CN109706065A - Tumor neogenetic antigen load detection device and storage medium - Google Patents
Tumor neogenetic antigen load detection device and storage medium Download PDFInfo
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Abstract
A kind of tumor neogenetic antigen load detection device and storage medium, the detection device include: data capture unit, for obtaining the sequencing data of tumor tissues DNA, the check sample DNA of test object and the targeted capture region of tumor tissues RNA;Somatic variation detection unit carries out variation detection for the sequencing data to tumor tissues DNA and check sample DNA and annotation obtains mutation peptide fragment;Fusion detection unit carries out fusion detection for the sequencing data to tumor tissues RNA and annotation obtains mutation peptide fragment;HLA parting detection unit, the sequencing data for the targeted capture region to check sample DNA carry out HLA parting;MHC affinity predicting unit, for predicting neoantigen using HLA parting testing result to mutation peptide fragment;TNB computing unit, for calculating TNB;With result output unit, for exporting TNB testing result.The present invention can be used in the monitoring of tumor neogenetic antigen cutting load testing, predict immunologic test point inhibitor curative effect.
Description
Technical field
The present invention relates to lesion detection technical fields, and in particular to a kind of tumor neogenetic antigen load detection device and storage
Medium.
Background technique
Tumour is the disease as caused by genome mutation.Immunologic test point inhibitor opens the new era of oncotherapy,
But due to lacking suitable clinical molecular marker, PD-1/PD-L1 (apoptosis receptor -1, programmed
Death-1, PD-1;Apoptosis ligand -1, programmed cell death ligand 1, PD-L1) drug
Beneficiaries can not efficiently be screened, and screening rate only has 20%-30%.The potential clinical molecular marker packet having now been found that
PD-L1 expression, tumor neogenetic antigen load etc. are included, these molecular markers can be used for the treatment effect of predicted portions patient
Fruit, but still have not applicable situation.Tumor neogenetic antigen load (TNB) is potential neoantigen number in direct reflection tumour cell
One index of amount, usually carrys out table with the tumor neogenetic antigen sum for including in the Oncogenome region of every megabase (Mb)
Show.TNB is directly related with tumour immunity, and existing research shows that the horizontal of high TNB can maximum probability prediction lung cancer, bladder cancer, black
The tumours such as plain tumor are to immunologic test point inhibitor medicaments response probability, and effect is better than other markers.
As molecular marker, clinically there is the demand of efficiently and accurately detection TNB.It there is no such mature production currently on the market
Product, the method that research aspect generallys use full sequencing of extron group, with defect at high cost, that the period is long, unsuitable clinic is answered
With.Urgently develop corresponding efficient detection method.
Summary of the invention
The present invention provides a kind of tumor neogenetic antigen load detection device and storage medium, can be used in tumor neogenetic antigen
Cutting load testing monitoring, predicts immunologic test point inhibitor curative effect.
According in a first aspect, providing a kind of tumor neogenetic antigen load detection device, the detection device in a kind of embodiment
Include:
Data capture unit, for obtaining tumor tissues DNA, the check sample DNA and tumor tissues RNA of test object
The sequencing data in targeted capture region;
Somatic variation detection unit, for the targeted capture region to above-mentioned tumor tissues DNA and check sample DNA
Sequencing data carries out variation detection to find somatic mutation, and above-mentioned somatic mutation is annotated and calculated mutational site
Front and back first sets the situation of change of the amino acid of quantity, as mutation peptide fragment;
Fusion detection unit, the sequencing data for the targeted capture region to above-mentioned tumor tissues RNA melt
Genetic test is closed to find fusion, and above-mentioned fusion is annotated and calculated the second setting number before and after position of fusion
The situation of change of the amino acid of amount, as mutation peptide fragment;
HLA parting detection unit, the sequencing data for the targeted capture region to above-mentioned check sample DNA carry out HLA
Parting is to obtain HLA parting testing result;
MHC affinity predicting unit, it is newborn anti-for being predicted using above-mentioned HLA parting testing result above-mentioned mutation peptide fragment
Original is to find potential neoantigen;
TNB computing unit, for calculating TNB:TNB=N/R according to following formula, wherein N is neoantigen quantity, and R is
The practical sequencing area size in targeted capture region;With
As a result output unit, for exporting above-mentioned TNB testing result.
In a preferred embodiment, above-mentioned check sample is selected from cancer beside organism or peripheral blood sample.
In a preferred embodiment, above-mentioned first quantity is set as 8-11;Above-mentioned second sets quantity as 8-11.
In a preferred embodiment, above-mentioned HLA parting detection unit is also used to the targeted capture to above-mentioned tumor tissues DNA
The sequencing data in region carries out HLA parting to obtain HLA parting testing result.
In a preferred embodiment, above-mentioned detection device further include:
The horizontal detection unit of mutation expression, sequencing data for the targeted capture region to above-mentioned tumor tissues RNA
Mutation is detected whether there is on RNA with the mutation judged on DNA.
In a preferred embodiment, above-mentioned potential neoantigen is affinity < 500nM and wild type peptide in above-mentioned mutation peptide fragment
Section affinity > 500nM peptide fragment.
In a preferred embodiment, above-mentioned targeted capture region is captured by targeted capture chip, above-mentioned targeted capture chip
Equipped with targeted capture probe, above-mentioned targeted capture probe obtains by the following method:
(1) gene expression information collected according to COSMIC database counts the gene expressed in tumor sample
As candidate gene;
(2) base of exon each on above-mentioned candidate gene is replaced with into mutating alkali yl that may be present one by one, to replacing
Nucleotide sequence after changing is annotated, and takes the peptide fragment of mutational site front and back predetermined quantity amino acid composition as potential mutant peptide
Section;
(3) statistics Chinese population HLA genotype frequency distribution, obtains the highest HLA genotype of frequency of setting quantity, makees
Genotype is represented for Chinese population;
(4) genotype is represented according to the Chinese population of setting quantity to every above-mentioned potential mutation peptide fragment and carries out MHC respectively
Affinity prediction;
(5) statistics is carried out to all affinity prediction results and obtains potential neoantigen peptide fragment;
(6) its mutational site is recalled to every above-mentioned potential neoantigen peptide fragment, if above-mentioned site is located at COSMIC data
In library, then scope of design is included in the site, if above-mentioned site is located at listed base in Cancer Gene Census list of genes
Because upper, scope of design also is included in the site;
(7) the design bit number of points that each exon includes on genome are calculated, and by above-mentioned design bit number of points by height
To low sequence, choosing total size is the exon that is sized as chip capture region;With
(8) above-mentioned capture probe is designed according to said chip capture region.
In a preferred embodiment, above-mentioned targeted capture region includes the capture region of gene as shown in table 1 below:
Table 1
Above-mentioned capture region can be captured by the capture chip designed based on Oncogenome database, capture chip
Size is 1.6M.Above-mentioned capture region can really reflect the variation tendency of tumor neogenetic antigen load on people's full-length genome.
In a preferred embodiment, above-mentioned targeted capture region further includes the polymorphic site for the pairs of Quality Control of sample, on
State polymorphic site be rs1327118, rs1402695, rs1414904, rs1131498, rs1079820, rs1805087,
rs1032807、rs1801262、rs1515002、rs1392265、rs11096957、rs1426003、rs1363333、
rs3734440、rs156318、rs1843026、rs1368136、rs1105176、rs156697、rs12828016、
Rs1395936, rs1541836, rs1805034, rs1030687, rs171953, rs753381, rs1293153 and
Rs1541290, the tumor tissues and check sample that above-mentioned polymorphic site ensures to detect are from same test object.
According to second aspect, a kind of tumor neogenetic antigen load detection device, the detection device are provided in a kind of embodiment
Include:
Memory, for storing program;
Processor realizes following tumor neogenetic antigen load inspection for the program by executing above-mentioned memory storage
Survey method:
Obtain the survey of tumor tissues DNA, the check sample DNA of test object and the targeted capture region of tumor tissues RNA
Ordinal number evidence;
To the sequencing data in the targeted capture region of above-mentioned tumor tissues DNA and check sample DNA carry out variation detection with
It was found that somatic mutation, and above-mentioned somatic mutation is annotated and is calculated the amino of the first setting quantity before and after mutational site
The situation of change of acid, as mutation peptide fragment;
Fusion detection is carried out to find fusion base to the sequencing data in the targeted capture region of above-mentioned tumor tissues RNA
Cause, and above-mentioned fusion is annotated and is calculated the situation of change that position of fusion front and back second sets the amino acid of quantity,
As mutation peptide fragment;
HLA parting is carried out to the sequencing data in the targeted capture region of above-mentioned check sample DNA to obtain the detection of HLA parting
As a result;
To above-mentioned mutation peptide fragment using above-mentioned HLA parting testing result prediction neoantigen to find potential neoantigen;
TNB:TNB=N/R is calculated according to following formula, wherein N is neoantigen quantity, and R is the reality in targeted capture region
Area size is sequenced in border;With
Export above-mentioned TNB testing result.
According to the third aspect, a kind of computer readable storage medium, including program are provided in a kind of embodiment, the program energy
It is enough executed by processor to realize following tumor neogenetic antigen load testing method:
Obtain the survey of tumor tissues DNA, the check sample DNA of test object and the targeted capture region of tumor tissues RNA
Ordinal number evidence;
To the sequencing data in the targeted capture region of above-mentioned tumor tissues DNA and check sample DNA carry out variation detection with
It was found that somatic mutation, and above-mentioned somatic mutation is annotated and is calculated the amino of the first setting quantity before and after mutational site
The situation of change of acid, as mutation peptide fragment;
Fusion detection is carried out to find fusion base to the sequencing data in the targeted capture region of above-mentioned tumor tissues RNA
Cause, and above-mentioned fusion is annotated and is calculated the situation of change that position of fusion front and back second sets the amino acid of quantity,
As mutation peptide fragment;
HLA parting is carried out to the sequencing data in the targeted capture region of above-mentioned check sample DNA to obtain the detection of HLA parting
As a result;
To above-mentioned mutation peptide fragment using above-mentioned HLA parting testing result prediction neoantigen to find potential neoantigen;
TNB:TNB=N/R is calculated according to following formula, wherein N is neoantigen quantity, and R is the reality in targeted capture region
Area size is sequenced in border;With
Export above-mentioned TNB testing result.
Tumor neogenetic antigen load detection device of the invention distinguishes tumor tissues and check sample DNA sequencing result
It is compared, carries out somatic variation detection using the two, while carrying out HLA gene point using check sample DNA sequencing result
Type, and tumor tissues RNA sequencing result is compared, detect Gene Fusion and expression status.It is carried out based on the above results
Neoantigen prediction, finally obtains tumor neogenetic antigen load.The present invention can accurately reflect tumor neogenetic antigen load in sample
Situation.This method is to targeted capture region rather than full exon detects, under the premise of meeting detection accuracy, effectively
Sequencing data amount is reduced, cost is reduced.
Detailed description of the invention
Fig. 1 is the tumor neogenetic antigen load detection device structural block diagram of the embodiment of the present invention;
Fig. 2 is that experiment flow figure is sequenced in the sample of the embodiment of the present invention;
Fig. 3 is the tumor neogenetic antigen load testing method flow chart of the embodiment of the present invention;
Fig. 4 is to use full exon region (WES) and this respectively to Chinese population cancer of the esophagus sample in the embodiment of the present invention
Chip design section (Panel) detection mutation (Mutation) and neoantigen (Neoantigen Type) quantity of invention
(Number per Mb) result figure;
Fig. 5 is that patient receives the survivorship curve after immunization therapy in the embodiment of the present invention, and abscissa is the time after treatment
(moon, Months), ordinate are the ratio (Percent Progression-Free) of patient's Progression free survival, show high TNB
Group has significantly different with the survival rate of low TNB group, can be used for distinguishing immunization therapy effective (Effective) and in vain
(Ineffective) patient.
Specific embodiment
Below by specific embodiment combination attached drawing, invention is further described in detail.In the following embodiments and the accompanying drawings
In, many datail descriptions are in order to enable the present invention can be better understood.However, those skilled in the art can be without lifting an eyebrow
Recognize, part of feature is dispensed in varied situations, or can be by other elements, material, method institute
Substitution.
It is formed respectively in addition, feature described in this description, operation or feature can combine in any suitable way
Kind embodiment.Meanwhile each step in method description or movement can also can be aobvious and easy according to those skilled in the art institute
The mode carry out sequence exchange or adjustment seen.Therefore, the various sequences in the description and the appended drawings are intended merely to clearly describe a certain
A embodiment is not meant to be necessary sequence, and wherein some sequentially must comply with unless otherwise indicated.
It is herein component institute serialization number itself, such as " first ", " second " etc., is only used for distinguishing described object,
Without any sequence or art-recognized meanings.
As shown in Figure 1, tumor neogenetic antigen load detection device includes: data acquisition list in one embodiment of the invention
First 101, somatic variation detection unit 102, fusion detection unit 103, HLA parting detection unit 104, MHC affinity
Predicting unit 105, TNB computing unit 106 and result output unit 107.It in a preferred embodiment, further include mutation expression level
Detection unit 108.
In the embodiment of the present invention, data capture unit 101, for obtaining tumor tissues DNA, the check sample of test object
The sequencing data in the targeted capture region of DNA and tumor tissues RNA.Test object can be any object, especially anyone,
Including Healthy People and suspected tumor patient.Tumor tissues can be any tumor tissues, including lung cancer, bladder cancer, melanoma
Equal tumor tissues.Check sample can be any nonneoplastic tissue class sample, especially cancer beside organism or peripheral blood sample.This hair
It is bright to be sequenced using targeted capture region rather than whole exon DNA, it is effectively dropped under the premise of meeting detection accuracy
Low sequencing data amount reduces cost.
The embodiment of the present invention, using the sequencing data in targeted capture region, rather than the survey of full-length genome or full exon
Ordinal number evidence.Wherein, targeted capture region is obtained by targeted capture chip, and targeted capture chip is equipped with targeted capture probe, target
Obtain by the following method to capture probe: (1) gene expression information collected according to COSMIC database is counted in tumour sample
The gene expressed in this is as candidate gene, for example, screening criteria are as follows: 50% before expression quantity comes in 50% sample
Gene, in this, as candidate gene;(2) base of exon each on candidate gene is replaced with into mutation that may be present one by one
Base annotates replaced nucleotide sequence, takes predetermined quantity (such as 8-11) amino acid group before and after mutational site
At peptide fragment as potential mutation peptide fragment;(3) statistics Chinese population HLA genotype frequency distribution obtains setting quantity (such as 31
Kind) the highest HLA genotype of frequency, genotype is represented as Chinese population;(4) to every potential mutation peptide fragment according to setting number
Amount (such as 31 kinds) Chinese population represents genotype and carries out MHC affinity prediction respectively, calculates error to eliminate, affinity prediction
(such as calculating respectively using NetMHCpan and MHCflurry software) is respectively calculated using 2 kinds of stand alone softwares;(5) to institute
There is affinity prediction result to carry out statistics and obtain potential neoantigen peptide fragment, for example, taking mutant peptide in 2 kinds of software prediction results
Section prediction affinity is respectively less than 50nM, and it is latent that corresponding wild type peptide fragment prediction affinity, which is all larger than the mutation peptide fragment of 500nM,
In neoantigen peptide fragment;(6) its mutational site is recalled to every potential neoantigen peptide fragment, if site is located at COSMIC database
In, then scope of design is included in this site, if site is located at Cancer Gene Census (oncogene application form) gene column
On table on listed gene, scope of design also is included in this site;(7) the design site that each exon includes on genome is calculated
Quantity, and sort from high to low by design bit number of points, choosing total size is the exon for being sized (such as 1.5M), as
Chip capture region;(8) capture probe is designed according to chip capture region.Above-mentioned targeted capture probe design process, is different from
Method in the prior art can capture to obtain the gene region that can accurately reflect tumor neogenetic antigen load condition in sample.
In one embodiment of the invention, sequencing is carried out using the capture region of gene shown in table 1 (following) and obtains sequencing
Data, and subsequent analysis is carried out, compared to using the sequencing detection of full exon, sequencing data amount is effectively reduced, cost is reduced, and
And it can really reflect tumor neogenetic antigen load.Sequencing data contains the sequencing reading length (reads) in targeted capture region, number
It according to amount may be the size of several G, such as in one embodiment, DNA carried out respectively to tumor tissues and blood check sample
It extracts, build library, captured using targeted capture technology, is sequenced using PE150 sequencing mode, tumor tissues DNA sequencing
The data volume 3.5G of data, the data volume 1.5G of blood check sample sequencing data.In addition, to tumor tissues carry out RNA extraction,
Library is built, is sequenced using PE150 sequencing mode, data volume 12G.
It can be sequenced using any two generations sequencing technologies, such as in one embodiment, be sequenced using Illumina
Technology is sequenced using PE150 sequencing mode.Obtained lower machine sequencing data is sequenced to need by certain pretreatment.For example,
In one embodiment, lower machine sequencing data is by following processing: machine data processing under (a);(b) data filtering and Quality Control;(c)
DNA sequence dna compares and Quality Control;(d) RNA sequence comparison and Quality Control.
In the embodiment of the present invention, somatic variation detection unit 102, for tumor tissues DNA's and check sample DNA
The sequencing data in targeted capture region carries out variation detection to find somatic mutation, and somatic mutation is annotated and counted
The situation of change that mutational site front and back first sets the amino acid of quantity is calculated, as mutation peptide fragment.In one embodiment of the invention,
Somatic variation detection, is carried out using samtools and varscan software, obtains original variation result.In original variation result
It makes a variation comprising more false positive, needs to be filtered.In one embodiment of the invention, Patent No. 201711107001.6 is used
Based on two generations sequencing point mutation detection filter method, device and storage medium and Patent No. 201810273763.1 base
Yu Erdai sequencing insertion and deletion mutation detection methods, device and storage medium patent, according to the base mass value of mutating alkali yl,
It compares mass value, the upper relative position reads, the frequency of mutation, whether be that the factors such as hot spot mutation are for statistical analysis, it is final to determine
True mutation.In one embodiment of the invention, somatic mutation result is annotated using SnpEff annotating software first, is made
It is GENCODE27 with reference to gene set, annotation obtains Gene Name, transcript number and location information, HGVS mutation number
Etc. essential informations.The situation of change for then calculating mutational site front and back 8-11 (the i.e. first setting quantity) amino acid, as prominent
Become peptide fragment.
In the embodiment of the present invention, fusion detection unit 103, for the targeted capture region to tumor tissues RNA
Sequencing data carries out fusion detection to find fusion, and position of fusion front and back is annotated and calculated to fusion
The situation of change of the amino acid of second setting quantity, as mutation peptide fragment.In one embodiment of the invention, fusion is used
RNA comparison result, by Patent No. 201711107002.0 for detect target area Gene Fusion method, apparatus and
Storage medium proprietary algorithms are detected, and are annotated to testing result.Then calculate 8-11 before and after position of fusion (i.e. the
Two setting quantity) amino acid situation of change, as mutation peptide fragment.
In the embodiment of the present invention, HLA parting detection unit 104, the survey for the targeted capture region to check sample DNA
Ordinal number is according to progress HLA parting to obtain HLA parting testing result.In one embodiment of the invention, using bwa-hla and
Polysolver software carries out HLA parting to check sample (blood sample), takes the two intersection as testing result.Preferred real
It applies in example, to eliminate the influence of HLA LOH in tumor tissues, and HLA parting is equally carried out to tumor tissues sample.Therefore, HLA
Parting detection unit is also used to carry out HLA parting to the sequencing data in the targeted capture region of tumor tissues DNA to obtain HLA
Parting testing result.
In the embodiment of the present invention, MHC affinity predicting unit 105, for using HLA parting testing result to mutation peptide fragment
Predict neoantigen to find potential neoantigen.In one embodiment of the invention, aforementioned mutation peptide fragment use is detected
HLA genetype for predicting neoantigen, prediction technique can using application No. is 201810601500.9 based on the sequencing of two generations
Tumor neogenetic antigen detection method, device and storage medium patent.In one embodiment of the invention, take mutation peptide fragment affinity <
500nM and wild type peptide fragment affinity > 500nM peptide fragment are potential neoantigen.
In the embodiment of the present invention, TNB computing unit 106 is used to calculate TNB:TNB=N/R according to following formula, wherein N
For high quality neoantigen quantity (unit is a), high quality neoantigen quantity computation method are as follows: according to previous step to every
The marking of neoantigen is by sorting from large to small, and greater than 0 and before ranking, 20 neoantigen resists selection score for high quality new life
It is former;R is the practical sequencing area size (unit Mb) in targeted capture region.
In the embodiment of the present invention, the horizontal detection unit 108 of mutation expression, for the targeted capture area to tumor tissues RNA
The mutation of the sequencing data in domain is detected whether there is on RNA with the mutation judged on DNA.
It will be understood by those skilled in the art that all or part of function of various methods can pass through in above embodiment
The mode of hardware is realized, can also be realized by way of computer program.When function all or part of in above embodiment
When being realized by way of computer program, which be can be stored in a computer readable storage medium, and storage medium can
To include: read-only memory, random access memory, disk, CD, hard disk etc., it is above-mentioned to realize which is executed by computer
Function.For example, program is stored in the memory of equipment, when executing program in memory by processor, can be realized
State all or part of function.In addition, when function all or part of in above embodiment is realized by way of computer program
When, which also can store in storage mediums such as server, another computer, disk, CD, flash disk or mobile hard disks
In, through downloading or copying and saving into the memory of local device, or version updating is carried out to the system of local device, when logical
When crossing the program in processor execution memory, all or part of function in above embodiment can be realized.
Therefore, one embodiment of the invention provides a kind of tumor neogenetic antigen load detection device, which includes:
Memory, for storing program;Processor, for the program by executing above-mentioned memory storage to realize that following tumour is new
Raw antigen load testing method: the targeting for obtaining the tumor tissues DNA, check sample DNA and tumor tissues RNA of test object is caught
Obtain the sequencing data in region;The sequencing data in the targeted capture region of above-mentioned tumor tissues DNA and check sample DNA is become
Different detection is annotated and is calculated the first setting number before and after mutational site to above-mentioned somatic mutation to find somatic mutation
The situation of change of the amino acid of amount, as mutation peptide fragment;To the sequencing data in the targeted capture region of above-mentioned tumor tissues RNA into
Row fusion is detected to find fusion, and above-mentioned fusion is annotated and calculated position of fusion front and back second and set
The situation of change of the amino acid of fixed number amount, as mutation peptide fragment;To the sequencing number in the targeted capture region of above-mentioned check sample DNA
According to progress HLA parting to obtain HLA parting testing result;Above-mentioned mutation peptide fragment is predicted using above-mentioned HLA parting testing result
Neoantigen is to find potential neoantigen;TNB:TNB=N/R is calculated according to following formula, wherein N is neoantigen quantity, R
For the practical sequencing area size in targeted capture region;With the above-mentioned TNB testing result of output.
One embodiment of the invention provides a kind of computer readable storage medium, including program, which can be processed
Device is executed to realize following tumor neogenetic antigen load testing method: obtaining tumor tissues DNA, the check sample of test object
The sequencing data in the targeted capture region of DNA and tumor tissues RNA;Targeting to above-mentioned tumor tissues DNA and check sample DNA
The sequencing data of capture region carries out variation detection to find somatic mutation, and above-mentioned somatic mutation is annotated and counted
The situation of change that mutational site front and back first sets the amino acid of quantity is calculated, as mutation peptide fragment;To above-mentioned tumor tissues RNA's
The sequencing data in targeted capture region carries out fusion and detects to find fusion, and annotates to above-mentioned fusion
And the situation of change that position of fusion front and back second sets the amino acid of quantity is calculated, as mutation peptide fragment;To above-mentioned check sample
The sequencing data in the targeted capture region of DNA carries out HLA parting to obtain HLA parting testing result;Above-mentioned mutation peptide fragment is made
With above-mentioned HLA parting testing result prediction neoantigen to find potential neoantigen;TNB:TNB=is calculated according to following formula
N/R, wherein N is neoantigen quantity, and R is the practical sequencing area size in targeted capture region;It is tied with above-mentioned TNB detection is exported
Fruit.
Below by way of one embodiment, the present invention will be described in detail, it should be noted that the embodiment is only example
Property, it should not be understood as limiting the scope of the invention.
Embodiment
As shown in Figures 2 and 3, the exploitation of the tumor neogenetic antigen load detection device of the present embodiment and application technology route
It is as follows:
Clinical samples collect (tumor tissues and blood) → DNA and RNA extraction → high throughput gene trap sequencing → sequencing
Data prediction → sequencing data comparison → somatic variation detection and analysis → HLA parting → mutation expression detection → neoantigen
Immunotherapy of tumors is instructed in prediction → TNB calculating → TNB result is interpreted →.It is embodied as follows:
1, targeted capture chip designs:
Traditional tumour neoantigen cutting load testing generallys use full exon sequencing, has the shortcomings that at high cost, the period is long.
To solve this problem, the present invention devises a kind of targeted capture chip, only captures specific gene sequence and is sequenced, is effectively dropped
Low sequencing data amount reaches and saves cost, the short-period purpose of contracting.The design process of the targeted capture chip is:
(1) according to COSMIC database (S.A.Forbes et al., " COSMIC:Exploring the world ' s
knowledge of somatic mutations in human cancer,”Nucleic Acids Res.,vol.43,
No.D1, pp.D805-D811, Oct.2015) gene expression information collected, count the base expressed in tumor sample
Cause.Screening criteria are as follows: 50% gene before expression quantity comes in 50% sample, in this, as candidate gene.
(2) base of exon each on candidate gene is replaced with into mutating alkali yl that may be present one by one, after replacement
Nucleotide sequence annotated, take the peptide fragment that 8-11 amino acid forms before and after mutational site as potential mutation peptide fragment.
(3) statistics Chinese population HLA genotype frequency distribution, obtains the highest HLA genotype of 31 kinds of frequencies, as China
Crowd represents genotype.
(4) genotype is represented according to 31 kinds of Chinese populations to every potential mutation peptide fragment and carries out MHC affinity prediction respectively.
Calculate error to eliminate, affinity prediction be respectively calculated using 2 kinds of stand alone softwares (such as respectively using NetMHCpan and
MHCflurry software calculates).
(5) all affinity prediction results are counted.In 2 kinds of software prediction results, take mutation peptide fragment prediction affine
Power is respectively less than 50nM, and it is potential neoantigen that corresponding wild type peptide fragment prediction affinity, which is all larger than the mutation peptide fragment of 500nM,
Peptide fragment.
(6) its mutational site is recalled to every potential neoantigen peptide fragment, if site is located in COSMIC mutation database,
Scope of design then is included in this site;If site is located in Cancer Gene Census list of genes on listed gene, also will
It is included in scope of design in this site.
(7) the design bit number of points that each exon includes on genome are calculated, and from high to low by design bit number of points
Sequence chooses the exon that total size is 1.5M, as chip capture region (table 1).
(8) HLA parting region is added.Capture probe is designed to 31 kinds of HLA genotype common in Chinese population.
(9) SNP Quality Control site is added.The selection method in the Quality Control site are as follows: according to Cell Lines Project
(K.Chen et al.,“Mutational landscape of gastric adenocarcinoma in Chinese:
implications for prognosis and therapy.,”Proc.Natl.Acad.Sci.U.S.A.,vol.112,
No.4, pp.1107-12, Jan.2015) database design Quality Control site, wherein the frequency of mutation exists in Chinese population for selection
The site in the section 0.4-0.6 is proved to be successful rate sequence according to PCR, selects highest 28 SNP sites as follows: rs1327118,
rs1402695、rs1414904、rs1131498、rs1079820、rs1805087、rs1032807、rs1801262、
rs1515002、rs1392265、rs11096957、rs1426003、rs1363333、rs3734440、rs156318、
rs1843026、rs1368136、rs1105176、rs156697、rs12828016、rs1395936、rs1541836、
Rs1805034, rs1030687, rs171953, rs753381, rs1293153 and rs1541290.
Table 1
It is as follows to the verifying of this design:
It is tested using 318 Chinese population cancer of the esophagus samples, designs area using full exon region and chip respectively
Domain detection mutation and neoantigen, as a result as shown in Figure 4, it is seen that no matter be mutated horizontal or neoantigen quantity, chip results
It is in same level with full exon result, proves that targeted capture chip design can really reflect that tumor neogenetic is anti-substantially
Former load.
2, experimental method optimizes:
Traditional tumour genome detection method generallys use tumour list pattern detection, finds that this method can not have in research
Effect distinguishes somatic mutation and germinal mutation.The defect targets detection influence less for conventional, but for tumor neogenetic
There are larger impacts for antigen cutting load testing.To solve this problem, present invention employs the modes of pairing detection, while detecting tumour
Tissue and check sample (cancer beside organism or peripheral blood), cooperate subsequent analysis method to obtain somatic mutation.
3, information analysis method designs:
The information analysis method that the present invention includes include lower machine data processing, data filtering and Quality Control, DNA sequence dna compare and
As a result Quality Control, RNA sequence compares and result Quality Control, somatic mutation detection and result filtering, variation result annotation, fusion
Detection and annotation, HLA parting, the pairs of Quality Control of sample, the detection of mutation expression level, the prediction of MHC affinity, TNB is calculated, TNB is used
The links such as medicine guidance.Above- mentioned information analysis method is run on analysis of biological information cluster by automatic dispatching system, is stablized
Efficiently output analysis result.
Each information analysis link is described in detail as follows:
A) machine data processing under: what sequenator generated is usually professional format data, need to be first converted into general fastq
File format.In addition, multiple samples can be mixed on 1 sequence testing chip, need to belong to before analysis the data of each sample
It splits and.The present invention is handled lower machine data using bcl2fastq software, and is surveyed for common NextSeq 500
Sequence instrument has carried out the optimization in parameter, achievees the purpose that improve data user rate, simplifies subsequent processing.Data processing passes through after finishing
Quality Control program Quality Control is crossed, judges whether data output and quality exception occur, it is without exception then to enter next step.
B) data filtering and Quality Control: the data of sequenator output in addition to comprising valid data, further include sequence measuring joints sequence,
Low quality sequence and the sequence of N base composition, these sequences can interfere subsequent analysis, need to remove.The present invention uses
Cutadapt software carries out aforesaid operations.Filtered data carry out Quality Control using Quality Control software, meet the number of following table 2 standard
According to for qualified data:
Table 2
Parameter | Numerical value |
Net base (Clean_Base) | >2500Mb |
Q20 | > 95% |
Q30 | > 80% |
GC | >45% and<50% |
GC-AT base separates (GC-AT_Seperation) | < 0.500% |
N base ratio (N_Rate) | < 0.100% |
Averagely read length (Average_read_length) | > 120bp and≤151bp |
Read length variance (Read_length_stddev) | <20.000 |
Average base quality (Average_base_quality) | >32.000 |
Net base rate (Clean_base_ratio) | > 80% |
C) DNA sequence dna comparison and Quality Control: DNA sequence dna is compared to be carried out using bwa mem algorithm, and the reference genome used is
GRCh37.73.Comparison result directly carries out being overlapped sequence processing, is not required to generate temporary file, reaches and save time and space
Purpose.Comparison result carries out Quality Control using Quality Control software, meets the data of following table 3 standard for qualified data:
Table 3
Parameter | Numerical value |
Comparison rate (Mapping_rate) | > 99% |
It compares quality (Mapping_quality) | >35 |
Insert Fragment size (Insert_size) | <180bp and>120bp |
Repetitive rate (Duplication_rate) | < 30% |
Capture rate (Capture_rate) | > 50% |
Target fragment depth (Depth_in_target) | >500X |
Target fragment covers (Target_coverage) | > 98% |
Target fragment _ 500X (Target_500X) | > 70% |
Target fragment _ 100X (Target_100X) | > 90% |
Target fragment _ 10X (Target_10X) | > 90% |
D) RNA sequence comparison and Quality Control: RNA sequence is compared to be carried out using STAR software, and the reference genome used is
GRCh38, the reference gene set used are GENCODE27.Comparison result using Quality Control software carry out Quality Control, data volume it is up to standard and
Transcript quantity reaches the data of saturation for qualified data.
E) somatic variation detection and result filtering: this method makes a variation simultaneously to tumor tissues and check sample data
Detection finds somatic mutation.Variation detection is carried out using samtools and varscan software, obtains original variation result.Become
It makes a variation in different detection baseline results comprising more false positive, needs to be filtered.Use Patent No. 201711107001.6
" point mutation detection filter method, device and storage medium based on the sequencing of two generations " and Patent No. 201810273763.1
" insertion and deletion mutation detection methods, device and storage medium based on the sequencing of two generations " patent, according to the base matter of mutating alkali yl
Whether magnitude comparison mass value, the upper relative position reads, the frequency of mutation, is that the factors such as hot spot mutation are for statistical analysis, most
True mutation is determined eventually.
F) variation result annotation: this method first annotates mutation result using SnpEff annotating software, uses
It is GENCODE27 with reference to gene set.Annotation obtains the bases such as Gene Name, transcript number and location information, HGVS mutation number
This information;The situation of change for then calculating the 8-11 amino acid in mutational site front and back, as mutation peptide fragment.
G) fusion detection and annotation: fusion uses RNA comparison result, passes through Patent No.
201711107002.0 " for detecting the method, apparatus and storage medium of target area Gene Fusion " proprietary algorithms are detected,
And testing result is annotated.The situation of change for then calculating the 8-11 amino acid in position of fusion front and back, as mutation peptide fragment.
H) HLA parting: the present invention carries out HLA parting to blood sample using bwa-hla and Polysolver software, takes two
Person's intersection is as testing result.Furthermore to eliminate the influence of HLA LOH in tumour, and bwa-hla is equally used to tumor sample
And Polysolver software carries out HLA parting, takes the two intersection as testing result.
I) the pairs of Quality Control of sample: tumour and check sample to ensure to detect come from the same person, and this method is in capture core
On piece devise 28 polymorphic sites (rs1327118, rs1402695, rs1414904, rs1131498, rs1079820,
rs1805087、rs1032807、rs1801262、rs1515002、rs1392265、rs11096957、rs1426003、
rs1363333、rs3734440、rs156318、rs1843026、rs1368136、rs1105176、rs156697、
rs12828016、rs1395936、rs1541836、rs1805034、rs1030687、rs171953、rs753381、
Rs1293153 and rs1541290), these sites have Polymorphic Population, and different genotype is shown as in different people, can be used
In pairs of Quality Control.
J) mutation expression level detects: to ensure that mutein is finally translated into the mutation of DNA level, the present invention is simultaneously
Mutation on RNA is detected, judges that the mutation on DNA whether there is on RNA.
K) MHC affinity is predicted: using the HLA genetype for predicting neoantigen detected, prediction to aforementioned mutation peptide fragment
Method is referred to " the tumor neogenetic antigen detection method, device based on the sequencing of two generations of Patent No. 201810601500.9
And storage medium " patent.It is potential new for taking the peptide fragment of mutation peptide fragment affinity<500nM and wild type peptide fragment affinity>500nM
Raw antigen.
L) TNB is calculated: finally obtained high quality neoantigen is taken, calculates TNB according to following formula:
TNB=N/R, wherein N is high quality neoantigen quantity (unit is a), and R is the practical sequencing area size of chip
(unit Mb).
M) TNB medication guide: domestic and international clinical trial information and genome database information of this method according to collection, if
It is following (Neos indicates neoantigen) to determine TNB medication guide principle:
TNB-H:TNB > 4.5Neos/Mb;
TNB-M:0.5Neos/Mb≤TNB≤4.5Neos/Mb;
TNB-L:TNB < 0.5Neos/Mb;
TNB is higher, more it is possible that benefiting from anti-PD-L1 immunization therapy.
It is as follows to the verifying of above- mentioned information analysis method: to use document (N.A.Rizvi et al., " Mutational
landscape determines sensitivity to PD-1 blockade in non-small cell lung
Cancer, " Science (80-.), vol.348, no.6230, pp.124-128, Apr.2015) 34 non-small cells delivering
Cases of lung cancer analyzes initial data using said chip capture region and information analysis method, as a result as shown in figure 5,
The figure is that patient receives the survivorship curve after immunization therapy, and abscissa is the time (moon) after treatment, ordinate be patient without into
Open up the ratio of existence.In figure it will also be seen that the survival rate of high TNB group and low TNB group have it is significantly different.The above results prove
The TNB result that method of the invention obtains can be used for distinguishing immunization therapy effectively and refractory patient, achieve the purpose that medication guide.
Using above-mentioned data, respectively according to based on TMB conventional method and new method proposed by the present invention carry out curative effect it is pre-
It surveys, as a result as shown in table 4 below:
Table 4
Table 4 is as the result is shown: accuracy of the invention is better than conventional method, can preferably instruct immunization therapy.
Use above specific case is illustrated the present invention, is merely used to help understand the present invention, not to limit
The system present invention.For those skilled in the art, according to the thought of the present invention, can also make several simple
It deduces, deform or replaces.
Claims (10)
1. a kind of tumor neogenetic antigen load detection device, which is characterized in that the detection device includes:
Data capture unit, the targeting of tumor tissues DNA, check sample DNA and tumor tissues RNA for obtaining test object
The sequencing data of capture region;
Somatic variation detection unit, for the sequencing to the tumor tissues DNA and the targeted capture region of check sample DNA
Data carry out variation detection to find somatic mutation, and the somatic mutation are annotated and calculated mutational site front and back
The situation of change of the amino acid of first setting quantity, as mutation peptide fragment;
Fusion detection unit, the sequencing data for the targeted capture region to the tumor tissues RNA carry out fusion base
Because detecting to find fusion, and the fusion is annotated and calculated position of fusion front and back second and set quantity
The situation of change of amino acid, as mutation peptide fragment;
HLA parting detection unit, the sequencing data for the targeted capture region to the check sample DNA carry out HLA parting
To obtain HLA parting testing result;
MHC affinity predicting unit, for the mutation peptide fragment using the HLA parting testing result predict neoantigen with
It was found that potential neoantigen;
TNB computing unit, for calculating TNB:TNB=N/R according to following formula, wherein N is neoantigen quantity, and R is targeting
The practical sequencing area size of capture region;With
As a result output unit, for exporting the TNB testing result.
2. detection device according to claim 1, which is characterized in that the check sample is selected from cancer beside organism or peripheral blood
Sample.
3. detection device according to claim 1, which is characterized in that described first sets quantity as 8-11;Described second
Quantity is set as 8-11.
4. detection device according to claim 1, which is characterized in that the HLA parting detection unit is also used to described
The sequencing data in the targeted capture region of tumor tissues DNA carries out HLA parting to obtain HLA parting testing result.
5. detection device according to claim 1, which is characterized in that the detection device further include:
The horizontal detection unit of mutation expression, the mutation of the sequencing data for the targeted capture region to the tumor tissues RNA
Being detected whether there is on RNA with the mutation judged on DNA.
6. detection device according to claim 1, which is characterized in that the potential neoantigen is in the mutation peptide fragment
The peptide fragment of affinity<500nM and wild type peptide fragment affinity>500nM.
7. detection device according to claim 1, which is characterized in that the targeted capture region passes through targeted capture chip
Capture, the targeted capture chip are equipped with targeted capture probe, and the targeted capture probe obtains by the following method:
(1) gene expression information collected according to COSMIC database counts the gene conduct expressed in tumor sample
Candidate gene;
(2) base of exon each on the candidate gene is replaced with into mutating alkali yl that may be present one by one, after replacement
Nucleotide sequence annotated, take the peptide fragment of predetermined quantity amino acid composition before and after mutational site as potential mutation peptide fragment;
(3) statistics Chinese population HLA genotype frequency distribution, obtains the highest HLA genotype of frequency of setting quantity, as in
State crowd represents genotype;
(4) genotype is represented according to the Chinese population of setting quantity to potential mutation peptide fragment described in every to carry out MHC respectively affine
Power prediction;
(5) statistics is carried out to all affinity prediction results and obtains potential neoantigen peptide fragment;
(6) its mutational site is recalled to potential neoantigen peptide fragment described in every, if the site is located in COSMIC database,
Scope of design then is included in the site, if the site is located in Cancer Gene Census list of genes on listed gene,
Also scope of design is included in the site;
(7) the design bit number of points that each exon includes on genome are calculated, and from high to low by the design bit number of points
Sequence, choosing total size is the exon that is sized as chip capture region;With
(8) capture probe is designed according to the chip capture region;
Preferably, the targeted capture region includes the capture region of gene as shown in table 1 below:
Table 1
8. detection device according to claim 7, which is characterized in that the targeted capture region further include for sample at
To the polymorphic site of Quality Control, the polymorphic site be rs1327118, rs1402695, rs1414904, rs1131498,
rs1079820、rs1805087、rs1032807、rs1801262、rs1515002、rs1392265、rs11096957、
rs1426003、rs1363333、rs3734440、rs156318、rs1843026、rs1368136、rs1105176、
rs156697、rs12828016、rs1395936、rs1541836、rs1805034、rs1030687、rs171953、
Rs753381, rs1293153 and rs1541290, the tumor tissues and check sample that the polymorphic site ensures to detect come from
Same test object.
9. a kind of tumor neogenetic antigen load detection device, which is characterized in that the detection device includes:
Memory, for storing program;
Processor, for the program by executing the memory storage to realize following tumor neogenetic antigen cutting load testing side
Method:
Obtain the sequencing number of tumor tissues DNA, the check sample DNA of test object and the targeted capture region of tumor tissues RNA
According to;
Variation detection is carried out to find to the sequencing data in the targeted capture region of the tumor tissues DNA and check sample DNA
Somatic mutation, and the somatic mutation is annotated and calculated the amino acid of the first setting of mutational site front and back quantity
Situation of change, as mutation peptide fragment;
Fusion is carried out to the sequencing data in the targeted capture region of the tumor tissues RNA to detect to find fusion,
And the situation of change that position of fusion front and back second sets the amino acid of quantity is annotated and calculated to the fusion, as
It is mutated peptide fragment;
HLA parting is carried out to the sequencing data in the targeted capture region of the check sample DNA to obtain HLA parting detection knot
Fruit;
To the mutation peptide fragment using HLA parting testing result prediction neoantigen to find potential neoantigen;
TNB:TNB=N/R is calculated according to following formula, wherein N is neoantigen quantity, and R is the practical survey in targeted capture region
Sequence area size;With
Export the TNB testing result.
10. a kind of computer readable storage medium, which is characterized in that including program, described program can be executed by processor with
Realize following tumor neogenetic antigen load testing method:
Obtain the sequencing number of tumor tissues DNA, the check sample DNA of test object and the targeted capture region of tumor tissues RNA
According to;
Variation detection is carried out to find to the sequencing data in the targeted capture region of the tumor tissues DNA and check sample DNA
Somatic mutation, and the somatic mutation is annotated and calculated the amino acid of the first setting of mutational site front and back quantity
Situation of change, as mutation peptide fragment;
Fusion is carried out to the sequencing data in the targeted capture region of the tumor tissues RNA to detect to find fusion,
And the situation of change that position of fusion front and back second sets the amino acid of quantity is annotated and calculated to the fusion, as
It is mutated peptide fragment;
HLA parting is carried out to the sequencing data in the targeted capture region of the check sample DNA to obtain HLA parting detection knot
Fruit;
To the mutation peptide fragment using HLA parting testing result prediction neoantigen to find potential neoantigen;
TNB:TNB=N/R is calculated according to following formula, wherein N is neoantigen quantity, and R is the practical survey in targeted capture region
Sequence area size;With
Export the TNB testing result.
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Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
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Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103180730A (en) * | 2010-05-14 | 2013-06-26 | 综合医院公司 | Compositions and methods of identifying tumor specific neoantigens |
WO2015063302A2 (en) * | 2013-11-04 | 2015-05-07 | Immatics Biotechnologies Gmbh | Personalized immunotherapy against several neuronal and brain tumors |
CN105524984A (en) * | 2014-09-30 | 2016-04-27 | 深圳华大基因科技有限公司 | Method and equipment for neoantigen epitope prediction |
US20160298185A1 (en) * | 2013-12-05 | 2016-10-13 | The Broad Institute Inc. | Polymorphic gene typing and somatic change detection using sequencing data |
US20170199961A1 (en) * | 2015-12-16 | 2017-07-13 | Gritstone Oncology, Inc. | Neoantigen Identification, Manufacture, and Use |
WO2017147139A1 (en) * | 2016-02-22 | 2017-08-31 | Oceanside Biotechnology | Neoantigen compositions and methods of using the same in immunooncotherapy |
CN108351916A (en) * | 2015-07-14 | 2018-07-31 | 个人基因组诊断公司 | Neoantigen is analyzed |
CN108491689A (en) * | 2018-02-01 | 2018-09-04 | 杭州纽安津生物科技有限公司 | Tumour neoantigen identification method based on transcript profile |
CN108796055A (en) * | 2018-06-12 | 2018-11-13 | 深圳裕策生物科技有限公司 | Tumor neogenetic antigen detection method, device and storage medium based on the sequencing of two generations |
CN109033749A (en) * | 2018-06-29 | 2018-12-18 | 深圳裕策生物科技有限公司 | A kind of Tumor mutations load testing method, device and storage medium |
CN109021062A (en) * | 2018-08-06 | 2018-12-18 | 倍而达药业(苏州)有限公司 | A kind of screening technique of tumour neoantigen |
CN109022553A (en) * | 2018-06-29 | 2018-12-18 | 深圳裕策生物科技有限公司 | Genetic chip for Tumor mutations cutting load testing and preparation method thereof and device |
-
2018
- 2018-12-29 CN CN201811642537.2A patent/CN109706065A/en active Pending
Patent Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103180730A (en) * | 2010-05-14 | 2013-06-26 | 综合医院公司 | Compositions and methods of identifying tumor specific neoantigens |
WO2015063302A2 (en) * | 2013-11-04 | 2015-05-07 | Immatics Biotechnologies Gmbh | Personalized immunotherapy against several neuronal and brain tumors |
US20160298185A1 (en) * | 2013-12-05 | 2016-10-13 | The Broad Institute Inc. | Polymorphic gene typing and somatic change detection using sequencing data |
CN105524984A (en) * | 2014-09-30 | 2016-04-27 | 深圳华大基因科技有限公司 | Method and equipment for neoantigen epitope prediction |
CN108351916A (en) * | 2015-07-14 | 2018-07-31 | 个人基因组诊断公司 | Neoantigen is analyzed |
US20170199961A1 (en) * | 2015-12-16 | 2017-07-13 | Gritstone Oncology, Inc. | Neoantigen Identification, Manufacture, and Use |
CN108601731A (en) * | 2015-12-16 | 2018-09-28 | 磨石肿瘤生物技术公司 | Discriminating, manufacture and the use of neoantigen |
WO2017147139A1 (en) * | 2016-02-22 | 2017-08-31 | Oceanside Biotechnology | Neoantigen compositions and methods of using the same in immunooncotherapy |
CN108491689A (en) * | 2018-02-01 | 2018-09-04 | 杭州纽安津生物科技有限公司 | Tumour neoantigen identification method based on transcript profile |
CN108796055A (en) * | 2018-06-12 | 2018-11-13 | 深圳裕策生物科技有限公司 | Tumor neogenetic antigen detection method, device and storage medium based on the sequencing of two generations |
CN109033749A (en) * | 2018-06-29 | 2018-12-18 | 深圳裕策生物科技有限公司 | A kind of Tumor mutations load testing method, device and storage medium |
CN109022553A (en) * | 2018-06-29 | 2018-12-18 | 深圳裕策生物科技有限公司 | Genetic chip for Tumor mutations cutting load testing and preparation method thereof and device |
CN109021062A (en) * | 2018-08-06 | 2018-12-18 | 倍而达药业(苏州)有限公司 | A kind of screening technique of tumour neoantigen |
Non-Patent Citations (5)
Title |
---|
HARTMAIER RJ, ET AL.: "Genomic analysis of 63,220 tumors reveals insights into tumor uniqueness and targeted cancer immunotherapy strategies.", 《GENOME MED.》 * |
KARASAKI T, ET AL.: "Neoantigens and Whole-Exome Sequencing", 《GAN TO KAGAKU RYOHO.》 * |
L.CHEN,: ""P1.07-026 Predicting Tumor Mutational Burden (TMB) and Tumor Neoantigen Burden (TNB) of East Asian ANSCLC Patients by a Targeted Genomic Profiling"", 《JOURNAL OF THORACIC ONCOLOGY》 * |
ŁUKSZA M, ET AL.: "A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy.", 《NATURE》 * |
闵慜,等: "PD-1/PD-L1阻断治疗及其疗效预测研究进展", 《现代免疫学》 * |
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