Genetically engineered mouse models of head and neck cancers.
Genetically engineered mouse models of head and neck cancers.
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DOI：
10.1038/s41388-023-02783-7
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发表时间：
2023-08
期刊：
影响因子：
8
通讯作者：
Amelio, Antonio L.
中科院分区：
文献类型：
--
作者：
Tasoulas, Jason;Srivastava, Sonal;Xu, Xiaonan;Tarasova, Valentina;Maniakas, Anastasios;Karreth, Florian A.;Amelio, Antonio L.
头颈部是癌症常累及的解剖部位之一，仅在2020年全球就有约150万新确诊病例。在理解潜在疾病机制、根据每个肿瘤的个体分子特征进行个性化治疗，甚至在治疗上利用这些肿瘤的固有弱点方面都取得了显著进展。在这方面，基因工程小鼠模型（GEMMs）发挥了重要作用。虽然GEMMs的开发进展比其他主要癌症类型要慢，但现在已有几种GEMMs可重现头颈部癌症的大多数异质性特征，比如肿瘤微环境。在GEMM的开发和应用中采用了不同的方法，不过每种方法通常只能重现某些疾病方面。因此，为了解决特定的研究问题，合适的模型选择至关重要。在这篇综述中，我们概述了目前所有可用的头颈部癌症GEMMs，包括头颈部鳞状细胞癌、鼻咽癌以及唾液腺和甲状腺癌的模型。
The head and neck region is one of the anatomic sites commonly afflicted by cancer, with ~1.5 million new diagnoses reported worldwide in 2020 alone. Remarkable progress has been made in understanding the underlying disease mechanisms, personalizing care based on each tumor’s individual molecular characteristics, and even therapeutically exploiting the inherent vulnerabilities of these neoplasms. In this regard, genetically engineered mouse models (GEMMs) have played an instrumental role. While progress in the development of GEMMs has been slower than in other major cancer types, several GEMMs are now available that recapitulate most of the heterogeneous characteristics of head and neck cancers such as the tumor microenvironment. Different approaches have been employed in GEMM development and implementation, though each can generally recapitulate only certain disease aspects. As a result, appropriate model selection is essential for addressing specific research questions. In this review, we present an overview of all currently available head and neck cancer GEMMs, encompassing models for head and neck squamous cell carcinoma, nasopharyngeal carcinoma, and salivary and thyroid gland carcinomas.
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DOI：
10.1158/1541-7786.mcr-14-0158-t
发表时间：
2014-07
期刊：
Molecular cancer research : MCR
影响因子：
--
作者：
Charles RP;Silva J;Iezza G;Phillips WA;McMahon M
通讯作者：
McMahon M
影响因子：
64.5
作者：
Cancer Genome Atlas Research Network
通讯作者：
Cancer Genome Atlas Research Network
影响因子：
6.6
作者：
Contrera, Kevin J.;Gule-Monroe, Maria K.;Zafereo, Mark E.
通讯作者：
Zafereo, Mark E.
影响因子：
2.9
作者：
Placzkowski KA;Reddi HV;Grebe SK;Eberhardt NL;McIver B
通讯作者：
McIver B
影响因子：
4
作者：
Zboray K;Mohrherr J;Stiedl P;Pranz K;Wandruszka L;Grabner B;Eferl R;Moriggl R;Stoiber D;Sakamoto K;Wagner KU;Popper H;Casanova E;Moll HP
通讯作者：
Moll HP