational burden of the target object is high.
If, at block 304, the electronic device 110 determines that the first tumor mutational burden is less than or equal to the threshold value, then, at block 308, the status of the tumor mutational burden of the target object is determined to be low.
Thus, by using a predetermined quantile among a plurality of second tumor mutation loads of a plurality of subjects associated with a target tumor type as a threshold value for the tumor mutation load for evaluating the level of the tumor mutation load of the target subject, the difference in the distribution of the tumor mutation load among different tumor types is sufficiently taken into consideration, and the accurate determination of the level of the tumor mutation load based on the tumor type can be realized.
Taking a genome assembly comprising 642 genes as an example, all patient whole exon sequencing results identical to the cancer species of a patient are firstly extracted, and then mutations in the region are screened according to the capture region of the gene assembly, so as to simulate the capture sequencing results of the gene assembly. The cancer mapping graph is drawn, the relative position of the patient is marked, the result shows that the result of the gene combination is consistent with the whole exon sequencing result, as shown in fig. 4, the left side is the result of the gene combination, the right side is the whole exon sequencing result, and the results are very similar, which indicates that the scheme disclosed by the invention is feasible.
Fig. 5 illustrates a schematic block diagram of an example device 500 that may be used to implement embodiments of the present disclosure. For example, the electronic device 110 as shown in FIG. 1 may be implemented by the device 500. As shown, device 500 includes a Central Processing Unit (CPU)501 that may perform various appropriate actions and processes according to computer program instructions stored in a Read Only Memory (ROM)502 or computer program instructions loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the random access memory 503, various programs and data required for the operation of the device 500 can also be stored. The central processing unit 501, the read only memory 502 and the random access memory 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in the device 500 are connected to the input/output interface 505, including: an input unit 506 such as a keyboard, a mouse, a microphone, and the like; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508, such as a magnetic disk, optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The various processes and processes described above, such as the methods 200, 300, may be performed by the central processing unit 501. For example, in some embodiments, the methods 200, 300 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 500 via the read only memory 502 and/or the communication unit 509. When the computer program is loaded into the random access memory 503 and executed by the central processing unit 501, one or more of the actions of the methods 200, 300 described above may be performed.
The present disclosure relates to methods, apparatuses, systems, electronic devices, computer-readable storage media and/or computer program products. The computer program product may include computer-readable program instructions for performing various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A method for determining the status of tumor mutational burden comprising:
obtaining sequencing data for a gene combination and a length of a capture region of the gene combination, the sequencing data being associated with a tumor sample of a target subject, the tumor sample being associated with a target tumor type;
determining a first tumor mutation burden based on the sequencing data and the length;
obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with the target tumor type;
determining, for each full exon sequencing result of the plurality of full exon sequencing results, a second tumor mutation burden in a capture region of the gene combination based on the full exon sequencing result and the length; and
determining a status of tumor mutational burden of the subject of interest based on the first tumor mutational burden and a plurality of second tumor mutational burdens associated with the plurality of whole exon sequencing results.
2. The method of claim 1, wherein determining the state of tumor mutational burden of the target subject comprises:
determining a predetermined quantile in the plurality of second tumor mutational burden as a threshold for tumor mutational burden associated with the target tumor type;
determining that the status of the tumor mutational burden of the target subject is high if it is determined that the first tumor mutational burden is greater than the threshold; and
determining the status of the tumor mutational burden of the target subject as low if it is determined that the first tumor mutational burden is less than or equal to the threshold.
3. The method of claim 1, wherein determining the first tumor mutational burden comprises:
determining, based on the sequencing data, a first number of mutations for which variant allele frequencies are greater than a predetermined number; and
determining a first tumor mutational burden based on the first number and the length.
4. The method of claim 3, wherein the mutations comprise synonymous mutations and non-synonymous mutations.
5. The method of claim 1, wherein determining a second tumor mutation burden in a capture region of the gene combination comprises:
determining a second number of mutations in the capture region of the gene combination for which the variant allele frequency is greater than the predetermined number based on the whole exon sequencing results; and
determining a second tumor mutation burden in the capture region of the gene combination based on the second number and the length.
6. The method of any one of claims 1-5, wherein obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with the target tumor type comprises:
obtaining a plurality of sets of whole exon sequencing results for a plurality of sets of objects associated with a plurality of tumor types, the plurality of tumor types including the target tumor type; and
obtaining a plurality of whole exon sequencing results for a plurality of subjects associated with the target tumor type from the plurality of whole exon sequencing result sets.
7. The method of claim 6, wherein the plurality of object sets belong to the same population as the target object.
8. The method of claim 6, wherein the plurality of sets of objects are associated with a plurality of ethnic groups, and the plurality of objects belong to the same ethnic group as the target object.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method of any one of claims 1 to 8.
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| CN115186087A (en) * | 2022-07-01 | 2022-10-14 | 至本医疗科技（上海）有限公司 | Method, apparatus and computer storage medium for retrieving information related to gene and tumor |
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| CN115186087A (en) * | 2022-07-01 | 2022-10-14 | 至本医疗科技（上海）有限公司 | Method, apparatus and computer storage medium for retrieving information related to gene and tumor |
| CN115186087B (en) * | 2022-07-01 | 2023-11-28 | 至本医疗科技（上海）有限公司 | Method, apparatus and computer storage medium for retrieving information related to genes and tumors |
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