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胶质肉瘤的生物学特性与预后

Biological characteristics and outcomes of Gliosarcoma.

作者信息

Hashmi Fauzan Alam, Salim Adnan, Shamim Muhammad Shahzad, Bari Muhammad Ehsan

机构信息

Aga Khan University Hospital, Karachi, Pakistan.

出版信息

J Pak Med Assoc. 2018 Aug;68(8):1273-1275.

PMID:30108403
Abstract

Gliosarcoma is a highly aggressive primary brain tumour. It is a relatively rare tumour and comprises of two histological components, glial and sarcomatous. Gliosarcomas carry a poorer prognosis than that of Glioblastoma Multiforme (GBM). The current review highlights important histological and radiological features of gliosarcoma in the light of recent literature, and also touches upon the treatment options and outcomes of various types of gliosarcoma.

摘要

胶质肉瘤是一种高度侵袭性的原发性脑肿瘤。它是一种相对罕见的肿瘤,由神经胶质和肉瘤两种组织学成分组成。胶质肉瘤的预后比多形性胶质母细胞瘤(GBM)更差。本综述根据近期文献重点介绍了胶质肉瘤重要的组织学和放射学特征,还探讨了各类胶质肉瘤的治疗选择及结果。

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Biological characteristics and outcomes of Gliosarcoma.胶质肉瘤的生物学特性与预后
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Shikonin inhibits epithelial-mesenchymal transition in glioblastoma cells by upregulating p53 and promoting miR-361-5p level to suppress ZEB1 expression.紫草素通过上调p53和提高miR-361-5p水平以抑制锌指蛋白E盒结合因子1(ZEB1)的表达,从而抑制胶质母细胞瘤细胞的上皮-间质转化。
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TGF-β and BMP signaling are associated with the transformation of glioblastoma to gliosarcoma and then osteosarcoma.
转化生长因子-β(TGF-β)和骨形态发生蛋白(BMP)信号传导与胶质母细胞瘤向胶质肉瘤进而向骨肉瘤的转变有关。
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Use of MRI, metabolomic, and genomic biomarkers to identify mechanisms of chemoresistance in glioma.利用磁共振成像(MRI)、代谢组学和基因组生物标志物来识别胶质瘤化疗耐药的机制。
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Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma.基于机器学习的磁共振影像组学分析用于胶质肉瘤和胶质母细胞瘤的分类
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