Lung cancer prognosis prediction model and construction method and device

A technique for predicting models and constructing methods, applied in the field of biomedicine, can solve unsatisfactory problems and achieve high clinical application value

Pending Publication Date: 2021-03-30
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

So far, traditional clinical indicators and staging can only roughly distinguish different stages of lung cancer, which cannot meet the increasing requirements of individualized treatment in clinical practice.
Currently, there is no combined model integrating infiltrating immune cells in lung cancer tumors for clinical prediction of lung cancer prognosis

Method used

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  • Lung cancer prognosis prediction model and construction method and device
  • Lung cancer prognosis prediction model and construction method and device
  • Lung cancer prognosis prediction model and construction method and device

Examples

Experimental program
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Effect test

Embodiment 1

[0055] like figure 1 As shown, in the present invention, the construction method of lung cancer prognosis prediction model comprises the following steps:

[0056] S1. Screen and download the original gene expression data and corresponding clinical survival information of 1175 lung adenocarcinoma samples from the Gene Expression Omnibus (GEO) database. The data are all from the same chip sequencing platform (GPL570). After normalizing the raw gene expression data using the MAS5 algorithm, the gene expression matrix was obtained. Samples with incomplete clinical data and overall survival time less than one month were removed, leaving 849 samples;

[0057] S2. Use the CIBERSORT deconvolution algorithm to estimate the composition of immune cells in the lung adenocarcinoma tumor and calculate their relative ratio. The calculation formula is as follows:

[0058] M=S*F

[0059] Among them, M is the gene expression matrix, S is the gene signature specific to the immune cell type, a...

Embodiment 2

[0094] This embodiment is used to verify the prognosis prediction model established in embodiment 1;

[0095] In this embodiment, the method for constructing a lung cancer prognosis prediction model includes the following steps:

[0096] S1. Screen and download the original gene expression data and corresponding clinical survival information of 576 lung adenocarcinoma samples from the Gene Expression Omnibus database. The data are all from the same chip sequencing platform (GPL96). After normalizing the raw gene expression data using the MAS5 algorithm, the gene expression matrix was obtained. Samples with incomplete clinical data and overall survival time less than one month were removed, leaving 557 samples;

[0097] S2. Use the CIBERSORT deconvolution algorithm to estimate the composition of immune cells in the lung adenocarcinoma tumor and calculate their relative ratio. The calculation formula is as follows:

[0098] M=S*F

[0099] Among them, M is the gene expression ...

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Abstract

The invention discloses a lung cancer prognosis prediction model and a construction method and device. The method comprises the steps of collecting original gene expression data and corresponding clinical survival data of a lung cancer sample, and carrying out standardization to obtain a gene expression matrix; obtaining the types of immune cells in the tumor and calculating the relative ratio ofthe various types of immune cells; screening out parameters for constructing a prognosis prediction model from the obtained immune cell types and obtaining corresponding regression coefficients, wherein the parameters are multiple immune cell types; and based on the screened parameters, calculating an immune score according to the relative ratio and the corresponding regression coefficient to obtain a lung cancer prognosis prediction model. Prognostic risk stratification of lung cancer patients is achieved from the molecular and immune cell level, high-risk and low-risk patients are remarkablyseparated, then the clinical result of lung cancer can be predicted, individualized treatment is guided, and high clinical application value is achieved.

Description

technical field [0001] The invention belongs to the technical field of biomedicine, and in particular relates to a lung cancer prognosis prediction model, a construction method and a device. Background technique [0002] The morbidity and mortality of lung cancer rank among the top among malignant tumors in my country. According to reports, there are more than 600,000 new lung cancer patients in my country each year, and more than 500,000 dead patients, and the mortality rate is increasing year by year. Lung cancer includes non-small cell lung cancer and small cell lung cancer. Non-small cell lung cancer mainly includes lung adenocarcinoma and lung squamous cell carcinoma. Among them, lung adenocarcinoma is the most common type of lung cancer, which is prone to distant metastasis and Poor prognosis features. [0003] Clinically, the operability of lung cancer depends on the TNM stage, and the prognosis of patients with resectable lung cancer depends on the histopathologica...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B40/00G16H50/20
CPCG16B40/00G16H50/20
Inventor 侯珺黎雪桃
Owner SOUTH CHINA UNIV OF TECH
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