A signature gene set for detecting pan-cancer BRAF mutation activity and its application

Abstract

The present invention discloses a method for detecting pan-cancer <h2 style=";text-align:left;direction:ltr">BRAF The characteristic gene set and its application of mutation activity, specifically, first construct a set of genes that can specifically reflect <h2 style=";text-align:left;direction:ltr"> BRAF A signature gene set for mutation activity was developed, and based on this, a customized fluorescence quantitative PCR kit was developed specifically for evaluating the transcriptional activity status of the BRAF pathway in tumor tissue samples. This signature gene set includes the following genes: <h2 style=";text-align:left;direction:ltr"> ADAM9, CCND1, CLDN1 <h2 style=";text-align:left;direction:ltr"> CTDSPL,DUSP6,EPHA2,ERRFI1,ETV4,ETV5,FZD7, <h2 style=";text-align:left;direction:ltr"> GPRC5A,IGFBP3,ITGA3,MTUS1,PHLDA2,PLEKHH1, <h2 style=";text-align:left;direction:ltr"> S100A16,S100A6,SEMA3A,SLC1A1,SPRY4, <h2 style=";text-align:left;direction:ltr"> TFAP2C,TNFRSF12A,TNFRSF21,TPD52L1 .

Description

Technical Field

[0001] The present invention belongs to the field of bioinformatics and provides a method for detecting pan-cancer BRAF Signature gene sets for mutation activity and their applications. Background Art

[0002] BRAF It is an important oncogene with significant activating mutations (such as V600E) in many tumor types and is widely used as a biomarker for targeted therapy. BRAF The mainstream approach to gene mutation detection patents is basically focused on detection BRAF Classic mutation sites (such as V600E, V600K) are often detected by combining allele-specific amplification (AS-PCR) with qPCR, the goal of which is to distinguish mutations from wild-type sequences.

[0003] However, clinical studies have shown that BRAF Mutation status cannot fully predict the response to BRAF inhibitors or chemotherapy in all patients, and there is significant heterogeneity and prognostic differences. In recent years, more and more studies have focused on the transcriptional activity of the BRAF signaling pathway rather than relying solely on gene mutations as an evaluation indicator. The BRAF pathway can be activated through various mechanisms, including upstream signal enhancement, co-mutation, and epigenetic regulation. Single mutation detection methods are no longer able to fully reflect the functional status of BRAF signaling. Therefore, it is of great significance to develop a multi-gene detection method to evaluate the degree of BRAF pathway activation based on expression levels.

[0004] The existing technology has the following disadvantages:

[0005] (1) Traditional mutation detection cannot assess the defect of functional activation status;

[0006] (2) In actual clinical practice, some BRAF Patients with wild-type mutations also have pathway activation and are sensitive to drugs;

[0007] (3) Failure to identify mutations in genes such as RAS, MEK, and PTEN that synergistically affect BRAF signaling;

[0008] (4) It can only determine the presence or absence of mutations, but cannot predict patient survival, drug resistance, and other risks;

[0009] (5) Some BRAF Mutations such as D594G are “suppressor” mutations and do not lead to signaling activation. Summary of the Invention

[0010] In view of this, the purpose of the present invention is to provide a method for detecting pan-cancer BRAF Signature gene sets for mutation activity and their applications.

[0011] To achieve the above object, the present invention provides the following technical solutions:

[0012] 1. The present invention provides a method for detecting pan-cancer BRAF The characteristic gene set of mutation activity includes the genes shown in Table 1 ;

[0013] Table 1

[0014] gene NCBI ID number ADAM9 8754 CCND1 595 CLDN1 9076 CTDSPL 10217 DUSP6 1848 EPHA2 1969 ERRFI1 54206 ETV4 2118 ETV5 2119 FZD7 8324 GPRC5A 9052 IGFBP3 3486 ITGA3 3675 MTUS1 57509 PHLDA2 7262 PLEKHH1 57475 S100A16 140576 S100A6 6277 SEMA3A 10371 SLC1A1 6505 SPRY4 81848 TFAP2C 7022 TNFRSF12A 51330 TNFRSF21 27242 TPD52L1 7164

[0015] 2. The present invention provides the aforementioned characteristic gene set for detecting pan-cancer BRAF Application of fluorescent quantitative PCR kit in the preparation of mutation activity.

[0016] 3. The present invention provides a method for detecting pan-cancer BRAF The fluorescent quantitative PCR kit for mutation activity contains specific primers for each gene in the aforementioned characteristic gene set.

[0017] As one of the preferred technical solutions, the kit also contains an internal reference gene GAPDH and ACTB .

[0018] 4. The present invention provides the aforementioned characteristic gene set in BRAF Application in the preparation of mutation-related tumor detection kits.

[0019] 5. The present invention provides a BRAF A mutation-related tumor detection kit comprises specific primers for each gene in the aforementioned characteristic gene set.

[0020] As one of the preferred technical solutions, BRAF Mutation-associated tumors include, but are not limited to, colorectal cancer, melanoma, thyroid cancer, lung adenocarcinoma, and pancreatic cancer. Typing different tumor cohorts based on the expression of the described gene set can help identify subtypes with different BRAF pathway activity and be used to enrich for BRAF mutation signature subtypes.

[0021] 6. The present invention provides an SVM classifier constructed based on the aforementioned characteristic gene set.

[0022] 7. The present invention provides a method for constructing the aforementioned SVM classifier, the specific steps of which are as follows:

[0023] S1. First, remove genes with highly correlated expression in the aforementioned signature gene set and divide the normalized expression matrix of the BRAF mutation-associated tumor cohort into a training set and a test set in an 8:2 ratio.

[0024] S2. Gene importance was assessed based on its ability to discriminate samples in the training set. Genes were ranked using a random forest algorithm, and gene subsets of varying sizes were constructed incrementally based on this ranking.

[0025] S3. For each subset, construct an SVM classifier for evaluation on the test set, and obtain the best performing classifier for typing in the external cohort.

[0026] The beneficial effects of the present invention are:

[0027] The present invention discloses a method for detecting pan-cancer BRAF The characteristic gene set and its application of mutation activity, specifically, first construct a set of genes that can specifically reflect BRAF A signature gene set for mutation activity was developed, and based on this, a customized fluorescence quantitative PCR kit was developed specifically for evaluating the transcriptional activity status of the BRAF pathway in tumor tissue samples. This signature gene set includes the following genes: ADAM9, CCND1, CLDN1, CTDSPL, DUSP6, EPHA2, ERRFI1, ETV4, ETV5, FZD7, GPRC5A, IGFBP3, ITGA3, MTUS1, PHLDA2, PLEKHH1, S100A16, S100A6, SEMA3A, SLC1A1, SPRY4, TFAP2C, TNFRSF12A, TNFRSF21, TPD52L1 .

[0028] The characteristic gene set of the present invention combined with the SVM machine learning model can stably reproduce BRAF activity typing in multiple tumor types and cohorts, and reveal its potential clinical application value in predicting chemotherapy and targeted therapy responses. BRAF Mutation status, the characteristic gene set score of the present invention provides a more biologically functional tumor subtype classification method, providing strong support for accurate treatment decision-making. BRAF Mutation detection can only indicate "whether there is a mutation", while the characteristic gene set expression profile evaluation of the present invention can indicate "whether this pathway is truly activated" and can also predict survival, typing and drug sensitivity, which is of great clinical significance.

[0029] The advantages of the present invention are as follows:

[0030] 1. Transcendence BRAF Gene mutations themselves accurately reflect the true activation status of the BRAF signaling pathway

[0031] Tradition BRAF Mutation detection methods can only identify typical mutations (such as V600E, V600K), but a large number of BRAF Patients with wild-type mutations also experience pathway activation and respond significantly differently to treatment. By constructing a BRAF25 transcriptional expression profile model, this study can identify "functionally activated" BRAF pathway states, significantly improving detection sensitivity and clinical predictive power.

[0032] 2. Expanding the detection dimension from "gene mutation" to "transcriptional activity" to achieve higher-dimensional pathway judgment

[0033] This invention uses 25 core downstream target genes as activity markers to reflect the "transcriptional output" of the entire pathway. It can not only identify activation caused by mutations, but also capture pathway abnormalities caused by other mechanisms (such as MAPK upstream mutations, feedback regulation, etc.).

[0034] 3. Strong clinical accessibility: Based on the qPCR platform, no expensive high-throughput sequencing equipment is required

[0035] Compared to RNA-seq or Nanostring platforms, this method uses standard fluorescent quantitative PCR methods and pre-packaged array plates to complete detection. It is suitable for most hospitals and third-party testing institutions, with low barriers to promotion and low testing costs.

[0036] 4. High throughput, short time consumption, and high degree of standardization

[0037] Through a 96-well array plate design and internal reference calibration process, a complete sample can be tested within 2 hours, enabling the analysis of 25 gene expression profiles in a single run. This highly standardized process facilitates scalable and automated applications, making it suitable for high-throughput genotyping screening.

[0038] 5. Support intelligent classification output and visual report

[0039] The present invention is equipped with an SVM classification model, which can automatically output the typing results after inputting the original Ct value, and predict drug response and survival prognosis, making it easier for doctors to interpret the results and make clinical decisions.

[0040] 6. Potential for broad application expansion

[0041] In addition to colorectal cancer, the present invention can be applied to a variety of cancers including melanoma, thyroid cancer, lung adenocarcinoma, pancreatic cancer, etc. BRAF Mutation-related tumors, in a variety of BRAF mutation It shows good versatility and consistency in relevant indications.

[0042] The present invention can be widely applied to the following scenarios:

[0043] 1. Clinical molecular diagnosis

[0044] right BRAF Identification of functional pathway isoforms in patients with mutant or wild-type tumors;

[0045] Make up for tradition BRAF The limitations of mutation detection methods in prognosis prediction and drug selection;

[0046] Provide a classification basis for the use of BRAF inhibitors, MEK inhibitors, immunotherapy or chemotherapy.

[0047] 2. Tumor precision medication guidance

[0048] Applicable to common cancers such as colorectal cancer, melanoma, lung cancer, thyroid cancer, etc. BRAF mutation-associated tumors;

[0049] Can assist in identification BRAF a potential “functionally active” patient population among wild-type patients;

[0050] Used to predict tumor sensitivity to various treatment options (including chemotherapy, BRAF inhibitors, etc.).

[0051] 3. Tumor Prognosis Assessment

[0052] Risk stratification and prognosis prediction are performed based on the gene expression characteristics in the characteristic gene set of the present invention;

[0053] Provide a basis for formulating postoperative adjuvant treatment strategies and assessing the risk of recurrence.

[0054] 4. Scientific research applications and new drug development

[0055] It can be used in basic research to explore the activation mechanism of the BRAF pathway and its transcriptional regulatory network, and to determine the degree of activation of the BRAF pathway;

[0056] Provide a model reference for targeted drug research and development companies to screen suitable indication populations;

[0057] It can be used as one of the biomarkers for the enrollment of subjects in clinical trials.

[0058] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings, in which:

[0060] Figure 1 BRAF25 gene set identification and screening process;

[0061] Figure 2 Evaluation of the BRAF25 gene panel's typing ability in CCLE cell lines;

[0062] Figure 3 Design of a fluorescent quantitative PCR kit based on the BRAF25 gene;

[0063] Figure 4BRAF25 gene set for genotyping of autologous cell line PCR array data;

[0064] Figure 5 Comparison of overexpression in different tumor cells BRAFV600E and after Vemurafenib BRAF Changes in mutation activity scores;

[0065] Figure 6 Validation analysis of the BRAF25 gene set in the TCGA colon cancer cohort. (A) Distribution of BRAF25 activity scores in different BRAF expression subtypes (BAG-0 to BAG-3), showing that the BAG-3 group has a significantly higher activity score; (B) BRAF Mutation frequency; (C) Precision-Recall Curve (AUPRC) shows BRAF Mutation activity scores are important in differentiating BRAF the ability to discriminate between mutant and wild-type samples;

[0066] Figure 7 . Constructing an SVM classifier using the BRAF25 gene set (screening process);

[0067] Figure 8 BRAF25 gene set typing was used for prognostic analysis of chemotherapy and anti-BRAF targeted therapy, where A represents overall survival (OS) of colorectal cancer, B represents overall survival (OS) with BRAF inhibitor therapy, and C represents progression-free survival (PFS) with BRAF inhibitor therapy. DETAILED DESCRIPTION

[0068] The present invention will be further described below in conjunction with specific embodiments.

[0069] 1. BRAF Construction of a gene set characterizing mutational activity

[0070] The present invention integrates the following eight founding gene sets to capture transcriptional signals related to BRAF pathway activity:

[0071] BRAFV600K signature set: 309 genes that are transgenically expressed in mouse intestinal epithelial cells BRAFV600KAfter plasmid transfection, BRAF is significantly upregulated in the early stages of tumorigenesis. (Riemer P, Sreekumar A, Reinke S, Rad R, Schafer R, Sers C, Blaker H, Herrmann BG, Morkel M: Transgenic expression of oncogenic BRAF induces loss of stem cells in the mouse intestine, which is antagonized by beta-catenin activity. Oncogene 2015, 34(24):3164-3175.)

[0072] shBRAF signature set: This signature set consists of 211 genes whose expression is downregulated after doxycycline-induced BRAF knockdown in A375 cells and is compared with the untreated control group. (Hoeflich KP, Herter S, TienJ, Wong L, Berry L, Chan J, O'Brien C, Modrusan Z, Seshagiri S, Lackner M etal: Antitumor efficacy of the novel RAF inhibitor GDC-0879 is predicted by BRAFV600E mutational status and sustained extracellular signal-regulatedkinase / mitogen-activated protein kinase pathway suppression. Cancer Res 2009,69(7):3042-3051)

[0073] Three tissue-specific BRAF pathway signature sets (melanoma, thyroid cancer, colon cancer): These signature sets are based on the expression of BRAF genes driven by different tissue-specific promoters. BRAFV600E Transgenic mouse models were constructed to induce cytotoxicity in melanocytes, thyroid cells, and intestinal epithelial cells. BRAFV600E The expression is intended to clarify BRAFVRole in driving cancer development. (Rusinek D, Swierniak M, Chmielik E, Kowal M, Kowalska M, Cyplinska R,Czarniecka A, Piglowski W, Korfanty J, Chekan M et al: BRAFV600E-Associated Gene Expression Profile: Early Changes in the Transcriptome, Based on a Transgenic Mouse Model of Papillary Thyroid Carcinoma. PLoS One 2015, 10(12):e0143688.

[0074] Lu H, Liu S, Zhang G, Kwong LN, Zhu Y, Miller JP, Hu Y, Zhong W, ZengJ, Wu L et al: Oncogenic BRAF-Mediated Melanoma Cell Invasion. Cell Rep 2016,15(9):2012-2024.

[0075] Leach JDG, Vlahov N, Tsantoulis P, Ridgway RA, Flanagan DJ, Gilroy K, Sphyris N, Vazquez EG, Vincent DF, Faller WJ et al: Oncogenic BRAF, unrestrained by TGFbeta-receptor signaling, drives right-sided colonictumorigenesis. Nat Commun 2021, 12(1):3464.)

[0076] TCGA-BRAFV600E signature set: This signature set is based on the TCGA melanoma cohort ​The top 200 genes with the most significant differential expression between mutant and wild-type samples were constructed. (Yao K, Zhou E, Cheng C: A B-RafV600E gene signature for melanoma predicts prognosis and reveals sensitivity to targeted therapies. Cancer Med 2022, 11(4):1232-1243.)

[0077] Vemurafenib treatment signature set: Consists of 167 genes that reflect changes in transcriptome levels after treatment with the BRAF inhibitor vemurafenib. (Parmenter TJ, Kleinschmidt M, Kinross KM, Bond ST, LiJ, Kaadige MR, Rao A, Sheppard KE, Hugo W, Pupo GM et al: Response of BRAF-mutant melanoma to BRAF inhibition is mediated by a network of transcriptional regulators of glycolysis. Cancer Discov 2014, 4(4):423-433.)

[0078] MSigDB feature set: This feature set is the “REACTOME_SIGNALING_BY_MODERATE_KINASE_ACTIVITY_BRAF_MUTANTS” meta-feature set in the Molecular Signature Database (MSigDB https: / / www.gsea-msigdb.org / gsea / msig), which contains a group of 45 genes that represent genes related to a certain degree of kinase activity. ​ Mutant-related signaling pathways.

[0079] 2. Screening and identification of the core gene set BRAF25

[0080] (1) Screening of dominantly expressed genes: Among the eight feature sets mentioned above, we further screened for key genes that were dominantly expressed in tumor cells. Loess regression analysis was used to fit the log2 mean expression levels of all genes to the expression coefficient of variation (logCV), and genes with positive regression residuals and log2 mean expression values ​​greater than 6 were selected as candidate core feature genes.

[0081] (2) Evaluation of each signature gene set​ Capability of Mutant Cells: Based on the gene expression data from each feature set, tumor cell lines were hierarchically clustered (using the hclust function and the Ward.D2 algorithm in R) and divided into three groups: high-expression, low-expression, and unclassified. A chi-square test was then used to analyze the significance of each feature set in distinguishing between cell populations with high and low BRAF mutation rates to assess its classification ability.

[0082] (3) Construction of BRAF meta-feature set: The specific driver genes screened by expression fold difference analysis were summarized from the shBRAF feature set, TCGA-BRAFV600E feature set, melanoma and colon cancer BRAF pathway feature set, and Vemurafenib treatment feature set to form a BRAF meta-feature set containing 134 genes ( ​ A), providing a basis for subsequent analysis.

[0083] (4) RRA method and stepwise screening to obtain candidate BRAF feature sets: We used the Robust Rank Aggregation (RRA) method and the RobustRankAggreg package in R language to implement integrated analysis of multiple sets of data. This method is based on a theoretical model and integrates the expression-specific ranking results of 134 genes in tumor cells from different single-cell RNA sequencing analyses (including thyroid cancer, lung cancer, melanoma, and colon cancer) and assigns a significance score to each gene ( ​ Finally, a candidate gene set of 94 genes was obtained. We then performed a step-by-step screening of this gene set to determine the optimal feature set size. The specific method was to construct multiple subsets, starting with the gene with the highest significance score, and then incrementally add it to the set. At each step, the classification performance was evaluated to determine whether it could effectively distinguish the genes from the controls. ​ Mutation-positive samples (active group) and ​ Wild-type samples (silence group). Finally, the top 25 genes with the highest classification accuracy were selected as the candidate feature set and named BRAF25 ( ​ Middle C). BRAF25 classification performance was verified in CCLE tumor cell line data, and the results showed that: 53 ​ Among the mutant cell lines, 47 were correctly classified as BRAF high activity group, 6 were classified as unclassified group, and none were misclassified as low activity group. This result was statistically significant, indicating that BRAF25 can be used as a reliable signature gene set for judging BRAF pathway activity ( ​ ).

[0084] 3. Design of fluorescent quantitative PCR kit based on BRAF25 gene (PCR chip)

[0085] (1) Gene sequence acquisition: Download the RefSeq mRNA sequence of the target gene from the NCBI or Ensembl database, including 25 characteristic genes related to the BRAF signaling pathway and 2 commonly used internal reference genes ( ​ and ​ ), providing an accurate template for primer design.

[0086] (2) Primer design: Specific primers for each gene were designed using OLIGO 7 software to ensure high amplification efficiency, low probability of dimer formation, and to meet the experimental requirements of fluorescence quantitative PCR (Table 2).

[0087] Table 2

[0088] ​ ​ ​ ​ ​ ​ 8754 ​ ​ 90 ​ 595 ​ ​ 135 ​ 9076 ​ ​ 145 ​ 10217 ​ ​ 166 ​ 1848 ​ ​ 153 ​ 1969 ​ ​ 108 ​ 54206 ​ ​ 156 ​ 2118 ​ ​ 125 ​ 2119 CAGTCAACTTCAAGAGGCTTGG TGCTCATGGCTACAAGACGAC 168 FZD7 8324 CAGACGTGCAAGAGCTATGC ACGATCATGGTCATCAGGTACT 104 GPRC5A 9052 CATGCTCACTCTCCCGATCC [[ID= 168 ​ 3486 ​ ​ 93 ​ 3675 ​ ​ 93 ​ 57509 ​ ​ 94 ​ 7262 ​ ​ 80 ​ 57475 ​ ​ 155 ​ 140576 ​ ​ 93 ​ 6277 ​ ​ 84 ​ 10371 ​ ​ 77 ​ 6505 ​ ​ 94 ​ 81848 ​ ​ 143 ​ 7022 ​ ​ 112 ​ 51330 ​ ​ 97 ​ 27242 ​ ​ 103 ​ 7164 ​ ​ 118 ​ 2597 ​ ​ 106 ​ 60 ​ ​ 72

[0089] (3) Fluorescence quantitative PCR kit composition:

[0090] The kit includes 2× qPCR Master Mix, custom primer pairs, ROX reference dye, RNase-free water, and standard operating instructions, enabling one-click, high-throughput assessment of BRAF pathway activity.

[0091] 96-well PCR chip plate layout Each plate has 3 sets of technical replicates (columns 1–4, 5–8, 9–12), each set fully covers 27 genes (25 BRAF signaling pathway related genes + ​ + ​ ), arranged in rows (A–H), with three technical replicates per well to improve the statistical robustness and repeatability of the data ( ​ ).

[0092] (4) Operation process:

[0093] (4-1) Sample preparation: Use Trizol or a commercial RNA extraction kit to extract total RNA from tissues / cells. The A260 / A280 ratio should be 1.8-2.0, and the total RNA concentration should be greater than 50 ng / µL.

[0094] (4-2) cDNA synthesis and reaction system configuration:

[0095] Transcribe 1 µg of total RNA into cDNA using a reverse transcription kit. Prepare 900 µL of cDNA and mix, then add 9 µL of the prepared mixture to each well: 5 µL of 2× qPCR Master Mix, 1 µL of cDNA template, 2.8 µL of nuclease-free water, and 0.2 µL of ROX reference dye.

[0096] (4-3) The amplification was performed in a Bio-Rad CFX96 system with the following program settings: initial denaturation at 95°C for 10 min, followed by 40 amplification cycles, each cycle consisting of denaturation at 95°C for 5 s and annealing / extension at 60°C for 30 s, while real-time fluorescence signal acquisition was performed.

[0097] (5) Data analysis: The ΔCt method was used to evaluate the expression level: ΔCt = Ct (target gene) − Ct (reference gene) ​ or ​ Then the relative expression was calculated and log2 transformed. The average log2 expression value of 25 BRAF pathway genes was taken as the “ ​ Mutation activity score".

[0098] 4. Functional validation of the BRAF25 signature gene set

[0099] (1) Cell line PCR chip validation: More than 10 tumor cell lines from different organs (covering BRAF mutant and wild-type) were selected and the BRAF25 gene expression profile was detected using a customized PCR chip. Hierarchical clustering analysis was performed using the hclust function in R language and the Ward.D2 clustering algorithm. The results showed that the gene set can effectively enrich and distinguish BRAF mutant cell lines ( ​ ).

[0100] (2) ​ Overexpression and BRAF inhibitor treatment validation: ​ In mutant cell lines, ​ The results showed that the BRAF inhibitor Vemurafenib was used to treat the BRAF gene overexpression in the treated group. ​ The mutation activity score decreased significantly, while the score of the overexpression group increased significantly, both of which were statistically significant ( ​ ), further verified the reliability and sensitivity of the BRAF25 scoring system in reflecting BRAF signaling activity.

[0101] (3) TCGA colon cancer large sample data validation: To further evaluate the applicability of the BRAF25 signature gene set in clinical samples, the applicant performed a hierarchical cluster analysis on the standardized expression matrix of BRAF25 based on the transcriptome data of the TCGA colon cancer (COAD) cohort, using the Ward.D2 clustering method. According to the average expression level of the BRAF25 gene set in each cluster category, all samples were divided into four expression subtypes, named BAG-0 to BAG-3, where BAG-3 represents the BRAF pathway high activity group ( ​ It is worth noting that in the BAG-3 group ​The mutation frequency increased significantly, reaching 37.8%, which was significantly higher than that of other groups ( ​ Furthermore, we divided TCGA samples into high expression group and low expression group according to BRAF25 activity score to evaluate its ability to distinguish ​ Considering that BRAF mutation-positive samples account for only about 10% of colorectal cancer samples and the ratio of positive and negative samples is seriously uneven, we used the PRROC package to draw the precision-recall curve and calculated the area under the curve (AUPRC) to obtain a more accurate evaluation index. The analysis results showed that although ​ The mutation rate is low, and the BRAF25 score performs well in distinguishing mutation and non-mutation samples, with an AUPRC of 0.25 ( ​ The results in middle C were better than random prediction, which verified that the gene set had a certain ability to identify the activity status of BRAF mutations.

[0102] 5. Using machine learning methods to build classifiers to expand the application value of the BRAF25 gene set

[0103] (1) Construction and validation of SVM classifier: To enhance the application of BRAF25 gene set in large cohort data, we first removed genes with highly correlated expression in the BRAF25 feature set and divided the standardized expression matrix in the TCGA colon cancer (COAD) cohort into a training set and a test set in an 8:2 ratio. Subsequently, the random forest algorithm was used to rank the remaining genes, and the importance of genes was evaluated based on their ability to distinguish samples in the training set, and gene subsets of different sizes were constructed accordingly. For each subset, a support vector machine (SVM) classification model was gradually constructed to identify the BRAF high activity expression subtype BAG-3. The model evaluation results showed that the classifier using all 25 genes achieved the best performance in terms of sensitivity and specificity ( ​ ), and the model can stably reproduce the BAG-3 subtype and significantly enrich for BRAF mutant tumors, indicating that it has good robustness and generalization ability.

[0104] (2) Application of the SVM classifier model: To further evaluate the potential of the BRAF25 classifier in clinical practice, we applied the SVM model to the Laetitia colorectal cancer cohort, which received standard first-line adjuvant chemotherapy and had complete prognostic follow-up information. After classification by the model, it was found that the overall survival (OS) of patients with BAG-3 subtype was significantly shorter than that of other subtypes, especially the difference between the BAG-0 and BAG-2 groups was statistically significant ( ​In multivariate Cox regression analysis incorporating BRAF mutation status and BAG subtype, BAG subtype was identified as an independent adverse prognostic factor.

[0105] We further evaluated whether the BRAF25 classifier could be used to predict the response to targeted therapy. In three independent external cohorts of melanoma patients treated with BRAF inhibitors, the BAG subtype distribution was successfully replicated. The results showed that although most patients with BAG-3 subtype melanoma showed a good response to BRAF inhibitor treatment in the early stage, the overall survival (OS, ​ Middle B) and disease-free survival (PFS, ​ C) were significantly inferior to other subtypes, suggesting that this subtype may be associated with acquired drug resistance mechanisms.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should all be included in the scope of the claims of the present invention.

Claims

1. Used for pan-cancer detection BRAF Specific primers for a set of characteristic genes of mutation activity, characterized in that: As shown in Table 2, the nucleotide sequences are shown in SEQ ID NOs. 1 to 50; Table 2 。 2. The specific primers according to claim 1 are used in the preparation of a pan-cancer detection BRAF Application of the kit for detecting mutagenic activity.

3. The use according to claim 2, characterized in that The specific primers described in claim 1 are used in the preparation of the detection BRAF Application of a kit for treating mutation-related tumors, wherein the BRAF The mutation-associated tumors were colorectal cancer, melanoma, thyroid cancer, or lung adenocarcinoma.

4. A pan-cancer detection method BRAF A fluorescent quantitative PCR kit for detecting mutation activity, characterized in that: Comprising the specific primer according to claim 1.

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