Application of CDC20 co-expression gene network as glioma treatment target

Abstract

The invention discloses an application of CDC20 co-expression gene network as a glioma treatment target. The invention provides an application of an inhibitor in any of the following: (A1) preparing aproduct for treating glioma; (A2) treating glioma, wherein the inhibitor is a substance capable of reducing the expression activity and / or expression level of the following genes or encoded proteinsthereof: AURKA gene, CDC20 gene and / or KIF2C gene. The application proves that CDC20-M is a sensitive marker of genomic instability and poor prognosis in glioma, and finds potential glioma treatment targets in experimental analysis of main members of CDC20-M, and thus a new idea is provided for clinical diagnosis and treatment.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular to the application of a CDC20 co-expression gene network as a therapeutic target for glioma. 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. These geno...

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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, take the median value to divide the patients into two groups of high and low, and then compare the prognosis between the two groups. If there is only one patient case, it is impossible effective prognostic prediction

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.

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