Gene combination for detecting hemangioma and vascular malformation and application thereof

Abstract

The invention relates to a gene combination for detecting hemangioma and vascular malformation and application thereof. 62 genes Panel closely related to hemangioma and vascular deformity are excavated, and the Panel comprises a DNA detection gene and an RNA detection gene, and can be effectively applied to identification of hemangioma and vascular deformity driving gene mutation, genetic susceptibility genes and fusion genes which possibly exist, so that pathologists are guided to clear pathological diagnosis and typing; according to the gene detection panel for the hemangioma and the vascular malformation, the target treatment selection and genetic risk evaluation and screening of a patient are guided, the blank of lack of the gene detection panel special for the hemangioma and the vascular malformation at present is filled, the detection rate and sensitivity of the hemangioma and the vascular malformation are improved, and the problems of misdiagnosis and missed diagnosis caused by easy omission of the current detection panel are effectively solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of gene detection, and relates to a gene combination for detecting hemangiomas and vascular malformations and an application thereof. Background Art

[0002] Hemangiomas and vascular malformations, collectively referred to as vasculature, encompass nearly 100 diseases, including benign and malignant tumors arising from the extracranial / peripheral vascular lumen, various vascular / lymphatic malformations, and unclassified conditions. Hemangiomas are benign or malignant tumors caused by the proliferation of vascular endothelial cells or an increase in angiogenic tissue. Their primary clinical manifestation is red or purple patchy lesions on the skin or mucous membranes, which may or may not be accompanied by pain. These lesions are usually confined to a single organ or tissue, and their symptoms are relatively mild. Vascular malformations are congenital diseases characterized by structural abnormalities of the vascular vessels. They are usually present at birth, and their clinical manifestations vary depending on the location of the lesion. Common symptoms include pain, numbness, and paresthesia. Lesions are often extensive, affecting multiple organs and tissues, and therefore can be more severe.

[0003] Studies have shown that most types of vascular lesions are caused by germline and / or somatic mutations in germ cells, including systemic / germline mutations or gene fusions in genes such as KRAS, NRAS, HRAS, BRAF, GNAQ, GNA11, GNA14, RASA1, ACVRL1, CAMTA1, and FOS. Hemangiomas and vascular malformations caused by different gene mutations exhibit significant differences in clinical manifestations and treatment approaches. For example, the PIK3CA-related overgrowth spectrum (PROS) is caused by activating mutations in the PIK3CA gene, and clinical manifestations depend on the timing, location, and intensity of the mutation. Currently, 47 PIK3CA mutations at different loci have been identified in PROS patients, with p.C420R, p.E542K, p.E545K, p.H1047R, and p.H1047L being the most frequently observed mutations in PROS. Due to the numerous and heterogeneous clinical manifestations, the incidence of PROS is significantly underestimated, making diagnosis and management particularly challenging.

[0004] Classification is the basis for the treatment of hemangiomas and vascular malformations. Misclassification may lead to inappropriate selection of treatment methods, which not only affects the patient's appearance, but may also cause complications. Currently, there is no genetic testing panel specifically for hemangiomas and vascular malformations on the market. Although high-throughput sequencing (NGS) large panel tests can cover hundreds of genes / sites in one test, they do not cover all the relevant genes for hemangiomas and vascular malformations, and are easily missed, resulting in misdiagnosis and missed diagnosis, affecting the patient's accurate diagnosis and correct treatment. In addition, due to the large detection area, the sequencing cost is high, the detection price is expensive, and data is wasted. Therefore, the development of a genetic testing panel for hemangiomas and vascular malformations is one of the research hotspots in the field of hemangioma and vascular malformation diagnosis. For example, CN117448438A discloses a gene panel for detecting central nervous system vascular malformations, but its diagnostic efficacy and applicability are limited.

[0005] In summary, developing targeted, systematic, and comprehensive new molecular detection panels and expanding diagnostic tools are of great significance in the diagnosis of hemangiomas and vascular malformations. Summary of the Invention

[0006] In response to the deficiencies of the existing technology and actual needs, the present invention provides a gene combination for detecting hemangiomas and vascular malformations and its application.

[0007] To achieve this object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a gene combination for detecting hemangiomas and vascular malformations, wherein the gene combination includes DNA detection genes and RNA detection genes, and the DNA detection genes include ACVRL1, AKT1, AKT2, AKT3, ARAF, ATM, BRAF, CBL, CCBE1, CCM2, ELMO2, ENG, EPHB4, FAT4, FLT1, FLT4, FOXC2, GATA2, GDF2, GJC2, GLMN, GNA11, GNA14, GNAQ, GNAS, HGF, HRAS, IDH1, IDH2, KDR, KIF11, KRAS, KRIT1, MAP2K1, MAP2K2, MAP3K3, and MAPK1. , MAPK3, MET, MTOR, MYC, NF1, NF2, NOTCH3, NPM1, NRAS, PDCD10, PDGFRB, PIK3CA, PIK3R1, PTEN, PTPN14, RAF1, RASA1, SMAD4, SOX18, STAMBP, TEK, TP53, TSC1, TSC2, VEGFC; the RNA detection genes include: CAMTA1, EPC1, FOS, FOSB, FOXO1, GATA6, MAML2, MIR143, NOTCH1, NOTCH2, NOTCH3, PHC2, PTBP1, RELA, SERPINE1, SRF, TFE3, WWTR1, YAP1.

[0009] The present invention targets the detection of hemangiomas and vascular malformations, explores 62 genes closely related to hemangiomas and vascular malformations, and designs a gene panel for detecting hemangiomas and vascular malformations. This panel can be effectively used to identify possible hemangioma and vascular malformation driving gene mutations, genetic susceptibility genes, and fusion genes, guide pathologists in clarifying pathological diagnosis and typing, guide patients in targeted treatment selection, genetic risk assessment and screening, etc., assist in the accurate diagnosis and treatment of vascular diseases while reducing the financial burden on patients.

[0010] In a second aspect, the present invention provides use of the gene combination for detecting hemangiomas and vascular malformations and / or its detection reagents described in the first aspect in the preparation of products for detecting hemangiomas and vascular malformations.

[0011] In a third aspect, the present invention provides a kit for detecting hemangiomas and vascular malformations, wherein the kit comprises probes for the gene combination for detecting hemangiomas and vascular malformations according to the first aspect.

[0012] Preferably, the kit further comprises at least one of library construction reagents, sequencing platform adapters and primers, hybridization capture reagents or capture magnetic beads.

[0013] In a fourth aspect, the present invention provides use of the gene combination for detecting hemangiomas and vascular malformations and / or its detection reagents described in the first aspect in assisting the detection of hemangiomas and vascular malformations.

[0014] The present invention can be used for non-disease diagnosis applications, such as distinguishing the sources and types of hemangioma and vascular malformation samples, and conducting basic research related to hemangiomas and vascular malformations.

[0015] In a fifth aspect, the present invention provides use of the gene combination for detecting hemangiomas and vascular malformations and / or its detection reagents described in the first aspect in constructing an apparatus for detecting hemangiomas and vascular malformations.

[0016] In a sixth aspect, the present invention provides a device for detecting hemangiomas and vascular malformations, the device comprising:

[0017] A detection module, used for performing second-generation sequencing on cells to be tested;

[0018] A data acquisition module, used to obtain the second-generation sequencing test result data;

[0019] The data analysis module is used to analyze the data acquired by the data acquisition module and determine whether the acquired gene variation is a gene variation with clinical significance for hemangioma and vascular malformation based on predetermined analysis logic and judgment criteria.

[0020] Preferably, the analysis in the data analysis module includes comparing the second-generation sequencing test result data with the human reference genome.

[0021] In the present invention, general analysis software in the field (such as Fastp, Sentieon, Annovar, Manta and Delly, etc.) can be used to determine the gene variation by comparing with the human reference genome, and disease diagnosis and typing can be performed based on the gene variation.

[0022] In a seventh aspect, the present invention provides an electronic device comprising one or more processors and a memory for storing executable instructions, wherein the one or more processors are configured to call the executable instructions stored in the memory to implement the functions of the device for detecting hemangiomas and vascular malformations as described in the sixth aspect.

[0023] In an eighth aspect, the present invention provides a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the functions of the device for detecting hemangiomas and vascular malformations described in the sixth aspect.

[0024] Compared with the prior art, the present invention has at least the following beneficial effects:

[0025] The present invention provides a gene panel and detection kit for detecting hemangiomas and vascular malformations. It designs a standard detection scheme, operating process and analysis method to ensure the accuracy and comparability of the results, assist in the clinical diagnosis of hemangiomas and vascular malformations, and guide patients' targeted treatment selection, genetic risk assessment and screening. DETAILED DESCRIPTION

[0026] The technical solution of the present invention will be further described below by way of specific embodiments. However, the following examples are merely simplified examples of the present invention and do not represent or limit the scope of protection of the present invention, which shall be subject to the claims.

[0027] If no specific techniques or conditions are specified in the examples, the experiments were carried out according to the techniques or conditions described in the literature in the field or according to the product instructions. If no manufacturer is specified for the reagents or instruments used, they are all conventional products that can be purchased through regular channels.

[0028] Example 1

[0029] This embodiment provides a gene panel for detecting hemangiomas and vascular malformations, including DNA detection genes and RNA detection genes. The DNA detection genes include: ACVRL1, AKT1, AKT2, AKT3, ARAF, ATM, BRAF, CBL, CCBE1, CCM2, ELMO2, ENG, EPHB4, FAT4, FLT1, FLT4, FOXC2, GATA2, GDF2, GJC2, GLMN, GNA11, GNA14, GNAQ, GNAS, HGF, HRAS, IDH1, IDH2, KDR, KIF11, KRAS, KRIT1, MAP2K1, MAP2K2, MAP3K3, MAPK1, and MAPK3. , MET, MTOR, MYC, NF1, NF2, NOTCH3, NPM1, NRAS, PDCD10, PDGFRB, PIK3CA, PIK3R1, PTEN, PTPN14, RAF1, RASA1, SMAD4, SOX18, STAMBP, TEK, TP53, TSC1, TSC2, VEGFC; the RNA detection genes include: CAMTA1, EPC1, FOS, FOSB, FOXO1, GATA6, MAML2, MIR143, NOTCH1, NOTCH2, NOTCH3, PHC2, PTBP1, RELA, SERPINE1, SRF, TFE3, WWTR1, YAP1.

[0030] Example 2

[0031] This embodiment provides a kit for detecting hemangiomas and vascular malformations.

[0032] Based on the panel in Example 1, Nanoda Biotechnology Co., Ltd. was commissioned to design gene probes and construct related detection kits, which also include library construction reagents commonly used in the field, sequencing platform adapters and primers, hybridization capture reagents, capture magnetic beads, etc.

[0033] The detection range of the probes for the hemangioma and vascular malformation detection panel is shown in Table 1.

[0034] Table 1

[0035]

[0036] Example 3

[0037] In this example, five fusion-positive clinical samples were used to validate the RNA portion of the panel to determine the detection performance of RNA fusions. The specimens were paraffin tissue samples.

[0038] (1) Sample processing: All five samples were paraffin tissue samples. RNA was first extracted using a magnetic bead-based FFPE RNA extraction kit (Meiji, catalog number IVD3022). The RNA concentration was accurately quantified using a Qubit 4.0 quantifier. The library construction requirement was that the total RNA amount was ≥400 ng.

[0039] (2) Library construction: Total RNA was denatured, fragmented, and reverse transcribed to obtain double-stranded DNA fragments of 300-400 bp. The Fast Stranded RNA Library Prep Kit v2.0 [KY] performs DNA end repair, adds an "A" to the 3' end, and then ligates specific adapters. Samples are labeled and DNA is enriched by PCR amplification. The transcriptome library with a specific index constructed through the above steps is liquid-phase hybridized with biotin-labeled DNA probes (hybridization probes corresponding to RNA detection genes in the panel). The binding between biotin and avidin is rapid, specific, and stable. Streptavidin-biotin-labeled magnetic beads are then used to capture the target gene exons (NadPrep ES HybridCapture Reagents), and target genes are then enriched by PCR amplification. Library quantification is performed using the Qubit 4.0 (Thermo Fisher Scientific Qubit 4.0 Fluorometer), and library length is measured using the Qsep 100.

[0040] Library requirements: Use Qsep 100 detection, the main peak of the library should be around 250-550bp, and there should be no mixed peaks before and after the main peak.

[0041] Take 1 μL of library for use Quantification was performed using a 1× dsDNA HS Assay Kit, and the library concentration was recorded. The library concentration was ≥20 ng / μL (total amount ≥800 ng);

[0042] Take 1 μL library sample and use Qsep 100 to measure the library fragment length. The library length is approximately between 250-550 bp; sequence it using a high-throughput sequencing platform.

[0043] (3) Use Illunima NovaSeq 6000 sequencer for sequencing, with a target data volume of 4G.

[0044] (4) Bioinformatics analysis: The RNA sequencing results are compared with the human reference genome to determine the mutation of the sample gene. Sequence alignment software and automatic analysis software can be Fastp, Sentieon, Annovar, Manta, Delly, etc.

[0045] The bioinformatics software listed in Table 2 was used for data analysis.

[0046] Table 2

[0047] software Software version Function Fastp v0.23.2 Remove the connector Sentieon STAR v202112.04 Sequence alignment Arriba v2.3.0 Detection of gene fusion variants STAR-Fusion v1.10.0 Detection of gene fusion variants

[0048] Quality control and assessment: Fastp software is used for this process, primarily encompassing sequencing quality assessment and library quality assessment. This assessment is often accompanied by quality control, including the removal of sequencing adapters and some low-quality sequences. The assessment results are typically reflected in several key performance indicators. Taking into account the actual sample sequencing quality and the requirements for accurate variant detection by the variant detection software, the quality control thresholds for sequencing data are shown in Table 3.

[0049] Table 3

[0050]

[0051] Alignment: Use STAR and samtools software to align the quality-assessed sequences to the reference genome.

[0052] Fusion gene detection: Arriba and STAR-Fusion software were used to identify fusion events in transcripts by comparing the differences between real data and the reference genome based on the STAR aligner.

[0053] (5) Site-directed mutation detection: Combined with the known positive site information of clinical samples, scan all fusions included in this detection panel and record the number of reads detected for each key fusion.

[0054] The specific values ​​of the quality control results obtained are shown in Table 4.

[0055] Table 4

[0056] Experiment No. Total RNA amount (ng) Number of valid reads 1 2856 29.271 2 3150 26.652 3 2870 30.04 4 3024 22.724 5 2653 69.58

[0057] The key fusion detection results obtained are shown in Table 5.

[0058] Table 5

[0059]

[0060]

[0061] Conclusion: The fusion variants in 5 clinical samples can be stably detected with an accuracy of 100%.

[0062] Example 4

[0063] Sample Overview: ctDNA standards from Shenzhen Jingliang Gene Technology Co., Ltd. were used. Product Name: ctDNA Quality Control Kit for Tumor Minimal Residual Lesion Detection (Cat. No.: GW-OCTM800). The test was performed to validate the hemangioma and vascular malformation gene panel to determine the actual detection performance of the gene portion of the panel DNA test for hemangioma and vascular malformation gene mutations.

[0064] (1) Sample processing: The ctDNA standard was serially diluted to 0.5%, 0.25%, and 0.1%;

[0065] (2) Library construction: using C10022 DNA was end-repaired and 3'-end amplified using the Fast Library Prep Kit v2.0; adapter ligation was performed; sample labeling and DNA enrichment were performed via PCR amplification. The library with specific indices constructed through these steps was then subjected to liquid-phase hybridization with biotin-labeled DNA probes (hybridization probes corresponding to the DNA detection genes in the panel). The rapid, specific, and stable nature of biotin-avidin binding was exploited. Streptavidin-biotin-labeled magnetic beads were then used to capture target gene exons (NadPrep ES Hybrid Capture Reagents), followed by PCR amplification for target gene enrichment. Library quantification was performed using a Qubit 4.0 (Thermo Fisher Scientific) fluorometer, and library length was determined using a Qsep 100.

[0066] Library requirements: Use Qsep 100 detection, the main peak of the library should be around 310bp, and there should be no mixed peaks before and after the main peak.

[0067] Take 1 μL of library for use Quantify the library using a 1× dsDNA HS Assay Kit and record the library concentration, which should be approximately ≥20 ng / μL (total volume ≥800 ng).

[0068] 1 μL of library sample was taken and the library fragment length was measured using Qsep 100. The library length was approximately 310 bp. Sequencing was performed using a high-throughput sequencing platform.

[0069] (3) Use Illunima NovaSeq 6000 sequencer for sequencing, with a target data volume of 10G.

[0070] (4) Bioinformatics analysis: The DNA sequencing results are compared with the human reference genome to determine the mutation status of the sample gene (a conventional technique in this field).

[0071] Table 6 Bioinformatics software was used for data analysis.

[0072] Table 6

[0073] software Software version use Function Fastp v0.23.2 Cut Adapter Remove the connector Sentieon v202112.04 Reads mapping Sequence alignment and detection of SNV / Indel variations annovar v2020 SNV / Indel annotation Annotation of SNV / Indel variants

[0074] Quality control and assessment: This is performed using Fastp software and primarily involves sequencing quality assessment and library quality assessment. This assessment is often accompanied by quality control, including the removal of sequencing adapters and low-quality sequences. The assessment results are typically reflected in several key performance indicators. Taking into account the actual sample sequencing quality and the requirements for accurate variant detection by the variant detection software, the quality control thresholds for sequencing data are shown in Table 7.

[0075] Table 7

[0076]

[0077] Alignment: Use bwa and samtools software to align the quality-assessed sequences to the reference genome, and use sentieon software to correct base quality and mark duplications.

[0078] Variant detection: samtools and sentieon software were used to compare the differences (i.e., variants) between the real data and the reference genome, and ANNOVAR software was used to annotate the detected mutations.

[0079] (5) Site-directed mutation detection: Combined with the instructions for the standard product, scan all positive pathogenic sites included in this test panel, record the base composition ratio and quality of each site, and determine possible low-abundance mutations.

[0080] The positive sites of the site-directed mutation ct standard are shown in Table 8.

[0081] Table 8

[0082] List of point mutation genes Amino acid mutation CDS mutations AKT1 p.E17K c.49G>A BRAF p.V600K c.1798_1799delinsAA BRAF p.V600E c.1799T>A IDH1 p.R132G c.394C>G IDH2 p.R172M c.515G>T KRAS p.G12C c.34G>T KRAS p.G12D c.35G>A KRAS p.Q61H c.183A>C KRAS p.G13D c.38G>A NRAS p.Q61R c.182A>G NRAS p.G12A c.35G>C PIK3CA p.H1047R c.3140A>G TP53 p.R273H c.818G>A

[0083] The quality control results obtained are shown in Table 9.

[0084] Table 9

[0085]

[0086]

[0087] The key site detection results obtained are shown in Table 10.

[0088] Table 10

[0089]

[0090] Conclusion: SNV / Indel variants with mutation frequencies of 0.5% and 0.25% can be stably detected with an input of 66 ng, and the detection rate of SNV / Indel variants with a mutation frequency of 0.1% is 92.3%.

[0091] Example 5

[0092] Sample Overview: Genetic variation analysis was performed on a single sample (diagnosed with hemifacial hypertrophy with erythema and arteriovenous malformation) using both a large NGS panel (detection range shown in Table 11) and the panel for hemangiomas and vascular malformations of this invention (detection range shown in Table 1). This validated the important role of this panel in guiding pathologists in clarifying pathological diagnoses and typing, guiding patients in targeted treatment selection, and assessing and screening for genetic risk. In this case, a paraffin section sample paired with peripheral blood was tested.

[0093] Table 11

[0094]

[0095]

[0096]

[0097] (1) Sample processing: In this case, paraffin sections and peripheral blood samples were paired for testing. DNA was extracted from paraffin sections using the Universal DNA Extraction Kit Type I (MeiGen, Catalog No. IVD3101). DNA was extracted from peripheral blood using the RC1001 Nucleic Acid Extraction and Purification Reagent. RNA was extracted using the FFPE RNA Extraction Kit (MeiGen, Catalog No. IVD3022). DNA and RNA concentrations were accurately quantified using the Qubit 4.0 quantifier.

[0098] (2) RNA library construction process refers to Example 2;

[0099] DNA library construction: using The EZ DNA Library Preparation Module v2 [KY] kit is used to digest tissue DNA and peripheral blood DNA for library construction. DNA fragmentation is performed first, so that the gDNA fragments are distributed within the range of 200-300bp. End repair and 3'-end "A" addition are then performed. Adapter ligation is then performed. Index and P5 and P7 sequences are then added to both ends of the library through PCR amplification, and the library is enriched. Finally, magnetic beads are used for library purification. The library with double-ended specific indexes constructed through the above steps is liquid-phase hybridized with biotin-labeled DNA probes. The binding between biotin and avidin is rapid, specific, and stable. Streptavidin-biotin-labeled magnetic beads are then used to obtain the target gene exons, and PCR amplification is then used to enrich the target library. Library quantification is performed using a Qubit4.0 (Thermo Fisher Scientific Qubit4.0 Fluorometer), and library length is detected using a Qsep 100.

[0100] Library requirements: Use Qsep 100 detection, the main peak of the library should be around 250-550bp, and there should be no mixed peaks before and after the main peak.

[0101] Take 1 μL of library and quantify it using Qubit dsDNA HS Assay Kit. Record the library concentration. The library concentration should be ≥10 ng / μL (total amount >300 ng / μL).

[0102] 1 μL of the final library (post-capture library) sample was taken and the library fragment length was measured using Qsep 100. The library length was approximately between 250-550 bp, with no impurity peaks before and after the main peak. Sequencing was performed using a high-throughput sequencing platform.

[0103] (3) Illunima NovaSeq 6000 sequencer was used for sequencing, with the target data volumes of RNA, tissue DNA, and peripheral blood DNA being 4G, 4G, and 1.5G, respectively.

[0104] (4) Bioinformatics analysis: The DNA sequencing results are compared with the human reference genome to determine the mutation status of the sample gene.

[0105] Data analysis was performed using bioinformatics software as shown in Table 12.

[0106] Table 12

[0107] software Software version Function Fastp v0.23.2 Remove the connector Sentieon v202112.04 Sequence alignment and detection of SNV / Indel variations annovar v2020 Annotation of SNV / Indel variants manta v1.6.0 Detection of gene fusion variants delly V0.8.1 Detection of gene fusion variants Sentieon STAR v202112.04 Sequence alignment Arriba v2.3.0 Detection of gene fusion variants STAR-Fusion v1.10.0 Detection of gene fusion variants

[0108] Quality control and assessment: This is performed using Fastp software and primarily involves sequencing quality assessment and library quality assessment. This assessment is often accompanied by quality control to remove sequencing adapters and some low-quality sequences. The assessment results are typically reflected in several key performance indicators. Taking into account the actual sample sequencing quality and the requirements for accurate variant detection by the variant detection software, the quality control thresholds for sequencing data are shown in Table 13.

[0109] Table 13

[0110]

[0111]

[0112] Alignment: Use bwa and samtools software to align the quality-assessed sequences to the reference genome, and use sentieon software to correct base quality and mark duplications.

[0113] Variant detection: samtools and sentieon software were used to compare the differences (i.e., variants) between the real data and the reference genome, and ANNOVAR software was used to annotate the detected mutations.

[0114] Fusion gene detection: Arriba and STAR-Fusion software were used to identify fusion events in transcripts by comparing the differences between real data and the reference genome based on the STAR aligner.

[0115] (5) Site-specific mutation detection: Combine clinical information to infer highly pathogenic sites and scan all possible pathogenic sites.

[0116] Record the base composition ratio and quality of each site to determine possible low-abundance mutations.

[0117] (6) Interpretation: Based on the proportion of detected sites, the molecular classification of the disease is given, and clinical prognosis recommendations and family genetic risks are given.

[0118] The quality control results obtained are shown in Table 14.

[0119] Table 14

[0120]

[0121] In the hemangioma and vascular malformation panel of the present invention, 92.99% / 94.73% of the tissue and peripheral blood sequencing data met the quality standards, 99.82% / 99.64% of the tissue and peripheral blood sequencing data could be successfully aligned to the human reference genome, and the average target sequencing coverage depth of tissue and peripheral blood reached 4004.18X / 2697.89X, passing quality control.

[0122] The obtained test results are shown in Table 15.

[0123] Table 15

[0124]

[0125] Conclusion: The large NGS panel for common solid tumors failed to detect the EPHB4 p.R365* mutation, while the hemangioma and vascular malformation panel of this invention detected the germline EPHB4 p.R365* mutation. Existing databases have determined that the EPHB4 stop mutation is a pathogenic mutation. The EPHB4 germline pathogenic variant is associated with capillary malformation-arteriovenous malformation (CM-AVM2), an autosomal dominant genetic disease. Combined with the patient's clinical condition, this suggests that the patient's disease has a familial hereditary nature and effectively guides the patient's genetic risk assessment.

[0126] In summary, the present invention discloses a gene panel, a kit and its application for detecting hemangiomas and vascular malformations, which has discovered 62 genes closely related to hemangiomas and vascular malformations. The panel includes DNA detection genes and RNA detection genes, specifically including single nucleotide variations (SNVs), small fragment deletions and insertions (indels), and copy number variations (CNVs) of some genes, and simultaneously performs paired germline mutation detection on 36 genes closely related to hemangiomas and vascular malformations; RNA sequencing fusion gene detection of 19 fusion genes related to vascular tumors can be effectively used to identify possible hemangioma and vascular malformation driving gene mutations, genetic susceptibility genes and fusion genes, guide pathologists to clarify pathological diagnosis and typing, guide patients in targeted treatment selection, genetic risk assessment and screening, fill the gap in the market for the lack of genetic detection panels specifically for hemangiomas and vascular malformations, improve the detection rate and sensitivity of hemangiomas and vascular malformations, and effectively solve the problem that current detection panels are easily missed, causing misdiagnosis and missed diagnosis.

[0127] The applicant declares that the above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention fall within the scope of protection and disclosure of the present invention.

Claims

1. A gene combination for detecting hemangiomas and vascular malformations, characterized in that: The gene combination includes DNA detection genes and RNA detection genes, and the DNA detection genes include ACVRL1, AKT1, AKT2, AKT3, ARAF, ATM, BRAF, CBL, CCBE1, CCM2, ELMO2, ENG, EPHB4, FAT4, FLT1, FLT4, FOXC2, GATA2, GDF2, GJC2, GLMN, GNA11, GNA14, GNAQ, GNAS, HGF, HRAS, IDH1, IDH2, KDR, KIF11, KRAS, KRIT1, MAP2K1, MAP2K2, MAP3K3, MAPK1, MAPK3, MET, MTOR, MYC, NF1, NF2, NOTCH3, NPM1, NRAS, PDCD10, PDGFRB, PIK3CA, PIK3R1, PTEN, PTPN14, RAF1, RASA1, SMAD4, SOX18, STAMBP, TEK, TP53, TSC1, TSC2, VEGFC; the RNA detection genes include: CAMTA1, EPC1, FOS, FOSB, FOXO1, GATA6, MAML2, MIR143, NOTCH1, NOTCH2, NOTCH3, PHC2, PTBP1, RELA, SERPINE1, SRF, TFE3, WWTR1, YAP1.

2. Use of the gene combination for detecting hemangiomas and vascular malformations and / or its detection reagent according to claim 1 in the preparation of products for detecting hemangiomas and vascular malformations.

3. A kit for detecting hemangiomas and vascular malformations, characterized in that: The kit comprises the probe of the gene combination for detecting hemangioma and vascular malformation according to claim 1.

4. The kit for detecting hemangioma and vascular malformation according to claim 3, characterized in that: The kit further comprises at least one of library construction reagents, sequencing platform adapters and primers, hybridization capture reagents or capture magnetic beads.

5. Use of the gene combination for detecting hemangiomas and vascular malformations and / or its detection reagent according to claim 1 in assisting the detection of hemangiomas and vascular malformations.

6. Use of the gene combination for detecting hemangiomas and vascular malformations and / or its detection reagent according to claim 1 in constructing an apparatus for detecting hemangiomas and vascular malformations.

7. A device for detecting hemangiomas and vascular malformations, characterized in that: The device comprises: A detection module, used for performing second-generation sequencing on cells to be tested; A data acquisition module, used to obtain the second-generation sequencing test result data; The data analysis module is used to analyze the data acquired by the data acquisition module and determine whether the acquired gene variation is a gene variation with clinical significance for hemangioma and vascular malformation based on predetermined analysis logic and judgment criteria.

8. The device for detecting hemangiomas and vascular malformations according to claim 7, characterized in that: The analysis in the data analysis module includes comparing the second-generation sequencing test result data with the human reference genome.

9. An electronic device comprising one or more processors and a memory for storing executable instructions, characterized in that: The one or more processors are configured to call the executable instructions stored in the memory to implement the functions of the device for detecting hemangiomas and vascular malformations according to claim 7 or 8.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the functions of the device for detecting hemangiomas and vascular malformations according to claim 7 or 8 are realized.

Images