CN107974506A - A kind of method and device for the instruction of acute myeloid leukemia medicine - Google Patents

Abstract

An embodiment of the present invention provides a kind of method and device for the instruction of acute myeloid leukemia medicine, method includes：The goal-based assessment gene of normal karyotype acute myeloid leukemia CN AML patients is obtained, the goal-based assessment gene is STAB1 genes；The gene expression amount that gene is assessed according to CN AML patients targets is layered the CN AML patients, and the CN AML patients are divided into prognosis bona's group and prognosis mala group；Corresponding drug information is indicated to the CN AML patients in prognosis mala group；In this way, because goal-based assessment gene only has one, therefore prognosis evaluation and disease layering can be simply carried out to CN AML patients；In addition the goal-based assessment gene is STAB1 genes, because STAB1 genes are membrane protein gene, therefore can be quickly detected using existing detection device, improve detection efficiency.

Description

A kind of method and device for the instruction of acute myeloid leukemia medicine

Technical field

The invention belongs to field of molecular biotechnology, more particularly to a kind of side for the instruction of acute myeloid leukemia medicine Method and device.

Background technology

Acute myeloid leukaemia (AML, Acute Myeloid Leukemia) is that one kind is obstructed with candidate stem cell differentiation Cause different phase immature cell abnormality proliferation and normal hematopoiesis tissue reduces the malignant clone disease being characterized, serious shadow Ring the health of the mankind.

AML prognosis can be divided into according to cytogenetics layering by low danger group, middle danger group and high-risk group, wherein, it is divided in Normal (CN-AML, the Cytogenetically normal Acute Myeloid Leukemia) patient of the caryogram of middle danger group Whole AML patients 50% are accounted for, this kind of patient has obvious heterogeneity, and there are notable difference for prognosis.

Can detect the change of molecular genetics in CN-AML patient at present, including with the relevant gene of CN-AML prognosis Mutation and the change of gene expression, are then combined multinomial clinical indication using molecular genetics and combination, such as：Gene mutation, Patient age, cytogenetics level and gene expression etc., which carry out joint marking, can realize the prognosis evaluation of CN-AML patient. But the process of this appraisal procedure is very cumbersome, and the disease layering of prognosis evaluation cannot be effectively performed, can not be to phase Answer the patient of level to indicate corresponding drug information, cause clinic to formulate treatment as early as possible according to corresponding medicine configured information Scheme, delay treatment opportunity.

The content of the invention

In view of the problems of the existing technology, an embodiment of the present invention provides one kind to be used for the white blood of normal karyotype acute myeloid The method and device of medicine instruction, for solving that effectively, simply prognosis cannot be carried out to CN-AML patient in the prior art Assessment and disease layering, and corresponding drug information cannot be indicated to the patient of corresponding level, cause clinic cannot be according to corresponding Medicine instruction rapid development therapeutic scheme, the technical problem on delay treatment opportunity.

The present invention provides a kind of method for the instruction of acute myeloid leukemia medicine, the described method includes：

The goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient is obtained, the goal-based assessment gene is STAB1 genes；

The gene expression amount that gene is assessed according to CN-AML patients targets is layered the CN-AML patient, by described in CN-AML patient is divided into prognosis bona's group and prognosis mala group；

Corresponding drug information is indicated to the CN-AML patient in prognosis mala group.

It is described that the gene expression amount of gene is assessed to the CN-AML patient according to CN-AML patients targets in such scheme Prognosis life span be layered, including：

Obtain each gene expression amount of the goal-based assessment gene in target sample；

Determine the median of each gene expression amount；

When the gene expression amount that the CN-AML patients targets assess gene is more than the intermediate value, the CN-AML is determined The goal-based assessment gene of patient is cance high-expression gene, and the current CN-AML patient is divided into prognosis mala group；

When the gene expression amount that the CN-AML patients targets assess gene is less than the intermediate value, the CN-AML is determined The goal-based assessment gene of patient is low expression gene, and the current CN-AML patient is divided into prognosis bona's group.

In such scheme, the described couple of CN-AML patient in prognosis mala group indicates corresponding drug information, including：

Obtain the antagonist of multiple medicines in sensitive to drug target or drug resistant gene and cancer drug database 503nhibiting concentration IC50 values, the drug target are Empirical drug clinically；

Determine the expression quantity of the STAB1 genes with described to medicaments insensitive or drug resistant gene using Pearson's function Correlation between expression quantity, if the expression quantity of the STAB1 genes with described to medicaments insensitive or drug resistant gene expression Correlation between amount is positive correlation, then the instruction medicine using the drug target as the CN-AML patient in prognosis mala group Thing；

The 503nhibiting concentration IC50 values of the Drug Antagonists in cancer drug database are determined using Pearson's function With the correlation of the STAB1 gene expression amounts, if the being proportionate property of the IC50 values and the STAB1 gene expression amounts, The then instruction medicine using the medicine as the CN-AML patient in prognosis mala group.

In such scheme, the described couple of CN-AML patient in prognosis mala group indicates corresponding drug information, including：

CN-AML patient in prognosis mala group is indicated cytarabine medicine, micromolecular inhibitor NVP-BHG712, Micromolecular inhibitor GSK-J4, micromolecular inhibitor BRD-K30748066 and Tao Zhasai replace Tozasertib drug informations.

In such scheme, the described method includes：

The gene expression information of target sample is obtained from database, the target sample is white for normal karyotype acute myeloid The sample of blood disease CN-AML patient；

It is criteria for classification according to default life span, the target sample is divided into first kind sample and the second class sample This, the time is less than the sample of 2 years to the first kind sample for survival, and the time is more than the sample of 2 years to the second class sample for survival This；

The gene of the first kind sample and the second class sample is screened according to default first screening conditions, Obtain multiple difference expression genes；

The multiple difference expression gene is screened according to default second screening conditions, when obtaining with the existence Between relevant multiple prognosis relevant difference expressing genes；

Being obtained from the database influences the clinical factors of the CN-AML prognosis, according to the influence CN-AML prognosis Clinical factors and influence the experience prognostic factor of acute myeloid leukemia AML existence the multiple prognosis relevant difference expressed Gene carries out multifactor Proportional hazards Cox regression analyses, obtains each independent prognostic gene；

Each independent prognostic gene is verified respectively according to default verification sample set, is determined according to verification result The goal-based assessment gene.

In such scheme, the gene expression information that target sample is obtained from database, including：

The gene expression information of default number of samples is obtained from cancer gene database TCGA；

According to the sample identification of target sample, the gene expression that target sample is extracted from the default number of samples is believed Breath.

In such scheme, it is described according to default first screening conditions to the first kind sample and the second class sample Gene screened, obtain multiple difference expression genes, including：

According to first screening conditions in all genes in the first kind sample and the second class sample All genes are screened, and obtain multiple difference expression genes；Wherein, first screening conditions are false positive gene False positive rate FDR<The 0.05 and fold differences fold-change of gene>1.5.

It is described that the multiple difference expression gene is screened according to default second screening conditions in such scheme, Acquisition and the relevant multiple prognosis relevant difference expressing genes of the life span, including：

The means of subsistence of each difference expression gene respectively in the target sample is obtained, the means of subsistence includes： Gene expression amount, each difference expression gene of each difference expression gene correspond to the life span and survival condition of sample；

Based on the means of subsistence of each difference expression gene, using the curvilinear function in KM statistical tools to each difference Different expressing gene carries out survival analysis, generates the first KM survivorship curves of each difference expression gene；

The first saliency value of each difference expression gene is obtained from each first KM survivorship curves；

The first saliency value of each difference expression gene is screened according to default second screening conditions, acquisition and institute State the relevant multiple prognosis relevant difference expressing genes of life span；Wherein, second screening conditions are P≤0.05；The P For saliency value.

In such scheme, it is described according to the clinical factors for influencing the CN-AML prognosis and influence prognosis that AML survives because Son carries out multifactor Proportional hazards Cox regression analyses to the multiple prognosis relevant difference expressing gene, obtains each independent prognostic Gene, including：

According to the clinical factors for influencing the CN-AML prognosis and the prognostic factor for influencing the AML existence to the multiple Prognosis relevant difference expressing gene carries out multifactor Proportional hazards Cox regression analyses, obtains each prognosis relevant difference table Up to the second saliency value of gene；

According to default second screening conditions to the second saliency value of each prognosis relevant difference expressing gene into Row screening, obtains each independent prognostic gene；Wherein, second screening conditions are P≤0.05；The P is saliency value；

The clinical factors for influencing the CN-AML prognosis include：The tyrosine kinase 3 (FLT3) of age Age, FMS sample Mutation, dnmt rna 3A (DNMT3A) mutation, different phosphate dehydrogenase 1 (IDH1) mutation, different phosphate dehydrogenase 2 (IDH2) Mutation, RUNT associated transcription factors 1 (RUNX1) mutation and chondriogen B (MTCYB) mutation, nuclear phosphoprotein (NPM1) mutation And WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) mutation；

The experience prognostic factor of the influence AML existence includes：NPM1 mutation, IDH1 mutation, IDH2 mutation and WT1 dash forward Become.

The present invention also provides a kind of device for the instruction of acute myeloid leukemia medicine, described device includes：

Acquiring unit, it is described for obtaining the goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient Goal-based assessment gene is STAB1 genes；

Delaminating units, for according to CN-AML patients targets assess gene gene expression amount to the CN-AML patient into Row layering, is divided into prognosis bona's group and prognosis mala group by the CN-AML patient；

Indicating member, for indicating corresponding drug information to the CN-AML patient in prognosis mala group.

An embodiment of the present invention provides a kind of method and device for the instruction of acute myeloid leukemia medicine, the method Including：The goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient is obtained, the goal-based assessment gene is STAB1 genes；The gene expression amount that gene is assessed according to CN-AML patients targets is layered the CN-AML patient, by institute State CN-AML patient and be divided into prognosis bona's group and prognosis mala group；It is corresponding to CN-AML patient's instruction in prognosis mala group Drug information；In this way, CN-AML patient is divided into according to the goal-based assessment gene of CN-AML patient by prognosis bona's group and prognosis Bad group, determine the disease layering of patient；Then corresponding drug information is indicated according to the CN-AML patient to prognosis mala group, With the therapeutic scheme of adjuvant clinical rapid development prognosis mala group, avoid delay therapic opportunity；Here, because of goal-based assessment gene only There is one, therefore prognosis evaluation and disease layering can be simply carried out to CN-AML patient；In addition the goal-based assessment gene is STAB1 genes, because STAB1 genes are membrane protein gene, therefore can be quickly detected using existing detection device, improve inspection Survey efficiency.

Brief description of the drawings

Fig. 1 is the method flow schematic diagram for being used for the instruction of acute myeloid leukemia medicine that the embodiment of the present invention one provides；

Fig. 2 is the apparatus structure schematic diagram provided by Embodiment 2 of the present invention for the instruction of acute myeloid leukemia medicine；

Fig. 3 is KM survivorship curve of the STAB1 genes of the offer of the embodiment of the present invention three in TCGA CN-AML forecast samples Schematic diagram；

Fig. 4 is that KM survivorship curve of the STAB1 genes of the offer of the embodiment of the present invention three in GSE12417A forecast samples shows It is intended to；

Fig. 5 is that KM survivorship curve of the STAB1 genes of the offer of the embodiment of the present invention three in GSE71014 forecast samples shows It is intended to；

Fig. 6 is KM survivorship curve signal of the STAB1 genes of the offer of the embodiment of the present invention three in GSE6891 forecast samples Figure.

Embodiment

In order to solve cannot effectively, simply to carry out disease layering and the medicine of prognosis to CN-AML patient in the prior art Instruction, causes clinic to be indicated to formulate therapeutic scheme as early as possible according to corresponding medicine, the technical problem on delay treatment opportunity, this Inventive embodiments provide a kind of method and device for the instruction of acute myeloid leukemia medicine, the described method includes：Obtain The goal-based assessment gene of CN-AML patient, the goal-based assessment gene are STAB1 genes；Base is assessed according to CN-AML patients targets The gene expression amount of cause is layered the CN-AML patient, and the CN-AML patient is divided into prognosis bona's group and prognosis not Good group；Corresponding drug information is indicated to the CN-AML patient in prognosis mala group.

Technical scheme is described in further detail below by drawings and the specific embodiments.

Embodiment one

The present embodiment provides a kind of method for the instruction of acute myeloid leukemia medicine, as shown in Figure 1, the method bag Include：

S111, obtains the goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient, the goal-based assessment Gene is STAB1 genes；

In this step, obtain normal karyotype acute myeloid leukemia CN-AML patient goal-based assessment gene before, it is necessary to First determine which gene goal-based assessment gene is, specific determination mode is as follows：

The gene expression information of target sample is obtained from database, the target sample is white for normal karyotype acute myeloid The sample of blood disease CN-AML patient；

In this step, downloaded from cancer gene database (TCGA, The Cancer Genome Atlas) and obtain present count The gene expression information of sample is measured, default sample includes：Normal karyotype acute myeloid leukemia CN-AML patient's and abnormal core The gene expression information of type Patients with Acute Myeloid Leukemia, the gene expression information include：Gene expression amount.

Here, because in data, CN-AML patient and abnormal karyotype Patients with Acute Myeloid Leukemia sample identification is Different, therefore the gene of target sample according to the sample identification of target sample, can be extracted from the default number of samples Expressing information.The target sample is the gene expression information of CN-AML patient.

It is criteria for classification according to default life span after getting target sample, the target sample is divided into first Class sample and the second class sample；The default life span is the experience index of clinically CN-AML complete incidence graphs, is specially 2 Year.The time is less than the sample of 2 years to first kind sample described in this implementation for survival, and the time is more than the second class sample for survival The sample of 2 years.

After getting first kind sample and the second class sample, according to first screening conditions, statistical modeling instrument R is utilized All genes in all genes and the second class sample in first kind sample described in the Deseq function pairs of bag are sieved Choosing, obtains multiple difference expression genes；Wherein, first screening conditions are the false positive rate (FDR) of false positive gene< 0.05 and the fold differences (fold-change) of gene>1.5.

After getting difference expression gene, the multiple difference expression gene is carried out according to default second screening conditions Screening, obtains and the relevant multiple prognosis relevant difference expressing genes of the life span.

Specifically, the means of subsistence of each difference expression gene respectively in the target sample, the existence money are obtained Material includes：Gene expression amount, each difference expression gene of each difference expression gene correspond to life span and the existence of sample State；The survival condition is the state of life or death, and raw state can be corresponded to 1, and dead state can be corresponded to 0.

Based on the means of subsistence of each difference expression gene, using the curvilinear function survival in R bags to each Difference expression gene carries out survival analysis, generates the first KM survivorship curves of each difference expression gene；

The first saliency value of each difference expression gene is obtained from each first KM survivorship curves；

The first saliency value of each difference expression gene is screened according to default second screening conditions, acquisition and institute State the relevant multiple prognosis relevant difference expressing genes of life span；Wherein, second screening conditions are P≤0.05；The P For saliency value.

For example by taking Gene A as an example, Gene A, there are a gene expression amount, determines target sample in each target sample The median (intermediate value) that expression of Gene A measures in this, is more than intermediate value using the Log Rank test functions in KM by expression quantity Sample and expression quantity be less than intermediate value sample distinguish, generate form；The sample that expression quantity is more than intermediate value is high expression quantity Sample, the sample that expression quantity is less than intermediate value is low expression amount sample.

Then according to the means of subsistence of Gene A, using the first KM survivorship curves of R bag survival functions generation Gene A, And the saliency value P values of Gene A are read from the first KM survivorship curves of the Gene A, it is definite when the P values≤0.05 of Gene A Gene A be and the relevant difference expression gene of the life span.

After determining the relevant multiple prognosis relevant difference expressing genes of the life span, according to the influence CN-AML The clinical factors of prognosis and the prognostic factor of influence acute myeloid leukemia AML existence express the multiple prognosis relevant difference Gene carries out multifactor Proportional hazards Cox regression analyses, obtains each prognostic gene.

Specifically, it is necessary first to which the clinical factors for influencing the CN-AML prognosis are screened.

There is also the need to the clinical factors of the influence CN-AML prognosis are obtained from the database.It is specific as follows：From The clinical information of target sample is obtained in database, using the survival functions of R bags, the clinical information of combining target sample, Filter out the significant clinical factors of statistical significance.As the p≤0.1 of the clinical factors, being considered as the clinical factors has system Meter learns meaning, you can be used as the clinical factors for influencing CN-AML prognosis.In the present embodiment influence CN-AML prognosis it is clinical because Attached bag includes：Tyrosine kinase 3 (FLT3) mutation of age Age, FMS sample, dnmt rna 3A (DNMT3A) mutation, different phosphorus Acidohydrogenase 1 (IDH1) mutation, different phosphate dehydrogenase 2 (IDH2) mutation, RUNT associated transcription factors 1 (RUNX1) mutation and line Mitochondrial genes B (MTCYB) mutation, nuclear phosphoprotein (NPM1) mutation and WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) mutation.

Then the experience prognostic factor for the influence AML existence assert in conjunction with document and clinically, the influence AML existence Prognostic factor include：Nuclear phosphoprotein (NPM1) mutation, different phosphate dehydrogenase 1 (IDH1) mutation, different phosphate dehydrogenase 2 (IDH2) Mutation and WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) mutation.

The prognosis finally survived according to the clinical factors and influence acute myeloid leukemia AML that influence the CN-AML prognosis The multiple prognosis relevant difference expressing gene of factor pair carries out multifactor Proportional hazards Cox regression analyses, obtains each described Second saliency value of prognosis relevant difference expressing gene.

As the second saliency value P≤0.05, then illustrate the gene be independently of Age, FLT3 mutation, DNMT3A mutation, The independent prognostic gene of IDH1 mutation, RUNX1 mutation, MT_CYB mutation, NPM1 mutation, IDH2 mutation and WT1 mutation.

After getting independent prognostic gene, each independent prognostic gene is tested respectively according to default verification sample set Card, a goal-based assessment gene is determined according to verification result.The verification sample set can be from NCBI websites (https:// Www.ncbi.nlm.nih.gov/ GEO data platforms) obtain.

Specifically, each gene expression amount of each independent prognostic gene respectively in the verification sample set is obtained, it is described Verification sample set includes multiple verification samples；Obtain existence money of each independent prognostic gene respectively in each verification sample Material, the means of subsistence include：Gene expression amount, each independent prognostic gene pairs of each independent prognostic gene answer the life of sample Deposit time and survival condition；The means of subsistence based on each independent prognostic gene in each verification sample, is counted using KM Curvilinear function in instrument carries out survival analysis to each prognostic gene, generates each prognostic gene respectively in each verification sample In the 2nd KM survivorship curves；The 3rd of each prognostic gene in each verification sample is obtained from each 2nd KM survivorship curves Saliency value；Obtain and meet each independent prognostic genes of second screening conditions and respectively verify the number of the 3rd saliency value in sample Amount, it is the goal-based assessment base to meet the corresponding independent prognostic gene of the 3rd saliency value of the quantity of the second screening conditions at most Cause；The goal-based assessment gene is STAB1 genes.

For example independent prognostic gene includes gene B, C and D；Verification sample includes：A, b and c；For by taking gene B as an example, Each gene expression amounts of each gene B respectively in each verification sample is obtained, while obtains the life in each verification sample Deposit data.

Then the means of subsistence according to gene B in each verification sample, gene is generated using R bag survival functions respectively The 3rd KM survivorship curves of B, and read gene B on the 3rd KM survivorship curves in different verification samples from the gene B and exist P values in difference verification sample, then the P value quantity for meeting the second screening conditions is counted, second screening conditions are saliency value P ≤0.05。

Then gene C and D the P values in each verification sample are counted in the same way, are determined for compliance with the P of the second screening conditions It is worth quantity.

Assuming that the quantity that P values of the gene B in each verification sample meets the second screening conditions is 3, gene C is in each verification sample The quantity that P values in this meet the second screening conditions is 2, and P values of the gene D in each verification sample meets the second screening conditions Quantity is 1, then it is goal-based assessment gene to determine that gene B.

Here, because goal-based assessment gene is STAB1 genes, it can utilize flow cytometer detection instrument quick obtaining CN-AML patient's Goal-based assessment gene, because STAB1 genes are membrane protein gene, therefore can be quickly detected using existing detection device.

S112, the gene expression amount that gene is assessed according to CN-AML patients targets are layered the CN-AML patient, The CN-AML patient is divided into prognosis bona's group and prognosis mala group.

After goal-based assessment gene is determined, the goal-based assessment gene of CN-AML patient is obtained, according to CN-AML patient The gene expression amount of goal-based assessment gene the CN-AML patient is layered, it is good that the CN-AML patient is divided into prognosis Good group and prognosis mala group.

Here, it is also necessary to first assess the accuracy of goal-based assessment predictive genes life span.Specifically, it is determined that goal-based assessment Each gene expression amount of the gene in each forecast sample, determines gene expression amount of the goal-based assessment gene in each forecast sample Intermediate value, the sample that gene expression amount is more than to the intermediate value are determined as assessing gene high expression sample, and gene expression amount is less than should The gene of intermediate value determines assessment gene low expression sample.

Using default life span as standard, then count the of gene high expression sample is assessed in each forecast sample respectively The second quantity of gene low expression sample is assessed in one quantity, and each forecast sample；According to first quantity and described second Quantity determines accuracy rate of the goal-based assessment gene in each forecast sample.Wherein, the forecast sample includes target sample And verification sample.

For example goal-based assessment gene is gene B, when determining accuracys rate of the gene B in target sample, first by sample root According to gene, B points are assessment gene high expression sample and assessment gene low expression sample, count assessment gene high expression sample Quantity of the life span less than 2 years is m, and quantity of the life span more than 2 years for counting assessment gene low expression sample is n, So it is in the accuracy rate of target sample in calculating goal-based assessment gene B：(m+n)/S；The S is the quantity of target sample.

After accuracy rate is determined, when accuracy rate is more than 60%, it is believed that the accuracy of the goal-based assessment gene is can Capable.

Then it is assumed that when the prognosis existence of CN-AML patient is assessed according to the gene expression amount of the goal-based assessment gene Between accuracy it is higher.

Then can according to the gene expression amount of the goal-based assessment gene of CN-AML patient to the CN-AML patient into Row layering.When the gene expression amount that the CN-AML patients targets assess gene is more than the intermediate value, the CN-AML is determined The goal-based assessment gene of patient is cance high-expression gene, and the current CN-AML patient is divided into prognosis mala group；

When the gene expression amount that the CN-AML patients targets assess gene is less than the intermediate value, the CN-AML is determined The goal-based assessment gene of patient is low expression gene, and the current CN-AML patient is divided into prognosis bona's group.

S113, corresponding drug information is indicated to the CN-AML patient in prognosis mala group.

, can be with after CN-AML patient is divided into prognosis bona's group and prognosis mala group according to goal-based assessment gene expression amount Corresponding drug information is indicated to the CN-AML patient in prognosis mala group, accurately layering treatment side is specified with adjuvant clinical Case.

It is specific as follows：First need to obtain sensitive to drug target or drug resistant gene, the drug target is clinically Empirical drug, such as cytarabine；After obtaining sensitive to cytarabine or drug resistant gene, using Pearson's function of R bags STAB1 and the expression quantity correlation to cytarabine sensitivity or drug resistant gene are calculated, finds STAB1 high expression and to arabinose born of the same parents Being proportionate property of glycosides expression of drug resistance genes, you can illustrate that STAB1 high expresses sample (prognosis mala group) and can disclose this some patients To cytarabine drug resistance, that is, illustrate to need to increase cytarabine dosage in STAB1 high expresses PATIENT POPULATION or select other Therapeutic scheme.

Calculate GDSC (Drug Sensitivity in Cancer) and CTRP (Cancer respectively at the same time Therapeutics Response Portal) the 503nhibiting concentration IC50 values of Drug Antagonists are expressed with STAB1 in database The Pearson correlation of amount, obtains p value<The medicine of 0.05 (i.e. correlation has statistical significance), including IC50 values and STAB1 The medicine of positive correlation and negative correlation is presented in expression quantity.IC50 values show that STAB1 high expresses sample with being proportionate property of STAB1 In this, there is sensitiveness to such medicine, that is, illustrate that STAB1 high expresses patient's (prognosis mala group) to such medicaments insensitive, can Drug candidate/micromolecular inhibitor is thought of as clinic.Here STAB1 high expresses patient to micromolecular inhibitor NVP- BHG712, micromolecular inhibitor GSK-J4, little molecules in inhibiting BRD-K30748066 and Tao Zhasai are sensitive for (Tozasertib).

To sum up, when the prognosis life span of CN-AML patient is less than 2 years, for the patient of STAB1 high expression, the type patient There is the resistance to the action of a drug to cytarabine, need to improve cytarabine drug dose in STAB1 high expresses patient or select other to replace For medicine.

Meanwhile in STAB1 high expression patients, to micromolecular inhibitor NVP-BHG712, micromolecular inhibitor GSK-J4, small Molecule inhibitor BRD-K30748066 and Tao Zhasai are more sensitive for (Tozasertib), and imply that may this few class medicine energy Have certain effect in STAB1 high expresses patient.Corresponding drug information thus is indicated to STAB1 high expression patients, Specified with adjuvant clinical and be accurately layered therapeutic scheme, avoid delay therapic opportunity.

Embodiment two

Corresponding to embodiment one, the present embodiment provides a kind of device for the instruction of acute myeloid leukemia medicine, such as Fig. 2 Shown, described device includes：Acquiring unit 21, delaminating units 22 and indicating member 23；Wherein,

Acquiring unit 21 needs before the goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient is obtained First to determine which gene goal-based assessment gene is, specific determination mode is as follows：

Acquiring unit 21 is used to download the gene expression letter for obtaining default number of samples from cancer gene database TCGA Breath, default sample include：Normal karyotype acute myeloid leukemia CN-AML patient's suffers from abnormal karyotype acute myeloid leukemia The gene expression information of person, the gene expression information include：Gene expression amount.

Because in data, CN-AML patient and abnormal karyotype Patients with Acute Myeloid Leukemia sample identification is different , therefore the gene expression of target sample according to the sample identification of target sample, can be extracted from the default number of samples Information.The target sample is the gene expression information of CN-AML patient.

After target sample is got, it is criteria for classification that taxon 24, which is used for according to default life span, by described in Target sample is divided into first kind sample and the second class sample；The default life span is clinically CN-AML complete incidence graphs Experience index, is specially 2 years.The time is less than the sample of 2 years, the second class sample to first kind sample described in this implementation for survival This for survival the time be more than the sample of 2 years.

After getting first kind sample and the second class sample, the first screening unit 25 is used for according to the default first screening bar Part, utilizes all genes in first kind sample described in the Deseq function pairs of R bags and all genes in the second class sample Screened, obtain multiple difference expression genes；Wherein, first screening conditions are the false positive of difference expression gene Rate (FDR)<0.05 and the fold differences (fold-change) of difference expression gene>1.5.

After getting difference expression gene, the second screening unit 26 is used for according to default second screening conditions to described more A difference expression gene is screened, and is obtained and the relevant multiple prognosis relevant difference expressing genes of the life span.

Specifically, the means of subsistence of each difference expression gene respectively in the target sample, the existence money are obtained Material includes：Gene expression amount, each difference expression gene of each difference expression gene correspond to life span and the existence of sample State；The survival condition is the state of life or death, and raw state can be corresponded to 1, and dead state can be corresponded to 0.

Based on the means of subsistence of each difference expression gene, using the curvilinear function survival in R bags to each Difference expression gene carries out survival analysis, generates the first KM survivorship curves of each difference expression gene；

The first saliency value of each difference expression gene is obtained from each first KM survivorship curves；

The first saliency value of each difference expression gene is screened according to default second screening conditions, acquisition and institute State the relevant multiple prognosis relevant difference expressing genes of life span；Wherein, second screening conditions are P≤0.05；The P For saliency value.

For example by taking Gene A as an example, Gene A, there are a gene expression amount, determines target sample in each target sample The intermediate value (median) that expression of Gene A measures in this, is more than intermediate value using the Log Rank test functions in KM by expression quantity Sample and expression quantity be less than intermediate value sample distinguish, generate form；The sample that expression quantity is more than intermediate value is high expression quantity Sample, the sample that expression quantity is less than intermediate value is low expression amount sample.

Then according to the means of subsistence of Gene A, using the first KM survivorship curves of R bag survival functions generation Gene A, And the saliency value P values of Gene A are read from the first KM survivorship curves of the Gene A, it is definite when the P values≤0.05 of Gene A Gene A be and the relevant difference expression gene of the life span.

After determining the relevant multiple prognosis relevant difference expressing genes of the life span, analytic unit 25 is used for basis The prognostic factor for influencing the clinical factors of the CN-AML prognosis and influencing AML existence expresses the multiple prognosis relevant difference Gene carries out multifactor Proportional hazards Cox regression analyses, obtains each prognostic gene.

Specifically, analytic unit 27 is screened firstly the need of the clinical factors to influencing the CN-AML prognosis.

There is also the need to obtain the clinical information of target sample from database, using the survival functions of R bags, with reference to The clinical information of target sample, filters out the significant clinical factors of statistical significance.As the p≤0.1 of the clinical factors, depending on There is statistical significance for the clinical factors, you can be used as the clinical factors for influencing CN-AML prognosis.Influenced in the present embodiment The clinical factors of CN-AML prognosis include：Tyrosine kinase 3 (FLT3) mutation of age Age, FMS sample, dnmt rna 3A (DNMT3A) mutation, different phosphate dehydrogenase 1 (IDH1) mutation, different phosphate dehydrogenase 2 (IDH2) mutation, RUNT associated transcription factors 1 (RUNX1) is mutated and chondriogen B (MTCYB) mutation, nuclear phosphoprotein (NPM1) mutation and WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) is mutated.

Then the prognostic factor for the influence AML existence assert in conjunction with document and clinically, the influence AML survive pre- Postfactor includes：Nuclear phosphoprotein (NPM1) mutation, different phosphate dehydrogenase 1 (IDH1) mutation, different phosphate dehydrogenase 2 (IDH2) mutation And WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) mutation.

The prognostic factor that ultimate analysis unit 27 is survived according to the clinical factors and influence AML that influence the CN-AML prognosis Multifactor Proportional hazards Cox regression analyses are carried out to the multiple prognosis relevant difference expressing gene, obtain each prognosis Second saliency value of relevant difference expressing gene.

As the second saliency value P≤0.05, then illustrate the gene be independently of Age, FLT3 mutation, DNMT3A mutation, The independent prognostic base of IDH1 mutation, RUNX1 mutation, MTCYB mutation, NPM1 mutation, IDH2 mutation and WT1mutation mutation Cause.

After getting independent prognostic gene, authentication unit 28 is used for according to default verification sample set respectively to each independence Prognostic gene is verified, a goal-based assessment gene is determined according to verification result.The verification sample set can be from NCBI nets Stand (https://www.ncbi.nlm.nih.gov/) GEO data platforms obtain.

Specifically, authentication unit 28 obtains each gene table of each independent prognostic gene respectively in the verification sample set Up to amount, the verification sample set includes multiple verification samples；Each independent prognostic gene is obtained respectively in each verification sample In the means of subsistence, the means of subsistence includes：Gene expression amount, each independent prognostic gene pairs of each independent prognostic gene Answer the life span and survival condition of sample；The means of subsistence based on each independent prognostic gene in each verification sample, Survival analysis is carried out to each prognostic gene using the curvilinear function in KM statistical tools, generates each prognostic gene respectively in each institute State the 2nd KM survivorship curves in verification sample；Each prognostic gene is obtained in each verification sample from each 2nd KM survivorship curves The 3rd saliency value in this；Obtain meet second screening conditions each independent prognostic gene respectively verify in sample the 3rd The quantity of saliency value, it is the mesh to meet the corresponding independent prognostic gene of the 3rd saliency value of the quantity of the second screening conditions at most Mark assessment gene；The goal-based assessment gene is STAB1 genes.

For example independent prognostic gene includes gene B, C and D；Verification sample includes：A, b and c；For by taking gene B as an example, Authentication unit 28 obtains each gene expression amounts of each gene B respectively in each verification sample, while obtains in each verification The means of subsistence in sample.

Then the means of subsistence according to gene B in each verification sample, gene is generated using R bag survival functions respectively The 3rd KM survivorship curves of B, and read gene B on the 3rd KM survivorship curves in different verification samples from the gene B and exist P values in difference verification sample, then the P value quantity for meeting the second screening conditions is counted, second screening conditions are saliency value P ≤0.05。

Then gene C and D the P values in each verification sample are counted in the same way, are determined for compliance with the P of the second screening conditions It is worth quantity.

Assuming that the quantity that P values of the gene B in each verification sample meets the second screening conditions is 3, gene C is in each verification sample The quantity that P values in this meet the second screening conditions is 2, and P values of the gene D in each verification sample meets the second screening conditions Quantity is 1, then it is goal-based assessment gene to determine that gene B.

After definite goal-based assessment gene, delaminating units 22 are used for the gene table that gene is assessed according to CN-AML patients targets The CN-AML patient is layered up to amount, the CN-AML patient is divided into prognosis bona's group and prognosis mala group.

Here, assessment unit 29 also needs to first assess the accuracy of goal-based assessment predictive genes life span.Specifically, really Set the goal each gene expression amount of the assessment gene in each forecast sample, determines base of the goal-based assessment gene in each forecast sample Because of the intermediate value of expression quantity, the sample that gene expression amount is more than to the intermediate value is determined as assessing gene high expression sample, by gene table Up to amount assessment gene low expression sample is determined less than the gene of the intermediate value.

Using default life span as standard, then count the of gene high expression sample is assessed in each forecast sample respectively The second quantity of gene low expression sample is assessed in one quantity, and each forecast sample；According to first quantity and described second Quantity determines accuracy rate of the goal-based assessment gene in each forecast sample.Wherein, the forecast sample includes target sample And verification sample.

For example goal-based assessment gene is gene B, when determining accuracys rate of the gene B in target sample, first by sample root According to gene, B points are assessment gene high expression sample and assessment gene low expression sample, count assessment gene high expression sample Quantity of the life span less than 2 years is m, and quantity of the life span more than 2 years for counting assessment gene low expression sample is n, So it is in the accuracy rate of target sample in calculating goal-based assessment gene B：(m+n)/S；The S is the quantity of target sample.

After assessment unit 29 determines accuracy rate, when accuracy rate is more than 60%, it is believed that the goal-based assessment gene Accuracy is feasible.

Then it is assumed that when the prognosis existence of CN-AML patient is assessed according to the gene expression amount of the goal-based assessment gene Between accuracy it is higher.

Then delaminating units 22 can be according to the gene expression amount of the goal-based assessment gene of CN-AML patient to the CN- AML patient is layered.When the gene expression amount that the CN-AML patients targets assess gene is more than the intermediate value, institute is determined The goal-based assessment gene for stating CN-AML patient is cance high-expression gene, and the current CN-AML patient is divided into prognosis mala group；

When the gene expression amount that the CN-AML patients targets assess gene is less than the intermediate value, the CN-AML is determined The goal-based assessment gene of patient is low expression gene, and the current CN-AML patient is divided into prognosis bona's group.

After delaminating units 22 determine the packet of CN-AML patient, indicating member 23 can be in prognosis mala group CN-AML patient indicates corresponding drug information, is specified with adjuvant clinical and is accurately layered therapeutic scheme, avoid delay treatment when Machine.

It is specific as follows：First need to obtain sensitive to drug target or drug resistant gene, the drug target is clinically Empirical drug, such as cytarabine；After obtaining sensitive to cytarabine or drug resistant gene, using Pearson's function of R bags STAB1 and the expression quantity correlation to cytarabine sensitivity or drug resistant gene are calculated, finds STAB1 high expression and to arabinose born of the same parents Being proportionate property of glycosides expression of drug resistance genes, you can illustrate that STAB1 high expresses sample (prognosis mala group) and can disclose this some patients To cytarabine drug resistance, that is, illustrate to need to increase cytarabine dosage in STAB1 high expresses PATIENT POPULATION or select other Therapeutic scheme.

Calculate GDSC (Drug Sensitivity in Cancer) and CTRP (Cancer respectively at the same time Therapeutics Response Portal) the 503nhibiting concentration IC50 values of Drug Antagonists are expressed with STAB1 in database The Pearson correlation of amount, obtains p value<The medicine of 0.05 (i.e. correlation has statistical significance), including IC50 values and STAB1 The medicine of positive correlation and negative correlation is presented in expression quantity.IC50 values show that STAB1 high expresses sample with being proportionate property of STAB1 In this, there is sensitiveness to such medicine, that is, illustrate that STAB1 high expresses patient's (prognosis mala group) to such medicaments insensitive, can Drug candidate/micromolecular inhibitor is thought of as clinic.Here STAB1 high expresses patient to micromolecular inhibitor NVP- BHG712, micromolecular inhibitor GSK-J4, little molecules in inhibiting BRD-K30748066 and Tao Zhasai are sensitive for (Tozasertib).

To sum up, when the prognosis life span of CN-AML patient is less than 2 years, for the patient of STAB1 high expression, the type patient There is the resistance to the action of a drug to cytarabine, need to improve cytarabine drug dose in STAB1 high expresses patient or select other to replace For medicine.

Meanwhile in STAB1 high expression patients, to micromolecular inhibitor NVP-BHG712, micromolecular inhibitor GSK-J4, small Molecules in inhibiting BRD-K30748066 and Tao Zhasai are more sensitive for (Tozasertib), imply that may this few class medicine can be Have certain effect in STAB1 high expression patients.Corresponding drug information thus is indicated to STAB1 high expression patients, with Adjuvant clinical, which is specified, is accurately layered therapeutic scheme, and avoid delay therapic opportunity.

Embodiment three

In practical application, the goal-based assessment gene of CN-AML can be determined according to the above method and device, and utilize the base Because carrying out prognosis layering to CN-AML, corresponding drug information is indicated, it is specific as follows：

The gene expression information and clinical information of 200 samples are downloaded first from TCGA databases, then according to CN- The sample identification of AML samples, extracts the gene expression information of CN-AML samples from the default number of samples.The CN-AML The quantity of sample is 79.

It is criteria for classification according to default life span, the CN-AML samples is divided into first kind sample and the second class sample This；The default life span is the experience index of clinically CN-AML complete incidence graphs, is specially 2 years.Described in this implementation The time is less than the CN-AML samples of 2 years to first kind sample for survival, and the time is more than the CN- of 2 years to the second class sample for survival AML samples.

After getting first kind sample and the second class sample, the institute in the first kind sample described in the Deseq function pairs of R bags There are all genes in gene and the second class sample to be screened, obtain multiple difference expression genes；Wherein, it is described First screening conditions are the false positive rate (FDR) of difference expression gene<0.05 and the fold differences (fold-change) of gene> 1.5.Here, the quantity of the difference expression gene is 353.

After getting difference expression gene, survival analysis is carried out to each difference expression gene using R bags survival, it is raw Into the first KM survivorship curves of each difference expression gene；The first of each difference expression gene is obtained based on the first KM survivorship curves Saliency value, filters out the prognosis relevant difference expressing gene related to the life span of saliency value P≤0.05, the prognosis phase The quantity for closing difference expression gene is 15.

Then the prognosis survived according to the clinical factors and influence acute myeloid leukemia AML that influence the CN-AML prognosis The multiple prognosis relevant difference expressing gene of factor pair carries out multifactor Proportional hazards Cox regression analyses, and it is pre- to obtain each independence Gene afterwards, the independent prognostic gene are 6.

The clinical factors of CN-AML prognosis are influenced in the present embodiment to be included：The tyrosine kinase 3 of age Age, FMS sample (FLT3) mutation, dnmt rna 3A (DNMT3A) mutation, different phosphate dehydrogenase 1 (IDH1) mutation, different phosphate dehydrogenase 2 (IDH2) mutation, RUNT associated transcription factors 1 (RUNX1) mutation and chondriogen B (MTCYB) mutation, nuclear phosphoprotein (NPM1) mutation and WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) mutation.

The prognostic factor of the influence AML existence includes：Nuclear phosphoprotein (NPM1) mutation, different phosphate dehydrogenase 1 (IDH1) Mutation, different phosphate dehydrogenase 2 (IDH2) mutation and WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) mutation.

After getting independent prognostic gene, verify sample set respectively to each independent prognostic base according to default genetic chip Because being verified, a goal-based assessment gene is determined according to verification result.The verification sample set can be obtained from GEO platforms. The verification sample set includes four groups, and the sample size of each verification sample is respectively：79th, 163,104 and 187.

Saliency value P of each independent prognostic gene in each verification sample is obtained, is determined for compliance with the P values of the second screening conditions Quantity；Second screening conditions are saliency value P≤0.05.Meet the most independent prognostic of the P value quantity of the second screening conditions Gene is goal-based assessment gene.Goal-based assessment gene in the present embodiment is STAB1.

Then the accuracy rate of STAB1 is determined using forecast sample collection, specifically, it is determined that STAB1 is in each forecast sample Each gene expression amount, determine the intermediate value of gene expression amounts of the STAB1 in each forecast sample, gene expression amount be more than in this The gene of value is determined as high expression assessment gene, and the gene that gene expression amount is more than to the intermediate value is determined as low expression gene.

Using default life span as standard, then first of high expression assessment gene in each forecast sample is counted respectively Quantity, and second quantity of the low expression assessment gene in each forecast sample；According to first quantity and second quantity Determine accuracys rate of the STAB1 in each forecast sample.Wherein, the forecast sample includes target sample and verification sample. Wherein, accuracys rate of the STAB1 in each forecast sample is as shown in table 1：

Table 1

In table 1, TCGA CN-AML (79) are target sample, remaining four groups are forecast sample, by taking target sample as an example, When calculating accuracys rate of the STAB1 in target sample, it is specially：(35+22)/79=0.72.

Then same method is recycled to calculate accuracys rate of the STAB1 in other verification samples, as can be seen from Table 1, Accuracys rate of the STAB1 in forecast sample is more than 60%, it was demonstrated that the accuracy of STAB1 is feasible.

Further, also the feasibility of STAB1 can be predicted according to KM survivorship curves of the STAB1 in each forecast sample, STAB1 genes are in TCGA CN-AML sample KM survivorship curves as shown in figure 3, STAB1 genes are in GSE12417A (79) sample KM Survivorship curve as shown in figure 4, STAB1 genes in GSE71014 (104) sample KM survivorship curves as shown in figure 5, STAB1 genes exist GSE6891 (187) sample KM survivorship curves are as shown in Figure 6.Wherein, in Fig. 3, Fig. 4, Fig. 5 and Fig. 6, the curve of top represents Be the corresponding KM survivorship curves of low expression STAB1, what the curve of lower section represented is that the corresponding KM existence of high expression STAB1 is bent Line, what corresponding n was represented respectively is the quantity of low expression sample and the quantity of high expression sample.

It should be noted that Fig. 3, Fig. 4, Fig. 5 and Fig. 6 are the quantity that low expression sample is determined according to the intermediate value of STAB1 And the quantity of high expression sample.And STAB1 high expression group and STAB1 low expressions are equally determined with the intermediate value of STAB1 in table 1 Group, but what is counted is sample size of the life span more than 2 years and STAB1 high expression samples in STAB1 low expression samples Middle life span is less than the sample size of 2 years, therefore inconsistent situation occurs in quantity.

It can be seen from Fig. 3, Fig. 4, Fig. 5 and Fig. 6 in four forecast samples, the P values of STAB1 genes are respectively less than 0.05, Also the accuracy for further illustrating STAB1 genes is feasible.

Then can according to the gene expression amount of the goal-based assessment gene of CN-AML patient to the CN-AML patient into Row layering.When the gene expression amount that the CN-AML patients targets assess gene is more than the intermediate value, the CN-AML is determined The goal-based assessment gene of patient is cance high-expression gene, and the current CN-AML patient is divided into prognosis mala group；Prognosis mala group The prognosis life span of CN-AML patient is less than 2 years；

When the gene expression amount that the CN-AML patients targets assess gene is less than the intermediate value, the CN-AML is determined The goal-based assessment gene of patient is low expression gene, and the current CN-AML patient is divided into prognosis bona's group；Prognosis bona's group The prognosis life span of CN-AML patient is more than 2 years.

, can be with after CN-AML patient is divided into prognosis bona's group and prognosis mala group according to goal-based assessment gene expression amount Corresponding drug information is indicated to the CN-AML patient in prognosis mala group, accurately layering treatment side is specified with adjuvant clinical Case, avoid delay therapic opportunity.

It is specific as follows：First need to obtain sensitive to drug target or drug resistant gene, the drug target is clinically Empirical drug, such as cytarabine；After obtaining sensitive to cytarabine or drug resistant gene, using Pearson's function of R bags STAB1 and the expression quantity correlation to cytarabine sensitivity or drug resistant gene are calculated, finds STAB1 high expression and to arabinose born of the same parents Being proportionate property of glycosides expression of drug resistance genes, you can illustrate that STAB1 high expresses sample (prognosis mala group) and can disclose this some patients To cytarabine drug resistance, that is, illustrate to need to increase cytarabine dosage in STAB1 high expresses PATIENT POPULATION or select other Therapeutic scheme.

Calculate GDSC (Drug Sensitivity in Cancer) and CTRP (Cancer respectively at the same time Therapeutics Response Portal) the 503nhibiting concentration IC50 values of Drug Antagonists are expressed with STAB1 in database The Pearson correlation of amount, obtains p value<The medicine of 0.05 (i.e. correlation has statistical significance), including IC50 values and STAB1 The medicine of positive correlation and negative correlation is presented in expression quantity.IC50 values show that STAB1 high expresses sample with being proportionate property of STAB1 In this, there is sensitiveness to such medicine, that is, illustrate that STAB1 high expresses patient's (prognosis mala group) to such medicaments insensitive, can Drug candidate/micromolecular inhibitor is thought of as clinic.Here STAB1 high expresses patient to micromolecular inhibitor NVP- BHG712, micromolecular inhibitor GSK-J4, little molecules in inhibiting BRD-K30748066 and Tao Zhasai are sensitive for (Tozasertib).

To sum up, when the prognosis life span of CN-AML patient is less than 2 years, for the patient of STAB1 high expression, the type patient There is the resistance to the action of a drug to cytarabine, need to improve cytarabine drug dose in STAB1 high expresses patient or select other to replace For medicine.

Meanwhile in STAB1 high expression patients, to micromolecular inhibitor NVP-BHG712, GSK-J4, BRD-K30748066 It is more sensitive for (Tozasertib) with Tao Zhasai, it imply that this possible a few class medicine can have one in STAB1 high expresses patient Fixed effect.Corresponding drug information thus is indicated to STAB1 high expression patients, is specified with adjuvant clinical and is accurately layered Therapeutic scheme, avoid delay therapic opportunity.

Method and device provided in an embodiment of the present invention for the instruction of acute myeloid leukemia medicine can be brought beneficial Effect is at least：

An embodiment of the present invention provides a kind of method and device for the instruction of acute myeloid leukemia medicine, the method Including：The goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient is obtained, the goal-based assessment gene is STAB1 genes；The gene expression amount that gene is assessed according to CN-AML patients targets is layered the CN-AML patient, by institute State CN-AML patient and be divided into prognosis bona's group and prognosis mala group；It is corresponding to CN-AML patient's instruction in prognosis mala group Drug information；In this way, being screened according to the difference expression gene filtered out in target sample, then to difference expression gene, obtain Take with the relevant multiple prognosis relevant difference expressing genes of life span, filter out multiple prognostic genes in conjunction with clinical information, Then each prognostic gene is verified respectively using the multigroup sample data verified in sample set, determines that a target is commented Estimate gene, CN-AML patient be divided into according to the goal-based assessment gene of CN-AML patient by prognosis bona's group and prognosis mala group, Determine the disease layering of patient；Then corresponding drug information is indicated according to the CN-AML patient to prognosis mala group, with auxiliary The therapeutic scheme that clinical rapid development is precisely layered, avoid delay therapic opportunity；Here, because definite goal-based assessment gene only has One, therefore prognosis evaluation and disease layering can be simply carried out to CN-AML patient；In addition the goal-based assessment gene is STAB1 genes, because STAB1 genes are membrane protein gene, therefore can utilize existing RT-PCR or flow cytometer to be easy and fast to Detect, improve detection efficiency, further increase the simplicity of prognosis delaminating process.

Algorithm and display be not inherently related to any certain computer, virtual system or miscellaneous equipment provided herein. Various general-purpose systems can also be used together with teaching based on this.As described above, required by constructing this kind of system Structure be obvious.In addition, the present invention is not also directed to any certain programmed language.It should be understood that it can utilize various Programming language realizes the content of invention described herein, and the description done above to language-specific is to disclose this hair Bright preferred forms.

In the specification that this place provides, numerous specific details are set forth.It is to be appreciated, however, that the implementation of the present invention Example can be put into practice in the case of these no details.In some instances, known method, structure is not been shown in detail And technology, so as not to obscure the understanding of this description.

Similarly, it will be appreciated that in order to simplify the disclosure and help to understand one or more of each inventive aspect, Above in the description to the exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes In example, figure or descriptions thereof.However, the method for the disclosure should be construed to reflect following intention：I.e. required guarantor The application claims of shield features more more than the feature being expressly recited in each claim.It is more precisely, such as following Claims reflect as, inventive aspect is all features less than single embodiment disclosed above.Therefore, Thus the claims for following embodiment are expressly incorporated in the embodiment, wherein each claim is in itself Separate embodiments all as the present invention.

Those skilled in the art, which are appreciated that, to carry out adaptively the module in the equipment in embodiment Change and they are arranged in one or more equipment different from the embodiment.Can be the module or list in embodiment Member or component be combined into a module or unit or component, and can be divided into addition multiple submodule or subelement or Sub-component.In addition at least some in such feature and/or process or unit exclude each other, it can use any Combination is disclosed to all features disclosed in this specification (including adjoint claim, summary and attached drawing) and so to appoint Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (including adjoint power Profit requires, summary and attached drawing) disclosed in each feature can be by providing the alternative features of identical, equivalent or similar purpose come generation Replace.

In addition, it will be appreciated by those of skill in the art that although some embodiments in this include institute in other embodiments Including some features rather than further feature, but the combination of the feature of different embodiment means to be in the scope of the present invention Within and form different embodiments.For example, in the following claims, embodiment claimed it is any it One mode can use in any combination.

The all parts embodiment of the present invention can be with hardware realization, or to be run on one or more processor Software module realize, or realized with combinations thereof.It will be understood by those of skill in the art that it can use in practice Microprocessor or digital signal processor (DSP) are realized in gateway according to embodiments of the present invention, proxy server, system Some or all components some or all functions.The present invention is also implemented as being used to perform side as described herein The some or all equipment or program of device (for example, computer program and computer program product) of method.It is such Realizing the program of the present invention can store on a computer-readable medium, or can have the shape of one or more signal Formula.Such signal can be downloaded from internet website and obtained, and either be provided or with any other shape on carrier signal Formula provides.

It should be noted that the present invention will be described rather than limits the invention for above-described embodiment, and ability Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.In the claims, Any reference symbol between bracket should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not Element or step listed in the claims.Word "a" or "an" before element does not exclude the presence of multiple such Element.The present invention can be by means of including the hardware of some different elements and being come by means of properly programmed computer real It is existing.In if the unit claim of equipment for drying is listed, several in these devices can be by same hardware branch To embody.The use of word first, second, and third does not indicate that any order.These words can be explained and run after fame Claim.

The foregoing is only a preferred embodiment of the present invention, is not intended to limit the scope of the present invention, it is all All any modification, equivalent and improvement made within the spirit and principles in the present invention etc., should be included in the protection of the present invention Within the scope of.

Claims (10)

1. A kind of 1. method for the instruction of acute myeloid leukemia medicine, it is characterised in that the described method includes：

   The goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient is obtained, the goal-based assessment gene is STAB1 genes；

   The gene expression amount that gene is assessed according to CN-AML patients targets is layered the CN-AML patient, by the CN- AML patient is divided into prognosis bona's group and prognosis mala group；

   Corresponding drug information is indicated to the CN-AML patient in prognosis mala group.
2. 2. the method as described in claim 1, it is characterised in that the gene table that gene is assessed according to CN-AML patients targets Prognosis life span up to amount to the CN-AML patient is layered, including：

   Obtain each gene expression amount of the goal-based assessment gene in target sample；

   Determine the median of each gene expression amount；

   When the gene expression amount that the CN-AML patients targets assess gene is more than the intermediate value, the CN-AML patient is determined Goal-based assessment gene be cance high-expression gene, the current CN-AML patient is divided into prognosis mala group；

   When the gene expression amount that the CN-AML patients targets assess gene is less than the intermediate value, the CN-AML patient is determined Goal-based assessment gene be low expression gene, the current CN-AML patient is divided into prognosis bona's group.
3. 3. the method as described in claim 1, it is characterised in that the described couple of CN-AML patient in prognosis mala group indicates phase The drug information answered, including：

   Obtain half suppression of the antagonist of multiple medicines in sensitive to drug target or drug resistant gene and cancer drug database Concentration IC50 values processed, the drug target are Empirical drug clinically；

   Determine the expression quantity of the STAB1 genes with described to medicaments insensitive or drug resistant gene expression using Pearson's function Correlation between amount, if the expression quantity of the STAB1 genes with it is described to medicaments insensitive or drug resistant gene expression amount it Between correlation be positive correlation, then using the drug target as in prognosis mala group CN-AML patient instruction medicine；

   503nhibiting concentration IC50 values and the institute of the Drug Antagonists in cancer drug database are determined using Pearson's function The correlation of STAB1 gene expression amounts is stated, will if the IC50 values and the being proportionate property of the STAB1 gene expression amounts Instruction medicine of the medicine as the CN-AML patient in prognosis mala group.
4. 4. the method as described in claim 1, it is characterised in that the described couple of CN-AML patient in prognosis mala group indicates phase The drug information answered, including：

   CN-AML patient in prognosis mala group is indicated cytarabine medicine, micromolecular inhibitor NVP-BHG712, small point Sub- inhibitor GSK-J4, micromolecular inhibitor BRD-K30748066 and Tao Zhasai replace Tozasertib drug informations.
5. 5. the method as described in claim 1, it is characterised in that the described method includes：

   The gene expression information of target sample is obtained from database, the target sample is normal karyotype acute myeloid leukemia The sample of CN-AML patient；

   It is criteria for classification according to default life span, the target sample is divided into first kind sample and the second class sample, institute Stating first kind sample, the time is less than the sample of 2 years for survival, and the time is more than the sample of 2 years to the second class sample for survival；

   The gene of the first kind sample and the second class sample is screened according to default first screening conditions, is obtained Multiple difference expression genes；

   The multiple difference expression gene is screened according to default second screening conditions, is obtained and the life span phase The multiple prognosis relevant difference expressing genes closed；

   Being obtained from the database influences the clinical factors of the CN-AML prognosis, according to facing for the influence CN-AML prognosis The bed factor and the experience prognostic factor of influence acute myeloid leukemia AML existence are to the multiple prognosis relevant difference expressing gene Multifactor Proportional hazards Cox regression analyses are carried out, obtain each independent prognostic gene；

   Each independent prognostic gene is verified respectively according to default verification sample set, according to being determined verification result Goal-based assessment gene.
6. 6. method as claimed in claim 5, it is characterised in that the gene expression letter that target sample is obtained from database Breath, including：

   The gene expression information of default number of samples is obtained from cancer gene database TCGA；

   According to the sample identification of target sample, the gene expression information of extraction target sample from the default number of samples.
7. 7. method as claimed in claim 5, it is characterised in that it is described according to default first screening conditions to the first kind The gene of sample and the second class sample is screened, and obtains multiple difference expression genes, including：

   According to first screening conditions to all in all genes in the first kind sample and the second class sample Gene is screened, and obtains multiple difference expression genes；Wherein, first screening conditions are positive for the vacation of false positive gene Property rate FDR<The 0.05 and fold differences fold-change of gene>1.5.
8. 8. method as claimed in claim 5, it is characterised in that it is described according to default second screening conditions to the multiple difference Different expressing gene is screened, acquisition and the relevant multiple prognosis relevant difference expressing genes of the life span, including：

   The means of subsistence of each difference expression gene respectively in the target sample is obtained, the means of subsistence includes：Each The gene expression amount of difference expression gene, each difference expression gene correspond to the life span and survival condition of sample；

   Based on the means of subsistence of each difference expression gene, using the curvilinear function in KM statistical tools to each difference table Survival analysis is carried out up to gene, generates the first KM survivorship curves of each difference expression gene；

   The first saliency value of each difference expression gene is obtained from each first KM survivorship curves；

   The first saliency value of each difference expression gene is screened according to default second screening conditions, is obtained and the life Deposit multiple prognosis relevant difference expressing genes of time correlation；Wherein, second screening conditions are P≤0.05；The P is aobvious Work value.
9. 9. method as claimed in claim 5, it is characterised in that it is described according to the clinical factors for influencing the CN-AML prognosis and The prognostic factor for influencing AML existence carries out the multiple prognosis relevant difference expressing gene multifactor Proportional hazards Cox recurrence Analysis, obtains each independent prognostic gene, including：

   According to the clinical factors for influencing the CN-AML prognosis and the prognostic factor for influencing the AML existence to the multiple prognosis Relevant difference expressing gene carries out multifactor Proportional hazards Cox regression analyses, obtains each prognosis relevant difference expression base Second saliency value of cause；

   The second saliency value of each prognosis relevant difference expressing gene is sieved according to default second screening conditions Choosing, obtains each independent prognostic gene；Wherein, second screening conditions are P≤0.05；The P is saliency value；

   The clinical factors for influencing the CN-AML prognosis include：The tyrosine kinase 3 (FLT3) of age Age, FMS sample is prominent Become, dnmt rna 3A (DNMT3A) is mutated, different phosphate dehydrogenase 1 (IDH1) is mutated, different phosphate dehydrogenase 2 (IDH2) is prominent Become, RUNT associated transcription factors 1 (RUNX1) mutation and chondriogen B (MTCYB) mutation, nuclear phosphoprotein (NPM1) mutation and WILLIAMS-DARLING Ton tumor suppressor 1 (WT1) is mutated；

   The experience prognostic factor of the influence AML existence includes：NPM1 mutation, IDH1 mutation, IDH2 mutation and WT1 mutation.
10. 10. a kind of device for the instruction of acute myeloid leukemia medicine, it is characterised in that described device includes：

    Acquiring unit, for obtaining the goal-based assessment gene of normal karyotype acute myeloid leukemia CN-AML patient, the target Assessment gene is STAB1 genes；

    Delaminating units, the gene expression amount for assessing gene according to CN-AML patients targets divide the CN-AML patient Layer, is divided into prognosis bona's group and prognosis mala group by the CN-AML patient；

    Indicating member, for indicating corresponding drug information to the CN-AML patient in prognosis mala group.