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Model for predicting prognosis of lung squamous cell carcinoma with seven genes as biomarkers, and establishing method thereof

A lung squamous cell carcinoma and prognosis technology, applied in the fields of genetic technology and biomedicine, can solve the problems of insensitive and accurate prognosis of lung squamous cell carcinoma, low overall survival rate, and no reference standard for prognosis judgment.

Pending Publication Date: 2019-06-07
辽宁省肿瘤医院
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

While the overexpression of p114RhoGEF may become a marker of poor overall survival reflecting its role in predicting lymph node metastasis, GASC1 and 5-microRNA indicate poor prognosis
However, single genes as biomarkers are not sensitive and accurate enough to predict the prognosis of lung squamous cell carcinoma
[0004] At present, multiple genes as biomarkers have no reference standards for predicting the prognosis of squamous cell carcinoma of the lung, and there are no specific indicators, which are far from meeting the needs of the prognosis of patients with squamous cell carcinoma of the lung

Method used

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  • Model for predicting prognosis of lung squamous cell carcinoma with seven genes as biomarkers, and establishing method thereof
  • Model for predicting prognosis of lung squamous cell carcinoma with seven genes as biomarkers, and establishing method thereof
  • Model for predicting prognosis of lung squamous cell carcinoma with seven genes as biomarkers, and establishing method thereof

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] Example 1 contains seven genes as biomarkers to predict the prognosis of lung squamous cell carcinoma model building method.

[0032] 1. Data collection.

[0033] A total of 551 samples were obtained from The Cancer Genome Atlas (TCGA) database (http: / / cancergenome.nih.gov / ), including 49 normal samples and 502 lung squamous carcinoma samples. Meanwhile, all samples contained corresponding clinical data on age, sex, race, smoking status, cancer stage, survival time and RNA expression profile from the database. Differentially expressed genes were screened by R (http: / / www.r-project.org) meeting the selection criteria as follows: 1) p 1.

[0034] 2. Construction of Cox regression model.

[0035] By collecting differently expressed genes, 363 samples were randomly selected as the training set, and 188 samples were used as the R-based test set; Cox univariate analysis was used to obtain prognosis-related genes. Cox multivariate analysis was performed by stepwise regressi...

Embodiment 2

[0044] Example 2 Application of a model containing seven genes as biomarkers to predict the prognosis of lung squamous cell carcinoma.

[0045] 1. Cox regression model predicts lung squamous cell carcinoma.

[0046] The 7 genes collected from the Cox multivariate regression analysis and the risk score formula can be calculated in each sample list as follows:

[0047] Risk score = -0.1311*CSRNP1+0.1390*MIR27A-0.1951*CLEC18B+0.1708*AC130456.4+0.1702*DEFA6+0.1821*ARL14EPL+0.1135*ZFP42. Only CSRNP1 and CLEC18B were positively associated with survival and acted as protective factors. MIR27A, AC130456.4, DEFA6, ARL14EPL and ZFP42 were inversely associated with survival and played a role in increased risk (Table 1).

[0048]

[0049] 2. Performance of the training set risk score.

[0050] According to the median risk score as the threshold, lung squamous cell carcinoma samples were divided into high-risk group and low-risk group. Kaplan-Meier curves were used to indicate diffe...

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Abstract

The invention relates to a the field of biomedicine, and specifically relates to a model for predicting prognosis of lung squamous cell carcinoma with seven genes as biomarkers, and an establishing method thereof. The model for predicting prognosis of lung squamous cell carcinoma includes seven genes related to prognosis of lung squamous cell carcinoma: CSRNP1, CLEC18B, MIR27A, AC130456.4, DEFA6,ARL14EPL and ZFP42, wherein expressions of CSRNP1 and CLEC18B are positively correlated with a survival rate while expressions of MIR27A, AC130456.4, DEFA6, ARL14EPL and ZFP42 are negatively correlated with the survival rate. The model for predicting prognosis of lung squamous cell carcinoma provides a plurality of genes as biomarkers, and improves the prognosis sensitivity and accuracy for predicting lung squamous cell carcinoma, thereby reducing mortality and local recurrence rate in patients with lung squamous cell carcinoma, and improving the prognosis of patients through the risk prediction model.

Description

technical field [0001] The invention belongs to the field of gene technology and biomedicine, and specifically relates to a model containing seven genes as biomarkers to predict the prognosis of lung squamous cell carcinoma and a method for establishing it. Background technique [0002] Squamous cell carcinoma of the lung, or squamous cell carcinoma of the lung, is one of the most important pathological types of lung cancer. It is derived from the malignant transformation of bronchial epithelial cells, and the number of cases accounts for about 30% of non-small cell lung cancer. Conventional treatment methods for lung squamous cell carcinoma mainly include surgical treatment, chemotherapy and molecular targeted therapy. The 5-year survival rate of patients is less than 15%, and more than 400,000 people die from it every year in the world. At present, there is no reference standard for the prognosis of patients with squamous cell carcinoma of the lung, and there is no specifi...

Claims

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Application Information

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IPC IPC(8): G16B40/00G16B25/10G16B50/00
Inventor 于韬李强赵丹王哲王浩天朱家伟
Owner 辽宁省肿瘤医院
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