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Molecular classification and application of glioma based on cdc20 gene co-expression network

A CDC20-M, gene expression technology, applied in the biological field, can solve the problems of chromosomal instability, genome instability, etc.

Active Publication Date: 2021-02-05
BEIJING NORMAL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, CIN70signature also has its limitations. First, CIN70signature cannot specifically represent the situation of glioma. The establishment of CIN70signature integrates the database of 6 different tumors, and can get those genes that are common in various tumors, but each tumor is unique. With specificity, CIN70signature cannot fully represent genomic instability in glioma; secondly, CIN70signature cannot fully represent genomic instability, and the establishment of CIN70signature is based on an aneuploid score algorithm proposed by the author, so that genes The scores obtained by this algorithm are sorted and the top 70 genes are selected to form the CIN70signature. Aneuploidy can only represent an abnormal state in the number of chromosomes. It is currently believed that this phenomenon is caused by abnormal chromosome division, and the genome is unstable. Sexuality includes not only chromosomal instability, but also mutations in gene loci, so CIN70signature cannot fully represent genomic instability; finally, CIN70signature cannot predict the prognosis of a patient after CIN70signature typing, and CIN70signature is important for patients The prediction of prognosis needs to rely on the expression database containing a large number of patient samples. According to the expression level of CIN70signature in the database, the median value is taken to divide the patients into two groups of high and low, and then the prognosis between the two groups is compared. It is impossible to make an effective prognosis for a single independent case. detection
In addition, although the above studies have revealed the importance of genome instability in the etiology of glioma, there are still very few studies on the mechanism and markers of genome instability.

Method used

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  • Molecular classification and application of glioma based on cdc20 gene co-expression network
  • Molecular classification and application of glioma based on cdc20 gene co-expression network
  • Molecular classification and application of glioma based on cdc20 gene co-expression network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] Example 1, the establishment of CDC20-M and CREBRF-M gene co-expression modules

[0054] The genomic instability of tumors is manifested in the fact that tumor samples carry a large number of dynamically changing chromosomal abnormalities and gene mutations. Different tumor samples may carry different chromosomal abnormalities and gene mutations, and tumors may accumulate important genomic abnormalities at a certain developmental point, and then their genomes remain relatively stable. Therefore, how to identify tumor samples with unstable genomes has become a key issue in this field. One possible strategy is to screen gene expression profiles that correlate with the number of chromosomal variants in representative samples.

[0055]In order to screen specific gene groups that are closely correlated with genome instability in glioma, the present invention uses Pearson correlation analysis, and takes Pearson correlation coefficient (Pearson correlation coefficient, PCC)>7...

Embodiment 2

[0058] Example 2, Comparison of CDC20-M and existing glioma prognostic markers

[0059] In order to verify the role of CDC20-M in the occurrence and development of glioma, the present invention first analyzed the ability of CDC20-M in the prognosis diagnosis and prediction of glioma patients, and explored whether CDC20-M has all types and grades of glioma The ability to distinguish tumors according to their prognostic differences. For the prognosis diagnosis of glioma, there are currently some commonly used markers in clinic, such as age, IDH1 mutation, co-deletion of chromosome arm 1p and 19q, and protein expression level of Ki-67, so the present invention combines CDC20-M with this Several mature prognostic markers were compared by multivariate cox regression analysis. The database used covered a total of 1305 patient samples from Europe, the United States and China (Rembrandt, GSE16011, TCGA and CGGA databases). The results are shown in Table 1 shown. It can be found that...

Embodiment 3

[0073] Example 3, independent sample prediction based on CDC20-M and CREBRF-M

[0074] After the stable CDC20-M grouping is obtained, the present invention uses the independent sample predictive analysis method to group glioma patient samples from other sources based on the TCGA training set. In the TCGA training set, for each group classified by CDC20-M, the average expression of each member in CDC20-M and CREBRF-M is calculated separately, so there is a set of 139+120 members for each group For the average expression level, four groups have four sets of average expression levels, and each set of average expression levels is called a group-specific expression pattern (Centroid). There are four Centroids in four groups. The present invention subsequently obtained 319 cases of glioma samples from CGGA (140 cases of glioblastoma, 67 cases of astrocytoma, 40 cases of oligodendroglioma, 72 cases of oligoastrocytoma) and New TCGA sample of 301 low-grade gliomas (100 astrocytomas,...

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Abstract

The invention discloses glioma molecular typing based on CDC20 gene co-expression network and application and provides application of various gene expression matters in CDC20-M gene group and CREBRF-Mgene group for detecting glioma patients in the preparation of products for estimating prognosis risk of the glioma patients; the CDC20-M gene group is composed of 139 genes; the CREBRF-M gene groupis composed of 120 genes. It is verified herein that CDC20-M is a sensitive marker for poor prognosis for gliomas.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular to a molecular classification and application of glioma based on CDC20 gene co-expression network. Background technique [0002] Glioblastoma (GBM) is the most common primary malignant tumor of the central nervous system in adults, accounting for more than 50%. Although there have been many studies to explore the causes of glioblastoma and feasible treatment options, the survival period of patients with glioblastoma is still very short, with a median survival period of less than two years. Glioblastoma is in a continuous evolutionary process with complex cytological and genetic heterogeneity. The genome of glioblastoma contains many single nucleotide variations and is also characterized by chromosomal instability (CIN). Studies have found that glioblastoma cells have a high frequency of abnormal chromosome number events (non- euploid) and chromosomal structural variation events. Thes...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): C12Q1/6886
Inventor 樊小龙张韵秋
Owner BEIJING NORMAL UNIVERSITY
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