Lung cancer prognosis comprehensive prediction model, construction method and device

A technology for comprehensive prediction and construction methods, applied in the field of biomedicine, which can solve problems such as inability to meet

Active Publication Date: 2021-04-09
SOUTH CHINA UNIV OF TECH
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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.
At present, in lung

Method used

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

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Embodiment

[0067] Such as figure 1 As shown, in the present invention, a method for constructing a comprehensive prediction model for the prognosis of lung cancer comprises the following steps:

[0068] S1. Screen and download the original gene expression data and corresponding clinical survival information of 1175 lung cancer samples from the Gene Expression Omnibus (GEO) database. The data are all from the same chip sequencing platform (GPL570). Samples with incomplete clinical data and overall survival time less than one month were removed, leaving 849 samples. After the gene expression data of the remaining samples were preprocessed and normalized, a gene expression matrix was obtained.

[0069] 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:

[0070] M=S*F

[0071] Among them, M is the gene expression matrix, S is the gene signature...

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Abstract

The invention discloses a lung cancer prognosis comprehensive prediction model and a construction method and device. The method comprises the following steps: collecting original gene expression data and corresponding clinical survival data of a lung cancer sample and conducting data preprocessing and standardization, thereby acquiring a gene expression matrix; obtaining the types of immune cells in the tumor and calculating the relative ratio of the 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; based on the screened parameters, calculating an immune score according to the relative ratio and the corresponding regression coefficient; identifying a gene co-expression module, searching for a gene module cooperatively expressed in the lung cancer sample, and determining a gene module related to prognosis; and constructing a prognosis comprehensive prediction model. According to the invention, immune scores, clinical information and gene co-expression module characteristics are integrated to construct a comprehensive prediction model to predict prognosis of lung cancer patients.

Description

technical field [0001] The invention belongs to the field of biomedicine, and in particular relates to a lung cancer prognosis comprehensive 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 histopatholo...

Claims

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Application Information

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IPC IPC(8): G16H50/30G16H50/50G16H50/70G16B25/10
CPCG16H50/30G16H50/50G16H50/70G16B25/10
Inventor 侯珺黎雪桃
Owner SOUTH CHINA UNIV OF TECH
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