Suppr超能文献

中枢神经系统肿瘤的免疫学

Immunology of central nervous system tumors.

作者信息

de Micco C

机构信息

Laboratoire de Neuropathologie, Faculté de Médecine, Marseilles, France.

出版信息

J Neuroimmunol. 1989 Dec;25(2-3):93-108. doi: 10.1016/0165-5728(89)90127-6.

Abstract

With progress in cellular immunology and the development of hybridoma technology, the idea of manipulating host-tumor immune interactions to improve the prognosis of brain tumors has aroused renewed interest. Although no brain tumor-specific antigens have been found, and in spite of the wide antigenic heterogeneity of brain tumor cells, some monoclonal antibodies possessing restricted specificity have been isolated and their potential clinical applications investigated. One of the most pronounced changes in the cellular immune responses of brain tumor patients is a profound depression of the T4-helper lymphocytes. Clinical and laboratory trials are under way to assess the ability of lymphokines, such as gamma-interferon or interleukin-2, to restore immunologic competence in these patients and potentiate a specific anti-tumor immunologic response. Recent work suggests that the endothelium-astrocyte complex may have a pivotal role in assisting the escape of brain tumors from the host's immunologic responses, since it is responsible for the intracerebral sequestration of antigens and local anti-tumor responses. In this review, the data on the antigenic properties of central nervous system tumors and the host's humoral and cellular immune responses to them are analyzed and potential immunologic therapies are discussed.

摘要

随着细胞免疫学的进展和杂交瘤技术的发展,通过调控宿主与肿瘤之间的免疫相互作用来改善脑肿瘤预后的想法再次引起了人们的关注。尽管尚未发现脑肿瘤特异性抗原,并且脑肿瘤细胞存在广泛的抗原异质性,但一些具有有限特异性的单克隆抗体已被分离出来,并对其潜在的临床应用进行了研究。脑肿瘤患者细胞免疫反应中最显著的变化之一是T4辅助淋巴细胞的严重抑制。目前正在进行临床和实验室试验,以评估诸如γ干扰素或白细胞介素-2等淋巴因子恢复这些患者免疫能力并增强特异性抗肿瘤免疫反应的能力。最近的研究表明,内皮细胞-星形胶质细胞复合体可能在协助脑肿瘤逃避宿主免疫反应方面起关键作用,因为它负责脑内抗原的隔离和局部抗肿瘤反应。在这篇综述中,分析了中枢神经系统肿瘤的抗原特性以及宿主对它们的体液和细胞免疫反应的数据,并讨论了潜在的免疫治疗方法。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验