CN108949979A - A method of judging that Lung neoplasm is good pernicious by blood sample - Google Patents
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Abstract
The good pernicious method of Lung neoplasm is judged by blood sample the invention discloses a kind of, it is determined using cfDNA polygenic variation combination machine learning, including carrying out library construction to Lung neoplasm peripheral blood in patients cfDNA, and hybrid capture is carried out to cfDNA using lung cancer related 18 gene trap probes, it is sequenced using sequenator, the accumulative frequency of mutation for analyzing each gene, using logistic regression model judgement sample it is good pernicious.The present invention is capable of the good pernicious of highly sensitive, high specific differentiation pulmonary nodule patient, avoids the artificial experience for reading CT images, and the missing inspection and benign protuberance patient for avoiding lung cancer puncture or the pain of operation sampling biopsy.
Description
Technical field
The present invention relates to the fields such as genetic test, bioinformatics, mathematical modeling, and in particular to one kind passes through blood sample
Judge the good pernicious method of Lung neoplasm.
Background technique
Lung cancer is to seriously endanger the disease of human health, and the data that WHO is announced is shown, lung cancer either disease incidence or disease
It is the first that dead rate occupies global cancer.The Chinese tumour year number of the infected that tumor center of China announces recently is 429.16 ten thousand (male
251.21 ten thousand, female 177.95 ten thousand), wherein lung cancer year number of the infected is 73.33 ten thousand (male 50.93 ten thousand, female 22.40 ten thousand
Example), year mortality is 61.02 ten thousand (male 43.24 ten thousand, female 17.78 ten thousand), also occupies (Chen et first of Chinese tumour
al.,2016).Further, since diagnosis is partially late, lung cancer 5 annual survival rate in China's is only 15.6%.Improve lung cancer for prognosis, is also badly in need of
It improves the early stage of lung cancer and (carcinoma in situ and Ia phase phase lung cancer is known as the early stage of lung cancer (similarly hereinafter) diagnosis here.Optimal strategy is will
Diagnosing port is migrated to diagnosis Lung neoplasm, thus the diagnosing and treating early stage of lung cancer as early as possible.
Many patients etc. have clinical tumor symptom just to check, have had been subjected to golden hour at this time.And mesh
There are no a kind of sensitivity, specificity height, the noninvasive early diagnosis screening methods of safety for the preceding diagnosis for the early stage of lung cancer.Therefore
The Non-invasive detection technology and means of a kind of novelty are highly desirable to for the early diagnosis of lung cancer.Currently in the diagnosis of Lung neoplasm
In, mainly with CT images data, go tentatively to judge in conjunction with doctor personal experience it is good pernicious, then by long-time follow-up and
Bronchoscope or aspiration biopsy are good pernicious to make a definite diagnosis.For this method since doctors experience limits, accuracy fluctuation is bigger, exists
The situation of a large amount of excessively detections and missing inspection.
A branch of the liquid biopsy as in-vitro diagnosis, refers to a kind of blood testing of non-intrusion type, can monitor tumour
Or transfer stove is discharged into the circulating tumor cell (CTC) and Circulating tumor DNA (ctDNA) fragment of blood, is detection tumour and cancer
Disease, adjuvant treatment disruptive technology.Currently, entered research and development there are many molecular level marker in liquid biopsy field,
If expressing quantity changes (Ma&Xu, 2017), miRNA (Mo, Chen, Fu, Wang , &Fu, 2012), cfDNA methylation
(Zhang et al., 2011), cfDNA horizontal (Szpechcinski et al., 2015), blood platelet RNA (Best et
Al., 2015) etc..Studies have shown that in cancer patient, containing micro in circulation dissociative DNA (cell-free DNA, cfDNA)
Circulating tumor DNA (circulating tumor DNA, ctDNA).The variation of ctDNA is from cancer cell, with tumor tissues
With high consistency, thus it can substitute tumor tissues, as detection and diagnosis tumour index and foundation and become
The important tool of early-stage cancer screening.Liquid biopsy need to only extract 10mL peripheral blood, to patient, and more easy,
It is sensitive.
Summary of the invention
In order to find the good pernicious judgment method of better Lung neoplasm, the invention discloses one kind to judge lung by blood sample
The good pernicious method of tubercle can be realized the good pernicious of highly sensitive, high specific differentiation pulmonary nodule patient, avoid
The artificial experience for reading CT images, the missing inspection and benign protuberance patient for avoiding lung cancer puncture or operation sampling is lived
The pain of inspection.
Used technical solution is as follows:
A method of judging that Lung neoplasm is good pernicious by blood sample, is using cfDNA polygenic variation bonding machine
Device learns to include the following steps: to determine
S1. library construction is carried out to Lung neoplasm peripheral blood in patients cfDNA；
S2. hybrid capture is carried out to cfDNA using lung cancer related 18 gene trap probes, which is respectively
STAT3、DDR2、STAT3、ERBB3、SOD2、RAF1、ERBB4、AKT1、SLIT1、NTRK1、DDR2、KEAP1、NOTCH1、
TSC2, JAK2, JAK2, EGFR and ATM；
S3. it is sequenced using sequenator, data analysis is carried out to sequencing data, analyze the accumulative mutation frequency of each gene
Rate, using logistic regression model judgement sample it is good pernicious.
Further, in S1, library construction is carried out to cfDNA, is specifically comprised the following steps:
S11. the free DNA in peripheral blood blood plasma is extracted, and quality control is carried out to the cfDNA of extraction, measures its piece
Duan great little and concentration, clip size peak value are located at 40-170bp, and DNA initial amount is between 5-25ng；
S12. T and then successively is added to the cfDNA progress duplex ends reparation of extraction, Sample Purification on Single, 3 ' ends, is connect
Head, PCR amplification enrichment,
S13. PCR product purifying finally is carried out to the product of PCR amplification enrichment, i.e. the acquisition library cfDNA.
Further, the PCR product of the Sample Purification on Single of S12 and S13 purifying is all carried out using magnetic bead absorption method.
Further, 3 ' ends of capture probe have biotin labeling in S2, and gene trap probe, which uses, covers tile style probe,
Probe length 120bp.
Further, it in S2, in hybrid capture, is added according to the dosage that a probe captures the 10-12 library cfDNA
Capture probe.
Further, in S3, sample is surveyed using second generation high-flux sequence instrument Illumina NextSeq550
Sequence, 18 gene target region cfDNA sequencing depth reach 10000X.
Further, in S3, data analysis includes that low quality data is removed using afterQC, and bwa carries out comparing,
It is repeated using dedup software removal PCR, samtools+VarScan2 carries out variation detection, then counts each using MrBam
Variant sites compare unique read quantity, filter variation of unique read less than 2, use normal person's baseline filtering based on database
The somatic variation occurred in normal person.
Further, in S3, the model using logistic regression is by formula log (p/ (1-p))=b0+b1*x1+b2*
X2+ ...+bn*xn is calculated, and is obtained at given gene mutation frequency (x1, x2 ... xn), and sample is pernicious Probability p；Work as p >
Judgement sample is pernicious when 0.5, remaining determines that sample is benign.
The beneficial effects of the present invention are:
The present invention uses related 18 genes of lung cancer by carrying out library construction to Lung neoplasm peripheral blood in patients cfDNA
Capture probe carries out hybrid capture to cfDNA, and then upper machine sequencing, analyzes the accumulative frequency of mutation of each gene, use logic
The model judgement sample of recurrence it is good pernicious, so as to the good evil of highly sensitive, high specific differentiation pulmonary nodule patient
Property, avoid the artificial experience for reading CT images, avoid lung cancer missing inspection and benign protuberance patient puncture or
The pain of operation sampling biopsy.
Detailed description of the invention
Fig. 1 is a kind of flow chart that the good pernicious method of Lung neoplasm is judged by blood sample.
Specific embodiment
The present invention is further elaborated with reference to the accompanying drawing, but scope of protection of the present invention is not limited thereto.
Embodiment 1
As shown in connection with fig. 1, a method of judging that Lung neoplasm is good pernicious by blood sample, be using the more bases of cfDNA
Determine because making a variation in conjunction with machine learning, includes the following steps:
1. pair 84 Lung neoplasm clinical samples (48 pernicious, and 36 benign) peripheral bloods are handled, peripheral blood blood is extracted
The cfDNA content that free DNA in slurry, cfDNA are extracted in peripheral blood is very low, therefore guarantees that blood plasma cfDNA extracts quality extremely
It closes important.CfDNA extraction scheme detailed step is as follows: the extraction purification of peripheral blood cfDNA generallys use 10mL whole blood, is obtaining
Separated plasma in the 3h of blood is obtained, 4 DEG C of 1600g of whole blood are centrifuged 10min, collect supernatant into 5mL centrifuge tube；Again by supernatant 4
DEG C, 16000g is centrifuged 10min, collects supernatant blood plasma and is transferred in 5mL centrifuge tube.The blood plasma of separator well preferably extracts immediately
DNA is the integrality in order to guarantee DNA in blood plasma in this way.It extracts in blood plasma there are many kinds of the kits of dissociative DNA, this example tool
Body uses the plasma/serum dissociative DNA extracts kit of QIAGEN company, and extraction step refers to kit specification.
Then quality control (i.e. Quality Control) is carried out to the cfDNA of extraction, measures its clip size and concentration.CfDNA Quality Control
Using the clip size of the cfDNA of 2100 Detection and Extraction of Agilent, using the concentration for the cfDNA that q-PCR measurement is extracted.Segment
Big small leak is located at 40-170bp, and DNA initial amount is between 5-25ng.
Then T, jointing, PCR successively are added to the cfDNA progress duplex ends reparation of extraction, Sample Purification on Single, 3 ' ends
Amplification enrichment finally carries out PCR product purifying to the product of PCR amplification enrichment and obtains the library cfDNA.More specifically
CfDNA library construction: the building in the library cfDNA can realize that the present invention is built using Agilent's using multiple product on the market
Library method (Sure SelectXT2 Ta rg e t Enrichment System for Illumina Paired-End
Sequencing Library), it is correspondingly improved and optimizes in some steps, library construction concrete operations are as follows: 1)
CfDNA duplex ends are repaired 2) cfDNA and are purified, and this example carries out purifying 3 to the cfDNA that end is repaired using paramagnetic particle method) DNA 3 '
End adds the both ends dTTP DNA to connect adapter 4) 5) cfDNA library purify for PCR amplification enrichment, to PCR amplification enriched product
The middle 50 μ L magnetic beads that are added carry out purifying 6) identification of cfDNA Library Quality, quality inspection is carried out to the library cfDNA, this example uses
Agilent 2100 identifies clip size.
2. carrying out hybrid capture to cfDNA using the related 18 gene trap probes of lung cancer.Capture chip used of the invention
Covering includes that whole exons of 18 genes and exon close on 10bp shearing site region altogether.18 genes include STAT3,
DDR2,STAT3,ERBB3,SOD2,RAF1,ERBB4,AKT1,SLIT1,NTRK1,DDR2,KEAP1,NOTCH1,TSC2,
JAK2, JAK2, EGFR and ATM.Gene trap probe covers tile style spy using Roche Nimblegen SeqCap EZ Developer
Needle, probe length 120bp.Capture probe is complementary with objective gene sequence, and is had at 3 ' ends of capture probe
Biotin label, the magnetic bead of streptomysin affine in this way, using the chemical reaction of affine streptomysin and biotin, energy will be with probe
The target gene of complementary pairing takes out, to realize the capture of target gene.
Then cfDNA elution is carried out, to remove the DNA of the ctDNA and some non-specific bindings that are not identified by probe；
DNA after capture is expanded；
3. sample is sequenced using second generation high-flux sequence instrument Illumina NextSeq550,18 gene mesh
Mark region cfDNA sequencing depth reaches 10000X.
Then sequencing data being analyzed, including afterQC is used to remove low quality data, bwa carries out comparing,
It is repeated using dedup software removal PCR, samtools+VarScan2 carries out variation detection, then counts each using MrBam
Variant sites compare unique read quantity, filter variation of unique read less than 2, use normal person's baseline filtering based on database
The somatic variation occurred in normal person.
Then 18 genes of each sample are counted and add up variation frequency and variant sites quantity as next step model training
Feature.
The present invention pernicious is judged using the model of logistic regression to Lung neoplasm is good.Its training step are as follows:
A. one group of parameter vector of random initializtion (b0, b1 ... bn)；
B. it is calculated by formula log (p/ (1-p))=b0+b1*x1+b2*x2+ ...+bn*xn in given gene mutation
When frequency (x1, x2 ... xn), sample is pernicious Probability p；
C. the probability for calculating known good pernicious sample, the error predicted is compared with actual conditions；
D. regard the sample frequency of mutation as constant, parameter vector regards variable as, calculates error leading for each parameter bi
Number, uses derivative undated parameter vector.The step is repeated until the derivative of each parameter is close to 0.Use random 90% sample
This training pattern, 10% sample repeat 1000 times as test.Verify model whether over-fitting, say that the feature of sample is random
Upset, repeats the above steps.By the formula mentioned in final parameter vector and b can good pernicious probability to new samples into
Row calculates.Probability > 0.5 think to be biased to it is pernicious ,≤0.5 think to be biased to it is benign.
Shown in two columns of the test result referring to the bottom Fig. 1, wherein left column indicates that the accuracy for being biased to pernicious judgement is
86.8%, sensitivity 94.5%, specificity is 75.2%；Right column indicates that the accuracy for being biased to benign judgement is 71.5%, spirit
Sensitivity is 84.6%, and specificity is 52.2%.
The series of detailed descriptions listed above are illustrated only for possible embodiments of the invention,
The protection scope that they are not intended to limit the invention, it is all without departing from equivalent embodiment made by technical spirit of the present invention or change
It should all be included in the protection scope of the present invention.
Claims (8)
1. a kind of judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that it is become using cfDNA polygenes
Different combination machine learning determines, includes the following steps:
S1. library construction is carried out to Lung neoplasm peripheral blood in patients cfDNA；
S2. hybrid capture carried out to cfDNA using lung cancer related 18 gene trap probes, 18 genes be respectively STAT3,
DDR2、STAT3、ERBB3、SOD2、RAF1、ERBB4、AKT1、SLIT1、NTRK1、DDR2、KEAP1、NOTCH1、TSC2、
JAK2, JAK2, EGFR and ATM；
S3. it is sequenced using sequenator, data analysis is carried out to sequencing data, analyzes the accumulative frequency of mutation of each gene,
Using logistic regression model judgement sample it is good pernicious.
2. according to claim 1 judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that in S1,
Library construction is carried out to cfDNA, is specifically comprised the following steps:
S11. the free DNA in peripheral blood blood plasma is extracted, and quality control is carried out to the cfDNA of extraction, it is big to measure its segment
Small and concentration, clip size peak value are located at 40-170bp, and DNA initial amount is between 5-25ng；
S12. T, jointing, PCR and then successively are added to the cfDNA progress duplex ends reparation of extraction, Sample Purification on Single, 3 ' ends
Amplification enrichment,
S13. PCR product purifying finally is carried out to the product of PCR amplification enrichment, i.e. the acquisition library cfDNA.
3. according to claim 2 judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that S12's
The purifying of the PCR product of Sample Purification on Single and S13 is all carried out using magnetic bead absorption method.
4. according to claim 1 judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that caught in S2
3 ' the ends for obtaining probe have biotin labeling, and gene trap probe, which uses, covers tile style probe, probe length 120bp.
5. according to claim 1 judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that in S2,
In hybrid capture, capture probe is added according to the dosage that a probe captures the 10-12 library cfDNA.
6. according to claim 1 judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that in S3,
Sample is sequenced using second generation high-flux sequence instrument Illumina NextSeq550,18 gene target region cfDNA
Sequencing depth reaches 10000X.
7. according to claim 1 judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that in S3,
Data analysis includes that low quality data is removed using afterQC, and bwa carries out comparing, uses dedup software removal PCR weight
Multiple, samtools+VarScan2 carries out variation detection, then counts each variant sites using MrBam and compares unique read number
Amount, filters variation of unique read less than 2, is become using the body cell occurred in normal person baseline filtering based on database normal person
It is different.
8. according to claim 1 judge the good pernicious method of Lung neoplasm by blood sample, which is characterized in that in S3,
Model using logistic regression is calculated by formula log (p/ (1-p))=b0+b1*x1+b2*x2+ ...+bn*xn, is obtained
When given gene mutation frequency (x1, x2 ... xn), sample is pernicious Probability p；As p > 0.5, judgement sample is pernicious, remaining
Determine that sample is benign.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110819700A (en) * | 2018-08-10 | 2020-02-21 | 杭州米天基因科技有限公司 | Method for constructing small pulmonary nodule computer-aided detection model |
| CN113160889A (en) * | 2021-01-28 | 2021-07-23 | 清华大学 | Cancer noninvasive early screening method based on cfDNA omics characteristics |
| CN113288110A (en) * | 2021-04-23 | 2021-08-24 | 四川省肿瘤医院 | Model and system for predicting benign and malignant pulmonary nodules based on platelet parameters |
| CN113637745A (en) * | 2020-04-27 | 2021-11-12 | 广州市基准医疗有限责任公司 | Methylated molecular markers for detecting benign and malignant lung nodules or combination and application thereof |
-
2018
- 2018-07-11 CN CN201810759269.6A patent/CN108949979A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110819700A (en) * | 2018-08-10 | 2020-02-21 | 杭州米天基因科技有限公司 | Method for constructing small pulmonary nodule computer-aided detection model |
| CN113637745A (en) * | 2020-04-27 | 2021-11-12 | 广州市基准医疗有限责任公司 | Methylated molecular markers for detecting benign and malignant lung nodules or combination and application thereof |
| CN113160889A (en) * | 2021-01-28 | 2021-07-23 | 清华大学 | Cancer noninvasive early screening method based on cfDNA omics characteristics |
| CN113288110A (en) * | 2021-04-23 | 2021-08-24 | 四川省肿瘤医院 | Model and system for predicting benign and malignant pulmonary nodules based on platelet parameters |
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Application publication date: 20181207 |