Preclinical modeling of lower-grade gliomas.
Preclinical modeling of lower-grade gliomas.
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DOI：
10.3389/fonc.2023.1139383
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发表时间：
2023
影响因子：
4.7
通讯作者：
Abdullah KG
中科院分区：
文献类型：
--
作者：
Tang LW;Mallela AN;Deng H;Richardson TE;Hervey-Jumper SL;McBrayer SK;Abdullah KG
事实证明，人脑胶质瘤模型不仅对促进我们对胶质瘤生物学的理解至关重要，而且对促进治疗方式的发展也至关重要。具体地说，建立低级别胶质瘤(LGG)模型一直是具有挑战性的，在过去十年中几乎没有研究，标准治疗方面的进展也很小。然而，为了可靠地预测和验证新治疗方法的有效性，LGG模型需要遵守概括肿瘤遗传异常和微环境的特定标准。这强调了需要重新审视LGG的现有模型，并探索可能弥合临床前洞察和临床转换之间差距的前瞻性模型。本审查首先概述了一套旨在解决当前阻碍模型开发的挑战的标准。然后，我们评估现有的LGG临床前模型相对于这些已建立的标准的优势和劣势。综上所述，综述讨论了整合现有模型以最大限度地探索疾病机制和治疗发展的潜在未来方向。
Models for human gliomas prove critical not only to advancing our understanding of glioma biology but also to facilitate the development of therapeutic modalities. Specifically, creating lower-grade glioma (LGG) models has been challenging, contributing to few investigations and the minimal progress in standard treatment over the past decade. In order to reliably predict and validate the efficacies of novel treatments, however, LGG models need to adhere to specific standards that recapitulate tumor genetic aberrations and micro-environment. This underscores the need to revisit existing models of LGG and explore prospective models that may bridge the gap between preclinical insights and clinical translation. This review first outlines a set of criteria aimed to address the current challenges hindering model development. We then evaluate the strengths and weaknesses of existing preclinical models of LGG with respect to these established standards. To conclude, the review discusses potential future directions for integrating existing models to maximize the exploration of disease mechanisms and therapeutics development.
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DOI：
10.4161/cc.8.20.9701
发表时间：
2009-10-15
期刊：
Cell cycle (Georgetown, Tex.)
影响因子：
--
作者：
Heddleston JM;Li Z;McLendon RE;Hjelmeland AB;Rich JN
通讯作者：
Rich JN
影响因子：
4.6
作者：
Kopinja J;Sevilla RS;Levitan D;Dai D;Vanko A;Spooner E;Ware C;Forget R;Hu K;Kral A;Spacciapoli P;Kennan R;Jayaraman L;Pucci V;Perera S;Zhang W;Fischer C;Lam MH
通讯作者：
Lam MH
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
50.3
作者：
Blouw, B;Song, HQ;Bergers, G
通讯作者：
Bergers, G
影响因子：
3.7
作者：
Klink B;Miletic H;Stieber D;Huszthy PC;Campos Valenzuela JA;Balss J;Wang J;Schubert M;Sakariassen PØ;Sundstrøm T;Torsvik A;Aarhus M;Mahesparan R;von Deimling A;Kaderali L;Niclou SP;Schröck E;Bjerkvig R;Nigro JM
通讯作者：
Nigro JM