胶质瘤生物信息学研究资源与进展  

Research progress in the bioinformatics of glioma

作　　者：吴从严 李镭 杨金成 赵耀东 Wu Congyan;Li Lei;Yang Jincheng;Zhao Yaodong(Department of Neurosurgery,Shanghai First People's Hospital of Nanjing Medical University,Shanghai 200080,China)

机构地区：[1]南京医科大学附属上海市第一人民医院神经外科,上海200080

出　　处：《中国临床保健杂志》2020年第6期851-854,共4页Chinese Journal of Clinical Healthcare

基　　金：国家自然科学基金(81172400,81101909)。

摘　　要：胶质瘤是一种常见的原发性恶性脑瘤,尽管治疗方法不断更新,但患者预后仍然很差,其中最具侵袭性的胶质瘤生存期仅有几个月。生物信息学起源于20世纪70年代,随着分子生物学和计算机科学技术的进步,生物信息学发展很快,带动基因组、转录组、蛋白组、代谢组等组学概念应运而生,从而推动了胶质瘤等疾病诊疗技术的进步。例如胶质瘤分类得到细化,已将分子亚型融入胶质瘤分类体系。现常用于胶质瘤研究的数据库有:GEO数据库、TCGA数据库、CGGA数据库、REMBRANDT数据库等,利用这些数据库中上传的样本测序信息,能够从基因组、转录组、蛋白组、代谢组、甲基化组等多组学的角度阐明胶质瘤的发生发展机制,为胶质瘤诊疗技术的进步带来新的希望。Glioma is a common primary malignant brain tumor.Despite continuous improvement in treatment,the prognosis is still poor,and the survival time is only a few months for the most aggressive gliomapatient.Bioinformatics,which originated in the 1970s,has been booming with the development of new molecular biology technologies and the progress of computer science.It leads to the emergence of such omics concepts as genome,transcriptome,proteome and metabolome,and promotes the progress of glioma diagnosis and treatment,such as the refinement of glioma classification and the integration of molecular subtypes into the classification of glioma.Currently,it is commonly used in glioma research databases such as GEO,TCGA,CGGA and REMBRANDT.By using the sample sequencing information uploaded in these databases,the occurrence and development mechanism of glioma can be studied from the perspective of multiomics,including genome,transcriptome,proteome,metabolome,methylome,and bring new hope for the improvement of diagnosis and treatment of glioma.

关 键 词：神经胶质瘤 计算生物学 综述 

分 类 号：R73[医药卫生—肿瘤]