Gene combination for detecting hemangioma and vascular malformation as well as detection kit and application thereof

Abstract

The invention provides a gene detection kit for molecular diagnosis of hemangioma and vascular malformation and application. Specifically, the invention provides a gene combination for determining molecular diagnosis of hemangioma and vascular malformation, and based on NGS panel + RNAseq gene sequencing, the gene combination for molecular diagnosis of hemangioma and vascular malformation provided by the invention can be applied to all molecular diagnosis and liquid biopsy related to hemangioma and vascular malformation. The correlation between mutation sites and abundance and disease phenotypes is disclosed, so that the method has a relatively great clinical popularization and application prospect.

Description

Technical Field

[0001] This invention relates to the field of biomedicine, specifically to a gene combination for detecting hemangiomas and vascular malformations, a detection kit for it, and its uses. Background Technology

[0002] Hemangiomas and vascular malformations are common childhood diseases, with an incidence rate of 2%–10% in newborns. Initially, hemangiomas / vascular malformations were named after foods based on their shape, color, and resemblance to the tumor, such as "strawberry hemangioma," "cherry hemangioma," "port-wine stain," and "salmon patch." It wasn't until 1862 that Rudolf Virchow, the father of cellular pathology, classified vascular diseases into capillary hemangiomas, cavernous hemangiomas, and racemose hemangiomas based on the morphological differences in the luminal structures contained within the lesions, collectively termed "angiomas." Traditional classifications, primarily based on morphological characteristics, are visually appealing and easily understood by doctors and patients, but they fail to reflect the true nature of the lesions. Therefore, traditional classifications hinder the selection of treatment methods and the accurate assessment of disease prognosis, negatively impacting patient treatment and long-term management. In 1996, the International Society for the Study of Vascular Diseases (ISSVA) developed a more comprehensive classification system, which has become the internationally recognized basis for classification. In order to keep pace with the progress in biological and genetic research on vascular malformations and tumors in recent years, the 22nd ISSVA in 2018 expanded and updated the classification based on the 2014 edition.

[0003] Vascular malformations (VMs) are numerous, numbering in the hundreds, and some subtypes present with similar symptoms. However, they are entirely different diseases, so accurate classification is essential before targeted treatment. Classification is the foundation of treatment. Although the internationally recognized ISSVA classification serves as a clinical guideline, some vascular lesions and complex subtypes of vascular malformations remain unclassified and cannot be directly diagnosed using the guidelines. Therefore, identifying more accurate predictive factors that aid in the diagnosis of vascular malformations is crucial.

[0004] Therefore, there is an urgent need in this field to develop a gene combination and application for the molecular diagnosis of hemangiomas and vascular malformations, to reveal the correlation between mutation sites and abundance and disease phenotypes, for molecular diagnosis and in vitro detection of hemangiomas and vascular malformations. Summary of the Invention

[0005] The purpose of this invention is to provide a gene combination and its application for the molecular diagnosis of hemangiomas and vascular malformations, revealing the correlation between mutation sites and abundance and disease phenotypes, for molecular diagnosis and in vitro detection of hemangiomas and vascular malformations.

[0006] In a first aspect, the present invention provides a gene combination for detecting hemangiomas and vascular malformations, said gene combination comprising the following genes: BRCA, HSPG2, FOS, GOPC, ROS1, AMER1, MML3, BRD4, ACVRL1, ELMO2, GJC2, KDR, NPM1, TEK, ADAMTS3, ENG, GLMN, KIF11, NRAS, TFE3, AGGF1, EPHB4, GNA11, KRAS, PDCD10, TNFRSF11A, AKT1, FAT4, GNA14, KRIT1, PIEZ. O1, TREM2, ANTXR1, FLT4, GNAQ, MAP2K1, PIK3CA, TSC1, BAD, FOS, HGF, MAP3K3, PTEN, TSC2, BRAF, FOSB, HRAS, MET, PTPN14, VEGFC, CA MTA1, FOXC2, IDH1, MTOR, RASA1, CCBE1, GATA2, IDH2, MYC, SMAD4, CCM2, GDF2, IKBKG, NF1, SOX18, CELSR1, GJA1, ITGA9, NF2 and STAMBP.

[0007] In another preferred embodiment, the gene combination further includes the following genes: EEF1DP3 / FRY, FOS / HBG2, CTSC / RAB38, GOPC / ROS1, HSPG2 / FOS, RNF213 / SLC26A11, SBDS, HAVCR, MLL3, RECQL5, ALK, APOD, AR, AXLCASC15, CCND1, CDH11, CDKN1C, CLU, FGFR3, GU2, GL3, GPC3, H19, IGF1, IGF1R, IGF2, IGFBP7, I... TGA3, KCNQ1OT1, LOX, MPL, MYCN, WT1, EZH2, GPS2, BLOC1S4, BPTF, BTBD2, C170r103, FOXO1, GAS1, GDF11, IRF2BPL, TTGA3, KLH DC10, MUC9, MYO6, SEC22C, SHC2, IP5B2, UTF1, ZNRF2, CSF1R, CXCL2, DLG2, ERBB3, FGF2, FGFR2, GLI2, GLI3, KIF1B, NMB, NOTCH2 , PRKCG, PTCH2, RUNX2, SIX1, SIX2, SMOC1, TNC, ARIDIA, C11orf95, CARMI, CASZI, CDC42EPS, CHKA, COPZ2, CTC1, ELMSANI, GAT AD1, IQSEC1, MAZ, MBD2, MEX3C, MEX3D, MUC6, NACAD, PLEKHH3, PPPIR12C, SH3BP2, SOX21, TAF4, TPSB2, YBX3, ZCCHC3, LPK3, BA AP3, BLOC154, CABLES1, CAPNS1, CDC27, COQ7, FBXL16, GSK3A, ID2, IL17D, INO80E, KCNF1, KCTD2, KDM1A, LLGL1, MTSS1L, NDUF B11, NRXN2, PDCD7, PGRMC2, POU3F3, PWWP2A, RAMP2, SCRT2, SHANK1, SLC25A43, SLC9A7, SRF, TMEM102, TMEM14S, USP43, and ZC3H4.

[0008] In another preferred embodiment, the gene combination is used to detect hemangiomas and vascular malformations by means of NGS panel sequencing, whole transcriptome sequencing (RNAseq), whole exome sequencing (WES), or a combination thereof.

[0009] In another preferred embodiment, the gene combination is a detection target for pathogenic genes of hemangiomas and vascular malformations, detected by NGS panel sequencing and whole transcriptome sequencing (RNAseq).

[0010] In another preferred embodiment, the gene combination is a detection target gene for detecting pathogenic genes of hemangiomas and vascular malformations by NGS panel sequencing, whole transcriptome sequencing (RNAseq), and whole exome sequencing (WES).

[0011] In another preferred embodiment, the target genes for NGS panel sequencing to detect pathogenic genes of hemangiomas and vascular malformations are selected from the following group: BRCA, HSPG2, FOS, GOPC, ROS1, AMER1, MML3, BRD4, ACVRL1, ELMO2, GJC2, KDR, NPM1, TEK, ADAMTS3, ENG, GLMN, KIF11, NRAS, TFE3, AGGF1, EPHB4, GNA11, KRAS, PDCD10, TNFRSF11A, AKT1, FAT4, GNA14, KRIT1, PIEZO1, TREM2, ANTXR1, FLT4, GNAQ, MAP2K1, PIK3CA, TS C1, BAD, FOS, HGF, MAP3K3, PTEN, TSC2, BRAF, FOSB, HRAS, MET, PTPN14, VEGFC, CAMTA1, FOXC2, IDH1, MTOR, RASA1, CCBE1, GATA2, IDH2, MYC, SMAD4, CCM 2. GDF2, IKBKG, NF1, SOX18, CELSR1, GJA1, ITGA9, NF2, STAMBP, EEF1DP3 / FRY, FOS / HBG2, CTSC / RAB38, GOPC / ROS1, HSPG2 / FOS, RNF213 / SLC26A11, SBDS , HAVCR, MLL3, RECQL5, ALK, APOD, AR, AXLCASC15, CCND1, CDH11, CDKN1C, CLU, FGFR3, GU2, GL3, GPC3, H19, IGF1, IGF1R, IGF2, IGFBP7, ITGA3, KCNQ1OT 1. LOX, MPL, MYCN, WT1, EZH2, GPS2, BLOC1S4, BPTF, BTBD2, C170r103, FOXO1, GAS1, GDF11, IRF2BPL, TTGA3, KLHDC10, MUC9, MYO6, SEC22C, SHC2, IP5B2, UTF1, ZNRF2, CSF1R, CXCL2, DLG2, ERBB3, FGF2, FGFR2, GLI2, GLI3, KIF1B, NMB, NOTCH2, PRKCG, PTCH2, RUNX2, SIX1, SIX2, SMOC1, TNC, ARIDIA, C11orf 95. CARMI, CASZI, CDC42EPS, CHKA, COPZ2, CTC1, ELMSANI, GATAD1, IQSEC1, MAZ, MBD2, MEX3C, MEX3D, MUC6, NACAD, PLEKHH3, PPPIR12C, SH3BP2, SOX21,TAF4, TPSB2, YBX3, ZCCHC3, LPK3, BAAP3, BLOC154, CABLES1, CAPNS1, CDC27, COQ7, FBXL16, GSK3A, ID2, IL17D, INO80E, KCNF1, KCTD2, KDM1A, LL GL1, MTSS1L, NDUFB11, NRXN2, PDCD7, PGRMC2, POU3F3, PWWP2A, RAMP2, SCRT2, SHANK1, SLC25A43, SLC9A7, SRF, TMEM102, TMEM14S, USP43, and ZC3H4. ,

[0012] In another preferred embodiment, the target genes for detecting pathogenic genes of hemangiomas and vascular malformations using whole transcriptome sequencing (RNAseq) are selected from the mRNA of all genes in the human genome, approximately 21,000 genes. This provides full transcriptome coverage, 15G of sequencing data, and comprehensive coverage of common fusion / translocation / alternative splicing-related genes.

[0013] In another preferred embodiment, the target genes for detecting hemangioma and vascular malformation pathogenic genes in whole exon sequencing (WES) are selected from all exons of the entire human genome, approximately 21,000 genes.

[0014] In another preferred embodiment, the NGS is Next Generation Sequencing.

[0015] In another preferred embodiment, the sequencing depth of the NGS panel is 20000X.

[0016] In another preferred embodiment, the sequencing depth of the RNAseq is 150X.

[0017] In another preferred embodiment, the whole exome sequencing includes peripheral blood genome exome sequencing (100X).

[0018] In another preferred embodiment, the sequencing depth of the whole exome sequencing is 600X tissue.

[0019] In another preferred embodiment, the gene includes a wild-type or mutant gene.

[0020] In another preferred embodiment, all the genes are derived from human genes.

[0021] In another preferred embodiment, the genes are all derived from children's genes.

[0022] In another preferred embodiment, in the lesion tissue of patients with hemangiomas and vascular malformations, the genes in the said gene combination have a mutation abundance of ≥0.5% compared with the human standard reference genome.

[0023] In another preferred embodiment, the gene combination is obtained by screening using the following method: sequencing is used to determine the gene sequence of different samples, and the standard for determining the variation is to compare the sample sequencing results with the human standard reference gene combination. If the gene locus sequencing results are different from the human standard reference gene combination, the mutation with a mutation abundance of more than 0.5% is a positive mutation, thereby identifying it as a high-risk pathogenic gene.

[0024] In another preferred embodiment, the sample is PROS lesion tissue or suspected PROS lesion tissue.

[0025] In another preferred embodiment, the sequencing method is selected from the group consisting of NGS panel sequencing, RNAseq sequencing, whole exome sequencing, or combinations thereof.

[0026] In another preferred embodiment, the sequencing results are processed by dedicated software to reduce noise, remove false positives, perform automated comparisons, or use other artificial intelligence techniques, and the abundance of each hotspot mutation site can be directly displayed.

[0027] In another preferred embodiment, the human standard reference gene combination is a peripheral blood gene combination.

[0028] In another preferred embodiment, the human standard reference gene combination is a self-control group, which consists of the gene combination of the child's own peripheral blood.

[0029] In another preferred embodiment, the mutations include germline mutations and somatic mutations.

[0030] In a second aspect of the invention, the use of gene combinations and / or their detection reagents as described in the first aspect of the invention in the preparation of a kit for detecting hemangiomas and vascular malformations is provided.

[0031] In another preferred embodiment, the kit includes instructions for use, which state:

[0032] If high expression or mutations of genes selected from the following groups are detected, it suggests that the patient has hemangioma and vascular malformation: ACVRL1, ELMO2, GJC2, KDR, NPM1, TEK, ADAMTS3, ENG, GLMN, KIF11, NRAS, TFE3, AGGF1, EPHB4, GNA11, KRAS, PDCD10, TNFRSF11A, AKT1, FAT4, GNA14, KRIT1, PIEZO1, TREM2, ANTXR1, FLT4, GNAQ, MAP2K1, PIK3CA, TSC1, BAD, FOS, HGF, MAP3K3, PTEN, TSC2, BRAF, FOSB, HRAS, MET, PTPN14, VEGFC, CAMTA1, FOXC2, ID H1, MTOR, RASA1, CCBE1, GATA2, IDH2, MYC, SMAD4, CCM2, GDF2, IKBKG, NF1, SOX18, CELSR1, GJA1, ITGA9, NF2 and STAMBP.

[0033] In another preferred embodiment, the instructions for the kit also state:

[0034] (1) If high expression or mutation of genes selected from the following groups is detected, it suggests that the patient has hemangioma and vascular malformation: BRCA, HSPG2, FOS, GOPC, ROS1, AMER1, MML3, BRD4, ACVRL1, ELMO2, GJC2, KDR, NPM1, TEK, ADAMTS3, ENG, GLMN, KIF11, NRAS, TFE3, AGGF1, EPHB4, GNA11, KRAS, PDCD10, TNFRSF11A, AKT1, FAT4, GNA14, KRIT1, PIEZO1, TREM2, ANTXR1, FLT4, GNAQ, MAP2K1, PIK3CA, TSC1, BAD, FOS, HGF, MAP3K3, PTEN, TSC2, BRAF, FOSB, HRAS, MET, PTPN14, VEGFC, CAMTA1, FOXC2, IDH1, MTOR, RASA1, CCBE1, GATA2, IDH2, MYC, SMAD4, CCM 2. GDF2, IKBKG, NF1, SOX18, CELSR1, GJA1, ITGA9, NF2, STAMBP, SBDS, HAVCR, MLL3, RECQL5, ALK, APOD, AR, AXLCASC15, CCND1, CDH11, CDKN1C, CLU, FGFR3 , GU2, GL3, GPC3, H19, IGF1, IGF1R, IGF2, IGFBP7, ITGA3, KCNQ1OT1, LOX, MPL, MYCN, WT1, BLOC1S4, BPTF, BTBD2, C170r103, FOXO1, GAS1, GDF11, IRF2BPL , TTGA3, KLHDC10, MUC9, MYO6, SEC22C, SHC2, IP5B2, UTF1, ZNRF2, CSF1R, CXCL2, DLG2, ERBB3, FGF2, FGFR2, GLI2, GLI3, KIF1B, NMB, NOTCH2, PRKCG, PTCH 2. RUNX2, SIX1, SIX2, SMOC1, TNC, ARIDIA, C11orf95, CARMI, CASZI, CDC42EPS, CHKA, COPZ2, CTC1, ELMSANI, GATAD1, IQSEC1, MAZ, MBD2, MEX3C, MEX3D, M UC6, NACAD, PLEKHH3, PPPIR12C, SH3BP2, SOX21, TAF4, TPSB2, YBX3, ZCCHC3, LPK3, BAAP3, BLOC154, CABLES1, CAPNS1, CDC27, COQ7, FBXL16, GSK3A, ID2,IL17D, INO80E, KCNF1, KCTD2, KDM1A, LLGL1, MTSS1L, NDUFB11, NRXN2, PDCD7, PGRMC2, POU3F 3. PWWP2A, RAMP2, SCRT2, SHANK1, SLC25A43, SLC9A7, SRF, TMEM102, TMEM14S, USP43 and ZC3H4;,

[0035] (2) If low expression or mutation of a gene selected from the following groups is detected, it indicates that the patient has hemangioma and vascular malformation: EZH2 or GPS2;

[0036] (3) If a fusion gene selected from the following groups is detected, it indicates that the patient has hemangioma and vascular malformation: EEF1DP3 / FRY, FOS / HBG2, CTSC / RAB38, GOPC / ROS1, HSPG2 / FOS, RNF213 / SLC26A11.

[0037] In another preferred embodiment, the detection reagent is a detection reagent suitable for sequencing selected from the group consisting of NGS panel sequencing, RNAseq sequencing, whole exome sequencing, or a combination thereof.

[0038] In another preferred embodiment, the mutation includes single-point mutation, multi-point mutation, gene fusion, or a combination thereof.

[0039] In a third aspect of the invention, a reagent combination is provided for detecting the expression level of genes in the gene combination described in the first aspect of the invention.

[0040] In another preferred embodiment, the reagent is a reagent for detecting the amount of RNA, mRNA, or cDNA complementary to the mRNA transcribed from the gene.

[0041] In another preferred embodiment, the reagent is a primer, a probe, or a combination thereof.

[0042] In another preferred embodiment, the reagent is a detection reagent suitable for sequencing selected from the group consisting of NGS panel sequencing, RNAseq sequencing, whole exome sequencing, or a combination thereof.

[0043] In a fourth aspect of the invention, a product for molecular diagnosis of hemangiomas and vascular malformations is provided, comprising the reagent combination described in the third aspect of the invention.

[0044] In another preferred embodiment, the product is also used to reveal the correlation between mutation sites and abundance of hemangioma-related molecules and disease phenotype.

[0045] In another preferred embodiment, the product is in the form of an in vitro diagnostic product.

[0046] In another preferred embodiment, the product is in the form of a diagnostic kit.

[0047] In another preferred embodiment, the product is a next-generation sequencing kit, a real-time quantitative PCR detection kit, or a gene chip.

[0048] In a fifth aspect of the invention, an apparatus is provided for assessing the genetic risk of hemangioma and vascular malformations in a subject by detecting gene combinations described in the first aspect of the invention, the apparatus comprising:

[0049] S1) Sequencing module, used to sequence genes from samples from subjects to obtain sequencing results;

[0050] S2) Analysis module, used to analyze mutation information of samples;

[0051] S3) The comparison module compares the mutation information with the gene combination described in the first aspect of the present invention to determine the subject's genetic risk of hemangioma and vascular malformation.

[0052] S4) Output module, which is used to output the judgment result.

[0053] In another preferred embodiment, the sequencing module performs sequencing using a sequencing method selected from the group consisting of:

[0054] NGS panel sequencing, whole transcriptome sequencing (RNAseq), whole exome sequencing (WES), or a combination thereof.

[0055] In another preferred embodiment, the bioinformatics analysis in the analysis module includes: using dedicated software to perform noise reduction, artifact removal, automated alignment, and other artificial intelligence processing on the sequencing results, and directly displaying the detection abundance of each hotspot mutation site.

[0056] It should be understood that, within the scope of this invention, the above-described technical features of this invention and the technical features specifically described below (such as in the embodiments) can be combined with each other to form new or preferred technical solutions. Due to space limitations, they will not be described in detail here. Attached Figure Description

[0057] Figure 1The results of sequential product testing for hemangiomas and vascular malformations are shown. Among 13 different patients, the positive rate of pathogenic genes detected by NGS panel sequencing was 61.5% (8 / 13), and the positive rate detected by NGS panel sequencing and RNA seq sequencing was 69.2% (9 / 13). Three additional samples were positive for fusion verification, further increasing the positive rate of pathogenic genes to 92.3% (12 / 13). WES did not find any clearly identified pathogenic genes compared to the NGS panel, indicating that the NGS panel we chose is very comprehensive. Specifically, somatic somatic mutations were detected using tissue specimens obtained from surgical biopsies, including NGS, WES, and RNA seq; fusion gene detection was performed using whole transcriptome sequencing (RNA seq) to sequence all human genome mRNAs; and germline germline mutations were detected using corresponding gene tests in the control group (patient's own peripheral blood leukocytes, germline control sample 100X) to perform germline variation detection and analysis, ensuring the accuracy of the mutation source and effective analysis of hereditary tumors. Other refers to non-pathogenic gene mutations, which may be associated mutations or unintentional mutations.

[0058] Figure 2 The results shown are from the sequential product testing for hemangioma and vascular malformation in patient sample number 1; including a summary of variant results and results of mRNA detection of related fusion genes, with the fusion gene being EEF1DP3 / FRY.

[0059] Figure 3 This display shows an overview of the whole-exome sequencing results for patient sample number 1—somatic variants. The exon mutations detected by whole-exome WES were all exon mutations occurring in genes within the genome; the vast majority were missense mutations, with only a few being frameshift and non-frameshift mutations. WES did not identify any clearly causative genes compared to the NGS panel.

[0060] Figure 4 The results displayed are from the sequential product testing for hemangioma and vascular malformation in patient sample number 8; including a summary of variant results and mRNA detection results related to fusion genes, with the fusion gene being HSPG2 / FOS.

[0061] Figure 5 This shows the analysis of variant sites and diagnostic results of the disease-related gene (BRD4) in patient sample number 8.

[0062] Figure 6This display shows an overview of the whole-exome sequencing results for patient sample number 8—somatic variants. The exon mutations detected by whole-exome WES were all exon mutations occurring in genes within the genome; the vast majority were missense mutations, with only a few being frameshift and non-frameshift mutations. WES did not identify any clearly causative genes compared to the NGS panel.

[0063] Figure 7 The results shown are from the mRNA detection of the fusion gene in patient sample number 9, which is GOPC / ROS1.

[0064] Figure 8 This shows the analysis of variant sites and diagnostic results of the gene (GJA1) that may be related to the disease in the patient sample with serial number 9.

[0065] Figure 9 This shows an overview of the whole-exome sequencing results for patient sample number 9—somatic variants. The exon mutations detected by whole-exome WES were all exon mutations occurring in genes within the genome, and the vast majority were missense mutations. WES did not identify any specific pathogenic genes compared to the NGS panel.

[0066] Figure 10 The graph shows the distribution (A) and mutation abundance (B) of the PIK3CA and TEK gene loci.

[0067] Taking p.E545K as an example, p.E545K refers to the mutation of glutamic acid Cys at position 545 of the PIK3CA protein amino acid sequence to lysine Lys. Other mutation sites are analogous and will not be described in detail here.

[0068] Figure 11 The image shows the results of patient A's 62-panel WES RNAseq test, along with its diagnosis, prognosis, and treatment outcomes.

[0069] Figure 12 The graph shows the percentage distribution of PIK3CA sites. Detailed Implementation

[0070] Through extensive and in-depth research, the inventors have developed a gene combination and application for the molecular diagnosis of hemangiomas and vascular malformations. Using lesion tissue from affected children as test samples, NGS panel sequencing of somatic mutation specimens can be performed to assess changes in gene mutation abundance. The NGS panel sequencing of this invention can perform gene detection on all hemangioma and vascular malformation lesion tissues, with a coverage of over 95% and a positive rate of approximately 80%. The NGS panel sequencing of this invention has high sensitivity, with a sequencing depth of up to 20,000X, and can detect gene mutations with an abundance of only 0.5%.

[0071] The NGS panel sequencing of this invention has high sensitivity and a sequencing depth of up to 20,000X, enabling pg-level gene mutation detection. This invention combines NGS panel sequencing with whole transcriptome sequencing (RNA-seq), which further improves the positive rate of detection results, providing a basis for targeted drug treatment and discontinuation criteria for hemangiomas and vascular malformations. Furthermore, this invention uses peripheral blood whole-exome sequencing (WES) at a depth of 100X to determine whether the mutation is germline or somatic.

[0072] Implementation scheme of the present invention:

[0073] This invention discloses a gene combination and its application for the molecular diagnosis of hemangiomas and vascular malformations, including a combination of all pathogenic genes for hemangiomas and vascular malformations, an NGS panel + RNAseq gene sequencing scheme, an automated analysis scheme, and the scope of diseases to which it is applied. The combination of all pathogenic genes for hemangiomas and vascular malformations, and the acquisition and processing of the lesion specimens, are constructed after specific optimization for gene detection. The self-control group consists of the genome of the child's own peripheral blood. The design of the NGS panel + RNAseq primers for the molecular diagnosis of hemangiomas and vascular malformations is based on a combination of all currently known pathogenic genes for hemangiomas and vascular malformations, after specific optimization and has been validated. The NGS panel + RNAseq sequencing scheme has an NGS panel sequencing depth of 20000X, an RNAseq sequencing depth of 150X, and a peripheral blood genome whole-exome sequencing (WES) depth of 100X. The automated analysis and processing of the sequencing results is performed by the NGS panel++ RNAseq sequencing-specific analysis software. Using machine learning algorithms, the sequencing results undergo artificial intelligence processing such as noise reduction, artifact removal, and automated alignment. This directly displays the detection abundance of each hotspot mutation site, allowing for the exploration of precise diagnostic molecular markers. The gene combination and disease range of this hemangioma / vascular malformation molecular diagnostic approach can be applied to all hemangioma / vascular malformation-related molecular diagnostics and liquid biopsies, revealing the correlation between mutation sites and abundance and disease phenotypes. Therefore, it has significant potential for clinical application.

[0074] the term

[0075] Unless otherwise defined, 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 pertains.

[0076] As used herein, the terms “genome” and “gene combination” are used interchangeably and both refer to the gene combination described in the first aspect of this invention.

[0077] As used in this article, the terms "62 panel" and "NGS panel" are used interchangeably.

[0078] Hemangioma and vascular malformation

[0079] Hemangiomas and vascular malformations are common childhood diseases, with an incidence rate of 2%–10% in newborns. Initially, based on the similarity of the tumor's shape and color to food, hemangiomas / vascular malformations were named after foods, such as "strawberry hemangioma," "cherry hemangioma," "port-wine stain," and "salmon patch." It wasn't until 1862 that Rudolf Virchow, the father of cytopathology, classified vascular diseases into capillary hemangiomas, cavernous hemangiomas, and racemose hemangiomas based on the morphological differences in the luminal structures contained within the lesions, collectively referring to them as "angiomas." In 1996, the International Society for the Study of Vascular Diseases (ISSVA) developed a more comprehensive classification system, which became the internationally recognized classification basis. To keep pace with recent advances in the biology and genetics of vascular malformations and tumors, the 22nd ISSVA in 2018 expanded and updated the classification based on the 2014 version.

[0080] Vascular malformations (VMs) are numerous, numbering in the hundreds, and some subtypes present with similar symptoms. However, they are entirely different diseases, so accurate classification is essential before targeted treatment. Classification is the foundation of treatment. Although the internationally recognized ISSVA classification serves as a clinical guideline, some vascular lesions and complex subtypes of vascular malformations remain unclassified and cannot be directly diagnosed using the guidelines. Therefore, identifying more accurate predictive factors that aid in the diagnosis of vascular malformations is crucial.

[0081] Mutation abundance

[0082] Mutation abundance refers to the relative proportion of mutant alleles among all alleles at a given gene locus. It is usually calculated by dividing the mutant copy number by (mutant copy number + wild-type copy number) and then multiplying by 100%. For example, a mutation abundance of 0.5% means that 5 out of every 1000 DNA molecules are mutant.

[0083] The NGS technology provided by this invention can be used to detect mutation abundance. Through single-molecule amplification and resequencing (SMART) technology, the mutation rate can be defined, and the number of mutated alleles / total alleles can be quantitatively detected. Therefore, it is possible to detect gene mutations with a mutation abundance of only 0.5%.

[0084] PIK3CA-Related Overgrowth Spectrum (PROS)

[0085] Mutations in the PIK3CA gene are associated with overgrowth syndromes. This is a group of diseases caused by somatic mutations in the PIK3CA gene, leading to overactivation of the PI3K / AKT / mTOR signaling pathway and resulting in pathological cell proliferation. These diseases include a variety of clinical manifestations, such as fibrofatty hyperplasia, unilateral hyperplastic lipomatosis, and Cloves syndrome.

[0086] The characteristics of overgrowth syndrome caused by PIK3CA gene mutations include congenital or early childhood onset, sporadic occurrence, no family history, and a progressive course. The lesions can be segmental, asymmetrical, and disproportionate in growth, with the lower limbs being more susceptible than the upper limbs, and the lesions are more common in the distal extremities.

[0087] Diagnosing PROS requires a combination of genetic testing and clinical presentation. Genetic testing is the gold standard for diagnosing PROS, but detecting low-level chimeric mutations in the PIK3CA gene remains a challenge. Treatment of PROS typically requires multidisciplinary collaboration, including surgery and interventional procedures, but treatment outcomes may be limited.

[0088] In recent years, targeted therapy has brought new hope to patients with PROS, especially those who have not responded well to traditional treatments. However, there is no consensus on whether to use targeted therapy for patients who test negative for genetic testing but clinically meet the characteristics of PROS.

[0089] NGS panel sequencing

[0090] As used herein, “NGS panel” and “Panel” are used interchangeably and both refer to NGS panel sequencing as defined in the first aspect of this invention.

[0091] NGS panel sequencing is a method based on next-generation sequencing (NGS) technology that allows for the simultaneous sequencing of multiple genes or gene regions. This method is widely used in oncology, genetic disease testing, and other gene-related research fields.

[0092] Transcriptome sequencing (RNA-seq)

[0093] The transcriptome, broadly speaking, refers to the collection of all transcribed products within a cell under a given physiological condition, including messenger RNA, ribosomal RNA, transfer RNA, and non-coding RNA; narrowly speaking, it refers to the collection of all mRNAs. Proteins are the primary carriers of cellular function, and the proteome is the most direct description of cellular function and state. The transcriptome, as the main means of studying gene expression, is the essential link between the genetic information of gene combinations and the proteome, and the regulation at the transcriptional level is currently the most studied and most important regulatory mechanism in organisms.

[0094] Transcriptome sequencing (RNA-Seq) studies the sum of all mRNAs that a specific cell can transcribe under a given functional state. Next-generation high-throughput sequencing technologies can comprehensively and rapidly obtain almost all transcript sequence information of a specific tissue or organ of a species under a given state, thereby accurately analyzing important life science issues such as gene expression differences, gene structural variations, and screening for molecular markers (SNPs or SSRs).

[0095] Whole exome sequencing (WES)

[0096] Whole-exome sequencing (WES) is a high-throughput genome sequencing technology that focuses on sequencing all exon regions of the genome, i.e., the parts of the genome that encode proteins. Although these regions only account for about 1% to 2% of the human genome, they contain approximately 85% of known pathogenic variants. WES can provide detailed information about hereditary diseases and is of great value in diagnosing genetic disorders, discovering new disease-related genes, and studying the molecular mechanisms of complex diseases.

[0097] The application areas of WES include, but are not limited to:

[0098] 1. Diagnosis of Hereditary Diseases: For cases suspected of having hereditary diseases but definitively diagnosed by traditional testing methods, WES can provide more genetic information, helping to improve diagnostic rates. 2. Discovery of New Genes: WES can reveal new disease-related genes and variants, advancing research into disease mechanisms. 3. Research on Complex Diseases: WES helps understand the genetic basis of complex diseases, providing new clues for disease prevention and treatment. 4. Research on the Genetic Basis of Drug Response: WES can identify genetic variations affecting drug response, contributing to the development of personalized medicine.

[0099] Limitations of WES:

[0100] (i) Incomplete coverage: It may not be able to capture all exon regions, especially for some complex gene families. (ii) Difficulty in detecting variations in non-coding regions: WES mainly targets coding regions, and its ability to detect variations in non-coding regions is limited. (iii) Data interpretation challenges: Professional bioinformatics analysis and genetic knowledge are required to accurately interpret sequencing results. (iv) WES technology is constantly developing and optimizing. With the reduction of sequencing costs and the advancement of analysis technology, its application in clinical diagnosis and disease research will become more widespread.

[0101] germline mutation

[0102] Germline mutations are gene mutations that occur in germ cells (such as eggs or sperm). These mutations can be inherited by offspring and affect all cells in an individual. Unlike somatic cell mutations, which occur in non-germ cells and are generally not inherited by the next generation.

[0103] In medical genetics, the detection of germline mutations is crucial for diagnosing hereditary diseases, understanding disease risk, and guiding clinical treatment. For example, germline mutations in the BRCA1 and BRCA2 genes are core risk factors for familial breast cancer, ovarian cancer, and other cancers. Detecting these mutations helps assess an individual's future risk of developing these cancers, enabling preventative measures to be taken.

[0104] BRCA gene mutation detection typically involves whole-exome sequencing (WES) and panel sequencing targeting specific genes. WES is a high-throughput sequencing technology that allows simultaneous sequencing of multiple genes or gene regions, covering all protein-coding regions in the genome. Panel sequencing targeting BRCA genes, on the other hand, is a more targeted approach, focusing on detecting gene variations associated with specific diseases.

[0105] Significant progress has been made in the clinical application of BRCA germline mutation screening and detection. For example, in the treatment of BRCA-mutated breast cancer, PARP inhibitors and platinum-based drugs are the two main treatment options. Identification of BRCA mutations is crucial for guiding personalized treatment and predicting disease risk.

[0106] Genetic counseling is typically conducted during BRCA germline mutation screening to ensure that the individual understands the purpose, procedure, and possible outcomes of the test. Interpretation of test results requires comprehensive consideration of family history, individual health background, and genetic data.

[0107] In summary, germline mutation detection plays a crucial role in the diagnosis and treatment of hereditary diseases, and BRCA gene mutation detection is a key application. With advancements in genetics and molecular biology techniques, the accuracy and accessibility of germline mutation detection will further improve, providing more possibilities for personalized medicine.

[0108] Somatic mutation

[0109] Somatic mutations are gene mutations that occur in somatic cells. These mutations are not inherited by offspring, but can spread between individual cells through mitosis. Somatic mutations are associated with a variety of diseases, the most well-known being cancer. The accumulation of somatic mutations can lead to abnormal cell function, thereby causing disease.

[0110] The detection of somatic mutations is crucial for cancer research and treatment. Somatic mutations can be identified by comparing the genomic sequences of tumor and normal tissue samples. These mutations may involve changes in a single nucleotide (single nucleotide variant, SNV), insertions or deletions (indels), gene fusions, copy number variations (CNVs), and more.

[0111] In cancer treatment, the detection of somatic mutations helps guide targeted and immunotherapies. For example, certain somatic mutations may make tumors sensitive to specific drugs, and mutation detection can help select the most effective treatment. Furthermore, monitoring somatic mutations can be used to assess treatment efficacy and detect disease recurrence early.

[0112] It is worth noting that the detection and interpretation of somatic mutations require highly specialized knowledge and technical support. For example, it is necessary to distinguish between driver gene mutations that drive cancer development and insignificant passenger gene mutations. Furthermore, the clinical significance grading of somatic mutations helps determine their potential impact on treatment, prognosis, and diagnosis.

[0113] In the field of research, scientists are exploring the patterns and mechanisms of somatic mutations. For example, one study revealed a map of somatic mutations in normal human tissues, finding significant differences in somatic mutation load and allele mutation frequency among different tissues and organs, which may be related to tissue regeneration capacity and cell division rate.

[0114] In summary, somatic mutations play a crucial role in the development and progression of diseases such as cancer, and their detection and research are of great significance for disease diagnosis and treatment. With technological advancements, our understanding of somatic mutations will continue to deepen, potentially leading to more precise treatment options for patients.

[0115] Fusion genes

[0116] Fusion genes are typically formed when partial sequences of two or more genes are linked together due to chromosomal structural abnormalities such as translocations, inversions, insertions, or deletions. This phenomenon is particularly common in hematologic malignancies and solid tumors, and the expression products of certain fusion genes can serve as targets for cancer therapy. The fusion gene EEF1D3 / FRY in this invention was identified and validated in 6.7% (8 / 120) of breast cancer samples. This fusion resulted in early truncation of the FRY gene, which plays a crucial role in structural integrity during mitosis.

[0117] HSPG2 / FOS

[0118] HSPG2 (Perlecan) is a heparan sulfate proteoglycan encoded by the HSPG2 gene, playing a role in various biological processes, including cell signaling, cell adhesion, and proliferation. In medical research, abnormal expression of HSPG2 is associated with a variety of diseases, including cancer. FOS is a gene family comprising multiple members, including c-fos, fosB, fra-1, and fra-2. FOS family genes encode proteins that are transcription factors containing leucine zipper structures, playing crucial roles in cell growth, differentiation, and tumorigenesis. HSPG2 / FOS fusion genes are very rare, and there is currently no definitive literature indicating that they form known fusion genes. However, fusion genes are typically formed when chromosomal translocations or other structural variations cause the coding regions of two genes to join together, resulting in a novel fusion transcript and protein.

[0119] Methods for detecting fusion genes include:

[0120] 1. Fluorescence in situ hybridization (FISH): Detects gene fusion events in cells using specific probes. 2. Reverse transcription polymerase chain reaction (RT-PCR): Detects fusion events using specific primers designed for known fusion genes. 3. Next-generation sequencing (NGS): Detects various fusion events, including unknown fusion genes, using high-throughput sequencing technology.

[0121] In clinical practice, the detection of fusion genes is very important for the diagnosis and treatment of cancer, because the presence of certain fusion genes may indicate specific treatment options, such as targeted therapy.

[0122] GOPC / ROS1

[0123] The GOPC / ROS1 fusion gene is a rare type of gene fusion in non-small cell lung cancer (NSCLC), resulting from the fusion of the ROS1 gene and the GOPC gene. The discovery of this fusion gene provides a new therapeutic target for patients with specific types of lung cancer.

[0124] Methods for detecting the GOPC / ROS1 fusion gene include immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), reverse transcription polymerase chain reaction (RT-PCR), and next-generation sequencing (NGS). IHC is typically used for initial screening, and positive results need to be validated by other methods such as FISH or RT-PCR. FISH is considered the gold standard for detecting ROS1 fusion genes, capable of detecting multiple fusion types, including GOPC / ROS1. RT-PCR and NGS can detect specific fusion types, but require targeted primer or probe design. NSCLC patients with GOPC / ROS1 fusion gene positivity may respond well to specific tyrosine kinase inhibitors (such as crizotinib). These drugs can effectively inhibit ROS1 activity, thereby controlling tumor growth and spread. Therefore, detecting the GOPC / ROS1 fusion gene is of great significance for guiding clinical treatment. For NSCLC patients with ROS1 fusion gene positivity, including those with GOPC / ROS1 fusions, recommended first-line treatments include crizotinib, entrectinib, ripretinib, and ceritinib. These drugs can significantly improve patients' objective response rate and progression-free survival.

[0125] As treatment progresses, patients may develop resistance to these drugs. Resistance mechanisms may include secondary mutations in the ROS1 gene or activation of other signaling pathways. Continuous genetic testing during treatment can help doctors adjust treatment plans in a timely manner. Scientists are exploring more biomarkers and therapeutic targets for ROS1 fusion genes, as well as how to overcome drug resistance. These studies are expected to provide more treatment options for ROS1 fusion gene-positive NSCLC patients. The detection and research of the GOPC / ROS1 fusion gene are of great significance for the diagnosis and treatment of NSCLC. With technological advancements and in-depth research, more targeted therapies against this fusion gene may be developed in the future.

[0126] AMER 1(APC membrane recruitment protein 1)

[0127] AMER1, also known as WTX or FAM123B, is a protein expressed in various tissues that plays an important role in regulating the Wnt signaling pathway. AMER1 interacts with various proteins such as APC, AXIN1, AXIN2, and CTNNB1 to participate in the regulation of cell proliferation, differentiation, and migration.

[0128] The role of the AMER1 gene has attracted attention in cancer research. It is mutated in certain cancers, such as Wilms' tumor (a rare childhood kidney cancer), and the mutations are typically somatic mutations, meaning they are acquired throughout an individual's life and are only present in the kidney cells that form the tumor. Mutations in the AMER1 gene can lead to protein inactivation, thereby weakening its ability to inhibit the Wnt signaling pathway, resulting in uncontrolled cell proliferation and tumor formation.

[0129] Furthermore, mutations in the AMER1 gene are also associated with colorectal cancer, breast cancer, and gastric cancer. In these cancers, the presence of AMER1 gene mutations may disrupt its function as a tumor suppressor gene, leading to uncontrolled cell proliferation.

[0130] In terms of treatment, studies have shown that IRF-2 can inhibit the proliferation of gastric cancer cells by directly activating the transcription of AMER1, and this process involves the inhibition of the Wnt / β-catenin signaling pathway.

[0131] In summary, the AMER1 gene may play an important role in the development and progression of various cancers. Its loss of function may lead to abnormal activation of the Wnt / β-catenin signaling pathway, thereby promoting cancer development and progression. Targeted therapy strategies against AMER1 may represent a new direction for future cancer treatment.

[0132] MML3(KMT2C)

[0133] KMT2C (also known as MLL3) is a histone methyltransferase that plays a crucial role in tumor suppression and DNA repair responses. It is responsible for catalyzing the methylation of histone H3K4, which is typically associated with the activation and expression of genes. Mutations or deletions of KMT2C are linked to the development and progression of various cancers.

[0134] As part of the COMPASS complex, KMT2C promotes gene expression by adding H3K4me1 modifications to the promoter and enhancer regions of genes. During DNA double-strand break repair, KMT2C helps maintain genomic stability; its loss of function may lead to a decline in the cell's ability to repair DNA damage. Mutations or downregulation of KMT2C expression are common in various tumors, including breast cancer, lung cancer, and bladder cancer. In triple-negative breast cancer (TNBC), the loss of KMT2C and KMT2D is associated with brain metastasis formation; they promote MMP3 expression in a KDM6A-dependent manner, thereby driving brain metastasis in TNBC. In small cell lung cancer (SCLC), the loss of KMT2C promotes distant metastasis of tumors through DNMT3A-mediated epigenetic reprogramming. Tumor cells lacking KMT2C may be sensitive to PARP inhibitors (such as olaparib) because these cells may rely on PARP1 / 2 for DNA repair mechanisms. Restoring KMT2C function or targeting its downstream pathways may provide new therapeutic strategies for tumors lacking KMT2C. Studies have shown that inhibition or loss of KMT2C leads to widespread changes in gene expression, particularly the downregulation of genes associated with DNA damage response (DDR) and DNA repair. In bladder cancer, downregulation of KMT2C is associated with tumor development and progression, and reduced expression is associated with poorer prognosis. In summary, KMT2C, as an epigenetic regulator, plays a crucial role in tumorigenesis and development, and its functional abnormalities may promote tumor progression and metastasis. Targeted therapeutic strategies against KMT2C and its regulatory network are under investigation and may provide new treatment options for patients with specific types of cancer.

[0135] BRD4

[0136] BRD4 is a transcriptional coactivator that is altered in various cancer types through amplification or chromosomal rearrangement. The biological significance of the BRD4 Q973H mutation remains unclear. BET (bromine and terminal extraterminal domains, including BRD4) is a novel determinant of transcriptional programming in vascular cells, such as endothelial cells and vascular smooth muscle inflammatory cells, acting on super-enhancer regulatory regions to guide gene expression. Inhibition of BET epigenetic reader proteins may be a promising therapeutic strategy for preventing adverse vascular remodeling.

[0137] GJA1

[0138] Ocular-dental-bidactyly syndrome (ODD; OMIM 164200) is a congenital disorder characterized by phenotypic features most commonly affecting the face, eyes, teeth, and fingers (toes). It is caused by a mutation in the GJA1 gene on chromosome 6. GJA1 encodes connexin 43, a gap connexin important for intercellular communication and expressed in lymphatic valves. This article presents a case of a patient with clinical and molecular diagnoses of ODD and lower extremity lymphedema. Sanger sequencing of family members confirmed a missense p.K206R GJA1 mutation that segregated from the phenotype suggesting a causal relationship, a correlation not previously reported.

[0139] The main advantages of this invention are:

[0140] (1) Using the lesion tissue of the child as the test sample, NGS panel sequencing of somatic mutation specimens can be achieved to assess the changes in gene mutation abundance;

[0141] (2) The NGS panel sequencing provided by this invention can perform gene detection on all hemangioma and vascular malformation lesions, with a coverage of over 95% and a positive rate of about 80%.

[0142] (3) The NGS panel provided by this invention has high sequencing sensitivity and sequencing depth up to 20,000X, which can achieve gene mutation detection with a mutation abundance of only 0.5%.

[0143] (4) The NGS panel sequencing combined with whole transcriptome sequencing (RNAseq) provided by this invention can further improve the positive rate of detection results and provide a basis for the treatment and discontinuation criteria of targeted drugs for hemangiomas and vascular malformations.

[0144] (5) The peripheral blood genome whole exon sequencing (WES) provided by this invention has a depth of 100X, which can determine whether it is a germline mutation or a somatic mutation.

[0145] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Experimental methods in the following embodiments, unless otherwise specified, are generally performed under conventional conditions, such as those described in Sambrook et al., Molecular Cloning: A Laboratory Manual (New York: Cold Spring Harbor Laboratory Press, 1989), or as recommended by the manufacturer. Unless otherwise stated, percentages and parts are weight percentages and parts by weight.

[0146] Unless otherwise specified, all experimental materials and reagents used in the following examples are available from commercially available sources.

[0147] This invention discloses a gene combination and its application for the molecular diagnosis of hemangiomas and vascular malformations, including a combination of all pathogenic genes for hemangiomas and vascular malformations, an NGS panel + RNAseq gene sequencing scheme, an automated analysis scheme, and the scope of diseases to which it is applied. The acquisition and processing of the lesion specimens are constructed after specific optimization for gene detection. The self-control group is composed of the genome of the child's own peripheral blood. The design of the NGS panel + RNAseq primers for the molecular diagnosis of hemangiomas and vascular malformations is based on a combination of all currently known pathogenic genes for hemangiomas and vascular malformations, after specific optimization and validation. The NGS panel + RNAseq sequencing scheme has an NGS panel sequencing depth of 20000X, an RNAseq sequencing depth of 150X, and a peripheral blood genome whole-exome sequencing (WES) depth of 100X. The automated analysis and processing of the sequencing results, performed by NGS panel + RNAseq sequencing-specific analysis software using machine learning algorithms, employs artificial intelligence processing such as noise reduction, artifact removal, and automated alignment. This directly displays the detection abundance of various hotspot mutation sites, enabling the exploration of precise diagnostic molecular markers. The gene combination and disease scope of this molecular diagnostic method for hemangiomas and vascular malformations can be applied to all molecular diagnostics and liquid biopsies related to hemangiomas and vascular malformations, revealing the correlation between mutation sites and abundance and disease phenotypes, thus possessing significant potential for clinical application.

[0148] Experimental methods

[0149] (1) NGS panel sequencing: This is a method based on next-generation sequencing (NGS) technology, which allows for the simultaneous sequencing of multiple genes or gene regions. This method is widely used in oncology, genetic disease testing, and other gene-related research fields.

[0150] The following is the experimental procedure for NGS panel sequencing:

[0151] 1. Sample collection and nucleic acid extraction: Collect samples and extract DNA or RNA according to the type of sample to be tested (such as blood, tumor tissue, etc.).

[0152] 2. Library construction: The extracted nucleic acids are constructed into sequencing libraries. This process includes steps such as fragmentation, end repair, and adapter ligation.

[0153] 3. Target region enrichment: Enriching genes or gene regions of interest through hybridization capture or PCR amplification.

[0154] 4. Sequencing: Use NGS platforms for sequencing, such as Illumina, ThermoFisher's Ion Torrent, etc.

[0155] 5. Data analysis: including read alignment, variant detection, copy number variation analysis, and structural variation analysis.

[0156] 6. Results Interpretation: The detected variants were compared with clinical databases to assess their clinical significance.

[0157] 7. Quality control: Ensure the accuracy and reliability of sequencing data.

[0158] In oncology, NGS panel sequencing can be used to detect driver gene mutations in tumors, helping to guide targeted therapy. For example, it can detect hotspot mutations in multiple genes associated with a specific tumor, or it can be designed to detect the entire coding and non-coding sequences of relevant genes.

[0159] Furthermore, pan-cancer analysis is a study using NGS panels that assesses frequently mutated genes as well as other genomic abnormalities common to multiple cancers, regardless of tumor origin. This analysis can incorporate markers for multiple cancers in a single test, streamlining workflows and reducing turnaround time.

[0160] It is worth noting that the experimental design for NGS panel sequencing needs to consider gene selection, sequencing depth, laboratory productivity, bioinformatics analysis capabilities, and the complexity of clinical interpretation. Furthermore, to ensure the accuracy of the results, thorough analytical validation is required, including using reference cell lines and reference materials to evaluate detection performance, determining the positive percentage and positive predictive value for each mutation type, and defining the minimum coverage depth and minimum sample size.

[0161] (2) WES experiment: The specific experimental procedure is as follows:

[0162] 1. Sample collection: Collecting blood, tissue or other biological samples.

[0163] 2. DNA extraction: Extracting DNA from the sample.

[0164] 3. Library construction: Sequencing libraries are constructed using the extracted DNA.

[0165] 4. Exon capture: Using specific probes or primers to capture exon regions in the genome.

[0166] 5. Sequencing: Sequencing is performed using high-throughput sequencing technologies (such as the Illumina platform).

[0167] 6. Data analysis: including sequence alignment, variant detection, annotation, and interpretation.

[0168] Advantages of WES:

[0169] Comprehensive coverage: It can cover the exon regions of more than 20,000 genes.

[0170] High cost-effectiveness: Compared to whole genome sequencing, WES is more economical and efficient.

[0171] High diagnostic rate: It has a high positive rate for the diagnosis of hereditary diseases.

[0172] (3) Fusion gene detection: The detection method is as follows:

[0173] 1. Fluorescence in situ hybridization (FISH): This method uses labeled DNA probes to hybridize with sample DNA, and the hybridization is observed through a fluorescence microscope. It is commonly used to detect known fusion genes.

[0174] 2. Reverse transcription polymerase chain reaction (RT-PCR): This method amplifies the mRNA of fusion genes by designing specific primers and is often used to detect known fusion genes.

[0175] 3. Immunohistochemistry (IHC): Based on the detection of gene fusions at the protein level, it is suitable for the detection of protein expression of known fusion genes.

[0176] 4. Next-generation sequencing (NGS): Through whole-genome sequencing (WGS), transcriptome sequencing (RNA-seq), or targeted sequencing of specific regions, various fusion events, including unknown fusion genes, can be detected.

[0177] Research Progress: The discovery of the ROS1 fusion gene in non-small cell lung cancer is of great significance for treatment, and targeted drugs have significantly improved patients' quality of life. Transcriptome sequencing technology has been used to comprehensively analyze pathogenic fusion genes in hematologic malignancies, including rare fusion genes and members of fusion gene families.

[0178] Clinical significance: The detection of fusion genes plays an important role in disease diagnosis, treatment selection, efficacy monitoring, and prognostic assessment. For example, in chronic myeloid leukemia (CML), the presence of the BCR-ABL1 fusion gene is one of the disease characteristics, and its quantitative detection is crucial for evaluating treatment efficacy.

[0179] Example 1

[0180] (1) Under anesthesia, lesion tissue (approximately 3 mm in diameter) of PIK3CA-related overgrowth syndrome (PROS) was excised, placed in RNAlater preservation solution and refrigerated for 30 minutes after excision, and DNA and RNA were extracted in time and frozen at -20°C.

[0181] (2) Simultaneously, 2 ml of peripheral blood was drawn from the patient, centrifuged, and the supernatant was discarded. RNAlater was added and stored at -20℃. Then, DNA and RNA were extracted according to the kit instructions and frozen at -20℃. The DNA sample was used for NGS panel or WES detection, and the RNA sample was used for RNA-seq detection.

[0182] (3) Following the experimental procedure, the extracted DNA and RNA were subjected to NGS panel sequencing (sequencing depth of 20000X). If the result was negative, RNAseq (sequencing depth of 150X) and tissue whole exome sequencing (sequencing depth of 600X) were performed. At the same time, peripheral blood genome whole exome sequencing (WES) (100X) was performed, and the detection and analysis results were automatically obtained.

[0183] The experimental process using next-generation sequencing (NGS) technology typically includes the following steps:

[0184] 1. Sample collection and quality control: Collect tumor tissue or blood samples and perform quality control to ensure that the samples contain sufficient tumor DNA.

[0185] 2. DNA extraction: Extract DNA from the sample and perform quality testing.

[0186] 3. Library preparation: Sequencing libraries are constructed using the extracted DNA. During library preparation, it is necessary to ensure that the size and quality of the DNA fragments are suitable for subsequent sequencing.

[0187] 4. Sequencing: Sequencing is performed using an NGS platform, such as Illumina, which can provide high-throughput sequencing services.

[0188] 5. Genome data generation: After sequencing is completed, a large amount of genome data is generated.

[0189] 6. Data Analysis: Data analysis includes three processes:

[0190] Variation identification: using bioinformatics tools to identify variations in the genome.

[0191] Variant annotation and filtering: Identified variants are annotated and filtered based on their potential clinical significance.

[0192] Clinical interpretation of variants: Based on information such as variants and drug sensitivity, conduct clinical interpretation of variants and establish a clinical interpretation knowledge base.

[0193] 7. Determination of mutation abundance: Mutation abundance is determined by analyzing the ratio of mutant alleles to wild-type alleles.

[0194] The formula for calculating mutation abundance is: mutant copy number divided by (mutant copy number + wild-type copy number) and then multiplied by 100%.

[0195] 8. Results Interpretation: Based on the mutation abundance results and clinical information, a comprehensive assessment of the patient's disease is conducted, and corresponding treatment strategies are formulated.

[0196] It is important to note that mutation abundance detection is influenced by various factors, including sample heterogeneity, detection method, tumor cell content, capture efficiency, amplification bias, and gene amplification. Therefore, these factors need to be adjusted for in clinical applications.

[0197] Furthermore, the 2020 CSCO guidelines for colorectal cancer recommend using 5% as the cutoff value for mutation abundance when using quantitative detection methods such as NGS to detect RAS and BRAF mutations. This indicates that mutation abundance can be used to predict drug sensitivity and has important clinical significance.

[0198] As time progressed, the inventors submitted different batches of samples for sequential product testing for hemangiomas or vascular malformations. The results are as follows:

[0199] (1) Sequential product testing was conducted on 13 samples of hemangiomas or vascular malformations. The results showed that the positive rate of NGS panel was 61.5% (8 / 13), the positive rate of NGS panel + RNAseq was 69.2% (9 / 13), and the positive rate of fusion gene verification in 3 additional samples increased the positive rate to 92.3% (12 / 13). Compared with NGS panel, WES did not find any clear pathogenic genes, indicating that the genomic composition of the NGS panel selected in this invention is very comprehensive. Figure 1) S、RNF213 / SLC26A11、SBDS、HAVCR、MLL3、RECQL5、BRCA、HSPG2、FOS、GOPC、R OS1, AMER1, MML3, BRD4, ACVRL1, ELMO2, GJC2, KDR, NPM1, TEK, ADAMTS3, ENG, GLMN, KIF11, NRAS, TFE3, AGGF1, EPHB4, GNA11, KRAS, PDCD10, TNFRSF11A, A KT1、FAT4、GNA14、KRIT1、PIEZO1、TREM2、ANTXR1、FLT4、GNAQ、MAP2K1、PIK3 CA、TSC1、BAD、FOS、HGF、MAP3K3、PTEN、TSC2、BRAF、FOSB、HRAS、MET、PTPN14、 VEGFC、CAMTA1、FOXC2、IDH1、MTOR、RASA1、CCBE1、GATA2、IDH2、MYC、SMAD4、 CCM2、GDF2、IKBKG、NF1、SOX18、CELSR1、GJA1、ITGA9、NF2、STAMBP、ALK、APOD 、AR、AXLCASC15、CCND1、CDH11、CDKN1C、CLU、FGFR3、GU2、GL3、GPC3、H19、IG F1、IGF1R、IGF2、IGFBP7、ITGA3、KCNQ1OT1、LOX、MPL、MYCN、WT1、BLOC1S4、B PTF、BTBD2、C170r103、FOXO1、GAS1、GDF11、IRF2BPL、TTGA3、KLHDC10、MUC9 、MYO6、SEC22C、SHC2、IP5B2、UTF1、ZNRF2、CSF1R、CXCL2、DLG2、ERBB3、FGF2、 FGFR2、GLI2、GLI3、KIF1B、NMB、NOTCH2、PRKCG、PTCH2、RUNX2、SIX1、SIX2、S MOC1、TNC、ARIDIA、C11orf95、CARMI、CASZI、CDC42EPS、CHKA、COPZ2、CTC1、E LMSANI、GATAD1、IQSEC1、MAZ、MBD2、MEX3C、MEX3D、MUC6、NACAD、PLEKHH3、P PPIR12C、SH3BP2、SOX21、TAF4、TPSB2、YBX3、ZCCHC3、LPK3、BAAP3、BLOC154、CABLES1, CAPNS1, CDC27, COQ7, FBXL16, GSK3A, ID2, IL17D, INO80E, KCNF1, KCTD2, KDM1A, LLGL1, MTSS1L, NDUFB11, NR XN2, PDCD7, PGRMC2, POU3F3, PWWP2A, RAMP2, SCRT2, SHANK1, SLC25A43, SLC9A7, SRF, TMEM102, TMEM14S, USP43, and ZC3H4. ,

[0200] Among them, with Figure 1 Taking patients No. 1, 8, and 9 as examples, the test results are as follows:

[0201] (1.1) Results of sequential product testing for hemangioma and vascular malformation in patient sample No. 1; including a summary of variant results and mRNA detection results related to fusion genes. Genes with abnormal expression levels include: upregulated genes: ALK, APOD, AR, AXLCASC15, CCND1, CDH11, CDKN1C, CLU, CSF1R, CXCL2, ERBB3, FGFR2, FGFR3, GU2, GL3, GPC3, H19, IGF1, IGF1R, IGF2, IGFBP7, ITGA3, KCNQ1OT1, KDR, LOX, MPL, MYCN, NOTCH2, PTCH2, RUNX2, SIX1, SIX2, SMOC1, TNC, WT1; downregulated genes: EZH2, GPS2; fusion gene is EEF1DP3 / FRY ( Figure 2 ).

[0202] An overview of the whole-exome sequencing results for patient number 1—somatic variants—was conducted. All exon mutations detected by whole-exome WES were exon mutations occurring in genes within the same genome. These mutated genes included: AMER1, BLOC1S4, BPTF, BTBD2, C170r103, FOXO1, GAS1, GDF11, IRF2BPL, TTGA3, KLHDC10, MLL3, MUC9, MYO6, SEC22C, SHC2, IP5B2, UTF1, and ZNRF2. The vast majority were missense mutations, with only a few being frameshift and non-frameshift mutations. Compared to the NGS panel, WES did not identify any clearly pathogenic genes. However, it did detect non-pathogenic mutations (unintentional mutations) or accompanying mutations, providing data support for research on gene-gene interactions. Figure 3 ).

[0203] (1.2) Genes with abnormal expression levels detected in Patient No. 8 included: upregulated genes: ALK, APOD, AR, AXLCASC15, CCND1, CDH11, CDKN1C, CSF1R, CXCL2, DLG2, ERBB3, FGF2, FGFR2, GLI2, GLI3, GPC3, H19, IGF1, IGF1R, IGF2, IGFBP7, ITGA3, KCNQ1OT1, KDR, KIF1B, LOX, MPL, MYCN, NMB, NOTCH2, PRKCG, PTCH2, RUNX2, SIX1, SIX2, SMOC1, and TNC; the fusion gene was HSPG2 / FOS ( Figure 4 The gene that may be related to the disease is BRD4. Figure 5 The exon mutations detected by whole-exome sequencing (WES) were all exon mutations occurring in genes contained within the genome. These mutated genes included: ARIDIA, BRD4, C11orf95, CARMI, CASIZI, CDC42EPS, CHKA, COPZ2, CTC1, ELMSANI, GATAD1, IQSEC1, MAZ, MBD2, MEX3C, MEX3D, MUC6, NACAD, PLEKHH3, PPPIR12C, SH3BP2, SOX21, TAF4, TPSB2, UTF1, YBX3, and ZCCHC3. The vast majority were missense mutations, with only a few being frameshift or non-frameshift mutations. Compared to NGS panels, WES did not identify any clearly pathogenic genes. However, it did detect non-pathogenic mutations (unintentional mutations) or accompanying mutations, providing data support for studying gene-gene interactions. Figure 6 ).

[0204] (1.3) Patient No. 9 was found to have a fusion gene of GOPC / ROS1 ( Figure 7 The gene that may be related to the disease is GJA1. Figure 8The exon mutations identified by whole-exome sequencing (WES) were all exon mutations occurring in genes contained within the genome. These mutated genes included: LPK3, BAAP3, BLOC154, CABLES1, CAPNS1, CDC27, COQ7, FBXL16, GATAD1, GDF11, GJA1, GSK3A, ID2, IL17D, INO80E, IRF2BPL, KCNF1, KCTD2, KDM1A, LLGL1, MTSS1L, NDUFB11, NRXN2, PDCD7, PGRMC2, POU3F3, PWWP2A, RAMP2, SCRT2, SHANK1, SLC25A43, SLC9A7, SOX21, SRF, TMEM102, TMEM14S, TPSB2, USP43, and ZC3H4. The vast majority were missense mutations. Compared to NGSpanel, WES did not identify any clearly pathogenic genes. However, non-pathogenic mutations (unintentional mutations) or accompanying mutations can be found, providing data support for the study of gene-gene interactions. Figure 9 ).

[0205] (2) Sequential products were sent for testing of 37 samples of hemangioma or vascular malformation. The test results showed that the positive rate of panel was 59.4% (22 / 37), the positive rate of panel + RNAseq was 70.3% (26 / 37), and the positive rate of fusion gene verification in 4 other samples increased to 81.1% (30 / 37). Compared with panel, WES did not find any clear pathogenic genes, indicating that the NGS panel selected in this invention is very comprehensive in terms of genome.

[0206] (3) Sequential products were sent for testing of 63 samples of hemangioma or vascular malformation. The test results showed that the positive rate of panel was 73% (46 / 63), and the positive rate of panel + RNAseq was 77.8% (49 / 63). Compared with panel, WES did not find any clear pathogenic genes, indicating that the NGS panel selected in this invention is very comprehensive in terms of genome.

[0207] (4) Sequential product testing was conducted on 71 samples of hemangiomas or vascular malformations. The results showed that the panel positivity rate was 69% (49 / 71), and the panel+RNAseq positivity rate was 73.2% (52 / 71). WES did not find any specific pathogenic genes compared to panel, indicating that the NGS panel selected in this invention has a very comprehensive genomic profile. Among them, the two genes with the highest positivity rates (TOP2 genes) were PIK3CA and TEK. From the PIK3CA gene site distribution results, it can be seen that the highest mutation site is the glutamic acid Cys mutation at position 545 of the PIK3CA protein amino acid sequence, which is changed to lysine Lys (i.e., p.E545K). 8 out of 24 samples had the p.E545K mutation. From the TEK gene site distribution results, it can be seen that the highest mutation site is the leucine Leu mutation at position 914 of the TEK protein amino acid sequence, which is changed to phenylalanine Phe (i.e., p.L9114F). 5 out of 27 samples had the p.L9114F mutation. Figure 10 (Figure A in the middle) Figure 10 B shows the mutation abundance distribution of the PIK3CA and TEK genes, ranging from 0.5% to 18%. The median mutation abundance of the PIK3CA gene is around 6%, and that of the TEK gene is around 10%.

[0208] Taking patient A as an example, the inventors discovered a mutation in the IDH1 gene using a 62-panel assay. Specifically, the cytosine C at position 394 of the IDH1 gene (transcription ID: NM-005896) nucleic acid sequence was mutated to thymine T (i.e., c.394C>T); and the arginine Arg at position 132 of the IDH1 protein amino acid sequence was mutated to cysteine ​​Cys (i.e., p.R132C), with a mutation abundance of 0.5%. IDH1 gene mutations are associated with spindle cell hemangiomas (…). Figure 11 ).

[0209] (5) The inventors submitted 109 sequential samples and 124 individual 62-panel samples for testing, totaling 233 samples. Among them, there were 233 62-panel data, 108 RNAseq data, and 39 WES data. The positive rate of sequential samples was 72.5%, and the positive rate of individual panels was 62.1% (the positive definition is relatively strict). Sequential samples improved the positive rate by 10%.

[0210] (6) 259 samples of hemangiomas or vascular malformations were submitted for sequential product testing. The results showed that the panel positivity rate was 73.4% (190 / 259), and the panel + RNAseq positivity rate was 76.1% (197 / 259). WES did not find any clearly significant pathogenic genes compared to panel testing, indicating that the NGS panel selected in this invention is very comprehensive and has completely covered all known pathogenic genes. Fusion genes were detected in 135 sequential orders (samples), and the RNAseq positivity rate of the remaining 124 panels increased by several percentage points from 76.1%. Among them, 108 samples tested positive for the PIK3CA gene, with a mutation frequency of 41.7%. The mutation site distribution is as follows: Figure 12 As shown in the figure, p.E545K accounted for 29.63%, the highest proportion. Furthermore, the TEK gene was detected in 39 out of 259 samples, with a mutation frequency of 15.6%. In the germline mutation site distribution of the TEK gene, the germline mutation site at the arginine (Arg) position 849 of the TEK protein amino acid sequence (i.e., p.R849W) accounted for 50%.

[0211] Slight fluctuations in the positivity rate are normal due to differences in sample size and disease composition across different batches. Within the total number of cases, each additional positive case increases the positivity rate, while each additional negative case decreases it. Once a relatively large number of cases are tested, the positivity rate will plateau.

[0212] Based on the above experimental methods, the Panel / WES+RNAseq detection provided by this invention can comprehensively detect genomic and transcriptomic changes. The detection method provided by this invention has the following advantages:

[0213] (i) "Deep": Panel detection accurately detects low-frequency variants in core genes through full exon coverage of 62 core genes and high-depth detection with an average sequencing depth of 20,000X.

[0214] (ii) "Comprehensive": RNAseq comprehensively covers common fusion / translocation / alternative splicing related genes and signaling pathway related gene expression analysis through full transcriptome coverage and 15G sequencing data, making up for the disadvantages of conventional methods, improving the accuracy of fusion genes, and promoting gene expression analysis.

[0215] (iii) "Broad": WES detection covers all exons of all genes in the human genome, approximately 21,000 genes, with a maximum sequencing depth of 600X for tissues.

[0216] Peripheral blood samples from the subjects were simultaneously sent for analysis (100X germline control samples) to detect and analyze germline variations, ensuring the accuracy of the source of variations and the effective analysis of hereditary tumors.

[0217] (4) Combine the patient’s phenotype and genotype to perform PROS-related molecular diagnosis to guide targeted drug treatment or guidance on drug discontinuation.

[0218] This embodiment uses lesion tissue from children as the detection sample, achieving NGS panel sequencing of somatic mutation specimens and assessing changes in gene mutation abundance. The NGS panel sequencing of this invention can perform gene detection on all hemangioma / vascular malformation lesion tissues, with a coverage of over 95% and a positive rate of approximately 80%. The NGS panel sequencing of this invention has high sensitivity, with a sequencing depth reaching 20,000X, enabling the detection of gene mutations with an abundance of only 0.5%. This invention combines NGS panel sequencing with whole transcriptome sequencing (RNA-seq), achieving a sequencing depth of 150X, further improving the positive rate and providing a basis for targeted drug treatment and discontinuation criteria for hemangioma / vascular malformations. Furthermore, this invention uses peripheral blood whole-exome sequencing (WES) at a depth of 100X to determine whether the mutation is germline or somatic. Clinical sample validation shows that the gene combinations and gene mutation detection targets screened by this invention have good sensitivity and specificity in the diagnosis of hemangioma / vascular malformations.

[0219] discuss

[0220] In recent years, with the generation of large-scale omics data, meta-analysis and large-scale computational modeling have become indispensable tools for overcoming the limitations of individual research statistics and obtaining evidence-based insights. Genome-wide transcriptomic profiling can identify molecular features in peripheral blood or tumor samples, which can be used to improve patient diagnosis and risk stratification, or guide targeted therapy strategies for cancer patients. Previous studies have reported the development and validation of an automated, high-precision diagnostic model for papillary thyroid carcinoma (PTC) using transcriptome (RNA-seq) data combined with clinical diagnosis and sophisticated machine learning algorithms. Other studies have reported the development of a precise diagnostic model for mediastinal lymph node disease using support vector machine (SVM) learning of differentially expressed genes combined with clinical diagnosis. Therefore, constructing a precise diagnostic model for vascular malformations using RNA-seq, combined with clinical diagnosis and machine learning algorithms, can contribute to the accurate diagnosis of hemangiomas and vascular malformations, aiming to achieve better treatment outcomes.

[0221] Hemangiomas / vascular malformations can be caused by genetic or somatic gene mutations. In 1994, the genetic basis of familial vascular abnormalities began to be identified, and the discovery of mutations in hemangiomas / vascular malformations made it possible to understand the genotype-phenotype relationship. Whole-exome sequencing (WES) of tissue samples from 81 patients with cavernous malformations revealed that 90.1% (73 / 81) of the patients carried somatic activation mutations in MAP3K3 and PIK3CA, demonstrating a correlation between genotype and phenotype. Luks et al. performed WES sequencing on 7 patients with solitary lymphovascular malformations (LM) and 8 patients with fibrofatty vascular malformations (FAVA), finding PIK3CA somatic mutations in 71% (5 / 7) of LM patients and 50% (4 / 8) of FAVA patients. WES sequencing of tissue samples from 26 patients with cerebral arteriovenous malformations and paired blood samples from 17 patients revealed that these cerebral arteriovenous malformations resulted from KRAS-induced activation of the MAPK-ERK signaling pathway in brain endothelial cells. In addition, RNAseq sequencing revealed a patient with lymphatic malformation carrying a known pathogenic GOPC / ROS1 gene fusion, who may be sensitive to ROS1 inhibitors.

[0222] Most of the gene variants detected so far play an important role in pathways related to angiogenesis and lymphangiogenesis, angiogenesis, apoptosis and proliferation. The main pathways involved include the angiopoietin / TIE2, PI3K / AKT / mTOR, EPHB4 / Ras / MEK / ERK and TGFB signaling pathways, and protein-coupled receptor signaling molecules (GNAQ / GNA11 / GNA14) are also frequently involved.

[0223] Interestingly, most somatic mutations leading to hemangiomas / lymphatic malformations occur in genes encoding oncogenic growth factor signaling pathways. This has led to the successful use of some cancer-targeting drugs to treat hemangiomas / lymphatic malformations. For example, apelisib, an approved oncology PIK3CA inhibitor, is currently used to treat PIK3CA-associated proliferative syndrome (PROS). Morin et al. first reported treating two infants with life-threatening PROS with apelisib (25 mg), with clinical improvement and no reported adverse events. Similarly, there are currently no targeted drugs for arteriovenous malformations (AVMs). Lekwuttikarn et al. reported a case of successful treatment with trametinib in a sporadic pediatric patient with extracranial AVM carrying a MAP2K1 mutation who had failed sirolimus treatment. To date, although breakthroughs have been made in the study of the pathogenesis and signaling pathways involved in hemangiomas / vascular malformations, and a new era has begun for the re-application of anticancer drugs in the treatment of hemangiomas / vascular malformations, treatment options for hemangiomas / vascular malformations remain limited, especially for a large number of patients who have not been completely cured by sclerotherapy, embolization, surgery, laser ablation, and their combination therapies. These patients experience severe chronic pain, devastation, and poor quality of life. Identifying the gene mutations or fusions associated with hemangiomas / lymphatic malformations is the first step in developing specific targeted drugs for these lesions.

[0224] Therefore, by using WES / RNAseq sequencing to discover new pathogenic genes and conducting cell and animal model experiments to validate them, we can further explore and discover new targeted therapies, providing a preclinical theoretical basis for targeted therapy clinical trials.

[0225] All documents mentioned in this invention are incorporated herein by reference as if each document were individually incorporated by reference. Furthermore, it should be understood that after reading the foregoing teachings of this invention, those skilled in the art can make various alterations or modifications to this invention, and these equivalent forms also fall within the scope defined by the appended claims.

Claims

1. A gene combination for detecting hemangiomas and vascular malformations, characterized in that, The gene combination includes the following genes: BRCA, HSPG2, FOS, GOPC, ROS1, AMER1, MML3, BRD4, ACVRL1, ELMO2, GJC2, KDR, NPM1, TEK, ADAMTS3, ENG, GLMN, KIF11, NRAS, TFE3, AGGF1, EPHB4, GNA11, KRAS, PDCD10, TNFRSF11A, AKT1, FAT4, GNA14, KRIT1, PIEZO1, TREM2, ANTXR1. FLT4, GNAQ, MAP2K1, PIK3CA, TSC1, BAD, FOS, HGF, MAP3K3, PTEN, TSC2, BRAF, FOSB, HRAS, MET, PTPN14, VEGFC, CAMTA1, FOX C2, IDH1, MTOR, RASA1, CCBE1, GATA2, IDH2, MYC, SMAD4, CCM2, GDF2, IKBKG, NF1, SOX18, CELSR1, GJA1, ITGA9, NF2 and STAMBP.

2. The gene combination as described in claim 1, characterized in that, The gene combination also includes the following genes: EEF1DP3 / FRY, FOS / HBG2, CTSC / RAB38, GOPC / ROS1, HSPG2 / FOS, RNF213 / SLC26A11, SBDS, HAVCR, MLL3, RECQL5, ALK, APOD, AR, AXLCASC15, CCND1, CDH11, CDKN1C, CLU, FGFR3, GU2, GL3, GPC3, H19, IGF1, IGF1R, IGF2, IGFBP7, ITGA3, K CNQ1OT1, LOX, MPL, MYCN, WT1, EZH2, GPS2, BLOC1S4, BPTF, BTBD2, C170r103, FOXO1, GAS1, GDF11, IRF2BPL, TTGA3, KLHDC10, MUC9, MYO6, SEC22C, SHC2, IP5B2, UTF1, ZNRF2, CSF1R, CXCL2, DLG2, ERBB3, FGF2, FGFR2, GLI2, GLI3, KIF1B, NMB, NOTCH2, PRK CG, PTCH2, RUNX2, SIX1, SIX2, SMOC1, TNC, ARIDIA, C11orf95, CARMI, CASZI, CDC42EPS, CHKA, COPZ2, CTC1, ELMSANI, GATAD1 , IQSEC1, MAZ, MBD2, MEX3C, MEX3D, MUC6, NACAD, PLEKHH3, PPPIR12C, SH3BP2, SOX21, TAF4, TPSB2, YBX3, ZCCHC3, LPK3, BAAP 3. BLOC154, CABLES1, CAPNS1, CDC27, COQ7, FBXL16, GSK3A, ID2, IL17D, INO80E, KCNF1, KCTD2, KDM1A, LLGL1, MTSS1L, NDUFB 11. NRXN2, PDCD7, PGRMC2, POU3F3, PWWP2A, RAMP2, SCRT2, SHANK1, SLC25A43, SLC9A7, SRF, TMEM102, TMEM14S, USP43 and ZC3H4.

3. The gene combination as described in claim 1, characterized in that, The gene combination is used to detect hemangiomas and vascular malformations by the following methods: NGS panel sequencing, whole transcriptome sequencing (RNAseq), whole exome sequencing (WES), or a combination thereof.

4. The gene combination as described in claim 1, characterized in that, In the lesion tissue of patients with hemangiomas and vascular malformations, the genes in the aforementioned gene combination have a mutation abundance of ≥0.5% compared with the human standard reference genome.

5. The use of the gene combination and / or its detection reagents as described in claim 1 in the preparation of a kit for detecting hemangiomas and vascular malformations.

6. The application as described in claim 5, characterized in that, The instructions for the kit state: (1) If high expression or mutation of genes selected from the following groups is detected, it suggests that the patient has hemangioma and vascular malformation: BRCA, HSPG2, FOS, GOPC, ROS1, AMER1, MML3, BRD4, ACVRL1, ELMO2, GJC2, KDR, NPM1, TEK, ADAMTS3, ENG, GLMN, KIF11, NRAS, TFE3, AGGF1, EPHB4, GNA11, KRAS, PDCD10, TNFRSF11A, AKT1, FAT4, GNA14, KRIT1, PIEZO1, TREM2, ANTXR1, FLT4, GNAQ, MAP2K1, PIK3CA, TSC1, BAD, FOS, HGF, MAP3K3, PTEN, TSC2, BRAF, FOSB, HRAS, MET, PTPN14, VEGFC, CAMTA1, FOXC2, IDH1, MTOR, RASA1, CCBE1, GATA2, IDH2, MYC, SMAD4, CCM 2. GDF2, IKBKG, NF1, SOX18, CELSR1, GJA1, ITGA9, NF2, STAMBP, SBDS, HAVCR, MLL3, RECQL5, ALK, APOD, AR, AXLCASC15, CCND1, CDH11, CDKN1C, CLU, FGFR3 , GU2, GL3, GPC3, H19, IGF1, IGF1R, IGF2, IGFBP7, ITGA3, KCNQ1OT1, LOX, MPL, MYCN, WT1, BLOC1S4, BPTF, BTBD2, C170r103, FOXO1, GAS1, GDF11, IRF2BPL , TTGA3, KLHDC10, MUC9, MYO6, SEC22C, SHC2, IP5B2, UTF1, ZNRF2, CSF1R, CXCL2, DLG2, ERBB3, FGF2, FGFR2, GLI2, GLI3, KIF1B, NMB, NOTCH2, PRKCG, PTCH 2. RUNX2, SIX1, SIX2, SMOC1, TNC, ARIDIA, C11orf95, CARMI, CASZI, CDC42EPS, CHKA, COPZ2, CTC1, ELMSANI, GATAD1, IQSEC1, MAZ, MBD2, MEX3C, MEX3D, M UC6, NACAD, PLEKHH3, PPPIR12C, SH3BP2, SOX21, TAF4, TPSB2, YBX3, ZCCHC3, LPK3, BAAP3, BLOC154, CABLES1, CAPNS1, CDC27, COQ7, FBXL16, GSK3A, ID2,IL17D, INO80E, KCNF1, KCTD2, KDM1A, LLGL1, MTSS1L, NDUFB11, NRXN2, PDCD7, PGRMC2, POU3F3, PWWP2A, RAMP2, SCRT2, SHANK1, SLC25A43, SLC9A7, SRF, TMEM102, TMEM14S, USP43 and ZC3H4; (2) If low expression or mutation of a gene selected from the following groups is detected, it indicates that the patient has hemangioma and vascular malformation: EZH2 or GPS2; (3) If a fusion gene selected from the following groups is detected, it indicates that the patient has hemangioma and vascular malformation: EEF1DP3 / FRY, FOS / HBG2, CTSC / RAB38, GOPC / ROS1, HSPG2 / FOS, RNF213 / SLC26A11.

7. A reagent combination for detecting the expression level of genes in the gene combination of claim 1.

8. A product for molecular diagnosis of hemangiomas and vascular malformations, comprising the reagent combination of claim 7.

9. An apparatus for assessing the genetic risk of hemangioma and vascular malformations in a subject by detecting the gene combination of claim 1, the apparatus comprising: S1) Sequencing module, used to sequence the genes in samples from the subject and obtain sequencing results; S2) Analysis module, used to analyze mutation information of samples; S3) The comparison module compares the mutation information with the gene combination described in claim 1 to determine the subject's genetic risk of hemangioma and vascular malformation. S4) Output module, which is used to output the judgment result.

10. The apparatus as claimed in claim 9, characterized in that, The sequencing module uses sequencing methods selected from the following group for sequencing: NGS panel sequencing, whole transcriptome sequencing (RNAseq), whole exome sequencing (WES), or a combination thereof.

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