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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。

Use of MRI, metabolomic, and genomic biomarkers to identify mechanisms of chemoresistance in glioma.

作者信息

Levenson Cathy W, Morgan Thomas J, Twigg Pamela D, Logan Timothy M, Schepkin Victor D

机构信息

Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL 32306, USA.

Program in Neuroscience, Florida State University, Tallahassee, FL 32306, USA.

出版信息

Cancer Drug Resist. 2019 Sep 19;2(3):862-876. doi: 10.20517/cdr.2019.18. eCollection 2019.

Abstract

Gliomas are the most common form of central nervous system tumor. The most prevalent form, glioblastoma multiforme, is also the most deadly with mean survival times that are less than 15 months. Therapies are severely limited by the ability of these tumors to develop resistance to both radiation and chemotherapy. Thus, new tools are needed to identify and monitor chemoresistance before and after the initiation of therapy and to maximize the initial treatment plan by identifying patterns of chemoresistance prior to the start of therapy. Here we show how magnetic resonance imaging, particularly sodium imaging, metabolomics, and genomics have all emerged as potential approaches toward the identification of biomarkers of chemoresistance. This work also illustrates how use of these tools together represents a particularly promising approach to understanding mechanisms of chemoresistance and the development individualized treatment strategies for patients.

摘要

神经胶质瘤是中枢神经系统肿瘤最常见的形式。最常见的类型,多形性胶质母细胞瘤,也是最致命的,平均存活时间不到15个月。这些肿瘤对放疗和化疗产生耐药性的能力严重限制了治疗方法。因此,需要新的工具来在治疗开始之前和之后识别和监测化疗耐药性,并通过在治疗开始前识别化疗耐药模式来优化初始治疗方案。在这里,我们展示了磁共振成像,特别是钠成像、代谢组学和基因组学如何都已成为识别化疗耐药生物标志物的潜在方法。这项工作还说明了如何将这些工具结合使用代表了一种特别有前景的方法,用于理解化疗耐药机制并为患者制定个性化治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60e0/8992521/db4bbc832f43/cdr-2-862.fig.1.jpg

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