Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.
St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
Front Immunol. 2018 Nov 12;9:2582. doi: 10.3389/fimmu.2018.02582. eCollection 2018.
Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches.
癌症是一种异质性和复杂性疾病。肿瘤由癌细胞和无数种非癌细胞类型组成,这些细胞与细胞外基质共同构成肿瘤微环境。这些与癌症相关的细胞和成分共同促进了癌症的进展,并深深地影响着患者的预后。免疫系统是肿瘤微环境的重要组成部分,诱导癌症免疫耐受是肿瘤形成和生长所必需的步骤。免疫机制与癌症的进展、侵袭和转移密切相关,也与肿瘤休眠和药物治疗敏感性的调节密切相关。转录组分析已被广泛用于了解肿瘤的异质性,将肿瘤分为分子亚型,并建立预测治疗反应和患者预后的特征。然而,在对肿瘤细胞群体的转录组分析中,肿瘤细胞多样性的分类,特别是稀有群体的识别,一直受到限制。大规模平行的单细胞 RNAseq 分析已成为一种强大的方法,可以通过对单细胞转录状态进行无监督采样和建模,揭示肿瘤的异质性并研究癌症中的稀有细胞群体。在这种情况下,单细胞方法将有利于研究免疫系统在癌症中的作用,因为它将能够对肿瘤免疫耐受涉及的细胞类型和途径进行特征描述和/或发现,否则在批量转录组信息中会被遗漏。因此,单细胞分辨率下的基因表达模式分析有可能提供关键信息,以开发精确和个性化的癌症治疗方法,包括免疫疗法。本综述重点介绍了最新的能够在数千个肿瘤细胞中进行无偏研究的单细胞 RNAseq 方法,以及针对肿瘤内稀有群体的靶向单细胞 RNAseq 方法。特别是,我们将讨论研究癌症中免疫系统的方法。我们还将讨论在单细胞水平上研究癌症的当前挑战,以及对当前方法的潜在解决方案。
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