CN108389625A - Computer system for assessing relapse and metastasis risk after drug therapy - Google Patents
Computer system for assessing relapse and metastasis risk after drug therapy Download PDFInfo
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Abstract
The present invention discloses a kind of computer system for assessing relapse and metastasis risk after drug therapy.The computer system of the present invention passes through nonsteroidal anti-estrogens drug metabolism relevant enzymes Polymorphism Analysis binding of pathological feature, relapse and metastasis algorithm model is predicted based on independent construct of mathematical statistics method, can relapse and metastasis risk after more comprehensive and accurate assessment nonsteroidal anti-estrogens drug therapy, provide reasonable, efficient medication suggested design for clinician.
Description
Technical field
The present invention relates generally to relapse and metastasis risk assessment fields after drug therapy, are particularly directed to assessment non-steroidal
The computer system of relapse and metastasis risk after the treatment of class antiestrogen.
Background technology
The problem of relapse and metastasis risk is first concern in mammary cancer endocrine auxiliary treatment.Nonsteroidal anti-estrogens
Drug is treatment estrogen receptor (ER) positive, the most common endocrine auxiliary therapeutic agent of progesterone receptor (PR) positive breast cancer
Object, but do not there is research to provide effectively comprehensive clinical prognosis prediction technique to it yet at present.Nonsteroidal anti-estrogens drug master
Reactive intermediates 4-hydroxytamoxifen and N- demethyl -4- hydroxyls are metabolized as by the cytochrome P 450 enzymes class in liver
Base-tamoxifen plays pharmacological action.In recent years multiple studies have shown that the key of regulation and control nonsteroidal anti-estrogens drug metabolism
The gene pleiomorphism of enzyme influences its metabolic rate and then influences the medication curative effect and clinical outcome of patient with breast cancer.Therefore,
According only to patient with breast cancer tumor tissue pathology be characterized in can not comprehensively, accurate evaluation patient take nonsteroidal anti-estrogens
The treatment curative effect of drug can not provide reasonable efficient therapeutic regimen for clinician in time.
Invention content
In order to solve the above technical problems, the present invention provides one kind for being answered after assessing nonsteroidal anti-estrogens drug therapy
Send out the computer system to shift risk comprising：
Input unit for receiving object data, wherein the object data includes the clinical pathology from the object
Data and gene pleiomorphism data；Memory with database is used to store at least described clinical pathology data and described
Gene pleiomorphism data；Processor is communicated with memory, and is configured as：In clinical pathology data and described
Multiple independents variable are determined in gene pleiomorphism data, the numerical value of each independent variable are calculated according to assignment rule, and utilize the number
Value passes through algorithm model calculation risk assessed value；With the output device for being configured to be notified according to risk assessment value transmission.
In certain embodiments, the clinical pathology data of the invention include from the age, whether menopause, ER, PR,
Ki67, HER2, LN shift number, the data of tumor size and organizational hierarchy；And the gene pleiomorphism data include coming from
The data of CYP3A5, CYP2D6 and CYP2C19.
In certain embodiments, the gene pleiomorphism data of the invention include coming from CYP2D6*2, CYP2D6*
3, CYP2D6*4, CYP3A5*3, CYP2D6*10, CYP2D6*41, CYP2C19*2, CYP2C19*3, CYP2C19*17 and
The gene pleiomorphism data of CYP2D6*5.
In certain embodiments, it is of the invention by flight time mass spectrum detect CYP2D6*2, CYP2D6*3,
The gene of CYP2D6*4, CYP3A5*3, CYP2D6*10, CYP2D6*41, CYP2C19*2, CYP2C19*3 and CYP2C19*17
Polymorphism data.
In certain embodiments, the fragmentary missing data of the invention by expanding electrophoresis detection CYP2D6*5.
In certain embodiments, the algorithm model of the invention is obtained by following step：In the clinical pathology
Multiple independents variable are determined in data and the gene pleiomorphism data, assignment are carried out to each independent variable according to assignment rule, so
Importance assessment is carried out afterwards, and is ranked up, the variable that correlation absolute value is more than threshold values is chosen, and is carried out logistic regression analysis and is obtained
Go out each independent variable weight and formation algorithm model.
In certain embodiments, the algorithm model of the invention is：
TAMRORs (1)=- 43.28+0.89CYP2D6*10+0.37CYP2C19*3+20.77LN-21.17 Age+
0.83ER-22.31HER2+64.71Grade；
TAM RORs (2)=1/ (1+e-TAMRORs(1))；Preferably, when TAM RORs (2) level off to 1 when, output dress
It sets and sends the high notice of relapse and metastasis risk；With when TAM RORs (2) level off to 0 when, the output device sends relapse and metastasis
The low notice of risk.
In certain embodiments, the assignment rule of the clinical pathology data of the invention is：
Age was 0 more than 40 years old, and 40 years old or less is 1；
Menopause is 0, and non-menopause is 1；
It is 0 that ER, which is more than 50%, and 50% or less is 1；
It is 0 that PR, which is more than 50%, and 50% or less is 1；
Ki6720% or less is 0, and it is 1 to be more than 20%；
HER2 feminine genders are 0, and positive (3+orFish+) is 1；
It is 1 that LN, which shifts number 4 or more, and it is 0 to be less than 4；
It is 0 that longest diameter of tumor, which is less than 2cm, and longest diameter of tumor 2cm or more is 1；
It is 0 that organizational hierarchy, which is less than or equal to 2 grades, and it is 1 to be more than 2 grades.
In certain embodiments, the assignment rule of the gene pleiomorphism data of the invention is：
The present invention by nonsteroidal anti-estrogens drug metabolism relevant enzymes Polymorphism Analysis binding of pathological feature,
Relapse and metastasis algorithm model is predicted based on independent construct of mathematical statistics method, can more comprehensively and accurately be assessed non-
Relapse and metastasis risk after the treatment of steroid antiestrogen, provides rationally, efficient medication suggested design for clinician.
Description of the drawings
Fig. 1-Fig. 9 is the testing result of the flight time mass spectrum of the polymorphism of the exemplary 9 kinds of gene locis of the present invention.
Figure 10 is the electrophoresis augmentation detection result of the exemplary CYP2D6*5 genes of the present invention.
Figure 11 is the assignment graph of exemplary 19 independents variable of the present invention.
Figure 12 is the importance assessment figure of the exemplary relapse and metastasis correlative factor random forest of the present invention.
Figure 13 is the sensitivity of example T AM RORs algorithm models, specific findings ROC curve.
Figure 14 is the figure of exemplary authentication TAM RORs algorithm model prediction results.
Figure 15-Figure 17 is reaction process of the present invention in PCR instrument.
Specific implementation mode
The existing various exemplary embodiment that the present invention will be described in detail, the detailed description are not considered as the limit to the present invention
System, and it is understood as the more detailed description to certain aspects of the invention, characteristic and embodiment.
It should be understood that heretofore described term is only to describe special embodiment, being not intended to limit this hair
It is bright.In addition, for the numberical range in the present invention, it is thus understood that specifically disclose the range upper and lower bound and they it
Between each median.Median and any other statement value in any statement value or stated ranges or in the range
Smaller range is also included in the present invention each of between interior median.These small range of upper and lower bounds can be independent
Ground includes or excludes in range.
Unless otherwise stated, all technical and scientific terms used herein has the routine in field of the present invention
The normally understood identical meanings of technical staff.Although the present invention only describes preferred method and material, the present invention's
Implement or can also be used and similar or equivalent any method and material described herein in testing.The institute mentioned in this specification
There is document to be incorporated by reference into, to disclosure and description and the relevant method of the document and/or material.It is incorporated to any
When document conflicts, it is subject to the content of this specification.
It is the term of opening, i.e., about "comprising" used herein, " comprising ", " having ", " containing " etc.
Mean including but not limited to.Any or all combinations about "and/or" used herein, including the things.
The present invention is for nonsteroidal anti-estrogens drug currently without accurate clinical application prognosis prediction side comprehensively
Method, and a kind of computer system for assessing relapse and metastasis risk after nonsteroidal anti-estrogens drug therapy is provided.This hair
Bright computer system refers to a kind of product, including device, instrument or equipment etc., not method itself.The computer of the present invention
System can more comprehensively and accurately assess relapse and metastasis risk after nonsteroidal anti-estrogens drug therapy.
The computer system that the present invention is used to assess relapse and metastasis risk after nonsteroidal anti-estrogens drug therapy includes：
Input unit for receiving object data, wherein the object data includes the clinical pathology from the object
Data and gene pleiomorphism data；Memory with database is used to store at least described clinical pathology data and described
Gene pleiomorphism data；Processor is communicated with memory, and is configured as：In clinical pathology data and described
Multiple independents variable are determined in gene pleiomorphism data, the numerical value of each independent variable are calculated according to assignment rule, and utilize the number
Value passes through algorithm model calculation risk assessed value；With the output device for being configured to be notified according to risk assessment value transmission.
Above-mentioned each component can be briefly referred to as input unit, memory, processor and output device in the present invention.It is preferred that
Ground can be communicated between above-mentioned each component.For example, input unit can be communicated with memory or processor.Memory
It is communicated with processor.Each component described further below.
[input unit]
It is of the present invention for receive the input unit of object data to include any type of input unit.The present invention
In, object data is and the relevant any data of nonsteroidal anti-estrogens drug therapy, sometimes referred to as object information.It is described
Treatment includes mammary cancer endocrine auxiliary treatment.Object data includes clinical pathology data and gene pleiomorphism from the object
Data.It needs to include above-mentioned two classes data simultaneously in the present invention.Preferably, clinical pathology data and gene pleiomorphism data can be come
From the data of same target.The result for only using clinical pathology data or only using the prognosis prediction of gene pleiomorphism data is inadequate
Comprehensively, and result is inaccurate.Two kinds of data, which are simply combined analysis, cannot equally obtain reasonable and accurate result.This
Two kinds of different data are combined by invention by creative analysis and processing method, to realize the purpose of comprehensive Accurate Prediction.
In certain embodiments, clinical pathology data include but not limited to from the age, whether menopause, estrogen receptor
(ER), progesterone receptor (PR), Ki67, HER2, LN transfer number, the data of tumor size and organizational hierarchy.Wherein whether absolutely
Through, estrogen receptor (ER), progesterone receptor (PR), Ki67, HER2, LN transfer number, tumor size and organizational hierarchy can adopt
It is obtained with any means known in the art, herein without being described in detail.The present invention can be used one in above-mentioned data
Kind is a variety of.Preferably, the present invention uses above-mentioned 9 kinds of data simultaneously, so that it is guaranteed that prediction result is more accurate.In this field
Will be one or more in above-mentioned data, such as Ki67 and HER2 etc. is used for the prediction that prognosis recurrence shifts risk, but have no
Above-mentioned 9 kinds of data are applied in combination, and the report being effectively predicted is handled by special algorithm.
In certain embodiments, gene pleiomorphism data refer to and the relevant base of nonsteroidal anti-estrogens drug metabolism
Because of polymorphism data.Preferably, the gene pleiomorphism in the present invention refers to coming from tri- bases of CYP3A5, CYP2D6, CYP2C19
The polymorphism in the different genes site of cause.Present invention discover that CYP2D6*2, CYP2D6*3, CYP2D6*4, CYP3A5*3,
The gene pleiomorphism data of CYP2D6*10, CYP2D6*41, CYP2C19*2, CYP2C19*3, CYP2C19*17 and CYP2D6*5
The complete occurrence type for covering nonsteroidal anti-estrogens drug metabolism relevant enzymes gene pleiomorphism, it can be advantageous to use
The relapse and metastasis risk after assessing nonsteroidal anti-estrogens drug therapy.Inventor has found the gene pleiomorphism number in these sites
According to directly affecting sensibility of the patient to drug, and then lead to the difference of therapeutic effect.The present invention by with after endocrine therapy
The research of detection tumor development related gene expression situation compares, it is found that above-mentioned 10 gene locis chosen more can be from
Basic mechanism of drug action, metabolic mechanism direction prediction relapse and metastasis risk, and relapse and metastasis risk assessment, drug are treated
Before effect predicted time point is significantly advanced to drug administration.
In certain embodiments, the polymorphism data in different genes site can be by using any skill known in the art
Art means obtain.Preferably, using flight time mass spectrum come obtain CYP2D6*2, CYP2D6*3, CYP2D6*4, CYP3A5*3,
The gene pleiomorphism data of CYP2D6*10, CYP2D6*41, CYP2C19*2, CYP2C19*3 and CYP2C19*17.Flight time
Mass spectrum can realize that multiple gene locis detection of multiple samples is completed in primary experiment.With sanger PCR sequencing PCRs, NGS high-flux sequences
Method, which is compared, is greatly saved time, manpower, experiment testing cost.Preferably, the present invention detects gene in time-of-flight mass spectrometry (TOFMS)
On the basis of loci polymorphism, connected applications electrophoresis amplification detects fragmentary missing, such as detects the fragmentary of CYP2D6*5
Missing.In the present invention, it is preferable that the sample of genetic polymorphism detection can be any types, preferably peripheral blood, peripheral blood sample
It noninvasive can obtain, reduce detection sample acquisition difficulty.
[memory]
In the present invention, the memory with database is for storing at least described clinical pathology data and the gene polymorphic
Property data.Memory sheet is as usually used product in the art.Preferably, memory can be with input unit, output device
Or processor communication, to realize the effective exchange of data among different components.
In certain embodiments, the database in memory can be one or more.For example, clinical pathology data and base
It can be stored respectively in the same database or be stored respectively in because of polymorphism data in different databases.With multiple numbers
In the case of according to library, the data of each database can be interacted or be exchanged, or can carry out phase interaction with processor respectively
With or communication, so that it is guaranteed that assessment effective progress.Preferably, memory has data management component, to effectively manage
All kinds of different data improve data utilization ratio.
[processor]
In the present invention, processor is at least communicated with memory, and it is configured as：In the clinical pathology data and
Multiple independents variable are determined in the gene pleiomorphism data, the numerical value of each independent variable are calculated according to assignment rule, and utilize institute
It states numerical value and passes through algorithm model calculation risk assessed value.
In certain embodiments, it is more to be configured as the determination in clinical pathology data and gene pleiomorphism data for processor
A independent variable.Preferably, independent variable includes multiple independents variable from clinical pathology data and from gene pleiomorphism data
Multiple independents variable.Preferably, multiple independents variable from clinical pathology data be the age, whether menopause, ER, PR, Ki67,
HER2, LN shift number, tumor size and organizational hierarchy.Preferentially, multiple independents variable from gene pleiomorphism data are
CYP2D6*2、 CYP2D6*3、CYP2D6*4、CYP3A5*3、CYP2D6*10、CYP2D6*41、CYP2C19*2、 CYP2C19*
3, CYP2C19*17 and CYP2D6*5.In certain embodiments, multiple independents variable be the age, whether menopause, ER, PR, Ki67,
HER2, LN shift number, tumor size, organizational hierarchy and CYP2D6*2, CYP2D6*3, CYP2D6*4, CYP3A5*3,
CYP2D6*10、 CYP2D6*41、CYP2C19*2、CYP2C19*3、CYP2C19*17、CYP2D6*5。
In the present invention, processor can calculate the numerical value of each independent variable according to assignment rule.Assignment rule is for realizing this
The purpose of invention, that is, of crucial importance.Different assignment rules obtains different assessment results, cannot even be assessed sometimes.This
Invention has obtained one group of effective independent variable assignment rule on the basis of a large amount of further investigations.Use it for commenting for the present invention
With unexpected sensitivity and accuracy when estimating.
The clinical pathology data and gene pleiomorphism data of the present invention use different assignment rules.In certain embodiments
In, the assignment rule of clinical pathology data is：
Age was 0 more than 40 years old, and 40 years old or less is 1；
Menopause is 0, and non-menopause is 1；
It is 0 that ER, which is more than 50%, and 50% or less is 1；
It is 0 that PR, which is more than 50%, and 50% or less is 1；
Ki6720% or less is 0, and it is 1 to be more than 20%；
HER2 feminine genders are 0, and positive (3+orFish+) is 1；
It is 1 that LN, which shifts number 4 or more, and it is 0 to be less than 4；
It is 0 that longest diameter of tumor, which is less than 2cm, and longest diameter of tumor 2cm or more is 1；
It is 0 that organizational hierarchy, which is less than or equal to 2 grades, and it is 1 to be more than 2 grades.
In certain embodiments, the assignment rule of gene pleiomorphism data is described in table 1 below：
The assignment rule of 1 gene pleiomorphism data of table
In the present invention, processor passes through algorithm model calculation risk assessed value.The algorithm model of the present invention can be fixed
Algorithm model (that is, general algorithm model).Fixed algorithm model refers to the scheduled algorithm by being obtained after researching and analysing
Model, can in different objects or multiple evaluation process Reusability.The present invention is obtained at different conditions by research
Generally applicable algorithm model.Such as：
TAMRORs (1)=- 43.28+0.89CYP2D6*10+0.37CYP2C19*3+20.77LN-21.17 Age+
0.83ER-22.31HER2+64.71Grade；
TAM RORs (2)=1/ (1+e-TAMRORs(1))
Wherein, CYP2D6*10, CYP2C19*3, LN, Age, ER, HER2, Grade indicate each independent variable respectively.According to
Assignment rule, each independent variable can be different numerical value.Wherein the meaning of CYP2D6*10 refers to CYP2D6 genes at position 10
Polymorphism (other like variables described herein have similar meaning, details are not described herein), Age indicates subject age, Grade
Organizational hierarchy is indicated, for example, 2 grades of organizational hierarchy.
The algorithm model of the present invention can also be special algorithm model.The algorithm used under different condition or specific condition
Model.Wherein special algorithm model can be obtained by following step：In clinical pathology data and the gene pleiomorphism data
Determine multiple independents variable, according to assignment rule (assignment rule herein can be consistent with aforementioned assignments rule) to each independent variable into
Then row assignment carries out importance assessment, and is ranked up, choose the variable that correlation absolute value is more than threshold values, carries out logic
Regression analysis obtains each independent variable weight and formation algorithm model.Importance assessment can be used known in the art in the present invention
Any method carries out, such as logistic regression method, random forest (Random Forest) method etc..It is preferred that random forest method,
Because random forest can easily remove low correlation variable, be conducive to obtain the significant algorithm model of classifying quality.This hair
Bright threshold values can be arranged according to different demands, different condition and distinct methods, not fixed value.In certain embodiments
In, the present invention carries out importance assessment by random forest, and obtains each independent variable weight using logistic regression analysis, two kinds
The combination of analysis method is more advantageous to difference classifying quality, obtains excellent algorithm model.
In the present invention, risk assessment value is calculated according to algorithm model in processor.In an exemplary embodiment, risk
Assessed value is the result of TAM RORs (2).
[output device]
In the present invention, output device is configured to send corresponding notice according to risk assessment value.Output device can be ability
Known any device in domain.Its specific example includes various visualization devices.For example, display etc..In exemplary embodiment party
In case, when TAM RORs (2) level off to 1 when the output device send the high notice and TAM RORs (2) of relapse and metastasis risk
Level off to 0 when the output device send the low notice of relapse and metastasis risk.
Unless otherwise stated, any device known in the art can be used in the device of the invention.Not special
In the case of explanation, connection or interrelational form between the device of the invention are common connection or interrelational form.
Embodiment
124 estrogen receptor (ER) positive/progesterone receptor (PR) positives of selection receive nonsteroidal anti-estrogens medicine
The infiltrative breast carcinoma patient of object treatment is as embodiment.Using in the present invention detection method and common mathematical statistics side
Method random forest importance is assessed and logistic regression carries out relapse and metastasis risk after medical statistical analysis medication.The embodiment into
5 years nonsteroidal anti-estrogens drug therapies of row specify disease treatment situation (relapse and metastasis or without progression of disease).Specific steps
It is as follows：
One, biological blood/tissue DNA paramagnetic particle method extracts kit (model is held high using will：GO-BTXD-100 45) are extracted
Patients with Peripheral blood genomic DNA is simultaneously quantified by Qubit 3.0；
1.1 take 20 μ L Proteinase Ks, are added to 1.5mL and centrifuge bottom of the tube, by whole blood sample fully shaking mixing.30 seconds again
It takes 200 μ L to be added in centrifuge tube after 5 times reverse, shakes mixing short centrifugation after 60 seconds.Add 200 μ L lysates BL.Vortex shakes
Short centrifugation after swinging mixing 30 seconds.70 DEG C be incubated 15 minutes, 1000 revs/min concussion (if not having continuous concussion condition, can be 3 points every
Clock fully shaking is primary and action is rapid).
Ice bath 5 minutes on ice chest are put after 1.2 incubations, add the absolute ethyl alcohol and 30 μ L magnetic of 380 μ L-20 DEG C precoolings
Pearl BC, vortex vibrate mixing 30 seconds, stand 10 minutes, the 3rd minute during standing, the 6th minute difference vortex shake mixing 1
It is secondary.
Magnetic bead is drawn at once after need to being mixed well before.If vortex vibrates mixing, the continuous oscillation time is no more than 30
Second, it can repeatedly vibrate in short-term.Magnetic bead using it is front and back can be in being stored on magnetic frame.
After 1.3 absorption, vortex vibrates mixing magnetic bead, and centrifuge tube is placed on magnetic frame, overturns magnetic frame repeatedly, will
The magnetic bead that pipe cover may be deposited in is washed away into solution in pipe, is stood magnetic 1 minute or is clarified to solution, discard pipe lid and
Supernatant in pipe, not touch magnetic bead.
Sample should be mixed well before magnetic.In addition to magnetic, sample be not placed on magnetic frame by other steps.
The cleaning solution BW1 of ethyl alcohol has been added in 1.4 700 μ l of addition, and high speed vortex vibrates 1 minute, and centrifuge tube is placed in magnetic force
On frame, magnetic frame is overturned repeatedly, it would be possible to which the magnetic bead for being deposited in pipe cover is washed away into solution in pipe, stands magnetic frame magnetic
1 minute or to solution clarify, discard Guan Gai and pipe in supernatant, be careful not to touching magnetic bead.
The cleaning solution BW1 of ethyl alcohol has been added in 1.5 800 μ l of addition, is washed 1 time according to the method for step 1.4.
1.6 are added 800 μ l, 80% ethanol solutions, are washed 1 time according to the method for step 1.5.
1.7 are placed in centrifuge tube on magnetic frame, room temperature uncap dry 5-10 minutes to no ethyl alcohol remain.
1.8 50 μ l ddH are added2O is mixed well, and magnetic bead is in suspended state, and carrying out within 10 minutes DNA in 56 DEG C of warm bath washes
It is de-, the 5th minute vortex oscillation mixing 1 time.Mixing magnetic bead after elution, magnetic 1 minute or is clarified to solution, turns supernatant to new
1.5ml centrifuge tubes in.
1.9 carry out concentration mensuration by Qubit 3.0.
Two, are template by flight time mass spectrum detection of platform CYP2D6*2, CYP2D6*3 using obtained genomic DNA,
CYP2D6*4, CYP3A5*3, CYP2D6*10, CYP2D6*41, CYP 2C19*2, CYP2C19*3, CYP2C19*17 locus gene
Polymorphism and the fragmentary missings of electrophoresis detection CYP2D6*5.Primer sequence is as shown in table 2 below.Flight time mass spectrum testing result is shown in
Fig. 1-Fig. 9.Electrophoresis detection the result is shown in Figure 10.
The primer sequence of 2 each gene loci of table
2.1EXT reaction
A. EXT primers, 10*Buffer (are contained into Mg2+)、MgCl2It is standby to take out defrosting from refrigerator by (25mM), dNTP (25mM)
With.Enzyme is current now takes by Hotstar (5U/ μ l).
B. after the freezing reagent in 2.1 thaws, vortex mixing reagent is put into PCR on hand held centrifuge after short centrifugation
Low temperature box is spare.
Reaction system is as follows：
| Ingredient | Volume (μ l) |
| Template DNA (30ng/ μ l) | 1 |
| Primer Mix (0.5 μM) | 1 |
| 10*Buffer (contains Mg2+) | 0.5 |
| MgCl2(25mM) | 0.4 |
| dNTP(25mM) | 0.1 |
| Hotstar(5U/μl) | 0.2* |
| Water | 1.8 |
| Total amount | 5μl |
According to reaction system, 10*PCR Buffer (are contained into Mg2+)、MgCl2(25mM)、dNTP(25mM)、 PCRZnzyme
(5U/ μ l), water blend together MIX, are prepared according to sample 10%-15% is had more.MIX mixings, short centrifugation.According to amplification table, in 96 holes
1 μ l primers, 1 μ l template DNAs and 3 μ l Mix are sequentially added in tang plate.It is tamping with PCR sealed membranes, prevents sample from evaporating,
3000rpm centrifuges PCR instrument on 1min.
The reaction such as Figure 15 is carried out in PCR instrument.
At the end of reaction, 96 hole PCR reaction plates are taken out.
2.2SAP digestion reaction
Plank 3000rpm after aforementioned PCR centrifuges 1min, the phenomenon that having seen whether to be evaporated.
SAP enzyme Mix are prepared, by the amount for having more 10-15%.
Reaction system is as follows：
| Ingredient | Volume (μ l) |
| SAPEnzyme | 0.3 |
| SAP*Buffer | 0.17 |
| Water | 1.53 |
| Total amount | 2μl |
According to above-mentioned reaction system, SAP Enzyme, SAP*Buffer, water are blended together into MIX, according to having more sample 10%-
15% prepares.MIX mixings, short centrifugation.It takes the Mix of 2 μ l to be added in each hole, sealed membrane is covered tightly, 3000rpm centrifugations
1min。
SAP enzymic digestions are carried out in PCR instrument：
37℃ 40min
85℃ 5min
4℃ hold
Digestion finishes, and takes out 96 hole reaction plates, estimates the situation that evaporates.
2.3UEP reacts (Single base extension)
SAP reaction plates are put into 3000rpm in centrifuge and centrifuge 1min.
It prepares and extends Mix：
| Ingredient | Volume (μ l) |
| Primer Mix | 0.94 |
| iPLEX*BufferPLUS | 0.2 |
| iPLEXTerminationmix | 0.2 |
| iPLEXEnzyme | 0.041 |
| Water | 0.619 |
| Total amount | 2μl |
According to above-mentioned reaction system, Gold*Buffer, Termination mix, Enzyme, water are blended together into MIX, shaken
It swings, short centrifugation.It takes 0.94 μ l UEP primers (terminating primer Mix) and 1.06 μ l Mix to be added in each hole respectively, will seal
Membrane cover is tight, and 3000rpm centrifuges 1min.
The reaction such as Figure 16 is carried out in PCR instrument.
Reaction finishes, and takes out 96 hole reaction plates, estimates the situation that evaporates.
2.4 purifying resin
A. a clean A4 paper is taken, 96 orifice plates of 6MG is placed on it, with small bale-out quantity of resin.It is anti-with plastic cover plate
Multiple left and right is bulldozed resin, is compacted, and makes every hole resin content uniformly (if resin is moist, can first spread resin out, dry).
B. 96 orifice plate 3000rpm are centrifuged into 1min, adds 42 μ l water, envelope sealed membrane centrifugation primary per hole.By 50 μ l after centrifugation
Product is transferred in 96 hole PCR plate of flat mouth, seals sealed membrane, and 3000rpm centrifuges 1min.
C. 96 orifice plates are placed on 96 hole brackets, gently turn around and is pressed on 96 orifice plates of 6MG, two plates are aligned, are turned over again
Turn, 6MG plates beat 6MG backs, resin is made to fall into 96 orifice plates equipped with single base extension product upper.Wait for that resin enters
In 96 orifice plates, 96 orifice plates of 6MG (attention is gently taken, and prevents other holes from falling into resin) are taken away, sealed membrane is sealed equipped with Single base extension
Plank is fixed on vertical blending instrument by 96 orifice plates of product and resin with rubber band, and 15rpm, 30min, turn upside down plank, makes
Resin is scattered in water, fully purifies.Mixing terminates, and 3000rpm centrifuges 1min.
Machine testing (flight time mass spectrum model on 2.6：Analyzer4；Testing result is shown in Fig. 1-Fig. 9)
2.7 electrophoresis detection
A. after reagent to be frozen thaws, vortex mixing reagent is put into PCR low temperature box on hand held centrifuge after short centrifugation
It is spare.
Amplification reaction system：
| Ingredient | Volume (μ l) |
| GCBuffer1 | 12.5 |
| dNTP(25mM) | 4 |
| LA-Taq | 0.25 |
| PrimerF(10P) | 1 |
| PrimerR(10P) | 1 |
| Template DNA (100ng-200ng) | 3 |
| ddH2O | 3.25 |
| Total amount | 25μl |
B. the reaction such as Figure 17 is carried out in PCR instrument.
C. electrophoresis detection (electrophoresis detection the result is shown in Figure 1 0)
Electrophoresis gum concentration：1.0%
Voltage：170V
Marker types：DL5000 2μl
Sample:Orange G：3μl:3μl
Electrophoresis duration：30min
Two pairs of primer amplifications：Product distinguishes 1.5K, covering part deletion fragment；Deletion fragment is completely covered in 3K.Electrophoresis knot
Fruit integrates interpretation by two pairs of primers.
Three, summarize clinical and pathological information, including：Age, menopausal state, ER, PR, Ki67, HER2, LN shift number,
Tumor size, organizational hierarchy totally 9.
Four, 19 independents variable summarized in second and three parts are subjected to assignment：According to three genes, 10 locus genes
Influence of the polymorphism to enzyme activity carries out assignment, and assignment rule is as shown in table 3 below：
3 gene pleiomorphism data assignment rule of table
Clinical pathological factors carry out assignment according to the influence to malignancy, medication condition.Assignment rule such as the following table 4
It is shown：
4 clinical pathology data assignment rule of table
Five, obtained in four 19 independent variable assignment tables are subjected to random forest and carry out importance assessment.The result is shown in Figure 12.
Six, 19 variables are obtained from the 5th step, by importance ranking, reject the independent variable that scoring absolute value is less than 10,
Remaining 7 independents variable carry out logistic regression analysis and obtain each independent variable weight and form logistic regression classifying quality significantly calculating
Method model.Confidence interval：95%, AUC：87.20%, Coefficients are the weighted value of each variable, and to dependent variable
Coefficient.As a result as shown in table 5 below：
Table 5TAM RORs algorithm parameters and independent variable weight coefficient table
Following algorithm model is obtained by weight coefficient：
TAMRORs (1)=- 43.28+0.89CYP2D6*10+0.37CYP2C19*3+20.77LN-21.17Age+
0.83ER-22.31HER2+64.71Grade
TAMRORs (2)=1/ (1+e-TAMRORs(1))
Seven, it brings assignment table (see Figure 11) information of embodiment into obtained in step 6 model, is determined according to clinic
Treatment results after medication in 5 years (relapse and metastasis or without progression of disease) can show that the patient of TAM RORs score values high (level off to 1) is multiple
Hair shifts risk higher, and relapse and metastasis risk is relatively low after the patient medication of TAM RORs score values low (level off to 0).
Example：
Test 1 (first patient in assignment sample table)：
TAMRORs (1)=- 43.28+0.89*2+0.37*0+20.77*0-21.17*0+0.83*1-22.31*0+
64.71*1=24.04
TAMRORs (2)=1/1+e-24.04=1
Relapse and metastasis risk is higher after TAMRORs=1 medicine taking promptings
Test 2 (last patient in assignment sample table)：
TAMRORs (1)=- 43.28+0.89*1+0.37*0+20.77*0-21.17*1+0.83*1-22.31*0+
64.71*0=-62.73
TAMRORs (2)=1/1+e-(-62.73)=5.74E-19
Relapse and metastasis risk is relatively low after TAMRORs=5.74E-19 medicine taking promptings.
Eight, using with algorithm model in unduplicated the 6th step of verification sample pair of test sample in the 4th step carry out verification obtain
Obtain model sensitivity and specific findings；Algorithm model sensitivity and specific findings ROC are as shown in figure 13, verification algorithm mould
Type prediction result is as shown in figure 14.
Without departing substantially from the scope or spirit of the invention, the specific implementation mode of description of the invention can be done more
Kind is improved and variation, this will be apparent to those skilled in the art.Other realities obtained by the specification of the present invention
It is apparent obtain to apply mode for technical personnel.Present specification and embodiment are merely exemplary.
Claims (10)
1. a kind of computer system for assessing relapse and metastasis risk after nonsteroidal anti-estrogens drug therapy comprising：
Input unit for receiving object data, wherein the object data includes the clinical pathology data from the object
With gene pleiomorphism data；
Memory with database is used to store at least described clinical pathology data and the gene pleiomorphism data；
Processor is communicated with memory, and is configured as：
Multiple independents variable are determined in the clinical pathology data and the gene pleiomorphism data, are calculated according to assignment rule each
The numerical value of a independent variable, and pass through algorithm model calculation risk assessed value using the numerical value；With
It is configured to send the output device of notice according to the risk assessment value.
2. computer system according to claim 1, wherein from the age, absolutely whether the clinical pathology data include
Through, ER, PR, Ki67, HER2, LN transfer number, the data of tumor size and organizational hierarchy；And the gene pleiomorphism data packet
Include the data from CYP3A5, CYP2D6 and CYP2C19.
3. computer system according to claim 2, wherein the gene pleiomorphism data include from CYP2D6*2,
CYP2D6*3、CYP2D6*4、CYP3A5*3、CYP2D6*10、CYP2D6*41、CYP2C19*2、CYP2C19*3、CYP2C19*17
With the gene pleiomorphism data of CYP2D6*5.
4. computer system according to claim 3, wherein detecting CYP2D6*2, CYP2D6* by flight time mass spectrum
3, the gene of CYP2D6*4, CYP3A5*3, CYP2D6*10, CYP2D6*41, CYP2C19*2, CYP2C19*3 and CYP2C19*17
Polymorphism data.
5. computer system according to claim 3, wherein the fragmentary missing by expanding electrophoresis detection CYP2D6*5
Data.
6. computer system according to claim 3, wherein the algorithm model is obtained by following step：
Multiple independents variable are determined in the clinical pathology data and the gene pleiomorphism data, according to assignment rule to each
Independent variable carries out assignment, then carries out importance assessment, and be ranked up, and chooses the variable that correlation absolute value is more than threshold values,
It carries out logistic regression analysis and obtains each independent variable weight and formation algorithm model.
7. computer system according to claim 3, wherein the algorithm model is：
TAMRORs (1)=- 43.28+0.89CYP2D6*10+0.37CYP2C19*3+20.77LN-21.17Age+0.83E R-
22.31HER2+64.71Grade；
TAM RORs (2)=1/ (1+e-TAMRORs(1))。
8. computer system according to claim 7, wherein when TAM RORs (2) level off to 1 when, the output device hair
The notice for sending relapse and metastasis risk high；With when TAM RORs (2) level off to 0 when, the output device sends relapse and metastasis risk
Low notice.
9. computer system according to claim 1 or 6, wherein the assignment rule of the clinical pathology data is：
Age was 0 more than 40 years old, and 40 years old or less is 1；
Menopause is 0, and non-menopause is 1；
It is 0 that ER, which is more than 50%, and 50% or less is 1；
It is 0 that PR, which is more than 50%, and 50% or less is 1；
Ki6720% or less is 0, and it is 1 to be more than 20%；
HER2 feminine genders are 0, and positive (3+orFish+) is 1；
It is 1 that LN, which shifts number 4 or more, and it is 0 to be less than 4；
It is 0 that longest diameter of tumor, which is less than 2cm, and longest diameter of tumor 2cm or more is 1；
It is 0 that organizational hierarchy, which is less than or equal to 2 grades, and it is 1 to be more than 2 grades.
10. computer system according to claim 1 or 6, wherein the assignment rule of the gene pleiomorphism data is：
。
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112201357A (en) * | 2020-11-19 | 2021-01-08 | 吾征智能技术(北京)有限公司 | Disease cognitive system based on female hormone examination information |
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