Khoo Bee Luan, Chaudhuri Parthiv Kant, Ramalingam Naveen, Tan Daniel Shao Weng, Lim Chwee Teck, Warkiani Majid Ebrahimi
Mechanobiology Institute, National University of Singapore.
BioSystems and Micromechanics (BioSyM) IRG, Singapore-MIT Alliance for Research and Technology (SMART) Centre, Singapore.
Int J Cancer. 2016 Jul 15;139(2):243-55. doi: 10.1002/ijc.30006. Epub 2016 Feb 16.
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.
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。