Interactions between cancer cells and non-cancer cells composing the tumour microenvironment play a primary role in determining cancer progression and shaping the response to therapy. The qualitative and quantitative characterisation of the different cell populations in the tumour microenvironment is therefore crucial to understand its role in cancer. In recent years, many experimental and computational approaches have been developed to identify the cell populations composing heterogeneous tissue samples, such as cancer. In this review, we describe the state-of-the-art approaches for the quantification of non-cancer cells from bulk and single-cell cancer transcriptomic data, with a focus on immune cells. We illustrate the main features of these approaches and highlight their applications for the analysis of the tumour microenvironment in solid cancers. We also discuss techniques that are complementary and alternative to RNA sequencing, particularly focusing on approaches that can provide spatial information on the distribution of the cells within the tumour in addition to their qualitative and quantitative measurements. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

中文翻译：

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从癌症转录组数据中鉴定非癌细胞。

构成肿瘤微环境的癌细胞和非癌细胞之间的相互作用在决定癌症进展和塑造治疗反应方面发挥着主要作用。因此，肿瘤微环境中不同细胞群的定性和定量特征对于理解其在癌症中的作用至关重要。近年来，已经开发了许多实验和计算方法来识别构成异质组织样本（例如癌症）的细胞群。在这篇综述中，我们描述了从大量和单细胞癌症转录组数据中量化非癌细胞的最先进方法，重点是免疫细胞。我们阐述了这些方法的主要特征，并重点介绍了它们在分析实体癌肿瘤微环境中的应用。我们还讨论了 RNA 测序的补充和替代技术，特别关注除了定性和定量测量之外还可以提供肿瘤内细胞分布空间信息的方法。本文是由 Federico Manuel Giorgi 博士和 Shaun Mahony 博士编辑的特刊的一部分，题为：转录谱和调控基因网络。