Cancer Genetics & Stem Cell Group, BioDiscovery Institute, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Department of Laboratory Medicine, Division of Translational Cancer Research, Lund University, Lund, Sweden.
Clin Transl Med. 2021 Feb;11(2):e308. doi: 10.1002/ctm2.308.
Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell-types. Cell-cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell-types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell-types requires cell-cell communication. This article aims to review the current in vitro and in vivo mono-cellular and multi-cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single-cell multi-omics approaches for isolating multiple types of molecules from a single-cell required for cell-cell communication to distinguish cancer cells from normal cells. Integrating the existing single-cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between- and within-patients responses.
癌是一种复杂的异质性细胞系统，包含上皮癌细胞、基质成纤维细胞和多种免疫细胞类型。这些肿瘤微环境（TME）和细胞之间的细胞间通讯驱动癌症进展，并影响对现有治疗方法的反应。为了为患者提供更好的治疗，我们必须了解各种细胞类型如何在 TME 中协作以推动癌症，并考虑不同癌症类型之间和内部存在的多种信号。为了研究组织如何发挥功能，我们需要一个模型来测量细胞间信号如何传递以及该信息如何在细胞内处理。不同细胞类型之间的协作相互作用需要细胞间通讯。本文旨在综述结直肠癌（CRC）的当前体外和体内单细胞和多细胞培养模型，并探讨它们如何用于单细胞多组学方法，从单个细胞中分离出进行细胞间通讯所需的多种类型的分子，以将癌细胞与正常细胞区分开来。整合现有的单细胞信号测量和模型，并通过了解细胞身份以及不同细胞类型如何进行通讯，将有助于预测肿瘤细胞和患者之间及患者内部的药物敏感性。
