CN117448438A - Gene Panel for detecting vascular malformation of central nervous system, kit and application - Google Patents

Gene Panel for detecting vascular malformation of central nervous system, kit and application Download PDF

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CN117448438A
CN117448438A CN202311112309.5A CN202311112309A CN117448438A CN 117448438 A CN117448438 A CN 117448438A CN 202311112309 A CN202311112309 A CN 202311112309A CN 117448438 A CN117448438 A CN 117448438A
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洪韬
姜晨旦
任健
于嘉兴
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Abstract

The invention provides a gene Panel for detecting central nervous system vascular malformations, which comprises familial spongiform vascular malformations, sporadic spongiform vascular malformations, arteriovenous malformations, central nervous system angioblastoma related genes, other genes related to various central nervous system vascular malformations and potential pathway key genes, adopts few genes to realize accurate and efficient sequence detection on selected genes so as to acquire mutation information thereof, aims at effectively attributing cerebral hemorrhage in people, then detects the genes related to various central nervous system vascular malformations to detect germ line level or pathological tissue level, can detect somatic mutation with low mutation abundance, accurately evaluates recurrent related bleeding related genetic risks related to the central nervous system vascular malformations according to detection results, guides user symptom monitoring and family early screening conditions, and accordingly effectively predicts and treats patients and risk patients.

Description

Gene Panel for detecting vascular malformation of central nervous system, kit and application
Technical Field
The invention relates to the technical field of central nervous system vascular malformation polygene detection, in particular to a gene Panel for detecting multiple central nervous system vascular malformations, a kit and application thereof.
Background
The central nervous system vascular malformation is a generic name of a group of congenital neurovascular diseases which occur in the central nervous system and mainly manifest as abnormal vascular clusters due to abnormal vascular development, and is mainly represented by high-flow arteriovenous malformations (Arteriovenous Malformation, AVM) and low-flow spongiform vascular malformations (Cavernous Malformation, CM), which are main causes of hemorrhagic stroke in young people and cause heavy burden to home society. With the progress of genetic mechanism research in recent years, the related genes of main central nervous system vascular malformations have been mainly recognized by domestic and foreign team achievements including research of the core role of KRAS/BRAF mutation found by the team of the applicant in dispersing central nervous system AVM, the core mechanism of MAP3K3 and PIK3CA mutation in dispersing central nervous system CM and the like. These key genes are closely related to clinical pathology typing of patient lesions, familial genetic risk and potential drug treatment; therefore, accurate detection of driving gene mutation of central nervous system vascular malformation becomes a key for accurate treatment.
Currently, direct or indirect means for accurately detecting genes include Sanger sequencing (first generation sequencing), RT-PCR (real-time polymerase chain reaction), IHC (immunohistochemistry), FISH (fluorescence in situ hybridization), MLPA (multiplex ligation probe amplification technique), HRM (high resolution melting curve), high throughput sequencing (NGS), etc., which enable gene detection by direct DNA detection, or indirect protein detection.
The Sanger sequencing is a classical method and is also a gold standard for sequencing, but the technology only can obtain a short sequence at a given position by single reaction, so that the sequencing flux is low and the purpose is high; although its single reaction is inexpensive, it is less than optimal in terms of parallelism; at the same time Sanger sequencing has low sensitivity, and mutation abundance is generally detected only at more than 20%, which is very important for somatic mutation. RT-PCR and HRM can only detect known sites and cannot find unknown sites. IHC is mainly used for detecting protein expression, is the detection of downstream functions of genes, and cannot directly detect the mutation of DNA itself. FISH detection is a gold standard for identifying gene Fusion (Fusion) and amplification (CNV), but is not applicable to detection of SNV/Indel, and has the problem of lower resolution; MLPA was also used for CNV detection, defect was similar to FISH. Compared with the technology, the high-throughput sequencing (NGS) technology which is rapidly developed in recent years has the advantages of high throughput (detecting several genes to hundreds of genes or even complete genome at one time), high sensitivity, lower detection limit and stronger exploration capability, and can discover unknown mutation and detect multiple mutation types (SNV/Indel/Fusion/CNV) at one time. The comprehensive guidance on accurate treatment can be realized only by one-time detection.
NGS products currently on the market for detecting DNA are numerous, mainly detecting Whole Genome (WGS), whole Exome (WES) and custom Panel sequencing. For vascular malformations of the central nervous system, the prior researches show that the gene mutation forms are various, part of disease types are germ line mutation, and part of disease types are somatic mutation. The known genetic mutations causing vascular malformation of the central nervous system are all located in the exon region, so WGS and WES can be considered to be completely consistent in terms of test effect, and are represented by WES.
The existing gene Panel is not designed aiming at vascular malformation, and the existing product only can cover partial genes related to central nervous system vascular malformation, and still has the defect of sequencing coverage insufficiency.
Because the proportion of vascular malformations with somatic mutations in the diseased population is not low, the vascular malformations are dominant in part of high-disease species, the abundance of the mutations is various, and the abundance of the mutations of part of patients can be reduced to 1% or even lower, which puts higher demands on the lower detection limit of detection means.
The mutation abundance is low, and the requirement of the detection lower limit is high. For example, in the detection of sporadic cases of arteriovenous malformations, lesions are detected in digital PCR (ddPCR) units to detect pathogenic mutations
KRAS: NM_001369786: exon2: c.G35A: p.G12D abundance is 5%, and the line sequencing device verifies that the site mutation is KRAS: NM_001369786: exon2: c.G35A: p.G12D, consistent and abundance is 4%. In the WES sequencing of a large number of cases in the early stage, the applicant finds that somatic mutations of a series of diseases such as sporadic cerebral spinal artery and vein malformations, sporadic spongiform vascular malformations, angioblastoma and the like all see cases ranging from 1 to 10%, and the current research considers that the somatic mutations are related to the cell type from which the lesions originate and are common phenomena.
Full exon sequencing (WES) covers comprehensively, and can detect sequences of almost all coding DNA in a sample at one time, but in contrast, the sequencing coverage depth is low, and common products are 100× or 300×; conventional whole genome-level NGS is not the optimal choice for mutation detection around 1% taking into account systematic errors of the sequencing method itself. WES covers comprehensively, but sequencing depth is low and error is easy.
The customized Panel has unique technical advantages in terms of significantly reduced gene number and higher sequencing depth than the whole genome, and the sequencing depth on the target gene can reach more than 1000 x-2000 x, which is definitely very advantageous for detecting mutation with low abundance.
The gene per se of the Panel reduces the number of genes to the greatest extent on the basis of completely covering the pedigree of the disease, the existing commercialized Panel scale of the general tumor which can be completely covered is positioned on hundreds of genes (such as the iGeneTech T364V1 641 gene and the GENETRON Onco PanScan 831 gene), and the coverage of the foreign central nervous system Panel similar to the number of the Panel on vascular malformations is poor; so the sequencing depth is increased, corresponding mutation can be measured, and in the detection of 14 lesions (from ddPCR, WES and pantumor Panel detection results respectively) and 5 normal control samples, the measured mutation sites are consistent with the earlier detection, and the mutation abundance is basically consistent.
The existing sequencing Panel is mainly focused on the tumor field, and the genes of the vascular malformation of the central nervous system are only partially overlapped and cannot meet the requirements; a small amount of foreign Panel sequencing products for CNS vascular malformations are focused on familial hereditary diseases, but key genes of several major diseases of CNS vascular malformations discovered in recent years are not covered, and the detection application range is limited.
Disclosure of Invention
In order to solve the technical problems, the applicant provides a gene Panel for detecting vascular malformations of the central nervous system, wherein the gene Panel comprises hereditary vascular malformations related genes of the central nervous system, sporadic vascular malformations related genes of the central nervous system, hereditary peripheral vascular malformations related genes, sporadic peripheral vascular malformations related genes, vascular development and function related genes, vascular malformation risk related genes found by NGS and central nervous system occupation differential diagnosis genes;
wherein the hereditary central nervous system vascular malformation related genes comprise KRIT1, CCM2, PDCD10, RASA1 and EPHB4;
wherein the sporadic central nervous system vascular malformation-related genes comprise MAP3K3, PIK3CA, BRAF, KRAS, MAP2K1, VHL, CCND1, GNA14, GNAQ;
wherein the hereditary peripheral vascular deformity-related genes include actrl 1, ENG, BMPR2, GDF2, TEK, PTEN, GLMN, SMAD4, GNA11, COL3A1, PIEZO1, CCBE1, ANTXR1, FLT4KDR, CELSR1, DOCK6, DLL4, STAMBP, ELMO2;
wherein the sporadic peripheral vascular malformation-associated genes comprise VEGFC, PIK3CA, AKT1, AKT2, AKT3, TEK, KRAS, NRAS, HRAS, GNA, MAP3K3, GJC2;
wherein the vascular development and function related genes include ADGRA2, ANGPT1, CCM2L, CAV1, CTNNB1, EFEMP2, FOXC2, FGFR3, FGFR1, GJA4, GATA2, HGF, MTOR, KCNK3, PDGFRB, PIK3R1, PIK3R2, PKD1, STK11, VEGFA, VCAN;
wherein the vascular malformation risk related genes discovered by NGS include ARAF, CCND2, CDKN1C, CTNNB1, DCHS1, FGFR2, FAT4, MAP2K3, MAP2K7, MET, KIF11, PTPN14, SMO, SOX18;
wherein the central nervous system occupancy differential diagnosis genes comprise IDH1 and IDH2.
Wherein, according to hereditary central nervous system vascular malformation related genes, whether the hereditary central nervous system related genes are familial hereditary central nervous system related genes or whether the germ line mutations are determined; according to sporadic central nervous system vascular malformation related genes, whether the genes are of non-familial hereditary central nervous system types or whether the genes are systemic somatic mutations can be judged; judging that the somatic mutation is generated according to sporadic peripheral vascular malformation related genes; judging whether the gene is related to the known potential pathogenic genes related to vascular development and function according to the vascular development and function related genes; judging whether other pathogenic risk causes are possible according to the vascular malformation risk related genes found by NGS; judging whether the central nervous system related tumor lesions with similar image performance possibly exist or not according to the central nervous system occupation differential diagnosis genes.
The NGS is Next Generation Sequencing, second generation sequencing.
In the above gene Panel for detecting vascular abnormalities of the central nervous system, the gene genes are further refined and typed as follows:
gene grouping genes
Spongiform vascular malformations (familial) KRIT1, CCM2, PDCD10;
spongy vascular malformation (sporadic) MAP3K3, PIK3CA;
arteriovenous malformation BRAF, KRAS, MAP K1;
hereditary telangiectasia ACVRL1 ENG, BMPR2, GDF2;
von Hippel-Lindau syndrome VHL, CCND1;
the epidural spongiform vascular deformities GNA14, GNAQ;
PTEN hamartoma syndrome PTEN;
hereditary cutaneous mucosal venous malformation TEK;
globoid cell venous malformation GLMN;
capillary malformation arteriovenous malformation 1-RASA 1;
juvenile polyps, hereditary telangiectasia syndrome SMAD4;
capillary malformation arteriovenous malformation 2-type EPHB4;
venous malformation TEK, PIK3CA;
protein syndrome AKT1, AKT2, AKT3;
clodes syndrome PIK3CA;
Sturge-Weber syndrome GNAQ;
megabrain-capillary malformation syndrome PIK3CA;
warty vein deformity MAP3K3;
lymphatic malformations PIK3CA, GJC2, PIEZO1, VEGFC;
capillary proliferative granuloma KRAS, NRAS, HRAS, BRAF, GNA;
Klippel-Trenaunay syndrome PIK3CA;
non-regressive and partially regressive congenital hemangioma GNAQ, GNA11;
blue rubber blister mole syndrome TEK;
multifocal venous malformation TEK;
carbocisid lymphoma disease NRAS;
Gorham-Stout syndrome KRAS;
infant capillary hemangioma ANTXR1, FLT4, KDR;
hennekam lymphangiogenesis CCBE1;
lymphatic vessel malformation 9 type CELSR1;
congenital connective tissue hypoplasia syndrome, vascular COL3A1;
primary endosteal vascular malformation ELMO2;
Adams-Oliver syndrome DLL4, DOCK6;
small head malformation-capillary hemangioma syndrome STAMBP;
less wool-lymphedema-telangiectasia syndrome SOX18;
primary endosteal vascular malformation ELMO2;
vascular development and function related ADGRA2, ANGPT1, CCM2L, CAV, CTNNB1, EFEMP2, FOXC2, FGFR3, FGFR1, GJA4, GATA2, HGF, MTOR, KCNK3, PDGFRB, PIK3R1, PIK3R2, PKD1, STK11, VEGFA, VCAN;
vascular malformation risk related genes ARAF, CCND2, CDKN1C, CTNNB1, DCHS1, FGFR2, FAT4, MAP2K3, MAP2K7, MET, KIF11, PTPN14 and SMO discovered by NGS;
central nervous system occupancy differential diagnostic genes include IDH1, IDH2.
The summary is table 1:
TABLE 1 genotyping
The techniques for obtaining the sequences of the above genes and detecting mutations are conventional in the art, and therefore will not be described in detail.
The genes are all derived from 77 human genes.
The above gene groupings are based on literature reports of different genes, and can infer relevant symptoms and genetic probabilities associated with the genes.
The application method of the gene panel comprises the following steps: and determining the gene sequences of different samples, wherein the standard for determining the mutation is that a sample sequencing result is compared with a human standard reference genome, and the gene locus sequencing result is different from the human standard reference genome, and the mutation with the mutation abundance of more than 1% is positive mutation, so that the high-risk pathogenesis gene is determined.
For example: the superposition of somatic mutation of PIK3CA H1047R and MAP3K 3I 441M in example 1 meets the common mutation of sporadic spinal spongiform vascular malformations of the patient, and can not be transmitted to offspring, and meanwhile, the higher bleeding risk of the patient can be deduced according to the test result.
PDCD10 gene mutation, namely CCM3, familial spongiform vascular malformation type 3. Patients carrying the pathogenic mutation show multiple cerebral spongiform vascular genes, can inherit, and have an autosomal dominant inheritance mode, so that the family members of the patients all recommend gene detection and periodical cerebral magnetic resonance examination to discover lesions early and prevent severe cerebral hemorrhage lethal disability.
VHL gene mutation, von Hippel-Lindau syndrome pathogenic genes, manifested as multiple, familial, multiple organ involvement benign and malignant tumor syndromes, wherein the central nervous system is manifested as multiple sub-cerebellar-level angioblastomas, peripheral organ lesions include renal clear cell carcinoma and cysts, pheochromocytomas, pancreatic tumors, etc.; wherever the first symptom is located, genetic testing and assessment of other possible sites of disease should be performed, and family members also suggest testing to discover disease early and to do genetic counseling. However, central nervous system angioblastomas are not entirely caused by VHL germ line mutations, some of which are very rarely known, and which are inherited.
In the invention, genes in the category of vascular malformation risk related genes discovered by NGS are based on the early-stage whole exon sequencing data of the center and are not recorded by other similar products. Vascular development and functionally related gene populations are rarely involved in similar products, but these genes are functionally pathogenic and mutations in some of them are detectable in clinical cases in this center. The knowledge about the remaining genes is published information. Therefore, the method has more comprehensive gene coverage in detecting vascular abnormalities of the central nervous system than other types of panel sequencing.
The standard of the genetic variation is that after the sequencing result is compared with a human standard reference genome (GRCh 37/hg19 or GRCh38/hg 38), the sequencing result of the genetic locus is different from the reference genome, and the false positive result caused by the special structure of an external gene sequence is eliminated from the sequencing quality control and comparison quality control passing result, and the mutation with the mutation abundance of more than 1% is considered as positive mutation.
The gene list sources of the invention are mainly based on three parts:
(1) Genes related to vascular abnormalities of the central nervous system in the OMIM (Online Mendelian Inheritance in Man, online human mendelian inheritance) database;
(2) Relevant genes in PubMed recording literature.
(3) The disease-related gene is obtained by sequencing the whole exon in the early stage of the team. (specific types of genes and test patterns see the examples)
The Panel sequencing covers the following genes related to vascular malformation of the central nervous system:
the invention further provides application of the gene Panel in preparing a kit for detecting vascular malformations of the central nervous system.
The invention further provides application of the gene Panel in constructing a device for evaluating the genetic risk of vascular malformation of the central nervous system.
In the above application, the apparatus comprises:
the sequencing module is used for extracting the DNA of the sample to be tested, and carrying out high-throughput sequencing to obtain a sequencing result;
the analysis module is used for carrying out bioinformatics analysis on the sequencing result of the high-throughput sequencing to obtain mutation information of the detection sample;
and the comparison module is used for comparing the mutation information with the gene detected by the gene Panel in claim 1 to judge the pathogenicity and the clinical value of the mutation.
The technical effects are as follows:
compared with WES technology, the gene panel provided by the invention has the advantages that the effect of detecting low-abundance genes is improved, and the detection depth is increased.
Comparison of technical characteristics
TABLE 2 advantage of detecting Gene Panel
The technical application is as follows:
the gene Panel applied to the field of nervous system vascular malformation for the first time belongs to a brand new application for detecting the nervous system vascular malformation gene Panel.
Detailed Description
The following examples serve to further illustrate the invention but are not limiting thereof.
Example 1
A differential diagnosis gene comprising hereditary central nervous system vascular malformation related genes, sporadic central nervous system vascular malformation related genes, hereditary peripheral vascular malformation related genes, sporadic peripheral vascular malformation related genes, vascular development and function related genes, vascular malformation risk related genes found by NGS;
wherein the hereditary central nervous system vascular malformation related genes comprise KRIT1, CCM2, PDCD10, RASA1 and EPHB4;
wherein the sporadic central nervous system vascular malformation-related genes comprise MAP3K3, PIK3CA, BRAF, KRAS, MAP2K1, VHL, CCND1, GNA14, GNAQ;
wherein the hereditary peripheral vascular deformity-related genes include actrl 1, ENG, BMPR2, GDF2, TEK, PTEN, GLMN, SMAD4, GNA11, COL3A1, PIEZO1, CCBE1, ANTXR1, FLT4KDR, CELSR1, DOCK6, DLL4, DOCK6, STAMBP, ELMO2;
wherein the sporadic peripheral vascular malformation-associated genes comprise VEGFC, PIK3CA, AKT1, AKT2, AKT3, TEK, KRAS, NRAS, HRAS, GNA, MAP3K3, GJC2;
wherein the vascular development and function related genes comprise ADGRA2, ANGPT1, CCM2L, CAV1, CDKN1C, CTNNB, EFEMP2, FOXC2, FGFR3, FGFR1, GJA4, GATA2, HGF, MTOR, KCNK3, PDGFRB, PIK3R1, PIK3R2, PKD1, STK11, VEGFA, VCAN;
wherein the vascular malformation risk related genes discovered by NGS include ARAF, CCND2, CTNNB1, DCHS1, FGFR2, FAT4, MAP2K3, MAP2K7, MET, KIF11, PTPN14, SMO, SOX18;
wherein the central nervous system occupancy differential diagnosis genes comprise IDH1 and IDH2.
Example 2
A detection kit developed according to example 1, the gene of the gene panel of claim 1 is delegated to Ai Jitai Kangshensu (Beijing) Biotechnology Co., ltd for gene probe design, and related detection kits are constructed, the kit comprises library construction reagents, sequencing platform adaptors and primers, hybridization capture reagents, capture magnetic beads, which are well known in the art, detection mutation results are related to the selected gene, and sequence alignment software and automatic analysis software (e.g., trimmomatic, BWA, samtools, GATK, varScan, ANNOVAR, pysam) are also well known in the art.
Example 3
Sample overview
The lesions were from spinal spongiform vascular malformation patients, numbered ZBJ, who received neurosurgical excision of the lesions, and were freshly frozen tissue for review.
Sample processing
The pathological specimens of the lesions were fresh frozen tissue, and the DNA was first extracted using the BunnyMag kit. The Qubit3.0 quantitative instrument can accurately quantify the concentration of DNA, and the total DNA amount is more than 50ng.
Sequencing flow
The genomic DNA was digested (IGT) TM Enzyme Plus Library Prep Kit v 2.0.2.0) or ultrasonic random Interrupt (IGT) TM Fast Library Prep Kit v 2.0.0) into a fragment of 150-250 bp; using IGT TM Adapter&DNA fragmented by UDI Primer 1-96 (for Illumina, plate) is subjected to end repair, 3' end is added with ' A '; the joints are connected; sample marking and DNA enrichment are carried out by a PCR amplification method; the library with specific index constructed by the steps is hybridized with DNA probe marked by biotin in liquid phaseTarget Probes T725V2, hybridization probe), the combination between biotin-avidin has the characteristics of rapidness, specificity and stability, and the streptavidin marked magnetic beads are used to obtain the Target gene exon (TargetSeq>Hyb&Wash Kit v2.0 with Eco Universal Blocking Oligo(for Illumina)、/>Cap Beads&nucleic-Free Water), and then enrichment of the target gene is performed by PCR amplification.
Library quantification was performed using Qubit3.0 (Thermo sammer flier Qubit3.0 fluorometer), library concentration >25 ng/. Mu.l reference was used as a qualified library;
library requirements: the Qsep 100 detection is used, the main peak of the library is about 220-450bp, and the main peak is free from impurity peaks before and after the main peak.
1 μl of library was quantified using Qubit dsDNA HS Assay Kit and library concentrations were recorded, with library concentrations ranging from about 1-20 ng/. Mu.l;
taking 1 μl of library sample, and performing library fragment length measurement by using Qsep 100, wherein the library length is about 220-450 bp; sequencing was performed using a high throughput sequencing platform.
The sequencing platform adopts: illunima NovaSeq 6000, target data volume 1G.
Data analysis (conventional in the art)
Quality control and evaluation: the method is carried out by using trimmonic software, and mainly comprises two parts of sequencing quality evaluation and library quality evaluation, wherein quality control is usually accompanied in the evaluation process, and sequencing joints and partial low-quality sequences are removed. The evaluation result is usually reflected on some important performance indexes, such as indexes of Q20, Q30, comparison rate, repetition rate, coverage rate, capturing rate, uniformity and the like, so that whether the data are qualified or not can be effectively evaluated.
And (3) comparison: sequences assessed by quality were aligned to a reference genome using bwa, samtools software, and base quality was corrected by GATK software (e.g., using parameters: baseRecalifier- -knock-gates 1000G_phase1. Index. B37.Vcf- -knock-gates Mills- -and- -1000 G_gold_standard. Index. B37.Vcf- -knock-gates dbnp- -138.b37.vcf ApplyBQSR), tag repeat (using GATK MarkDeplicates- -remove-sequencing-duplex tree).
And (3) mutation detection: the difference (i.e., variation) between the true data and the reference genome was compared using samtools, varScan, GATK software, and the detected mutations were annotated using ANNOVAR software.
Site-directed mutagenesis detection: combining with clinical information, the potential sites of high pathogenicity are estimated, all the potential sites of pathogenicity are scanned, the base composition proportion and quality of each site are recorded, and the potential low abundance mutation is judged.
And (3) interpretation: according to the proportion of the detected sites, the molecular typing of the diseases is given, and the clinical prognosis advice and the family genetic risk are given.
The quality control results obtained are as follows.
The specific values are shown in Table 3.
TABLE 3 Gene Panel test results
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94% of sequencing data is qualified in quality, 99% of sequencing data can be successfully compared to a human reference genome, the coverage of a target sequence reaches 100%, the average coverage depth of the target sequencing reaches 2598x, the expected coverage depth is more than 1000x, and the WES method is remarkably superior to the WES method.
The detection condition of the somatic mutation at the 1 position is detected by the data after comparison, the position is the mutation of chr3:178952085:A > G, and the mutation abundance is about 5%; the PIK3CA hypermutant gene was identified, and MAP3K3 mutation was confirmed, as shown in Table 4.
TABLE 4 Critical site depth detection results
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Conclusion: the sample carries PIK3CA H1047R and MAP3K 3I 441M overlapped somatic mutation, accords with common mutation of sporadic spinal spongiform vascular malformations of the patient, cannot be inherited to offspring, and has higher bleeding risk.
Example 4
Sample overview
The lesions are from patients with arteriovenous malformations, the number is YDC, the patients receive neurosurgery excision lesions, and the specimens are fresh frozen tissues for inspection.
Sample processing
The pathological specimens of the lesions were fresh frozen tissue, and the DNA was first extracted using the BunnyMag kit. The Qubit3.0 quantitative instrument accurately quantifies the concentration of DNA, the total amount of DNA is more than 50ng, and the requirement of library establishment is met.
The sequencing procedure is described in example 3.
The results are shown in Table 5.
TABLE 5 Gene Panel test results
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84% of sequencing data is qualified in quality, 99% of sequencing data can be successfully compared to a human reference genome, the coverage of a target sequence reaches 100%, the average coverage depth of the target sequencing reaches 1479x, the expected coverage depth is more than 1000x, and the WES method is remarkably superior.
The detection condition of 1 part of somatic mutation is detected by the data after comparison, and the locus is chr12:25398284:G > A mutation, and the mutation abundance is about 4%; the KRAS hypermutant gene was identified.
TABLE 6 Critical site depth detection results
Conclusion: the sample carries KRAS G12D somatic mutation, accords with common mutation of sporadic arteriovenous malformations of the patient, has definite pathology and can not be inherited to offspring. The sample is subjected to tumor gene Panel and ddPCR in the early stage, the tumor Panel mutation abundance return of the site is 6.57%, and the mutation abundance detected by ddPCR is 5.61%, which is basically consistent with the result obtained by the method.
Example 5
Sample overview
Lesions were from a brain spongiform vascular malformation patient, accession number ZJJ, who received neurosurgical excision of lesions, and were sampled in fresh frozen tissue for review.
Sample processing
The pathological specimens of the lesions were fresh frozen tissue, and the DNA was first extracted using the BunnyMag kit. The Qubit3.0 quantitative instrument accurately quantifies the concentration of DNA, the total amount of DNA is more than 50ng, and the requirement of library establishment is met.
The sequencing procedure was as in example 3.
The results are shown in Table 7.
TABLE 7 Panel detection results
/>
94% of sequencing data is qualified in quality, 99% of sequencing data can be successfully compared to a human reference genome, the coverage of a target sequence reaches 100%, the average coverage depth of the target sequencing reaches 1655x, the expected coverage depth is more than 1000x, and the WES method is remarkably superior to the WES method.
The content of the obtained assembled genome BAM file is subjected to data after comparison, the germ line mutation at 1 part is detected, and the locus is chr 7:91855572:G > A mutation, and the mutation abundance is about 48.2%; the hypermutated gene identified as KRIT 1. See table 8.
TABLE 8 Critical site depth detection results
Conclusion: the sample carries KRIT1 (CCM 1) termination mutation, the mutation proportion is about 48.2%, the mutation is germ line mutation, the conventional database judges that the mutation is pathogenic mutation, the mutation accords with common mutation of cerebral spongiform vascular malformation of the patient, family genetics exist, the gene can be inherited to offspring, the probability of the gene transmitted to the offspring is about 50%, and the probability of the offspring suffering from the disease is about 1/2 because the pathogenic mode of the gene is autosomal dominant inheritance.
Example 6
Depth of coverage
The basic principle of the NGS sequencing technology, including the whole exon sequencing technology and the Panel sequencing technology, is that short DNA fragments are sequenced in parallel at high throughput, so that the sequencing result is composed of millions or even tens of millions of short sequence fragments with 150 bases. These fragments overlap to form the complete genomic sequence. Sequencing depth refers to how many times it is covered by NGS sequencing fragments at one genomic location, as the source of DNA for the sequencing itself is a multitude of cells in the sample, so different sequencing fragments represent the result that may be from different nuclear DNA; therefore, as the sequencing depth increases, it will be possible for the results to present more information from different cells, which is also the basis for somatic mutation detection. For mutations of low abundance, i.e. where only a few cells carry the mutation, a higher sequencing depth is more advantageous for detecting these mutations. Common WES sequencing depths are typically 100x or 300x.
The sequencing results under 300x whole exon sequencing were compared with the sequencing results of the present Panel. Detection was performed on 186 samples, respectively, and coverage selected all of the full exon regions of the target area. An average representation of its depth of coverage can be obtained. At the sequencing depth, the total target region length of the Panel is 165283bp, the Panel reaches 2592x at the average sequencing depth, which is far higher than 179x of WES (whole exon sequencing); considering that repeated amplification may exist during library amplification in the sequencing process, the sequencing result of the part is substantially produced by the same DNA fragment and is nonsensical repetition, so that the repeated removal treatment is needed, the effective sequencing depth is only needed after the repeated removal, and the average effective depth of the Panel can still reach 1383x after the repeated sequences in the sequencing process are removed. See table 9.
TABLE 9 sequencing depth alignment
Coverage area
The sequencing results under 300x whole exon sequencing were compared with the sequencing results of the present Panel. Detection was performed on 186 samples, respectively, and coverage selected all of the full exon regions of the target area. The average performance of its coverage can be obtained as shown in table 9. In terms of sequencing quality, each measurement index is more than 95% effective and is similar to WES. For the coverage of the target region (namely the included vascular malformation related genes), 1000x coverage can be realized by the Panel in 79% of the region, the coverage rate of WES (we) in 1000x is only 0.02%, even if the coverage rate is reduced to 300x, the coverage rate is only less than 15%, and the coverage rate of the Panel in 300x is 92.99%. For the possible missing areas, the present Panel is only less than 0.01%, while WES is 0.27%.
The sequencing depth refers to the total number of bases obtained by sequencing per the size of the genome to be tested, and is one of indexes for evaluating the sequencing quantity. Assuming that the number of coverage bases of one panel is 2.0M and the sequencing depth is 500X, the total amount of data obtained is 1.0G. See table 10.
TABLE 10 sequencing Range and sequencing Effect depth
In combination, the Panel has lower cost and deeper coverage than WES in finishing the detection of vascular malformation genes; compared with the commonly considered gold standard digital PCR, the PCR has more comprehensive coverage and has the vital capacity of discovering new mutation; compared with the traditional Panel for tumor detection, the Panel realizes targeted coverage, and the full coverage of vascular malformation genes is realized under the design of only 1/8 of the main flow tumor detection Panel scale (hundreds of genes of the main flow tumor); the targeted design also enables the high-throughput data processing calculation force requirement and the time cost to be obviously reduced.
The Panel realizes the full coverage of the central nervous vascular deformity and covers the known peripheral vascular deformity related genes. Such gene inclusion is based on the following considerations: 1. peripheral vascular malformation causative genes are associated with vascular function and development, and potential central nervous system causative possibilities exist. 2. Diseases that are considered in part to be mainly peripheral vascular malformations may involve the central nervous system, such as hereditary telangiectasia, typically present with peripheral vascular malformations, but at the same time arteriovenous malformations of the central nervous system may occur. 3. The application range is enlarged, and the method can be applied to detection of peripheral vascular malformation related genes while detecting central nervous system vascular malformation.
The Panel has prospective incorporated genes related to potential pathogenicity which have not been reported to be clearly pathogenic, but are found in functional and clinical tests, and the genes have correlation with diseases, which are closely related to angiogenesis structures on pathogenic molecules and biochemical mechanisms or are shown in WES sequencing results of a large number of cases in the early stage.
The full design flow aims at the pathological change characteristics of the central nervous system vascular diseases from probe design, data processing to analysis and interpretation so as to adapt to the characteristic that somatic mutation with low mutation abundance is common, and the omission of the low-abundance mutation is reduced to the maximum extent. The method has originality in data processing, and realizes the detection of mutations which are difficult to find in conventional mutation searching by outputting full information of key pathogenic sites.
The application adds related genes discovered by the sequencing of the whole exons in the early stage of the center:
taking MAP2K7 as an example, the subject group carried out an integration analysis on 205 sporadic spongiform vascular malformation WES sequencing data, removed two main pathogenic mutations known as MAP3K3 and PIK3CA, and found that MAP2K7 mutation of MAPK signaling pathway also occurred in 16% of patients, and more than half of them did not accompany known pathogenic mutation. Mutations were less than 1/10000 in the population database and the resulting amino acid changes were concentrated at amino acid numbers 54, 221, 389. The above-described behavior suggests that MAP2K7 may have a direct or indirect relationship with sporadic spongiform vascular abnormalities. In the same manner, the newly added genes of the inventor are vascular development and function related gene groups and vascular malformation risk related gene groups discovered by NGS.
Wherein the vascular development and function related genes include ADGRA2, ANGPT1, CCM2L, CAV1, CTNNB1, EFEMP2, FOXC2, FGFR3, FGFR1, GJA4, GATA2, HGF, MTOR, KCNK3, PDGFRB, PIK3R1, PIK3R2, PKD1, STK11, VEGFA, VCAN; among them, the vascular malformation risk related genes found by NGS include ARAF, CCND2, CDKN1C, CTNNB1, DCHS1, FGFR2, FAT4, MAP2K3, MAP2K7, MET, KIF11, PTPN14, SMO, SOX 18), which are also important theoretical basis established in the present application.

Claims (7)

1. The gene Panel for detecting the vascular malformation of the central nervous system is characterized by comprising hereditary central nervous system vascular malformation related genes, sporadic central nervous system vascular malformation related genes, hereditary peripheral vascular malformation related genes, sporadic peripheral vascular malformation related genes, vascular development and function related genes, vascular malformation risk related genes discovered by NGS and central nervous system occupation differential diagnosis genes;
wherein the hereditary central nervous system vascular malformation related genes comprise KRIT1, CCM2, PDCD10, RASA1 and EPHB4;
wherein the sporadic central nervous system vascular malformation-related genes comprise MAP3K3, PIK3CA, BRAF, KRAS, MAP2K1, VHL, CCND1, GNA14, GNAQ;
wherein the hereditary peripheral vascular deformity-related genes include actrl 1, ENG, BMPR2, GDF2, TEK, PTEN, GLMN, SMAD4, GNA11, COL3A1, PIEZO1, CCBE1, ANTXR1, FLT4KDR, CELSR1, DOCK6, DLL4, STAMBP, ELMO2;
wherein the sporadic peripheral vascular malformation-associated genes comprise VEGFC, PIK3CA, AKT1, AKT2, AKT3, TEK, KRAS, NRAS, HRAS, GNA, MAP3K3, GJC2;
wherein the vascular development and function related genes comprise ADGRA2, ANGPT1, CCM2L, CAV1, CDKN1C, CTNNB, EFEMP2, FOXC2, FGFR3, FGFR1, GJA4, GATA2, HGF, MTOR, KCNK3, PDGFRB, PIK3R1, PIK3R2, PKD1, STK11, VEGFA, VCAN;
wherein the vascular malformation risk related genes discovered by NGS include ARAF, CCND2, CTNNB1, DCHS1, FGFR2, FAT4, MAP2K3, MAP2K7, MET, KIF11, PTPN14, SMO, SOX18;
wherein the central nervous system occupancy differential diagnosis genes comprise IDH1 and IDH2.
2. The gene Panel for detecting vascular abnormalities of the central nervous system according to claim 1, characterized in that said genes are respectively classified as:
gene grouping genes
Spongiform vascular malformations (familial) KRIT1, CCM2, PDCD10;
spongy vascular malformation (sporadic) MAP3K3, PIK3CA;
arteriovenous malformation BRAF, KRAS, MAP K1;
hereditary telangiectasia ACVRL1, ENG, BMPR2, GDF2;
von Hippel-Lindau syndrome VHL, CCND1;
the epidural spongiform vascular deformities GNA14, GNAQ;
PTEN hamartoma syndrome PTEN;
hereditary cutaneous mucosal venous malformation TEK;
globoid cell venous malformation GLMN;
capillary malformation arteriovenous malformation 1-RASA 1;
juvenile polyps, hereditary telangiectasia syndrome SMAD4;
capillary malformation arteriovenous malformation 2-type EPHB4;
venous malformation TEK, PIK3CA;
protein syndrome AKT1, AKT2, AKT3;
clodes syndrome PIK3CA;
Sturge-Weber syndrome GNAQ;
megabrain-capillary malformation syndrome PIK3CA;
warty vein deformity MAP3K3;
lymphatic malformations PIK3CA, GJC2, PIEZO1, VEGFC;
capillary proliferative granuloma KRAS, NRAS, HRAS, BRAF, GNA; klippel-Trenaunay syndrome PIK3CA;
non-regressive and partially regressive congenital hemangioma GNAQ, GNA11; blue rubber blister mole syndrome TEK;
multifocal venous malformation TEK;
carbocisid lymphoma disease NRAS;
Gorham-Stout syndrome KRAS;
infant capillary hemangioma ANTXR1, FLT4, KDR;
hennekam lymphangiogenesis CCBE1;
lymphatic vessel malformation 9 type CELSR1;
congenital connective tissue hypoplasia syndrome, vascular COL3A1;
primary endosteal vascular malformation ELMO2;
Adams-Oliver syndrome DLL4, DOCK6; small head malformation-capillary hemangioma syndrome STAMBP;
less wool-lymphedema-telangiectasia syndrome SOX18;
primary endosteal vascular malformation ELMO2;
vascular development and function related ADGRA2, ANGPT1, CCM2L, CAV1, CDKN1C, CTNNB1, EFEMP2, FOXC2, FGFR3, FGFR1, GJA4, GATA2, HGF, MTOR, KCNK3, PDGFRB, PIK3R1, PIK3R2, PKD1, STK11, VEGFA, VCAN;
vascular malformation risk related genes ARAF, CCND2, CTNNB1, DCHS1, FGFR2, FAT4, MAP2K3, MAP2K7, MET, KIF11, PTPN14 and SMO discovered by NGS;
central nervous system occupancy differential diagnostic genes include IDH1, IDH2.
3. The gene Panel for detecting vascular abnormalities of the central nervous system according to claim 1, characterized in that said genes are all derived from 77 genes of human origin.
4. The gene Panel for detecting vascular abnormalities of the central nervous system according to claim 1, characterized in that the method of use of said gene Panel: and determining the gene sequences of different samples, wherein the standard for determining the mutation is that a sample sequencing result is compared with a human standard reference genome, and the gene locus sequencing result is different from the human standard reference genome, and the mutation with the mutation abundance of more than 1% is positive mutation, so that the high-risk pathogenesis gene is determined.
5. Use of a gene Panel according to claim 1 for the preparation of a kit for detecting vascular abnormalities of the central nervous system.
6. Use of a gene Panel according to claim 1 for constructing a device for assessing the genetic risk of vascular malformations in the central nervous system.
7. The use of a gene Panel according to claim 6, wherein the device comprises:
the sequencing module is used for extracting the DNA of the sample to be tested, and carrying out high-throughput sequencing to obtain a sequencing result;
the analysis module is used for carrying out bioinformatics analysis on the sequencing result of the high-throughput sequencing to obtain mutation information of the detection sample;
and the comparison module is used for comparing the mutation information with the gene detected by the gene Panel in claim 1 to judge the pathogenicity and the clinical value of the mutation.
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