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胶质瘤干细胞和人胶质母细胞瘤的基本基因表达特征

Basic Gene Expression Characteristics of Glioma Stem Cells and Human Glioblastoma.

作者信息

Sakamoto Daisuke, Takagi Toshinori, Fujita Mitsugu, Omura Seiichi, Yoshida Yasunori, Iida Tomoko, Yoshimura Shinichi

机构信息

Department of Neurosurgery, Hyogo College of Medicine, Hyogo, Japan.

Department of Microbiology, Faculty of Medicine, Kindai University, Osaka, Japan

出版信息

Anticancer Res. 2019 Feb;39(2):597-607. doi: 10.21873/anticanres.13153.

DOI:10.21873/anticanres.13153
PMID:30711935
Abstract

BACKGROUND

Glioma stem cells (GSCs) play important roles in the tumorigenesis of glioblastoma multiforme (GBM). Using a novel cellular bioinformatics pipeline, we aimed to characterize the differences in gene-expression profiles among GSCs, U251 (glioma cell line), and a human GBM tissue sample.

MATERIALS AND METHODS

Total RNA was extracted from GSCs, U251 and GBM and microarray analysis was performed; the data were then applied to the bioinformatics pipeline consisting of a principal component analysis (PCA) with factor loadings, an intracellular pathway analysis, and an immunopathway analysis.

RESULTS

The PCA clearly distinguished the three groups. The factor loadings of the PCA suggested that v-myc avian myelocytomatosis viral oncogene neuroblastoma derived homolog (MYCN), dipeptidyl-peptidase 4 (DPP4), and macrophage migration-inhibitory factor (MIF) contribute to the stemness of GSCs. The intracellular pathway and immunopathway analyses provided relevant information about the functions of representative genes in GSCs.

CONCLUSION

The newly-developed cellular bioinformatics pipeline was a useful method to clarify the similarities and differences among samples.

摘要

背景

胶质瘤干细胞(GSCs)在多形性胶质母细胞瘤(GBM)的肿瘤发生中起重要作用。我们旨在使用一种新型细胞生物信息学流程,来表征GSCs、U251(胶质瘤细胞系)和人类GBM组织样本之间基因表达谱的差异。

材料与方法

从GSCs、U251和GBM中提取总RNA并进行微阵列分析;然后将数据应用于由具有因子载荷的主成分分析(PCA)、细胞内途径分析和免疫途径分析组成的生物信息学流程。

结果

PCA清晰地区分了这三组。PCA的因子载荷表明,v-myc禽骨髓细胞瘤病毒癌基因神经母细胞瘤衍生同源物(MYCN)、二肽基肽酶4(DPP4)和巨噬细胞迁移抑制因子(MIF)有助于GSCs的干性。细胞内途径和免疫途径分析提供了有关GSCs中代表性基因功能的相关信息。

结论

新开发的细胞生物信息学流程是一种阐明样本之间异同的有用方法。

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