Drug sensitivity prediction method for cancer precision treatment

A drug-sensitivity and precision medicine technology, applied in the field of molecular biology, can solve the problems of ignoring the mutual regulatory relationship between genes and unsatisfactory accuracy, and achieve the effect of reducing operating costs

Inactive Publication Date: 2018-01-19
TONGJI UNIV
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Problems solved by technology

However, the prediction accuracy of such models is still unsatisfactory. These methods have an obvious defect: they are all based on t

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  • Drug sensitivity prediction method for cancer precision treatment
  • Drug sensitivity prediction method for cancer precision treatment
  • Drug sensitivity prediction method for cancer precision treatment

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Embodiment 1

[0018] (1) Data collection and preprocessing. Collect and download drug response (IC50, GC50, AUC) and cell line genome (global gene expression, cancer gene mutation and copy number variation) data from high-throughput drug response databases CCLE, CGP, CTRP, BRCA, etc. or experimentally cultured tumor cells The system was sequenced, and drug sensitivity data were generated by experimentally adding different concentrations of drugs. The genomic data of the same data set were first standardized to remove batch effects.

[0019] Preliminary analysis of the data, including whether there is a significant difference in the effect of the drug on different types of cell lines, whether there is a stronger or weaker response to a specific tumor type, whether the drug response indicators are consistent, etc.

[0020] (2) Integrate genomic data to build a drug sensitivity prediction model.

[0021] In the first step, in the above-mentioned large-scale database, the gene expression data...

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Abstract

The invention discloses a drug sensitivity prediction method for cancer precision treatment. Anti-cancer drug sensitivity prediction is performed by comprehensively utilizing genomics data of cell lines, so that theoretical medication guidance is provided for individual treatment. A calculation model is built for predicting drug sensitivity to individuals, thereby guiding clinical medication, which is one of core goals of precision treatment. According to the method, interaction terms among genes are added by utilizing a protein interaction network; a mutual relationship among the cell lines is described by utilizing the similarity of gene expression profiles of the cell lines; a local weighted linear model is built without depending on an independence assumption among genomic characteristics; and compared with a conventional linear model, a better prediction effect is achieved, the problem of high-latitude input caused by large-scale data characteristics is solved, and the operation cost of the model is reduced. The method can be widely applied to the drug sensitivity prediction of new cell lines, and provides the theoretical guidance for guiding the clinical medication.

Description

technical field [0001] The invention belongs to the field of molecular biology, and in particular relates to anticancer drug sensitivity prediction and cancer individualized medical research. Background technique [0002] Precision medicine refers to the design of precise medical diagnosis and treatment strategies that match the patient based on the patient's molecular biopathological characteristics, such as the genome, proteome, or metabolome, and other relevant internal environmental information. Compared with traditional diagnosis and treatment methods based on patients' clinical symptoms and individual characteristics, precision medicine can usually achieve better therapeutic effects and reduce side effects. It is one of the core goals of precision medicine to establish computational models to predict the sensitivity of drugs to individuals, and then to guide clinical medication. Taking the treatment of cancer as an example, there are more than one thousand anticancer ...

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Application Information

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IPC IPC(8): G06F19/00G06F19/12
Inventor 张乃千殷俊锋
Owner TONGJI UNIV
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