Genetic material specificity based tumor cell drug sensitivity evaluation method

A drug sensitivity and tumor cell technology, which is applied in the field of tumor cell drug sensitivity assessment based on genetic material specificity, can solve problems such as different drug responses or curative effects, toxic side effects, etc.

Active Publication Date: 2015-10-28
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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Problems solved by technology

However, clinical applications have shown that different individual tumor patients, even patients at the same st

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  • Genetic material specificity based tumor cell drug sensitivity evaluation method
  • Genetic material specificity based tumor cell drug sensitivity evaluation method
  • Genetic material specificity based tumor cell drug sensitivity evaluation method

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0038] like figure 1 As shown, a method for assessing drug sensitivity of tumor cells based on genetic material specificity comprises the following steps:

[0039] S1. The tumor cell sample set is divided into a training sample subset and a test sample subset according to a certain ratio (such as 3:2), wherein the training sample subset is used to learn the relationship model between the gene mutation spectrum and the drug IC50 value index, A subset of test samples was used to select the best extreme learning machine prediction model for tumor cell drug IC50 value as a tumor cell drug sensitivity assessment model.

[0040] The training sample subset data can be expressed as:

[0041] x tr ={x i , t i |x i ∈R p , t i ∈R,i=1,...L}

[0042] where x i Represents the gene mutation spectrum of the i-th training sample, p rep...

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Abstract

The invention provides a genetic material specificity based tumor cell drug sensitivity evaluation method. The method comprises steps of: dividing a tumor cell sample set into a training sample subset and a test sample subset; performing training by using the training sample subset and obtaining an extreme learning machine prediction model set of tumor cell drug IC50 value under different parameter conditions; testing the prediction models one by one by using the training sample subset, and selecting the prediction model that has best performance as a tumor cell drug sensitivity evaluation model; and calculating a drug sensitivity evaluation value of the tumor cell to be tested. According to the method provided by the invention, tumor cell drug sensitivity evaluation on the biological genetic level is implemented; meanwhile, artificial subjective influence can be avoided by using drug IC50 value, thereby making drug sensitivity determination more objective and reliable; iteration is not needed in learning by using the extreme learning machine; the number of parameters to be adjusted is small, and global optimization can be ensured, thereby making tumor cell drug sensitivity detection more convenient, highly efficient and practical.

Description

technical field [0001] The invention relates to the technical field of detection and evaluation of drug sensitivity of tumor cells, in particular to a method for evaluating drug sensitivity of tumor cells based on genetic material specificity. Background technique [0002] Tumor has become the "number one killer" of human beings, seriously threatening human health. According to the report of the World Health Organization, the incidence and mortality of global tumors have increased by about 22% in the past 10 years. It is estimated that by 2020, new cases will Reaching 20 million, about 12 million people will die of cancer. In my country, due to the deterioration of environmental pollution in the past 10 years, many cancer villages, cancer counties and other high-incidence areas of cancer have emerged. How to effectively treat cancer is a worldwide problem, and it is also an urgent task for my country's medical and health services. [0003] Chemotherapy is one of the main m...

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Application Information

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IPC IPC(8): G06F19/00
Inventor 王红强靖高见
Owner HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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