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Tumor immune subtype classification method and system

A classification method and tumor technology, applied in the fields of bioinformatics and computational biology, can solve the problems of only considering immune gene expression, the classification effect of the classification method is not ideal, and the organization of the microbial population structure and the infiltration of immune cells are not taken into account. To achieve the effect of improving the classification effect

Active Publication Date: 2021-03-02
UNIV OF SCI & TECH BEIJING
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Problems solved by technology

[0006] The present invention provides a method and system for classifying tumor immune subtypes to solve the problem that the existing research on immune subtypes often only considers the expression of immune genes, and does not take into account the structure of tissue microbial populations and the infiltration of immune cells. The technical problem that the classification effect of some classification methods is not ideal

Method used

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  • Tumor immune subtype classification method and system
  • Tumor immune subtype classification method and system
  • Tumor immune subtype classification method and system

Examples

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no. 1 example

[0049] This embodiment provides a method for classifying tumor immune subtypes. The method for classifying tumor immune subtypes can be implemented by an electronic device, and the electronic device can be a terminal or a server. The execution flow of the tumor immune subtype classification method is as follows: figure 1 shown, including the following steps:

[0050] S101, acquiring a sample data set including RNA-seq sequencing data and gene expression profile data of multiple tumor tissues;

[0051] S102, calculating microbial abundance data, immune cell ratio data, and immune-related gene expression data in the tumor tissue corresponding to each sample in the sample data set;

[0052] S103, using microbial abundance data, immune cell ratio data and immune-related gene expression data as classification features, constructing a training sample data set, and training an integrated classifier of a preset type;

[0053] S104, input the microbial abundance data, immune cell rat...

no. 2 example

[0171] This embodiment provides a tumor immune subtype classification system, which includes the following modules:

[0172] A sample data set acquisition module, configured to acquire a sample data set including RNA-seq sequencing data and gene expression profile data of multiple tumor tissues;

[0173] The classification feature acquisition module is used to calculate the microbial abundance data, immune cell ratio data and immune-related gene expression data in the tumor tissue corresponding to each sample in the sample data set;

[0174] The model training and classification module is used to use microbial abundance data, immune cell ratio data and immune-related gene expression data as classification features to construct a training sample data set and train a preset type of integrated classifier; and pass the training A good ensemble classifier achieves immune subtype classification of tumor tissue.

[0175] The tumor immune subtype classification system of this embodim...

no. 3 example

[0177] This embodiment provides an electronic device, which includes a processor and a memory; at least one instruction is stored in the memory, and the instruction is loaded and executed by the processor, so as to implement the method of the first embodiment.

[0178] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) and one or more memories, wherein at least one instruction is stored in the memory, so The above instruction is loaded by the processor and executes the above method.

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Abstract

The invention discloses a tumor immune subtype classification method and a tumor immune subtype classification system. The method comprises the following steps: acquiring a sample data set comprisingRNA-seq sequencing data and gene expression profile data of a plurality of tumor tissues; calculating microorganism abundance data, immune cell proportion data and gene expression data related to immunity in the tumor tissue corresponding to each sample in the sample data set; constructing a training sample data set by taking microorganism abundance data, immune cell proportion data and gene expression data related to immunity as classification features, expanding minority classes by adopting an SMOTE algorithm, training a random forest model, and improving the random forest model in a weighting form: increasing the weight of the minority classes. And thus, the decision tree classifier focuses on the minority class, and the classification accuracy of the minority class is improved. According to the invention, the accuracy of tumor immune subtype classification prediction can be improved, and a new target is provided for tumor immunotherapy.

Description

technical field [0001] The invention relates to the technical fields of bioinformatics and computational biology, in particular to a method and system for classifying tumor immune subtypes. Background technique [0002] The theory that the normal body's immune system can eliminate tumor cells in the process of transformation through an immune response has been used to treat cancer decades ago. On this basis, immunotherapy is applied to the treatment of cancer, that is, to artificially enhance or suppress the immune function of the body to achieve the purpose of treating the disease. But researchers have found that immunotherapy has had little effect in trials related to colorectal and gastric cancer. For highly heterogeneous diseases such as gastric cancer and colorectal cancer, the clinical efficacy of tumor immunotherapy is not satisfactory. The reason for this result is still unclear, but studies have shown that: Tumor heterogeneity: Although patients with the same mali...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B40/00G16B25/10G06K9/62
CPCG16B40/00G16B25/10G06F18/24323G06F18/214
Inventor 艾冬梅王瑜多李晓鑫
Owner UNIV OF SCI & TECH BEIJING
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