Pharmaceutical activity prediction and selection method based on genetic expressions and drug targets

A technology of drug activity and screening method, applied in the field of biomedicine, can solve the problems of overfitting, not considering biological mechanism, affecting practical value, etc., and achieve the effect of easy use, wide application range and high efficiency

Inactive Publication Date: 2016-10-26
HUAZHONG AGRI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method needs to establish a prediction model for each disease, and the construction of each model requires a large number of gene expression data sets, which greatly affects the practical value of this type of method
At the same time, due to the high heterogeneity of complex diseases such as cancer (see: Burrell R A, McGranahan N, Bartek J, et al. The causes and consequences of geneticheterogeneity in cancer evolution [J]. Nature, 2013, 501(7467 ):338-345.), this completely data-driven method that does not consider the biological mechanism behind the disease has overfitting phenomenon

Method used

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  • Pharmaceutical activity prediction and selection method based on genetic expressions and drug targets
  • Pharmaceutical activity prediction and selection method based on genetic expressions and drug targets
  • Pharmaceutical activity prediction and selection method based on genetic expressions and drug targets

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] Using the method of the present invention to predict the drug activity of ovarian cancer patients

[0044] 1. Collect human successfully marketed or researched drugs and their targets

[0045] Find drug target databases (including DGIdb: http: / / dgidb.genome.wustl.edu / , DrugBank: http: / / www.drugbank.ca / and TTD: http: / / bidd.nus.edu.sg / group / ttd / ttd.asp), to get all the drugs contained in the database and their corresponding target data.

[0046] 2. Collection of gene expression data and clinical data of ovarian cancer patient samples

[0047] The gene expression data (level 3 data of AgilentG4502A chip), the patient's prognosis tracking data (death time, death status) and the patient's medication information of ovarian cancer (OV) patients and control samples were downloaded from TCGA (The Cancer Genome Atlas). Excluding samples with lack of drug information (or unknown drug targets) and missing prognostic information, a total of 499 cancer patients and 10 normal ov...

Embodiment 2

[0056] Prediction of drug activity in patients with glioblastoma multiforme using the method of the invention

[0057] The steps of this embodiment are the same as embodiment 1, and the other steps are as follows:

[0058] 2. Collection of gene expression data and clinical data of glioblastoma multiforme patient samples

[0059] Download the gene expression data (level 3 data of AgilentG4502A chip) of glioblastoma multiforme patients (GBM) and control samples from TCGA (The Cancer Genome Atlas), the patient's prognosis tracking data (death time, death status) and Patient medication information. Excluding samples with lack of drug information (or unknown drug targets) and missing prognostic information, a total of 193 cancer patients and 10 corresponding normal tissue samples were obtained. Gene expression data, prognosis tracking information and drug information of these 193 patients (445 drug groups information).

[0060] 3. Calculating the key gene list in the patient's...

Embodiment 3

[0068] Using the method of the present invention to predict the activity of combined drugs for breast cancer patients

[0069] 1. The drug target database used in this embodiment is the same as in Example 1 and Example 2. For the combined drug, the target is the union of the target data of these drugs, and the other steps are as follows:

[0070] 2. Download the two breast cancer datasets MDA1 and MDA / MAQC-II from NCBI GEO. The data set contains the gene expression data of these patients (GPL96 microarray data of 278 breast cancer patients) and the response status information after subsequent T-FAC (paclitaxel, fluorouracil, doxorubicin and cylclophosphamide) treatment. Download the GSE9574 dataset from NCBI GEO, which contains gene chip data (GPL96 chip) of normal breast tissue. Firstly, the gene chip probe data of breast cancer patients and control data are matched to the gene ID, and the gene expression data with the gene ID as the basic unit is obtained through processi...

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Abstract

The invention discloses a pharmaceutical activity prediction and selection method based on genetic expressions and drug targets. The method comprises following steps: 1) obtaining target genes corresponding to drugs to be detected according to information in drug target database; obtaining genetic expression data of disease tissues of patients and corresponding compression data and obtaining important genetic lists of morbidity processes of patients by evaluating importance of genes through a systems biology method; 2) searching for whether the target genes obtained in the step 1) target the important gene lists during mobility of the patients or not through statistical analysis of in order to predict pharmaceutical activity of patients and select drugs suited to patients. The method is easily used with high efficiency and broad application scope. The prediction method can be used for selecting drugs suitable for individual patients such that a personalized treatment schme can be provided for patients.

Description

technical field [0001] The invention relates to the technical field of biomedicine, in particular to a method for predicting drug activity and drug screening for an individual patient based on gene expression and drug target data. Background technique [0002] Precision Medicine refers to the use of high-throughput biological data such as genome, transcriptome, and proteome to accurately classify the different states and processes of a disease through bioinformatics and other technical means, and finally realize the accurate classification of diseases and specific patients. Carry out personalized and precise treatment to improve the effectiveness of disease diagnosis, treatment and prevention (see: Collins F S, Varmus H.A new initiative on precision medicine [J]. N Engl J Med, 2015, 372(9): 793-795.) Concept and medical model. For complex diseases such as cancer, precision medicine is of great significance (see: Friedman A A, Letai A, Fisher D E, et al. Precision medicine f...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/18G06F19/00
CPCG06F19/3456G16B20/00
Inventor 张红雨周雄辉朱丽达全源崔泽嘉杨庆勇
Owner HUAZHONG AGRI UNIV
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