| Objective:Glioma is one of the most common types of tumor in the human central nervous system, which accounts for 77-80 per cent of primary malignant tumor of the brain. It greatly threatens human health. Current treatment of glioma is mainly comprehensive treatment of medical operation and chemotherapy, but it cannot effect a radical cure of glioma patients.Ever since Bailey and Cushing first proposed the pathological classification of glioma in 1926, almost all classifications belong to histological classification. However, pathological classification based on the obeservation under the microscope cannot be relied on as a good criterion for disease condition and prognosis result. The new pathological classification of glioma issued by the International Association of Neuropathology and Cancer Foundation in 2000 includes large amount of clinical and genetic statistics. This kind of meta-classification indicates new knowlege of glioma in recent years and offers important evidence for clinical diagnosis and scientific research.The genesis and progress of tumor and the experimental reversion and recurrence of neoplasia are accompanied by the change of complex gene expression pattern. Mircoarray provides a powerful tool to study this phenomenon. Microarray techonology is a new technique originated from the joint development of life sciences and microelectronics in recent years. It can analyse data of nucleotide, proterin or cell sample with hight speed, high accuracy and high throughput, which is widely applied to discover and study tumor markers.Mircoarray profile technique can test thousands of genes in a single experiment and comprehensively analyse different grades of tumor in a certain growth peroid, thus revealing many new and important cancer-related genes. However, due to the heterogenous platforms, arrays and samples, data of microarray are not consistent or even leading to contradictory conclusions. Therefore, shortcomings of microarray technique exist such as poor reproducibility and reliability of microarray data.The purpose of this study is to use cDNA microarray and Affymetrix Oligo microarray to screen and analyze glioma specific markers based on about 150 clinically collected glioma samples on different platforms, and verify the 12 important genes selected from both platforms by RT-PCR. We hope to find markers for dignosis and treatment which have further research value. This study also use meta-analysis to analyze the data generated from both platfroms integratively, which gives a good way to solve the problem of low reproducibility and reliability of data from different platforms, microarrays and samples. Finally, this study summarizes the methods of microarray application in glioma study.Methods:1. cDNA microarray glioma data analysis Generate 38 glioms gene profiles using cDNA microarray technique and illuminate the interaction of these genes on a integrated and network perspective in order to explore the genesis and malignant progress of glioma.2. Affymetrix Oligo microarray glioma data analysis3. Verification of the 12 important genes selected from both platforms by RT-PCR.4. Meta-analysis of cDNA microarray Affymetrix Oligo microarray of glioma data and summary of the methods to apply microarray to glioma study.Results:1. Differentially expressed genes by selection(1) Select differentially expressed genes in different types of glioma and different grades of glioma using different selecting method(2) Select differentially expressed genes in AII 7cases,AIII 5 cases,GBM 20 cases2. Establish a discriminant equation based on the glioma cDNA microarray expression data combined with statistical methods to predict and judge glioma samples.3. The study finds differentially expressed genes, important chromosomes and pathways which plays an important role in the development of glioma.4. Astrocytomas tumor marker studies5. Study of molecular markers of glioma in three different type of glioma with the same grade, i.e. astrocytoma grade II, oligodendroglioma grade II, ependymoma grade II.6. Six genes-VEGF, SOD2 ,COL1A2, MAP3K7, CDC2, SPP1 have been verified by RT-PCR, and they are positively correlated with the pathological grade of astrocytomas.Conclusion:1. The microarray technology in the post-genome era still play an important role in glioma studies;2. Data from different platforms, different arrays and different samples are not consistent. Meta-analysis of microarray data can be a better way to solve the problem of poor reproducibility and reliability;3. Bioinformatics is good for the excavation and analysis of microarray data;4. Six genes, namely VEGF, unrelated, COL1A2, MAP3K7, D2, SPP1 closely linked with astrocytoma and can be used as a diagnostic and therapeutic target for in-depth study.
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