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Application of immune-related genes in kit and system for predicting prognosis of diffuse glioma

A glioma and kit technology, applied in the field of biomedicine, can solve the problems of no large-scale research on diffuse glioma, no immune-related genes, and no large-scale verification.

Pending Publication Date: 2021-10-08
广东中科清紫医疗科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, no large-scale studies have been performed on the use of immune-related genes to predict prognosis in diffuse glioma
[0005] The main disadvantage of the existing technology: there is no organic combination of immune-related genes in diffuse glioma, and no large-scale validation

Method used

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  • Application of immune-related genes in kit and system for predicting prognosis of diffuse glioma
  • Application of immune-related genes in kit and system for predicting prognosis of diffuse glioma
  • Application of immune-related genes in kit and system for predicting prognosis of diffuse glioma

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0021] Construction of immune prognostic model of diffuse glioma ( figure 1 ):

[0022] Download the GSE4290 dataset from the GEO database, which contains 153 cancer tissues and 27 paracancerous tissues.

[0023] The limma R package was used to analyze the differential expression of the cancer group and the adjacent cancer group in the GSE4290 dataset. The screening criteria for differentially expressed genes were |log2foldchange|>0.5 and p.adjust<0.05. After differential expression analysis, a total of 3383 differentially expressed genes were obtained. genes, including 1459 up-regulated genes and 1924 down-regulated genes.

[0024] The immune-related genes were obtained from the ImmPort database, with a total of 1811 genes. These genes were intersected with differentially expressed genes to obtain 236 differentially expressed immune-related genes (DE-IRGs).

[0025] Using these 236 DE-IRGs to perform weighted co-expression network analysis in the CGGA dataset to obtain the ...

Embodiment 2

[0029] Use this model to predict the prognosis of diffuse glioma;

[0030] Tested on a training cohort (CGGA) and a validation cohort (TCGA) with a total of 902 case samples. like Figure 1 shown, where the test effect in CGGA (1-, 3-, and 5-year AUC values ​​were 0.795, 0.855, and 0.896, respectively), and the test effect on glioma patients in the TCGA validation set (1-, 3-, and 5-year AUC values, respectively) The 5-year AUC values ​​were 0.815, 0.855 and 0.813)

[0031] As shown in Table 1 and Table 2, the present invention also carried out univariate cox regression analysis and multivariate cox regression analysis, which proves that the immune risk score model (IRGS) calculated by the model of the present invention can indeed independently predict the prognosis risk of glioma patients .

[0032]Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit the protection scope of the ...

Embodiment 3

[0058] Expression levels of genes used to validate immune prognostic models in clinical samples

[0059] Based on the GEO database and TCGA database to construct and preliminarily validate the immune prognosis model of diffuse glioma, we collected 12 diffuse glioma tissue samples from the hospital (728487G, 691253G, 689599G, 695948G, 754905G, 719303G, 779526G, 756384G, 786591G, 700690G, 694592G, 701763G) and 6 normal tissue samples (709872N, 531955N, 786009N, 605854N, 705306N, 474898N). Total RNA was extracted, and the expression levels of 5 IPS genes used in the immune prognosis model were detected by qPCR: CDC42, PPP4C, NRG3, VIM and HDAC1. ACTB was used as an internal reference positive control. The assessed significance of our model was validated at the qPCR level.

[0060] Table 3. qPCR primer table

[0061]

[0062]

[0063] "-F" indicates forward primer and "-R" indicates reverse primer.

[0064] Main instruments and reagents used for qPCR validation

[0065] ...

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Abstract

The invention provides application of immune-related genes in a kit and a system for predicting prognosis of diffuse glioma. According to the application, a group of characteristic genes capable of stably predicting prognosis of diffuse glioma are found by combining the immune-related genes; the prognosis of diffuse glioma can be well predicted by adopting the system; and single-factor and multi-factor Cox proportional risk regression analysis is carried out, and the immune risk score is proved to be really capable of being used as an independent prognosis factor of diffuse glioma.

Description

technical field [0001] The invention belongs to the field of biomedicine, and particularly relates to the application of immune-related genes in a kit and a system for predicting the prognosis of diffuse glioma. Background technique [0002] Gliomas are the most common primary tumors of the brain and central nervous system, accounting for approximately 30% of all brain and central nervous system tumors, and more than 80% of all malignant primary brain tumors. The annual incidence rate is 3.55 cases per 100,000 people. According to the 2007 World Health Organization (WHO) classification of tumors of the central nervous system, diffuse gliomas are classified into grades II and III low-grade gliomas (LGGs) and grades IV glioblastomas ( GBM). GBM is the deadliest tumor of all grades. Despite major advances in therapies including chemotherapy, radiation therapy, and surgical resection, the median overall survival for GBM is only 15 months. At present, the histological grade o...

Claims

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Application Information

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IPC IPC(8): C12Q1/6886C12N15/11
CPCC12Q1/6886C12Q2600/158C12Q2600/118
Inventor 杜军张金阔马丹军
Owner 广东中科清紫医疗科技有限公司
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