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用于探究肿瘤异质性的单细胞分析方法。

Single-cell profiling approaches to probing tumor heterogeneity.

作者信息

Khoo Bee Luan, Chaudhuri Parthiv Kant, Ramalingam Naveen, Tan Daniel Shao Weng, Lim Chwee Teck, Warkiani Majid Ebrahimi

机构信息

Mechanobiology Institute, National University of Singapore.

BioSystems and Micromechanics (BioSyM) IRG, Singapore-MIT Alliance for Research and Technology (SMART) Centre, Singapore.

出版信息

Int J Cancer. 2016 Jul 15;139(2):243-55. doi: 10.1002/ijc.30006. Epub 2016 Feb 16.

Abstract

Tumor heterogeneity is a major hindrance in cancer classification, diagnosis and treatment. Recent technological advances have begun to reveal the true extent of its heterogeneity. Single-cell analysis (SCA) is emerging as an important approach to detect variations in morphology, genetic or proteomic expression. In this review, we revisit the issue of inter- and intra-tumor heterogeneity, and list various modes of SCA techniques (cell-based, nucleic acid-based, protein-based, metabolite-based and lipid-based) presently used for cancer characterization. We further discuss the advantages of SCA over pooled cell analysis, as well as the limitations of conventional techniques. Emerging trends, such as high-throughput sequencing, are also mentioned as improved means for cancer profiling. Collectively, these applications have the potential for breakthroughs in cancer treatment.

摘要

肿瘤异质性是癌症分类、诊断和治疗的主要障碍。最近的技术进步已开始揭示其异质性的真实程度。单细胞分析(SCA)正在成为检测形态、基因或蛋白质组表达变化的重要方法。在本综述中,我们重新审视肿瘤间和肿瘤内异质性问题,并列出目前用于癌症特征分析的各种SCA技术模式(基于细胞、基于核酸、基于蛋白质、基于代谢物和基于脂质)。我们进一步讨论了SCA相对于混合细胞分析的优势以及传统技术的局限性。还提到了诸如高通量测序等新兴趋势,作为癌症分析的改进手段。总体而言,这些应用有可能在癌症治疗方面取得突破。

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