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从肿瘤免疫学到癌症免疫疗法:任重道远。

From tumor immunology to cancer immunotherapy: miles to go.

作者信息

Tiwari Manjul

机构信息

Department of Oral Pathology, School of Dental Sciences, Sharda University, Greater Noida Uttar Pradesh, India.

出版信息

J Cancer Res Ther. 2010 Oct-Dec;6(4):427-31. doi: 10.4103/0973-1482.77071.

Abstract

Advances in tumor immunology are supporting the clinical implementation of several immunological approaches to cancer in the clinical setting. However, the alternate success of current immunotherapeutic regimens underscores the fact that the molecular mechanisms underlying immune-mediated tumor rejection are still poorly understood. Given the complexity of the immune system network and the multidimensionality of tumor/host interactions, the comprehension of tumor immunology might greatly benefit from high-throughput microarray analysis, which can portrait the molecular kinetics of immune response on a genome-wide scale, thus accelerating the discovery pace and ultimately catalyzing the development of new hypotheses in cell biology. Although the general principles of microarray-based gene profiling with the application of DNA microarray have rapidly spread in the scientific community, the need for mastering this technique to produce meaningful data and correctly interpret the enormous output of information generated by this technology is critical and represents a tremendous challenge for investigators. To describe the sequence of events conductive to an effective immune recognition and killing of malignant cells, clinicians might use gene profiling as a powerful tool to assess the activation status of the immune system before and during immunotherapy.

摘要

肿瘤免疫学的进展正在推动多种癌症免疫治疗方法在临床环境中的实际应用。然而,当前免疫治疗方案的不同程度的成功凸显了一个事实,即免疫介导的肿瘤排斥反应背后的分子机制仍未得到充分理解。鉴于免疫系统网络的复杂性以及肿瘤/宿主相互作用的多维度性,肿瘤免疫学的理解可能会极大地受益于高通量微阵列分析,这种分析可以在全基因组范围内描绘免疫反应的分子动力学,从而加快发现速度,并最终促进细胞生物学新假说的发展。尽管基于DNA微阵列的微阵列基因谱分析的一般原理已在科学界迅速传播,但掌握这项技术以产生有意义的数据并正确解释该技术产生的大量信息输出的需求至关重要,并且对研究人员来说是一个巨大的挑战。为了描述导致有效免疫识别和杀伤恶性细胞的一系列事件,临床医生可以将基因谱分析用作一种强大的工具,以评估免疫治疗之前和期间免疫系统的激活状态。

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