Method, equipment and medium for screening gene marker and gene marker obtained by screening

Abstract

The invention discloses a gene marker screening method, equipment and medium and a gene marker obtained through screening, and belongs to the technical field of tumor gene marker detection. According to the method, comprehensive variation scores of genes are obtained based on tumor exon sequencing data, so that candidate genes are determined. Specifically, firstly, exon sequencing data is preprocessed, then genomes are compared, then somatic mutation analysis and copy number variation analysis are carried out, and then a comprehensive variation score is calculated based on mutation frequency and copy number variation frequency. And finally, selecting the genes of which the comprehensive variation fractions are greater than a preset threshold value as candidate genes of the tumor gene marker. By utilizing the method disclosed by the invention, the gene marker of the tumor can be enriched, and the sensitivity and the specificity of the obtained gene marker on tumor identification are greatly improved, so that the gene marker has very important clinical value.

Description

[0001] Related patents This application is a divisional application of the Chinese invention patent application with application number 202311534650X, application date November 16, 2023, and invention name “Methods, devices and media for screening tumor gene markers based on exon sequencing”. Technical Field

[0002] The present invention belongs to the technical field of tumor gene marker detection, and specifically relates to a method, device and medium for screening gene markers and the gene markers obtained by screening. Background Art

[0003] Exome sequencing is a high-throughput sequencing technology designed to sequence the exon regions in the genome of an organism. In the human genome, exons occupy about 1-2% of the entire genome. Although the proportion of exon regions is small, they are the key parts of encoding proteins and undertake many biological functions. The main purpose of exome sequencing is to identify genetic variations in the exon regions of organisms, which can provide information about gene mutations, mutation frequencies, potential pathogenic mutations, and possible therapeutic targets in tumor cells. These genetic variations may affect the structure, function, and association of proteins with diseases.

[0004] The two main contents of tumor exome sequencing data analysis include gene mutation site detection and copy number variation. Mutation sites are used to detect mutations in the sequencing data after alignment to identify gene mutations in tumors, including single nucleotide polymorphisms (SNPs) and insertion / deletion variations (Indels). Commonly used variation detection tools include GATK, MuTect, VarScan, etc. Gene copy number variation (CNV) in tumor cells includes copy number gain (Copy Number Gain) and copy number loss (Copy Number Loss). Copy number gain means that the copy number of a gene increases in tumor cells, which may lead to overexpression of genes and promote the growth and proliferation of tumor cells. Copy number loss means that the copy number of a gene decreases in tumor cells, which may lead to downregulation or loss of gene expression, affecting the normal function and regulation of tumor cells.

[0005] In the current study of tumor genomes, some commonly used tools and algorithms are used to detect gene mutation sites and copy number changes. For example, MuTect and VarScan in GATK (Genome Analysis Toolkit) are commonly used tools for detecting gene mutation sites, which can identify single nucleotide variations (SNVs), insertion / deletion variations (Indels) and structural variations. ADTEx (Allelic Depth from Tumor-Exome) and CNVkit are tools for analyzing tumor exome sequencing data. Based on read coverage and sequencing depth information, it uses statistical models to infer the copy number and gene mutation status. The main function of these tools is to obtain information on gene mutations and copy number variations through analysis.

[0006] Intratumoral gene research requires the support of a large number of samples only through spectrum analysis of intratumoral gene somatic mutations, and it is often difficult to obtain specific types of samples in a short period of time. However, in the study of cohort samples, functional verification based only on the functional changes of mutant genes is often inconsistent with expectations, wasting a lot of manpower, computing power and time. Summary of the invention

[0007] In order to solve the above technical problems, the present invention obtains the comprehensive variation score of genes based on tumor exome sequencing data, thereby determining candidate genes. Specifically, the exome sequencing data is first preprocessed, then the genome is compared, and then somatic mutation analysis and copy number variation analysis are performed, and then the comprehensive variation score is calculated based on the mutation frequency and copy number variation frequency, and finally the gene with a comprehensive variation score greater than a preset threshold is selected as a candidate gene for tumor gene markers. To this end, the technical solution adopted by the present invention is as follows: The first aspect of the present invention provides a method for screening tumor gene markers based on exon sequencing, comprising the following steps: S1, obtain exome sequencing data of multiple tumor paired samples; S2: Detect mutation sites in exome sequencing data, determine mutation information, and determine the mutation frequency of each gene based on the mutation information of multiple tumor paired samples ; S3, calculate the copy number of each gene, determine the copy number variation information, and determine the copy number variation frequency of each gene

[0008] S Based on mutation frequency and copy number variation frequency , calculate the comprehensive mutation frequency :

[0009] Comprehensive mutation frequency for each gene Perform normalization and calculate the comprehensive variation score of the gene :

[0010] in, is the maximum value of the comprehensive mutation frequency of all genes, is the minimum value of the comprehensive mutation frequency of all genes, S5, select comprehensive variation score Genes with a value greater than a preset threshold are selected as candidate genes for tumor gene markers.

[0011] In the present invention, the tumor gene marker refers to a gene that can be used for tumor diagnosis, prognosis and prediction of treatment response.

[0012] In the present invention, the exon sequencing data can be obtained by self-sequencing or from a public database, using TCGA or cBioPortal, as long as it can be used for mutation site detection and copy number analysis.

[0013] In some embodiments of the present invention, in step S1, the exon sequencing data is obtained after the original offline data is subjected to quality control and preprocessing, and the quality control and preprocessing include: (1) Filter adapter reads; (2) Filter reads containing N greater than 5%; (3) Filter reads whose base numbers with quality values ​​Q≤10 account for more than 20% of the entire reads.

[0014] In some embodiments of the present invention, in step S2, mutation site detection is performed using tools including but not limited to MuTect2, VarScan, and Strelka.

[0015] In some embodiments of the present invention, in step S2, after determining the mutation information, mutations known to be unrelated to the tumor and non-functional mutations are further removed.

[0016] The purpose of the present invention is to screen tumor gene markers, so some known and recognized mutations that are not related to tumors can be removed first to avoid entering the next step of analysis. Obviously, non-functional mutations or nonsense mutations are not potential tumor gene markers and can be removed.

[0017] In some embodiments of the invention, the mutations include single nucleotide variations and insertion / deletion variations.

[0018] In some embodiments of the present invention, in step S2, for a particular gene, the mutation frequency The calculation formula is as follows:

[0019] in, Refers to the number of somatic mutations in the specific gene in all samples. Refers to the number of somatic mutations occurring in all samples.

[0020] In some embodiments of the present invention, in step S3, mutation site detection is performed using methods including but not limited to CNVkit, control-FREEC and ExomeCNV.

[0021] In some embodiments of the present invention, for a particular gene, the copy number variation frequency The calculation formula is as follows:

[0022] in, Refers to the number of copy number variations of the specific gene in all samples. Refers to the number of copy number variations occurring in all samples.

[0023] In some embodiments of the present invention, the preset threshold is 0.65, that is, genes with a comprehensive variation score greater than 0.65 are selected as candidate genes for tumor gene markers.

[0024] The second aspect of the present invention provides the use of a detection reagent for a gene marker in the preparation of a kit for diagnosing a tumor, wherein the gene marker is screened using the method for screening tumor gene markers based on exon sequencing described in the first aspect of the present invention.

[0025] In some embodiments of the present invention, the gene markers include one or more of NBPF10, PDE4DIP, COL6A1, CNTNAP3 and FAM210A.

[0026] In some embodiments of the present invention, the detection reagent is a primer or a probe, and detection can be performed based on methods such as qPCR and capture sequencing.

[0027] The present invention also provides a system for predicting whether a subject has cancer or has a risk of developing cancer or predicting the prognosis risk of a cancer patient, comprising the following modules: A data input module, used to input the expression level of the subject's gene marker; The prediction module is connected to the data input module and is used to determine whether the subject has cancer or has a risk of developing cancer or the prognostic risk according to the expression level of the gene marker.

[0028] In some embodiments of the present invention, the prediction module uses a machine learning model to make judgments.

[0029] Furthermore, the machine learning model is trained using any one of the following algorithms: random forest algorithm, support vector machine algorithm, linear regression algorithm, logistic regression algorithm, Bayesian classifier and neural network algorithm.

[0030] A third aspect of the present invention provides a computer device, comprising: Memory for storing computer programs; A processor is used to implement the steps of a method for screening tumor gene markers based on exon sequencing as described in the first aspect of the present invention when executing the computer program.

[0031] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of a method for screening tumor gene markers based on exon sequencing as described in the first aspect of the present invention are implemented.

[0032] Beneficial Effects of the Invention Compared with the prior art, the present invention has the following beneficial effects: The method of the present invention adopts a strategy based on copy number variation to comprehensively determine gene mutation sites, obtain accurate driver genes for mutation marker identification, further narrow the selection range of candidate genes, and improve the accuracy of driver gene mining. By screening out mutation sites or genes that occur frequently in tumors, markers for diagnosis, prognosis, and prediction of treatment response can be developed, thereby enriching the gene markers of tumors.

[0033] The gene markers obtained by the method of the present invention have greatly improved sensitivity and specificity for tumor identification and have very important clinical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The expression of NBPF10, PDE4DIP, COL6A1, CNTNAP3 and FAM210A in tumor samples and normal samples in Example 2 of the present invention is shown.

[0035] Figure 2 The effect of abnormal expression of NBPF10, PDE4DIP, COL6A1, CNTNAP3 and FAM210A on the prognosis and survival of lung cancer patients in Example 2 of the present invention is shown. DETAILED DESCRIPTION

[0036] Unless otherwise indicated, implied from the context, or customary in the prior art, all parts and percentages in this application are based on weight, and the tests and characterization methods used are all synchronized with the filing date of this application. Where applicable, the contents of any patent, patent application or disclosure involved in this application are fully incorporated herein by reference, and their equivalent patent families are also introduced as references, especially the definitions of relevant terms in the art disclosed in these documents. If the definition of a specific term disclosed in the prior art is inconsistent with any definition provided in this application, the definition of the term provided in this application shall prevail.

[0037] Numerical ranges in this application are approximate values, so unless otherwise specified, they may include values ​​outside the range. Numerical ranges include all values ​​from the lower limit to the upper limit increased by 1 unit, provided that there is an interval of at least 2 units between any lower value and any higher value. For a range containing a value less than 1 or containing a fraction greater than 1 (e.g., 1.1, 1.5, etc.), 1 unit is appropriately regarded as 0.0001, 0.001, 0.01 or 0.1. For a range containing a single digit less than 10 (e.g., 1 to 5), 1 unit is generally regarded as 0.1. These are only specific examples of what is intended to be expressed, and all possible combinations of the values ​​between the lowest and highest values ​​listed are considered to be clearly recorded in this application.

[0038] The terms "comprising", "including", "having" and their derivatives do not exclude the presence of any other components, steps or processes, and are irrelevant to whether these other components, steps or processes are disclosed in this application. To eliminate any doubt, unless explicitly stated, all compositions using the terms "comprising", "including", or "having" in this application may include any additional additives, adjuvants or compounds. On the contrary, except for those necessary for operating performance, the term "essentially consisting of..." excludes any other components, steps or processes from the scope of any description of the term below. The term "consisting of..." does not include any components, steps or processes that are not specifically described or listed. Unless explicitly stated, the term "or" refers to the listed individual members or any combination thereof.

[0039] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments.

[0040] Example The following examples are used to demonstrate preferred embodiments of the present invention. It will be appreciated by those skilled in the art that the techniques disclosed in the following examples represent techniques discovered by the inventors that can be used to implement the present invention and therefore can be considered as preferred embodiments of the present invention. However, it will be appreciated by those skilled in the art based on this specification that many modifications may be made to the specific embodiments disclosed herein and still achieve the same or similar results without departing from the spirit or scope of the present invention.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and the disclosure and materials cited therein are hereby incorporated by reference.

[0042] Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many technical equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the claims.

[0043] The experimental methods in the following examples are conventional methods unless otherwise specified. The instruments and equipment used in the following examples are conventional laboratory instruments and equipment unless otherwise specified; the experimental materials used in the following examples are purchased from conventional biochemical reagent stores unless otherwise specified.

[0044] Example 1 Analysis of exome sequencing data of paired tumor samples This example is based on exome sequencing data from 20 pairs of lung cancer samples to perform comprehensive variation score analysis on tumor mutation genes.

[0045] 1. Sequencing data preprocessing and genome alignment (1) Filter adaptor reads; (2) Filter reads containing N (N means the base information cannot be determined) with a ratio greater than 5%; (3) Filter reads of low quality (the number of bases with quality value Q≤10 accounts for more than 20% of the entire read).

[0046] After preprocessing, high-quality exome sequencing data (clean data) was obtained.

[0047] Use BWA software to align the clean data with the reference genome and remove duplicate reads to obtain the deduplicated bam file. The next step is to detect mutation sites and analyze copy numbers.

[0048] 2. Somatic mutation analysis After comparing the result file with the reference genome, MuTect2 was used to analyze the somatic mutations of each sample to obtain the result file in vcf format, and then the annovar tool was used to annotate the detected mutation file with the genome database. Based on the results of mutation annotation, mutations and non-functional mutations known to be unrelated to tumors were removed, and non-synonymous mutations were retained. There were a total of 1997 somatic mutation genes.

[0049] Calculate the mutation frequency of each gene , the calculation formula is as follows:

[0050] in, Refers to the number (frequency) of somatic mutations in a specific gene in all samples. Refers to the number of somatic mutations in all samples (in this example, =38).

[0051] Table 1 shows the top 30 genes ranked from highest to lowest in terms of mutation frequency.

[0052] Table 1 Somatic mutation genes (top 30 mutation frequencies)

[0053] 3. Copy Number Variation Analysis The inventors used CNVkit to analyze the copy number variation of the comparison results of 20 pairs of tumor samples. The copy number estimation results were statistically analyzed to identify potential CNVs regions. After that, the number of gene copy number variations was obtained after sorting by the gistic tool. A total of 1,844 gene copy number variations were obtained, and the copy number variation frequency of each gene was finally calculated. , the calculation formula is as follows:

[0054] in, Refers to the number of copy number variations of a specific gene in all samples. Refers to the number of copy number variations in all samples (in this example, =34).

[0055] The copy number variation frequencies are shown in Table 2: Table 2 Sample copy number variation results (first 30 genes)

[0056] 4. Calculation of comprehensive mutation score Based on mutation frequency and copy number variation frequency , calculate the comprehensive mutation frequency .

[0057]

[0058] Comprehensive mutation frequency for each gene Perform normalization and calculate the comprehensive variation score of the gene , the calculation formula is as follows:

[0059] in, is the maximum value of the comprehensive mutation frequency of all genes (0.8483 in this example); is the minimum value of the comprehensive mutation frequency of all genes (0.0264 in this example).

[0060] Comprehensive variation score The results are shown in Table 3.

[0061] Table 3 Comprehensive variation scores Results (show only Top 30)

[0062] As shown in Table 3, genes such as NBPF10, PDE4DIP, COL6A1, CNTNAP3, and FAM210A have relatively high comprehensive variation scores ( >0.65), indicating that these genes with somatic mutations have the potential to change in expression levels and can serve as markers for tumor diagnosis or identification.

[0063] Example 2 Application of the Screened Genes In order to study the clinical significance of NBPF10, PDE4DIP, COL6A1, CNTNAP3 and FAM210A genes in human lung cancer and verify the application value of the comprehensive variation score of Example 1, this example collected 1154 lung cancer-related samples, 110 normal samples, and 1054 lung cancer samples from the TCGA website, and used high-throughput data for differential analysis. The results showed that the reproducibility between groups was not high. After principal component analysis to eliminate outlier samples, 952 tumor samples (tumor) and 102 normal samples (normol) were finally retained. The expression levels of the above five genes in tumor samples and normal samples are shown in Figure 2. Figure 1 shown.

[0064] Depend on Figure 1It can be seen that the expression of COL6A1, FAM210A and NBPF10, PDE4DIP, CNTNAP3 genes between lung cancer and normal samples was significantly different. The expression of COL6A1 and FAM210A genes in tumor samples was upregulated compared with that in normal samples, while the expression of NBPF10, PDE4DIP, and CNTNAP3 was downregulated, indicating that the use of comprehensive variation score ( ) can reflect the expression level of the gene.

[0065] Furthermore, the inventors analyzed the relationship between the expression levels of NBPF10, PDE4DIP, COL6A1, CNTNAP3 and FAM210A genes and the prognosis of lung cancer: the clinical data of 952 patients were sorted out and samples without valid clinical information were removed, and the remaining 371 tumor samples were used for Kaplan-Meier survival analysis, such as Figure 2 shown.

[0066] Depend on Figure 2 It can be seen that the survival of patients with high expression of CNTNAP3, PDE4DIP and NBPF10 (median survival of 30 months) was significantly shortened compared with patients with low expression (median survival of 48 months) (Log-rank, P < 0.001). The survival of patients with low expression of FAM210A gene (median survival of 42 months) was significantly shortened compared with patients with high expression of FAM210A gene (median survival of 48) (Log-rank, P < 0.05). However, the expression of COL6A1 gene had no significant effect on the survival of tumor patients.

[0067] In summary, the abnormal expression of NBPF10, PDE4DIP, CNTNAP3 and FAM210A provided by the present invention is highly correlated with the prognostic risk of lung cancer, and can be used for the diagnosis, efficacy evaluation and monitoring of lung cancer, and the diagnostic results can be used for auxiliary judgment of clinical symptoms.

[0068] All documents mentioned in the present invention are cited as references in this application, just as each document is cited as reference individually. In addition, it should be understood that after reading the above teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the claims attached to this application.

Claims

1. Use of a detection reagent for a gene marker in the preparation of a kit for predicting whether a subject has a tumor or has a risk of developing a tumor or predicting the prognosis risk of a tumor patient, wherein the gene marker comprises one or more of NBPF10, PDE4DIP, COL6A1, CNTNAP3 and FAM210A, and the tumor is lung cancer.

2. The use according to claim 1, characterized in that: The gene marker combination includes NBPF10, PDE4DIP, CNTNAP3 and FAM210A.

3. A method for screening tumor gene markers based on copy number variation, characterized in that: The following steps are involved: S1, obtaining exome sequencing data of multiple paired tumor samples, wherein the tumor is lung cancer; S2: Detect mutation sites in exome sequencing data, determine mutation information, and determine the mutation frequency of each gene based on the mutation information of multiple tumor paired samples ; S3, calculate the copy number of each gene, determine the copy number variation information, and determine the copy number variation frequency of each gene S Based on mutation frequency and copy number variation frequency , calculate the comprehensive mutation frequency : Comprehensive mutation frequency for each gene Perform normalization and calculate the comprehensive variation score of the gene : in, is the maximum value of the comprehensive mutation frequency of all genes, is the minimum value of the comprehensive mutation frequency of all genes, S5, select comprehensive variation score Genes with values ​​greater than a preset threshold are used as candidate genes for tumor gene markers to obtain the gene marker combination.

4. The method for screening tumor gene markers based on copy number variation according to claim 3, characterized in that: In step S1, the exon sequencing data is obtained after the original data is quality controlled and preprocessed, and the quality control and preprocessing include: (1) Filter adapter reads; (2) Filter reads containing N greater than 5%; (3) Filter reads whose base numbers with quality value Q≤10 account for more than 20% of the total reads.

5. The method for screening tumor gene markers based on copy number variation according to claim 3, characterized in that: In step S2, after the mutation information is determined, mutations known to be unrelated to the tumor and non-functional mutations are further removed.

6. The method for screening tumor gene markers based on copy number variation according to claim 3, characterized in that: The mutations include single nucleotide variations and insertion / deletion variations.

7. A method for screening tumor gene markers based on copy number variation according to any one of claims 3 to 6, characterized in that: In step S2, for a specific gene, the mutation frequency The calculation formula is as follows: in, Refers to the number of somatic mutation sites of the specific gene in all samples. Refers to the number of somatic mutations occurring in all samples.

8. A method for screening tumor gene markers based on copy number variation according to any one of claims 3 to 6, characterized in that: For a specific gene, the copy number variation frequency The calculation formula is as follows: in, Refers to the number of copy number variations of the specific gene in all samples. Refers to the number of copy number variations occurring in all samples.

9. A computer device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of a method for screening tumor gene markers based on copy number variation as described in any one of claims 3 to 8 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the steps of a method for screening tumor gene markers based on copy number variation as described in any one of claims 3 to 8 are implemented.

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